南昌市环境空气污染时空变化特征及影响因素研究
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摘要
选取2014～2017年南昌市不同时间尺度AQI及主要空气污染物数据,利用GIS技术、神经网络分析、后向轨迹模型及地统计分析方法,分析了南昌市环境空气污染时空变化特征及影响因素。结果表明,南昌市近年来空气质量总体变化不大,空气质量等级以良为主,占全年比例为57%～61%。但首要污染物变化较大,即PM_(2.5)比例显著下降,NO_2和O_3比例显著上升,PM_(10)变化不大。南昌市空气污染季节变化显著,冬春季空气质量较差,以PM_(10)、PM_(2.5)污染为主,夏季空气质量最好,以O_3污染为主。空气污染周变化以周末及周一污染较重、周四污染最轻,说明南昌市空气污染除了与群众出行习惯有关,还存在其他影响因素。南昌市空气质量日变化呈双峰型(9:00～11:00和20:00～22:00),主要受上、下班高峰期带来的交通尾气影响。南昌市空气污染空间变化呈典型的"郊区-市区"分布,其中AQI、PM_(10)、PM_(2.5)、SO_2、NO_2、CO值均以市区较高、郊区较低,而O_3的空间分布规律正好相反,这主要与城区NO_x排放较多,O_3易与其迅速反应而消耗有关。后向轨迹聚类分析结果表明,来自本地的短轨迹气团占比高,对PM_(2.5)、PM_(10)、NO_2、O_3的影响大。气象因素上,PM_(2.5)、PM_(10)、NO_2受相对湿度影响较大,O_3受温度影响较大。
Base on GIS, self-organizing map(SOM), back trajectory model and geostatistical method, this study investigates the spatiotemporal distribution of air pollution and its impacted factors in Nanchang City. For this purpose, the data of air quality index(AQI) and the main air pollutants in different time scales from 2014 to 2017 is selected, as well as the meteorological factors. Results show that the air quality of Nanchang City is not significantly improved in recent years. 51≤AQI≤100 is the main level of AQI with the ratios between 57% and 61%. But the primary pollutants are greatly changed, e.g. the number of polluted days of PM_(2.5) decrease, while the counterpart of NO_2 and O_3 increase. For seasonal variation, the air quality in Nanchang City is poor in winter and spring, with PM_(10) and PM_(2.5) as the primary pollutants. In comparison, the counterpart is good in summer, with O_3 as the primary pollutant. The air quality is relatively bad on Monday and the weekends, and relatively good on Wednesdays and Thursday. It reveals that travel habit of people is not the only influence factor for the air quality in Nanchang City. The diurnal variation of air quality in Nanchang City shows a bimodal distribution peaked at 9:00-11:00 and 20:00-22:00, which is primarily related to the traffic exhaust during the rush hours. For spatial distribution, the air quality in Nanchang City is poor in the downtown area compared with that in the suburban area. Specifically, the concentrations of PM_(10), PM_(2.5), SO_2, NO_2, CO are higher in the downtown area. In contrary, O_3 shows the higher concentration in the suburban area. Because there is more amount of NO_x emission in the downtown area and O_3 is easily consumed by rapid reaction with them. Back trajectories and cluster analysis suggest that the prevailing air masses were from the nearby area in Nanchang and PM_(10), PM_(2.5), NO_2 and O_3 pollution may mainly originate from these areas. Principal component analysis(PCA) demonstrates that the relative humidity and temperature is the main impact corresponding to the high concentration of PM_(2.5), PM_(10) and NO_2 and the concentration of O_3, respectively.
Base on GIS, self-organizing map(SOM), back trajectory model and geostatistical method, this study investigates the spatiotemporal distribution of air pollution and its impacted factors in Nanchang City. For this purpose, the data of air quality index(AQI) and the main air pollutants in different time scales from 2014 to 2017 is selected, as well as the meteorological factors. Results show that the air quality of Nanchang City is not significantly improved in recent years. 51≤AQI≤100 is the main level of AQI with the ratios between 57% and 61%. But the primary pollutants are greatly changed, e.g. the number of polluted days of PM_(2.5) decrease, while the counterpart of NO_2 and O_3 increase. For seasonal variation, the air quality in Nanchang City is poor in winter and spring, with PM_(10) and PM_(2.5) as the primary pollutants. In comparison, the counterpart is good in summer, with O_3 as the primary pollutant. The air quality is relatively bad on Monday and the weekends, and relatively good on Wednesdays and Thursday. It reveals that travel habit of people is not the only influence factor for the air quality in Nanchang City. The diurnal variation of air quality in Nanchang City shows a bimodal distribution peaked at 9:00-11:00 and 20:00-22:00, which is primarily related to the traffic exhaust during the rush hours. For spatial distribution, the air quality in Nanchang City is poor in the downtown area compared with that in the suburban area. Specifically, the concentrations of PM_(10), PM_(2.5), SO_2, NO_2, CO are higher in the downtown area. In contrary, O_3 shows the higher concentration in the suburban area. Because there is more amount of NO_x emission in the downtown area and O_3 is easily consumed by rapid reaction with them. Back trajectories and cluster analysis suggest that the prevailing air masses were from the nearby area in Nanchang and PM_(10), PM_(2.5), NO_2 and O_3 pollution may mainly originate from these areas. Principal component analysis(PCA) demonstrates that the relative humidity and temperature is the main impact corresponding to the high concentration of PM_(2.5), PM_(10) and NO_2 and the concentration of O_3, respectively.
引文
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[2] GORDON T,STANEK L W,BRONW J.Pollution,air in encyclopedia of toxicology.In:Wexler P (ed) Encyclopedia of toxicology (third edition)[M].Academic Press,Oxford:995-1002.
[3] WHO.WHO’s first global report on antibiotic resistance reveals serious,worldwide threat to public health(2014)[R].Geneva:World Health Organization
[4] ZIOMAS I C,MELAS D,ZEREFOS C S,et al.Forecasting peak pollutant levels from meteorological variables[J].Atmospheric Environment,1995,29(24):3703-3711.
[5] GIORGI F,MELEUX F.Modelling the regional effects of climate change on air quality[J].Comptes Rendus Geoscience,2007,339(11-12):721-733.
[6] 邹滨,许珊,张静.土地利用视角空气污染空间分异的地理分析[J].武汉大学学报(信息科学版),2017,42(2):216-222.ZOU B,XU S,ZHANG J.Spatial variation analysis of urban air pollution using GIS:A land use perspective[J].Geomatics and Information Science of Wuhan University,2017,42(2):216-222.
[7] PU H,LUO K,WANG P,et al.Spatial variation of air quality index and urban driving factors linkages:Evidence from Chinese cities[J].Environmental Science and Pollution Research,2017,24(5):4457-4468.
[8] 邓霞君,蔡振群,项晓美,等.浙江省空气质量及主要气象因子的影响分析[J].环境科学与技术,2014(s2):372-377.DENG X J,CAI Z Q,XIANG X M,et al.Air quality in Zhejiang province and the impact of main meteorological elements[J].Environmental Science & Technology,2014(s2):372-377.
[9] 肖建能,杜国明,施益强,等.厦门市环境空气污染时空特征及其与气象因素相关分析[J].环境科学学报,2016,36(9):3363-3371.XIAO J N,DU G M,SHI Y Q,et al.Spatiotemporal distribution pattern of anbient air pollution and its correlation with meteorological factors in Xiamen city[J].Acta Scientiae Circumstantiae,2016,36(9):3363-3371.
[10] 王媛林,王哲,陈学舜,等.珠三角秋季典型气象条件对空气污染过程的影响分析[J].环境科学学报,2017,37(9):3229-3239.WANG Y L,WANG Z,CHEN X S,et al.Impact of typical meteorological conditions on air pollution over pearl river delta in autumn[J].Acta Scientiae Circumstantiae,2017,37(9):3229-3239.
[11] 杨旭,张小玲,康延臻,等.京津冀地区冬半年空气污染天气分型研究[J].中国环境科学,2017,37(9):3201-3209.YANG X,ZHANG X L,KANG Y Z,et al.Circulation weather type classification for air pollution over the Beijing-Tianjin-Hebei region during winter[J].China Environmental Science,2017,37(9):3201-3209.
[12] 许文轩,田永中,肖悦,等.华北地区空气质量空间分布特征及成因研究[J].环境科学学报,2017,37(8):3085-3096.XU W X,TIAN Y Z,XIAO Y,et al.Study on the spatial distribution characteristics and the drivers of AQI in north China[J].Acta Scientiae Circumstantiae,2017,37(8):3085-3096.
[13] 廖晓农,张小玲,王迎春,等.北京地区冬夏季持续性雾-霾发生的环境气象条件对比分析[J].环境科学,2014,35(6):2031-2044.LIAO X N,ZHANG X L,WANG Y C,et al.Comparative analysis on meteorological condition for persistent haza cases in summer and winter in Beijing[J].Environmental Science,2014,35(6):2031-2044.
[14] 李云婷,王占山,安欣欣,等.2015年“十一”期间北京市大气重污染过程分析[J].中国环境科学,2016,36(11):3218-3226.LI Y T,WANG Z S,AN X X,et al.Analysis on a heavy air pollution process in Beijing during National Day holiday,2015[J].China Environmental Science,2016,36(11):3218-3226.
[15] 陈镭,马井会,甄新蓉,等.上海地区空气污染变化特征及其气象影响因素[J].气象与环境学报,2017,33(3):59-67.CHEN L,MA J H,ZHEN X R,et al.Variation characteristics and meteorological influencing factors of air pollution in Shanghai[J].Journal of Meteorology and Environment,2017,33(3):59-67.
[16] 陈翔翔,胡磊,彭王敏子,等.1960-2014年南昌市霾天气气象要素及主要大气污染物变化特征[J].气象与环境学报,2016,32(5):114-121.CHEN X X,HU L,PENG W M Z,et al.Characteristics of meteorological parameters and main atmospheric pollutants of haze events in Nanchang from 1960 to 2014[J].Journal of Meteorology and Environment,2016,32(5):114-121.
[17] 赵阳,胡恭任,于瑞莲,等.2013年南昌市区PM2.5的浓度水平及时空分布特征与来源[J].环境科学研究,2017,30(6):854-863.ZHAO Y,HU G R,YU R L,et al.Concentrations and spatial-temporal characteristics and source analysis of PM2.5 in Nanchang city in 2013[J].Research of Environmental Sciences,2017,30(6):854-863.
[18] 蔡哲,贺志明,唐春燕,等.南昌市酸雨特征与气象条件关系分析研究[J].安徽农业科学,2010,38(21):11292-1129.CAI Z,HE Z M,TANG C Y,et al.Study on the relationship between acid rain characteristics and weather conditions in Nanchang[J].Journal of Agricultural Sciences,2010,38(21):11292-1129.
[19] 彭希珑,何宗健,刘小真,等.南昌市大气PM2.5中多环芳烃的来源解析[J].环境污染与防治,2009,31(10):28-32.PENG X L,HE Z J,LIU X Z,et al.Source apportionment of PAHs in fine particulate matter(PM2.5) of Nanchang city[J].Environmental Pollution Control,2009,31(10):28-32.
[20] 王占山,李云婷,陈添,等.2013年北京市PM2.5的时空分布[J].地理学报,2015,70(1):110-120.WANG Z S,LI Y T,CHEN T,et al.Spatial-temporal characteristics of PM2.5 in Beijing in 2013[J].Acta Geographica Sinica,2015,70(1):110-120.
[21] 戴伟,高佳琪,曹罡,等.深圳市郊区大气中PM2.5的特征分析[J].环境科学,2012,33(6):1952-1957.DAI W,GAO J Q,CAO G,et al.Characteristics of atmospheric PM2.5 in the suburb of Shenzhen[J].Environmental Science,2012,33(6):1952-1957.
[22] 郝吉明,吴烨,傅立新,等.北京市机动车污染分担率的研究[J].环境科学,2001,22(5):1-6.HAO J M,WU Y,FU L X,et al.Motor vehicle source contributions to air pollutants in Beijing[J].Environmental Science,2001,22(5):1-6.
[23] 郝吉明,王丽涛,李林,等.北京市能源相关大气污染源的贡献率和调控对策分析[J].中国科学D辑:地球科学,2005,35(S1):115-122.
[24] 冷中笑,张新华,格丽玛.新疆机动车氮氧化物排放现状及控制对策[J].新疆环境保护,2014,36(1):22-25.LENG Z X,ZHANG X H,GE L M.Research on current situation and control countermeasures of NOx emission by vehicles in Xinjiang[J].Environmental Protection of Xinjiang,2014,36(1):22-25.
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