Climate Change Data Portal
DOI | 10.1021/es5050248 |
Temporalization of Peak Electric Generation Particulate Matter Emissions during High Energy Demand Days | |
Farkas, Caroline M.1; Moeller, Michael D.1; Felder, Frank A.2; Baker, Kirk R.3; Rodgers, Mark4; Carlton, Annmarie G.1 | |
发表日期 | 2015-04-07 |
ISSN | 0013-936X |
卷号 | 49期号:7页码:4696-4704 |
英文摘要 | Underprediction of peak ambient pollution by air quality models hinders development of effective strategies to protect health and welfare. The U.S. Environmental Protection Agencys 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. |
语种 | 英语 |
WOS记录号 | WOS:000352659000083 |
来源期刊 | ENVIRONMENTAL SCIENCE & TECHNOLOGY
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来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/57805 |
作者单位 | 1.Rutgers State Univ, Dept Environm Sci, New Brunswick, NJ 08901 USA; 2.Rutgers State Univ, Bloustein Sch Planning & Publ Policy, Ctr Energy Econ & Environm Policy, New Brunswick, NJ 08901 USA; 3.US EPA, Off Air Qual Planning & Stand, Res Triangle Pk, NC 27711 USA; 4.Rutgers State Univ, Dept Ind & Syst Engn, Piscataway, NJ 08854 USA |
推荐引用方式 GB/T 7714 | Farkas, Caroline M.,Moeller, Michael D.,Felder, Frank A.,et al. Temporalization of Peak Electric Generation Particulate Matter Emissions during High Energy Demand Days[J]. 美国环保署,2015,49(7):4696-4704. |
APA | Farkas, Caroline M.,Moeller, Michael D.,Felder, Frank A.,Baker, Kirk R.,Rodgers, Mark,&Carlton, Annmarie G..(2015).Temporalization of Peak Electric Generation Particulate Matter Emissions during High Energy Demand Days.ENVIRONMENTAL SCIENCE & TECHNOLOGY,49(7),4696-4704. |
MLA | Farkas, Caroline M.,et al."Temporalization of Peak Electric Generation Particulate Matter Emissions during High Energy Demand Days".ENVIRONMENTAL SCIENCE & TECHNOLOGY 49.7(2015):4696-4704. |
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