Sensitivity assessment of PM2.5 simulation to the below-cloud washout schemes in an atmospheric chemical transport model

Xingcheng Lu, J. Fung
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引用次数: 8

Abstract

Abstract This study analyses the sensitivity of PM2.5 simulation and source apportionment results by integrating different below-cloud washout (BCW) schemes from various models into the CAMx model during the rainy days (3–13 September 2010). Furthermore, this study has also considered the influence of different raindrop size distribution parameterizations on the simulation. PM2.5 time series, spatial maps and the average concentration of the study region using different BCW schemes are presented. Our results show that different BCW schemes can cause over 50 μg m−3 discrepancies in a PM2.5 simulation during the heavy rain periods. The source apportionment (, and ) results for some cities (e.g. Hong Kong) are also sensitive to the choice of the BCW scheme. After implementing the composition dependent BCW coefficients calculated by using the field observation data, the PM2.5 simulation performance was improved and mean bias was reduced to 0.5 μg m−3 during the study period. Future BCW studies should focus on the effects caused by aerosol compositions and raindrop size distributions in order to produce reliable simulation results for the rainy season.
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大气化学输送模式中PM2.5模拟对云下冲刷方案的敏感性评估
本文通过将不同模式的云下冲洗(BCW)方案整合到CAMx模型中,分析了PM2.5模拟和源分配结果的敏感性。此外,本文还考虑了不同雨滴大小分布参数化对模拟的影响。给出了不同BCW方案下研究区PM2.5的时间序列、空间图和平均浓度。结果表明,不同的BCW方案对暴雨期PM2.5模拟的影响大于50 μg m−3。一些城市(例如香港)的源分配(和)结果对BCW方案的选择也很敏感。采用利用野外观测数据计算的成分相关BCW系数,提高了PM2.5模拟性能,研究期间平均偏差降至0.5 μg m−3。为了获得可靠的雨季模拟结果,未来的BCW研究应重点关注气溶胶成分和雨滴大小分布对BCW的影响。
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