安徽省O_3浓度的时空分布特征及影响因素
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摘要
基于2016年安徽省空气质量监测站的O_3数据,分析O_3的时空分布特征,运用地理探测器方法,探讨O_3浓度的影响因素。结果表明:①2016年安徽省O_3浓度在季度上呈现春夏高、秋冬低的规律;在月度上5—9月O_3浓度中位值较高,1月、2月、12月O_3浓度中位值较低;O_3浓度日变化总体呈单峰型,最高值出现在下午15:00,最低值出现在7:00。②安徽省O_3浓度空间分布总体为北高南低。③因子探测结果表明,对臭氧浓度影响较大的因子有PM_(10)、CO、相对湿度、气压、降水量、日照时数、风速、PM_(2.5)、第三产业产值、工业企业个数、工业废气排放量、全社会用电量及公路里程。交互探测分析表明,不同因子间的交互作用,正向强化了各因子的解释力,最大交互因子为相对湿度∩公路里程,降水量∩气温,CO∩常住人口。
This study is based on the O_3 data of the 2016 Anhui Air Quality Monitoring Substation,analyzes the temporal and spatial distribution characteristics of O_3,and uses the geo-detector method to explore the influencing factors of O_3 concentration.The results show that:①In 2016,the concentration of O_3 in Anhui Province showed a pattern of high in spring and summer and low in autumn and winter.The median value of O_3 concentration in May-September was higher,and the concentration of O_3 in January,February and December was higher.The median value was lower;the daily variation of O_3 concentration was generally unimodal,with the highest value occurring at 15:00 pm and the lowest value appearing at 7:00.②The spatial distribution of O_3 concentration in Anhui province is generally high in North and South.③Factor detection results show that the factors that have a greater impact on ozone concentration are PM_(10),CO,relative humidity,air pressure,precipitation,sunshine hours,wind speed,PM_(2.5),tertiary industry output value,number of industrial enterprises,industrial exhaust emissions,total social electricity consumption and highway mileage.The interactive detection analysis shows that the interaction between different factors positively enhances the explanatory power of each factor.The maximum interaction factor is relative humidity∩highway mileage,precipitation∩temperature,CO∩resident population.
This study is based on the O_3 data of the 2016 Anhui Air Quality Monitoring Substation,analyzes the temporal and spatial distribution characteristics of O_3,and uses the geo-detector method to explore the influencing factors of O_3 concentration.The results show that:①In 2016,the concentration of O_3 in Anhui Province showed a pattern of high in spring and summer and low in autumn and winter.The median value of O_3 concentration in May-September was higher,and the concentration of O_3 in January,February and December was higher.The median value was lower;the daily variation of O_3 concentration was generally unimodal,with the highest value occurring at 15:00 pm and the lowest value appearing at 7:00.②The spatial distribution of O_3 concentration in Anhui province is generally high in North and South.③Factor detection results show that the factors that have a greater impact on ozone concentration are PM_(10),CO,relative humidity,air pressure,precipitation,sunshine hours,wind speed,PM_(2.5),tertiary industry output value,number of industrial enterprises,industrial exhaust emissions,total social electricity consumption and highway mileage.The interactive detection analysis shows that the interaction between different factors positively enhances the explanatory power of each factor.The maximum interaction factor is relative humidity∩highway mileage,precipitation∩temperature,CO∩resident population.
引文
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[23] 赵小风,李娅娅,赵雲泰,等.基于地理探测器的土地开发度时空差异及其驱动因素[J].长江流域资源与环境,2018(11):2426-2433.
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[27] 黄小刚,赵景波,曹军骥,等.中国城市O3浓度时空变化特征及驱动因素[J].环境科学,2019(3):1-14.
[28] 周磊,武建军,贾瑞静,等.京津冀PM2.5时空分布特征及其污染风险因素[J].环境科学研究,29(4):484-493.
[29] 南国卫,孙虎.基于灰色关联模型对陕西省O3浓度影响因素分析[J].环境科学学报,2017(12):4519-4527.
[30] 刘芷君,谢小训,谢旻,等.长江三角洲地区臭氧污染时空分布特征[J].生态与农村环境学报,2016,32(3):445-450.
[2] 柴敏平,罗勇,商娟,等.江西省城市空气臭氧污染状况及时空分布特征[J].江西科学,2018(1):95-100.
[3] 刘闽,王闯,侯乐,等.沈阳臭氧污染时空分布特征及变化趋势[J].中国环境监测,2017,33(4):126-131.
[4] 程麟钧,王帅,宫正宇,等.京津冀区域臭氧污染趋势及时空分布特征[J].中国环境监测,2017,33(1):14-21.
[5] 沈劲,黄晓波,汪宇,等.广东省臭氧污染特征及其来源解析研究[J].环境科学学报,2017,37(12):4449-4457.
[6] 贾海鹰,尹婷,瞿霞,等.2015年北京及周边地区臭氧浓度特征及来源模拟[J].中国环境科学,2017,37(4):1231-1238.
[7] 黄争超,洪礼楠,尹佩玲,等.保定市夏季臭氧污染来源及大气传输影响研究[J].北京大学学报(自然科学版),2018,54(3):665-672.
[8] 陈宜然,陈长虹,王红丽,等.上海臭氧及前体物变化特征与相关性研究[J].中国环境监测,2011,27(5):44-49.
[9] 单源源,李莉,刘琼,等.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,2016,10(5):72-78.
[10] 王俊秀,安俊琳,邵平,等.南京北郊大气臭氧周末效应特征分析[J].环境科学,2017,38(6):2256-2263.
[11] 吕慧珂,何红弟,郝杨杨.香港港口氮氧化物和臭氧的变化特征和周末效应[J].环境工程学报,2017,11(7):4196-4201.
[12] KARLSSON P E,KLINGBERG J,ENGARDT M,et al.Past,present and future concentrations of ground-level ozone and potential impacts on ecosystems and human health in northern Europe [J].Science of the Total Environment,2017,576:22-35.
[13] LEFOHN A S,MALLEY C S,SIMON H,et al.Responses of human health and vegetation exposure metrics to changes in ozone concentration distributions in the European Union,United States,and China [J].Atmospheric Environment,2016,152:123-145.
[14] 王磊,刘端阳,韩桂荣,等.南京地区近地面臭氧浓度与气象条件关系研究[J].环境科学学报,2018,38(4):1285-1296.
[15] 严仁嫦,叶辉,林旭,等.杭州市臭氧污染特征及影响因素分析[J].环境科学学报,2018,38(3):1128-1136.
[16] 曹庭伟,吴锴,康平,等.成渝城市群臭氧污染特征及影响因素分析[J].环境科学学报,2018,38(4):1275-1284.
[17] 张祥志,陈文泰,黄樱,等.江苏省2013—2016年臭氧时空分布特征[J].中国环境监测,2017,33(4):50-59.
[18] WANG Y,DU H,XU Y,et al.Temporal and spatial variation relationship and influence factors on surface urban heat island and ozone pollution in the Yangtze River Delta,China [J].Science of the Total Environment,2018,s 631-632(1 August 2018):921-933.
[19] JASAITIS D,VASILIAUSKIEN,et al.Surface ozone concentration and its relationship with UV radiation,meteorological parameters and radon on the eastern coast of the Baltic Sea [J].Atmosphere,2016,7(2):27.
[20] 环境保护部科技标准司.环境空气质量评价技术规范(试行):HJ663—2013[S].北京:中国环境科学出版社,2013:2-3.
[21] BRUS D J,HEUVELINK G B M.Optimization of sample patterns for universal kriging of environmental variables [J].Geoderma,2007,138(1):86-95.
[22] 王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(01):116-134.
[23] 赵小风,李娅娅,赵雲泰,等.基于地理探测器的土地开发度时空差异及其驱动因素[J].长江流域资源与环境,2018(11):2426-2433.
[24] JU H R,ZHANG Z X,ZUO L J,et al.2016.Driving forces and their interactions of built-up land expansion based on the geographical detector:A case study of Beijing,China [J].International Journal of Geographical Information Science,30(11):2188-2207.
[25] 李宗哲.陕西省县域经济发展水平空间差异及影响因素研究[D].兰州:兰州交通大学,2018:25-35.
[26] 武鹏.山阳县农村贫困化空间分异及其影响因素[D].西安:西北大学,2018:30-39.
[27] 黄小刚,赵景波,曹军骥,等.中国城市O3浓度时空变化特征及驱动因素[J].环境科学,2019(3):1-14.
[28] 周磊,武建军,贾瑞静,等.京津冀PM2.5时空分布特征及其污染风险因素[J].环境科学研究,29(4):484-493.
[29] 南国卫,孙虎.基于灰色关联模型对陕西省O3浓度影响因素分析[J].环境科学学报,2017(12):4519-4527.
[30] 刘芷君,谢小训,谢旻,等.长江三角洲地区臭氧污染时空分布特征[J].生态与农村环境学报,2016,32(3):445-450.