what is a mitigation report in research

• PHS Addendum

This PHS Addendum implements the requirements of certain federal regulations, specifically 42 CFR 50 and 45 CFR 94, and applies to all projects funded, directly or indirectly through a subaward from another organization, by the PHS other than SBIR or STTR awards. This PHS Addendum supplements MIT’s Policy on Conflicts of Interest in Research. PHS regulations differ, in some respects, from MIT’s Policy. It is imperative, therefore, that every MIT Investigator that accepts PHS funding, whether directly or indirectly, becomes familiar with, and abides by, the provisions of this PHS Addendum. 

This policy also applies to projects funded by certain foundations that have elected to apply the PHS standards and requirements relating to financial conflicts of interest. 

• Identifying Investigators

Sponsored Travel

• Reporting to PHS
• Public Accesibility

Subawards Issued BY MIT Under PHS Funded Prime Awards

Subawards issued to mit under funded prime awards, investigator non-compliance - retrospective review.

• Record Retention

IDENTIFYING INVESTIGATORS

Investigator means the individual or individuals who are independently responsible for the design, conduct, or reporting of the research project. This is typically the principal investigator and any co-principal investigator (i.e. the project leadership), though in some cases the principal investigator may determine that others are independently responsible for the project. While a title alone cannot determine who is an Investigator, postdoctoral appointees and graduate students are rarely considered independently responsible for a project. For NIH projects, the individuals identified in the proposal as “key personnel” may be Investigator s.  

A matrix designed to assist Principal Investigators in identifying Investigators can be found here.

MIT must provide training regarding MIT’s Policy and the regulations to Investigator s. PHS Investigators must complete the training prior to MIT charging effort to the PHS award, and at least every four years thereafter. Investigator s must also complete training within a period of time determined by the Institutional Official if (i) this PHS Addendum is substantively amended in a manner that affects the requirements of Investigator s or (ii) MIT determines that the Investigator has not complied with this PHS Addendum or with a management plan related to his or her research.

Training will be provided through the Collaborative Institutional Training Initiative (CITI). More information can be found here.

PHS requires that Sponsored Travel be included in the determination of whether the Aggregate value of an Investigator ’s financial interests rises to the level of a Significant Financial Interest . Sponsored Travel includes (a) travel expenses paid to an Investigator or travel paid on an Investigator ’s behalf, by a single entity in any 12-month period and (b) travel reimbursed to or paid on behalf of an Investigator ’s Family by a single entity in any 12-month period, ONLY if such travel reasonably appears to be related to the Investigator ’s Institutional Responsibilities. 

NIH states that looking back over the previous twelve-month period provides baseline information that allows MIT to take into account whether Investigator s have an ongoing financial relationship with an entity providing a payment or reimbursement or whether the payment or reimbursement was limited in duration.

In order to ensure compliance with PHS regulations, therefore, an Investigator must update his or her master COI disclosure to include Sponsored Travel if the Sponsored Travel equals or exceeds $5,000, alone or in combination with other Remuneration and Equity Interests:

• at the time of submission of a proposal to PHS , looking back over the previous 12 months; 
• thereafter, within 30 days following reimbursement or within 30 days following the completion of a trip, if the PHS Investigator has an active award or pending proposal with a PHS agency. 

An Investigator need not disclose Sponsored Travel paid for or reimbursed by:

• MIT (e.g. paid from MIT funds or from sponsored awards funds managed at MIT)
• U.S. Federal, state or local governmental agencies
• U.S. Institutes of higher education
• U.S. Research institutions affiliated with institutions of higher education 
• U.S. Academic teaching hospitals and medical centers

The disclosure must include at a minimum, the purpose, cost of the trip (estimate if unknown), the identity of the organization or entity funding the travel, the destination, the duration of the trip (usually days), and the relationship between the trip and the PHS Investigator ’s proposals and awards. The Designated Official may request additional information to determine whether the Sponsored Travel is related to the Investigator ’s Institutional Responsibilities in accordance with the Review, Evaluation and Resolution section of this policy.

Reporting To PHS

PHS agency funded Investigator s are required to disclose a Significant Financial Interest within 30 days of identifying the Significant Financial Interest . MIT shall, within 60 days, review the disclosure, determine its relatedness, determine if it is a Financial Conflict of Interest and if so, implement a management plan. Within 60 days of determining whether an Significant Financial Interest is a Financial Conflict of Interest , MIT must report the Financial Conflict of Interest details, including details of the management plan, to the PHS funding agency.

The PHS regulations require MIT to provide the following information regarding Financial Conflicts of Interest t:  

• if the Financial Conflict of Interest existed prior to award, prior to expenditure of funds;
• if the Financial Conflicts of Interest arises during the term of the award, within 60 days of determining whether a Significant Financial Interest is a Financial Conflicts of Interest (see Disclosure Requirements above);
• as part of the annual progress report on the Research;
• as part of any requests for an extension of the award; and 
• following a retrospective review as discussed in more detail under RETROSPECTIVE REVIEW below.

Each report to PHS must include sufficient information to enable PHS to understand the nature and extent of the financial conflict and to assess the appropriateness of the management plan. The required information includes:

• project number;
• Principal Investigator or Contact Principal Investigator if there are multiple Principal Investigator s on the project;
• name of the Investigator with the Financial Conflict of Interest ;
• name of the entity with which the Investigator has a Financial Conflict of Interest ;
• nature of the Significant Financial Interest (e.g., Equity, consulting fees, travel reimbursement, honorarium);
• value of the Significant Financial Interest , which value may be expressed as being within a range ($0– $4,999; $5,000–$9,999; $10,000– $19,999; amounts between $20,000– $100,000 by increments of $20,000; amounts above $100,000 by increments of $50,000) or, if the value of the interest cannot be readily determined through reference to public prices or other reasonable measures of fair market value, a statement confirming that fact;
• a description of the relationship of the Significant Financial Interest to the PHS -funded research and the basis for MIT’s determination that the Significant Financial Interest conflicts with the research; and
• the role and principal duties of the conflicted Investigator in the research;
• the conditions of the management plan;
• how the management plan is designed to safeguard the objectivity of the research;
• confirmation of the Investigator ’s agreement to the management plan;
• how the management plan will be monitored to ensure Investigator compliance; and
• other relevant information.

Public Acccessibility

PHS requires MIT to make information regarding Financial Conflict of Interest reported to PHS , available to the public upon request. The minimum amount of information that must be made available includes the following:

• Investigator ’s name; 
• Investigator ’s title and role with respect to the research; 
• name of the entity in which the Significant Financial Interest is held or from which it is received; 
• nature of the Significant Financial Interest ; and 
• approximate value of the Significant Financial Interest , which value may be expressed as being within a range as described above or if the value of the interest cannot be readily determined through reference to public prices or other reasonable measures of fair market value, a statement confirming that fact.

MIT may also disclose information regarding the management of the Financial Conflict of Interest .

Instructions for requesting information about a reported Financial Conflict of Interest can be found at /contact-us/fcoi-public-information-request-form .

When MIT issues a subaward to another organization to carry out a portion of a PHS funded project, the subawardee must comply with the PHS conflict of interest regulations. MIT, therefore, will only issue subawards under PHS funded awards to institutions that have financial conflict of interest policies that comply with the PHS regulations. 

If a subawardee Investigator has a Financial Conflicts of Interest , MIT is responsible for reporting the Financial Conflict of Interest to the PHS on behalf of the subawardee. As a result, subawardees must report Financial Conflicts of Interest to MIT within 30 days of determining whether there is a Financial Conflict of Interest so that MIT may report it to PHS in a timely manner. In addition, MIT is required by PHS to make information regarding subawardee Financial Conflicts of Interest available to the public. MIT will report subawardee Financial Conflicts of Interest using the same method it uses to disclose its own Financial Conflicts of Interest , and will notify the subawardee of any requests for information. Questions regarding the specifics of subawardee Financial Conflicts of Interest are directed to the subawardee.

When MIT makes a proposal for or receives a subaward from another organization to carry out a portion of a PHS funded project, MIT must comply with the PHS regulations regarding conflicts of interest. MIT’s Policy and this PHS Addendum apply to these proposals and awards rather than the policies of the subawarding organization. MIT provides reports of Financial Conflicts of Interest to the subawarding organization for reporting to PHS as specified in the PHS regulations.

Reports are provided in the same form and format as MIT uses in connection with its direct awards from PHS . The subawarding organization is also responsible for the public accessibility reporting (see above). The subawarding organization may choose to do so either by posting MIT’s report to a publicly available website or responding to written requests within 5 business days.

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In cases where a Financial Conflict of Interest is not identified or managed in a timely manner, including due to

• failure by the Investigator to disclose a Significant Financial Interest that is determined by the Institution to constitute a Financial Conflict of Interest ;
• failure by MIT to review or manage such a Financial Conflict of Interest ; or
• failure by the Investigator to comply with a Financial Conflict of Interest management plan,

MIT must, within 120 days of its determination of noncompliance, complete a retrospective review of the Investigator ’s activities and the PHS -funded research to determine whether the design, conduct, or reporting of the PHS -funded research, or any portion thereof, conducted during the period of noncompliance, was biased. Retrospective reviews will be conducted by the Office of the General Counsel or other MIT personnel, as determined by the Conflict of Interest Committee .

MIT is required to document the retrospective review and report detailed findings to PHS , including at least the following key elements:

• project title;
• Principal Investigator or contact Principal Investigator if there are multiple Principal Investigator s on the project;
• name of the Entity with which the Investigator has a Financial Conflict of Interest ;
• reason(s) for the retrospective review;
• detailed methodology used for the retrospective review (e.g., methodology of the review process, composition of the review panel, documents reviewed);
• findings of the review; and
• conclusions of the review.

Based on the results of the retrospective review, MIT will update the previously submitted Financial Conflict of Interest report, if appropriate, specifying the actions that will be taken to manage the Financial Conflict of Interest . If bias is found, MIT must notify PHS promptly and submit a mitigation report. The mitigation report must include, at a minimum:

• the elements documented in the retrospective review above;
• a description of the impact of the bias on the research; and
• MIT’s plan of action or the actions taken to eliminate or mitigate the effect of the bias (e.g., extent of harm done, including any qualitative and quantitative data to support any actual or future harm; analysis of whether the research is salvageable).

Thereafter, MIT will submit Financial Conflict of Interest reports annually, as specified under the PHS regulations. Depending on the nature of the Financial Conflict of Interest , MIT may determine that additional interim measures are necessary with regard to the Investigator ’s participation in the PHS - funded research between the date that the Financial Conflict of Interest or the Investigator ’s noncompliance is determined and the completion of MIT’s retrospective review.

Record Retention

The COI Officer will retain all disclosures, conflict management plans, and related documents for a period of at least three years following submission of the final expenditure report for the applicable project to the PHS or the prime PHS awardee, unless any litigation, claim or negotiation, audit, or other action involving the records is commenced before expiration of the three-year period, in which case, records will be retained until completion of the action and resolution of all issues.

• Policy Statement
• Definitions
• Guiding Principles
• Application of Guiding Principles
• Disclosure Requirements
• Review, Evaluation and Resolution
• Disclosure to Third Parties
• Disciplinary Action
• Summary of Updates to the MIT Policies and Procedures on Conflicts of Interest in Research
• Community COI Portal
• Who is an Investigator
• Change in Status or Absence of PI or Key Personnel
• NIH FAQs about Senior/Key Personnel
• National Science Foundation (NSF)
• Helpful Hints About SBIR/STTR Phase 1 Awards
• Training Requirements
• What do I need to know before starting my COI Disclosure?
• COI vs. OPA: What You Need to Know
• Screening Result
• Create an SFI Entity
• Entity Definition Section
• Maintaining the Relationship Details Grid
• Overview of Relationships Screen
• Relating Projects to SFIs
• Why Can’t I Save & Continue a Project Relationship Page?
• What Happens If I Skip A Project?
• Step 4: Certify
• Revise or Update an Initial Disclosure in Progress
• Revise or Update a Revision in Progress
• View SFI Entity (make Inactive)
• Create Travel Disclosure
• Revise Travel Disclosure(s) in Progress
• View Travel Disclosure(s)
• Prepare Your Proposal Disclosure
• Questionnaire Screening Result – No Conflicts
• Questionnaire Screening Result – Potential Conflict
• Step 1: Proposal Certification Questionnaire
• Step 2: Significant Financial Interest
• Step 3: Relationships
• Step 1: Screening Questions
• Modifying Your Proposal Certification Questionnaire Answers
• Step 2: Significant Financial Interests
• Integration with Proposal Certification
• View and Print Your Master Disclosure
• Why can’t I edit my Disclosure?
• FCOI Public Information Request Form
• COI Training Requirement
• Investigator Self Certification
• Key Persons
• NIH Individual Fellowships
• NIH Travel Disclosures
• Outside Professional Activities
• Significant Financial Interest

Research Policy Handbook

PHS and NSF Requirements Regarding Financial Disclosures and Agency Notifications

Policy authority.

VPDoR (Office of the Vice Provost and Dean of Research)

Policy Contact

Now in Policy Details

Establishes policy for implementation of agency requirements related to financial disclosures by faculty members and other Investigators involved with submitting proposals and notifications to agencies in the event a financial conflict of interest (FCOI) is identified.  This policy will be modified as necessary to maintain compliance with the requirements of external agency.

1. Introduction

Stanford's Faculty Policy on Conflict of Commitment and Interest (RPH 4.1) establishes requirements for faculty disclosures (on both an annual and an ad hoc basis) of financial interests and professional relationships in outside entities that would reasonably appear to be related to institutional responsibilities, and for annual certifications of policy compliance. In addition, Stanford's policy requires that faculty members seeking funding from an external sponsor comply with any financial disclosure or notification requirements of that sponsor.

Certain federal agencies have specific requirements for disclosure and management of personal financial interests related to their sponsored research projects.  The focus of these requirements is to ensure responsible stewardship of federal funds and to promote research free from bias resulting from Investigator financial conflicts of interest.  Agencies with such requirements include the Public Health Service (PHS) and related components such as the National Institutes of Health (NIH) and the Centers for Disease Control and Prevention (CDC), the Food and Drug Administration (FDA)as well as the National Science Foundation (NSF). This policy provides specific guidance related to the requirements of PHS and NSF.

2. PHS Requirements

A. definitions.

• Designated Official means the individual(s) designated by each Stanford School Dean to review disclosures of significant financial interests and determine whether there is a financial conflict of interest. For School Deans, the Vice Provost and Dean of Research, or their designee may review disclosures and determine whether there is a financial conflict of interest.
• Financial conflict of interest (FCOI) means a significant financial interest (SFI) that could directly and significantly affect the design, conduct, or reporting of PHS-funded research.
• Financial interest means anything of monetary value, whether or not the value is readily ascertainable. 
• Institutional Responsibilities means an Investigator’s professional responsibilities on behalf of Stanford, including research and other scholarly activities; clinical care activities; teaching or educational activities; and administrative activities.
• Investigator means the project director (PD) or principal investigator (PI) any Stanford faculty contributing effort to a PHS funded project and any other person, regardless of title or position, who is responsible for the design, conduct, or reporting of research funded by the PHS, or proposed for such funding, designated by the PI/PD or Stanford Faculty.  These individuals may include, for example, academic or teaching staff. 
• Manage means taking action to address a financial conflict of interest, which can include reducing or eliminating the financial conflict of interest, to ensure, to the extent possible, that the design, conduct, and reporting of research will be free from bias.
• PD/PI   means a project director or principal investigator of a PHS-funded research project; the PD/PI is included in the definitions of senior/key personnel and Investigator.
• Senior/key personnel means the PD/PI and any other person identified as senior/key personnel by Stanford in the grant application, progress report, or any other report submitted to the PHS by Stanford under this policy.
• With regard to any publicly traded entity, an SFI exists if the value of any remuneration received from the entity in the twelve months preceding the disclosure and the value of any equity interest in the entity as of the date of disclosure, when aggregated, exceeds $5,000. For purposes of this definition, remuneration includes salary and any payment for services not otherwise identified as salary (e.g., consulting fees, honoraria, paid authorship); equity interest includes any stock, stock option, or other ownership interest, as determined through reference to public prices or other reasonable measures of fair market value; 
• With regard to any non-publicly traded entity, an SFI exists if the value of any remuneration received from the entity in the twelve months preceding the disclosure, when aggregated, exceeds $5,000, or when the Investigator (or the Investigator’s spouse or dependent children) holds any equity interest (e.g., stock, stock option, or other ownership interest); or
• Intellectual property rights and interests (e.g., patents, copyrights), upon receipt of income related to such rights and interests.
• Reimbursed or sponsored travel that reasonably appears related to the Investigator’s Institutional Responsibilities may be an SFI.  Investigators must disclose the occurrence of any reimbursed or sponsored travel, $5,000 or more (i.e., that which is paid on behalf of the Investigator and not reimbursed to the Investigator so that the exact monetary value may not be readily available), related to their institutional responsibilities; provided, however, that this disclosure requirement does not apply to travel that is reimbursed or sponsored by a Federal, state, or local government agency in the United States, or a United States public or non-profit institution of higher education (as defined at 20 U.S.C. 1001(a)) or its affiliated hospital, medical center or research institute.  The Investigator’s disclosure must include the purpose of the trip, the identity of the sponsor/organizer, the destination, and the duration.
•  The term significant financial interest does not include the following types of financial interests: salary, royalties, or other remuneration paid by Stanford to the Investigator if the Investigator is currently employed or otherwise appointed by Stanford, including intellectual property rights assigned to Stanford and agreements to share in royalties related to such rights.
•  SFI also does not include income from investment vehicles, such as mutual funds and retirement accounts, as long as the Investigator does not directly control the investment decisions made in these vehicles; and
• SFI also does not include income from seminars, lectures, or teaching engagements sponsored by a Federal, state, or local government agency in the United States, a United States public or non-profit institution of higher education (as defined at 20 U.S.C. 1001(a)) or its affiliated hospital, medical center or research institute; or income from service on advisory committees or review panels for a Federal, state, or local government agency in the United States, or  a United States institution of higher education.

1. Disclosure

Regular disclosure requirements.

All Stanford faculty who are planning to participate or who are participating in PHS-funded research at Stanford must disclose all financial interests, including those of the their spouse and dependent children, that could reasonably be related to the Investigator’s Institutional Responsibilities.  As described above, Institutional Responsibilities include research and other scholarly activities; clinical care activities; teaching or educational activities; and administrative activities.  Such disclosures must be made in the Outside Professional Activities Certification System (OPACS) on an annual basis or within thirty days of discovering or acquiring (e.g. through purchase, marriage, or inheritance) a new SFI. SFIs disclosed will be identified and reviewed in accordance with this policy.  

PHS-Funded Research Disclosure Requirements

For each project proposed to or funding by PHS, the following people are considered Investigators for purposes of this policy:

• the Principal Investigator (PI), and
• all Stanford faculty contributing effort to a PHS sponsored project, and 
• any other person that the PI or a contributing faculty member designates as responsible for the design, conduct, or reporting of research.

The OPACS system will prompt all these Investigators (faculty and non-faculty alike) to complete a disclosure in OPACS for the proposal. All disclosed financial interests of the Investigators, including those of their spouses or dependent children, are reviewed to identify SFIs that may reasonably appear to be related to the proposed research project, and a determination is made whether there is an FCOI.  All FCOI  are eliminated or managed, in accordance with this policy, to ensure compliance with PHS requirements prior to expenditure of PHS funds. In addition to fulfilling disclosure requirements, all Investigators complete training, as described below, before expenditure of PHS funds.

2. Review of Disclosures by the Designated Official

Each School Dean will identify and appoint a Designated Official (usually a faculty senior associate dean and/or COI program administrator) to assume the review responsibility for its own Investigators.  Designated Officials will review annual disclosures in OPACS and transactional/ad hoc disclosures submitted by faculty as required byStanford's Faculty Policy on Conflict of Commitment and Interest in RPH 4.1, and for academic and teaching staff as required by RPH 4.4 Conflict of Commitment and Interest for Academic Staff and Other Teaching Staff.  The Vice Provost and Dean of Research, or their designee, will review disclosures and act as the Designated Official, with regard to disclosures made by the School Deans.

All financial interests of the Investigator are reviewed by the Designated Official.  Any financial interest that qualifies as an SFI and that may reasonably appear to be related to the proposed research project is further reviewed by the Designated Official to determine whether there is an FCOI and, if so, the FCOI is eliminated or managed and reported to PHS, as applicable, in accordance with this policy and in compliance with PHS requirements regarding conflict of interest. All FCOI identified that are specifically related to PHS-funded research are eliminated or managed prior to expenditure of PHS funds. 

3. Determining if an SFI is Related to PHS-funded Research

An SFI is related to the PHS-funded research when the Designated Official reasonably determines that the SFI could affect PHS-funded research. Stanford may involve the Investigator in the Designated Official’s determination of whether an SFI is related to the PHS-funded research. An SFI with an Entity would be reasonably considered related to an Investigator's research study in circumstances such as the following:

• Entity is a collaborator on or provider of materials, products, data or trainee support for the PHS-funded research or is a licensee with improvement rights to technology likely to arise out of the PHS-funded research. 
• Investigator or Entity has financial interests that could reasonably be considered to have a potential influence on the design, conduct or reporting of the PHS funded research
• Entity has a reasonable possibility of being financially affected by the PHS funded research
• Entity sponsors research at Stanford in which the Investigator is directly involved
• Entity makes gifts to Stanford that benefit Investigator's research/scholarship (including equipment gifts or loans)
• Entity sponsors or makes a product that is under study in research in which Investigator is involved
• Entity sponsors or makes a product that is under study in human subjects in which Investigator is directly or indirectly involved 
• Entity licenses Stanford intellectual property in which Investigator has a financial interest
• Entity owns intellectual property, materials, or data that may be used in research at Stanford
• Entity has a Materials Transfer Agreement, Human Tissue Agreement (MTA/HTA), or Data Transfer and Use Agreement (DTUA) to provide materials or data used in Investigator's research or for materials provided by Investigator to the company/organization
• Entity is the sole-source provider of materials or services or of procurements required for the Investigator to carry out research 
• Entity provides financial support for the faculty member's trainees (including graduate students and postdoctoral fellows)

4. FCOI Determination

A financial conflict of interest (FCOI) exists when the Designated Official reasonably determines that the SFI could directly and significantly affect the design, conduct, or reporting of the PHS-funded research.

Timing of Review and Requirements

• Newly Funded Project

Prior to Stanford’s expenditure of any funds under a PHS- funded research project, the Designated Official(s) shall review all Investigator SFI disclosures and:

• determine whether the SFI relates to PHS-funded research; 
• determine whether a financial conflict of interest (FCOI) exists; 
• if there is an FCOI, either take steps to eliminate the conflict or develop and implement a management plan that shall specify the actions that have been, and shall be, taken to manage such FCOI; and 
• If an FCOI is not eliminated and a management plan is implemented, Stanford must file an FCOI report with the appropriate PHS awarding component.
• Ongoing Project (Timely Disclosure)

In the course of an ongoing PHS-funded research project (timely disclosure), should an Investigator who is new to participating in the research project disclose a SFI or should an existing Investigator disclose a new SFI to Stanford, the Designated Official shall, within sixty days, review the disclosure of the SFI and:

• if there is an FCOI, either take steps to eliminate the conflict or develop and implement, on at least an interim basis, a management plan that shall specify the actions that have been, and shall be, taken to manage such FCOI. Depending on the nature of the SFI, Stanford may determine that additional interim measures are necessary with regard to the Investigator’s participation in the PHS- funded research project between the date of disclosure and the completion of Stanford’s review; and
• if an FCOI is not eliminated and a management plan is implemented, Stanford must file an FCOI report (or update an existing one) with the appropriate PHS awarding component within 60 days.
• Ongoing Project (Failure to Timely Disclose or Review)

In the course of an ongoing PHS-funded research project, should Stanford identify an SFI that was not disclosed timely by an Investigator or, for whatever reason, was not previously reviewed by Stanford during an ongoing PHS-funded research project, the Designated Official shall, within sixty days, review the SFI and: 

• if there is an FCOI, either take steps to eliminate it or develop and implement, on at least an interim basis, a management plan that shall specify the actions that have been, and will be, taken to manage such financial conflict of interest going forward;
• if there is an FCOI, complete a retrospective review, within 120 days. Depending on the nature of the FCOI, Stanford may determine that additional interim measures are necessary with regard to the Investigator’s participation in the PHS-funded research project between the date that the financial conflict of interest or the Investigator’s noncompliance is determined and the completion of Stanford’s retrospective review; and
• If an FCOI is not eliminated and a management plan is implemented, Stanford must file an FCOI report (or update an existing one) with the appropriate PHS awarding component within 60 days.

5. FCOI Management and Monitoring

Management of an identified FCOI requires development and implementation of a management plan and, if necessary, a retrospective review and a mitigation report (described below).  Examples of conditions or restrictions that Stanford may impose to manage a FCOI include, but are not limited to: (i) Public disclosure of FCOI (e.g., when presenting or publishing the research); (ii) For research projects involving human subjects research, disclosure of FCOI directly to participants; (iii) Appointment of an independent monitor capable of taking measures to protect the design, conduct, and reporting of the research against bias resulting from the FCOI; (iv) Modification of the research plan; (v) Change of personnel or personnel responsibilities, or disqualification of personnel from participation in all or a portion of the research; (vi) Reduction or elimination of the financial interest (e.g., sale of an equity interest); or (vii) Severance of relationships that create financial conflicts. 

The management plan should include: (A) A description of the SFI and the FCOI (B) Role and principal duties of the conflicted Investigator in the research project; (C) Specific conditions of the management plan; (D) A description of how the management plan is designed to safeguard objectivity in the research project; (D) Confirmation of the Investigator’s agreement to the management plan; (F) How the management plan will be monitored to ensure Investigator compliance.  The appropriate Investigator shall sign and certify each manage plan, along with the cognizant (department or center head, or both), and the Designated Official.  

The Investigator will provide an update to the details of the management plan at least annually, and more often if circumstances related to the SFI change.  Such plans shall remain in effect until the completion of the PHS-funded research project, or until the FCOI is eliminated, whichever comes first. 

6. FCOI Reports to PHS

Prior to Stanford’s expenditure of any funds under a PHS-funded research project, Stanford shall provide to the PHS awarding component, through the NIH eRA Commons, an FCOI report regarding any Investigator’s SFI found by Stanford to be conflicting and ensure that Stanford has implemented management plan in accordance with the PHS regulations. In cases in which Stanford identifies an FCOI and eliminates the conflict prior to the expenditure of PHS-awarded funds, Stanford will not submit an FCOI report.

For any SFI that Stanford identifies as conflicting subsequent to Stanford’s initial FCOI report and during an ongoing PHS-funded research project ( e.g. , upon the participation of an Investigator who is new to the research project), Stanford shall provide an FCOI report to the PHS Awarding Component, within sixty days,. 

Where an FCOI report involves a SFI that was not disclosed timely by an Investigator or, for whatever reason, was not previously reviewed or managed by Stanford (e.g.,   was not timely reviewed or reported by a subrecipient), in addition to providing an FCOI report, Stanford also is required to complete a retrospective review (see below) to determine whether any PHS-funded research, or portion thereof, conducted prior to the identification and management of the financial conflict of interest was biased in the design, conduct, or reporting of such research. If bias is found, Stanford is required to notify and promptly and submit a mitigation report to the PHS Awarding Component.

After initial submission of an FCOI report, Stanford shall provide the PHS Awarding Component an annual FCOI report that addresses the status of the FCOI and any changes to the management plan for the duration of the PHS-funded research project. The annual FCOI report shall specify whether the financial conflict is still being managed or explain why the financial conflict of interest no longer exists. Stanford shall provide annual FCOI reports to the PHS Awarding Component for the duration of the project period (including extensions with or without funds) in the time and manner specified by the PHS Awarding Component.

The FCOI report shall include sufficient information to enable the PHS Awarding Component to understand the nature and extent of the financial conflict and to assess the appropriateness of Stanford’s management plan. Elements of the FCOI report shall include, but are not necessarily limited to, the following: (i) Project number; (ii) PD/PI or Contact PD/PI if a multiple PD/PI model is used; (iii) Name of the Investigator with the financial conflict of interest; (iv) Name of the entity with which the Investigator has a financial conflict of interest; (v) Nature of the financial interest (e.g., equity, consulting fee, travel reimbursement, honorarium); (vi) Value of the financial interest (dollar ranges are permissible: $0–$4,999; $5,000–$9,999; $10,000–$19,999; amounts between $20,000– $100,000 by increments of $20,000; amounts above $100,000 by increments of $50,000), or a statement that the interest is one whose value cannot be readily determined through reference to public prices or other reasonable measures of fair market value; (vii) A description of how the financial interest relates to the PHS-funded research and the basis for Stanford’s determination that the financial interest conflicts with such research; and (viii) A description of the key elements of Stanford’s management plan, including: (A) Role and principal duties of the conflicted Investigator in the research project; (B) Conditions of the management plan; (C) How the management plan is designed to safeguard objectivity in the research project; (D) Confirmation of the Investigator’s agreement to the management plan; (E) How the management plan will be monitored to ensure Investigator compliance; and (F) Other information as needed.

7. Retrospective Review

Whenever an FCOI is not identified or managed in a timely manner, including failure by the Investigator to timely disclose a SFI that is later determined by Stanford to constitute a FCOI; failure by Stanford to timely review or manage such an FCOI; or failure by the Investigator to comply with a FCOI management plan, Stanford shall, within 120 days of Stanford’s determination of noncompliance, complete a retrospective review of the Investigator’s activities and the PHS-funded research project to determine whether any PHS-funded research, or portion thereof, conducted during the time period of the noncompliance, was biased in the design, conduct, or reporting of such research. 

Under PHS policy, Stanford is required to document the retrospective review; such documentation shall include, but not necessarily be limited to, all of the following key elements: (1) Project number; (2) Project title; (3) PD/PI or contact PD/PI if a multiple PD/PI model is used; (4) Name of the Investigator with the FCOI; (5) Name of the entity with which the Investigator has a financial conflict of interest; (6) Reason(s) for the retrospective review; (7) Detailed methodology used for the retrospective review (e.g., methodology of the review process, composition of the review panel, documents reviewed); (8) Findings of the review; and (9) Conclusions of the review. 

Based on the results of the retrospective review, if appropriate, Stanford shall update the previously submitted FCOI report, specifying the actions that will be taken to manage the FCOI going forward. 

If bias is found, Stanford is required to notify the PHS Awarding Component promptly and submit a mitigation report to the PHS Awarding Component. The mitigation report must include, at a minimum, the key elements documented in the retrospective review, above, and a description of the impact of the bias on the research project and Stanford’s plan of action or actions taken to eliminate or mitigate the effect of the bias (e.g., impact on the research project; extent of harm done, including any qualitative and quantitative data to support any actual or future harm; analysis of whether the research project is salvageable). 

Thereafter, Stanford will submit FCOI reports annually, as specified elsewhere in this policy. 

8. Remedies for Non-Compliance

The Vice Provost and Dean of Research is responsible for interpretation and overall coordination of the policy. Violation of any part of this policy may cause a faculty member to be subject to sanctions, including those described in the Statement on Faculty Discipline. Violation by academic or teaching staff may result in disciplinary action.  

Whenever an FCOI is not identified or managed in a timely manner, including failure by the Investigator to disclose a SFI that is determined by Stanford to constitute a FCOI; failure by Stanford to review or manage such a FCOI; or failure by the Investigator to comply with a FCOI management plan, Stanford shall, within 120 days of Stanford’s determination of noncompliance, complete a retrospective review of the Investigator’s activities and the PHS-funded research project to determine whether any PHS-funded research, or portion thereof, conducted during the time period of the noncompliance, was biased in the design, conduct, or reporting of such research.

If the failure of an Investigator to comply with Stanford’s financial conflicts of interest policy or a FCOI management plan appears to have biased the design, conduct, or reporting of the PHS-funded research, Stanford shall promptly notify the PHS Awarding Component of the corrective action taken or to be taken. 

The PHS Awarding Component will consider the situation and, as necessary, take appropriate action, which may include directing Stanford on how to maintain appropriate objectivity in the PHS-funded research project, requiring Stanford to submit records, submit to on site review, accept special award conditions, suspension of funding, or other enforcement actions until the matter is resolved.

Should HHS determine that a PHS-funded project of clinical research whose purpose is to evaluate the safety or effectiveness of a drug, medical device, or treatment has been designed, conducted, or reported by an Investigator with a financial conflict of interest that was not managed or reported by Stanford as required by this policy, Stanford shall require the Investigator involved to disclose the financial conflict of interest in each public presentation of the results of the research and to request an addendum to previously published presentations.

C. Additional PHS Requirements

1. public accessibility.

This PHS Policy is available on a publicly accessible website and has been made available to PHS via its NIH eRA Commons.

Information concerning FCOIs held by senior/key personnel is made publicly accessible by a written response to anyrequester within five business days of a request or as required by law.  Requests can be made using the form found here . This information provided will include: the Investigator’s name; the Investigator’s title and role with respect to the research project; the name of the entity in which the significant financial interest is held; the nature of the significant financial interest; and the approximate dollar value of the significant financial interest (in pre-specified dollar ranges), or a statement that a value cannot be readily determined. This information will remain publiclyaccessible for at least three years from the date that it was most recently updated.

2. Investigator Training

Each Investigator must complete training regarding Stanford’s policy on financial conflicts of interest, the Investigator’s responsibilities regarding disclosure of significant financial interests, and of these specific PHS requirements.  Training must be completed prior to engaging in research related to any PHS-funded grant and refreshed at least every four years.  The Stanford OPACS system has been designed to be a training tool as well as a disclosure tool, so all Investigators receive annual training through the disclosure process.

Additional training must be completed when (1) Financial conflict of interest policies are revised in a manner that changes researcher requirements; (2) A researcher is new to the organization; and (3) A researcher is non-compliant with financial conflict of interest policies and procedures.

3. Subawards

When Stanford carries out PHS-funded research through a subrecipient (e.g., subcontractors or consortium members), Stanford, as the awardee Institution, will take reasonable steps to ensure that all subrecipient Investigators comply with PHS FCOI policy.  Stanford will incorporate, as part of a written agreement with the subrecipient, terms that establish that (1) the subrecipient’s financial conflicts of interest policy is compliant with PHS FCOI policy, (2) all subrecipient’s Investigators must comply with the subrecipient’s financial conflicts of interest policy, and (3) there is a specified time period for the subrecipient to report all identified conflicts of interest to Stanford, where this time period is sufficient to enable Stanford to provide timely FCOI reports to the PHS as required.  The subrecipient shall certify that its policy complies with PHS FCOI policy. 

Stanford will maintain records relating to all Investigator disclosures of financial interests and Stanford’s review of and response to such disclosures (whether or not a disclosure resulted in Stanford’s determination of a financial conflict of interest) and all actions under Stanford’s policy for PHS COI review or retrospective review, as applicable, for at least three years from the date the final expenditures report is submitted to the PHS or, where applicable, from other dates specified in PHS regulations.

3. NSF Requirements

The National Science Foundation (NSF) requires Stanford to maintain an appropriate written and enforced policy on conflict of interest and that all conflicts of interest for each award be managed, reduced or eliminated prior to the expenditure of the award funds.

• Investigator means the principal investigator (PI), project director (PD), a co-PI or co-PD, any Stanford faculty contributing effort to an NSF funded project and any other person designated by the PI/PD or other Stanford faculty, who is responsible for the design, conduct, or reporting of research or educational activities funded by, or proposed for funding by NSF.
• Significant Financial Interest (SFI) means anything of monetary value, including, but not limited to, salary or other payments for services (e.g., consulting fees or honoraria); equity interest (e.g., stocks, stock options, or other ownership interests); and intellectual property rights (e.g., patents, copyrights, and royalties from such rights).

SFI does NOT include:

• salary, royalties, or other remuneration from Stanford
• income from seminars, lectures, or teaching engagements sponsored by public or non-profit entities
• income from service on advisory committees or review panels for public or nonprofit entities
• an equity interest that, when aggregated for the Investigator and the Investigator’s spouse and dependent children, meets both of the following tests: does not exceed $5,000* in value as determined through reference to public prices or other reasonable measures of fair market value, and does not represent more than a 5% ownership interest in any single entity
• salary, royalties or other payments that, when aggregated for the Investigator and the Investigator’s spouse and dependent children, are not expected to exceed $5,000 during the twelve-month period

*NOTE: Although current NSF regulations specify a higher threshold for SFI than PHS (NIH), Stanford policy identifies $5,000 as the monetary threshold. Similarly, in non-publicly traded companies, PHS and Stanford policy identify any equity amount as the threshold.

3. Responsible Representative means the individual identified and appointed by the School Dean  (usually a faculty senior associate dean and/or COI program administrator) to assume the  review responsibility for its own Investigators, relying on the annual OPACS and transactional/ad hoc disclosures submitted by faculty as required by Stanford's Faculty Policy on Conflict of Commitment and Interest in RPH 4.1 and for academic and teaching staff as required by RPH 4.4 Conflict of Commitment and Interest for Academic Staff and Other Teaching Staff.  For School Deans, the Vice Provost and Dean of Research, or their designee will review disclosures and act as the Responsible Representative.

As required by NSF, and in accordance with Stanford’s Faculty Policy on Conflict of Commitment and Interest, RPH 4.1, and Stanford’s Policy on Conflict of Interest and Commitment for Academic and Teaching Staff,  RPH 4.4, Stanford requires each Investigator to disclose all SFIs of the Investigator (including those of the Investigator’s spouse and dependent children) that would reasonably appear to be affected by the research or educational activities funded or proposed for funding by NSF or in entities whose financial interests would reasonably appear to be affected by such activities. 

Investigators must provide all required financial disclosures to Stanford’s responsible representative through OPACS at the time the proposal is submitted to NSF. Investigators must ensure their disclosures are updated during the period of the award, either on an annual basis, or as new reportable SFI are obtained.

2. Overview of Review, Management, Reporting and Remedies for Non-Compliance

Stanford designates a responsible representative to review financial disclosures, determine whether a conflict of interest exists, and determine what conditions or restrictions, if any, should be imposed by the Stanford to manage, reduce or eliminate such conflict of interest. 

A conflict of interest exists when the responsible representative(s) reasonably determines that a significant financial interest could directly and significantly affect the design, conduct, or reporting of NSF-funded research or educational activities.

When a conflict of interest is identified, efforts must be made to manage, reduce or eliminate the conflict.  Examples of conditions or restrictions that might be imposed to manage, reduce or eliminate conflicts of interest include, but are not limited to:

• public disclosure of significant financial interests
• monitoring of research by independent reviewers
• modification of the research plan
• disqualification from participation in the portion of the NSF-funded research that would be affected by significant financial interests
• divestiture of significant financial interests
• severance of relationships that create conflicts

If the responsible representative, in consultation with the Dean and the Dean of Research, determines that imposing conditions or restrictions would be either ineffective or inequitable, and that the potential negative impacts that may arise from a significant financial interest are outweighed by interests of scientific progress, technology transfer, or the public health and welfare, then the reviewer(s) may allow the research to go forward without imposing such conditions or restrictions.

If it is decided that there is no way to satisfactorily manage a conflict of interest and if Stanford finds that research will proceed without the imposition of conditions or restrictions when a conflict of interest exists, Stanford must notify NSF through Stanford’s AOR representative using NSF’s electronic systems. The responsible representative should also coordinate with Stanford’s Office of General Counsel to keep NSF’s Office of the General Counsel appropriately informed.

Remedies for Non-Compliance

The Vice Provost and Dean of Research is responsible for interpretation and overall coordination of the policy. Violation of any part of this policy, including failure to appropriately manage a conflict of interest, may result in sanctions or disciplinary action against a faculty or academic or teaching staff member. In such cases, the responsible representative should also coordinate with Stanford’s Office of General Counsel to keep NSF’s Office of the General Counsel appropriately informed.

C. Additional NSF Requirements

1. subawards.

When Stanford carries out NSF-funded research through subawardees, contractors or collaborators, Stanford, as the awardee Institution, will take reasonable steps to ensure that all subawardee, contractor or collaborator Investigators comply with NSF COI requirements.  Stanford will incorporate, as part of a written agreement with the subawardees, contractors, or collaborators, terms that establish that (1) their conflicts of interest policy is compliant with NSF COI requirements, (2) all their Investigators must comply with the their conflicts of interest policy.

Stanford will maintain records of all financial disclosures and of all actions taken to resolve conflicts of interest for at least three years beyond the termination or completion of the grant to which they relate, or until the resolution of any NSF action involving those records, whichever is longer.

4. References

NSF PAPPG 2020  (This should be reviewed on an annual basis to ensure continued compliance)

42 CFR Part 50 Subpart F  

PHS Checklist

Current Version: 05.17.13

Original Version: 08.04.95

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• Title 42 —Public Health
• Chapter I —Public Health Service, Department of Health and Human Services
• Subchapter D —Grants
• Part 50 —Policies of General Applicability
• Subpart F —Promoting Objectivity in Research

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Sec. 215, Public Health Service Act, 58 Stat. 690 ( 42 U.S.C. 216 ); Sec. 1006, Public Health Service Act, 84 Stat. 1507 ( 42 U.S.C. 300a-4 ), unless otherwise noted.

43 FR 52165 , Nov. 8, 1978, unless otherwise noted.

42 U.S.C. 216 , 289b-1 , 299c-4 ; Sec. 219, Tit. II, Div. D, Pub. L. 111-117 , 123 Stat. 3034.

76 FR 53283 , August 25, 2011, unless otherwise noted.

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§ 50.605 Management and reporting of financial conflicts of interest.

( a ) Management of financial conflicts of interest.

( 1 ) Prior to the Institution's expenditure of any funds under a PHS-funded research project, the designated official(s) of an Institution shall, consistent with § 50.604(f) : review all Investigator disclosures of significant financial interests; determine whether any significant financial interests relate to PHS-funded research; determine whether a financial conflict of interest exists; and, if so, develop and implement a management plan that shall specify the actions that have been, and shall be, taken to manage such financial conflict of interest. Examples of conditions or restrictions that might be imposed to manage a financial conflict of interest include, but are not limited to:

( i ) Public disclosure of financial conflicts of interest (e.g., when presenting or publishing the research);

( ii ) For research projects involving human subjects research, disclosure of financial conflicts of interest directly to participants;

( iii ) Appointment of an independent monitor capable of taking measures to protect the design, conduct, and reporting of the research against bias resulting from the financial conflict of interest;

( iv ) Modification of the research plan;

( v ) Change of personnel or personnel responsibilities, or disqualification of personnel from participation in all or a portion of the research;

( vi ) Reduction or elimination of the financial interest (e.g., sale of an equity interest); or

( vii ) Severance of relationships that create financial conflicts.

( 2 ) Whenever, in the course of an ongoing PHS-funded research project, an Investigator who is new to participating in the research project discloses a significant financial interest or an existing Investigator discloses a new significant financial interest to the Institution, the designated official(s) of the Institution shall, within sixty days: review the disclosure of the significant financial interest; determine whether it is related to PHS-funded research; determine whether a financial conflict of interest exists; and, if so, implement, on at least an interim basis, a management plan that shall specify the actions that have been, and will be, taken to manage such financial conflict of interest. Depending on the nature of the significant financial interest, an Institution may determine that additional interim measures are necessary with regard to the Investigator's participation in the PHS-funded research project between the date of disclosure and the completion of the Institution's review.

( 3 ) Whenever an Institution identifies a significant financial interest that was not disclosed timely by an Investigator or, for whatever reason, was not previously reviewed by the Institution during an ongoing PHS-funded research project (e.g., was not timely reviewed or reported by a subrecipient), the designated official(s) shall, within sixty days: review the significant financial interest; determine whether it is related to PHS-funded research; determine whether a financial conflict of interest exists; and, if so:

( i ) Implement, on at least an interim basis, a management plan that shall specify the actions that have been, and will be, taken to manage such financial conflict of interest going forward;

( A ) In addition, whenever a financial conflict of interest is not identified or managed in a timely manner including failure by the Investigator to disclose a significant financial interest that is determined by the Institution to constitute a financial conflict of interest; failure by the Institution to review or manage such a financial conflict of interest; or failure by the Investigator to comply with a financial conflict of interest management plan, the Institution shall, within 120 days of the Institution's determination of noncompliance, complete a retrospective review of the Investigator's activities and the PHS-funded research project to determine whether any PHS-funded research, or portion thereof, conducted during the time period of the noncompliance, was biased in the design, conduct, or reporting of such research.

( B ) The Institution is required to document the retrospective review; such documentation shall include, but not necessarily be limited to, all of the following key elements:

( 1 ) Project number;

( 2 ) Project title;

( 3 ) PD/PI or contact PD/PI if a multiple PD/PI model is used;

( 4 ) Name of the Investigator with the FCOI;

( 5 ) Name of the entity with which the Investigator has a financial conflict of interest;

( 6 ) Reason(s) for the retrospective review;

( 7 ) Detailed methodology used for the retrospective review (e.g., methodology of the review process, composition of the review panel, documents reviewed);

( 8 ) Findings of the review; and

( 9 ) Conclusions of the review.

( iii ) Based on the results of the retrospective review, if appropriate, the Institution shall update the previously submitted FCOI report, specifying the actions that will be taken to manage the financial conflict of interest going forward. If bias is found, the Institution is required to notify the PHS Awarding Component promptly and submit a mitigation report to the PHS Awarding Component. The mitigation report must include, at a minimum, the key elements documented in the retrospective review above and a description of the impact of the bias on the research project and the Institution's plan of action or actions taken to eliminate or mitigate the effect of the bias (e.g., impact on the research project; extent of harm done, including any qualitative and quantitative data to support any actual or future harm; analysis of whether the research project is salvageable). Thereafter, the Institution will submit FCOI reports annually, as specified elsewhere in this subpart. Depending on the nature of the financial conflict of interest, an Institution may determine that additional interim measures are necessary with regard to the Investigator's participation in the PHS-funded research project between the date that the financial conflict of interest or the Investigator's noncompliance is determined and the completion of the Institution's retrospective review.

( 4 ) Whenever an Institution implements a management plan pursuant to this subpart, the Institution shall monitor Investigator compliance with the management plan on an ongoing basis until the completion of the PHS-funded research project.

( i ) Prior to the Institution's expenditure of any funds under a PHS-funded research project, the Institution shall ensure public accessibility, via a publicly accessible Web site or written response to any requestor within five business days of a request, of information concerning any significant financial interest disclosed to the Institution that meets the following three criteria:

( A ) The significant financial interest was disclosed and is still held by the senior/key personnel as defined by this subpart;

( B ) The Institution determines that the significant financial interest is related to the PHS-funded research; and

( C ) The Institution determines that the significant financial interest is a financial conflict of interest.

( ii ) The information that the Institution makes available via a publicly accessible Web site or written response to any requestor within five business days of a request, shall include, at a minimum, the following: the Investigator's name; the Investigator's title and role with respect to the research project; the name of the entity in which the significant financial interest is held; the nature of the significant financial interest; and the approximate dollar value of the significant financial interest (dollar ranges are permissible: $0-$4,999; $5,000-$9,999; $10,000-$19,999; amounts between $20,000-$100,000 by increments of $20,000; amounts above $100,000 by increments of $50,000), or a statement that the interest is one whose value cannot be readily determined through reference to public prices or other reasonable measures of fair market value.

( iii ) If the Institution uses a publicly accessible Web site for the purposes of this subsection, the information that the Institution posts shall be updated at least annually. In addition, the Institution shall update the Web site within sixty days of the Institution's receipt or identification of information concerning any additional significant financial interest of the senior/key personnel for the PHS-funded research project that was not previously disclosed, or upon the disclosure of a significant financial interest of senior/key personnel new to the PHS-funded research project, if the Institution determines that the significant financial interest is related to the PHS-funded research and is a financial conflict of interest. The Web site shall note that the information provided is current as of the date listed and is subject to updates, on at least an annual basis and within 60 days of the Institution's identification of a new financial conflict of interest. If the Institution responds to written requests for the purposes of this subsection, the Institution will note in its written response that the information provided is current as of the date of the correspondence and is subject to updates, on at least an annual basis and within 60 days of the Institution's identification of a new financial conflict of interest, which should be requested subsequently by the requestor.

( iv ) Information concerning the significant financial interests of an individual subject to paragraph (a)(5) of this section shall remain available, for responses to written requests or for posting via the Institution's publicly accessible Web site for at least three years from the date that the information was most recently updated.

( 6 ) In addition to the types of financial conflicts of interest as defined in this subpart that must be managed pursuant to this section, an Institution may require the management of other financial conflicts of interest in its policy on financial conflicts of interest, as the Institution deems appropriate.

( b ) Reporting of financial conflicts of interest.

( 1 ) Prior to the Institution's expenditure of any funds under a PHS-funded research project, the Institution shall provide to the PHS Awarding Component an FCOI report regarding any Investigator's significant financial interest found by the Institution to be conflicting and ensure that the Institution has implemented a management plan in accordance with this subpart. In cases in which the Institution identifies a financial conflict of interest and eliminates it prior to the expenditure of PHS-awarded funds, the Institution shall not submit an FCOI report to the PHS Awarding Component.

( 2 ) For any significant financial interest that the Institution identifies as conflicting subsequent to the Institution's initial FCOI report during an ongoing PHS-funded research project (e.g., upon the participation of an Investigator who is new to the research project), the Institution shall provide to the PHS Awarding Component, within sixty days, an FCOI report regarding the financial conflict of interest and ensure that the Institution has implemented a management plan in accordance with this subpart. Pursuant to paragraph (a)(3)(ii) of this section, where such FCOI report involves a significant financial interest that was not disclosed timely by an Investigator or, for whatever reason, was not previously reviewed or managed by the Institution (e.g., was not timely reviewed or reported by a subrecipient), the Institution also is required to complete a retrospective review to determine whether any PHS-funded research, or portion thereof, conducted prior to the identification and management of the financial conflict of interest was biased in the design, conduct, or reporting of such research. Additionally, pursuant to paragraph (a)(3)(iii) of this section, if bias is found, the Institution is required to notify the PHS Awarding Component promptly and submit a mitigation report to the PHS Awarding Component.

( 3 ) Any FCOI report required under paragraphs (b)(1) or (b)(2) of this section shall include sufficient information to enable the PHS Awarding Component to understand the nature and extent of the financial conflict, and to assess the appropriateness of the Institution's management plan. Elements of the FCOI report shall include, but are not necessarily limited to the following:

( i ) Project number;

( ii ) PD/PI or Contact PD/PI if a multiple PD/PI model is used;

( iii ) Name of the Investigator with the financial conflict of interest;

( iv ) Name of the entity with which the Investigator has a financial conflict of interest;

( v ) Nature of the financial interest (e.g., equity, consulting fee, travel reimbursement, honorarium);

( vi ) Value of the financial interest (dollar ranges are permissible: $0-$4,999; $5,000-$9,999; $10,000-$19,999; amounts between $20,000-$100,000 by increments of $20,000; amounts above $100,000 by increments of $50,000), or a statement that the interest is one whose value cannot be readily determined through reference to public prices or other reasonable measures of fair market value;

( vii ) A description of how the financial interest relates to the PHS-funded research and the basis for the Institution's determination that the financial interest conflicts with such research; and

( viii ) A description of the key elements of the Institution's management plan, including:

( A ) Role and principal duties of the conflicted Investigator in the research project;

( B ) Conditions of the management plan;

( C ) How the management plan is designed to safeguard objectivity in the research project;

( D ) Confirmation of the Investigator's agreement to the management plan;

( E ) How the management plan will be monitored to ensure Investigator compliance; and

( F ) Other information as needed.

( 4 ) For any financial conflict of interest previously reported by the Institution with regard to an ongoing PHS-funded research project, the Institution shall provide to the PHS Awarding Component an annual FCOI report that addresses the status of the financial conflict of interest and any changes to the management plan for the duration of the PHS-funded research project. The annual FCOI report shall specify whether the financial conflict is still being managed or explain why the financial conflict of interest no longer exists. The Institution shall provide annual FCOI reports to the PHS Awarding Component for the duration of the project period (including extensions with or without funds) in the time and manner specified by the PHS Awarding Component.

( 5 ) In addition to the types of financial conflicts of interest as defined in this subpart that must be reported pursuant to this section, an Institution may require the reporting of other financial conflicts of interest in its policy on financial conflicts of interest, as the Institution deems appropriate.

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For covered individuals engaged in Public Health Service (PHS) or Department of Energy (DOE) sponsored research, a retrospective review of a conflicted investigator’s activities and sponsored research is conducted to determine whether any PHS or DOE sponsored research, or portion thereof, conducted prior to the identification and management of a conflict of interest (COI) was biased in the design, conduct, or reporting of the research.

This procedure may be used for non-PHS sponsored research conflicts when directed by the Vice President for Research and Innovation, at their discretion.

Requirements for a Retrospective Review

A retrospective review is not required if a COI is timely identified and managed. A COI is considered to have been timely identified and managed if the conflict management plan (CMP) is (1) implemented before the expenditure of project funds, or (2) is established within 60 days of an investigator’s timely disclosure of a significant financial interest (SFI) or business interest (BI) discovered or acquired during the course of an on-going project. Since University policy requires an Investigator to report a significant financial interest (SFI) or business interest (BI) within 30 days of discovering or acquiring (e.g. through purchase, marriage, inheritance) the interest, the COI is timely managed if a management plan is implemented, at least on an interim basis, within 90 days of its discovery or acquisition by the Investigator during the course of an on-going project.

When a Retrospective Review is required . The retrospective review must be completed within 120 days of a standing Conflict Review Panel’s (CRP) determination that a COI exists and that it was not identified or managed in a timely manner (hereafter “retrospective review criteria”). A COI could be identified or managed in an untimely manner in any of the following circumstances:

• failure by the Investigator to disclose a SFI or BI that is determined by a Conflict Review Panel to constitute an COI;
• failure by the University to review or manage a COI (e.g., not timely reported by a subrecipient or timely reviewed by the University) ; or
• failure by an Investigator to comply with a Conflict Management Plan.

Retrospective Review Procedures  

The retrospective review, bias determination, and mitigation plan will be accomplished by a standing Conflict Review Panel (CRP), with support as required from an ad hoc Retrospective Review Committee (RRC).

• No Bias Finding . If the CRP concludes that the research is in the preliminary stages such that bias could not yet have occurred, the CRP will document that determination in the CRP meeting minutes. If applicable, the CRP will determine the appropriate action to address an untimely disclosure.
• Possible Bias . If the CRP determines the research is at a stage at which bias could have occurred, the CRP will direct the COI Program to promptly submit a written request to the investigator’s Associate Dean for Research to appoint an ad hoc Retrospective Review Committee (RRC) to complete a retrospective review. 
• Project number
• Project title
• Project Director (PD)/PI or contact PD/PI if a multiple PD/PI model is used
• Name of the investigator with the COI
• Name of the entity with which the Investigator has a COI
• Reason(s) for the retrospective review
• Detailed methodology used for the retrospective review (e.g., methodology of the review process, composition of the review panel, documents reviewed);
• Findings of the review;
• Conclusions of the review.
• As soon as practicable, the Associate Dean for Research will appoint an RRC comprised of an individual or individuals with rank and expertise comparable to the conflicted investigator.
• Once appointed, the RRC will promptly conduct the retrospective review. The RRC should inform the staff of the Conflict of Interest Program if it is experiencing difficulties in accomplishing a timely and complete review.
• Why was the SFI/BI not reported in a timely fashion?
• What have your contributions or involvement in the project been thus far?
• Do you think you have made judgments in this research project that could have been influenced by your SFI/BI?
• Did any of your research team ever ask whether you have financial or business interests related to this project?
• Have you presented results from the project to an audience or published an abstract, poster, or article?
• Have you made any disclosures of your interest to your research team, to an audience, or in a publication?
• Have you participated in the experimentation or other study procedures on this research project?
• How far along is this project?
• Were you aware that the conflicted investigator has a SFI/BI related to this research?
• Have any project data been presented to a scientific audience or published as an abstract, poster, or article?
• Do you recall an instance in which the conflicted investigator made a decision that could favor their SFI/BI and went beyond sound scientific judgment?
• Were outlier data ever culled by the conflicted investigator in a way that you think was not compatible with accepted statistical practices?
• Were data that in hindsight might be interpreted to be unfavorable to the SFI/BI ever ignored or suppressed?
• The RRC will submit its written report containing its methodology, findings, and conclusions, through the Chief Compliance Officer to the Conflict Review Panel. The RRC report is advisory to the CRP. The RRC member(s) shall make themselves available to discuss their review, findings, and conclusions with the CRP.
• The CRP will review the RRC report and vote on the issue of whether bias occurred in the design, conduct, or reporting of the sponsored research. If the CRP finds there is no reasonable basis on which to conclude that bias occurred, the finding will documented in writing and the matter will be closed.
• If the CRP concludes there is a reasonable basis on which to conclude that bias has occurred, it will determine whether the research project is salvageable. If the CRP concludes that the research is salvageable, it will also determine whether additional CMP mechanisms are required to mitigate the bias and to effectively manage the conduct of the research going forward. The CRP also will determine the appropriate response to any untimely disclosure. If the CRP believes the research project is not salvageable, the matter will be referred to the appropriate College Dean and/or Associate Dean for Research for review and further action. In these circumstances, the CRP will request that the College Dean and/or Associate Dean provide the CRP with their assessment of the matter and proposed resolution. Once feedback from the Dean and/or Associate Dean has been received, the CRP will be updated and a decision will be made regarding the need for any further action. 
• If the CRP believes that the facts support an allegation of research misconduct as it is defined in Administrative Policy: Research Misconduct , it will forward the RRC report and any other facts bearing on the matter through the Chief Compliance Officer to the University’s Research Integrity Officer.
• If bias is found, the COI Program will provide the results of the retrospective review and a mitigation report to Sponsored Projects Administration (SPA) so that it can notify the research sponsor as required. If the sponsor is a PHS agency or the DOE, SPA will notify the PHS or DOE awarding component promptly and submit a mitigation report to the PHS or DOE awarding component. The mitigation report must include, at a minimum, the key elements documented in the retrospective review, a description of the impact of the bias on the research project and the University’s plan of action or actions to eliminate or mitigate the effect of the bias (e.g., impact on the research project, extent of harm, including any qualitative and quantitative data to support any actual or future harm; and an analysis of whether the research project is salvageable). 
• If the CMP is modified, the COI Program will notify SPA, and SPA will update the FCOI report to the PHS or DOE funding agency.
• The COI Program will maintain the results of a retrospective review for at least three years from the date the final expenditures report for the project is submitted to the research sponsor.
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42 CFR § 50.605 - Management and reporting of financial conflicts of interest.

(a) Management of financial conflicts of interest.

(1) Prior to the Institution 's expenditure of any funds under a PHS -funded research project, the designated official(s) of an Institution shall, consistent with § 50.604(f) : review all Investigator disclosures of significant financial interests ; determine whether any significant financial interests relate to PHS -funded research ; determine whether a financial conflict of interest exists; and, if so, develop and implement a management plan that shall specify the actions that have been, and shall be, taken to manage such financial conflict of interest . Examples of conditions or restrictions that might be imposed to manage a financial conflict of interest include, but are not limited to:

(i) Public disclosure of financial conflicts of interest (e.g., when presenting or publishing the research);

(ii) For research projects involving human subjects research , disclosure of financial conflicts of interest directly to participants;

(iii) Appointment of an independent monitor capable of taking measures to protect the design, conduct, and reporting of the research against bias resulting from the financial conflict of interest ;

(iv) Modification of the research plan;

(v) Change of personnel or personnel responsibilities, or disqualification of personnel from participation in all or a portion of the research ;

(vi) Reduction or elimination of the financial interest (e.g., sale of an equity interest); or

(vii) Severance of relationships that create financial conflicts.

(2) Whenever, in the course of an ongoing PHS -funded research project, an Investigator who is new to participating in the research project discloses a significant financial interest or an existing Investigator discloses a new significant financial interest to the Institution , the designated official(s) of the Institution shall, within sixty days: review the disclosure of the significant financial interest ; determine whether it is related to PHS -funded research ; determine whether a financial conflict of interest exists; and, if so, implement, on at least an interim basis, a management plan that shall specify the actions that have been, and will be, taken to manage such financial conflict of interest . Depending on the nature of the significant financial interest , an Institution may determine that additional interim measures are necessary with regard to the Investigator 's participation in the PHS -funded research project between the date of disclosure and the completion of the Institution 's review.

(3) Whenever an Institution identifies a significant financial interest that was not disclosed timely by an Investigator or, for whatever reason, was not previously reviewed by the Institution during an ongoing PHS -funded research project (e.g., was not timely reviewed or reported by a subrecipient), the designated official(s) shall, within sixty days: review the significant financial interest ; determine whether it is related to PHS -funded research ; determine whether a financial conflict of interest exists; and, if so:

(i) Implement, on at least an interim basis, a management plan that shall specify the actions that have been, and will be, taken to manage such financial conflict of interest going forward;

(A) In addition, whenever a financial conflict of interest is not identified or managed in a timely manner including failure by the Investigator to disclose a significant financial interest that is determined by the Institution to constitute a financial conflict of interest ; failure by the Institution to review or manage such a financial conflict of interest ; or failure by the Investigator to comply with a financial conflict of interest management plan, the Institution shall, within 120 days of the Institution 's determination of noncompliance, complete a retrospective review of the Investigator 's activities and the PHS -funded research project to determine whether any PHS -funded research , or portion thereof, conducted during the time period of the noncompliance, was biased in the design, conduct, or reporting of such research .

(B) The Institution is required to document the retrospective review; such documentation shall include, but not necessarily be limited to, all of the following key elements:

(1) Project number;

(2) Project title;

(3) PD/PI or contact PD/PI if a multiple PD/PI model is used;

(4) Name of the Investigator with the FCOI;

(5) Name of the entity with which the Investigator has a financial conflict of interest ;

(6) Reason(s) for the retrospective review;

(7) Detailed methodology used for the retrospective review (e.g., methodology of the review process, composition of the review panel, documents reviewed);

(8) Findings of the review; and

(9) Conclusions of the review.

(iii) Based on the results of the retrospective review, if appropriate, the Institution shall update the previously submitted FCOI report , specifying the actions that will be taken to manage the financial conflict of interest going forward. If bias is found, the Institution is required to notify the PHS Awarding Component promptly and submit a mitigation report to the PHS Awarding Component . The mitigation report must include, at a minimum, the key elements documented in the retrospective review above and a description of the impact of the bias on the research project and the Institution 's plan of action or actions taken to eliminate or mitigate the effect of the bias (e.g., impact on the research project; extent of harm done, including any qualitative and quantitative data to support any actual or future harm; analysis of whether the research project is salvageable). Thereafter, the Institution will submit FCOI reports annually, as specified elsewhere in this subpart. Depending on the nature of the financial conflict of interest , an Institution may determine that additional interim measures are necessary with regard to the Investigator 's participation in the PHS -funded research project between the date that the financial conflict of interest or the Investigator 's noncompliance is determined and the completion of the Institution 's retrospective review.

(4) Whenever an Institution implements a management plan pursuant to this subpart, the Institution shall monitor Investigator compliance with the management plan on an ongoing basis until the completion of the PHS -funded research project.

(i) Prior to the Institution 's expenditure of any funds under a PHS -funded research project, the Institution shall ensure public accessibility, via a publicly accessible Web site or written response to any requestor within five business days of a request, of information concerning any significant financial interest disclosed to the Institution that meets the following three criteria:

(A) The significant financial interest was disclosed and is still held by the senior/key personnel as defined by this subpart;

(B) The Institution determines that the significant financial interest is related to the PHS -funded research ; and

(C) The Institution determines that the significant financial interest is a financial conflict of interest .

(ii) The information that the Institution makes available via a publicly accessible Web site or written response to any requestor within five business days of a request, shall include, at a minimum, the following: the Investigator 's name; the Investigator 's title and role with respect to the research project; the name of the entity in which the significant financial interest is held; the nature of the significant financial interest ; and the approximate dollar value of the significant financial interest (dollar ranges are permissible: $0-$4,999; $5,000-$9,999; $10,000-$19,999; amounts between $20,000-$100,000 by increments of $20,000; amounts above $100,000 by increments of $50,000), or a statement that the interest is one whose value cannot be readily determined through reference to public prices or other reasonable measures of fair market value.

(iii) If the Institution uses a publicly accessible Web site for the purposes of this subsection, the information that the Institution posts shall be updated at least annually. In addition, the Institution shall update the Web site within sixty days of the Institution 's receipt or identification of information concerning any additional significant financial interest of the senior/key personnel for the PHS -funded research project that was not previously disclosed, or upon the disclosure of a significant financial interest of senior/key personnel new to the PHS -funded research project, if the Institution determines that the significant financial interest is related to the PHS -funded research and is a financial conflict of interest . The Web site shall note that the information provided is current as of the date listed and is subject to updates, on at least an annual basis and within 60 days of the Institution 's identification of a new financial conflict of interest . If the Institution responds to written requests for the purposes of this subsection, the Institution will note in its written response that the information provided is current as of the date of the correspondence and is subject to updates, on at least an annual basis and within 60 days of the Institution 's identification of a new financial conflict of interest , which should be requested subsequently by the requestor.

(iv) Information concerning the significant financial interests of an individual subject to paragraph (a)(5) of this section shall remain available, for responses to written requests or for posting via the Institution 's publicly accessible Web site for at least three years from the date that the information was most recently updated.

(6) In addition to the types of financial conflicts of interest as defined in this subpart that must be managed pursuant to this section, an Institution may require the management of other financial conflicts of interest in its policy on financial conflicts of interest, as the Institution deems appropriate.

(b) Reporting of financial conflicts of interest.

(1) Prior to the Institution 's expenditure of any funds under a PHS -funded research project, the Institution shall provide to the PHS Awarding Component an FCOI report regarding any Investigator 's significant financial interest found by the Institution to be conflicting and ensure that the Institution has implemented a management plan in accordance with this subpart. In cases in which the Institution identifies a financial conflict of interest and eliminates it prior to the expenditure of PHS -awarded funds, the Institution shall not submit an FCOI report to the PHS Awarding Component .

(2) For any significant financial interest that the Institution identifies as conflicting subsequent to the Institution 's initial FCOI report during an ongoing PHS -funded research project (e.g., upon the participation of an Investigator who is new to the research project), the Institution shall provide to the PHS Awarding Component , within sixty days, an FCOI report regarding the financial conflict of interest and ensure that the Institution has implemented a management plan in accordance with this subpart. Pursuant to paragraph (a)(3)(ii) of this section, where such FCOI report involves a significant financial interest that was not disclosed timely by an Investigator or, for whatever reason, was not previously reviewed or managed by the Institution (e.g., was not timely reviewed or reported by a subrecipient), the Institution also is required to complete a retrospective review to determine whether any PHS -funded research , or portion thereof, conducted prior to the identification and management of the financial conflict of interest was biased in the design, conduct, or reporting of such research . Additionally, pursuant to paragraph (a)(3)(iii) of this section, if bias is found, the Institution is required to notify the PHS Awarding Component promptly and submit a mitigation report to the PHS Awarding Component .

(3) Any FCOI report required under paragraphs (b)(1) or (b)(2) of this section shall include sufficient information to enable the PHS Awarding Component to understand the nature and extent of the financial conflict, and to assess the appropriateness of the Institution 's management plan. Elements of the FCOI report shall include, but are not necessarily limited to the following:

(i) Project number;

(ii) PD/PI or Contact PD/PI if a multiple PD/PI model is used;

(iii) Name of the Investigator with the financial conflict of interest ;

(iv) Name of the entity with which the Investigator has a financial conflict of interest ;

(v) Nature of the financial interest (e.g., equity, consulting fee, travel reimbursement, honorarium);

(vi) Value of the financial interest (dollar ranges are permissible: $0-$4,999; $5,000-$9,999; $10,000-$19,999; amounts between $20,000-$100,000 by increments of $20,000; amounts above $100,000 by increments of $50,000), or a statement that the interest is one whose value cannot be readily determined through reference to public prices or other reasonable measures of fair market value;

(vii) A description of how the financial interest relates to the PHS -funded research and the basis for the Institution 's determination that the financial interest conflicts with such research ; and

(viii) A description of the key elements of the Institution 's management plan, including:

(A) Role and principal duties of the conflicted Investigator in the research project;

(B) Conditions of the management plan;

(C) How the management plan is designed to safeguard objectivity in the research project;

(D) Confirmation of the Investigator 's agreement to the management plan;

(E) How the management plan will be monitored to ensure Investigator compliance; and

(F) Other information as needed.

(4) For any financial conflict of interest previously reported by the Institution with regard to an ongoing PHS -funded research project, the Institution shall provide to the PHS Awarding Component an annual FCOI report that addresses the status of the financial conflict of interest and any changes to the management plan for the duration of the PHS -funded research project. The annual FCOI report shall specify whether the financial conflict is still being managed or explain why the financial conflict of interest no longer exists. The Institution shall provide annual FCOI reports to the PHS Awarding Component for the duration of the project period (including extensions with or without funds) in the time and manner specified by the PHS Awarding Component .

(5) In addition to the types of financial conflicts of interest as defined in this subpart that must be reported pursuant to this section, an Institution may require the reporting of other financial conflicts of interest in its policy on financial conflicts of interest, as the Institution deems appropriate.

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Potential Risks and Mitigation Strategies Before the Conduct of a Clinical Trial: An Industry Perspective

Affiliation.

• 1 Wockhardt Limited, Wockhardt Towers, Bandra Kurla Complex, Mumbai - 400 051 (India). [email protected].
• PMID: 26435140
• DOI: 10.2174/1574887110666151005110751

Conduct of clinical trials has undergone substantial changes over the last two decades. Newer markets, evolving guidelines and documentation and high cost involved in conducting the trials have led pharmaceutical companies to prepare a risk mitigation plan. Extensive monitoring of potential risks is an essential element of clinical trials which helps to ensure quality and integrity of a clinical investigation. Every clinical trial has pre (before the trial), conduct and post phase. This article which has been developed as a result of extensive research at ground level by a reputed pharmaceutical company to identify the potential stages of risks that could affect the overall quality and safety of a trial and its outcome during the pre-phase of trial (the stage of the trial where the study design is being planned before initiation of the clinical trial). It includes risks associated with basic study concept, protocol design, Confidential Disclosure Agreement (CDA) and Clinical Trial Authorization (CTA) application signing, vendors of central drug laboratory, site and investigator selection, Clinical Research Coordinator (CRC) meet, Informed Consent Form (ICF), Case Report Form (CRF)/ Status Report Form (SRF) preparation, Ethics Committee (EC) submission, etc. have been highlighted. The risk based mitigation strategy (to develop an effective risk monitoring plan before staring a clinical trial) has also been suggested by authors. A well-tailored and integrated plan, recognition of potential risks and their mitigation strategy can result in the pre exclusion or end to end solution of all the risks associated with pre- phase of clinical trials.

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Mitigating your research security risks.

Research security risk mitigation aims to reduce the likelihood and impact of risks to a level that is acceptable to the researcher, their institution, the federal research funding organization, and the Government of Canada.

This page offers information that can be used for the development of risk mitigation plans. Other resources that provide best practices to protect Canadian research include the following two guides:

• Mitigating economic and/or geopolitical risks in sensitive research projects
• Travel security guide for university researchers and staff

Why is developing a risk mitigation plan important?

Risk mitigation plans should identify the appropriate mitigation measures to reduce the likelihood of an identified security risk from materializing, and/or to lessen the impact in case the identified risk materializes. Having a risk-targeted mitigation plan in place will secure the research project while pursuing open and collaborative research partnerships that benefit Canada.

All researchers, whether or not they seek federal funding, can use this guidance to develop their risk mitigation plan when establishing and/or continuing research partnerships with national, international and multinational partners.

Who should be involved in the development of a risk mitigation plan?

A risk mitigation plan should be developed with your institution. The institution’s corporate support services (e.g., IT, security, legal) should also be involved to confirm the viability and feasibility of the proposed measures.

What are mitigation measures?

Mitigation measures should be tailored to the research project and commensurate with the risks identified while considering open science principles. Examples of risk mitigation measures include, but are not limited to:

• Training Courses (e.g., research security, cyber security, and intellectual property training)
• Guidance on how to identify, assess and mitigate security risks to research, including best practices, published by the Government of Canada departments and agencies
• Research partnership agreements that include clauses to protect intellectual property and technology transfer
• Data management plans
• Cyber security plans
• Establishing internal protocols to restrict access to research facilities for partners and personnel to an “as needed” basis
• Ensuring internal regular reporting mechanisms are in place on the implementation and effectiveness of the proposed risk mitigation measures

The Government of Canada recognizes the importance of making Canadian science open to all, maximizing benefits for the well-being, health, and economy of our country. Open Science is the practice of making scientific inputs, outputs, and processes freely available to all with minimal restrictions. Scientific research outputs include peer-reviewed science articles and publications; scientific and research data; and public contribution to and dialogue about science. Open Science is enabled by people, technology and infrastructure. It is practiced in full respect of privacy, security, ethical considerations, and appropriate intellectual property protection.

Additional guidance on principles, tools, and resources for research data management can be found in the Frequently Asked Questions of the Tri-Agency Data Management Policy .

A risk mitigation plan could cover areas, such as, but not limited to:

1. building a strong research team.

The integrity of your research relies heavily on knowing and trusting the people who make up your research team (e.g., researchers, fellows, and graduate students). In sensitive research areas, people may be more motivated to misrepresent themselves to gain access to information. Strong, trust-driven research teams set the foundation to pursue research in sensitive areas with a high degree of confidence. There are several best practices that can help mitigate these risks:

• Verify all team members' professional history and assess alignment with the research objectives for this project: Conduct appropriate reference and background checks on all members of the research team. Are their credentials, publications and affiliations in line with what they told you? Consider asking colleagues who have previously worked with the individual within or outside of your organization to confirm any information on the individual’s history and research affiliations. In addition to that, one can review and verify an individual’s publication history though SCOPUS or a similar tool.
• Assess existing or potential conflicts of interest or affiliation that would impede collaboration with any team member: Ask yourself, "Could the interests or affiliations of a team member compromise the integrity of the team’s research in a manner that jeopardizes Canada’s national and economic security?".
• Discuss project risks internally and make a plan for their mitigation, involving external team members as appropriate: Brainstorm potential project security risks with your team. Researchers can use the online risk register template to assess whether the practices of your collaborator(s) and/or collaborating institution(s) are consistent with your institution's standards on ethics and research conduct. Ask yourself whether all aspects of the project, regardless of where the work is or was performed, would pass ethics review at your institution.

2. Assessing the Alignment of Your Partners Motivations With Your Own

Collaboration with partner organizations can bring significant benefits. When working with partner organizations, it is important to verify alignment of their motivations with your research objectives and that your partner organization does not have ulterior motives. There are several best practices that can help mitigate these risks:

• Verify that the motivations of all partners are clear and aligned with the goals of the research team, including any expectations about intellectual property: Ask the partner directly what they expect from the research team throughout the duration of the project in terms of everyone’s roles, responsibilities, and deliverables. It is also important to ask what the partner hopes to gain from the research project once it has been successfully completed (e.g., access to new intellectual property or the commercialization of the research results).
• Assess if the partner's governance structure is transparent and whether the ultimate beneficiary of their collaboration on your project is clear: Conduct your own open source due diligence by looking at your partner’s website to identify who leads the organization and if there are any linkages to foreign governments, organizations, and/or actors. Ask yourself, “Are there are any information gaps that exist?”.
• Explore if other academics have had positive experiences collaborating with this partner organization: Reach out to researchers across your institution and at other institutions to gather valuable information on past experiences and solutions to address potential concerns.
• Assess whether the practices and contributions of your partner(s) are consistent with the standards on ethics and research conduct at your own institution: Ask yourself whether any contributions (e.g., data, IP) are consistent with your institution’s policies and/or Canadian laws. Open source due diligence can be used to verify that your research partner’s intentions and relationships are clear and appropriate for your project. This will help you assess potential risks to your intellectual property, stay in control of your research, and ensure that the partnership meets its intended goals. For more information on conducting open source due diligence, researchers are encouraged to reference the Government of Canada’s voluntary guide titled Conducting Open Source Due Diligence for Safeguarding Research Partnerships .

3. Using Sound Cybersecurity and Data Management Practices

The emergence of new technology has opened the doors to greater research collaboration by facilitating the sharing of data and results in real time. It is important to verify that adequate cybersecurity and data management policies, practices, and infrastructure are in place and agreed on by all research team members and partners to maintain the integrity and intended ownership of the research.

• Verify that all team members have completed cyber hygiene and data management training: Discuss appropriate training options with your Chief Information Officer (CIO) or with the relevant person in your institution who is responsible for maintaining strong cyber hygiene and data management practices.
• Assess if the data management and cybersecurity measures needed to adequately protect research integrity are in place across all partners: Consult and engage with your institution on the policies and practices in place. Internal research and IT services should also be involved. Public Safety Canada and the Canadian Centre for Cyber Security offer resources and best practices.
• Focus on addressing divergent cybersecurity and data management practices and decide on a mutually acceptable approach to securing your research data: Verify that your organization has a strong security posture as it will assist in protecting core assets, including research data and results. It is good practice to identify areas of vulnerability within an organization’s infrastructure and business processes that could contribute to unauthorized access to research methods, techniques, and results. When reflecting on existing divergences, ask yourself, "Given the sensitivity of the research topic and data, what is the level of risk associated with a breach and what is the probability it may occur?".
• If professional or personal international travel is expected during the project, agree to a protocol for device management: Consult the Travel security guide for university researchers and staff for more information on how to protect your research when traveling within or outside of Canada is required.

4. Agreement on Intended Use of Research Findings

The publication of research findings and the generation of intellectual property are lucrative within the academic community. Partner organizations that are involved in a research project may have different views on the intended use of the research. There are several best practices that can help to confirm that the researcher and partner organization are aware and agree on the potential use of the research and its results:

• Agree to a plan of how and when you will share details about the project, including publication, conferences, teaching, mass media, social media and personal communication. This will increase effectiveness and minimize disagreement later: Consult the Communications in Health Care Improvement toolkit that has been published by the UK’s Health Foundation. This resource provides an introduction on how to increase your understanding and use of communications to better plan, implement, and spread of your research work.
• Assess the potential value of any project- related IP and what you need to do to protect it: Ask yourself, "What types of IP could be generated through this research project? What do we need to do to preserve the value of this IP?"
• Ensure all collaborators and partners have agreed on how IP will be handled: Consult the appropriate contacts at your institution to better understand your institution's policies with respect to IP, as well as how internal policies, laws and enforcement measures might vary across relevant institutions and jurisdictions.
• Discuss how restrictions on academic freedom or commercial interests may impact the research project and the communication of research results: Ask yourself, "Do the restrictions imposed on communicating results have potentially harmful impacts on the integrity of our research or our ability to publish results?"
• Ensure all collaborators and partners are comfortable with the likely uses of any research results: Brainstorm with your team the likely uses of the results of the project, then ask members if they remain comfortable proceeding with the project.
• Ensure mechanisms exist that guarantee that any researcher involved in the project is able to use the results to complete their studies: Verify with the appropriate contacts at your institution what measures exist at your institution and make all partners and collaborators aware of this requirement. Participants in NSERC-supported research must ensure that a researcher’s graduation is not impeded by intellectual property issues, and must support the publication of results in the open literature. See the Policy on Intellectual Property for more information.

National Climate Assessment Home

Introduction.

• Observed Change
• Future Climate Change
• Recent U.S. Temperature Trends
• Frost-free Season
• Precipitation Change
• Heavy Downpours Increasing
• Extreme Weather
• Changes in Hurricanes
• Changes in Storms
• Sea Level Rise
• Melting Ice
• Ocean Acidification
• Transportation
• Agriculture
• Human Health
• Energy, Water, and Land
• Indigenous Peoples
• Land Use and Land Cover Change
• Rural Communities
• Biogeochemical Cycles
• Great Plains
• Hawai‘i and Pacific Islands
• Decision Support
• Research Needs
• Sustained Assessment
• Report Findings
• Climate Trends
• Our Changing Climate
• Water Supply
• Future Climate
• Widespread Impacts
• Ecosystems and Biodiversity
• Infrastructure
• Response Strategies
• Climate Science Supplement

This website is the digital version of the 2014 National Climate Assessment, produced in collaboration with the U.S. Global Change Research Program.

For the official version, please refer to the PDF in the downloads section. The downloadable PDF is the official version of the 2014 National Climate Assessment.

Search Options

Search form, welcome to the national climate assessment.

The National Climate Assessment summarizes the impacts of climate change on the United States, now and in the future.

A team of more than 300 experts guided by a 60-member Federal Advisory Committee produced the report, which was extensively reviewed by the public and experts, including federal agencies and a panel of the National Academy of Sciences.

The amount of future climate change will largely be determined by choices society makes about emissions. Lower emissions of heat trapping gases mean less future warming and less severe impacts. Emissions can be reduced through improved energy efficiency and switching to low-carbon or non-carbon energy sources.

Explore mitigation – ways of reducing future climate change.

Convening Lead Authors

Henry D. Jacoby, Massachusetts Institute of Technology

Anthony C. Janetos, Boston University

Lead Authors

Richard Birdsey, U.S. Forest Service

James Buizer, University of Arizona

Katherine Calvin, Pacific Northwest National Laboratory, University of Maryland

Francisco de la Chesnaye, Electric Power Research Institute

David Schimel, NASA Jet Propulsion Laboratory

Ian Sue Wing, Boston University

Contributing Authors

Reid Detchon, United Nations Foundation

Jae Edmonds, Pacific Northwest National Laboratory, University of Maryland

Lynn Russell, Scripps Institution of Oceanography, University of California, San Diego

Jason West, University of North Carolina

Mitigation refers to actions that reduce the human contribution to the planetary greenhouse effect. Mitigation actions include lowering emissions of greenhouse gases like carbon dioxide and methane, and particles like black carbon (soot) that have a warming effect. Increasing the net uptake of carbon dioxide through land-use change and forestry can make a contribution as well. As a whole, human activities result in higher global concentrations of greenhouse gases and to a warming of the planet – and the effect is increased by various self-reinforcing cycles in the Earth system (such as the way melting sea ice results in more dark ocean water, which absorbs more heat, and leads to more sea ice loss). Also, the absorption of increased carbon dioxide by the oceans is leading to increased ocean acidity with adverse effects on marine ecosystems.

Four mitigation-related topics are assessed in this chapter. First, it presents an overview of greenhouse gas emissions and their climate influence to provide a context for discussion of mitigation efforts. Second, the chapter provides a survey of activities contributing to U.S. emissions of carbon dioxide and other greenhouse gases. Third, it provides a summary of current government and voluntary efforts to manage these emissions. Finally, there is an assessment of the adequacy of these efforts relative to the magnitude of the climate change threat and a discussion of preparation for potential future action. While the chapter presents a brief overview of mitigation issues, it does not provide a comprehensive discussion of policy options, nor does it attempt to review or analyze the range of technologies available to reduce emissions.

These topics have also been the subject of other assessments, including those by the National Academy of Sciences 53 and the U.S. Department of Energy. 76 Mitigation topics are addressed throughout this report (see Ch. 4: Energy, Key Message 5 ; Ch. 5: Transportation,  Key Message 4 ; Ch. 7: Forests, Key Message 4 ; Ch. 9: Human Health, Key Message 4 ; Ch. 10: Energy, Water, and Land, Key Messages 1 , 2 , 3 ; Ch. 13: Land Use & Land Cover Change, Key Messages 2 , 4 ; Ch. 15: Biogeochemical Cycles, Key Message 3 ; Ch. 26: Decision Support, Key Messages 1 , 2 , 3 ; Appendix 3: Climate Science Supplemental Message 5 ; Appendix 4: FAQs N, S, X, Y, Z).

Emissions, Concentrations, and Climate Forcing

Setting mitigation objectives requires knowledge of the Earth system processes that determine the relationship among emissions, atmospheric concentrations and, ultimately, climate. Human-caused climate change results mainly from the increasing atmospheric concentrations of greenhouse gases. 3 These gases cause radiative “forcing” – an imbalance of heat trapped by the atmosphere compared to an equilibrium state. Atmospheric concentrations of greenhouse gases are the result of the history of emissions and of processes that remove them from the atmosphere; for example, by “sinks” like growing forests. 4 The fraction of emissions that remains in the atmosphere, which is different for each greenhouse gas, also varies over time as a result of Earth system processes.

The impact of greenhouse gases depends partly on how long each one persists in the atmosphere. 5 Reactive gases like methane and nitrous oxide are destroyed chemically in the atmosphere, so the relationships between emissions and atmospheric concentrations are determined by the rate of those reactions. The term “lifetime” is often used to describe the speed with which a given gas is removed from the atmosphere. Methane has a relatively short lifetime (largely removed within a decade or so, depending on conditions), so reductions in emissions can lead to a fairly rapid decrease in concentrations as the gas is oxidized in the atmosphere. 6 Nitrous oxide has a much longer lifetime, taking more than 100 years to be substantially removed. 7 Other gases in this category include industrial gases, like those used as solvents and in air conditioning, some of which persist in the atmosphere for hundreds or thousands of years.

Carbon dioxide (CO 2 ) does not react chemically with other gases in the atmosphere, so it does not, strictly speaking, have a “lifetime.” 8 Instead, the relationship between emissions and concentrations from year to year is determined by patterns of release (for example, through burning of fossil fuels) and uptake (for example, by vegetation and by the ocean). 9 Once CO 2 is emitted from any source, a portion of it is removed from the atmosphere over time by plant growth and absorption by the oceans, after which it continues to circulate in the land-atmosphere-ocean system until it is finally converted into stable forms in soils, deep ocean sediments, or other geological repositories (Figure 27.1).

Of the carbon dioxide emitted from human activities in a year, about half is removed from the atmosphere by natural processes within a century, but around 20% continues to circulate and to affect atmospheric concentrations for thousands of years. 10 Stabilizing or reducing atmospheric carbon dioxide concentrations, therefore, requires very deep reductions in future emissions – ultimately approaching zero – to compensate for past emissions that are still circulating in the Earth system. Avoiding future emissions, or capturing and storing them in stable geological storage, would prevent carbon dioxide from entering the atmosphere, and would have very long-lasting effects on atmospheric concentrations.

In addition to greenhouse gases, there can be climate effects from fine particles in the atmosphere. An example is black carbon (soot), which is released from coal burning, diesel engines, cooking fires, wood stoves, wildfires, and other combustion sources. These particles have a warming influence, especially when they absorb solar energy low in the atmosphere. 11 Other particles, such as those formed from sulfur dioxide released during coal burning, have a cooling effect by reflecting some of the sun’s energy back to space or by increasing the brightness of clouds (see: Ch. 2: Our Changing Climate ; Appendix 3: Climate Science Supplement ; and Appendix 4: FAQs ).

The effect of each gas is related to both how long it lasts in the atmosphere (the longer it lasts, the greater its influence) and its potency in trapping heat. The warming influence of different gases can be compared using “global warming potentials” (GWP), which combine these two effects, usually added up over a 100-year time period. Global warming potentials are referenced to carbon dioxide – which is defined as having a GWP of 1.0 – and the combined effect of multiple gases is denoted in carbon dioxide equivalents, or CO 2 -e.

The relationship between emissions and concentrations of gases can be modeled using Earth System Models. 4 Such models apply our understanding of biogeochemical processes that remove greenhouse gas from the atmosphere to predict their future concentrations. These models show that stabilizing CO 2 emissions would not stabilize its atmospheric concentrations but instead result in a concentration that would increase at a relatively steady rate. Stabilizing atmospheric concentrations of CO 2 would require reducing emissions far below present-day levels. Concentration and emissions scenarios, such as the recently developed Representative Concentration Pathways (RCPs) and scenarios developed earlier by the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emissions Scenarios (SRES), are used in Earth System Models to study potential future climates. The RCPs span a range of atmospheric targets for use by climate modelers, 12 , 13 as do the SRES cases. These global analyses form a framework within which the climate contribution of U.S. mitigation efforts can be assessed. In this report, special attention is given to the SRES A2 scenario (similar to RCP 8.5), which assumes continued increases in emissions, and the SRES B1 scenario (close to RCP 4.5), which assumes a substantial reduction of emissions (Ch. 2: Our Changing Climate ; Appendix 5: Scenarios and Models ).

Geoengineering

Geoengineering has been proposed as a third option for addressing climate change in addition to, or alongside, mitigation and adaptation. Geoengineering refers to intentional modifications of the Earth system as a means to address climate change. Three types of activities have been proposed: 1) carbon dioxide removal (CDR), which boosts CO 2 removal from the atmosphere by various means, such as fertilizing ocean processes and promoting land-use practices that help take up carbon, 2) solar radiation management (SRM), which reflects a small percentage of sunlight back into space to offset warming from greenhouse gases, 14 and 3) direct capture and storage of CO 2 from the atmosphere. 15

Current research suggests that SRM or CDR could diminish the impacts of climate change. However, once undertaken, sudden cessation of SRM would exacerbate the climate effects on human populations and ecosystems, and some CDR might interfere with oceanic and terrestrial ecosystem processes. 16 SRM undertaken by itself would not slow increases in atmospheric CO 2 concentrations, and would therefore also fail to address ocean acidification. Furthermore, existing international institutions are not adequate to manage such global interventions. The risks associated with such purposeful perturbations to the Earth system are thus poorly understood, suggesting the need for caution and comprehensive research, including consideration of the implicit moral hazards. 17

Key Message 1

Carbon dioxide is removed from the atmosphere by natural processes at a rate that is roughly half of the current rate of emissions from human activities. Therefore, mitigation efforts that only stabilize global emissions will not reduce atmospheric concentrations of carbon dioxide, but will only limit their rate of increase. The same is true for other long-lived greenhouse gases.

Supporting Evidence

Process for developing key messages:.

Evaluation of literature by Coordinating Lead Authors

Description of evidence base

The message is a restatement of conclusions derived from the peer-reviewed literature over nearly the past 20 years (see Section 1 of chapter). Publications have documented the long lifetime of CO 2 in the atmosphere, resulting in long time lags between action and reduction, 9 , 10 , 18 and Earth System Models have shown that stabilizing emissions will not immediately stabilize atmospheric concentrations, which will continue to increase. 4

New information and remaining uncertainties

There are several important uncertainties in the current carbon cycle, especially the overall size, location, and dynamics of the land-use sink 9 , 10 and technological development and performance.

Simulating future atmospheric concentrations of greenhouse gases requires both assumptions about economic activity, stringency of any greenhouse gas emissions control, and availability of technologies, as well as a number of assumptions about how the changing climate system affects both natural and anthropogenic sources.

Assessment of confidence based on evidence

Very High . Observations of changes in the concentrations of greenhouse gases are consistent with our understanding of the broad relationships between emissions and concentrations.

Confidence Level

Strong evidence (established theory, multiple sources, consistent results, well documented and accepted methods, etc.), high consensus

Moderate evidence (several sources, some consistency, methods vary and/or documentation limited, etc.), medium consensus

Suggestive evidence (a few sources, limited consistency, models incomplete, methods emerging, etc.), competing schools of thought

Inconclusive evidence (limited sources, extrapolations, inconsistent findings, poor documentation and/or methods not tested, etc.), disagreement or lack of opinions among experts

Key Message 2

To meet the lower emissions scenario (B1) used in this assessment, global mitigation actions would need to limit global carbon dioxide emissions to a peak of around 44 billion tons per year within the next 25 years and decline thereafter. In 2011, global emissions were around 34 billion tons, and have been rising by about 0.9 billion tons per year for the past decade. Therefore, the world is on a path to exceed 44 billion tons per year within a decade.

A large number of emissions scenarios have been modeled, with a number of publications showing what would be required to limit CO 2 12 , 19 , 20 , 21 to any predetermined limit. At current concentrations and rate of rise, the emissions of CO 2 would need to peak around 44 billion tons within the next 25 years in order to stabilize concentrations as in the B1 scenario. Given the rate of increase in recent years, 1 , 2 this limit is expected to be surpassed. 22

Uncertainties about the carbon cycle could affect these calculations, but the largest uncertainties are the assumptions made about the strength and cost of greenhouse gas emissions policies.

The confidence in the conclusion is high . This is a contingent conclusion, though – we do not have high confidence that the current emission rate will be sustained. However, we do have high confidence that if we do choose to limit concentrations as in the B1 scenario, emissions will need to peak soon and then decline.

Key Message 3

Over recent decades, the U.S. economy has emitted a decreasing amount of carbon dioxide per dollar of gross domestic product. Between 2008 and 2012, there was also a decline in the total amount of carbon dioxide emitted annually from energy use in the United States as a result of a variety of factors, including changes in the economy, the development of new energy production technologies, and various government policies.

Trends in greenhouse gas emissions intensity are analyzed and published by governmental reporting agencies. 23 , 24 , 25 Published, peer-reviewed literature cited in Section 2 of the Mitigation Chapter supports the conclusions about why these trends have occurred. 26 , 27

Economic and technological forecasts are highly uncertain.

High . The statement is a summary restatement of published analyses by government agencies and interpretation from the reviewed literature.

Key Message 4

Carbon storage in land ecosystems, especially forests, has offset around 17% of annual U.S. fossil fuel emissions of greenhouse gases over the past several decades, but this carbon “sink” may not be sustainable.

Underlying data come primarily from U.S. Forest Service Forest Inventory and Analysis (FIA) plots, supplemented by additional ecological data collection efforts. Modeling conclusions come from peer-reviewed literature. All references are in Section 2 of the Mitigation Chapter. Studies have shown that there is a large land-use carbon sink in the United States. 25 , 28 , 29 Many publications attribute this sink to forest re-growth, and the sink is projected to decline as a result of forest aging 30 , 31 , 32 , 33 and factors like drought, fire, and insect infestations 31 reducing the carbon sink of these regions.

FIA plots are measured extremely carefully over long time periods, but do not cover all U.S. forested land. Other U.S. land types must have carbon content estimated from other sources. Modeling relationships between growth and carbon content, and taking CO 2 and climate change into account have large scientific uncertainties associated with them.

High . Evidence of past trends is based primarily on government data sources, but these also have to be augmented by other data and models in order to incorporate additional land-use types. Projecting future carbon content is consistent with published models, but these have intrinsic uncertainties associated with them.

Key Message 5

Both voluntary activities and a variety of policies and measures that lower emissions are currently in place at federal, state, and local levels in the United States, even though there is no comprehensive national climate legislation. Over the remainder of this century, aggressive and sustained greenhouse gas emission reductions by the United States and by other nations would be needed to reduce global emissions to a level consistent with the lower scenario (B1) analyzed in this assessment.

The identification of state, local, regional, federal, and voluntary programs that will have an effect of reducing greenhouse gas emissions is a straightforward accounting of both legislative action and announcements of the implementation of such programs. Some of the programs include the Carbon Disclosure Project (CDP), the American College and University Presidents' Climate Commitment (ACUPCC), U.S. Mayors Climate Protection Agreement, 34 and many other local government initiatives. 35 , 36 Several states have also adapted climate policies including California's Global Warming Solutions Act (AB 32) and the Regional Greenhouse Gas Initiative (RGGI). The assertion that they will not lead to a reduction of US CO 2 emissions is supported by calculations from the U.S. Energy Information Administration.

The major uncertainty in the calculation about future emissions levels is whether a comprehensive national policy will be implemented.

Very High . There is recognition that the implementation of voluntary programs may differ from how they are originally planned, and that institutions can always choose to leave voluntary programs (as is happening with RGGI, noted in the chapter). The statement about the future of U.S. CO 2 emissions cannot be taken as a prediction of what will happen – it is a conditional statement based on an assumption of no comprehensive national legislation or regulation.

Section 1: U.S. Emissions and Land-Use Change

Industrial, commercial, and household emissions.

U.S. greenhouse gas emissions, not accounting for uptake by land use and agriculture (see Figure 27.3), rose to as high as 7,260 million tons CO 2 -e in 2007, and then fell by about 9% between 2008 and 2012. 38 Several factors contributed to the decline, including the reduction in energy use in response to the 2008-2010 recession, the displacement of coal in electric generation by lower-priced natural gas, and the effect of federal and state energy and environmental policies. 23

Carbon dioxide made up 84% of U.S. greenhouse gas emissions in 2011. Forty-one percent of these emissions were attributable to liquid fuels (petroleum), followed closely by solid fuels (principally coal in electric generation), and to a lesser extent by natural gas. 23 The two dominant production sectors responsible for these emissions are electric power generation (coal and gas) and transportation (petroleum). Flaring and cement manufacture together account for less than 1% of the total. If emissions from electric generation are allocated to their various end-uses, transportation is the largest CO 2 source, contributing a bit over one-third of the total, followed by industry at slightly over a quarter, and residential use and the commercial sector at around one-fifth each.

A useful picture of historical patterns of carbon dioxide emissions can be constructed by decomposing the cumulative change in emissions from a base year into the contributions of five driving forces: 1) decline in the CO 2 content of energy use, as with a shift from coal to natural gas in electric generation, 2) reduction in energy intensity – the energy needed to produce each unit of gross domestic product (GDP) – which results from substitution responses to energy prices, changes in the composition of the capital stock, and both autonomous and price-induced technological change, 3) changes in the structure of the economy, such as a decline in energy-intensive industries and an increase in services that use less energy, 4) growth in per capita GDP, and 5) rising population.

Over the period 1963-2008, annual U.S. carbon dioxide emissions slightly more than doubled, because growth in emissions potential attributable to increases in population and GDP per person outweighed reductions contributed by lowered energy and carbon intensity and changes in economic structure (Figure 27.2). Each series in the figure illustrates the quantity of cumulative emissions since 1963 that would have been generated by the effect of the associated driver. By 2008, fossil fuel burning had increased CO 2 emissions by 2.7 billion tons over 1963 levels. However, by itself the observed decline in energy would have reduced emissions by 1.8 billion tons, while the observed increase in per capita GDP would have increased emissions by more than 5 billion tons.

Figure 27.2: Drivers of U.S. Fossil Emissions

Drivers of u.s. fossil emissions.

Figure 27.2: This graph depicts the changes in carbon dioxide (CO 2 ) emissions over time as a function of five driving forces: 1) the amount of CO 2 produced per unit of energy (CO 2 intensity); 2) the amount of energy used per unit of gross domestic product (energy intensity); 3) structural changes in the economy; 4) per capita income; and 5) population. Although CO 2 intensity and especially energy intensity have decreased significantly and the structure of the U.S. economy has changed, total CO 2 emissions have continued to rise as a result of the growth in both population and per capita income. (Baldwin and Sue Wing, 2013 37 ).

After decades of increases, CO 2 emissions from energy use (which account for 97% of total U.S. emissions) declined by around 9% between 2008 and 2012, largely due to a shift from coal to less CO 2 -intensive natural gas for electricity production. 38 Trends in driving forces shown in Figure 27.2 are expected to continue in the future, though their relative contributions are subject to significant uncertainty. The reference case projection by the U.S. Energy Information Administration (EIA) shows their net effect being a slower rate of CO 2 emissions growth than in the past, with roughly constant energy sector emissions to 2040. 39 It must be recognized, however, that emissions from energy use rise and fall from year to year, as the aforementioned driving forces vary.

The primary non-CO 2 gas emissions in 2011 were methane (9% of total CO 2 -e emissions), nitrous oxide (5%), and a set of industrial gases (2%). U.S. emissions of each of these gases have been roughly constant over the past half-dozen years. 39 Emissions of methane and nitrous oxide have been roughly constant over the past couple of decades, but there has been an increase in the industrial gases as some are substituted for ozone-destroying substances controlled by the Montreal Protocol. 24

Yet another warming influence on the climate system is black carbon (soot), which consists of fine particles that result mainly from incomplete combustion of fossil fuels and biomass. Long a public health concern, black carbon particles absorb solar radiation during their short life in the atmosphere (days to weeks). When deposited on snow and ice, these particles darken the surface and reduce the reflection of incoming solar radiation back to space. These particles also influence cloud formation in ways yet poorly quantified. 40

Land Use, Forestry, and Agriculture

The main stocks of carbon in its various biological forms (plants and trees, dead wood, litter, soil, and harvested products) are estimated periodically and their rate of change, or flux, is calculated as the average annual difference between two time periods. Estimates of carbon stocks and fluxes for U.S. lands are based on land inventories augmented with data from ecosystem studies and production reports. 41 , 25

U.S. lands were estimated to be a net sink of between approximately 640 and 1,074 million tons CO 2 -e in the late 2000s. 25 , 28 Estimates vary depending on choice of datasets, models, and methodologies (see Ch. 15: Biogeochemical Cycles, “Estimating the U.S. Carbon Sink ,” for more discussion). This net land sink effect is the result of sources (from crop production, livestock production, and grasslands) and sinks (in forests, urban trees, and wetlands). Sources of carbon have been relatively stable over the last two decades, but sinks have been more variable. Long-term trends suggest significant emissions from forest clearing in the early 1900s followed by a sustained period of net uptake from forest regrowth over the last 70 years. 29 The amount of carbon taken up by U.S. land sinks is dominated by forests, which have annually absorbed 7% to 24% (with a best estimate of about 16%) of fossil fuel CO 2 emissions in the U.S. over the past two decades. 23

The persistence of the land sink depends on the relative effects of several interacting factors: recovery from historical land-use change, atmospheric CO 2 and nitrogen deposition, natural disturbances, and the effects of climate variability and change – particularly drought, wildfires, and changes in the length of the growing season. Deforestation continues to cause an annual loss of 877,000 acres (137,000 square miles) of forested land, offset by a larger area gain of new forest of about 1.71 million acres (268,000 square miles) annually. 42 Since most of the new forest is on relatively low-productivity lands of the Intermountain West, and much of the deforestation occurs on high-productivity lands in the East, recent land-use changes have decreased the potential for future carbon storage. 30 The positive effects of increasing carbon dioxide concentration and nitrogen deposition on carbon storage are not likely to be as large as the negative effects of land-use change and disturbances. 31 In some regions, longer growing seasons associated with climate change may increase annual productivity. 43 Droughts and other disturbances, such as fire and insect infestations, have already turned some U.S. land regions from carbon sinks into carbon sources (see Ch. 13: Land Use & Land Cover Change and Ch. 15: Biogeochemical Cycles) . 31 The current land sink may not be sustainable for more than a few more decades, 32 , 33 though there is a lack of consistency in published results about the relative effects of disturbance and other factors on net land-use emissions. 31 , 44 , 45

Section 2: Activities Affecting Emissions

Early and large reductions in global emissions would be necessary to achieve the lower emissions scenarios (such as the lower B1 scenario; see Ch. 2: Our Changing Climate ) analyzed in this assessment. The principal types of national actions that could effect such changes include putting a price on emissions, setting regulations and standards for activities that cause emissions, changing subsidy programs, and direct federal expenditures. Market-based approaches include cap and trade programs that establish markets for trading emissions permits, analogous to the Clean Air Act provisions for sulfur dioxide reductions. None of these price-based measures has been implemented at the national level in the United States, though cap and trade systems are in place in California and in the Northeast’s Regional Greenhouse Gas Initiative. Moreover, a wide range of governmental actions are underway at federal, state, regional, and city levels using other measures, and voluntary efforts, that can reduce the U.S. contribution to total global emissions. Many, if not most of these programs are motivated by other policy objectives – energy, transportation, and air pollution – but some are directed specifically at greenhouse gas emissions, including:

• reduction in CO 2 emissions from energy end-use and infrastructure through the adoption of energy-efficient components and systems – including buildings, vehicles, manufacturing processes, appliances, and electric grid systems;
• reduction of CO 2 emissions from energy supply through the promotion of renewables (such as wind, solar, and bioenergy), nuclear energy, and coal and natural gas electric generation with carbon capture and storage; and
• reduction of emissions of non-CO 2 greenhouse gases and black carbon; for example, by lowering methane emissions from energy and waste, transitioning to climate-friendly alternatives to hydrofluorocarbons (HFCs), cutting methane and nitrous oxide emissions from agriculture, and improving combustion efficiency and means of particulate capture.

Programs underway that reduce carbon dioxide emissions include the promotion of solar, nuclear, and wind power and efficient vehicles.

Federal Actions

The Federal Government has implemented a number of measures that promote energy efficiency, clean technologies, and alternative fuels. 46 , 47 , 48 , 49 , 50 A sample of these actions is provided in Table 27.1 and they include greenhouse gas regulations, other rules and regulations with climate co-benefits, various standards and subsidies, research and development, and federal procurement practices.

The U.S. Environmental Protection Agency (EPA) has a 40-year history of regulating the concentration and deposition of criteria pollutants (six common air pollutants that affect human health). A 2012 Supreme Court decision upheld the EPA’s finding that greenhouse gases “endanger public health and welfare.” 51 This ruling added the regulation of greenhouse gas emissions to the Agency’s authority under the Clean Air Act. Actions taken and proposed under the new authority have focused on road transport and electric power generation.

The U.S. Department of Energy (DOE) provides most of the funding for a broad range of programs for energy research, development, and demonstration. DOE also has the authority to regulate the efficiency of appliances and building codes for manufactured housing. In addition, most of the other federal agencies – including the Departments of Defense, Housing and Urban Development, Transportation, and Agriculture – have programs related to greenhouse gas mitigation.

The Administration’s Climate Action Plan 52 supplements these activities with a broad range of mitigation, adaptation, and preparedness measures. The mitigation elements of the plan are in part a response to the commitment made during the 2010 Cancun Conference of the Parties of the United Nations Framework Convention on Climate Change to reduce U.S. emissions of greenhouse gases by 17% below 2005 levels by 2020. Actions proposed in the Plan include: 1) limiting carbon emissions from both new and existing power plants, 2) continuing to increase the stringency of fuel economy standards for automobiles and trucks, 3) continuing to improve energy efficiency in the buildings sector, 4) reducing the emissions of non-CO 2 greenhouse gases through a variety of measures, 5) increasing federal investments in cleaner, more efficient energy sources for both power and transportation, and 6) identifying new approaches to protect and restore our forests and other critical landscapes, in the presence of a changing climate.

City, State, and Regional Actions

Jurisdiction for greenhouse gases and energy policies is shared between the federal government and the states. 53 For example, states regulate the distribution of electricity and natural gas to consumers, while the Federal Energy Regulatory Commission regulates wholesale sales and transportation of natural gas and electricity. In addition, many states have adopted climate initiatives as well as energy policies that reduce greenhouse gas emissions. For a survey of many of these state activities, see Table 27.2. Many cities are taking similar actions.

The most ambitious state activity is California’s Global Warming Solutions Act (AB 32), a law that sets a state goal to reduce greenhouse gas emissions to 1990 levels by 2020. The state program caps emissions and uses a market-based system of trading in emissions credits (cap and trade), as well as a number of regulatory actions. The most well-known, multi-state effort has been the Regional Greenhouse Gas Initiative (RGGI), formed by ten northeastern and Mid-Atlantic states (though New Jersey exited in 2011). RGGI is a cap and trade system applied to the power sector with revenue from allowance auctions directed to investments in efficiency and renewable energy.

Voluntary Actions

Corporations, individuals, and non-profit organizations have initiated a host of voluntary actions. The following examples give the flavor of the range of efforts:

• The Carbon Disclosure Project has the largest global collection of self-reported climate change and water-use information. The system enables companies to measure, disclose, manage, and share climate change and water-use information. Some 650 U.S. signatories include banks, pension funds, asset managers, insurance companies, and foundations.
• Many local governments are undertaking initiatives to reduce greenhouse gas emissions within and outside of their organizational boundaries. 35 , 36 For example, over 1,055 municipalities from all 50 states have signed the U.S. Mayors Climate Protection Agreement, 34 and many of these communities are actively implementing strategies to reduce their greenhouse gas footprint.
• Under the American College and University Presidents’ Climate Commitment (ACUPCC), 679 institutions have pledged to develop plans to achieve net-neutral climate emissions through a combination of on-campus changes and purchases of emissions reductions elsewhere.
• Voluntary compliance with efficiency standards developed by industry and professional associations, such as the building codes of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), is widespread.
• Federal voluntary programs include Energy STAR, a labeling program that identifies energy efficient products for use in residential homes and commercial buildings and plants, and programs and partnerships devoted to reducing methane emissions from fossil fuel production and landfill sources and high GWP emissions from industrial activities and agricultural conservation programs.

Costs of Emissions Reductions

The national cost of achieving U.S. emissions reductions over time depends on the level of reduction sought and the particular measures employed. Studies of price-based policies, such as a cap and trade system, indicate that a 50% reduction in emissions by 2050 could be achieved at a cost of a year or two of projected growth in gross domestic product over the period (for example, Paltsev et al. 2009; EIA 2009 54 , 55 ). However, because of differences in analysis method, and in assumptions about economic growth and technology change, cost projections vary considerably even for a policy applying price penalties. 56 Comparisons of emissions reduction by prices versus regulations show that a regulatory approach can cost substantially more than a price-based policy. 57 , 58

Co-Benefits for Air Pollution and Human Health

Actions to reduce greenhouse gas emissions can yield co-benefits for objectives apart from climate change, such as energy security, health, ecosystem services, and biodiversity. 59 , 60 The co-benefits for reductions in air pollution have received particular attention. Because air pollutants and greenhouse gases share common sources, particularly from fossil fuel combustion, actions to reduce greenhouse gas emissions also reduce air pollutants. While some greenhouse gas reduction measures might increase other emissions, broad programs to reduce greenhouse gases across an economy or a sector can reduce air pollutants markedly. 13 , 61 (Unfortunately for climate mitigation, cutting sulfur dioxide pollution from coal burning also reduces the cooling influence of reflective particles formed from these emissions in the atmosphere. 62 )

There is significant interest in quantifying the air pollution and human health co-benefits of greenhouse gas mitigation, particularly from the public health community, 60 , 63 as the human health benefits can be immediate and local, in contrast to the long-term and widespread effects of climate change. 64 Many studies have found that monetized health and pollution control benefits can be of similar magnitude to abatement costs (for example, Nemet et al. 2010; Burtraw et al. 2003 64 , 65 ). Methane reductions have also been shown to generate health benefits from reduced ozone. 66 Similarly, in developing nations, reducing black carbon from household cook stoves substantially reduces air pollution-related illness and death. 67 , 68 , 69 Ancillary health benefits in developing countries typically exceed those in developed countries for a variety of reasons. 64 But only in very few cases are these ancillary benefits considered in analyses of climate mitigation policies.

Section 3: Preparation for Potential Future Mitigation Action

To meet the emissions reduction in the lower (B1) scenario used in this assessment (Ch. 2: Our Changing Climate ) under reasonable assumptions about managing costs, annual global CO 2 emissions would need to peak at around 44 billion tons within the next 25 years or so and decline steadily for the rest of the century. At the current rate of emissions growth, the world is on a path to exceed the 44 billion ton level within a decade (see “Emissions Scenarios and RCPs”). Thus achievement of a global emissions path consistent with the B1 scenario will require strenuous action by all major emitters.

Policies already enacted and other factors lowered U.S. emissions in recent years. The Annual Energy Outlook prepared by the EIA, which previously forecasted sustained growth in emissions, projected in 2013 that energy-related U.S. CO 2 emissions would remain roughly constant for the next 25 years. 39 Moreover, through the President’s Climate Action Plan, the Administration has committed to additional measures not yet reflected in the EIA’s projections, with the goal of reducing emissions about 17% below 2005 levels by 2020. Still, additional and stronger U.S. action, as well as strong action by other major emitters, will be needed to meet the long-term global emission reductions reflected in the B1 scenario.

Achieving the B1 emissions path would require substantial decarbonization of the global economy by the end of this century, implying a fundamental transformation of the global energy system. Details of the energy mix along the way differ among analyses, but the implied involvement by the U.S. can be seen in studies carried out under the U.S. Climate Change Science Program 20 and the Energy Modeling Forum. 70 , 71 , 72 , 73 In these studies, direct burning of coal without carbon capture is essentially excluded from the power system, and the same holds for natural gas toward the end of the century – to be replaced by some combination of coal or gas with carbon capture and storage, nuclear generation, and renewables. Biofuels and electricity are projected to substitute for oil in the transport sector. A substantial component of the task is accomplished with demand reduction, through efficiency improvement, conservation, and shifting to an economy less dependent on energy services.

Emissions Scenarios and RCPs

The Representative Concentration Pathways (RCPs) specify alternative limits to human influence on the Earth’s energy balance, stated in watts per square meter (W/m 2 ) of the Earth’s surface. 12 , 74 The A2 emissions scenario implies atmospheric concentrations with radiative forcing slightly lower than the highest RCP, which is 8.5 W/m 2 . The lower limits, at 6.0, 4.5 and 2.6 W/m 2 , imply ever-greater mitigation efforts. The B1 scenario (rapid emissions reduction) is close to the 4.5 W/m 2 RCP 19 and to a similar case (Level 2) analyzed in a previous federal study. 20 Those assessments find that, to limit the economic costs, annual global CO 2 emissions from fossil fuels and industrial sources like cement manufacture, need to peak by 2035 to 2040 at around 44 billion tons of CO 2 , and decline thereafter. The scale of the task can be seen in the fact that these global emissions were already at 34 billion tons CO 2 in 2011, and over the previous decade they rose at around 0.92 billion tons of CO 2 per year. 1 , 2 The lowest RCP would require an even more rapid turnaround and negative net emissions – that is, removing more CO 2 from the air than is emitted globally – in this century. 74

The challenge is great enough even starting today, but delay by any of the major emitters makes meeting any such target even more difficult and may rule out some of the more ambitious goals. 20 , 70 A study of the climate change threat and potential responses by the U.S. National Academies therefore concludes that there is “an urgent need for U.S. action to reduce greenhouse emissions.” 75 The National Research Council (NRC) goes on to suggest alternative national-level strategies that might be followed, including an economy-wide system of prices on greenhouse gas emissions and a portfolio of possible regulatory measures and subsidies. Deciding these matters will be a continuing task, and U.S. Administrations and Congress face a long series of choices about whether to take additional mitigation actions and how best to do it. Two supporting activities will help guide this process: opening future technological options and development of ever-more-useful assessments of the cost effectiveness and benefits of policy choices.

Many technologies are potentially available to accomplish emissions reduction. They include ways to increase the efficiency of fossil energy use and facilitate a shift to low-carbon energy sources, sources of improvement in the cost and performance of renewables (for example, wind, solar, and bioenergy) and nuclear energy, ways to reduce the cost of carbon capture and storage, means to expand terrestrial sinks through management of forests and soils and increased agricultural productivity, 76 and phasing down HFCs. In addition to the research and development carried out by private sector firms with their own funds, the Federal Government traditionally supports major programs to advance these technologies. This support is accomplished in part by credits and deductions in the tax code, and in part by federal expenditure. For example, the 2012 federal budget devoted approximately $6 billion to clean energy technologies. 77 Success in these ventures, lowering the cost of greenhouse gas reduction, can make a crucial contribution to future policy choices. 53

Because they are in various stages of market maturity, the costs and effectiveness of many of these technologies remain uncertain: continuing study of their performance is important to understanding their role in future mitigation decisions. 78 , 79 In addition, evaluation of broad policies and particular mitigation measures requires frameworks that combine information from a range of disciplines. Study of mitigation in the near future can be done with energy-economic models that do not assume large changes in the mix of technologies or changes in the structure of the economy. Analysis over the time spans relevant to stabilization of greenhouse gas concentrations, however, requires Integrated Assessment Models, which consider all emissions drivers and policy measures that affect them, and that take account of how they are related to the larger economy and features of the climate system. 20 , 70 , 80 , 81 , 82 This type of analysis is also useful for exploring the relations between mitigation and measures to adapt to a changing climate.

Interactions Between Adaptation and Mitigation

There are various ways in which mitigation efforts and adaptation measures are interdependent (see Ch. 28: Adaptation ). For example, the use of plant material as a substitute for petroleum-based transportation fuels or directly as a substitute for burning coal or gas for electricity generation has received substantial attention. 83 But land used for mitigation purposes is potentially not available for food production, even as the global demand for agricultural products continues to rise. 84 , 85 , 86 Conversely, land required for adaptation strategies, like setting aside wildlife corridors or expanding the extent of conservation areas, is potentially not available for mitigation involving the use of plant material, or active management practices to enhance carbon storage in vegetation or soils. These possible interactions are poorly understood but potentially important, especially as climate change itself affects vegetation and ecosystem productivity and carbon storage. Increasing agricultural productivity to adapt to climate change can also serve to mitigate climate change.

Continued development of these analytical capabilities can help support decisions about national mitigation and the U.S. position in international negotiations. In addition, as shown above, mitigation is being undertaken by individuals and firms as well as by city, state, and regional governments. The capacity for mitigation from individual and household behavioral changes, such as increasing energy end-use efficiency with available technology, is known to be large. 87 Although there is capacity, there is not always broad acceptance of those behavioral changes, nor is there sufficient understanding of how to design programs to encourage such changes. 88 Behavioral and institutional research on how such choices are made and the results evaluated would be extremely beneficial. For many of these efforts, understanding of cost and effectiveness is limited, as is understanding of aspects of public support and institutional performance; so additional support for studies of these activities is needed to ensure that resources are efficiently employed.

Section 4: Research Needs

• Engineering and scientific research is needed on the development of cost-effective energy use technologies (devices, systems, and control strategies) and energy supply technologies that produce little or no CO 2 or other greenhouse gases.
• Better understanding of the relationship between emissions and atmospheric greenhouse gas concentrations is needed to more accurately predict how the atmosphere and climate system will respond to mitigation measures.
• processes controlling the land sink of carbon in the U.S. require additional research, including better monitoring and analysis of economic decision-making about the fate of land and how it is managed, as well as the inherent ecological processes and how they respond to the climate system.
• Uncertainties in model-based projections of greenhouse gas emissions and of the effectiveness and costs of policy measures need to be better quantified. Exploration is needed of the effects of different model structures, assumptions about model parameter values, and uncertainties in input data.
• Social and behavioral science research is needed to inform the design of mitigation measures for maximum participation and to prepare a consistent framework for assessing cost effectiveness and benefits of both voluntary mitigation efforts and regulatory and subsidy programs.

Table 27.1: Sample Federal Mitigation Measures

Table 27.1: A number of existing federal laws and regulations target ways to reduce future climate change by decreasing greenhouse gas emissions emitted by human activities.

Table 27.2: State Climate and Energy Initiatives

State climate and energy initiatives.

Most states and native communities have implemented programs to reduce greenhouse gases or adopt increased energy efficiency goals. Examples of greenhouse gas policies include:

• Greenhouse Gas Reporting and Registries http://www.c2es.org/us-states-regions/policy-maps/ghg-reporting 89
• Greenhouse Gas Emissions Targets http://www.c2es.org/us-states-regions/policy-maps/emissions-targets 90
• CO 2 Controls on Electric Power plants http://www.edf.org/sites/default/files/state-ghg-standards-03132012.pdf 91
• Low-Carbon Fuel Standards http://www.c2es.org/us-states-regions/policy-maps/low-carbon-fuel-standard 92
• Climate Action Plans http://www.c2es.org/us-states-regions/policy-maps/action-plan 93
• Cap and Trade Programs http://arb.ca.gov/cc/capandtrade/capandtrade.htm 94
• Regional Agreements http://www.c2es.org/us-states-regions/regional-climate-initiatives#WCI 95
• Tribal Communities http://www.epa.gov/statelocalclimate/tribal 96

Also, states have taken a number of energy measures, motivated in part by greenhouse gas concerns. For example:

• Renewable Portfolio Standards http://www.dsireusa.org/documents/summarymaps/RPS_map.pdf 97
• Energy Efficiency Resource Standards http://www.dsireusa.org/documents/summarymaps/EERS_map.pdf 98
• Property Tax Incentives for Renewables http://www.dsireusa.org/documents/summarymaps/ 99

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• Perspective
• Published: 11 November 2021

The cost of mitigation revisited

• Alexandre C. Köberle   ORCID: orcid.org/0000-0003-0328-4750 1 ,
• Toon Vandyck   ORCID: orcid.org/0000-0001-5927-0310 2 ,
• Celine Guivarch   ORCID: orcid.org/0000-0002-9405-256X 3 ,
• Nick Macaluso 4 ,
• Valentina Bosetti   ORCID: orcid.org/0000-0003-4970-0027 5 , 6 ,
• Ajay Gambhir   ORCID: orcid.org/0000-0002-5079-4537 1 ,
• Massimo Tavoni 6 , 7 &
• Joeri Rogelj   ORCID: orcid.org/0000-0003-2056-9061 1 , 8  

Nature Climate Change volume  11 ,  pages 1035–1045 ( 2021 ) Cite this article

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• Climate-change mitigation

A Publisher Correction to this article was published on 29 November 2021

This article has been updated

Estimates of economic implications of climate policy are important inputs into policy-making. Despite care to contextualize quantitative assessments of mitigation costs, one strong view outside academic climate economics is that achieving Paris Agreement goals implies sizable macroeconomic losses. Here, we argue that this notion results from unwarranted simplification or omission of the complexities of quantifying mitigation costs, which generates ambiguity in communication and interpretation. We synthesize key factors influencing mitigation cost estimates to guide interpretation of estimates, for example from the Intergovernmental Panel on Climate Change, and suggest ways to improve the underlying models. We propose alternatives for the scenario design framework, the framing of mitigation costs and the methods used to derive them, to better inform public debate and policy.

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The United Nations Framework Convention on Climate Change states that “policies and measures to deal with climate change should be cost effective to ensure global benefits at the lowest possible costs” 1 . Correspondingly, the government-approved outlines of Intergovernmental Panel on Climate Change (IPCC) reports often explicitly indicate that the macroeconomic costs of mitigation should be assessed. For example, the outline for the upcoming Sixth Assessment Report (AR6) requests that authors assess “Economics of mitigation and development pathways, including mitigation costs” 2 , reflecting concerns about the costs of climate policy. This concern is mirrored in national policy documents such as the 2007 Stern Review 3 , and more recently from the USA 4 , the UK 5 and the European Union 6 .

For decades now, the IPCC has been tasked with assessing the literature on macroeconomic costs of mitigating climate change and has responded by publishing both estimates of, and the limitations inherent in, long-term macroeconomic projections 7 , 8 (Fig. 1 and Supplementary Section 1 ). Making such estimates is a complex undertaking that, although rooted in economics, requires consideration of elements from engineering, political science and sociology. It is not surprising that these complexities have led to misunderstandings and controversy. For example, numerical estimates of the costs of climate mitigation reported in the IPCC’s Fifth Assessment Report (AR5) have elicited reactions ranging from “their bills have become enormous” 9 to “salvation gets cheap” 10 . Relevant stakeholders, especially those more at risk from a transition to a low-carbon economy, have emphasized the interpretation that efforts to mitigate climate change will lead to substantial macroeconomic losses. This emphasis may have succeeded despite the cautious framing of the estimates in IPCC reports, especially in AR5. The caveats, clearly stated in the report, caution against taking these estimates at face value, but they risk getting lost when these numbers are used in the general audience discourse.

Each successive IPCC report synthesizes the main messages emerging from recent developments in the underlying scenarios literature. *Instead of mitigation, ‘limitation’ was the term used in the early days of the IPCC to refer to reduction of GHG emissions. CoM, cost of mitigation; NRP, no-regret potential; CP, climate policies.

So that this discourse can become more critically informed by the underlying facts, we here review the process of developing and interpreting mitigation cost estimates and unpack key elements that form the basis for their estimation. Earlier IPCC Assessment Reports explored costs of mitigation more theoretically, but their treatment has gradually shifted towards a more quantitative basis (Fig. 1 ). Scenario quantification with models such as integrated assessment models (IAMs) has been part of IPCC assessment reports since the beginning 11 (Box 1 ).

Currently, climate mitigation scenarios do not consider important determinants of net costs. In this Perspective, we discuss missing elements, highlighting the uncertainties involved and the ambiguities in the size and sign of the changes resulting from these deficiencies. We also illustrate opportunities for an improved presentation of mitigation costs that may help size opportunities for social, environmental and economic benefits beyond those from direct climate mitigation.

Box 1 Estimating costs through models

The IPCC’s SAR emphasized that modelling studies provide insights, such as identifying low-cost opportunities, that are more important than the “specific numerical results of any one analysis” 7 . It highlighted that what matters are net costs, that is, the difference between the required expenditures and the accrued benefits from the structural changes implied in a transition. Subsequent reports have taken an increasingly quantitative approach (Supplementary Section 1 ). This evolution comes with the increased importance of a proper framing of numerical estimates.

Understanding critical debates about mitigation costs requires clear definition of what is meant by costs 7 (Supplementary Section 2 ). Four types of cost concept exist in the climate mitigation literature: technical, sectoral, macroeconomic and welfare costs. These types of cost are not comparable or equivalent. Technical or engineering costs represent the difference in cost between incumbent and new technologies; sectoral costs represent the transition cost for a full sector, say the transport sector, without accounting for broader effects in the rest of the economy; macroeconomic costs are typically measured as a reduction in GDP and welfare costs may account for factors such as distribution of income, environmental degradation or health outcomes. Different models can provide estimates of different types of cost, depending on their structures. Paltsev and Capros 136 identify cost concepts often used in modelling studies as change in GDP, change in consumption, change in welfare, energy system cost and area under the marginal abatement cost curve. In AR5, the deliberate choice of the consumption loss metric to report estimates of mitigation costs ensured comparability between model outputs. However, this diversity of cost concepts in the IAM literature can lead to inadvertent comparison of inequivalent quantities.

Independently of the metric adopted, costs can be calculated for scenarios that represent varying degrees of ideality in the conditions surrounding the transition. Structural changes resulting from disorderly mitigation actions may lead to transition risks 137 that would unavoidably add to the cost of mitigation. Recent literature explores concerns over how transition costs are distributed across time, regions and societies 138 , 139 , 140 . Such concerns are evident in government reviews of climate policy 141 , and an assessment of the new literature will be presented in the IPCC’s forthcoming AR6.

To explore low-carbon transitions, researchers employ mathematical tools to produce numerical pathways integrating the economy, energy, climate and land-use sectors. These range from bottom-up energy system models to computable general equilibrium models to agent-based models. For simplicity, we will use the term IAMs 11 here to label this heterogeneous set of tools. Although IAMs vary widely in their structure and behaviour 11 , 82 , the majority of IAMs have traditionally represented the results of policies in an idealized economy with perfectly functioning markets (market clearing and profit or individual utility maximization). In this Perspective we focus on detailed-process IAMs as opposed to cost–benefit IAMs 11 (Supplementary Section 3 ), since the former are most commonly used in IPCC assessments and the estimates we discuss here typically originate from such models.

Estimates of the costs of public policies must be measured against some reference scenario that does not include the policies in question—that is, they are calculated as the difference between a counterfactual world without climate policy and one where climate policies and the related production, consumption and investment choices take place 12 . This counterfactual—interchangeably referred to as baseline, reference, benchmark or business as usual—has long been identified as a key determinant for the magnitude and even sign of estimated costs of mitigation scenarios (for example, see the Second Assessment Report (SAR) 7 ). Therefore, defining a realistic reference is essential to contextualize estimates of the cost of climate policy scenarios appropriately. As already recognized by Grant et al. 12 , several countries are likely to remain in a paradigm where they will need to keep reassessing the economy-wide cost of mitigation to different emission levels, for example as they seek to ratchet their NDCs to the Paris Agreement. Currently, these reference scenarios do not consider important determinants of net costs 12 .

Costs of a changing climate

Perhaps the most important omission from estimates of economic impacts of mitigation is that calculated costs do not include impacts from climate change itself, and the associated economic benefits of avoided impacts 11 , 12 , 13 , 14 . That is, reported estimates represent the gross costs of mitigation. Impacts include loss of agricultural productivity 15 , heat-induced mortality and morbidity 16 , 17 and loss of labour productivity 18 , 19 , infrastructure losses from extreme events and sea-level rise 20 , biodiversity losses 21 and many others 22 . Climate stress also has a complex relationship with migration and related geopolitical instability 23 and with financial instability 24 , 25 . The omission of impacts from estimates of economic costs of mitigation reflects the historical structure of the IPCC, with mitigation benefits (that is, avoided impacts) and mitigation costs featured in different so-called Working Groups II and III. However, this separation has created room for scholars and policy-makers to focus only on the cost side of mitigation, ignoring the benefits 26 , 27 , 28 , 29 , 30 . Moreover, this separation also results in unrealistic reference scenarios that ignore climate damage.

The challenge of estimating the aggregate economic effects of the physical impacts of climate change lies in a dearth of data, high uncertainties in regional climate change and the controversial or impossible nature of assigning costs to human lives, biodiversity or cultural heritage. We do not assess these complex aspects here in detail. However, studies that also include economic impacts of climate change in detailed-process-based IAMs are emerging in the literature 31 , 32 , 33 , but robust comprehensive estimates are not available. Bringing new elements such as non-market damages 34 into the analysis adds further value to avoiding damages, but also adds sources of uncertainty to the overall outcome. Continuing use of no-impact baselines in most studies and assessments is therefore likely. Still, refining the granularity of climate impacts, and bridging results of bottom-up approaches (for example, ref. 35 ), which start from detailed biophysical impact modules, and econometric top-down methods 36 provide fruitful avenues for future research 37 .

While methodological improvements in estimating economic impacts of climate change are welcome, available literature already indicates that structural uncertainty about damages and the risk of tipping points warrant ambitious climate action 38 , 39 . Furthermore, climate change poses serious risks to economic and geopolitical stability, via, for example, risk transmission channels in the financial 24 , 25 , 40 , 41 and agricultural 42 , 43 sectors. Finally, climate change increases the risks of extreme events at the ‘tail end’ of distributions—low-probability but high-impact events potentially causing catastrophic and irreversible damage 38 , 44 . However, the high uncertainty attached to the economic implications of such events 38 means that including them in numerical cost estimates may further obscure rather than clarify policy options. Still, the avoided impacts resulting from mitigation must be present in the framing of the economic impacts of climate policy, and the social cost of carbon remains an important concept, particularly when political commitment is uncertain 45 , 46 .

Crucially, estimating costs of mitigation by comparing against a hypothetical reference without climate impacts provides a skewed image to policy-makers and stakeholders. A more relevant question might be how to implement mitigation in a way that is compatible with improving human welfare or promoting sustainable development. One way to abstract from climate change impacts in the discussion on mitigation pathways is to explore sets of scenarios that achieve similar cumulative emissions, as this would compare scenarios with similar climate impacts. Such temperature-clustered scenarios could differ in how they achieve their climate goals (timing, technology and instrument choices), and would therefore provide insight into the corresponding costs and how they are distributed across society. Although IAMs routinely produce these types of scenario (see, for example, ref. 47 or the illustrative scenarios in the IPCC 1.5 °C report 48 ), currently the macroeconomic costs of mitigation are calculated by comparing mitigation scenarios with a baseline with very different temperature outcomes. While climate impact variability is reduced across temperature-clustered scenarios, it is not necessarily eliminated altogether. Temperature overshoot may imply strong impacts, particularly when thresholds for tipping points are crossed. For this, recent literature 49 can guide design of temperature-clustered scenario ensembles. Furthermore, how climate policy itself is implemented may influence impacts of global warming by affecting the capacity of vulnerable socioeconomic groups and regions to adapt to changing climate conditions. This should be acknowledged in future work, for instance by revealing the economic impacts for heterogeneous agents and regions in the world 50 , 51 .

Minor losses to a wealthier world

A common instinctive reaction of an untrained reader to the estimates of numerical losses is that mitigation leads to a reduction in economic output and is not worth the cost. However, when presented differently, mitigation scenarios can highlight that decarbonizing the economy is understood to happen alongside persistent growth of per capita income over time. This key perspective of the economic impacts of climate change mitigation points to a communication opportunity for the upcoming IPCC AR6. We illustrate this in Fig. 2 . At the basis of mitigation cost estimates typically lie annual global consumption (and gross domestic product, GDP) growth rates between 1% and 4% throughout the century (for example, Shared Socioeconomic Pathway 2 (SSP2) projections in ref. 52 ). As such, the consumption losses reported in AR5 represent a small reduction in wealth over the entire century, when considered in the context of a reference in which consumption “grows anywhere from 300% to more than 900% over the century” 53 . As is clearly explained in the AR5 text, the median annualized reduction in the growth rate of consumption is only 0.06 percentage points (0.04 to 0.14) compared with consumption that grows between 1.6% and 3% per year in the baseline 53 . The order of magnitude of this cost estimate arguably represents a negligible number when put in the perspective of economic growth over the century and the corresponding uncertainties involved in projecting long-term economic activity (Fig. 2a ). This presentation of the economic impacts of mitigation could be reinforced in future estimates (including IPCC reports), emphasizing that steady economic progress is consistent with reaching the climate goals of the Paris Agreement, and that comparable levels of per capita income can be obtained while enhancing the economy’s carbon efficiency by a factor of five (Fig. 2b ). Furthermore, highlighting channels that can bring economic gains of climate policy in key figures and headline statements in the report would provide a more balanced representation of the economics of mitigation.

a , Consumption growth variation across baselines, models and mitigation scenarios. The green bar indicates the results range of the WITCH-GLOBIOM model. The grey wedge is the range of consumption growth across all SSP baselines from the SSP database. b , Producing more (GDP) with less (GHG emissions). Model results from four IAMs with endogenous GDP estimation for scenarios that combine middle-of-the-road socioeconomic assumptions (SSP2) with five different levels of climate change mitigation stringency. Thin black lines in b indicate GDP per capita mitigation frontiers for milestone years for each model. Perfectly vertical lines would indicate no reduction in GDP per capita. Negative slopes indicate decreasing GDP per capita with growing mitigation effort. See Supplementary Section 4 for variations of b using other SSP scenarios. Data source: SSP database 135 .

What is not evident in the panels in Fig. 2 is how this growing wealth, as well as the mitigation costs, are distributed across geographies, income classes and socioeconomic groups. In fact, moderate GDP changes hide deep transformations in economic structures that may lead to regionally and sectorally differentiated economic decline or prosperity 8 , 54 , 55 . Mitigation creates new low-carbon value chains (‘sunrise’ industries) and phases out old carbon-intensive industries and occupations (‘sunset’ industries). For example, levels of stranded fossil fuel assets will vary by region and by commodity 56 , with the lowest-cost producers potentially gaining or maintaining market share while higher-cost producers see sunset industries diminish or disappear completely 57 . While there is potential for well-designed policy to reduce undesired effects of mitigation, ill-designed transitions can cause rapid repricing of assets and economic uncertainty, raising the risks of financial instability 25 and social unrest 58 . For instance, coal phase-out raises acute issues of just transition for coal-dependent communities 59 , 60 . Similarly, the avoided climate damage would be different across geographies and income classes. Climate action can potentially benefit vulnerable households that may be disproportionally impacted by climate change, if mitigation policies and complementary measures seek to strengthen the resilience of low-income households, reduce energy poverty and enhance social protection simultaneously 61 , 62 . Failing to do so would further exacerbate the challenges to adapt to climate change for vulnerable socioeconomic groups and regions 63 . Moreover, emission taxation has important distributive effects 64 . Revenues from emission taxation can be used to lessen its regressive distributional impacts or even turn the policy into a progressive policy, reducing inequality or improving wellbeing of lower-income households 65 , 66 , 67 , 68 .

In addition to highlighting the small relative consumption losses overall, IPCC assessments could put more emphasis on distributional issues of climate policies and corresponding complementary policy measures that ensure an equitable transition to a low-carbon economy. Regional cost estimates are presented in AR5 Chapter 6 (ref. 8 ) but, due to political sensitivity, were excluded from the Summary for Policymakers. Scenarios exploring how to mitigate distributional inequities could help increase ambition in the revised nationally determined contributions (NDCs). Furthermore, clearly acknowledging the caveats of GDP as a mitigation cost metric, and reporting broader and additional welfare metrics such as distribution of income, will enable a science-based societal debate and the design of appropriate complementary measures to ensure a fair transition.

Imperfections define reality

Climate action in line with the Paris Agreement will require structural changes to the economy 69 , 70 , 71 . Rather than isolated climate policies, this deep transition will need to be supported by policy packages containing sector-specific instruments, which can, and arguably should, be designed in coordinated ways that enhance cross-sectoral synergies and minimize trade-offs. Such packages can concomitantly reduce emissions and improve economic efficiency by enhancing policy coordination across sectors and geographies, lifting information barriers and removing incumbent power, ensuring a stable climate for long-run investments through credible government signals or enabling innovators to be rewarded for socialized benefits of their investments. A broad-based policy package approach can help accelerate the transition to meet ambitious societal objectives 72 , 73 , 74 . This transition also probably requires a full quiver of fiscal, financial and monetary policy instruments to be deployed to enable a favourable financial environment to unlock required investments across geographies and sectors 75 . It stands to reason then that such far-reaching policy packages should be aimed at also removing existing inefficiencies by including pro-development measures that ensure broader human welfare gains.

The reference scenario against which the costs of climate action are calculated by design reflects the assumptions and concepts underlying the modelling approach with which it was created. Currently, models that assume well-functioning economic systems dominate the literature (although there are notable exceptions 76 , 77 , 78 , 79 , 80 , 81 ). Assumptions of such ‘first-best’ or idealized economies often include that agents make rational choices under perfect information, markets operate under perfect competition (no market power) and goods, capital and workers move across sectors of the economy without transaction costs 11 , 82 . Clearly, this represents an overly stylized view of the real-world economy, which is characterized by biases and imperfections in information, competition and access to capital 83 , as well as by limitations to the flow of goods, capital 76 and labour, across regions, sectors and social classes. Such imperfections are often referred to as market failures 84 , 85 , 86 .

These imperfections imply that resources are allocated in suboptimal ways by the economy. This keeps the economy from operating at its production frontier and may lead to a misallocation of capital from its most productive uses as well as persistent unemployment. However, typically, these market failures are not explicitly represented in studies estimating the macroeconomic costs of climate policy. When limits on greenhouse gas (GHG) emissions are introduced into such an idealized reference economy, model simulations will invariably result in economic losses. The constraint restricts the choice set of economic agents (for example, no fossil fuel use in a production process) and the benefits of mitigation are not accounted for. Hence, models that take a simplified first-best economy—without distortions, imperfections and market failures—as a starting point of their analysis tend to limit the potential range of outcomes at both ends. On the one hand, such models exclude the economic gains that would result from correcting the market failures and imperfections. On the other, they do not include the economic losses that would arise if the climate transition did not resolve economic inefficiencies, or even exacerbated them by, for example, further concentrating market power. In this sense, the current estimates span a narrow range of economic outcomes, which will depend on the way in which climate policies are implemented. Capturing and quantifying a broad set of behavioural imperfections and market failures, however, is a daunting task, while a stylized or simplified representation of the economy makes it possible to model the transformation and to explain the results transparently. More research effort is needed to explore the size and sign of the change in economic activity that results from including second-best elements in a modelling framework.

Useful policy insights can be provided by including such channels in models and scenarios, which are useful tools with which to explore the interlinkages and ramifications of policy packages. Overlooking these opportunities in models that intend to inform policies may come at the risk of mitigation cost estimates that are biased high, and potentially diminishing both societal support for strong climate action and the identification of win–win opportunities. Conversely, it can also highlight transition assistance costs that add to the mitigation burden. Reskilling workers, reindustrializing states that lose their vital fossil fuel revenues and other such policies will take coordinated effort and additional resources.

Comparing with appropriate benchmarks

A no-climate policy world does not exist, and assuming away all existing policies is neither trivial nor desirable. A reference that ignores already adopted climate policies artificially inflates the divergence with ambitious pathways 12 , 87 , 88 , driving up the mitigation cost. Recent research 88 , 89 shows that current policies are compatible with global temperature increases that are lower than projected warming in scenarios that neglect any existing climate policy measures. Starting from a reference scenario that represents a plausible future emission pathway, including technological progress and climate impacts, is a first step in ensuring mitigation cost estimates are realistic. The next step is designing a reference scenario accounting for economic imperfections that can be potentially resolved with smart climate policy packages.

When imperfections and multiple externalities are introduced in a model-based assessment and the implications studied explicitly (a situation referred to as a ‘second-best’ setting), well-designed policy interventions could enhance economic efficiency and generate positive economic impacts 90 . We next explore some of the relevant mechanisms by which this can be done. However, including real-world features does not automatically imply that mitigation costs will be lower. Accounting for some types of market failure in models may actually work in the opposite direction, since some mechanisms may raise estimates of the costs of climate action, as is the case of potential short- to medium-run frictions in the transition to a low-carbon economy. For example, frictions to reallocation of workers from one sector to another or other rigidities in labour markets have been found to increase cost estimates if left unresolved 77 , 91 . Conversely, by explicitly including such dynamics, it becomes possible to assess how specific compensatory policies can alleviate these burdens 58 , 79 , 91 , 92 , 93 .

Capturing real-world features

Explicitly modelling the key channels affecting the cost of mitigation will improve our understanding of the implications of any effective set of climate policy measures. We identify and review five categories of institutional or behavioural imperfections, instances in which the idealized world view often adopted in modelling exercises (first best) behaves markedly and often persistently differently from reality (second best). These categories include co-benefits, behavioural imperfections, knowledge spillovers, investment and finance, and pre-existing distortions (we summarize the categories here and provide a detailed discussion in Supplementary Section 5 ).

In addition to avoided climate impacts, well-designed climate policies can result in co-benefits such as reduced air pollution. These synergies and co-benefits may offset costs and potentially deliver net benefits (no-regret potentials in SAR 7 ). Moreover, they are desirable from a welfare standpoint and should be considered in drafting and evaluation of policy measures, whether in monetized form 94 , 95 or not: for example, simply as health outcomes 96 , 97 , 98 .

Humans often behave in ways detrimental to our health, wellbeing and purses, outright irrationally in some instances and boundedly rationally in others. For example, food and energy consumption may deviate from the optimum for welfare maximization due to habit formation and myopic views. A first-best reference based on rational behaviour implies optimal decision-making for energy and health, leaving no margin for welfare gains from climate policies that spur energy efficiency or nudge towards healthier diets. However, it is challenging to steer decisions towards energy efficiency and healthy diets, mitigation options typically considered very cheap in IAMs. Importantly, bringing this kind of behavioural bias into the analysis has implications for the optimal mix of policy instruments 99 . As many existing models and scenarios rely on (implicit) carbon pricing as the primary policy lever, they do not represent the opportunities of alternative instruments explicitly.

First-best references also imply optimal research and development investment levels to produce innovation in new technologies and market design. However, innovators may not fully capture the benefits of their innovation, since knowledge spillovers allow other agents to benefit from the new knowledge and capture some of the benefits (known as positive externalities). Second-best reference scenarios may imply low research and development, providing an opportunity for climate policy packages to address this imperfection through incentives.

On finance and investment, first-best references or scenarios that assume optimal allocation of resources at all times are ill equipped to explore policies that address capital underallocation, a situation in which we are currently living 100 , 101 , 102 as indicated by negative interest rates. This was true even before COVID-19 and is relevant for stimulus package discussions. Some models operate under equilibrium paradigms, which limit annual investments to the amount of savings available each year. In reality, fiscal and monetary policies such as quantitative easing aimed to stimulate the economy inject cash beyond available savings and increase available funds for debt financing through loans 103 , 104 . In times of low growth, low interest rates and apparent underinvestment, taxing carbon emissions rather than capital can increase economic efficiency 105 .

Finally, pre-existing distortions are often the result of inefficient taxation, and some constituencies with particularly inefficient tax systems can leverage climate policy to deliver ‘double dividends’ 106 , 107 and improve economic performance by using revenues from carbon taxation to, for example, remove labour market imperfections by lowering labour taxes 79 or raising the efficiency of other types of tax (see Supplementary Section 7 for a discussion on the European Union’s energy excise tax reform).

The assessment of policy design results from the ability to compare costs and benefits—and how they are distributed across sectors, households and regions—between scenarios that differ in terms of instrument choice, policy coverage and speed of implementation. An encompassing approach to climate policy may provide the leverage and momentum to address some of these imperfections through institutional reform and broad policy packages. Studies that start from a second-best situation explicitly incorporating these channels can identify positive economic outcomes and inform policy design. In addition, these mechanisms affect GDP through total factor productivity (TFP). TFP is an exogenous input to many models because endogenizing it involves complexities and uncertainties, but doing so can provide policy-relevant insights (Box 2 ).

Although we do not enter into a detailed discussion here, shortcomings of GDP as a metric for progress have widely been acknowledged (including in AR5 54 ), along with potential alternatives 108 , 109 , 110 . Recent work suggests that decreasing consumption 111 , such as reductions in final energy demand 112 and food waste 113 , can form an integral part of the climate solution with desirable features from a societal point of view. The narrower concept of economic activity is still used as a measure of impact in policy documents, such as the UK Climate Change Commission’s report on reaching net zero 5 . While economic growth and the associated living standards and fiscal revenues remain important, there are other considerations that should weigh in on policy assessment. As noted, GDP is a poor metric for welfare, and the underlying structure of the economic flows that make up GDP should be unpacked and assessed for their desirability or alignment with broader policy objectives. Although there are tensions between the concepts of green growth and degrowth, there are also synergies 114 , suggesting that climate action can benefit from wider-scope policies 115 . When extending the concept of GDP to properly account for the environment, evidence from the USA suggests that environmental regulation brings macroeconomic benefits, not costs 116 , 117 . Recent evidence from Europe indicates that the direct link between air pollution and GDP growth may be larger than thought previously 118 . Conversely, GDP is sometimes linked to welfare-reducing activities, creating opportunities to decouple GDP from resource use and GHG emissions 119 .

Box 2 Endogenizing TFP

An important driver of economic growth is TFP growth. TFP is measured as the ratio of aggregate output (GDP) to inputs such as labour ( L ) and capital ( K ) (the production factors). TFP growth is factor neutral, that is, it increases the productivity of labour and capital (and other factors of production, such as human capital) in proportional ways. Examples of factors driving TFP growth are technological change and innovation (for example, information and communications technology), education and human capital, and quality of institutions.

Input factors and their productivity are impacted by climate change in different ways, intermediated by the role of behaviour, policy, markets and many other factors. Arguably, the radical structural changes to the economy required to achieve climate neutrality (as well as the radical changes brought about by climate impacts in those scenarios) will affect productivity of specific and generic factors. In particular, innovation and the introduction of new, more efficient, products and processes will affect TFP, possibly leading to higher aggregate output from the same level of inputs, or direct innovation towards certain factors 142 . A combination of demand-pull forces, learning and scaling, and the cumulative nature of innovation can lead to virtuous cycles that are path dependent and endogenous to the process 143 . Conversely, unabated climate change can be a drag on TFP through downward pressure on factor productivity, decreasing aggregate output 15 , 36 .

Most (but not all) models used in climate policy assessment assume exogenous TFP growth, meaning that changes in aggregate output are independent of the structural changes projected by the scenario. In addition, in many cases the exogenous TFP growth assumptions are the same across reference and mitigation scenarios. A mitigation cost estimate arising from this set-up is inaccurate as it assumes that TFP is unchanged from the reference, even though the technological mix, climate impacts and behaviours are likely to be radically different. This constrains the capacity of models to compute the economic consequences of climate policies.

This points to an opportunity for future research or model development to explore various approaches for endogenizing innovation and TFP. Endogenous growth models were developed more than 30 years ago and led to the award of the 2018 Nobel Prize in Economics 144 . For general equilibrium models, Baccianti and Löschel 145 provide a review and examples of methods used, while Hughes and Narayan 146 report on challenges and approaches for endogenizing an aggregate indicator such as TFP. The complexities and uncertainties, especially for model calibration, involved in endogenizing growth need to be acknowledged, making this a long-term research agenda. Statistically, identifying the determinants of TFP growth has been a challenge. However, certain factors of productivity enhancement such as education and Schumpeterian innovation have been included in IAMs and agent-based models 147 , 148 . In addition, TFP changes “feed forward to economic growth and on to the various subsystems that indirectly or directly drive those same variables affecting it” 146 . This circularity relates to the endogeneity of growth and the path dependence of innovation and investments.

Another issue is that some drivers of TFP change are not related to economic structure. Technology, in particular, may evolve regardless of policy changes once market forces react to initial innovation stimuli. Diffusion of new products and processes follows technological and social learning dynamics that can be mutually reinforcing 143 , 149 , 150 , 151 . The combination of these forces drives TFP changes that are challenging to model but can provide useful insights 133 , 149 , 151 . In sum, there is much to be done to holistically incorporate TFP considerations in mitigation (and reference) scenarios.

Net welfare is what matters

The mechanisms explored above map onto three transmission channels for the impacts of mitigation action on economic activity: avoided impacts from climate change, co-benefits of mitigation measures and resolution of socioeconomic distortions and imperfections (including behavioural imperfections, knowledge spillovers and suboptimal investment and finance). This Perspective argues that measures feeding into these channels are expected to increase economic activity and welfare, potentially offsetting mitigation costs such that net gains arise. It is not possible to say ex ante whether the benefits exceed the costs or vice versa, that is, whether mitigation action will lead to higher or lower economic activity. This will depend on the measures being analysed and the context into which new policies are introduced.

Accounting for uncertainties, Fig. 3 is a conceptual representation of the effect on aggregate economic activity through each channel. Rather than absolute values, the arrows indicate the direction of change resulting from these effects. Mitigation applied to a first-best reference that does not account for avoided damages, co-benefits, underinvestment and other imperfections in the economic system invariably leads to losses to the aggregate economy (grey arrow pointing down). These losses can be offset by the three transmission channels. The first two involve the inclusion of avoided impacts and co-benefits (green and blue arrows pointing up). The third channel involves the implementation of second-best features into the reference scenario that are corrected via policy packages (yellow arrows pointing up). Insight on each of these four arrows can inform policy design and investment decisions. The more successfully the policy packages resolve reference scenario imperfections, the larger the positive contributions of the green, blue and yellow arrows. If the magnitude of these gains is larger than the direct losses typically captured by economic models, the scenario results in welfare gains or higher economic activity.

Impacts are shown in the short term (top row) and long term (bottom row) and across variations in mitigation timing. The three channels include avoided climate change impacts (green), co-benefits of the mitigation policies (blue) and resolution of socioeconomic distortions and imperfections (yellow). Light shading represents the economic impacts through each channel. The additional dark-shaded tips represent the impacts that earlier action may have through each channel (see text).

Models that explicitly represent these channels can provide deeper insight to inform policy decisions. Quantifying each of the channels individually and transparently may help identify policy options that justify lower temperature targets, earlier mitigation or different combinations of policy instruments (the variations in Fig. 3 ). Although these actions entail costs (for example higher short-term costs from earlier mitigation, dark tips on the grey arrows in the variation case), they generate economic benefits that accrue through the three other transmission channels (dark tips on the yellow, green and blue arrows).

If scenarios do not account for any of these channels, this should be clearly acknowledged when providing estimates for costs of mitigation action. Better yet, scenarios can be designed in ways that account for the channels (we have provided some examples) or minimize the consequences of excluding them. As mentioned, temperature-clustered scenarios can circumvent the challenges in modelling economic impacts of climate damages, by exploring alternative policy packages that achieve the same temperature outcomes. For example, such a framework could use as benchmark (or base case) a (second-best) scenario that achieves its climate objective via a globally uniform carbon price or emissions cap. This could then serve as the counterfactual to possible policy intervention scenarios including progrowth measures that, for example, improve resource efficiency, eliminate unfair market power or use carbon tax revenues to boost employment opportunities, enhance labour mobility by reskilling workers or ensure progressivity of a broader tax reform. This way, various policy interventions can be tested to identify economic trade-offs or synergies across potential policy packages and mitigation strategies. As such, a temperature-clustered scenario framework could help focus the policy debate on the appropriate combination of instruments to reach a given emission reduction target effectively.

An important concern for policy-making is the net outcome of the costs of action and the benefits that may accrue, including the results of their interactions. However, this is not to say that it is possible to determine a single best policy alternative or temperature target that is free from value judgements or political decisions regarding the distribution of “impacts over time and across individuals when values are heterogeneous” 54 . However, a reasonable range of cost estimates is useful and should not rule out potential positive outcomes. Ethical considerations of intergenerational justice should also inform the risk appetite towards, for example, large-scale tail events that may lead to irreversible changes in the Earth system. These considerations can be part of multicriterion analysis approaches that enable the assessment of conflicting priorities. When facing uncertainty, adaptive decision-making allows for dynamic realignment to changing circumstances 120 . Most policies can be amended if their costs are found to be too high, but this does not apply to the climate system (AR5 Synthesis Report 54 , page 79).

The cost of mitigation reloaded

To refine the role of economic analyses of the cost of mitigation in support of policy and the societal debate, we offer three suggestions for future work.

First, and starting immediately, existing and upcoming scenario studies should provide appropriate context and framing of findings, including not only caveats, but also risks and opportunities, surrounding the cost of climate change mitigation, supported by the literature and discussion provided in this Perspective. Reallocating economic resources from activities that have undesirable causes (for example, healthcare spending due to diseases related to air pollution) or consequences (for example, global warming induced by fossil fuel subsidies) to productive and sustainable uses will improve welfare outcomes, and modelling frameworks should differentiate accordingly to enable exploration of policy alternatives that maximize the latter. Emphasizing the risks associated with inaction places mitigation costs within a context of potential irreversibility of impacts and the more profound consequences for welfare and economic activity. Highlighting opportunities from alternative climate policy outcomes can help guide transition decisions.

In communicating climate policy, the choice of words can skew public opinion 121 . Properly communicating the benefits of climate action and the stakes involved helps dissipate public opposition, as demonstrated for the case of British Columbia, Canada, where carbon revenues were redistributed directly to families via carbon dividend cheques 122 , 123 . Framing the policy as a ‘carbon dividend’ instead of a ‘carbon tax’ allows for an explicit discussion of the benefits of climate action rather than just the costs. This is relevant in current debates around the European Union’s Green Deal, the USA’s Green New Deal and the inclusion of sustainability criteria in post-COVID-19 recovery efforts 124 .

Second, a temperature-clustered second-best scenario framework allows exploration of alternative climate policy packages and their associated macroeconomic costs. A scenario protocol could describe an ensemble of 1.5-°C- or 2-°C-compatible scenarios with alternative climate policy implementations. These alternatives can be measured against a benchmark scenario with similar temperature outcome that, for example, assumes the immediate introduction of globally uniform, comprehensive carbon prices. Relying only on carbon taxes has notable welfare costs 125 but by enabling explicit exploration of mechanisms that may lead to welfare gains, this framework may help capture the opportunities presented by the deep transformations that a low-carbon transition entails. Importantly, it also paves the way for an open discussion of the limitations of current estimates of macroeconomic costs of mitigation. This framework’s central idea is to compare welfare and development outcomes of climate trajectories that are similar but stem from different policy packages. It resembles recent proposals 126 in the field of impacts and adaptation, translated to the context of mitigation.

Third, combining various approaches to estimate mitigation costs can provide a more comprehensive view. Different model types each have their strengths; they are complementary tools, but the research community could put more effort into learning from one another 127 , 128 . In this respect, including relevant insights and tools from financial economics may help to better capture risk and uncertainty 129 . A more diverse modelling landscape with fertilization across different fields could result in improved understanding of the costs of climate change mitigation. Embracing uncertainty in scenario design to explore risks and opportunities 130 , 131 and endogenizing key parameters can broaden the possibility space 132 , 133 (Box 2 ). Importantly, while diversity is desirable and a lot can be learned from it, the risk that broadening the range of estimates may create confusion, misinterpretation and even distrust, calls for nuanced communication. Empirical work 134 on the propagation of policy effects can provide important input.

Further work on the cost of climate action is important for several reasons. Costs need to be analysed to inform smart policy design that strives for effective emission reductions in an efficient manner and with the largest benefits to society. Importantly, the cost of climate policy needs to be acknowledged to develop complementary measures that guide vulnerable people and regions in the transition towards a carbon-neutral economy.

The framework proposed here will not invariably reveal that there are net welfare gains from climate mitigation policy. However, by not including the mechanisms and channels that could lead to growth, an overly pessimistic picture is sketched—one that suggests irreconcilable trade-offs between climate action and development. This framework rebalances the odds by introducing options to align the climate action narrative with one of increasing welfare and sustainable development. Recovery from the COVID-19 recession is an opportunity for policy-makers around the world to revive flailing economies through public investments (for example in renewable energy) at a time when they are likely to have large positive impacts. We hope the ideas proposed here will contribute to a better understanding of how to use the recovery and climate policy packages to spur growth that is green, inclusive and self-sustaining.

Change history

29 november 2021.

A Correction to this paper has been published: https://doi.org/10.1038/s41558-021-01252-x

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Acknowledgements

The authors acknowledge support from the following European Union’s Horizon 2020 research and innovation programme projects: PARIS REINFORCE (grant agreement no. 820846) for A.C.K., A.G. and J.R.; ENGAGE (grant agreement no. 821471) for V.B.; NAVIGATE (grant agreement no. 821124) for C.G. and M.T.

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Köberle, A.C., Vandyck, T., Guivarch, C. et al. The cost of mitigation revisited. Nat. Clim. Chang. 11 , 1035–1045 (2021). https://doi.org/10.1038/s41558-021-01203-6

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Mitigation strategies and compliance in the COVID-19 fight; how much compliance is enough?

Swati mukerjee.

1 Department of Economics, Bentley University, Waltham, Massachusetts, United States of America

Clifton M. Chow

2 Academic Technology Center, Bentley University, Waltham, Massachusetts, United States of America

3 Department of Mathematical Science, Bentley University, Waltham, Massachusetts, United States of America

Associated Data

The New York Times repository of coronavirus data on GitHub and state level data from the various state web portals (State of New Hampshire, 2020; State of Colorado, 2020; State of New Mexico, 2020; State of Texas, 2020; State of Arizona, 2020; State of New York, 2020) were used.

The U.S. with only 4% of the world’s population, bears a disproportionate share of infections in the COVID-19 pandemic. To understand this puzzle, we investigate how mitigation strategies and compliance can work together (or in opposition) to reduce (or increase) the spread of COVID-19 infection. Building on the Oxford index, we create state-specific stringency indices tailored to U.S. conditions, to measure the degree of strictness of public mitigation measures. A modified time-varying SEIRD model, incorporating this Stringency Index as well as a Compliance Indicator is then estimated with daily data for a sample of 6 U.S. states: New York, New Hampshire, New Mexico, Colorado, Texas, and Arizona. We provide a simple visual policy tool to evaluate the various combinations of mitigation policies and compliance that can reduce the basic reproduction number to less than one, the acknowledged threshold in the epidemiological literature to control the pandemic. Understanding of this relationship by both the public and policy makers is key to controlling the pandemic. This tool has the potential to be used in a real-time, dynamic fashion for flexible policy options. Our methodology can be applied to other countries and has the potential to be extended to other epidemiological models as well. With this first step in attempting to quantify the factors that go into the “black box” of the transmission factor β , we hope that our work will stimulate further research in the dual role of mitigation policies and compliance.

Introduction

By July 31, 2020, the COVID-19 pandemic had resulted in 31.65 million infections and 971,711 deaths globally [ 1 ] with the U.S. contributing 6.9 million cases, with 200,818 deaths. Though testing accelerated over the summer, on August 13, 2020, the U.S. had an overall positivity rate (the percentage of tests conducted that are positive for COVID-19) of 7.5% [ 2 ], well above the upper bound recommended by the WHO (World Health Organization). Before reopening is considered, the positivity rate should be 5% or below for at least 14 days [ 3 ]. Why is the U.S. then bearing such a disproportionate burden of infective cases when it has only 4.25% of the world’s population? [ 4 ].

Clues to this conundrum can only be seen by disaggregating to the state level where we encounter considerable heterogeneity. On August 16, 2020, only 17 states had met the positivity recommendations [ 5 ]. Further, the state disparities are a confusing mosaic of community mitigation strategies (with varying degrees of strictness) and diverse degrees of compliance by the public to such policies.

The objective of this study is to investigate how mitigation strategies and compliance can work together (or in opposition) to reduce (or increase) the spread of infection. To accomplish this, we build an epidemiological model that specifically takes into account not only the community mitigation strategies that slow the spread of the virus, but also compliance by the public. The importance of compliance is generally acknowledged and can be seen, for instance, in the controlling of the Ebola outbreak [ 6 ] where even a day’s delay in full compliance could double the number of infections. The model is applied to a sample of 6 U.S. states (New York, New Hampshire, New Mexico, Colorado, Texas, and Arizona) chosen for three reasons: varying success in flattening the infection curve; availability of daily data on recoveries needed for estimation; a range of positivity ratios. As of August 16 2020, the positivity ratios were 0.83 for New York, 1.34 for New Hampshire, 2.59 for New Mexico, 3.83 for Colorado, 15.32 for Texas and 10.79 for Arizona. Based on the estimation of our model, we offer some recommendations and a practical tool to aid public policy in combating the pandemic.

Apart from widespread vaccination, mitigation actions are the primary bulwark against COVID-19 and this is well established in the literature. Anderson, Heesterbeek, & Hollingsworth [ 7 ], discuss the importance of various country-wide mitigation measures. Kucharski, et al. [ 8 ] investigate the effect of isolation, contact tracing, testing and physical distancing on reducing transmission. Hellewell, et al. [ 9 ] show that in most cases if contact tracing is effective then together with isolation, three months would be sufficient to control COVID-19. Prem et al. [ 10 ] looked at physical distancing measures in Wuhan, China and concluded that these potentially could both reduce and flatten the peak of the epidemic. In fact they warned that a too early and sudden removal of these restrictions could precipitate a secondary peak. To give a historical context, Hatchett, Mecher, & Lipsitch [ 11 ] and Bootsma & Ferguson [ 12 ] inform us on public health intervention measures during the 1918 pandemic. These ranged from the individual level like washing hands, wearing face masks, and maintaining physical distance to those imposed by authorities such as restrictions on gatherings, school and workplace closings etc. Teslya, et al. [ 13 ] showed the importance of mask wearing and hand washing in conjunction with social distancing. Mask wearing and handwashing are two measures entirely within the control of the individual, whereas other measures may need group cooperation. These recommendations can, however, be ignored and that is where the importance of compliance comes in. The Oxford University Blavatnik School of Government has created an index to capture such strategies [ 14 ]. With data from more than 160 countries including the U.S., it has calculated, for each country, a Government Response Stringency Index (GRSI), scaled from 0 to 100, using 9 indicators of mitigation such as school closings, restrictions on gatherings and so on [ 15 ]. See Appendix A in S1 Appendix for the individual indicators. As of July 31, 2020, the Index for the U.S. is 69.0 and to give this some context, it is 67.13 for Canada, 68.06 for Australia and 81.94 for China. Very recently, it has also constructed Stringency Indices for each U.S. state [ 14 ].

The national GRSI has been used by researchers [ 16 ] and has also been used in a modified version applied to Brazil [ 17 ]. We build on and extend the contribution by the Oxford University Blavatnik School of Government. Since certain elements had to be modified to fit varying U.S. state conditions, we created another set of state-specific Stringency Indices that we call the Bentley State Stringency Index (BSI).

As the purpose of mitigation measures is to slow down the spread of infection, we introduced an exponential Mitigation Function on the transmission term in a time-varying SEIRD model. This Mitigation Function, incorporating the Bentley State Stringency Index (BSI), plays a crucial role in slowing down the progression of the disease, provided there is compliance. The latter is represented by an estimable Compliance Indicator (CI) that captures the average degree of compliance in each state. The Compliance Indicator thus modifies the effect of the BSI. It can allow the BSI to work at its full potential in reducing infection or it can progressively choke off completely the effect of mitigation policies as compliance by the public moves to zero. Sheikh et al. [ 18 ] outlined some indirect ways in which one may assess the degree of compliance such as by cell phone GPS data or traffic congestion and public transport usage. Our approach provides a data-based estimation of the degree of compliance for each state. To the best of our knowledge, our approach of employing a Mitigation Function with a tailored, state-specific Stringency Index and a Compliance Indicator has not been taken before.

The estimated Compliance Indicator was then simulated using varying values of the Stringency Index to bring the basic reproductive number R 0 to less than 1 in each of the states studied. See [ 19 , 20 ] for a history of the basic reproductive number and its complexities. A fundamental result in epidemiology is the “threshold” value of the basic reproduction number R 0 : “ There is a difference in epidemic behavior when the average number of secondary infections caused by an average infective during his/her period of infectiousness , called the basic reproduction number, is less than one and when this quantity exceeds one” [ 21 ]. By focusing on the Mitigation Function with its two crucial components, the BSI and the Compliance Indicator, our analysis helps explain why some states have not been successful in controlling infections. In this study we demonstrate the efficacy of this metric from a public health and policy perspective by indicating the minimum level of compliance needed to control the epidemic, given a particular level of stringency. The visual tool created by us is simple enough to be understood by the public and can be used by policy makers to guide decisions as well.

Data, variables and descriptive statistics

Our work is based on multiple data sources: the New York Times repository [ 22 ] of coronavirus data on GitHub, and state level data from the various state web portals [ 23 – 29 ]. Though these data sets begin from Jan 1 2020, COVID-19 infections were not apparent during the early period. Beginning from March 2 when the earliest observation is available, our data runs through July 31, 2020. Additional data on average household size and state population were gathered from the U.S. Department of the Census projections [ 30 ]. Within-household transmission is an important element for success in controlling the infection [ 31 ]. A study [ 32 ] of nearly 400 pregnant women in New York City did not find an association between infection and population density but did find a higher risk of COVID-19 infection due to increased household crowding.

We calculated daily cumulative infection cases ( confirmed infections) from the daily numbers of new confirmed cases. Similarly, daily cumulative recovery ( recovery) and daily cumulative death ( death) were computed from daily numbers of recoveries and confirmed deaths. All three variables are from the New York Times repository [ 22 ] for each state. States may differ on how recovery is defined. For example, Texas calculates recoveries from those who are hospitalized by estimating the proportion of those who are hospitalized for no more than 32 days. To this number they add those who have not been hospitalized but have been infected with COVID-19 for 14 days [ 33 ]. Colorado bases recovery data on those discharged from COVID-19-related hospitalization [ 25 ]. For New Hampshire, recoveries are estimated from the resolution of COVID-19 fever without the use of fever-reducing medications and improvements in respiratory symptoms [ 24 ]. No definitions were released by New York, Arizona or New Mexico at the time the manuscript was completed. Due to the uneven data, there are a few missing daily entries that occur on different days in each state across the three different variables that we used: daily confirmed infections , daily recovery and daily deaths . These missing entries comprise 4% of our 2736 data points and were imputed by taking the average of the previous seven days. Since it takes the CDC coders that length of time to record COVID-19 deaths [ 34 ], the CDC uses a 7-day moving average to report new daily cases [ 35 ].

Overview of the six states

According to WHO, to ensure that the testing rate is sufficient, the positivity rate should be between 3% to 5% [ 5 ]. As of August 13 th , only New York, New Hampshire, New Mexico and Colorado were within this threshold. In mid-August, Arizona had the highest positivity rate of all 50 states (surpassed only by Puerto Rico with the highest possible, 100%). The trend of new cases per 100,000 shows a wide disparity in controlling the infection among these states. As seen from Table 1 , New York which began with the highest rate of 1154.6 per 100,000 people, sank to the lowest (111.5) at the end of the period. On the other hand, Arizona started with 87.4 and rose to 1302.4. New Mexico and New Hampshire started with very similar rates (144.5 and 167.4 respectively), but by June New Mexico’s rate was almost twice that of New Hampshire.

Source: New York Times Repository of COVID-19 Data.

*This is obtained by dividing total new cases over the whole month by the state population and then multiplying by 100,000.

Abbreviations used: TX is Texas; NM is New Mexico; AZ is Arizona; CO is Colorado; NH is New Hampshire; NY is New York.

These varying trends of infections and recoveries in each state are shown in Fig 1 . In some states like Texas, Arizona and New Mexico, the infection rate has accelerated from a previously slower rate of increase. However, in each state there is a clear point of inflection that occurred in June. On the other hand, the remaining three states, most noticeably New York, began entering a phase where the infection was flattening at different rates. Investigating this disparity is the objective of this paper.

Legend : Time series plot for all six states on cumulative confirmed infections, recovery and death. The left column has the cumulative infection (blue) and recovery cases (green) for each state from January to July 2020. The right column has the cumulative deaths for each state for the same period. The varying patterns between the states show up clearly.

The stringency index

A Stringency Index was calculated for each state by modifying the Oxford Index as shown in Appendix B in S1 Appendix . Three items that could not be included by us were restrictions that either were not applicable at the State level or were not applicable to the U.S. in general. These were restrictions on internal travel controls, international transportation, and public officials commenting or coordinating campaigns. However, we needed to add four important restrictions applicable to the U.S. that were not included in the Oxford Index. These were the wearing of face masks, social or physical distancing of 6 feet, nursing home visiting restrictions as per CDC guidelines [ 36 – 38 ], and state border restrictions. Stutt, Retkute, Bradley, Gilligan, & Colvin [ 39 ] showed the effectiveness of wearing face masks in managing the COVID-19 pandemic. It may be noted that instead of the term “social distancing”, some are advocating the term “physical distancing” to clarify to clarify that social connectivity is to be encouraged while yet maintaining physical distancing [ 40 ].

Following the methodology adopted by the Oxford University Blavatnik School of Government (see Appendix A in S1 Appendix ) the Bentley Stringency Index (BSI) was calculated for each state for the entire period. What do these BSI numbers mean? The two extremes of the BSI are 0 where there are no restrictions, and 10 where all the restrictions given in Table 2 (Appendix A in S1 Appendix ) apply to the entire state at the maximum of the scales applicable to that category. The actual BSI will be a combination of the different elements and the scale at which they are applied. For instance, if face masks are recommended but not required, the level of the variable H6 (Appendix A in S1 Appendix ) becomes 1 instead of the maximum of 2 and the BSI will go down. Therefore, a particular BSI number cannot point to a unique combination of mitigation measures but may be consistent with different combinations of restrictions whether applied to the entire state or to targeted areas.

To further clarify the significance of the BSI, we illustrate it from our calculations using the state data from New York and Arizona, two states with very different success in controlling their infection rates. On the 25 April, the BSI for New York was 6.47 but the next day, 26 th April, the BSI jumped to 7.03 because the testing policy was refined to say that anyone showing COVID-19 symptoms should be tested. In Arizona, the BSI on March 30 was 3.75 and the next day it rose to 4.72. The big jump was due to the introduction of new stay at home requirements and limits on public transportation. Again, in Arizona, on May 1, there was a one day drop in the BSI from 5.0 to 4.4 reflecting the removal of the stay at home order.

The movement of the BSI for each state is shown in Fig 2 . Notice that the six states began mitigation interventions around mid-March but subsequently they diverged in terms of timing and extent. By April, Colorado had the highest BSI, whereas Arizona had the lowest. New York slackened restrictions in June and was slightly below New Mexico, but from mid-April to May, New York was more restrictive than New Mexico.

Legend : A comparison of the degree of stringency of mitigation measures by each state shows that though the states all responded by introducing mitigation measures, there are substantial variations between states.

The model that we adopt is based on the SEIRD (Susceptible, Exposed, Infected, Recovered or Died) model that has been developed by Weitz and Dushoff [ 41 ] Loli and Zama [ 42 ] and Lattanzio and Palumbo [ 43 ]. Diagrammatically it can be shown as follows Fig 3 .

Legend : This model shows how, beginning from S, the susceptible population moves from being exposed E, to infected I, and then to either recovery R, or death D, the movement being regulated by different parameters.

The structure of this model that is used in the literature can be described by the following equations:

Following Lolli and Zama [ 42 ], we have the compartments S, E, I, R and D where S is the susceptible group, E consists of those who are infected but may not be infectious, I is the infectious group, while R and D respectively consist of those who recovered or died.

S(t) comprises the total state population at time t after subtracting for those who were exposed or infected, and those who recovered or died. E(t) is approximated by the cumulative number of people tested at time t, and I(t) is the cumulative confirmed positive cases at time t. The variables S(t), E(t) and I(t) were taken from the Covid Tracking Project [ 23 ] and are observed. SI(t), the Bentley Stringency Index that has been calculated as explained earlier is the average measure of the degree of stringency of a state’s mitigation policies.

The term β (though with slightly different names in the literature) is often called the transmission rate of infection or the rate at which two specific individuals come into effective contact per unit of time [ 44 , 45 ]. Specifically, β is the product of the Contact Rate (average number of contacts per person per unit of time) * Transmission Probability or probability of disease transmission in a contact. α is the incubation rate, and 1/ α is the average period (days) of moving from E to I. The average infectious period (days) for the infectious group I is 1/ γ . For instance, if γ = 0.2, then 1/ γ = 5 days means that with an infectious period of 5 days, 20% of patients recover each day. γ denotes the recovery rate for those infected and who have recovered. They move from I to R. δ is the death rate corresponding to a movement from I to D. α t , β t , γ t , δ t , θ t are estimated parameters emerging from the model structure. This model assumes that there is no reinfection and so eliminates movement from R to S. In addition, due to the short period under consideration for epidemics, the population is assumed to be constant with equal birth and death rates.

We extend this SEIRD model by explicitly modeling two important drivers of β , the transmission rate. In the epidemiological literature, it is acknowledged that β can depend on factors like age, living conditions and behavioral interventions such as the closing of theaters, schools and staggering of office hours as happened during the 1918 pandemic [ 11 , 12 , 45 ]. Thus the standard β in the literature is a kind of “black box” containing a complex of factors affecting β and the transmission of disease. We investigate two important factors that influence β : mitigation policies that the BSI captures, and the compliance to these by the public. The latter is being increasingly discussed in the media as being crucial to the success of the various mitigation measures. On Aug 5 2020, in a virtual symposium hosted by the Harvard University’s T.H. Chan School of Public Health, Dr. Fauci, Director of the National Institute of Allergy and Infectious Diseases, explained that it was due to the difference in the states’ mitigation measures and the different ways in which the public has complied with these measures that the U.S. is having difficulty in controlling the pandemic. In the words of the Harvard Gazette, “In addition, he (Dr. Fauci) said, state reopening plans proceeded at different paces. Some states reopened slowly, similar to the pace of European nations, while others went much faster. Another variable, he said, was the extent to which residents of different states adhered to reopening guidelines, with some following recommendations while others ignored the restrictions, sometimes in notably large groups” [ 46 ].

To operationalize these two factors that drive β we explicitly formulate a Mitigation Function that acts to reduce the transmission of disease. This Mitigation Function has two major components: the Bentley Stringency Index (BSI) and what we call the Compliance Indicator (CI). The third component, average household size, is taken as constant over the period under consideration. The BSI has been calculated daily for each state while the Compliance Indicator is estimated from our adaptive computing procedure.

We therefore propose the following formula for β :

β 0 connotes the transmission without policy intervention, e k · SI · θ is defined as the Mitigation Function, k is 1/(average household size) and is a fixed parameter for each state taken from the US Census [ 30 ]. SI is the stringency index, and θ is the Compliance Indicator. β will decrease at an exponential rate of 1 e k ∙ S I ∙ θ .

To incorporate the transmission factor in a time-varying model, we extended β to a time-dependent format β t in our model for estimation purposes.

The time-varying Mitigation Function is: e k ∙ S I t - h ∙ θ t where, SI t is the stringency index at time t. The time lag introduced by a delay in policy implementation is denoted by h . We assume a modest policy lag of 1 day in our model using daily data. θ t is the Compliance Indicator at time t. The thrust of the model is the estimation of the Compliance Indicator θ t and in the process, it also estimates the other unknown parameters: β 0 , α , γ , and θ that have been defined above.

Note that the Compliance Indicator (CI) can vary from 0 (no one complies) to a theoretical maximum of 1 (everyone complies). When the CI = 0, the BSI index has no effect irrespective of its value and the model collapses to the standard model where the mitigation efforts do not affect βt . On the other hand, the BSI can also vary from 0 (no restrictions) to a theoretical maximum of 10 (akin to a total lockdown). This 0 to 10 scale follows the 0 to 100 scale used in the GRSI by Oxford University. When BSI = 0, the model again collapses to the standard model. When BSI is greater than 0, then the effect on βt will depend also on the Compliance Indicator. Even if BSI is at its maximum, a low CI will reduce the Mitigation Function. In other words, it is both BSI and the Compliance Indicator that will determine (given the household size that varies by state) the power of the Mitigation Function which affects the transmission of the disease. Incorporating this extension, our model structure is as follows.

Methodology and results

To estimate the parameters of our proposed model, we use numerical analysis methods and statistical approaches with COVID-19 data from six states beginning from March 2020 to July 2020. In this computing process, we first develop the difference equation system as per the following system:

Then, we develop the overall error function: Error ( t ) = max{ Er S ( t ), Er I ( t ), Er R ( t ), Er D ( t )}, where E r S t = S ^ t - S t ; E r I t = I ^ t - I t ; E r R t = R ^ t - R t ; and finally, E r D t = D ^ t - D t .

As is commonly used, we take the absolute difference between S ^ t and S ( t ) to denote the error Er S ( t ) at time t. We use a similar process to define the errors for Infection ( Er I ( t )), recovery ( Er R ( t )) and death ( Er D ( t )) at time t.

S ^ t , I ^ t , R ^ t , D ^ t are the model estimations at time t for susceptible cases, confirmed infections, recovered individuals and those who died. Correspondingly, S ( t ), I ( t ), R ( t ), D ( t ) are the observed data for each compartment at time t. The estimated value s of the parameters at time t giving the minimum of Error ( t ), were found by applying the interior-point algorithms with dynamically modified constraints on the parameter estimations. Parameters ( S ^ , I ^ , R ^ , D ^ in all six states) were estimated, and predicted values found by the 4 th order Runge-Kutta method using MATLAB 2020a.

The model provides insights into the relationship between three crucial factors in controlling an epidemic: the Bentley Stringency Index (embodying the policy measures recommended or required by Federal or State authorities), the Compliance Indicator (embodying the extent of compliance by the public to these policy measures) and R 0 the basic reproductive rate (defined in the literature as the average number of people an infectious person will infect assuming that the rest of the population is susceptible). It is important to note that though the Mitigation Function has the two variables, BSI and the CI entering as a product, the Compliance Index is the only one endogenously determined and estimated from the model. The BSI is pre-determined and has been built exogenously. Thus, it is possible at any point of time to identify the Compliance Index independently of the BSI.

Having the estimated parameters, the next step explores the interaction of the time-varying values of the Stringency Index and the Compliance Index in each state with the movement of the infection rates.

To examine this, we did two sets of simulations to explore the interacting effect of BSI and CI on R 0 . Both simulations are based on the formula above, with fixed parameters of an average household size of 2.6 individuals [ 31 ], γ = 0.2 [ 47 , 48 ] and δ = 0.032 [ 1 ]. β 0 = 2 was taken from the range of transmission rates (1.5 to 3.5) estimated by Statista [ 49 ].

Simulation 1: Comparing the Oxford and Bentley stringency indices

For both simulations, we used our proposed formula for β and calculated the movement of R 0 using both the Bentley and the Oxford indices. The basic reproduction number R 0 is:

For an epidemic to die out, R 0 must be less than one.

We ran the comparative simulations with fixed parameters, including the Compliance Indicator on all 6 states. The results ( Fig 4 ) are reported for New York and Texas. Results for other states, not reported in the interest of space, are available on request. Comparing the two Stringency Indices, the Bentley Stringency Index is overwhelmingly (with a few exceptions) more conservative in that the simulated R 0 is higher than that obtained by using the Oxford Index.

Legend : This graphs shows the simulated R 0 by using New York and Texas as examples. The simulation period was from January to August 2020. The BSI gives a slightly more conservative result than the OSI.

These simulations gave us further confidence about using the Bentley Stringency Index which has been constructed using policy conditions specific to each state. We were able to start with the first statewide announcement regarding mitigation measures [ 25 , 27 ].

Simulation 2: Interaction of compliance indicator and R 0 at different levels of BSI

Next, we compared New York and Texas by simulating the Compliance Indicator and R 0 at different levels of the BSI, using the same formula as used in the first simulation. See Fig 5 .

Legend : This simulation tool shows the various combinations of policy measures and degrees of public compliance that will be sufficient to bring R 0 <1 thus bringing the pandemic under control. R 0 is indicated by the bold black line which divides the graph into the “undesirable” portion (above) and the “desirable” portion (below). We have simulated where New York and Texas were for two different periods as they moved closer to the desirable portion.

In Fig 5 , the vertical axis is R 0 while the horizontal axis shows the range of the Compliance Indicator. Each grey scale line shows the relationship between R 0 and the Compliance Indicator at different levels of the Stringency Index. The maximum Stringency Index is 10 and is shown by the lowest line. The horizontal line denotes R 0 = 1 which is accepted in the literature as the threshold above which the epidemic will keep spreading. The lower part of the graph can be denoted as “desirable” and the upper portion as “undesirable”. When R 0 is less than one the epidemic will die out.

Our simulations show the different levels of compliance that would be compatible with different degrees of stringency in order for R 0 to go below the threshold. For instance, when the BSI is at 1, then even if the Compliance Indicator is at the maximum, R 0 will not be lower than one. On the other hand, with the highest value of the BSI, the Compliance Indicator has to be at least 25% for R 0 to be at the threshold.

Since Fig 5 is based on the average household size in the U.S., it must be remembered that when the household number increases, then to reach the same R 0 level, the combination of the Stringency Index and the Compliance Indicator has to be at higher levels.

For instance, New York began high in the “undesirable” portion as the higher red dot indicates. That was during Day 65 (March 5th) to Day 75 (March 15th). However, between Day 120 (April 29 th ) to Day 130 (May 9 th ), New York moved to closer to the “desirable” portion of the graph as the lower red dot shows. Similarly, Texas (blue dot) also moved from an undesirable point between Day 170 (June 18 th ) to Day 180 (June 28 th ) to being closer to the “desirable” portion during the period Day 190 (July 8 th ) to Day 200 (July 18). Neither state was, however, successful in crossing into the desirable portion of the graph.

Fig 5 can be of use to guide policy regarding the extent of mitigation measures and compliance needed by the public. Let us illustrate what we mean by going back to the two states we showed in Fig 5 , namely New York and Texas. In Fig 6a and 6b we show plots of the estimated mitigation function against daily infections.

a. New York: Plots of mitigation function estimation (daily) vs daily infections (7-day average). Legend: This figure for New York shows the pattern of the relationship between the observed daily infection cases (red dots) with the mitigation function (blue dots). The red line is the 7-day average of confirmed daily infection cases. The blue line is the trend line of the mitigation function obtained by spline smoothing. b. Texas: Plots of mitigation function estimation (daily) vs daily infections (7-day average). Legend: This figure for Texas shows the pattern of the relationship between the observed daily infection cases (red dots) with the mitigation function (blue dots) as measured by the BSI. The red line is the 7-day average of confirmed daily infection cases. The blue line is the trend line of the mitigation function obtained by spline smoothing.

In Fig 6a for New York, the inverse relation between the Mitigation Function (blue line) and daily infections (red line) can be clearly seen. It must be remembered that the Mitigation Function captures only a portion of all the factors that drive β , the transmission rate. When the infection was raging, the Mitigation Function was increasing and we find that the BSI increased from, essentially, 0 to 0.8 with a mean value of 0.358 during the 10-day period March 5 th to March 15 th (Days 65 to 75). This was because New York restricted public gatherings, cancelled public events and recommended against nursing home visits. The mean estimated CI was 36%. This placed New York in the upper “undesirable” portion of the graph in Fig 5 . When the state initiated the face mask requirement around April 15 th (Day 106) and the testing policy was introduced and defined on April 26 (Day 117), infections, which had hit a peak, began a trajectory downwards until it plateaued around mid-June. By the beginning of May the infection had abated, and the mean values of BSI and CI were 7.028 and 54% respectively during the 10-day period between April 29 th and May 9 th . This trend corresponded with the announcement of New York’s COVID-19 Testing Policy. With this combination of BSI and Compliance Index, New York moved closer to the lower “desirable” range ( Fig 5 ) as the infection rate came more under control.

For Texas, on May 20 th (day 141 in the figure) Governor Abbott signed an executive order on Phase III reopening, to allow more businesses to reopen and to reduce restrictions on gatherings. The Mitigation function decreased accordingly. Note in Fig 6b that as the Mitigation Function decreased with the relaxation of state restrictions, COVID-19 infections also began to climb.

Further, between Day 170 (June 18 th ) to Day 180 (June 28 th ), the BSI increased from 3.9 to 5.0 with a mean value of 4.5. The mean value of the estimated CI is 31%. Even though the state had increased the mitigation policies, it was not enough. The fact that the compliance also is far too low can be seen with a little thought experiment using Fig 5 . Suppose the BSI were 5 (more stringent), then the compliance indicator would need to be at least 50% for the infection to die out as Texas moves to the desirable lower portion of the graph. On the other hand, with this low level of compliance, it can be confidently predicted that the infection will rise. In fact, in the following weeks between June 22 and July 17 the confirmed COVID-19 cases reached 14,916, the highest one-day mark for Texas.

Our results also indicate that when stringency measures are constant, changes in the Compliance Indicator is associated with changes in the infection rates. In Texas, from July 2nd to July 18th (Day 184 to 200 since Jan 1 st ), the BSI stayed constant at 6.18. On the other hand, the estimated CI showed a dramatic 10-day average increase from approximately 24% to 44%.On June 4, Texas reduced restrictions on gatherings by allowing for indoor assemblies such as at places of worship, among local government operations, child-care services and recreational sports for youths and adults. The daily infections during the corresponding period reached a peak and then began to slowly decrease from the end of July 2020. This is clearly visible in Fig 6b .

To examine the sensitivity of the estimated compliance indicator from our model, we conducted three sets of sensitivity analyses using New York as a test case. With a 0%-5% random perturbation (increase or decrease) of daily infection data, we did N = 1000 simulations on the Compliance Indicator, household size and the Bentley Stringency Index. The results are in the S1 Table and show acceptable 90% confidence levels.

Discussion and conclusion

The objective of this paper was to examine how mitigation policies and compliance to these polices can combine to advance or frustrate the fight against the COVID-19 pandemic. Our concern arose from the observation that states with similar community mitigation measures were experiencing very divergent trends in infection rates. To the best of our knowledge, there is no epidemiological model that can help us understand this phenomenon. In this paper we propose a simple modification to bring both mitigation policies and compliance into a standard epidemiological model and, in exploring their interaction, see the minimum levels of each that would lead each state studied to a point where the epidemic would die out.

To accomplish our purpose, we use a standard SEIRD model and then explicitly incorporate two factors that are already present in the “black box” that is βt : mitigation measures and public compliance. In doing this, we build upon the work of Kurcharski et al. [ 8 ] where they suggest that a combination of methods (testing, tracing, physical distancing, self-isolation and quarantine) may be needed to reduce effective transmission so that the epidemic is contained. We go further by taking a vector of mitigation policy measures and encapsulating them into a Bentley Stringency Index (BSI) similar to that built by Blavatnik School of Government of the University of Oxford. Building on and extending their methodology, we create state stringency indices by incorporating directives like wearing face masks, restrictions on nursing home visits that are appropriate to U.S. states to different degrees.

The best of mitigation measures need to be actually followed if they are to be successful. To capture public compliance, a state-specific Compliance Indicator was estimated from the model using the daily COVID-19 data from each state. In this context, Cano et al. [ 50 ] have modelled scenarios with different levels of what they have termed social distancing. However, this term is also used by them interchangeably with lockdown. They show that the less seriously the public takes the lockdown measures, the longer the epidemic will take to resolve and the number of deaths will increase. By quantifying public compliance through the Compliance Indicator, we build the Mitigation Function that encompasses both the BSI and the CI. We demonstrate the association of the movement of infections with movements in the Mitigation Function, ceteris-paribus. Thus, it is the combined effect of the mitigation measures and the compliance that is key. Without either, there can be no containing the pandemic.

Compliance by the public to mitigation measures is largely exogenous in democratic societies. However, by coordinated and effective public information campaigns, through example, by helping people understand that obeying these restrictions is crucial to reclaiming their lives, compliance may be enhanced. In this regard, Arriola and Grossman’s work, though in the context of Africa, may be interesting [ 51 ]. They wanted to see how the social identity of individuals could affect their compliance with advice from public health officials. In the U.S., some states have adopted the “stick” approach; California cut off power to those who were defying restrictions [ 52 ]. However, if the public understands that it is in their own self-interest, the degree of compliance can be increased with their cooperation.

We have also contributed by suggesting a practical, real-time visual policy tool that can be used flexibly not only to monitor the progress in controlling the disease but also to adjust policy in a dynamic fashion. It can be used to support decisions in adjusting mitigation policies by taking into consideration the level of public compliance as well. This tool is also simple enough to be used to educate the public on the importance of compliance.

The chief limitation of our analysis is a problem that all researchers on COVID-19 have to contend with at this time with an ongoing deadly and fast-moving pandemic. Even though we had only 4% of our observation points that were missing or questionable, there are concerns regarding the overall quality of the data [ 53 ]. In addition, a critical issue that has emerged is the under-reporting of cases with continued difficulties in getting tested. We have conducted a sensitivity analysis by adding a random percentage increase of up to 5% to the daily observed infection cases and then examining the variation in the estimated result with regard to both compliance and mitigation (see S1 and S2 Figs). As expected, this does affect the precision of the estimates to varying degrees in different states. Though this is a shortcoming that we are unable to overcome, we do not believe that this affects the main thrust of our paper which is the importance of considering the dual impact of mitigation policies and compliance by the public on controlling the pandemic. The transmission factor β, has hitherto been a “black box”. What we have done is taken the first step to model two important drivers of β.

Our work has opened up several avenues of future research and we give here only a sample of possibilities. With a relatively scant literature on compliance, we hope our work will stimulate more research on this. An important contribution that we intend to take up in a future study would be an exploration of the optimal path of the Compliance Indicator over time. Our method of using the Mitigation Function in SEIRD can be applied to other epidemiological models as well. In addition, this methodology can also be translated to other countries, thereby providing another tool to the authorities in combating this pandemic. We have also made the first step in attempting to quantify the factors that go into the “black box” of β and hope that our work will stimulate further exploration.

Supporting information

Legend: This table shows the effect on the Compliance Indicator by perturbing 3 sets of numbers at a time: the daily infection, household size, k and the Bentley Stringency Index. • N refers to the number of simulations done. • std_t is the standard deviation of 1000 simulations at time t. • Mean of std_t is the average of all the 1000 standard deviations obtained. • The 90% Confidence Interval is obtained by sorting all the std_t in ascending order and then computing the 5 th and 95 th percentiles.

Legend: This figure shows the simulation on NY observed infection cases from Mar to July. A random inflation rate (uniformly from 0% to 5%) was applied to the observed infection cases for each day. The daily compliance rate was estimated from the algorithm. With N = 1000 simulation, the 90% confidence band for the daily compliance rate was shown in the figure, as well as the 7-day average (blue dots) and spline smoothing trend (blue line).

Legend: This figure shows the simulation on NY observed infection cases from Mar to July. A random inflation rate (uniformly from 0% to 5%) was applied to the observed infection cases for each day. The daily compliance rate was estimated from the algorithm. With N = 1000 simulation, the 90% confidence band for the daily mitigation function from the daily compliance rate was shown in the figure, as well as the 7-day average (blue dots) and spline smoothing trend (blue line).

S1 Appendix

Acknowledgments.

We thank Jason Wells, Gaurav Shah, and Maria Skaletsky for their unstinting help with software support. We also thank our student assistants Amitabh Agrawal and Piotr Kolodziej for assistance with data collection and Dhruv Talwar and Ying Wang for helping to solve some technical and formatting issues.

Funding Statement

The authors received no specific funding for this work.

Data Availability

Where We Work

Arab states, asia and the pacific, europe & central asia, latin america & the caribbean.

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What is climate change mitigation and why is it urgent?

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• Climate change mitigation involves actions to reduce or prevent greenhouse gas emissions from human activities.
• Mitigation efforts include transitioning to renewable energy sources, enhancing energy efficiency, adopting regenerative agricultural practices and protecting and restoring forests and critical ecosystems.
• Effective mitigation requires a whole-of-society approach and structural transformations to reduce emissions and limit global warming to 1.5°C above pre-industrial levels.
• International cooperation, for example through the Paris Agreement, is crucial in guiding and achieving global and national mitigation goals.
• Mitigation efforts face challenges such as the world's deep-rooted dependency on fossil fuels, the increased demand for new mineral resources and the difficulties in revamping our food systems.
• These challenges also offer opportunities to improve resilience and contribute to sustainable development.

What is climate change mitigation?

Climate change mitigation refers to any action taken by governments, businesses or people to reduce or prevent greenhouse gases, or to enhance carbon sinks that remove them from the atmosphere. These gases trap heat from the sun in our planet’s atmosphere, keeping it warm. 

Since the industrial era began, human activities have led to the release of dangerous levels of greenhouse gases, causing global warming and climate change. However, despite unequivocal research about the impact of our activities on the planet’s climate and growing awareness of the severe danger climate change poses to our societies, greenhouse gas emissions keep rising. If we can slow down the rise in greenhouse gases, we can slow down the pace of climate change and avoid its worst consequences.

Reducing greenhouse gases can be achieved by:

• Shifting away from fossil fuels : Fossil fuels are the biggest source of greenhouse gases, so transitioning to modern renewable energy sources like solar, wind and geothermal power, and advancing sustainable modes of transportation, is crucial.
• Improving energy efficiency : Using less energy overall – in buildings, industries, public and private spaces, energy generation and transmission, and transportation – helps reduce emissions. This can be achieved by using thermal comfort standards, better insulation and energy efficient appliances, and by improving building design, energy transmission systems and vehicles.
• Changing agricultural practices : Certain farming methods release high amounts of methane and nitrous oxide, which are potent greenhouse gases. Regenerative agricultural practices – including enhancing soil health, reducing livestock-related emissions, direct seeding techniques and using cover crops – support mitigation, improve resilience and decrease the cost burden on farmers.
• The sustainable management and conservation of forests : Forests act as carbon sinks , absorbing carbon dioxide and reducing the overall concentration of greenhouse gases in the atmosphere. Measures to reduce deforestation and forest degradation are key for climate mitigation and generate multiple additional benefits such as biodiversity conservation and improved water cycles.
• Restoring and conserving critical ecosystems : In addition to forests, ecosystems such as wetlands, peatlands, and grasslands, as well as coastal biomes such as mangrove forests, also contribute significantly to carbon sequestration, while supporting biodiversity and enhancing climate resilience.
• Creating a supportive environment : Investments, policies and regulations that encourage emission reductions, such as incentives, carbon pricing and limits on emissions from key sectors are crucial to driving climate change mitigation.

Photo: Stephane Bellerose/UNDP Mauritius

Photo: La Incre and Lizeth Jurado/PROAmazonia

What is the 1.5°C goal and why do we need to stick to it?

In 2015, 196 Parties to the UN Climate Convention in Paris adopted the Paris Agreement , a landmark international treaty, aimed at curbing global warming and addressing the effects of climate change. Its core ambition is to cap the rise in global average temperatures to well below 2°C above levels observed prior to the industrial era, while pursuing efforts to limit the increase to 1.5°C.

The 1.5°C goal is extremely important, especially for vulnerable communities already experiencing severe climate change impacts. Limiting warming below 1.5°C will translate into less extreme weather events and sea level rise, less stress on food production and water access, less biodiversity and ecosystem loss, and a lower chance of irreversible climate consequences.

To limit global warming to the critical threshold of 1.5°C, it is imperative for the world to undertake significant mitigation action. This requires a reduction in greenhouse gas emissions by 45 percent before 2030 and achieving net-zero emissions by mid-century.

What are the policy instruments that countries can use to drive mitigation?

Everyone has a role to play in climate change mitigation, from individuals adopting sustainable habits and advocating for change to governments implementing regulations, providing incentives and facilitating investments. The private sector, particularly those businesses and companies responsible for causing high emissions, should take a leading role in innovating, funding and driving climate change mitigation solutions. 

International collaboration and technology transfer is also crucial given the global nature and size of the challenge. As the main platform for international cooperation on climate action, the Paris Agreement has set forth a series of responsibilities and policy tools for its signatories. One of the primary instruments for achieving the goals of the treaty is Nationally Determined Contributions (NDCs) . These are the national climate pledges that each Party is required to develop and update every five years. NDCs articulate how each country will contribute to reducing greenhouse gas emissions and enhance climate resilience.   While NDCs include short- to medium-term targets, long-term low emission development strategies (LT-LEDS) are policy tools under the Paris Agreement through which countries must show how they plan to achieve carbon neutrality by mid-century. These strategies define a long-term vision that gives coherence and direction to shorter-term national climate targets.

Photo: Mucyo Serge/UNDP Rwanda

Photo: William Seal/UNDP Sudan

At the same time, the call for climate change mitigation has evolved into a call for reparative action, where high-income countries are urged to rectify past and ongoing contributions to the climate crisis. This approach reflects the UN Framework Convention on Climate Change (UNFCCC) which advocates for climate justice, recognizing the unequal historical responsibility for the climate crisis, emphasizing that wealthier countries, having profited from high-emission activities, bear a greater obligation to lead in mitigating these impacts. This includes not only reducing their own emissions, but also supporting vulnerable countries in their transition to low-emission development pathways.

Another critical aspect is ensuring a just transition for workers and communities that depend on the fossil fuel industry and its many connected industries. This process must prioritize social equity and create alternative employment opportunities as part of the shift towards renewable energy and more sustainable practices.

For emerging economies, innovation and advancements in technology have now demonstrated that robust economic growth can be achieved with clean, sustainable energy sources. By integrating renewable energy technologies such as solar, wind and geothermal power into their growth strategies, these economies can reduce their emissions, enhance energy security and create new economic opportunities and jobs. This shift not only contributes to global mitigation efforts but also sets a precedent for sustainable development.

What are some of the challenges slowing down climate change mitigation efforts?

Mitigating climate change is fraught with complexities, including the global economy's deep-rooted dependency on fossil fuels and the accompanying challenge of eliminating fossil fuel subsidies. This reliance – and the vested interests that have a stake in maintaining it – presents a significant barrier to transitioning to sustainable energy sources.

The shift towards decarbonization and renewable energy is driving increased demand for critical minerals such as copper, lithium, nickel, cobalt, and rare earth metals. Since new mining projects can take up to 15 years to yield output, mineral supply chains could become a bottleneck for decarbonization efforts. In addition, these minerals are predominantly found in a few, mostly low-income countries, which could heighten supply chain vulnerabilities and geopolitical tensions.

Furthermore, due to the significant demand for these minerals and the urgency of the energy transition, the scaled-up investment in the sector has the potential to exacerbate environmental degradation, economic and governance risks, and social inequalities, affecting the rights of Indigenous Peoples, local communities, and workers. Addressing these concerns necessitates implementing social and environmental safeguards, embracing circular economy principles, and establishing and enforcing responsible policies and regulations .

Agriculture is currently the largest driver of deforestation worldwide. A transformation in our food systems to reverse the impact that agriculture has on forests and biodiversity is undoubtedly a complex challenge. But it is also an important opportunity. The latest IPCC report highlights that adaptation and mitigation options related to land, water and food offer the greatest potential in responding to the climate crisis. Shifting to regenerative agricultural practices will not only ensure a healthy, fair and stable food supply for the world’s population, but also help to significantly reduce greenhouse gas emissions.  

Photo: UNDP India

Photo: Nino Zedginidze/UNDP Georgia

What are some examples of climate change mitigation?

In Mauritius , UNDP, with funding from the Green Climate Fund, has supported the government to install battery energy storage capacity that has enabled 50 MW of intermittent renewable energy to be connected to the grid, helping to avoid 81,000 tonnes of carbon dioxide annually. 

In Indonesia , UNDP has been working with the government for over a decade to support sustainable palm oil production. In 2019, the country adopted a National Action Plan on Sustainable Palm Oil, which was collaboratively developed by government, industry and civil society representatives. The plan increased the adoption of practices to minimize the adverse social and environmental effects of palm oil production and to protect forests. Since 2015, 37 million tonnes of direct greenhouse gas emissions have been avoided and 824,000 hectares of land with high conservation value have been protected.

In Moldova and Paraguay , UNDP has helped set up Green City Labs that are helping build more sustainable cities. This is achieved by implementing urban land use and mobility planning, prioritizing energy efficiency in residential buildings, introducing low-carbon public transport, implementing resource-efficient waste management, and switching to renewable energy sources. 

UNDP has supported the governments of Brazil, Costa Rica, Ecuador and Indonesia to implement results-based payments through the REDD+ (Reducing emissions from deforestation and forest degradation in developing countries) framework. These include payments for environmental services and community forest management programmes that channel international climate finance resources to local actors on the ground, specifically forest communities and Indigenous Peoples. 

UNDP is also supporting small island developing states like the Comoros to invest in renewable energy and sustainable infrastructure. Through the Africa Minigrids Program , solar minigrids will be installed in two priority communities, Grand Comore and Moheli, providing energy access through distributed renewable energy solutions to those hardest to reach.

And in South Africa , a UNDP initative to boost energy efficiency awareness among the general population and improve labelling standards has taken over commercial shopping malls.

What is UNDP’s role in supporting climate change mitigation?

UNDP aims to assist countries with their climate change mitigation efforts, guiding them towards sustainable, low-carbon and climate-resilient development. This support is in line with achieving the Sustainable Development Goals (SDGs), particularly those related to affordable and clean energy (SDG7), sustainable cities and communities (SDG11), and climate action (SDG13). Specifically, UNDP’s offer of support includes developing and improving legislation and policy, standards and regulations, capacity building, knowledge dissemination, and financial mobilization for countries to pilot and scale-up mitigation solutions such as renewable energy projects, energy efficiency initiatives and sustainable land-use practices. 

With financial support from the Global Environment Facility and the Green Climate Fund, UNDP has an active portfolio of 94 climate change mitigation projects in 69 countries. These initiatives are not only aimed at reducing greenhouse gas emissions, but also at contributing to sustainable and resilient development pathways.

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New Research Report—Developing New Zealand Blue Carbon Projects

September 03, 2024 | Auckland, New Zealand

A comprehensive research report into coastal wetland blue carbon has identified a range of actions that can help accelerate coastal wetland restoration in New Zealand.

The Nature Conservancy Aotearoa New Zealand (TNC NZ) today released the Coastal Wetland Blue Carbon Policy Research in Aotearoa report —a research report commissioned by TNC NZ and Ministry for the Environment (MfE) intended to explore the policy, legal and market conditions that would be needed to enable coastal wetlands projects to result in blue carbon credits.

“Blue carbon markets are relatively new compared with markets for carbon sequestration on land, such as tree planting, but they are expected to have great potential as part of the global demand for nature-based pathways to address climate change,” said Abbie Reynolds, country director, TNC NZ.

Quote : Abbie Reynolds

Coastal communities can reap benefits from healthy coastal wetlands through increased resilience, enhanced biodiversity, cleaner water and opportunities for eco-tourism.

"We’re excited to be working in this area and exploring the role that investing in nature-based solutions via carbon credits can play to avert the climate crisis. Other solutions include reducing emissions, protecting and restoring natural ecosystems, developing and implementing innovative technological solutions, and investing in and deploying renewable energy to deliver the majority of the mitigation needed.”

Revenue from blue carbon credits could also help support landowners at restoration sites.

“Coastal communities can reap benefits from healthy coastal wetlands through increased resilience, enhanced biodiversity, cleaner water and opportunities for eco-tourism. They can also enjoy the social and cultural benefits from living in a healthy functioning ecosystem.”

The report also recommends ways to address the existing policy, regulatory and legal complexities so that New Zealand projects could participate in carbon markets at scale. The report was authored by Jacobs, Environmental Accounting Services, Anderson Lloyd and Conservation International.

The authors identified the following priority recommendations:

• Develop a national blue carbon roadmap or strategy, with suggested pathways for enabling blue carbon projects at scale.
• A Māori-led study into the barriers, opportunities and benefits of blue carbon for Māori.
• Government and Māori to develop clear guidance and/or regulatory tools to grant carbon rights in the coastal marine area.
• Government to create an enabling environment for voluntary markets to operate in Aotearoa New Zealand, including Paris Agreement Article 6 policy clarity.

The report explored the implications of including blue carbon in New Zealand’s GHG inventory and Nationally Determined Contributions and whether the best place for these projects would be voluntary markets.

Read the Report

Coastal Wetland Blue Carbon Policy Research in Aotearoa, Sept. 2024

It also investigated how changing the regulatory environment could impact on the development of blue carbon projects and what we can learn from established blue carbon accounting schemes overseas. The research suggested voluntary carbon markets would be a better option for pursuing carbon credits from coastal wetland restoration, compared to the New Zealand Emissions Trading Scheme.

“Promoting the restoration of coastal wetlands via blue carbon credits can contribute to our collective climate response by helping New Zealand adapt to the impacts of climate change and supporting our communities through the transition,” said Olya Albot, project manager for nature-based solutions at The Nature Conservancy Aotearoa New Zealand.

“Addressing policy barriers and creating an enabling environment has the potential to accelerate pilot projects already underway in New Zealand and support the uptake of blue carbon projects in New Zealand for the international voluntary market, at scale,” Olya Albot said.

More Information

Blue carbon ecosystems, such as coastal wetlands, face threats from rising sea levels and extreme weather events. However, coastal wetlands help mitigate climate change by converting CO₂ emissions into plant biomass, potentially more effectively than forests. Coastal wetlands also help protect communities against storm surge and sea-level rise by providing natural protection.

Six priority research themes around the policy and legal landscape were:

• Greenhouse Gas Inventories and Nationally Determined Contributions
• Carbon markets and trading
• Environmental policy and law
• Coastal land tenure and carbon rights
• Blue carbon schemes and methodologies
• Benefits of blue carbon projects

The report also outlined opportunities and implications of including coastal wetlands in New Zealand’s GHG inventory and NDC, including:

• Creating a more complete inventory, including a more accurate representation of the country’s carbon emissions and sinks;
• The opportunity for New Zealand to lead by example regarding conservation and sustainable use of coastal and marine ecosystems and offer insights for the Pacific region.

More on The Nature Conservancy’s work on blue carbon

Although coastal wetland blue carbon is not included in New Zealand’s national Greenhouse Gas (GHG) inventory, the opportunity to restore coastal wetlands is mentioned in the country’s  Emissions Reduction Plan , as well as in the new  Climate Change Strategy  as nature-based solutions.

Any blue carbon projects would need to demonstrate high integrity and meet independently assured standards such as Verified Carbon Standard (VCS).

The Nature Conservancy is a global conservation organization dedicated to conserving the lands and waters on which all life depends. Guided by science, we create innovative, on-the-ground solutions to our world’s toughest challenges so that nature and people can thrive together. We are tackling climate change, conserving lands, waters and oceans at an unprecedented scale, providing food and water sustainably and helping make cities more sustainable. The Nature Conservancy is working to make a lasting difference around the world in 77 countries and territories (41 by direct conservation impact and 36 through partners) through a collaborative approach that engages local communities, governments, the private sector, and other partners. To learn more, visit nature.org or follow @nature_press on X.

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6 Takeaways from the 2022 IPCC Climate Change Mitigation Report

• Clean Energy
• climate science
• climatewatch-pinned

With every fraction of a degree of global warming, climate change impacts will intensify. In the latest installment of the Intergovernmental Panel on Climate Change’s (IPCC) Sixth Assessment Report , 278 scientists from 65 countries find that the world should peak GHG emissions in the next three years to preserve our chances of meeting the Paris Agreement's 1.5 degrees C (2.7 degrees F) target.

Coming on the heels of two previous reports focused on the physical science of climate change and its impacts , this report from Working Group III concentrates primarily on mitigation, or reducing greenhouse gas (GHG) emissions and removing carbon dioxide (CO 2 ) from the atmosphere. Analyzing over 18,000 studies published since the IPCC’s Fifth Assessment Report in 2014, the world’s leading climate scientists identify pathways to limit global warming to 1.5 degrees C, among other temperature thresholds, as well as assess the feasibility, effectiveness and benefits of different mitigation strategies.

Here are six key findings from the IPCC’s report on climate change mitigation: 

1. Global GHG emissions have continued to rise, but in pathways that limit warming to 1.5 degrees C, they peak before 2025.  

Globally, GHG emissions rose over the past decade, reaching 59 gigatonnes of CO 2 equivalent (GtCO 2 e) in 2019 — roughly 12% higher than emissions in 2010 and 54% greater than 1990. But in modelled pathways that hold global warming to the Paris Agreement’s 1.5 degree C goal (with no or limited overshoot), GHG emissions peak before 2025 and then fall by 43% from 2019 levels by 2030.

While there are some signs of progress — the annual rate of GHG emissions growth declined from an average of 2.1% between 2000 and 2009 to 1.3% between 2010 and 2019, and 24 countries have sustained their GHG emissions reductions for over a decade — global efforts to mitigate climate change remain far off-track.

For example, even if countries achieve their most recent national climate commitments (NDCs), the gap between global GHG emissions and the level associated with limiting warming to 1.5 degrees C would be 19-26 GtCO 2 e in 2030. This is more than the 2018 emissions from the United States and China combined. While some countries have announced new or enhanced NDCs since the IPCC’s cut-off date, these pledges are not ambitious enough to close the gap.

2. There's no room for building new fossil fuel infrastructure.

The IPCC shows that in pathways that limit warming to 1.5 degrees C (with no or limited overshoot), just a net 510 Gt of CO 2 can still be emitted before CO 2 emissions reach net zero around mid-century (2050-2055). Yet future CO 2 emissions from existing and planned fossil fuel infrastructure alone could reach 850 Gt — 340 Gt more than that limit.

A mix of strategies can help avoid locking in these CO 2 emissions, including retiring existing fossil fuel infrastructure, cancelling new projects, retrofitting fossil-fueled power plants with carbon capture and storage (CCS) technologies, and switching to lower-carbon fuels.

Although coal-fired power plants are beginning to be retired across the United States and Europe, some international development banks are still investing in new coal capacity. Failure to change course will result in trillions of dollars of stranded assets.  

3. We need rapid transformations across all systems to avoid the worst climate impacts.

GHG emissions have risen across all major systems since last assessed. The IPCC finds that reversing course will require decision-makers in government, civil society and the private sector to prioritize the following actions, many of which pay for themselves or cost less than $20 per tonne of CO 2 e:

• Scale up clean energy . All electricity generation must be low-carbon by 2050, while total generation must grow to allow the electrification of end-uses like HVAC, transportation, industrial machinery and more. Pathways holding warming to 1.5 degrees C (with no or limited overshoot) rely on grids predominantly powered by renewables and storage, complemented by a mix of nuclear, a small amount of fossil fuels with CCS, and/or other forms of clean power. Alternative energy carriers such as hydrogen and ammonia must substitute for fossil fuels in sectors where electrification will be difficult, such as industry and heavy-duty transport. The good news is that the per-unit costs of low-carbon technologies like photovoltaics have dropped by as much as 85% over the last decade.  
• Double-down on innovation to decarbonize industry . Improving energy efficiency, reducing material demand through circular economy solutions, deploying CCS in hard-to-abate sectors like cement, and switching to new low- and zero-emission industrial processes are necessary for producing materials like steel, cement, plastic, pulp and paper, and chemicals. However, the IPCC states this will require 5-15 years of “intensive innovation, commercialization and policy” – alongside immediate investments in technologies that already exist – to drive costs down and achieve the required uptake.  
• Incentivize green buildings . Since the IPCC’s Fifth Assessment Report in 2014, an increasing number of zero-carbon buildings have been constructed in almost all climate zones. Electric heating, more efficient appliances and lighting, and the circular use of materials have been key. However, progress must accelerate rapidly to retrofit older buildings and ensure that these improved technologies and approaches are incorporated into a growing share of new construction projects. Green building guidelines for construction and use, as well as building energy codes, can further drive progress.  
• Redesign cities and shift to zero- and low-carbon transport . Without a change in trajectory, CO 2 emissions from the transport sector are set to increase by up to 50% by 2050. The world needs a suite of actions to avert this trend. The IPCC found that cities can reduce their transport-related fuel consumption by about a quarter through combinations of more compact land use and the provision of car-free infrastructure, like pedestrian lanes and bike pathways. These shifts toward low-carbon, highly accessible urban design also improve well-being by reducing congestion and air pollution. Simultaneously, electromobility options like battery-electric vehicles (the fastest-growing segment of the auto industry) and electric railways charged by clean power have already reduced transport-related GHGs and must continue to accelerate. For hard-to-decarbonize transport systems like shipping and aviation, advanced biofuels, ammonia and synthetic fuels are emerging as viable options, but they require more financing and policy support.  
• Conserve ecosystems and improve food systems . The IPCC finds that protecting, restoring and sustainably managing carbon-rich ecosystems like forests and peatlands — as well as reducing the GHG intensity of food production, curbing food waste, and shifting to more sustainable diets — can mitigate 8-14 GtCO 2 e per year from now through 2050 at relatively low costs. (Note that other research finds more limited mitigation potentials for several agricultural practices included in this estimate.) Halting the conversion of ecosystems can play an outsized role, as deforestation alone accounts for 45% of emissions from the land sector. Yet much of this overall potential exists in developing countries, where weak institutions, insecure land rights and scarce finance hinder implementation.       

If well-designed and effectively implemented, many of these mitigation strategies can generate critical co-benefits for sustainable development. Conserving natural landscapes, for example, can support nearby households’ livelihoods, bolster food and water security, and protect biodiversity. But not all efforts to reduce emissions or remove carbon will deliver win-wins for both climate action and development. When managed poorly or implemented inappropriately, these actions can disrupt local economies, exacerbate existing inequities, and displace communities, among other unintended consequences. The IPCC finds that managing these tradeoffs through inclusive, transparent, and participatory decision-making processes can cultivate social trust, as well as deepen public support for transformative climate action. Doing so can also help ensure that transitions to a net-zero future are just and equitable.

4. Changes in lifestyle and behaviors have a significant role to play in mitigating climate change.

Worldwide, households with incomes in the top decile, which includes a large share of households in developed countries, are responsible for 36-45% of total GHG emissions, while families earning in the bottom 50% account for just 13-15%. Achieving universal access to modern energy for the world’s poorest, the IPCC further finds, would not significantly impact global emissions. But shifting consumption patterns, particularly among the world’s wealthiest, can slash GHG emissions by 40-70% by 2050 when compared with current climate policies. Walking or cycling, avoiding long-haul flights, shifting to plant-based diets, cutting food waste, and using energy more efficiently in buildings are among the most effective demand-side mitigation options.

Policy measures that make these lifestyle and behavior changes less disruptive can help ease these shifts, such as subsidizing low-emissions technologies, taxing high-emissions technologies like fossil-fueled cars, and setting standards that mandate greater energy efficiency. Infrastructure design — like reallocating street space for sidewalks or bike lanes — can help people transition to lower-emissions lifestyles.

Similarly, how sustainable options are presented to consumers (also known as “ choice architecture ”) can help nudge people toward low-emissions goods and services. For example , including vegetarian dishes alongside meat entrées on menus, rather than in separate vegetarian sections, can help increase consumption of plant-based meals.

5. Limiting global temperature rise to 1.5 degrees C will be impossible without carbon removal.

The IPCC found that all pathways that limit warming to 1.5 degrees C (with no or limited overshoot) depend on carbon removal. These approaches can include both natural solutions, such as sequestering and storing carbon in trees and soil, as well as technologies that pull CO 2 directly out of the atmosphere. The amount of carbon removal required depends on how quickly we reduce GHG emissions across other systems, and the extent to which climate targets are overshot, with estimates ranging from 5-16 GtCO 2 per year by mid-century.

In the near-term, restoring natural carbon sinks like forests is a relatively cost-effective, readily available carbon removal approach that, when implemented appropriately, can deliver a wide range of benefits to nearby communities. Yet carbon stored in these ecosystems is also vulnerable to disturbances like wildfires – disturbances that will only intensify in a changing climate and release stored carbon back into the atmosphere.

Given the scale of carbon removal required in some 1.5 degree C pathways, as well as concerns about the impermanence of natural sinks, the world will likely also need carbon removal technologies. Currently, these innovations are relatively nascent and come with a variety of challenges and risks. Scaling up biomass crop production for the deployment of bioenergy with carbon capture and storage (BECCS), for example, may displace croplands, and in doing so, threaten food security and spur additional deforestation.

Responsibly developing and deploying carbon-removal technologies, alongside natural approaches, will require a better understanding of each innovation’s unique benefits, costs and risks. The need for increased finance for research, development and deployment is urgent.

Hover over each carbon removal approach to learn more:

Note: The natural vs. technological categorization shown here is illustrative rather than definitive and will vary depending on how approaches are applied, particularly for carbon removal approaches in the ocean.

6. Climate finance for mitigation must be 3 to 6 times higher by 2030 to limit warming to below 2 degrees C.

Annual public and private finance for climate change mitigation and adaptation rose by up to 60% from 2013 to 2020. However, these gains have slowed in recent years, and to make matters worse, the IPCC found that finance for fossil fuels still outstrips funding for climate action.

This misalignment of global capital has resulted in a substantial shortfall between current levels of climate finance and those needed to mitigate climate change, which persists across all regions and all sectors. This gap is widest in developing countries, particularly those already struggling with debt, poor credit ratings and economic burdens from the COVID-19 pandemic. Investors’ tendency to channel greater shares of capital into their own countries, as well as the systemic underpricing of climate risks, pose additional challenges for scaling up private finance across these nations. Recent mitigation investments, for example, need to increase by at least sixfold in Southeast Asia and developing countries in the Pacific, fivefold in Africa and fourteenfold in the Middle East by 2030 to hold warming below 2 degrees C (3.6 degrees F). And across sectors, this shortfall is most pronounced for agriculture, forestry and other land use, where recent financial flows are 10 to 29 times below what is required to achieve the Paris Agreement’s goals.

Clear policy signals from the international community and governments — such as increasing subsidies for mitigation, pricing carbon emissions, phasing out public finance for fossil fuels, or adopting strong regulations that mandate low-carbon transitions — can help create the certainty the private sector needs to scale up investments in mitigation. Innovative financing mechanisms that enable governments to share risks with private companies can also go a long way in mobilizing private sector finance. And expanding public climate finance, particularly across low-income countries, can deliver significant returns at relatively low costs. 

Where Do We Go from Here?

As this latest IPCC report makes clear, holding global temperature rise to 1.5 degrees C is still possible, but only if we act immediately. The world needs to peak GHG emissions before 2025, nearly halve GHG emissions by 2030, and reach net-zero CO 2 emissions around mid-century, while also ensuring a just and equitable transition. With escalating risks from droughts, floods, wildfires and other disastrous effects of climate change, these are deadlines we simply cannot afford to miss.

WRI's Podcast on the IPCC Report

Learn more about the podcast and view the transcription here .

This article was corrected with the latest rates of mitigation investments.

Published based on IPCC report Technical Summary and underlying chapters.

Interactive graphics by Rosie Ettenheim.

Relevant Work

10 big findings from the 2023 ipcc report on climate change, closing the emissions gap: a climate action roadmap for limiting warming to 1.5 degrees c, tracking climate action: how the world can still limit warming to 1.5 degrees c, statement: ipcc report sounds the alarm: the climate clock is ticking, the time to act is now, how you can help.

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Risk Mitigation Strategies: Types & Examples (+ Free Template)

Effective enterprise risk management is more important than ever. A recent 2023 State of Risk Oversight Report by NC State University shows that while two-thirds of business leaders (out of 454 respondents) acknowledge escalating risks, only a third are geared up to tackle them.

This points to a serious disconnect between the organization’s needs and its risk management strategy. No plan is bulletproof, but effective preparation and monitoring will help you minimize risks and their impact on business.

In this article, we explore the different risk mitigation strategies and how you can implement them to protect your organization’s performance and stability.  

What Is Risk Mitigation?

Risk mitigation is a proactive business strategy to identify, assess, and mitigate potential threats or uncertainties that could harm an organization’s objectives, assets, or operations. It entails specific action plans to reduce the likelihood or impact of these identified risks. 

Conversely, risk management is a broader, more comprehensive process that involves various stages like risk identification, assessment, response, and monitoring. 

While risk mitigation focuses on direct actions to eliminate or diminish threats, risk management encompasses the entire life cycle of dealing with risks. 

They may sound similar, but risk mitigation is a subset and vital component of the risk management process.

Why Is Risk Mitigation Important?

The stakes are high, according to the 2023 State of Risk Oversight Report. We're seeing near-record levels of risk events and complexities across organizations.

So what does a robust risk mitigation plan offer you? For starters, it's not about ignoring risks, but rather tackling them head-on with actionable steps. This ensures you have a business continuity plan in the face of disruptions. 

An effective risk mitigation process also provides a clearer picture of potential obstacles, which helps with strategic decision-making. This helps manage operational risks and create a resilient supply chain . It also assures employees that they are working with a company that prioritizes job security.

But risk mitigation isn't all defense—it also sets you up to seize growth opportunities. By identifying and minimizing risks, you can make calculated moves that optimize your business portfolio .

What Are The Types Of Risks?

Your risk mitigation strategies should be tailored to your business, which means it can't be a carbon copy of another organization's risk mitigation strategy. The risks you face will vary based on your industry, sector, and other unique factors.

Some of the most common types of risks include:

• Competitor risk: Threats from rival organizations.
• Economic risk: Vulnerabilities due to economic fluctuations.
• Political risk: Impact of political factors.
• Financial risk: Exposure to financial uncertainties.
• Operational risk: Daily hazards in operations , including cybersecurity risks. 

📚You can learn more about risk types and strategies to mitigate them in this article .

What Are The Risk Mitigation Strategies?

Described below are the most common risk mitigation strategies.

Tip: You should always start with a complete risk analysis to pick the right strategy for your business.

Risk avoidance strategy

The most straightforward way to deal with risks is to remove them entirely. This involves steering clear of any actions or situations that could harm your business. But be cautious: sidestepping one risk might require sacrificing other resources.

A large technology company plans to launch a new product in an international market, but a risk assessment uncovers considerable regulatory and political obstacles. 

Opting for a risk avoidance strategy, the company chooses not to enter the new market, eliminating these high-stakes risks. Instead, it reallocates resources to bolster existing markets or pursue other low-risk opportunities. 

While this approach removes immediate risks, it also sacrifices the potential revenue and growth the new product could have generated in that market.

Risk transfer strategy

Sometimes you can pass risks on to someone else. This usually involves using contracts, insurance, or outsourcing . This is a good strategy if it's cheaper to pay another company to take on the risk than to deal with it yourself.

💡 Examples:  

• Work with a third-party logistics provider (3PL) for your shipping and delivery needs. The contract often includes clauses that transfer the risk of damaged or lost goods during transit to the 3PL. Upon damaged products, the 3PL is liable to compensate your business for the losses.
• Pay an insurance company a small fee to avoid the full financial implications of unforeseen events like accidents.

📚 Recommended read: Unlocking The Power Of Logistics Strategy To Achieve Supply Chain Excellence

Risk acceptance strategy

Sometimes taking a risk is a good choice, especially if the potential reward is high or the likelihood of problems is low. Each business has its own comfort level for risk and uses that to decide which risks are worth taking. It’s also better to accept risks if the costs of avoiding them are too high.

Many startups know they have a high chance of failing early on. But they're willing to take that risk because the possible rewards, like growth and profit, make it worthwhile. 

If you’re following this strategy, you must constantly monitor the threat level. If it rises above acceptable risk levels, or if your risk appetite changes, you might need to switch to a different strategy to protect your business.

Risk reduction strategy

In cases where you can’t avoid or accept the risks, it’s best to pursue measures to reduce their impact altogether. Risk reduction involves implementing proactive and concrete actions to make a potential problem less severe.

💡 Examples: 

• An oil drilling company in a hurricane-prone region may invest in advanced high-tech weather systems to better predict stores. This move will help them to prepare in advance and reduce the likelihood of costly disruptions due to natural disasters. 
• If you identified that you’ll run out of funds to complete a project, you could switch to more affordable materials or scale back the project size. You could also look for extra funding. Each option helps lower the risk of running out of money before completing the project.

Risk monitoring strategy

Risks are an ongoing fact of doing business and carefully monitoring them will ensure that mitigation measures remain effective. Risk monitoring involves regular evaluations and adjustments to strategies to address changing circumstances. 

💡 Example: 

A manufacturing company can continually monitor supply chain risks like supplier reliability, geopolitical issues, and market trends. If there are potential disruptions, they can take timely actions to adjust sourcing strategies or secure alternative suppliers.

What Are The Steps To Mitigate Risks?

The following steps will help you identify risks and implement a responsive risk mitigation strategy:

1. Understand what you’re up against

Systematically examine all the possible risks to your business by conducting an internal and external analysis. You can use the SWOT analysis to identify the current and future state of your business. Pay attention to the “Threats” quadrant that highlights potential risks. 

You can also use other strategic analysis tools like PESTLE Analysis or Porter’s 5 Forces to analyze the business’s external environment for any potential threats. 

💡Involve key stakeholders to gain a diverse perspective and access to insights that may not be immediately apparent. They can help you see what’s happening on the front lines so you can assess risks accurately.

2. Assess and prioritize the risks

After listing all the possible risks, it’s time to analyze the probability of their occurrence and the potential negative impact. You can use a risk matrix to help you assess and prioritize risks based on their likelihood and impact. This will help you focus your resources on the most critical risks.

💡While the risk matrix is easy to read and use, it often relies on qualitative judgments. This can sometimes result in poor resource allocation. To avoid this, whenever possible, convert risks into monetary terms. This provides a more accurate picture of how each risk could financially impact your business.

3. Prepare a plan to execute your risk mitigation initiatives

Once you’ve identified and categorized the potential risks to your business, it’s time to create an action plan. For each identified risk, decide on the most suitable approach: will you avoid, mitigate, transfer, or simply accept it?

Once you've determined your approach for each risk, allocate the needed resources. This includes people, money, and time devoted to implementing the chosen risk mitigation strategies . Have a backup with contingency plans for risks that may not be fully addressed by your initial strategies.

💡You can use Cascade’s Risk Mitigation Strategy Plan Template to cover all the key elements of an effective strategy. 

4. Execute your strategy and monitor risks 

Risks are always changing. That's why you need to continuously keep an eye on them to make sure your mitigation plans are up-to-date. Establish regular check-ins, such as daily or weekly meetings, to quickly assess the status of your risk mitigation strategies. 

To make this process even more efficient, use specific metrics tied to the risks you're managing. Set up triggers that alert you when it's time to take extra steps.

💡Look for strategy execution tools like Cascade that integrate seamlessly with various business platforms. This allows you to bring all your key business data together in a centralized hub, making it easier to stay on top of risks and adjust your strategies as needed.

5. Update risk and adapt your plan

As your business landscape evolves—whether due to market shifts, technological upgrades, or internal developments—your risk mitigation plan must keep pace. Not only can new risks arise, but the importance of existing risks can change as well.

To make these adjustments more data-driven, you can use Cascade's reports . 

These reports help you pinpoint any threats, monitor risks, and keep your team aligned with updated priorities. By constantly refining your plan, you ensure it remains effective in a shifting environment.

Mitigate Risks And Master Chaos With Cascade 🚀

To be resilient and successful, it's crucial to spot and neutralize threats before they escalate. Instead of being reactive, the key is to be proactive—maintaining financial stability, safeguarding your reputation, and staying ahead of the competition.

With features like alignment and collaboration, real-time analytics, and data tracking in one place, Cascade empowers you to detect and manage risks with confidence. 

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• Mitigation Matters: Policy Solutions to Reduce Local Flood Risk (PDF)

Mitigation Matters: Policy Solutions to Reduce Local Flood Risk

Since 2000, floods have cost the United States more than $845 billion in damage to homes, businesses, and critical infrastructure. The expense of adapting to more frequent and severe storms is projected to rise over the next several decades, placing a premium on the need to take action now to reduce the impacts of future floods.

“Mitigation Matters,” new research from The Pew Charitable Trusts, identifies 13 states or cities that have adopted policies resulting in effective flood mitigation. To learn more, read the overview , which includes lessons from these jurisdictions, or go directly to briefs below about each city or state. The policies are organized into three categories: 1) using existing funds for mitigation by redirecting revenue and spending, 2) creating revenue sources, and 3) establishing smarter regulations.

Using existing funds for mitigation by redirecting revenue and spending

State and local governments are making long-term commitments to support flood mitigation efforts by establishing programs that draw from their annual budgets, such as grant and rebate programs, or by offering tax credits to help fund projects.

Arkansas Tax Credit Rewards Landowners for Conserving Wetlands

Illinois village offers rebates for flood mitigation projects.

South Holland, Illinois

Vermont’s Fund Helps Communities to Become More Flood Ready

Washington partnership fosters collaboration for flood plain restoration, wisconsin grant program helps people relocate from flood-prone areas, creating revenue sources for mitigation.

Some states and cities are generating new revenue to fund flood mitigation measures by asking residents or the federal government to share the burden. This effort includes leveraging bonds and tax collections, establishing state revolving loan funds, and combining state funding with financial assistance from the federal government.

Indiana’s Flood Control Revolving Fund Makes Resources Available to Communities

Iowa flood mitigation program leads to $1.4 billion in projects, maryland’s living shorelines help communities become resilient, minnesota uses bonds to support flood-ready infrastructure, establishing smarter regulations to reduce flood risk.

Some jurisdictions have used regulatory strategies to help guide less-risky development to reduce the impact of flooding. These strategies include updating city zoning ordinances to account for sea-level rise, encouraging landowners to opt for natural solutions to prevent erosion when possible, acting to ensure that building in a flood plain doesn’t lead to flood problems for other properties, and limiting the amount and type of development in flood plains.

North Carolina City Adopts Stringent Standard for Building in Flood Plain

Brevard, North Carolina

Colorado City Revamps Flood Plain Management After Severe Flood

Fort Collins, Colorado

Milwaukee Uses Nature-Based Regulations to Reduce Flooding

Norfolk’s revised zoning ordinance aims to improve flood resilience.

Norfolk, Virginia

Read more about lessons learned below

Devastating floods are on the rise. Since 2000, flood-related disasters have cost the United States more than $845 billion in damage to homes, businesses, and critical infrastructure, according to the National Oceanic and Atmospheric Administration. 1 The expense of adapting to more frequent and severe storms is projected to increase over the next several decades, placing a premium on the need to take action now to reduce flood impacts in the future.

Research from the National Institute of Building Sciences shows that every dollar spent on risk reduction measures—such as creating green space to help absorb floodwaters, buying out residents in at-risk areas who want to move out of harm’s way, and adopting the most up-to-date building codes and standards— saves an average of $6 in disaster costs. 2 Efforts to take advantage of this return on investment are beginning to gain traction at all levels of government.

At the national level, the Disaster Recovery Reform Act signed into law by President Donald Trump in 2018 dedicated a significant percentage of disaster-related spending toward helping communities prepare before storms strike. Congress is considering going further, with proposals that would provide communities with funds or incentives to reduce their risk of flooding. And the Federal Emergency Management Agency recently launched the Mitigation Investment Moonshot, which has a goal of quadrupling mitigation spending by federal, state, local, and tribal governments; corporations; nonprofits; and private foundations by 2022.

Many states and localities are also being proactive. Governors from South Carolina, Tennessee, and Texas, among others, have recently tasked officials in their administrations with improving natural disaster planning with local governments and recommending actions to minimize future flood impacts. Elected officials in other states are exploring effective ways to fund flood mitigation measures.

Noting the recent increase in such efforts, The Pew Charitable Trusts—in partnership with Dewberry— examined policies across the country and identified 13 states or cities that have adopted measures resulting in effective flood mitigation activities. Detailed in this set of 13 briefs, the policies fall into three categories:  1) using existing funds for mitigation by redirecting revenue and spending, 2) creating revenue sources for mitigation, and 3) establishing smarter regulations to reduce flood risk.

The research found that state and local governments are making long-term commitments to support flood mitigation efforts by establishing programs that draw from their annual budgets, such as grant and rebate programs, or by offering tax credits to help fund projects. 

Washington state ’s Legislature has provided more than $115 million in grants since 2013 for the state’s Floodplains by Design program. The grants support projects to restore rivers and their flood plains and  remove dams and other engineered systems that are no longer operating effectively. Grant programs such as Wisconsin ’s have funded the purchase of repeatedly flooded properties to allow people to relocate. The village  of South Holland, Illinois , offers rebates to help residents afford mitigation projects that reduce risk  to their properties, such as installing drain tile systems that move water away from their homes. To date,  1,172 households in South Holland—with a population of just 8,200—have used the rebates. 

This type of government commitment to flood resilience is not limited to payouts. Some states are incentivizing projects by offering tax credits; Arkansas , for example, allows income tax credits for property owners who restore or create wetlands that absorb floodwaters.

And Vermont , through its Emergency Relief and Assistance Fund (ERAF), rewards communities that take mitigation actions by giving them more funds for recovery assistance when flooding occurs, while communities that have not taken such steps must pay more of their recovery costs. .  

Some states and cities are generating new revenue to fund flood mitigation measures by asking residents or  the federal government to share the cost. Minnesota used bonds as well as a portion of its tax collections:  After catastrophic flooding in 2010, the state’s Legislature began using $50 million in bonds—leveraged partly  by revenue from a higher gas tax—to make roads and bridges more resilient.  Iowa has established a flood mitigation fund, seeded by a local sales tax, to pay for measures that are  designed to prevent significant costs—with one project alone expected to reduce future flood damage by  nearly $600 million. Other states have combined their own funding with financial assistance from the  federal government; Washington state developed its Floodplains by Design program after using a federal  grant to assess and address the root causes of its flood problems. Both Indiana and Maryland have established revolving loan funds to help residents and communities pay for flood mitigation projects. Each state seeds its fund with state money, with the fund replenished over time as recipients repay the loans. Maryland’s fund has financed nearly $3 million in loans to help protect more than 200,000 linear feet of shoreline..

Some jurisdictions have used regulatory strategies to help guide less risky development in order to reduce the impact of flooding. Norfolk, Virginia , for example, updated its city zoning ordinance to account for sea level rise, rather than rely solely on historical data; the changes included the creation of a scoring system that encourages development in safer areas.  

To protect its coasts from sea level rise and storm surge, Maryland requires property owners to opt for natural solutions to prevent erosion—instead of using hard structures, such as seawalls and levees—unless they can prove that such methods would not work on their property.

In Milwaukee , the city set ambitious permitting goals to help embrace nature-based solutions, supporting projects such as green roofs and native landscaping.

Brevard, North Carolina , established one of the nation’s most robust flood-related regulations: a no-adverse-impact certification, designed to ensure that building in a flood plain doesn’t lead to flood problems for communities downstream. And in Colorado, Fort Collins enacted forward-thinking regulations limiting the amount and type of development in flood plains for the Cache la Poudre River. The change helped the city achieve greater resilience during heavy flooding in 2013.

* Maryland’s mitigation actions fall into both the new or replenished revenue and low-cost regulations categories.

Lessons learned

States and local jurisdictions plan for and mitigate future risks based on their unique needs and circumstances. Nevertheless, the actions featured in the policy briefs provide a variety of lessons for other jurisdictions to consider as they develop their own mitigation policies.

Invest in planning—and understand the risks

Some of the most effective mitigation policies first took shape following efforts to understand the root of a flooding problem. Officials in Washington state used an Environmental Protection Agency grant to study the state’s flooding problem before presenting a solution to the Legislature. Minnesota assessed flood impacts to transportation assets, such as roadways and bridges, and identified projects based on the costliest and most frequent closures of those assets due to flooding. In both cases, officials maximized the effectiveness of limited funding by being deliberate in examining vulnerability to floods and the greatest sources of possible disruption.

In South Holland, Illinois, a resident committee assessed options for combating flooding, leading to a proposal that eventually became the city’s rebate program—which has since led to more than 1,000 households strengthening their properties against flood risk. On a larger scale, Iowa dedicated an agency to studying flood models and related patterns.

Use regulations and cost-shares as cost-effective options

Several states and localities are driving down the cost of flood mitigation by using regulations to guide development away from high-risk areas as well as establishing policies that maximize the value of relatively small upfront government investments.

Fort Collins’ flood plain regulations, Norfolk’s zoning ordinance, and Brevard’s no-adverse-impact certifications are helping to ensure that housing, infrastructure, and other assets are located away from vulnerable areas, thus minimizing damage when floods occur. Indiana’s revolving loan fund maximizes the impact of a relatively small investment by making low-interest loans for mitigation projects to jurisdictions that then repay them so that others can take out similar loans. 

Other policies leverage cost-sharing, in which jurisdictions combine their own resources with funding from individual homeowners and other levels of government to cover the expense of flood mitigation. Wisconsin’s buyout program, for instance, provides up to half the cost for local mitigation projects, and municipalities make up the remainder.

Tap into nature-based solutions

When designing policies to improve disaster resilience, some states are leveraging the benefits of nature-based solutions, such as creating open spaces and restoring wetlands, which serve as buffers between oncoming storms and otherwise vulnerable communities.

Maryland’s living-shorelines regulations prioritize the use of native plants and other natural elements that stabilize coastlines, reduce erosion, and mitigate flood damage, as opposed to structures like levees and seawalls. Buyout programs such as Wisconsin’s can replace hard surfaces such as concrete with green spaces such as parks and wetlands, which better absorb rainwater and bring additional benefits to communities, including providing places for recreation.

Officials in these states and others are nurturing more sustainable communities by weighing the impacts of development decisions on natural flood plains. And some places are moving to policies that reverse previous actions that manipulated bodies of water, such as Washington state’s history of straightening its rivers and Milwaukee’s lining of streams with concrete. Some communities have come to realize that these disruptions of natural waterway functions actually increased their flood risk and have since turned to nature-based solutions. 

Communicate the benefits and engage stakeholders

Many programs’ effectiveness depends on whether communities understand how to take advantage of them, and how well municipalities collect feedback and improve the programs. Arkansas’s tax credit incentive has proved immensely popular in communities where awareness has spread through word-of-mouth, but other communities in the state have not seen the same level of interest. And while a significant portion of residents have used South Holland’s rebate incentive, program managers believe more would take advantage of it if they better understood the benefits.

In Iowa, officials have used the state’s network of Water Management Authorities to bring stakeholders into the conversation about curbing floods and to ensure that their concerns about the state’s mitigation program are addressed.

Make policy changes part of recovery efforts

As communities try to recover after flooding, some legislatures have responded by passing forward-thinking laws aimed at lessening the impacts of future floods. For example, after Tropical Storm Irene, lawmakers in Vermont created the ERAF program, which rewards localities that take measures to reduce their future risk.

Likewise, in Norfolk, the persistent problem of sea level rise motivated officials to improve the city’s zoning ordinance, buoyed by polls showing that 70 percent of city residents were concerned about flooding. As communities encounter more frequent and widespread damage from storms or rising seas, they can harness residents’ awareness and concern to initiate positive change.

Pew’s research highlights state and local policies and regulations that have been important catalysts for flood mitigation. As green spaces expand, wetlands recover, natural shorelines are created, infrastructure becomes more resilient, and homes are removed from or not built in vulnerable areas, communities are reducing the impact of future floods.  

Although there is no one-size-fits-all solution to the threat posed by more frequent and severe flooding, the 13 policy briefs provide a variety of models for officials to consider when trying to make their own communities more resilient.

Methodology

Pew contracted with Dewberry, a consulting engineering firm, on the 13 briefs. Dewberry conducted a literature survey of jurisdictions across the U.S., identifying a range of state and local policies designed to drive increases in pre-disaster mitigation. Local officials and representatives from 17 expert organizations were consulted to understand the impact of the policies in order to draw a connection between a policy and mitigation activity. Two external reviewers—Nate Woiwode, project manager of The Nature Conservancy’s North American Risk Reduction and Resilience team, and  Elizabeth Albright, assistant professor of the practice of environmental science and policy methods at Duke University’s Nicholas School of the Environment—provided expert insight. Neither they nor their organizations necessarily endorse the findings.

• National Oceanic and Atmospheric Administration, National Centers for Environmental Information, “Billion-Dollar Weather and Climate Disasters” (2019), https://www.ncdc.noaa.gov/billions/events .
• National Institute of Building Sciences, “Natural Hazard Mitigation Saves: 2017 Interim Report” (January 2018), https://www.nibs.org/news/381874/National-Institute-of-Building-Sciences-Issues-New-Report-on-the-Value-of-Mitigation.htm .

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Posted: Mon 2nd Sep 2024

Update on Tŷ Pawb budget mitigation measures: Councillors to review financial stability and progress

An update report on the sixteen Tŷ Pawb “budget pressure mitigation points” is set to be probed by councillors who have previous expressed their concerns over the finances of the council run centre.

The points were first presented to the Employment, Business and Investment Scrutiny Committee back in January ( Councillors “very, very concerned” over Ty Pawb finances ) with requests for regular future updates.

Back then the forecast financial projections showed, without mitigation actions, net forecast budget pressures of £277,768 in 2023/24 and up to £288,502 in 2026/27. As reported at the time, a contributor to those figures was the huge energy bill of the building with a utility rate increase adding £144k.

It was agreed on 5th March: ‘That the Committee receive an update report in six months’ time that outlines the sixteen mitigation points including the invest to save together with any income or offsetting costs such as solar panels and pre decision outcomes because it will benefit the Executive Board.’

Issues were also highlighted with leases, with councillors now told, “Currently 100% of traders are in possession of compliant tenancies and have been issued with updated market regulations and guidelines.”

Extra information is given, “At the time of writing this report, Tŷ Pawb has a current occupancy level of 70% which equates to 34 occupied and 14 vacant trading units, with 4 applications currently in process”.

A 14% increase in car park revenue has been reported after “persistent issues with the car park exit barrier have been resolved”.

Four paragraphs and a table are dedicated to an “Energy Update from Decarbonisation Team”, that detail how the council’s energy advance purchase arrangements meant the two year window at first benefited the council, and thus the centre, but latterly “The energy for 2023/24 was purchased after the significant rise in energy prices which is why there was a considerable increase in WCBC’s energy prices from 2022/23 to 2023/24. The energy prices for the current financial year, 2024/25, have fallen from their peak in 2023/24, but not to the levels they were at in 2022/23”.

The overview report notes, “The projected net budget pressure for 2023-24 was £277,768. The actual year-end net budget pressure was £195,000, which is £82,768 lower than projected.

“A forward cost-saving was identified for 2024-25 however, this was achieved in 2023-24, due, in part, to the implementation of the 16 point mitigation plan and additional one-off grant payments being received in relation to the cultural programmes.

Therefore it concludes there is still a gap, “At the time of submitting this report (27th August 2024), the financial projection for Tŷ Pawb 2024-25 is a net pressure of £170,000.”

The ‘financial stability’ of Ty Pawb is seen as a key element of the City of Culture bid, with the finance risk having a “…corresponding impact on Wrexham’s bid to become UK City of Culture 2029”.

The main report is accompanied with a break dow of the 16 ‘mitigation’ actions, with elements from them summarised below:

• Income maximisation group that has met four times, has ‘generated an income of £8,700 towards their target of £20k.
• Ty Pawb rental costs are seen as ‘competitive’ and a 5% increase was ‘implemented in line with inflation’.
• Operating hours review is ‘ongoing’ and several years after opening they are going to ‘trial a full Friday night program’.
• A new ‘fit for purpose’ car park system will be in place by January 2025 with new equipment. There is no cost to this known yet but the council are confident it ‘will be funded through part of the anticipated increase in income’.
• Carbon footprint will be tackled with £30,000 for rain water harvesting, £60,000 for flat roof solar and £25,000 for wind turbines or equivalent. This appears to be the project that the Lead Member was highly critical over reporting on, however it turns out that criticism was misplaced and inaccurate .
• The centre’s roof is ‘not fit for purpose’, with a ‘feasibility study’ taking place to identify a ‘long term solution’ however it appears the finances on how any solution will be paid for is unknown.
• Funding has been ‘identified’ to pay for a study to quantify the social return on investment from activities delivered within the centre.
• Venue hire is being ‘maximised’ with ‘complimentary bookings are no longer being taken’ for the Useful Art Space, with the report stating “Formalised marketing materials being developed for this space. Income generated via paid hires between March and August 2024 is £2,000.”
• A new tiered charging framework is being created for the Performance Space.
• Promoting venue hire has had a ‘multi pronged approach’ since April, including groundbreaking activities like ‘a series of social media posts on X, Instagram and Facebook’. Basic promotion of the centre has been a long term regular suggestion from councillors.  The impact of such promo several years after opening is noted, with ‘the average number of weekly venue hire enquiries more than doubling’ (with no numbers given).
• External hire of the Learning Studio has resulted in an increase of £1,320 revenue.
• The ‘Makers Space’ conversion to a rentable retail unit benefit is booked to the ‘income maximisation group’ above.
• £10k grant from the Arts Council Wales will be spent on “Specialist support with development of new sponsorship package Arts Award training for 2 x staff members Options appraisal for new systems to expedite receipt of donations Graphic design, production, and marketing for new exhibitions education pack Capital equipment” 
• There has been an increase in specialist fairs in the centre with 6 additional scheduled, which is ‘double’ the 2023-24 figures.
• More activities are taking place in the Market Hall to help make it ‘animated’, therefore “…making it a more desirable and profitable location for permanent traders; thus safeguarding the presence of permanent traders and associated rental income”
• Sponsorship is hoped for the 2025 exhibitions programme.

The committee meet tomorrow to discuss the reports here .

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