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Temporalization of peak electric generation particulate matter emissions during high energy demand days.
Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Baker, Kirk R; Rodgers, Mark; Carlton, Annmarie G.
Afiliación
  • Farkas CM; †Department of Environmental Science, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08901, United States.
  • Moeller MD; †Department of Environmental Science, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08901, United States.
  • Felder FA; ‡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.
  • Baker KR; §Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States.
  • Rodgers M; ∥Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, 96 Frelinghuysen Road, Piscataway, New Jersey 08854, United States.
  • Carlton AG; †Department of Environmental Science, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08901, United States.
Environ Sci Technol ; 49(7): 4696-704, 2015 Apr 07.
Article en En | MEDLINE | ID: mdl-25705922
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Centrales Eléctricas / Material Particulado Tipo de estudio: Prognostic_studies País/Región como asunto: America do norte Idioma: En Revista: Environ Sci Technol Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Centrales Eléctricas / Material Particulado Tipo de estudio: Prognostic_studies País/Región como asunto: America do norte Idioma: En Revista: Environ Sci Technol Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos