天津污染天气边界层温度层结变化特征及预报阈值确定
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摘要
针对天津市大气污染防治需求,基于2016年4月1日—2017年3月31日天津255 m气象塔观测资料及数值模拟,开展天津地区污染天气边界层温度层结变化特征及预报阈值研究.结果表明:(1)天津地区10~250 m高度的气温递减率为0.56℃/100 m,当日均气温递减率小于0.4℃/100 m时,垂直扩散条件不利于大气污染物扩散,出现中度以上污染概率为64%,重污染概率为47%.从温度廓线和逆温频率统计分析,贴地逆温占所有逆温的55%,除贴地逆温以外逆温底部最易出现在160 m的高度,大量脱地逆温的出现不利于高架源夜间的排放.(2)每年10月—次年2月天津逆温频率为20%,冬季需要关注逆温情况对大气污染物扩散的影响.如秋、冬季8:00逆温仍然存在,重污染天气出现概率高达56%,中度及以上污染出现概率为72%,是重污染天气辨识的重要指标.(3)7:00—10:00在逆温消散或者日均气温递减率由0.6℃/100 m向0.4℃/100 m变化时,任何细微变化对大气垂直扩散有显著影响.基于天津地区PM_(2.5)污染情况下,数值模拟显示10~250 m的气温递减率由于气溶胶的存在可减少0.06℃/100 m,在25个重污染过程中,日均气温递减率平均下降0.18℃/100 m,对大气垂直扩散条件产生显著影响.因此,在空气污染预报分析时使用不考虑气溶胶辐射效应的天气模式分析温度层结,需要适当调整阈值,尤其是在7:00—10:00逆温消散及垂直温度递减率由0.6℃/100 m向0.4℃/100 m变化时.
Based on the observation data and numerical simulation in Tianjin from March,2016 to April,2017. The research of threshold and regularity of temperature stratification under heavy pollution weather situation was conducted in Tianjin. The result showed that: 1) The average temperature difference was 0.56 ℃/100 m between10 and 250 m. If the value of temperature difference was less than 0. 4 ℃/100 m,the vertical diffusion condition was not conducive to the diffusion of air pollutants. Meanwhile,the probability of moderate pollution was 64%,and the probability of heavy pollution was 47%. On the basis of statistics and analysis of the temperature profile and inversion probability,the inversion temperature on ground accounted for 55% of all inversion temperature,In addition to inversion temperature on ground,the bottom of inversion was most likely to appear at the height of 160 m. At night,a large number of inversion were not good for the diffusion of air pollutants about elevated sources. 2) The inversion frequency in Tianjin from October to February was 20%. The value was 1.63 times higher it between March and September. In winter,the influence of temperature inversion on air pollutant dispersion should be paid more attention. If the temperature inversion still existed at 8 AM,the probability of heavy pollution weather was 56%,which wasan important indicator of heavy pollution weather. 3) When the inversion temperature collapses from 7 AM to 10 AM,or the vertical temperature lapse rate varied from 0.4 ℃/100 m to 0.6 ℃/100 m,any slight changes would bring a significant effect on atmospheric vertical diffusion. Considering the PM_(2.5) mass concentration in Tianjin,model simulation showed that the temperature lapse rate between 250 m to10 m reduced by 0.06 ℃/100 m due to aerosols.The value can even drop to 0.18 ℃/100 m in heavy pollution condition. It had a significant influence on atmospheric vertical diffusion conditions. It was necessary to adjust the threshold when analyzing the temperature stratification by the weather model without considering the aerosol radiation effect,especially when the inversion temperature collapsed from 7 AM to 10 AM and the vertical temperature lapse rate varied from 0.6 ℃/100 m to 0.4 ℃/100 m.
Based on the observation data and numerical simulation in Tianjin from March,2016 to April,2017. The research of threshold and regularity of temperature stratification under heavy pollution weather situation was conducted in Tianjin. The result showed that: 1) The average temperature difference was 0.56 ℃/100 m between10 and 250 m. If the value of temperature difference was less than 0. 4 ℃/100 m,the vertical diffusion condition was not conducive to the diffusion of air pollutants. Meanwhile,the probability of moderate pollution was 64%,and the probability of heavy pollution was 47%. On the basis of statistics and analysis of the temperature profile and inversion probability,the inversion temperature on ground accounted for 55% of all inversion temperature,In addition to inversion temperature on ground,the bottom of inversion was most likely to appear at the height of 160 m. At night,a large number of inversion were not good for the diffusion of air pollutants about elevated sources. 2) The inversion frequency in Tianjin from October to February was 20%. The value was 1.63 times higher it between March and September. In winter,the influence of temperature inversion on air pollutant dispersion should be paid more attention. If the temperature inversion still existed at 8 AM,the probability of heavy pollution weather was 56%,which wasan important indicator of heavy pollution weather. 3) When the inversion temperature collapses from 7 AM to 10 AM,or the vertical temperature lapse rate varied from 0.4 ℃/100 m to 0.6 ℃/100 m,any slight changes would bring a significant effect on atmospheric vertical diffusion. Considering the PM_(2.5) mass concentration in Tianjin,model simulation showed that the temperature lapse rate between 250 m to10 m reduced by 0.06 ℃/100 m due to aerosols.The value can even drop to 0.18 ℃/100 m in heavy pollution condition. It had a significant influence on atmospheric vertical diffusion conditions. It was necessary to adjust the threshold when analyzing the temperature stratification by the weather model without considering the aerosol radiation effect,especially when the inversion temperature collapsed from 7 AM to 10 AM and the vertical temperature lapse rate varied from 0.6 ℃/100 m to 0.4 ℃/100 m.
引文
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樊琦,段献忠,蔡志盛,等.2008.华南地区逆温个例的数值模拟研究[J].中山大学学报(自然科学版),47(1):103-107
葛跃,王明新,孙向武,等.2017.基于增强回归树的城市PM2.5日均值变化分析:以常州为例[J].环境科学,38(2):485-494
Han S,Cai Z,Zhang Y,et al.2015.Long-term trends in fog and boundary layer characteristics in Tianjin,China[J].Particuology,20(3):61-68
Han S,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].The Science of the tota Environment,616-617:135
Han S,Zhang Y,Wu J,et al.2015.Evaluation of regional background particulate matter concentration based on vertical distribution characteristics[J].Atmospheric Chemistry&Physics,15(19):14889-14921
郝子龙,蔡恒明,王慧鹏,等.2014.面向WRF/Chem模式MOSAIC气溶胶方案的资料同化实现[J].气象水文海洋仪器,31(4):1-6
JoséR S,Pérez J L,Balzarini A,et al.2015.Sensitivity of feedback effects in CBMZ/MOSAIC chemical mechanism[J].Atmospheric Environment,115:646-656
蒋瑞宾,吴永莲.1990.北京冬季城、郊辐射逆温的分析[J].气象,16(1):33-36
李浩文,张阿思,步巧利,等.2017.2015年干季佛山一次重空气污染过程形成机理研究[J].环境科学学报,37(8):3044-3053
李梦,唐贵谦,黄俊,等.2015.京津冀冬季大气混合层高度与大气污染的关系[J].环境科学,36(6):1935-1943
李小庆,王鹏飞,李子华.1988.河流对雾形成和发展过程的影响[J].大气科学学报,(4):433-442
廖晓农,孙兆彬,唐宜西,等.2015.高空偏北风背景下北京地区高污染形成的环境气象机制研究[J].环境科学,36(3):801-808
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刘超,花丛,张恒德,等.2017.L波段探空雷达秒数据在污染天气边界层分析中的应用[J].气象,43(5):591-597
陆春松,牛生杰,杨军,等.2008.南京冬季平流雾的生消机制及边界层结构观测分析[J].大气科学学报,31(4):520-529
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
潘锦秀,朱彬,晏平仲,等.2016.京津冀区域重污染天气过程数值预报评估新方法[J].环境科学学报,36(8):2752-2760
孙兆彬,李梓铭,廖晓农,等.2017.北京大气热力和动力结构对污染物输送和扩散条件的影响[J].中国环境科学,37(5):1693-1705
Tang G,Zhang J,Münkel C,et al.2016.Mixing layer height and the implications for air pollution over Beijing,China[J].Atmospheric Chemistry&Physics,16(4):2459-2475
Tang G,Zhu X,Hu B,et al.2015.Impact of emission controls on air quality in Beijing during APEC 2014:lidar ceilometer observations[J].Atmospheric Chemistry&Physics,15(21):12667-12680
王静,施润和,李龙,等.2015.上海市一次重雾霾过程的天气特征及成因分析[J].环境科学学报,35(5):1537-1546
王跃思,姚利,刘子锐,等.2013.京津冀大气霾污染及控制策略思考[J].中国科学院院刊,(3):353-363
王自发,李杰,王哲,等.2013.2013年1月我国中东部强霾污染的数值模拟和防控对策[J].中国科学:地球科学,44(1):3-14
吴蒙,吴兑,范绍佳.2015.基于风廓线仪等资料的珠江三角洲污染气象条件研究[J].环境科学学报,35(3):619-626
熊亚军,廖晓农,李梓铭,等.2015.KNN数据挖掘算法在北京地区霾等级预报中的应用[J].气象,41(1):98-104
徐敬,马志强,赵秀娟,等.2015.边界层方案对华北低层O3垂直分布模拟的影响[J].应用气象学报,26(5):567-577
薛文博,付飞,王金南,等.2014.基于全国城市PM2.5达标约束的大气环境容量模拟[J].中国环境科学,34(10):2490-2496
薛亦峰,周震,聂滕,等.2016.2015年12月北京市空气重污染过程分析及污染源排放变化[J].环境科学,37(5):1593-1601
颜娇珑,张武,单云鹏,等.2016.西北东部霾的时空特征与天气特征研究[J].高原气象,35(4):1073-1086
杨洋,王红磊,侯雪伟,等.2017.石家庄一次持续性霾过程形成原因及气溶胶垂直探空分析[J].环境科学学报,37(3):824-832
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
张人禾,李强,张若楠.2014.2013年1月中国东部持续性强雾、霾天气产生的气象条件分析[J].中国科学:地球科学,44(1):27-36
张小曳,孙俊英,王亚强等.2013.我国雾-霾成因及其治理的思考[J].科学通报,44(13):1178-1187
Zhu X,Tang G,Hu B,et al.2016.Regional pollution and its formation mechanism over North China Plain:A case study with ceilometer observations and model simulations[J].Journal of Geophysical Research Atmospheres,121(24):1-15
陈燕,蒋维楣,郭文利,等.2005.珠江三角洲地区城市群发展对局地大气污染物扩散的影响[J].环境科学学报,25(5):700-710
蔡子颖,姚青,韩素芹,等.2017.气溶胶直接气候效应对天津气象和空气质量的影响[J].中国环境科学,37(3):908-914
邓涛,邓雪娇,吴兑,等.2012.珠三角灰霾数值预报模式与业务运行评估[J].气象科技进展,2(6):38-44
邓雪娇,吴兑,唐浩华,等.2007.南岭山地一次锋面浓雾过程的边界层结构分析[J].高原气象,26(4):881-889
樊琦,段献忠,蔡志盛,等.2008.华南地区逆温个例的数值模拟研究[J].中山大学学报(自然科学版),47(1):103-107
葛跃,王明新,孙向武,等.2017.基于增强回归树的城市PM2.5日均值变化分析:以常州为例[J].环境科学,38(2):485-494
Han S,Cai Z,Zhang Y,et al.2015.Long-term trends in fog and boundary layer characteristics in Tianjin,China[J].Particuology,20(3):61-68
Han S,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].The Science of the tota Environment,616-617:135
Han S,Zhang Y,Wu J,et al.2015.Evaluation of regional background particulate matter concentration based on vertical distribution characteristics[J].Atmospheric Chemistry&Physics,15(19):14889-14921
郝子龙,蔡恒明,王慧鹏,等.2014.面向WRF/Chem模式MOSAIC气溶胶方案的资料同化实现[J].气象水文海洋仪器,31(4):1-6
JoséR S,Pérez J L,Balzarini A,et al.2015.Sensitivity of feedback effects in CBMZ/MOSAIC chemical mechanism[J].Atmospheric Environment,115:646-656
蒋瑞宾,吴永莲.1990.北京冬季城、郊辐射逆温的分析[J].气象,16(1):33-36
李浩文,张阿思,步巧利,等.2017.2015年干季佛山一次重空气污染过程形成机理研究[J].环境科学学报,37(8):3044-3053
李梦,唐贵谦,黄俊,等.2015.京津冀冬季大气混合层高度与大气污染的关系[J].环境科学,36(6):1935-1943
李小庆,王鹏飞,李子华.1988.河流对雾形成和发展过程的影响[J].大气科学学报,(4):433-442
廖晓农,孙兆彬,唐宜西,等.2015.高空偏北风背景下北京地区高污染形成的环境气象机制研究[J].环境科学,36(3):801-808
Lin M,Holloway T,Carmichael G R,et al.2010.Quantifying pollution inflow and outflow over East Asia in spring with regional and globa models[J].Atmospheric Chemistry&Physics,10(1):4221-4239
刘超,花丛,张恒德,等.2017.L波段探空雷达秒数据在污染天气边界层分析中的应用[J].气象,43(5):591-597
陆春松,牛生杰,杨军,等.2008.南京冬季平流雾的生消机制及边界层结构观测分析[J].大气科学学报,31(4):520-529
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
潘锦秀,朱彬,晏平仲,等.2016.京津冀区域重污染天气过程数值预报评估新方法[J].环境科学学报,36(8):2752-2760
孙兆彬,李梓铭,廖晓农,等.2017.北京大气热力和动力结构对污染物输送和扩散条件的影响[J].中国环境科学,37(5):1693-1705
Tang G,Zhang J,Münkel C,et al.2016.Mixing layer height and the implications for air pollution over Beijing,China[J].Atmospheric Chemistry&Physics,16(4):2459-2475
Tang G,Zhu X,Hu B,et al.2015.Impact of emission controls on air quality in Beijing during APEC 2014:lidar ceilometer observations[J].Atmospheric Chemistry&Physics,15(21):12667-12680
王静,施润和,李龙,等.2015.上海市一次重雾霾过程的天气特征及成因分析[J].环境科学学报,35(5):1537-1546
王跃思,姚利,刘子锐,等.2013.京津冀大气霾污染及控制策略思考[J].中国科学院院刊,(3):353-363
王自发,李杰,王哲,等.2013.2013年1月我国中东部强霾污染的数值模拟和防控对策[J].中国科学:地球科学,44(1):3-14
吴蒙,吴兑,范绍佳.2015.基于风廓线仪等资料的珠江三角洲污染气象条件研究[J].环境科学学报,35(3):619-626
熊亚军,廖晓农,李梓铭,等.2015.KNN数据挖掘算法在北京地区霾等级预报中的应用[J].气象,41(1):98-104
徐敬,马志强,赵秀娟,等.2015.边界层方案对华北低层O3垂直分布模拟的影响[J].应用气象学报,26(5):567-577
薛文博,付飞,王金南,等.2014.基于全国城市PM2.5达标约束的大气环境容量模拟[J].中国环境科学,34(10):2490-2496
薛亦峰,周震,聂滕,等.2016.2015年12月北京市空气重污染过程分析及污染源排放变化[J].环境科学,37(5):1593-1601
颜娇珑,张武,单云鹏,等.2016.西北东部霾的时空特征与天气特征研究[J].高原气象,35(4):1073-1086
杨洋,王红磊,侯雪伟,等.2017.石家庄一次持续性霾过程形成原因及气溶胶垂直探空分析[J].环境科学学报,37(3):824-832
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
张人禾,李强,张若楠.2014.2013年1月中国东部持续性强雾、霾天气产生的气象条件分析[J].中国科学:地球科学,44(1):27-36
张小曳,孙俊英,王亚强等.2013.我国雾-霾成因及其治理的思考[J].科学通报,44(13):1178-1187
Zhu X,Tang G,Hu B,et al.2016.Regional pollution and its formation mechanism over North China Plain:A case study with ceilometer observations and model simulations[J].Journal of Geophysical Research Atmospheres,121(24):1-15
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