Accountability assessment of regulatory impacts on ozone and PM2.5 concentrations using statistical and deterministic pollutant sensitivities


Since the 1990 Clean Air Act Amendments, the USA has seen dramatic decreases in air pollutant emissions from a wide variety of source sectors, which have led to changes in pollutant concentrations: both up and down. Multiple stakeholders, including policy-makers, industry, and public health professionals, seek to quantify the benefits of regulations on air pollution and public health, a major focus of air pollution accountability research. Two methods, one empirical, the other based on a chemical transport model (CTM), are used to calculate the sensitivities of ozone (O3) and particulate matter with diameters less than 2.5 μ m (PM2.5) to electricity-generating unit (EGU) and mobile source emissions. Both methods are applied to determine impacts of controls on daily concentrations (which are important in assessing acute health responses to air pollution), accounting for nonlinear, meteorologically, and emission-dependent responses of pollutant concentrations. The statistical method separates contributions of nearby EGU, regional EGU, and mobile source emissions on ambient city-center concentrations. Counterfactual emissions, an estimate of emissions under a scenario where no new controls were implemented on local EGU sources after 1995, regional EGUs after 1997, and mobile sources after 1993, are combined with these sensitivities to estimate counterfactual concentrations that represent what daily air quality in Atlanta, GA would have been had controls not been implemented and other emissions-reducing actions not been taken. Regulatory programs are linked with reduced peak summertime O3, but have had little effect on annual median concentrations at the city-center monitoring site, and led to increases in pollutant levels under less photochemically-active conditions. The empirical method and the CTM method found similar relationships between ozone concentrations and ozone sensitivity to anthropogenic emissions. Compared to the counterfactual between 2010 and 2013, the number of days on which O3 (PM2.5) concentrations exceeded 60 p p b (12.0 μ g m −3) was reduced from 396 to 200 (1391 to 222). In 2013, average daily ambient O3 and PM2.5 concentrations were reduced by 1.0 p p b (2 %) and 9.9 μ g m −3 (48 %), respectively, and fourth highest maximum daily average 8-h O3 was reduced by 14 p p b. Comparison of model-derived sensitivities to those derived using empirical methods show coherence, but some important differences, such as the O3 concentration where the sensitivity to NOx emissions changes sign.

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This material is based upon work supported by Health Effects Institute and the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1148903. Detailed data and guidance was provided for MOVES modeling by Gil Grodzinsky and Jon Morton of the Georgia Environmental Protection Division Air Protection Branch. We thank Charles Huling, formerly of Southern Company, for his input.

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Correspondence to Lucas RF Henneman.

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Henneman, L.R., Chang, H.H., Liao, K. et al. Accountability assessment of regulatory impacts on ozone and PM2.5 concentrations using statistical and deterministic pollutant sensitivities. Air Qual Atmos Health 10, 695–711 (2017).

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  • Air pollution modeling
  • Sensitivity
  • Accountability
  • Statistical modeling