该研究以武汉及其周边地区为研究区域,基于2014年武汉市本地化高分辨率大气污染排放清单,采用CMAQ空气质量模式及CMAQ-DDM(Decoupled Direct Method,三维去耦合直接法)敏感性分析模块,探究和揭示了武汉市大气污染的时空分布特征及各地...该研究以武汉及其周边地区为研究区域,基于2014年武汉市本地化高分辨率大气污染排放清单,采用CMAQ空气质量模式及CMAQ-DDM(Decoupled Direct Method,三维去耦合直接法)敏感性分析模块,探究和揭示了武汉市大气污染的时空分布特征及各地区的排放贡献,并进一步结合FLEXPART (Flexible Particle Dispersion Mode)-WRF模式模拟了不同典型月份潜在影响的排放源区分布。结果表明,印痕模型及空气质量模式互为补充和相互验证,可为污染来源解析提供有力的技术支撑。研究发现,武汉市PM_(2.5)的污染具有区域性特征且存在季节性差异,污染严重的地区主要集中在武汉市中部,并呈现1月份PM_(2.5)污染最严重,7月份PM_(2.5)污染最轻的特征;以武汉地区及周边为研究区域,研究区域外对国控点PM_(2.5)的贡献大于研究区域内贡献,且1月份受研究区域外的影响最大,7月份最小,其中沉湖七壕受区域外其他城市贡献最大,青山钢花受武汉市本地贡献最大;1、4、10 3个月PM_(2.5)的潜在源区主要集中在武汉市东北及东南部包括河南南部及安徽西部等地,其中4月和10月受来自东南部地区的潜在影响较重;7月份潜在源区主要集中在西南部,包括湖南东北部等地。展开更多
We integrated Enviro-HIRLAM(Environment-High Resolution Limited Area Model)meteorological output into FLEXPART(FLEXible PARTicle dispersion model).A FLEXPART simulation requires meteorological input from a numerical w...We integrated Enviro-HIRLAM(Environment-High Resolution Limited Area Model)meteorological output into FLEXPART(FLEXible PARTicle dispersion model).A FLEXPART simulation requires meteorological input from a numerical weather prediction(NWP)model.The publicly available version of FLEXPART can utilize either ECMWF(European Centre for Medium-range Weather Forecasts)Integrated Forecast System(IFS)forecast or reanalysis NWP data,or NCEP(U.S.National Center for Environmental Prediction)Global Forecast System(GFS)forecast or reanalysis NWP data.The primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological fields.We compared backward trajectories gener-ated with FLEXPART using Enviro-HIRLAM(both with and without aerosol effects)to trajectories generated using NCEP GFS and ECMWF IFS meteorological inputs,for a case study of a heavy haze event which occurred in Beijing,China in November 2018.We found that results from FLEXPART were considerably different when using different meteorological inputs.When aerosol effects were included in the NWP,there was a small but noticeable differ-ence in calculated trajectories.Moreover,when looking at potential emission sensitivity instead of simply expressing trajectories as lines,additional information,which may have been missed when looking only at trajectories as lines,can be inferred.展开更多
基金the Jenny and Antti Wihuri Foundation project,with the grant for“Air pollution cocktail in Gigacity”Funding was also received from the Research Council of Finland(formerly the Academy of Finland,AoF)project 311932 and applied towards this project+1 种基金Partially,funding included contribution from EU Horizon 2020 CRiceS project“Climate relevant interactions and feedbacks:the key role of sea ice and snow in the polar and global climate system”under grant agreement No 101003826and AoF project ACCC“The Atmosphere and Climate Competence Center”under grant agreement No 337549.
文摘We integrated Enviro-HIRLAM(Environment-High Resolution Limited Area Model)meteorological output into FLEXPART(FLEXible PARTicle dispersion model).A FLEXPART simulation requires meteorological input from a numerical weather prediction(NWP)model.The publicly available version of FLEXPART can utilize either ECMWF(European Centre for Medium-range Weather Forecasts)Integrated Forecast System(IFS)forecast or reanalysis NWP data,or NCEP(U.S.National Center for Environmental Prediction)Global Forecast System(GFS)forecast or reanalysis NWP data.The primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological fields.We compared backward trajectories gener-ated with FLEXPART using Enviro-HIRLAM(both with and without aerosol effects)to trajectories generated using NCEP GFS and ECMWF IFS meteorological inputs,for a case study of a heavy haze event which occurred in Beijing,China in November 2018.We found that results from FLEXPART were considerably different when using different meteorological inputs.When aerosol effects were included in the NWP,there was a small but noticeable differ-ence in calculated trajectories.Moreover,when looking at potential emission sensitivity instead of simply expressing trajectories as lines,additional information,which may have been missed when looking only at trajectories as lines,can be inferred.
