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首页> 外文期刊>Stochastic environmental research and risk assessment >Evaluation and potential improvements of WRF/CMAQ in simulating multi-levels air pollution in megacity Shanghai, China
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Evaluation and potential improvements of WRF/CMAQ in simulating multi-levels air pollution in megacity Shanghai, China

机译:WRF / CMAQ在模拟上海特大城市多级空气污染中的评估及潜在改进

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摘要

The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO2 (from 2 to 14%) and for PM10 (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO2 in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO2 and 19% for NO2 decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future.
机译:大气数值模型的准确性对于预测城市大气污染具有重要意义。这项研究调查并量化了多级空气污染期间气象和空气质量模型的不确定性。我们使用WRF / CMAQ(天气研究和预测模型以及社区多尺度空气质量模型)在2012年无污染和重污染事件中模拟了中国特大城市的空气质量。天气预报模型无法再现地表温度气溶胶负荷高时的风速空气质量模型的准确性显示出明显的下降趋势,即从良好的空气质量状况到严重污染的事件。在城市和郊区,SO2(从2%增至14%)和PM10的PM10(从1%增至33%),从城市的CO(从8%增至48%),绝对模型偏差从轻度空气污染显着增加%)和郊区站点的NO2(从1到58%)。将城市机盖模型方案应用于WRF模型的测试表明,在预测气象领域方面有相当不错的改进,但对空气污染物的影响较小(仅在城市地区发现的模型偏差中,SO2减少6%,NO2减少19%) )。这项研究为模型性能对空气污染水平的敏感性提供了明确的证据。建议将该影响视为模型评估中模型偏差的来源,并在将来改进模型开发。

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  • 作者单位

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

    Shanghai Environm Monitoring Ctr, Shanghai 200030, Peoples R China;

    Shanghai Environm Monitoring Ctr, Shanghai 200030, Peoples R China;

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

    Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200433, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Environmental modeling; Model evaluation; WRF; CMAQ; Pollution-meteorology interaction; Model uncertainty;

    机译:环境建模;模型评估;WRF;CMAQ;污染-气象相互作用;模型不确定性;

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