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

• Published in: Air quality, atmosphere and health Vol. 10; no. 6; pp. 695 - 711
• Main Authors: Henneman, Lucas RF, Chang, Howard H, Liao, Kuo-Jen, Lavoué, David, A Mulholland, James, Russell, Armistead G
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2017; Springer Nature B.V
• Subjects: Accountability; Air pollution; Air quality; Atmospheric Protection/Air Quality Control/Air Pollution; Clean Air Act-US; Earth and Environmental Science; Emissions; Environment; Environmental Health; Environmental monitoring; Health Promotion and Disease Prevention; Human influences; Medical personnel; Methods; Nitrogen oxides; Nitrogen oxides emissions; Outdoor air quality; Ozone; Particulate emissions; Particulate matter; Pollutants; Pollution; Pollution levels; Pollution monitoring; Public health; Sensitivity; Statistical methods; Statistics; Air pollution modeling; Sensitivity; Statistical modeling; Accountability
• ISSN: 1873-9318; 1873-9326
• DOI: 10.1007/s11869-017-0463-2

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 (O 3 ) and particulate matter with diameters less than 2.5 μ m (PM 2.5 ) 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 O 3 , 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 O 3 (PM 2.5 ) 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 O 3 and PM 2.5 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 O 3 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 O 3 concentration where the sensitivity to NO x emissions changes sign.