Based on the ozone concentration and the meteorological elements data of the Beijing, Shenyang, Yinchuan, Chengdu, Nanjing and Guangzhou representative cities in 2014 -2016, the variation of ozone concentration and its relationship with meteorological conditions in typical cities were analyzed and compared.The results showed that the average annual ozone concentration from high to low was Nanjing>Shenyang>Beijing>Yinchuan>Chengdu>Guangzhou during 2014 -2016, and during these three years, the ozone concentration of Guangzhou decreased, the ozone concentration of Shenyang changed little, while the ozone concentration generally increased in the other cities, among which Yinchuan increased the most, and Beijing increased the least.The monthly variation of ozone concentration was greatly affected by latitude, the higher latitude, the more obvious the single peak structure of ozone concentration, and the ozone concentration in clean control point was generally higher than that in the urban area in all months.The maximum value of diurnal ozone all appeared at 15:00 (Beijing Time, the same as after)or 16:00 for the 6 cities, and the minimum value mostly appeared at 07:00 or 08:00, but the peak value, the valley value and the daily variation were obviously different in different cities.The ozone in clean control point was significantly higher than that in urban area in Guangzhou all-day, but for another cities, the difference between clean control point and urban area was small during 11:00 -17:00, and the peak concentration of clean control point in Chengdu, Nanjing and Yinchuan was even slightly lower than that in urban areas.The ozone had the strongest correlation with the temperature and sunshine time for all 6 cities, followed by relative humidity and the wind speed.The high temperature, the long sunshine and the low humidity were beneficial to the formation of ozone.In comparison, for the Beijing, Yinchuan and Shenyang with longer sunshine time, the change of ozone was more sensitive to temperature than other cities, and had a weak positive correlation with wind speed, while for the Guangzhou, Nanjing and Chengdu with higher temperature and humidity, the correlation between ozone and sunshine hours and relative humidity was better than that of the other three cities, and ozone is weakly negatively correlated with wind speed.As to regions, the correlation between ozone concentration and meteorological elements in urban was generally better than that in clean control point.
[1]Duan J C, Tan J H, Yang L, al et, 2008.Concentration sources and ozone formation potential of volatile organic compounds（VOCs）during ozone episode in Beijing[J].Atmosphere Research, 88(1): 25-35.
[2]Fujita E M, Campbell D E, Zielinska B, al et, 2003.Diurnal and weekday variations in the source contributions of ozone precursors in California’s south coast air basin[J].Journal of the Air & Waste Management Association, 53(7): 844-863.
[3]Jia L, Xu Y F, 2014.Effects of relative humidity on ozone and secondary organic aerosol formation from the photooxidation of Benzene and Ethylbenzene[J].Aerosol Science and Technology, 48(1), 1-12.
[4]Jiang X Y, Wiedinmyer C, Carlton A G, 2012.Aerosols from fires: an examination of the effects on ozone photochemistry in the western United States[J].Environmental Science &Technology, 46(21): 11878-11886．
[5]Kalabokas P, Hjorth J, Foret G, al et, 2017.An investigation on the origin of regional springtime ozone episodes in the western Mediterranean[J].Atmospheric Chemistry and Physics, 17(6): 3905-3928.
[6]Pan X, Kanaya Y, Tanimoto H, al et, 2015.Examining the major contributors of ozone pollution in a rural area of the Yangtze river delta region during harvest season[J].Atmospheric Chemistry and Physics, 15(11): 6101-6111.
[7]Wang Y G, Hopke P K, Xia X Y, al et, 2012.Source apportionment of airborne particulate matter using inorganic and organic species as tracers[J].Atmospheric Environment, 55: 525-532．
[8]Wang Y, Luo H, Jia L, al et, 2016.Effect of particle water on ozone and secondary organic aerosol formation from benzene-NO2-NaCl irradiations[J].Atmospheric Environment, 140: 386-394.
[9]安俊琳, 王跃思, 李昕, 等, 2007.北京大气中NO、 NO<sub>2</sub>和O<sub>3</sub>浓度变化的相关性分析[J].环境科学, 28(4): 4706-4711.
[10]蔡彦枫, 王体健, 谢旻, 等, 2013.南京地区大气颗粒物影响近地面臭氧的个例研究[J].气候与环境研究, 18(2): 251-260.
[11]程麟钧, 王帅, 宫正宇, 等, 2017.中国臭氧浓度的时空变化特征及分区[J].中国环境科学, 37(11): 4003-4012.
[12]丁国安, 罗超, 汤洁, 等, 1995.清洁地区气象因子与地面O<sub>3</sub>关系的初步研究[J].应用气象学报, 6(3): 350-355.
[13]段晓瞳, 曹念文, 王潇, 等, 2017.2015年中国近地面臭氧浓度特征分析[J].环境科学, 38(12): 4976-4982.
[14]国家环境保护部, 2012.HJ633-2012中华人民共和国国家环境保护标准环境空气质量指数(AQI)技术规定[S].北京: 中国环境科学出版社.
[15]国家环境保护部, 2012.GB3095-2012中华人民共和国国家标准环境空气质量标准[S].北京: 中国环境科学出版社.
[16]黄俊, 廖碧婷, 吴兑, 等, 2018.广州近地面臭氧浓度特征及气象影响分析[J].环境科学学报, 38(1): 23-31.
[17]焦铂洋, 苏昱丞, 郭胜利, 等, 2017.青藏高原臭氧谷的分布及其与太阳辐射的关系[J].高原气象, 36(5) : 1201-1208.DOI: 10. 7522 /j.issn.1000-0534.2016.00106.
[18]金明红, 黄益宗, 2003.臭氧污染胁迫对农作物生长与产量的影响[J].生态环境, 12(4): 482-486.
[19]孔琴心, 刘广仁, 李桂忱, 1999.近地面臭氧浓度变化及其对人体健康的可能影响[J].气候与环境研究, 4(1): 61-66.
[20]刘建, 吴兑, 范绍佳, 等, 2017.前体物与气象因子对珠江三角洲臭氧污染的影响[J].中国环境科学, 37(3): 813-82.
[21]刘姝岩, 包云轩, 金建平, 等, 2018.重霾天气气溶胶辐射效应对近地面臭氧峰值的影响[J].高原气象, 37(1): 296-304.DOI: 10. 7522 /j.issn.1000-0534.2016.00141.
[22]刘雅婷, 彭跃, 白志鹏, 等, 2011.沈阳市大气挥发性有机物(VOCs)污染特征[J].环境科学, 32(9): 2777-2785.
[23]齐冰, 牛彧文, 杜荣光, 等, 2017.杭州市近地面大气臭氧浓度变化特征分析[J].中国环境科学, 37(2): 443-451.
[24]单源源, 李莉, 刘琼, 等, 2016.长三角地区典型城市臭氧及其前体物时空分布特征[J].沙漠与绿洲气象, 10(5): 72-78.
[25]邵振艳, 周涛, 史培军, 等, 2009.大气污染对中国重点城市地面辐射影响的时空特征[J].高原气象, 28(5): 1105-1114.
[26]宋艳玲, 郑水红, 柳艳菊, 等, 2005.2000-2002年北京市城市大气污染特征分析[J].应用气象学报, 16(增刊): 116-122.
[27]谈建国, 陆国良, 耿福海, 等, 2007.上海夏季近地面臭氧浓度及其相关气象因子的分析和预报[J].热带气象学报, 23(5): 515-520.
[28]王闯, 王帅, 杨碧波, 等, 2015.气象条件对沈阳市环境空气臭氧浓度影响研究[J].中国环境监测, 31(3): 32-37.
[29]汪明圣, 郭世昌, 2017.ENSO循环对东亚地区平流层臭氧分布的影响[J].高原气象, 36(3): 865-874.DOI: 10.7522 /j.issn. 1000-0534.2016.00068.
[30]王男, 2015.气象因素对沈阳市大气中臭氧的影响[J].环境科学与技术, 38(S1): 61-65.
[31]王占山, 李云婷, 安欣欣, 等, 2018.2006～2015年北京市不同地区O<sub>3</sub>浓度变化[J].环境科学, 39(1): 1-8.
[32]王占山, 李云婷, 陈添, 等, 2014.北京城区臭氧日变化特征及与前体物的相关性分析[J].中国环境科学, 34(12): 3001-3008.
[33]吴锴, 康平, 王占山, 等, 2017.成都市臭氧污染特征及气象成因研究[J].环境科学学报, 37(11): 4241-4252.
[34]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.
[35]谢志英, 刘浩, 唐新明, 等, 2015.北京市近12年空气污染变化特征及其与气象要素的相关性分析[J].环境工程学报, 9(9): 4471-4478.
[36]严晓瑜, 缑晓辉, 刘玉兰, 等, 2015.银川市大气污染物浓度变化特征及其与气象条件的关系[J].气象与环境学报, 31(2): 21-30.
[37]杨春宇, 汪统岳, 陈霆, 等, 2017.基于光气候区的日照时数特征及变化规律[J].同济大学学报(自然科学版), 45(8): 1123-1130.
[38]湛社霞.2018.粤港澳大湾区常规大气污染物变化趋势与影响因素研究[D].广州： 中国科学院大学(中国科学院广州地球化学研究所).
[39]赵辉, 郑有飞, 徐静馨, 等, 2016a.南京市北郊夏季臭氧浓度变化特征分析[J].地球与环境, 44(2): 161-168.
[40]赵辉, 郑有飞, 徐静馨, 等, 2016b.中国典型城市大气污染物浓度时空变化特征分析[J], 地球与环境, 44(5): 549-556.
[41]郑景云, 卞娟娟, 葛全胜, 等, 2013.1981～2010年中国气候区划[J].科学通报, 58(30): 3088-3099.
[42]周天娇, 陈丹, 王咏青, 等, 2018.不同类型和强度的东亚切断低压过程中UTLS 区域臭氧变化对比分析[J].高原气象, 37(3): 837-849.DOI: 10.7522 /j.issn.1000-0534.2017.00079.
[43]朱毓秀, 徐家骝, 1994.近地面臭氧污染过程和相关气象因子的分析[J].环境科学研究, 7(6): 13-18.
