Multicity accountability and uncertainty assessment of the impacts of regulations on air quality in Atlanta, New York City, and Southern California

Abstract

Multiple regulations have been promulgated to improve air quality, and previous studies have used an accountability chain to evaluate the effects of these regulations on emission levels, air quality, and human health. However, quantifying these impacts through the accountability chain is complex due to interactions between multiple factors that can influence the efficacy of control policies and introduce uncertainties at each step. We evaluated and quantified the impact of emission controls on electricity generating units (EGU) and motor vehicle sources on emissions and air quality via Generalized Additive Models. These GAMs have minimal bias (around 10⁻⁵ to 10⁻² μg/m³ or ppbV) and r² values for daily concentrations ranging from 0.4 to 0.7 Counterfactual air pollutant concentrations, in the absence of EGU and mobile source regulations, were calculated using estimated counterfactual emissions for the period 2005 to 2019 in Atlanta, New York City, and California's South Coast Air Basin. Counterfactual air pollutant concentrations indicated that the effects of regulations on air pollutants varied depending on the season and location. Predicted counterfactual air pollutant concentrations were generally 2–12 times higher than the measured concentrations at these sites, except for ozone. The impact of regulations on ozone concentrations typically resulted in reduced peak ozone values in the summer, but increased concentrations in the winter. Monte Carlo modeling found small to modest uncertainties, depending on the pollutant, location and regulations assessed. Counterfactual concentrations predicted in this project will be used in the assessment of the trends of toxicity in PM_2.5.