title: Cost analysis of impacts of climate change on regional air quality.
abstract: Climate change has been predicted to adversely impact regional air quality with resulting health effects. Here a regional air quality model and a technology analysis tool are used to assess the additional emission reductions required and associated costs to offset impacts of climate change on air quality. Analysis is done for six regions and five major cities in the continental United States. Future climate is taken from a global climate model simulation for 2049-2051 using the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario, and emission inventories are the same as current ones to assess impacts of climate change alone on air quality and control expenses. On the basis of the IPCC A1B emission scenario and current control technologies, least-cost sets of emission reductions for simultaneously offsetting impacts of climate change on regionally averaged 4th highest daily maximum 8-hr average ozone and yearly averaged PM2.5 (particulate matter [PM] with an aerodynamic diameter less than 2.5 microm) for the six regions examined are predicted to range from $36 million (1999$) yr(-1) in the Southeast to $5.5 billion yr(-1) in the Northeast. However, control costs to offset climate-related pollutant increases in urban areas can be greater than the regional costs because of the locally exacerbated ozone levels. An annual cost of $4.1 billion is required for offsetting climate-induced air quality impairment in 2049-2051 in the five cities alone. Overall, an annual cost of $9.3 billion is estimated for offsetting climate change impacts on air quality for the six regions and five cities examined. Much of the additional expense is to reduce increased levels of ozone. Additional control costs for offsetting the impacts everywhere in the United States could be larger than the estimates in this study. This study shows that additional emission controls and associated costs for offsetting climate impacts could significantly increase currently estimated control requirements and should be considered in developing control strategies for achieving air quality targets in the future.
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0512, USA. kuojenliao@gmail.com
authors.forename: Kuo-Jen
authors.initials: KJ
authors.lastname: Liao
authors.forename: Efthimios
authors.initials: E
authors.lastname: Tagaris
authors.forename: Armistead G
authors.initials: AG
authors.lastname: Russell
authors.forename: Praveen
authors.initials: P
authors.lastname: Amar
authors.forename: Shan
authors.initials: S
authors.lastname: He
authors.forename: Kasemsan
authors.initials: K
authors.lastname: Manomaiphiboon
authors.forename: Jung-Hun
authors.initials: JH
authors.lastname: Woo
mesh_terms: D000395:Air Pollutants, Occupational / Q000032:analysis; D000397:Air Pollution / Q000191:economics* / Q000706:statistics & numerical data*; D016902:Air Pollution, Indoor; D000465:Algorithms; D003365:Costs and Cost Analysis; D057232:Global Warming; D015233:Models, Statistical; D010083:Oxidants, Photochemical / Q000032:analysis; D010126:Ozone / Q000032:analysis; D014481:United States
chemical_list: D000395:Air Pollutants, Occupational; D010083:Oxidants, Photochemical; D010126:Ozone