Abstract
Abstract. This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).
Highlights
Atmospheric pollution due to particulate matter (PM) has raised worldwide attention for its relationship with environmental and public health issues (Fuzzi et al, 2015; Nel, 2005)
China and India are the top two countries suffering from outdoor air pollution, which altogether accounted for 20 % of global mortality caused by PM2.5 exposure in 2010 (Lelieveld et al, 2015)
The models involved in this study include the Weather Research and Forecasting Model (WRF) coupled with Community Multiscale Air Quality (CMAQ) modeling, the Regional Atmospheric Modeling System coupled with CMAQ (RAMSCMAQ), WRF model coupled with chemistry (WRF-Chem) (v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASAUnified WRF (NU-WRF)
Summary
Atmospheric pollution due to particulate matter (PM) has raised worldwide attention for its relationship with environmental and public health issues (Fuzzi et al, 2015; Nel, 2005). Outdoor PM2.5 pollution is estimated to cause 2.1– 5.2 million premature deaths worldwide annually (Lelieveld et al, 2015; Rao et al, 2012; Silva et al, 2013). It accounted for 8 % of global mortality in 2015 and ranks fifth in the list of global mortality risk (Cohen et al, 2017). China and India are the top two countries suffering from outdoor air pollution, which altogether accounted for 20 % of global mortality caused by PM2.5 exposure in 2010 (Lelieveld et al, 2015). The impact evaluation of PM pollution is of high uncertainty due to the unclearness of the toxicity of PM components (Lippmann, 2014) and difficulty in the measurement and prediction of PM concentrations
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