新型垂直探测资料在污染天气分析中的应用
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摘要
针对2017年1月上旬广州地区出现的一次持续时间长的重污染天气过程,基于地面观测资料、激光雷达、风廓线雷达和微波辐射计数据,从水平和垂直扩散条件2个方面分析了此次污染过程的形成和维持的原因.结果表明:(1)本次污染过程期间,广州地区地面风速基本为小于2m/s的偏北风,在300m高度以下普遍存在平均水平风速低于2.6m/s的小风层;污染前期640m高度内的各层回流指数廓线小于0.6,100m高度小于0.4,污染缓解后回流指数高于0.7.(2)地面PM_(2.5)浓度与逆温强度的相关系数为0.42,过程平均逆温厚度167m,平均逆温强度为1.08℃/100m;(3)PM_(2.5)浓度与边界层高度的相关系数为-0.56,清洁时段的平均边界层高度(876m)约为污染时段(620m)的1.4倍,过程最低边界层高度为267m;PM_(2.5)浓度与边界层通风量的相关系数为-0.61,清洁时段的平均边界层通风量(2538m~2/s)约为污染时段(1136m~2/s)的2.2倍,使用边界层通风量能更好表征大气污染的程度.
A long-lasting air pollution episode was occurred in Guangzhou in early January 2017. Based on the data set of ground observation, Lidar, wind profiler and microwave radiometer, the formation mechanism of this episode was investigated and discussed from two aspects of horizontal and vertical diffusion conditions. The results showed that:(1) During the pollution process, the surface wind speed in Guangzhou area was basically northerly wind and less than 2m/s. A small wind speed layer with an average wind speed less than 2.6m/s was below 300m; The return index profile of each layer within the height of 640 m in the pre-pollution period was less than 0.6, and within the 100 m height was less than 0.4.(2) The correlation coefficient between surface PM_(2.5)mass concentration and inversion temperature was 0.42. The average temperature during the polluted period was 167 m, and the average inversion temperature was 1.08°C/100 m.(3) The correlation coefficient between PM_(2.5) mass concentration and the boundary layer height was-0.56, and the average boundary layer height(876m) during the clean period was approximately 1.4times higher than that of the polluted period(620m). The minimum boundary layer height during the process was 267 m. The boundary layer ventilation showed a higher anti-correlation with PM_(2.5) concentration(-0.61), and the average boundary layer ventilation volume(2538m~2/s) during clean period was 2.2times of the polluted period(1136m~2/s), indicating that the boundary layer ventilation can be more useful to characterize the degree of atmospheric pollution.
A long-lasting air pollution episode was occurred in Guangzhou in early January 2017. Based on the data set of ground observation, Lidar, wind profiler and microwave radiometer, the formation mechanism of this episode was investigated and discussed from two aspects of horizontal and vertical diffusion conditions. The results showed that:(1) During the pollution process, the surface wind speed in Guangzhou area was basically northerly wind and less than 2m/s. A small wind speed layer with an average wind speed less than 2.6m/s was below 300m; The return index profile of each layer within the height of 640 m in the pre-pollution period was less than 0.6, and within the 100 m height was less than 0.4.(2) The correlation coefficient between surface PM_(2.5)mass concentration and inversion temperature was 0.42. The average temperature during the polluted period was 167 m, and the average inversion temperature was 1.08°C/100 m.(3) The correlation coefficient between PM_(2.5) mass concentration and the boundary layer height was-0.56, and the average boundary layer height(876m) during the clean period was approximately 1.4times higher than that of the polluted period(620m). The minimum boundary layer height during the process was 267 m. The boundary layer ventilation showed a higher anti-correlation with PM_(2.5) concentration(-0.61), and the average boundary layer ventilation volume(2538m~2/s) during clean period was 2.2times of the polluted period(1136m~2/s), indicating that the boundary layer ventilation can be more useful to characterize the degree of atmospheric pollution.
引文
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[12]邓涛,吴兑,邓雪娇,等.一次严重灰霾过程的气溶胶光线特性垂直分布[J].中国环境科学,2013,33(11):1779-1784.Deng T,Wu D,Deng X J,et al.The vertical distribution of aerosol optical properties in a severe haze event.China Environmental Science,2013,33(11):1921-1928.
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[15]王耀庭,苗世光,张小玲.基于激光雷达的北京市气溶胶光学参数季节特征[J].中国环境科学,2016,36(4):970-978.Wang Y T,Miao S G,Zhang X L.Seasonal characteristics of the aerosol optical parameters based on lidar over the Beijing Area[J].China Environmental Science,2016,36(4):970-978.
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[17]张舒婷,苏德斌,徐文静,等.利用风廓线雷达资料对北京地区边界层日变化特征的分析研究[J].大气与环境光学学报,2017,12(1):1-7.Zhang S T,Su D B,Xu W J,et al.Analysis and research on daily variation characteristics of boundary layer in beijing area by wind profile radar data[J].Journal of Atmospheric and Environmental optics,2017,12(1):1-7.
[18]花丛,刘超,张恒德.风廓线雷达资料在北京秋季雾霾天气过程分析中的应用[J].气象科技,2017,45(5):870-875.Hua C,Liu C,Zhang H D.Application of wind profile radar in analyzing autumn fog and haze process in Beijing[J].Meteorological Science and Technology,2017,45(5):870-875.
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[21]高晓荣,谭浩波,邓涛,等.三种激光雷达监测污染物分布和输送对比[J].中国环境科学,2018,38(2):444-454.Gao X R,Tan H B,Deng T,et al.Experimental results comparative analysis of pollutant distribution and transport by different kinds of lidar[J].china environmental science,2018,38(2):444-454.
[22]贺千山,毛节泰.北京城市大气混合层与气溶胶垂直分布观测研究[J].气象学报,2005,63(3):374-384.He Q S,Mao J T.Observation of urban mixed layer at Beijing using a micro pulse lidar[J].Acta Meteorological Sinica,2005,63(3):374-384.
[23]Fernald F G.Analysis of atmospheric lidar observations:some comments[J].Applied optics,1984,23(5):652-653.
[24]王琳,谢晨波,韩永,等.测量大气边界层高度的激光雷达数据反演方法研究[J].大气与环境光学学报,2012,7(4):241-247.Wang L,Xie C B,Han Y,et al.Comparison of retrieval methods of planetary boundary layer height from lidar data[J].Journal of Atmospheric and Environmental optics,2012,7(4):241-247.
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