Impact of model grid spacing on regional- and urban- scale air quality predictions of organic aerosol

被引:49
作者
Stroud, C. A. [1 ]
Makar, P. A. [1 ]
Moran, M. D. [1 ]
Gong, W. [1 ]
Gong, S. [1 ]
Zhang, J. [1 ]
Hayden, K. [1 ]
Mihele, C. [1 ]
Brook, J. R. [1 ]
Abbatt, J. P. D. [2 ]
Slowik, J. G. [2 ]
机构
[1] Environm Canada, Air Qual Res Div, Toronto, ON, Canada
[2] Univ Toronto, Dept Chem, Toronto, ON M5S 1A1, Canada
关键词
UNITED-STATES; ALPHA-PINENE; OZONE; SENSITIVITY; SIMULATION; EMISSIONS; MASS; OZONOLYSIS; RESOLUTION; FLUX;
D O I
10.5194/acp-11-3107-2011
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Regional-scale chemical transport model predictions of urban organic aerosol to date tend to be biased low relative to observations, a limitation with important implications for applying such models to human exposure health studies. We used a nested version of Environment Canada's AURAMS model (42- to- 15- to- 2.5-km nested grid spacing) to predict organic aerosol concentrations for a temporal and spatial domain corresponding to the Border Air Quality and Meteorology Study (BAQS-Met), an air-quality field study that took place in the southern Great Lakes region in the summer of 2007. The use of three different horizontal grid spacings allowed the influence of this parameter to be examined. A domain-wide average for the 2.5-km domain and a matching 15-km subdomain yielded very similar organic aerosol averages (4.8 vs. 4.3 mu g m(-3), respectively). On regional scales, secondary organic aerosol dominated the organic aerosol composition and was adequately resolved by the 15-km model simulation. However, the shape of the organic aerosol concentration histogram for the Windsor urban station improved for the 2.5-km simulation relative to those from the 42- and 15-km simulations. The model histograms for the Bear Creek and Harrow rural stations were also improved in the high concentration "tail" region. As well the highest-resolution model results captured the midday 4 July organic-aerosol plume at Bear Creek with very good temporal correlation. These results suggest that accurate simulation of urban and large industrial plumes in the Great Lakes region requires the use of a high-resolution model in order to represent urban primary organic aerosol emissions, urban VOC emissions, and the secondary organic aerosol production rates properly. The positive feedback between the secondary organic aerosol production rate and existing organic mass concentration is also represented more accurately with the highest-resolution model. Not being able to capture these finer-scale features may partly explain the consistent negative bias reported in the literature when urban-scale organic aerosol evaluations are made using coarser-scale chemical transport models.
引用
收藏
页码:3107 / 3118
页数:12
相关论文
共 47 条
[21]   Impact of vegetative emissions on urban ozone and biogenic secondary organic aerosol: Box model study for Berlin, Germany [J].
Bonn, Boris ;
von Schneidemesser, Erika ;
Butler, Tim ;
Churkina, Galina ;
Ehlers, Christian ;
Grote, Ruediger ;
Klemp, Dieter ;
Nothard, Rainer ;
Schaefer, Klaus ;
von Stuelpnagel, Albrecht ;
Kerschbaumer, Andreas ;
Yousefpour, Rasoul ;
Fountoukis, Christos ;
Lawrence, Mark G. .
JOURNAL OF CLEANER PRODUCTION, 2018, 176 :827-841
[22]   Multiphase Reactions of Hydrocarbons Into an Air Quality Model With CAMx-UNIPAR: Impacts of Humidity and NOx on Secondary Organic Aerosol Formation in the Southern USA [J].
Jo, Yujin ;
Jang, Myoseon ;
Madhu, Azad ;
Choi, Jiwon ;
Park, Jinsoo .
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2024, 16 (10)
[23]   Multi-scale modeling of roadway air quality impacts: Development and evaluation of a Plume-in-Grid model [J].
Briant, Regis ;
Seigneur, Christian .
ATMOSPHERIC ENVIRONMENT, 2013, 68 :162-173
[24]   Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality [J].
Trail, M. ;
Tsimpidi, A. P. ;
Liu, P. ;
Tsigaridis, K. ;
Hu, Y. ;
Nenes, A. ;
Russell, A. G. .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2013, 6 (05) :1429-1445
[25]   A preliminary study of turbulent coherent structures and ozone air quality in Seoul using the WRF-CMAQ model at a 50 m grid spacing [J].
Han, Beom-Soon ;
Baik, Jong-Jin ;
Kwak, Kyung-Hwan .
ATMOSPHERIC ENVIRONMENT, 2019, 218
[26]   A LONG-TERM ASSESSMENT OF THE IMPACT OF NATURAL GAS PRODUCTION IN NORTH TEXAS INFLUENCING URBAN AND REGIONAL AIR QUALITY [J].
John, Kuruvilla ;
Lim, Guo Quan ;
Kanayankottupoyil, Jithin .
PROCEEDINGS OF ASME 2021 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION (IMECE2021), VOL 8A, 2021,
[27]   Modeling organic aerosols over east China using a volatility basis-set approach with aging mechanism in a regional air quality model [J].
Han, Zhiwei ;
Xie, Zuxin ;
Wang, Gehui ;
Zhang, Renjian ;
Tao, Jun .
ATMOSPHERIC ENVIRONMENT, 2016, 124 :186-198
[28]   Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study [J].
Chen, Jianjun ;
Ying, Qi ;
Kleeman, Michael J. .
ATMOSPHERIC ENVIRONMENT, 2010, 44 (10) :1331-1340
[29]   Impact of Marcellus Shale Natural Gas Development in Southwest Pennsylvania on Volatile Organic Compound Emissions and Regional Air Quality [J].
Swarthout, Robert F. ;
Russo, Rachel S. ;
Zhou, Yong ;
Miller, Brandon M. ;
Mitchell, Brittney ;
Horsman, Emily ;
Lipsky, Eric ;
McCabe, David C. ;
Baum, Ellen ;
Sive, Barkley C. .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2015, 49 (05) :3175-3184
[30]   A two-way coupled regional urban-street network air quality model system for Beijing, China [J].
Wang, Tao ;
Liu, Hang ;
Li, Jie ;
Wang, Shuai ;
Kim, Youngseob ;
Sun, Yele ;
Yang, Wenyi ;
Du, Huiyun ;
Wang, Zhe ;
Wang, Zifa .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2023, 16 (19) :5585-5599