Evaluation of on-road vehicle CO and NOx National Emission Inventories using an urban-scale source-oriented air quality model. Kota, S. H., Zhang, H., Chen, G., Schade, G. W., & Ying, Q. ATMOSPHERIC ENVIRONMENT, 85:99-108, PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, MAR, 2014.
doi  abstract   bibtex   
The MOBILE6.2 model was replaced by the Motor Vehicle Emission Simulator (MOVES) in 2012 as an official tool recommended by the United States Environmental Protection Agency (US EPA) to predict vehicular pollutant emission factors. In this study, on-road vehicle emission inventories of CO and NOx for Southeast Texas generated by MOVES and MOBILE6.2 in two versions of the 2005 National Emission Inventory (NEI) were studied by comparing predicted CO and NOx using the EPA's Community Multiscale Air Quality (CMAQ) Model incorporated with a source-oriented gas phase chemical mechanism with measurements made at six urban and industrial sites in Southeast Texas. The source tracing technique allows direct determination of contributions of on-road vehicles to overall CO and NOx concentrations and identification of ambient concentration measurements which are mostly impacted by vehicle emissions. By grouping the fractional bias (FB) values of the hourly predictions based on vehicle contributions to total CO or NOx concentrations, clear trends in the FB were observed, indicating systematic biases in the emission inventory for these species. Data points dominated by vehicle emissions suggest that surface CO concentrations due to vehicle exhaust are significantly over-estimated by a factor of 2 using either MOVES or MOBILE6.2. NOx concentrations are overestimated by approximately 20-35% and 70% by using the MOBILE6.2 and MOVES emissions, respectively. Emission scaling runs show that a domain-wide reduction of MOBILE6.2 CO emissions by 60% and NOx emissions by 15-25% leads to better model performance of exhaust CO and NOx concentrations in the current study. (C) 2013 Elsevier Ltd. All rights reserved.
@article{ WOS:000331417700012,
Author = {Kota, Sri Harsha and Zhang, Hongliang and Chen, Gang and Schade, Gunnar
   W. and Ying, Qi},
Title = {{Evaluation of on-road vehicle CO and NOx National Emission Inventories
   using an urban-scale source-oriented air quality model}},
Journal = {{ATMOSPHERIC ENVIRONMENT}},
Year = {{2014}},
Volume = {{85}},
Pages = {{99-108}},
Month = {{MAR}},
Abstract = {{The MOBILE6.2 model was replaced by the Motor Vehicle Emission Simulator
   (MOVES) in 2012 as an official tool recommended by the United States
   Environmental Protection Agency (US EPA) to predict vehicular pollutant
   emission factors. In this study, on-road vehicle emission inventories of
   CO and NOx for Southeast Texas generated by MOVES and MOBILE6.2 in two
   versions of the 2005 National Emission Inventory (NEI) were studied by
   comparing predicted CO and NOx using the EPA's Community Multiscale Air
   Quality (CMAQ) Model incorporated with a source-oriented gas phase
   chemical mechanism with measurements made at six urban and industrial
   sites in Southeast Texas. The source tracing technique allows direct
   determination of contributions of on-road vehicles to overall CO and NOx
   concentrations and identification of ambient concentration measurements
   which are mostly impacted by vehicle emissions.
   By grouping the fractional bias (FB) values of the hourly predictions
   based on vehicle contributions to total CO or NOx concentrations, clear
   trends in the FB were observed, indicating systematic biases in the
   emission inventory for these species. Data points dominated by vehicle
   emissions suggest that surface CO concentrations due to vehicle exhaust
   are significantly over-estimated by a factor of 2 using either MOVES or
   MOBILE6.2. NOx concentrations are overestimated by approximately 20-35\%
   and 70\% by using the MOBILE6.2 and MOVES emissions, respectively.
   Emission scaling runs show that a domain-wide reduction of MOBILE6.2 CO
   emissions by 60\% and NOx emissions by 15-25\% leads to better model
   performance of exhaust CO and NOx concentrations in the current study.
   (C) 2013 Elsevier Ltd. All rights reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ying, Q (Corresponding Author), Texas A\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77845 USA.
   Kota, Sri Harsha; Zhang, Hongliang; Chen, Gang; Ying, Qi, Texas A\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77845 USA.
   Schade, Gunnar W., Texas A\&M Univ, Dept Atmospher Sci, College Stn, TX 77845 USA.}},
DOI = {{10.1016/j.atmosenv.2013.11.020}},
ISSN = {{1352-2310}},
EISSN = {{1873-2844}},
Keywords = {{Source apportionment; CMAQ; MOVES; MOBILE6.2; National Emission
   Inventory (NEI); Urban-scale air quality modeling}},
Keywords-Plus = {{SECONDARY ORGANIC AEROSOL; PARTICULATE MATTER; SOURCE APPORTIONMENT;
   POLLUTION; MOBILE6.2; MORTALITY; RATIOS; IMPACT; OZONE; MOVES}},
Research-Areas = {{Environmental Sciences \& Ecology; Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Environmental Sciences; Meteorology \& Atmospheric Sciences}},
Author-Email = {{qying@civil.tamu.edu}},
ResearcherID-Numbers = {{Schade, Gunnar/G-9000-2012
   Zhang, Hongliang/C-2499-2012
   }},
ORCID-Numbers = {{Schade, Gunnar/0000-0003-4327-0839
   Zhang, Hongliang/0000-0002-1797-2311
   Ying, Qi/0000-0002-4560-433X
   Kota, Sri/0000-0002-1977-2954}},
Funding-Acknowledgement = {{U.S. Environmental Protection Agency's Science to Achieve Results (STAR)
   programUnited States Environmental Protection Agency; U.S. Environmental
   Protection Agency's STAR programUnited States Environmental Protection
   Agency {[}R834556]}},
Funding-Text = {{This research has been partially supported by a grant from the U.S.
   Environmental Protection Agency's Science to Achieve Results (STAR)
   program. Although the research described in the article has been funded
   in part by the U.S. Environmental Protection Agency's STAR program
   through grant (R834556), it has not been subjected to any EPA review and
   therefore does not necessarily reflect the views of the Agency, and no
   official endorsement should be inferred.}},
Number-of-Cited-References = {{36}},
Times-Cited = {{45}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{88}},
Journal-ISO = {{Atmos. Environ.}},
Doc-Delivery-Number = {{AA9MN}},
Unique-ID = {{WOS:000331417700012}},
DA = {{2021-12-02}},
}

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