风场对江淮地区颗粒物的影响分析
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摘要
文章根据江淮地区气象资料和污染物质量浓度资料,分析风向、风速等气象要素对颗粒物质量浓度的影响。研究发现,江淮地区受PM_(2.5)污染程度高于PM_(10)。春季各风向所占比例较均匀,风速适中,较好的扩散条件使得空气优良比例居多;夏季主导风向转为东风至南风,携带较清洁西太平洋暖湿气流,使得空气优良比例较多;秋、冬季西北、北、东北风向所占比例较高,不良扩散条件和气流输送使得空气污染比例增高,占比达到55.6%。颗粒物对风速敏感程度分析研究表明,春、夏、冬季敏感风速较大,秋季较小;春、夏、冬季皖北与沿江城市的颗粒物对风速敏感程度较小,敏感风速为5.0～5.7 m/s,需要较大风速才具有强扩散和稀释能力;江淮之间及皖南对风速敏感程度较大,敏感风速为2.2～3.0 m/s,具有相对较好扩散和稀释能力。对一次典型污染过程的研究发现,风对空气污染过程起到促进作用,风速为2.0～4.0 m/s的偏北风将北方颗粒物运输至江淮地区,且主要为高空传输。
Based on the analysis of meteorological and air pollutant concentration data in Yangtze-Huaihe region, the influence of wind direction, wind speed and other information on the concentration of particulate matter was studied. The study found that the extent of PM_(2.5) pollution in this region was higher than that of PM_(10). In spring, the wind directions were relatively average, the wind speed was moderate, and there were more days with good air quality. The summer wind direction changed from southeast to south, and the proportion of good air quality was higher with warm and humid air flows from the Western Pacific. The NE, N, NW wind direction ratio accounted for autumn and winter was the highest and the pollution ratio is 55.6% due to poor diffusion conditions. The analysis of the sensitivity of particles to wind speeds revealed that the sensitive wind speeds in spring, summer and winter were relatively high, and that in autumn was relatively low. In spring, summer and winter, particles in Bozhou, Bengbu, Huainan, Ma'anshan, Chizhou and Tongling were less sensitive to wind speed, the sensitive wind speed ranged from 5.0 m/s to 5.7 m/s, and high wind speed was required for good diffusion and dilution. Particles in Suzhou, Lu'an, Hefei, Huangshan and Xuancheng were relatively more sensitive to wind speed, the sensitive wind speed ranged from 2.2 m/s to 3.0 m/s, with relatively good diffusion and dilution. In a typical pollution process, it was found that the wind contributed to the pollution process. The northern particles were transported to this region by the northerly wind with a wind speed of 2.0-4.0 m/s, and were mainly transported in high altitude.
Based on the analysis of meteorological and air pollutant concentration data in Yangtze-Huaihe region, the influence of wind direction, wind speed and other information on the concentration of particulate matter was studied. The study found that the extent of PM_(2.5) pollution in this region was higher than that of PM_(10). In spring, the wind directions were relatively average, the wind speed was moderate, and there were more days with good air quality. The summer wind direction changed from southeast to south, and the proportion of good air quality was higher with warm and humid air flows from the Western Pacific. The NE, N, NW wind direction ratio accounted for autumn and winter was the highest and the pollution ratio is 55.6% due to poor diffusion conditions. The analysis of the sensitivity of particles to wind speeds revealed that the sensitive wind speeds in spring, summer and winter were relatively high, and that in autumn was relatively low. In spring, summer and winter, particles in Bozhou, Bengbu, Huainan, Ma'anshan, Chizhou and Tongling were less sensitive to wind speed, the sensitive wind speed ranged from 5.0 m/s to 5.7 m/s, and high wind speed was required for good diffusion and dilution. Particles in Suzhou, Lu'an, Hefei, Huangshan and Xuancheng were relatively more sensitive to wind speed, the sensitive wind speed ranged from 2.2 m/s to 3.0 m/s, with relatively good diffusion and dilution. In a typical pollution process, it was found that the wind contributed to the pollution process. The northern particles were transported to this region by the northerly wind with a wind speed of 2.0-4.0 m/s, and were mainly transported in high altitude.
引文
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[12]刘宇,王式功,尚可政,等.兰州市低空风时空变化特征及其与空气污染的关系[J].高原气象,2002,21(3):322-326.
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[14]胡江波,王云鹏,杨利霞,等.汉中市空气污染特征及其气象条件分析[J].陕西气象,2016(6):31-34.
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[16]COURYA C,DILLNER A M.Trends and sources of particulate matter in the Superstition Wilderness using air trajectory and aerosol cluster analysis[J].Atmospheric Environment,2007,41:9309-9323.
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[20]BANTA R M,SENFF C J,ALVAREZ R J,et al.Dependence of daily peak O3concentrations near Houston,Texas on environmental factors:wind speed,temperature,and boundary-layer depth[J].Atmospheric Environment,2011,45:162-173.
[21]石春娥,邓学良,杨元建,等.2013年1月安徽持续性霾天气成因分析[J].气候与环境研究,2014,19(2):227-236.
[22]石春娥,邓学良,杨元建,等.1992-2013年安徽省酸雨变化特征及成因分析[J].南京大学学报(自然科学),2015,51(3):508-516.
[23]吕鑫,郝连秀,郭庆彪.安徽省空气质量时空分布特征分析[J].长江科学院院报,2016,33(12):144-147.
[24]张浩,谢伟,石春娥,等.安徽省霾天气变化特征及影响因素[C]//第26届中国气象学会年会大气成分与天气气候及环境变化分会场论文集.杭州:[出版者不详],2009:7-10.
[25]环境保护部科技标准司.环境空气质量评价技术规范(试行):HJ 663-2013[S].北京:中国环境科学出版社,2013:7-10.
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[27]王东霞,娜日苏,李健.包头市气象因素对空气自动监测结果的影响分析[J].环境与发展,2009,21(3):86-90.
[28]环境保护部科技标准司.环境空气质量指数(AQI)技术规定(试行):HJ 633-2012[S].北京:中国环境科学出版社,2012:2-3.
[29]霍彦峰,邓学良,杨关盈,等.传输指数在合肥市重污染过程中的应用分析[J].环境科学学报,2017,37(4):1277-1286.
[30]郭勇涛,佘峰,王式功,等.兰州市空气质量状况及与常规气象条件的关系[J].干旱区资源与环境,2011,25(11):100-105.
[31]赵娟.ArcGIS插值方法对比及其在云南省土壤污染状况调查中的应用[J].环境科学导刊,2010,29(增刊1):85-87.
[32]董晓华,薄会娟,邓霞,等.降雨空间插值方法及在清江流域的应用[J].三峡大学学报(自然科学版),2009,31(6):6-10.
[33]范玉洁,余新晓,张红霞,等.降雨资料Kriging与IDW插值对比分析:以漓江流域为例[J].水文,2014,34(6):61-66.
[34]周琰,刘宣飞,李智.海洋锋海表风速最小值及其成因[J].热带气象学报,2017,33(2):167-176.
[35]赵军平,罗玲,郑亦佳,等.G20峰会期间杭州地区空气质量特征及气象条件分析[J].环境科学学报,2017,37(10):3885-3893.
[36]王自发,李丽娜,吴其重,等.区域输送对北京夏季臭氧浓度影响的数值模拟研究[J].自然杂志,2008,30(4):194-198.
[37]石琳琳,李令军,李倩,等.2016年北京市春节大气颗粒物污染特征激光雷达监测分析[J].环境科学,2017,38(10):4092-4099.
[38]包青,贺军亮,查勇,等.结合激光雷达分析2014年春季南京地区一次大气污染过程[J].环境科学,2015,36(4):1187-1194.
[39]王珊,廖婷婷,王莉莉,等.西安一次霾重污染过程大气环境特征及气象条件影响分析[J].环境科学学报,2015,35(11):3452-3462.
[40]张钰伊,吴非,储文超.利用Hysplit模式探究长江三角洲冬春季霾的来源及其成因[J].普洱学院学报,2016,32(3):4-8.
[2]TAO M H,CHEN L F,WANG Z F,et al.A study of urban pollution and haze clouds over northern China during the dusty season based on satellite and surface observations[J].Atmospheric Environment,2014,82(19):183-192.
[3]王章明,汪家权,胡淑恒.合肥市机动车尾气排放特征及分担率的研究[J].合肥工业大学学报(自然科学版),2018,41(4):539-544.
[4]RAMANATHAN V,CRUTZEN P J,LELIEVELD J,et al.The Indian Ocean experiment:an integrated analysis of the climate forcing and effects of the great Indo-Asian haze[J].J Geophys Res,2001,106(22):371-398.
[5]RAMANATHAN V,RAMANA M V.Atmospheric brown clouds:long-range transport and climate impacts[J].Air and Waste Management Association’s Magazine for Environmental Managers,2003,12:28-33.
[6]邹长伟,黄虹,杨帆,等.大气颗粒物和气态污染物的降雨清除效率及影响因素[J].环境科学与技术,2017(1):133-140.
[7]杨超,徐洁玲,李恒,等.九江市PM2.5时间变化特征及其与气象要素的关系[J].江西科学,2016,34(6):790-794.
[8]AKKOYUNLU B O,TAYANC M.Analyses of wet and bulk deposition in four different regions of Istanbul,Turkey[J].Atmospheric Environment,2003,37(25):3571-3579.
[9]陈渤黎,吴建秋,吴晶璐,等.2012-2014年常州市空气质量与气象要素关系分析[J].气象与减灾研究,2015,38(3):68-74.
[10]张欢,高云.昌吉市空气质量现状及影响因素分析[J].新疆环境保护,2016,38(2):27-30.
[11]王丽.城市近地层风分布特征及其对大气污染的影响[J].农业与技术,2017,37(20):232,251.
[12]刘宇,王式功,尚可政,等.兰州市低空风时空变化特征及其与空气污染的关系[J].高原气象,2002,21(3):322-326.
[13]李名升,任晓霞,于洋,等.中国大陆城市PM2.5污染时空分布规律[J].中国环境科学,2016,36(3):641-650.
[14]胡江波,王云鹏,杨利霞,等.汉中市空气污染特征及其气象条件分析[J].陕西气象,2016(6):31-34.
[15]OCAK S,TURALIOGLU F S.Relationship between air pollutants and some meteorological parameters in Erzurum,Turkey[M]//Global Warming.Boston:Springer,2010:485-499.
[16]COURYA C,DILLNER A M.Trends and sources of particulate matter in the Superstition Wilderness using air trajectory and aerosol cluster analysis[J].Atmospheric Environment,2007,41:9309-9323.
[17]BORGE R,LUMBRERAS J,VARDOULAKIS S,et al.A-nalysis of long-range transport influences on urban PM10using two-stage atmospheric trajectory clusters[J].Atmospheric Environment,2007,41(21):4434-4450.
[18]COHEN D D,CRAWFORD J,STELCER E,et al.Long range transport of fine particle windblown soils and coal fired power station emissions into Hanoi between 2001to2008[J].Atmospheric Environment,2010,44(31):3761-3769.
[19]WANG F,CHEN D S,CHENG S Y,et al.Identification of regional atmospheric PM10transport pathways using HY-SPLIT,MM5-CMAQ and synoptic pressure pattern analysis[J].Environmental Modelling&Software,2010,25(8):927-934.
[20]BANTA R M,SENFF C J,ALVAREZ R J,et al.Dependence of daily peak O3concentrations near Houston,Texas on environmental factors:wind speed,temperature,and boundary-layer depth[J].Atmospheric Environment,2011,45:162-173.
[21]石春娥,邓学良,杨元建,等.2013年1月安徽持续性霾天气成因分析[J].气候与环境研究,2014,19(2):227-236.
[22]石春娥,邓学良,杨元建,等.1992-2013年安徽省酸雨变化特征及成因分析[J].南京大学学报(自然科学),2015,51(3):508-516.
[23]吕鑫,郝连秀,郭庆彪.安徽省空气质量时空分布特征分析[J].长江科学院院报,2016,33(12):144-147.
[24]张浩,谢伟,石春娥,等.安徽省霾天气变化特征及影响因素[C]//第26届中国气象学会年会大气成分与天气气候及环境变化分会场论文集.杭州:[出版者不详],2009:7-10.
[25]环境保护部科技标准司.环境空气质量评价技术规范(试行):HJ 663-2013[S].北京:中国环境科学出版社,2013:7-10.
[26]环境保护部科技标准司.环境空气质量标准:GB 3095-2012[S].北京:中国环境科学出版社,2012:3.
[27]王东霞,娜日苏,李健.包头市气象因素对空气自动监测结果的影响分析[J].环境与发展,2009,21(3):86-90.
[28]环境保护部科技标准司.环境空气质量指数(AQI)技术规定(试行):HJ 633-2012[S].北京:中国环境科学出版社,2012:2-3.
[29]霍彦峰,邓学良,杨关盈,等.传输指数在合肥市重污染过程中的应用分析[J].环境科学学报,2017,37(4):1277-1286.
[30]郭勇涛,佘峰,王式功,等.兰州市空气质量状况及与常规气象条件的关系[J].干旱区资源与环境,2011,25(11):100-105.
[31]赵娟.ArcGIS插值方法对比及其在云南省土壤污染状况调查中的应用[J].环境科学导刊,2010,29(增刊1):85-87.
[32]董晓华,薄会娟,邓霞,等.降雨空间插值方法及在清江流域的应用[J].三峡大学学报(自然科学版),2009,31(6):6-10.
[33]范玉洁,余新晓,张红霞,等.降雨资料Kriging与IDW插值对比分析:以漓江流域为例[J].水文,2014,34(6):61-66.
[34]周琰,刘宣飞,李智.海洋锋海表风速最小值及其成因[J].热带气象学报,2017,33(2):167-176.
[35]赵军平,罗玲,郑亦佳,等.G20峰会期间杭州地区空气质量特征及气象条件分析[J].环境科学学报,2017,37(10):3885-3893.
[36]王自发,李丽娜,吴其重,等.区域输送对北京夏季臭氧浓度影响的数值模拟研究[J].自然杂志,2008,30(4):194-198.
[37]石琳琳,李令军,李倩,等.2016年北京市春节大气颗粒物污染特征激光雷达监测分析[J].环境科学,2017,38(10):4092-4099.
[38]包青,贺军亮,查勇,等.结合激光雷达分析2014年春季南京地区一次大气污染过程[J].环境科学,2015,36(4):1187-1194.
[39]王珊,廖婷婷,王莉莉,等.西安一次霾重污染过程大气环境特征及气象条件影响分析[J].环境科学学报,2015,35(11):3452-3462.
[40]张钰伊,吴非,储文超.利用Hysplit模式探究长江三角洲冬春季霾的来源及其成因[J].普洱学院学报,2016,32(3):4-8.
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