A Proof-Of-Concept Approach for Quantifying Multipollutant Health Impacts Using Joint Effects Models within the Open-Source BenMAP-CE Software Program

摘要

Air pollution risk assessments often use results from epidemiologic studies to quantify health impacts of air quality changes to individual pollutants, but tend not to account for exposure to complex mixtures. Multipollutant statistical models consider collinearity among pollutants by identifying mixtures commonly emitted from specific sources. Using a proof-of-concept version of the environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) we aim to answer: (1) can the results from multipollutant statistical models (joint effect models) be used in air pollution risk assessments?; (2) how does the procedure for quantifying population health impacts differ between a single and multipollutant context? We identified studies using joint effect models with/without interactions to estimate the risk of air pollutant-attributable asthma emergency department (ED) visits. These studies examine associations between short-term criteria pollutant exposures (O3, PM2.5, CO, NO2, SO2) and PM components, which represent predefined source groupings (oxidant gases, secondary pollutants, traffic, power plant, criteria pollutants). We use results from these studies and daily air quality data in BenMAP-CE for a case study in the city of Atlanta and the state of Georgia. Preliminary results indicate: (1) interaction models yield larger estimates of pollutant-attributable asthma ED visits; (2) warm season impacts are greater than cold season; and (3) certain pollutant groups yield a negative number of cases. BenMAP-CE runtime for multipollutant models was commensurate with runtime for single pollutant models. This study suggests that risk assessments for multipollutant exposures are feasible, but data-intensive. Future risk assessments using single and multipollutant approaches can potentially provide a more comprehensive evaluation to inform air quality management strategies. Disclaimer: The views expressed do not necessarily reflect the views/policies of U.S. EPA.