The causes of severely polluted weather in Tianjin from 2014 to 2017 were studied based on WRF/Chem model by decomposing the impact of horizontal transport, turbulent mixing and vertical motion on near-surface air pollution with CO as a tracer.The findings showed that horizontal transport, turbulent mixing and vertical motion of severely polluted weather can be quantitatively described, and attribution analysis was conducted on the values of causes of severely polluted weather based on the above method.For example, the severely polluted weather on January 26, 2017 was mainly caused by decreasing turbulent mixing ability; That on February 12, 2017 by decreasing mixing layer thickness; That on February 16, 2017 by horizontal transmission; That on February 16, 2017 by decreasing downdraft and turbulent mixing capacity and mixing layer thickness.In the analysis, the meteorological conditions that are prone to severely polluted weather are formed as follows:rate of decrease of CO mass concentration per hour caused by turbulent mixing is less than 40%, the rate of increase of CO mass concentration per hour caused by vertical movement more than 1.4%, the mixed layer thickness less than 250 m, and the rate of decrease of surface CO mass concentration per hour caused by horizontal diffusion less than zero.Up to 99 of 116 severely polluted days from 2014 to 2017 met one or more of the above conditions, covering 85% of all the severe pollution processes.Although some failed to meet any of the above conditions, 99% of the processes can be interpreted as per the analysis standard for severely polluted weather.As shown by the analysis, 58% of the processes were caused by two or three meteorological factors which are closely related to weather types, such as the pollution in the rear of high pressure and horizontal transport, the pollution caused by weak high pressure from north and sinking motion.Compared with horizontal transport and the decreasing turbulent mixing capacity, the rise of near-surface air pollutant mass concentration caused by sinking motion is often neglected.However, in some processes, the rise of near-surface air pollutant mass concentration may also be caused by sinking motion, making it an important influencing factor for the formation of severely polluted weather, such as January 1011, 2014.The turbulent diffusion coefficient KZ and the hourly decrease rate of surface CO mass concentration caused by turbulent mixing β show a good power exponential relationship with the near-surface PM2.5 mass concentration, with the correlation coefficients of 0.57 and 0.73 respectively, which can play an active role in the cause analysis and prediction of severe pollution.
[1]Li M, Zhang Q, Streets D G, et al, 2014.Mapping Asian anthropogenic emissions of non-methane volatile organic compounds to multiple chemical mechanisms[J].Atmospheric Chemistry & Physics, 14(11):32649-32701.
[2]Zhao H Y, Zhang Q, Davis S J, et al, 2014.Assessment of China's virtual air pollution transport embodied in trade by a consumption-based emission inventory[J].Atmospheric Chemistry & Physics, 14(12):6815-6815.
[3]Gao Y, Zhang M, Liu Z, et al, 2015.Modeling the feedback between aerosol and meteorological variables in the atmospheric boundary layer during a severe fog-haze event over the North China Plain[J].Atmospheric Chemistry & Physics, 15(8):1093-1130.
[4]Cheng X H, Xiang de X U, Ding G A, et al, 2009.Differences in MM5 and WRF Meteorological Field Simulations and Impact on Air Quality Forecasting by CMAQ Model[J].Research of Environmental Sciences, 22(12):1411-1419.
[5]Han S Q, Hao T Y, Zhang Y F, et al, 2017.Vertical observation and analysis on rapid formation and evolutionary mechanisms of a prolonged haze episode over central-eastern China.[J].Science of the Total Environment, 135:616-617.
[6]Li L, Cheng S, Li J, et al, 2013.Application of MM5-CAMx-PSAT modeling approach for investigating emission source contribution to atmospheric SO<sub>2</sub> Pollution in Tangshan, Northern China[J].Mathematical Problems in Engineering, 2013(4):707-724.
[7]Liu X H, Zhang Y, Xing J, et al, 2010.Understanding of regional air pollution over China using CMAQ, part Ⅱ.Process analysis and sensitivity of ozone and particulate matter to precursor emissions[J].Atmospheric Environment, 44(30):3719-3727.
[8]Mu M, Zhang R H, 2014.Addressing the issue of fog and haze:A promising perspective from meteorological science and technology[J].Science China Earth Sciences, 57(1):1-2.
[9]Yang Y, Wang J, Gong S, et al, 2015.PLAM-a meteorological pollution index for air quality and its applications in fog-haze forecasts in north China[J].Atmospheric Chemistry & Physics, 15(6):9077-9106.
[10]Zheng B, Huo H, Zhang Q, et al, 2014.High-resolution mapping of vehicle emissions in China in 2008[J].Atmospheric Chemistry & Physics, 14(18):9787-9805.
[11]蔡子颖, 韩素芹, 汪靖, 等, 2017.基于天气背景天津地区重污染天气特征分析[J].环境科学学报, 37(10):3906-3917.
[12]蔡子颖, 姚青, 韩素芹, 等, 2017.21世纪以来天津细颗粒物气象扩散能力趋势分析[J].中国环境科学, 37(6):2040-2046.
[13]韩永翔, 宋昊冬, 刘烽, 等, 2016.对流边界层湍流通量及逆梯度输送参数化分析[J].大气科学学报, 39(3):417-425.
[14]胡晓, 徐璐, 俞科爱, 等, 2017.宁波地区一次重污染天气过程的成因分析[J].高原气象, 36(5):1412-1421.DOI:10.7522/j.issn.1000-0534.2016.00098.
[15]郝巨飞, 张功文, 王晓娟, 等, 2017.一次环境大气重污染过程的监测分析[J].高原气象, 36(5):1404-1411.DOI:10.7522/j.issn.1000-0534.2016.00118.
[16]李令军, 王占山, 张大伟, 等, 2016.2013-2014年北京大气重污染特征研究[J].中国环境科学, 36(1):27-35.
[17]毛卓成, 马井会, 许建明, 等, 2015.上海地区持续东风系统控制下污染扩散条件分析[J].气象, 41(7):890-898.
[18]孙兴池, 韩永清, 李静, 等, 2017.垂直运动对雾-霾及空气污染过程的影响分析[J].高原气象, 36(4):1106-1114.DOI:10.7522/j.issn.1000-0534.2016.00076.
[19]尚可政, 王式功, 杨德保, 等, 2001.兰州城区稳定能量及其与空气污染的关系[J].高原气象, 20(1):76-81.
[20]王超, 安兴琴, 翟世贤, 等, 2017.伴随模式在追踪污染事件重点源区中的应用[J].中国环境科学, 37(4):1283-1290.
[21]王丛梅, 杨永胜, 李永占, 等, 2013.2013年1月河北省中南部严重污染的气象条件及成因分析[J].环境科学研究, 26(7):695-702.
[22]王媛林, 李杰, 李昂, 等, 2016.2013-2014年河南省PM<sub>(2.5)</sub>浓度及其来源模拟研究[J].环境科学学报, 36(10):3543-3553.
[23]吴萍, 丁一汇, 柳艳菊, 等, 2016.中国中东部冬季霾日的形成与东亚冬季风和大气湿度的关系[J].气象学报, 74(3):352-366.
[24]许启慧, 范引琪, 井元元, 等, 2017.1972-2013年河北省大气环境容量的气候变化特征分析[J].高原气象, 36(6):1682-1692.DOI:10.7522/j.issn.1000-0534.2016.00133.
[25]杨洪斌, 李元宜, 邹旭东, 等, 2009.辽宁空气中度污染和重污染天气类型分析[J].气象与环境学报, 25(6):15-17.
[26]杨旭, 2017.京津冀地区空气污染特征与气象成因及其预报研究[D].兰州: 兰州大学.
[27]袁媛, 周宁芳, 李崇银, 2017.中国华北雾霾天气与超强El Nino事件的相关性研究[J].地球物理学报, 60(1):11-21.
[28]翟世贤, 2015.GRAPES-CUACE气溶胶模块的伴随构建及模式在大气污染优化控制中的应用[D].北京: 中国气象科学研究院.
[29]张恒德, 吕梦瑶, 张碧辉, 等, 2016.2014年2月下旬京津冀持续重污染过程的静稳天气及传输条件分析[J].环境科学学报, 36(12):4340-4351.
[30]张恒德, 张碧辉, 吕梦瑶, 等, 2017.北京地区静稳天气综合指数的初步构建及其在环境气象中的应用[J].气象, 43(8):998-1004.
[31]张雅斌, 林琳, 吴其重, 等, 2016."13·12"西安重污染气象条件及影响因素[J].应用气象学报, 27(1):35-46.
[32]张瑜, 银燕, 石立新, 等, 2012.华北地区典型污染天大气气溶胶飞机探测个例分析[J].高原气象, 31(5):1432-1438.
