BenMAP

BenMAP quantifies the health and economic impacts of air pollution by applying concentration–response relationships to air quality, population, health, and economic data to estimate morbidity, mortality, and monetized damages for PM2.5.

Key Features:

• Health Impact Assessment: Calculates numbers of air pollution–related deaths and illnesses by translating changes in air quality into health outcomes using health impact models and concentration–response functions.
• Economic Valuation: Estimates monetized values of health impacts to support cost–benefit assessments of emissions control scenarios.
• Integration with Reduced Complexity Models: Accepts inputs from reduced complexity models as lower-compute alternatives to photochemical grid models such as CAMx and CMAQ while maintaining predictive capability for emissions-to-air-quality relationships.
• Benchmarking and Intercomparison: Performs systematic comparisons between reduced complexity model predictions and photochemical grid model outputs using consistent input parameters.
• Scenario Analysis: Facilitates analysis of emissions control scenarios, including sector-specific policies for on-road mobile sources, electrical generating units (EGUs), and hypothetical reductions across sectors such as cement kilns, refineries, and pulp and paper.
• Data Sharing and Resource Utilization: Utilizes the publicly available RFMEVAL repository (https://github.com/epa-kpc/RFMEVAL) that provides inputs, outputs, and run control files for models including APEEP v2 and v3, InMAP, EASIUR, and EPA's source apportionment benefit-per-ton reduced complexity models.
• County-Level Analysis: Generates county-level estimates of health benefits and monetized health damages to provide spatially resolved impact assessments.

Scientific Applications:

• Policy evaluation: Translates emissions changes from regulatory or hypothetical scenarios into estimated air quality improvements, health outcomes, and monetized benefits for decision making.
• Model intercomparison and evaluation: Compares performance of reduced complexity models against photochemical grid models such as CAMx and CMAQ using standardized inputs and RFMEVAL resources.
• Spatial health burden estimation: Produces county-level morbidity, mortality, and economic damage estimates for regional and local impact assessments.
• Cost–benefit analysis: Provides monetized health impact estimates to inform economic appraisal of emissions control strategies.

Methodology:

Applies concentration–response relationships with population, air quality, health incidence, and economic metrics to compute health incidence and monetized damages; performs systematic comparisons using consistent input parameters and RFMEVAL-provided inputs, outputs, and run-control files for APEEP v2/v3, InMAP, EASIUR, and EPA reduced complexity models.