A mixed integer programming model for National Ambient Air Quality Standards (NAAQS) attainment strategy analysis. (May 2017)

• Record Type: Journal Article
• Authors: Macpherson, Alexander J.; Simon, Heather; Langdon, Robin; Misenheimer, David
• Is Part Of: Environmental modelling & software. Volume 91(2017)
• Page Start: 13
• Page End: 27
• Publication Date: 2017-05
• Subjects: Air quality -- Ozone -- Optimization -- Pollution control -- Control strategy -- Attainment strategy; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.01.008
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The United States federal government establishes National Ambient Air Quality Standards (NAAQS) for six pollutants, including ozone. States with areas designated in nonattainment of the standards are required to develop State Implementation Plans (SIPs) to demonstrate how pollution levels will be reduced to meet the standards. Historically, most states have developed SIPs independently. However, for ozone and other air pollutants, some states have agreed to cooperate to address regional pollution problems. These types of cooperative efforts have the potential to improve pollution control efficiency. We present a mathematical programming model that can help identify potential minimum-cost emissions control strategies that employ regional strategies. We present a series of national-level applications using information from a set of air quality simulations along with spatially and technologically detailed emissions control information. The model quickly evaluates alternative attainment planning scenarios, tests regional strategies, and identifies monitors that potentially have significant influence on attainment strategies. Highlights: We present a national-level model that optimizes multipollutant emissions control strategies. The model combines detailed air quality and emissions control information. Marginal values of emission constraints estimate the influence of controlling monitors on attainment strategies. The model is potentially useful for states in exploring collaborative strategies for air quality management.