Assessment of PM2.5 Air Pollutant Health Damages with the REACH Reduced-Complexity Model
MEDINAT AKINDELE, Peter Adams, Nicholas Muller, Rebecca Garland,
Carnegie Mellon University Abstract Number: 500
Working Group: Aerosols Spanning Spatial Scales: Measurement Networks to Models and Satellites
AbstractThe US has made strides in improving air quality since the enactment of the 1970 Clean Air Act, while air pollution has worsened in other countries over the same period. Evaluating the benefits of air pollution strategies requires models to estimate pollutant concentrations. The models typically used in the US for regulatory purposes are chemical transport models (CTMs): they simulate atmospheric and physical processes to predict ambient PM
2.5 concentrations. Although they are the gold standard for air quality modeling, they necessitate high computational costs and technical expertise. Therefore, they can only assess a limited number of policy scenarios, and many countries lack the technical capacity to use CTMs for policy evaluations. These limitations motivated the development of reduced-complexity models (RCMs), which are faster than CTMs and can assess many policy scenarios. However, most RCMs are hard coded to the US. Thus, we introduce the Rapid Estimation of Air Concentrations for Health (REACH) Gaussian plume model with chemistry. It is location-agnostic, allowing user-specified meteorology and emissions for any region. Here, we show results for the REACH model applied to the US to estimate county-level ambient PM
2.5 concentrations and health damages (premature mortalities per tonne of PM
2.5 or precursor emitted). Like CTMs, REACH-US reproduces PM
2.5 concentrations against standard monitors better in the eastern US (R
2 = 0.39) compared to the West. The estimated national-average health damages associated with PM
2.5 exposure resulting from ground-level emissions of PM
2.5, SO
2, NO
X, NH
3, and VOCs are 110, 106, 15, 33, and 17 $/ktonne, respectively. The health damage evaluations against other US RCMs (AP2, EASIUR, and InMAP) for ground-level PM
2.5 resulted in an R
2 correlation of 0.71-0.72. REACH can be expanded to other regions, and sample results from Southern Africa are presented to highlight its potential use in data-scarce areas.