title: Temporalization of peak electric generation particulate matter emissions during high energy demand days.
abstract: Underprediction of peak ambient pollution by air quality models hinders development of effective strategies to protect health and welfare. The U.S. Environmental Protection Agency's community multiscale air quality (CMAQ) model routinely underpredicts peak ozone and fine particulate matter (PM2.5) concentrations. Temporal misallocation of electricity sector emissions contributes to this modeling deficiency. Hourly emissions are created for CMAQ by use of temporal profiles applied to annual emission totals unless a source is matched to a continuous emissions monitor (CEM) in the National Emissions Inventory (NEI). More than 53% of CEMs in the Pennsylvania-New Jersey-Maryland (PJM) electricity market and 45% nationally are unmatched in the 2008 NEI. For July 2006, a United States heat wave with high electricity demand, peak electric sector emissions, and elevated ambient PM2.5 mass, we match hourly emissions for 267 CEM/NEI pairs in PJM (approximately 49% and 12% of unmatched CEMs in PJM and nationwide) using state permits, electricity dispatch modeling and CEMs. Hourly emissions for individual facilities can differ up to 154% during the simulation when measurement data is used rather than default temporalization values. Maximum CMAQ PM2.5 mass, sulfate, and elemental carbon predictions increase up to 83%, 103%, and 310%, at the surface and 51%, 75%, and 38% aloft (800 mb), respectively.
authors.affiliation: †Department of Environmental Science, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08901, United States.
authors.forename: Caroline M
authors.initials: CM
authors.lastname: Farkas
authors.affiliation: †Department of Environmental Science, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08901, United States.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Moeller
authors.affiliation: ‡Center for Energy, Economic and Environmental Policy, Bloustein School of Planning and Public Policy, Rutgers, The State University of New Jersey, 33 Livingston Avenue, New Brunswick, New Jersey 08901, United States.
authors.forename: Frank A
authors.initials: FA
authors.lastname: Felder
authors.affiliation: §Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States.
authors.forename: Kirk R
authors.initials: KR
authors.lastname: Baker
authors.affiliation: ∥Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, 96 Frelinghuysen Road, Piscataway, New Jersey 08854, United States.
authors.forename: Mark
authors.initials: M
authors.lastname: Rodgers
authors.affiliation: †Department of Environmental Science, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08901, United States.
authors.forename: Annmarie G
authors.initials: AG
authors.lastname: Carlton
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D004784:Environmental Monitoring; D008396:Maryland; D008962:Models, Theoretical; D009515:New Jersey; D010126:Ozone / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis*; D010414:Pennsylvania; D011210:Power Plants / Q000706:statistics & numerical data*; D014481:United States; D014484:United States Environmental Protection Agency
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D010126:Ozone