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• W797342605 abstract "Many state and local air quality agencies use the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system to determine compliance with the National Ambient Air Quality Standards (NAAQS). Because emission reduction scenarios are tested using CMAQ with an aim of determining the most efficient and cost effective strategies for attaining the NAAQS, it is very important that trace gas concentrations derived by CMAQ are accurate. Overestimating concentrations can literally translate into billions of dollars lost by commercial and government industries forced to comply with the standards. Costly health, environmental and socioeconomic problems can result from concentration underestimates. Unfortunately, lightning modeling for CMAQ is highly oversimplified. This leads to very poor estimates of lightning-produced nitrogen oxides (= NO + NO2) which directly reduces the accuracy of the concentrations of important CMAQ trace gases linked to NOx concentrations such as ozone and methane. Today it is known that lightning is the most important NOx source in the upper troposphere with a global production rate estimated to vary between 2-20 Tg(N)/yr. In addition, NOx indirectly influences our climate since it controls the concentration of ozone and hydroxyl radicals (OH) in the atmosphere. Ozone is an important greenhouse gas and OH controls the oxidation of various greenhouse gases. We describe a robust NASA lightning model, called the Lightning Nitrogen Oxides Model (LNOM) that combines state-of-the-art lightning measurements, empirical results from field studies, and beneficial laboratory results to arrive at a realistic representation of lightning NOx production for CMAQ. NASA satellite lightning data is used in conjunction with ground-based lightning detection systems to assure that the best representation of lightning frequency, geographic location, channel length, channel altitude, strength (i.e., channel peak current), and number of strokes per flash are accounted for. LNOM combines all of these factors in a straightforward approach that is easily implemented into CMAQ. We anticipate that future applications of LNOM will produce significant and important changes in CMAQ trace gas concentrations for various regions and times. We also anticipate that these changes will have a direct impact on decision makers responsible for NAAQS attainment." @default.
• W797342605 created "2016-06-24" @default.
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• W797342605 date "2009-01-11" @default.
• W797342605 modified "2023-09-27" @default.
• W797342605 title "A NASA Lightning Parameterization for CMAQ" @default.
• W797342605 hasPublicationYear "2009" @default.
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