globalchange  > 气候变化事实与影响
DOI: 10.1016/j.atmosenv.2015.06.026
Scopus记录号: 2-s2.0-84930678811
论文题名:
Understanding interannual variations of biomass burning from Peninsular Southeast Asia, part I: Model evaluation and analysis of systematic bias
作者: Dong X; , Fu J; S
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 116
起始页码: 293
结束页码: 307
语种: 英语
英文关键词: Biomass burning ; Interannual variation ; Peninsular Southeast Asia ; WRF/CMAQ
Scopus关键词: Air quality ; Biomass ; Dust ; Storms ; Surface measurement ; Weather forecasting ; Anthropogenic emissions ; Biomass burning emissions ; Biomass-burning ; Community multi-scale air quality models ; Interannual variation ; Southeast Asia ; Weather research and forecasting models ; WRF/CMAQ ; Uncertainty analysis ; air quality ; annual variation ; anthropogenic source ; biomass burning ; concentration (composition) ; dust storm ; emission inventory ; ground-based measurement ; model validation ; population distribution ; satellite data ; spatial data ; urban population ; World Bank ; Article ; biomass ; dust ; electric power plant ; evaluation study ; human ; industrial area ; plume ; population density ; population distribution ; priority journal ; simulation ; Southeast Asia ; statistical bias ; surface property ; systematic error ; urban area ; Far East ; Southeast Asia
Scopus学科分类: Environmental Science: Water Science and Technology ; Earth and Planetary Sciences: Earth-Surface Processes ; Environmental Science: Environmental Chemistry
英文摘要: The Weather Research and Forecasting model and the Community Multiscale Air Quality model (WRF/CMAQ) modeling system was applied over Peninsular Southeast Asia (PSEA) and East Asia (EA) for 5 consecutive years from 2006 to 2010 in March and April to understand the PSEA biomass burning for its interannual variations, transport pathway, and impacts at local and downwind areas. As many of the modeling applications over PSEA or EA were usually evaluated with limited regional or local observations focusing on short simulation periods, in this work we incorporated ground surface measurements from multiple networks covering different sub-regions and satellite retrievals to comprehensively examine the performance of WRF/CMAQ and probe into the possible uncertainties of the modeling system. We found increasing simulation discrepancy for CO, NO2, and SO2 from 2006 to 2010 at south part of PSEA (≤17°N) due to outmoded anthropogenic emission in INTEX-B, while local surface observations and CO2 emission data from World Bank suggested substantial growth of anthropogenic emission over PSEA during the 5 years. The spatial allocation of emission based on population distribution was also found to introduce large uncertainty with overestimation at populated urban area and underestimation at industry area. Over north PSEA (>17°N) CMAQ systematically overestimated CO, surface NO2, troposheric column NO2 by around 6%-20%, 8-15%, and 40%-50% respectively, indicating positive bias within the biomass burning emission due to overestimated emission factor as suggested by OMI retrievals. At EA, despite moderate overestimations for surface NO2 and SO2 by 20%-30% and moderate underestimation for AOD by 30%-50%, no significant temporal trend was found. We found CMAQ underestimated PM10 concentrations at north and northeast EA by 50%-60% due to impact of dust storm, yet the dust plume rise scheme within the model was unable to reproduce it. Our results suggested that an urgent research effort is needed for updating the anthropogenic emission of PSEA countries, and the dust emission module within CMAQ need further improvement for applications over EA. © 2015 Elsevier Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81585
Appears in Collections:气候变化事实与影响

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作者单位: Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, TN, United States

Recommended Citation:
Dong X,, Fu J,S. Understanding interannual variations of biomass burning from Peninsular Southeast Asia, part I: Model evaluation and analysis of systematic bias[J]. Atmospheric Environment,2015-01-01,116
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