EPA Science Advisory Board (SAB)

Review of Reduced-Form Tools Evaluation

EPA Designated Federal Officer (DFO):Suhair Shallal
Responsible Committee/Panel:Reduced Form Tools Review Panel
A list of members can be found in the final report included in the Advisory Activity linked to this panel or committee.

See EPA’s PDF page to learn more about PDF files.

Quantifying and valuing the public health impacts of changes in air quality can be a time- and resource-intensive endeavor that often requires large, detailed datasets and sophisticated computer models. The U.S. Environmental Protection Agency (EPA) routinely undertakes these analyses as part of Regulatory Impact Analyses (RIAs) to estimate the costs and health benefits of major air pollution regulations. EPA strives to estimate the public health benefits of air quality changes in ozone and/or fine particulates (PM2.5) using a state-of-the-science “full-form” approach that couples a photochemical air quality model, such as the Community Multiscale Air Quality (CMAQ) model, with a health benefits tool such as the Environmental Benefits Mapping and Analysis Program – Community Edition (BenMAP-CE). However, there are times when EPA has instead used “reduced-form” tools, which employ simpler models to approximate the more complex analyses with a lower computational burden.

EPA has conducted a study of reduced-form tools utilizing a protocol for systematically comparing PM2.5 monetized health benefits estimated using reduced-form tools with those generated using full-form air quality and health benefits models, in the specific context of using such tools to inform the economic impacts of regulatory analyses. EPA has requested a peer review to assess whether the evaluation framework developed in this study is appropriate, and to provide input with regard to future design improvements to enhance the capabilities of reduced form tools.

Agency Charge . (PDF, 3 pp., 118,159 bytes)

Agency Review Document(s):

PDF for Evaluating Reduced-form Tools for Estimating Air Quality Benefits (October 2019). (PDF, 81 pp., 1,891,753 bytes)