Spatial and temporal variation and combined pollution characteristics of atmospheric pollutants in urban Guiyang
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摘要: 选取贵阳市10个空气质量监测站发布的PM2.5、PM10、SO2、NO2、CO和O3实时浓度数据,通过时间序列分析法和插值法研究贵阳市大气污染物的时空变化和复合污染特征。结果表明:(1)贵阳市2014-2018年主要污染物PM2.5和PM10的年平均浓度逐渐下降,光化学污染物O3年平均浓度有所增加,空气质量逐渐转好,环境治理取得明显效果;(2)2018-2019自然年PM2.5、PM10、NO2和O3在春季污染最严重,SO2和CO在冬季污染最严重,反映出污染源、阶段性燃料燃烧和二次离子生成等因素对不同污染物的影响不同;(3)PM2.5和PM10日变化特征为“午峰晚峰”型,峰值发生的时间因季节而异,主要由不同季节人类作息的起止时间不同所致,O3日变化为单峰型,夜间O3浓度较低,从早晨8:00点开始随着太阳辐射的增大和温度的升高,在15:00-16:00点左右达到峰值;(4)PM2.5的空间分布呈现出部分郊区和工业区较高,市中心居民区较低的特征,指示城市建设向郊区推进。O3浓度呈现出市区低、郊区高的空间分布特征,反映郊区植被覆盖好,释放的天然源VOCs促进了O3生成;(5)主要污染物O3与颗粒物PM2.5和PM10在春季造成的复合污染最为严重,在夏季O3与PM10造成一定程度的复合污染,在秋冬季O3浓度最低,O3与颗粒物不产生复合污染;一天之内同一时刻O3与颗粒物不会产生叠加从而造成复合污染。Abstract: Guiyang city,located in southwestern China,is a big data center of southern China.Its special industrial structure raises higher requirements on air quality.In order to reduce the negative impact of air pollution on the social and economic development of Guiyang,it is necessary to study the characteristics of air pollution in this area. In this study, we obtained real time data of PM2.5,PM10,SO2,NO2,CO and O3 concentration from 10 air quality monitoring stations in Guiyang by time series analysis and the interpolation method to study the spatial and temporal changes and combined pollution of atmospheric pollutants.The results show that the annual average concentrations of the main pollutants PM2.5 and PM10 in urban Guiyang decreased gradually from 2014 to 2018,the average concentration of photochemical pollutants O3 increased,the quality of air gradually improved,and environmental treatment achieved good results.The PM2.5,PM10,NO2 and O3 are most polluted in spring,and the SO2 and CO are most polluted in winter in the natural year from 2018 to 2019,which reflect the influences of pollution sources,staged fuel combustion,and secondary ion generation on different pollutants were different.The daily variation of PM2.5 and PM10 was characterized by the "noon peak and evening peak" type.The peak occurrence time varied with seasons due to different day and night lengths in different seasons,and different start and stop times of human life in different seasons.The daily variation of O3 day was single-peak type, and the concentration of O3 was low at night. From 8:00 in the morning,as the solar radiation increased and the temperature rose,it reached a peak around 15:00 to 16:00.The spatial distribution of PM2.5 presented the characteristics of some suburbs and industrial areas were higher, and the downtown residential areas were lower,indicating that urban construction is expanded to the suburbs construction. The spatial distribution of O3 concentration presented characteristics of low in the urban and high in suburb, reflecting the good coverage of suburban vegetation, and the release of natural source VOCs promoting the generation of O3.The major pollutant O3 and particulates PM2.5 and PM10 casued the most serious combined pollution in spring,while O3 and PM10 caused a certain degree of combined pollution in summer,and the concentration of O3 was the lowest in autumn and winter,which will not produce combined pollution with particulate pollutants. At the same moment within a day, the particulates and O3 did not superimpose and cause combined pollution.
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[1] Jia M W, Zhao T L, Cheng X H, et al. Inverse relations of PM2.5 and O3 in air compound pollution between cold and hot seasons over an urban area of East China [J]. Atmosphere, 2017, 8(12):59-70. [2] 杨孝文, 周颖, 程水源,等. 北京冬季一次重污染过程的污染特征及成因分析 [J]. 中国环境科学, 2016, 36(3): 679-686. [3] Pausata F S R, Gaetani M, Messori G, et al. The role of aerosol in altering North Atlantic atmospheric circulation in winter and its impact on air quality [J]. Atmospheric Chemistry and Physics, 2015, 15(4):1725-1743. [4] 舒卓智, 赵天良, 郑小波,等. 清洁大气背景下贵阳空气质量变化及气象作用[J].中国环境科学, 2017, 37(12): 4460-4468. [5] 郑小波, 王学锋, 罗宇翔,等. 云贵高原1961—2006年大气能见度和消光因素变化趋势及原因 [J]. 生态环境学报, 2010, 19(2): 314-319. [6] Zhao T, Liu D, Zheng X, et al. Revealed variations of air quality in industrial development over a remote plateau of Southwest China: an application of atmospheric visibility data [J]. Meteorology and Atmospheric Physics, 2016, 129(6): 659-667. [7] 苏志华, 王建华. 贵阳市大气颗粒物的污染特征及其影响因素分析 [J]. 中山大学学报(自然科学版), 2015, 54(5): 77-84. [8] 杨佳, 葛馨, 吴起鑫. 贵阳市主城区空气质量指数时空分布特征 [J]. 长江流域资源与环境, 2018, 27(8): 1827-1835. [9] 梁隆超, 仇广乐, 陈卓. 贵阳市城区大气颗粒物PM2.5的污染特征与季节变化规律 [J]. 地球与环境, 2015, 43(3): 290-295. [10] 李松, 邓宝昆, 邵技新,等. 基于GIS的贵阳PM2.5质量浓度城乡过渡特征及影响因素研究 [J]. 生态环境学报, 2014, 23(8): 1298-1304. [11] 刘娜, 冯新斌. 贵阳市大气颗粒物PM2.5污染特征及气象参数的影响 [J]. 地球与环境, 2014, 42(3): 311-315. [12] 杜德艳, 李金娟, 陶芸,等. 贵阳市PM2.5微观特征的季节变化分析 [J]. 环境科学学报, 2015, 35(6): 1645-1650. [13] 尚媛媛, 舒卓智, 郑小波,等. 云贵高原城市冬夏季PM2.5与O3相互作用机理:以贵阳市为例 [J]. 生态环境学报, 2018, 27(12): 110-115. [14] 李卫海, 李阳兵, 周焱,等. 岩溶山地城市扩展空间差异的地形效应 [J]. 地理科学进展, 2009, 28(1): 85-92. [15] 尚媛媛, 郑小波, 夏晓玲,等. 贵阳市PM2.5分布特征及气象条件的影响 [J]. 高原山地气象研究, 2018, 38(3): 45-50. [16] 何尧启, 汪永进, 孔兴功,等. 贵州董哥洞近1 000a来高分辨率洞穴石笋δ18O记录 [J]. 科学通报, 2005(11):1114-1118. [17] 段平, 盛业华, 李佳,等. 自适应的IDW插值方法及其在气温场中的应用 [J]. 地理研究, 2014, 33(8): 1417-1426. [18] 李凯, 赵华甫, 吴克宁,等. 土壤重金属Cd污染指数的适宜插值方法和合理采样数量研究 [J]. 土壤通报, 2016, 47(5): 1056-1064. [19] 唐宜西, 张小玲, 徐敬,等. 北京城区和郊区本底站大气污染物浓度的多时间尺度变化特征 [J]. 环境科学学报, 2016, 8: 2783-2793. [20] 周勤迁, 潘月鹏, 王剑,等. 黑龙江海伦农业区冬春PM2.5和气态污染物污染特征 [J]. 中国环境科学, 2014, 34(4): 844-851. [21] 赖安琪, 陈晓阳, 刘一鸣,等. 珠江三角洲高质量浓度PM2.5和O3复合污染特征 [J]. 中山大学学报(自然科学版), 2018, 57(4): 30-36. [22] 朱佳文, 余光辉, 李振国,等. 中国典型城市环境空气质量变化趋势分析研究 [J]. 环境科学与管理, 2014,39(12): 45-49. [23] 张思远, 吴开亚. 合肥市PM2.5污染特征及影响因素分析研究 [J]. 环境科学与管理, 2015, 40(1): 51-56. [24] Tai A P K, Mickley L J, Jacob D J. Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change [J]. Atmospheric Environment, 2010, 44(32): 3976-3984. [25] Pateraki S, Asimakopoulos D, Flocas H A, et al. The role of meteorology on different sized aerosol fractions (PM10, PM2.5, PM2.5-10) [J]. Science of the Total Environment, 2012, 419(3): 124-135. [26] 张东海, 白慧, 周文钰,等. 气候季节划分标准在贵州地区的适用性分析 [J]. 高原山地气象研究, 2014, 34(4): 77-82. [27] 林燕芬, 王茜, 伏晴艳,等. 上海市臭氧污染时空分布及影响因素 [J]. 中国环境监测, 2017, 33(4): 60-67. [28] Kong S, Han B, Bai Z, et al. Receptor modeling of PM2.5, PM10 and TSP in different seasons and long-range transport analysis at a coastal site of tianjin, China [J]. Science of the Total Environment, 2010, 408(20): 4681-4694. [29] 杜吴鹏, 王跃思, 宋涛,等. 夏秋季石家庄大气污染变化特征观测研究 [J]. 环境科学, 2010, 31(7): 1409-1416. [30] 徐锋. 乌鲁木齐市2011年冬季PM2.5/PM10浓度特征分析 [J]. 干旱环境监测, 2012, 26(2): 81-84. [31] Heidi O, Gaarder P I, Johansen B V. Quantification and cha-acterization of suspended particulate matter in indoor air [J]. The Science of the Total Environment, 1997, 193: 185-196. [32] 赵辉, 郑有飞, 魏莉,等. G20峰会期间杭州及周边地区空气质量的演变与评估 [J]. 中国环境科学, 2017, 37(6): 2016-2024. [33] Louie P K K, Watson J G, Chow J C, et al. Seasonal characteristics and regional transport of PM2.5 in Hong Kong [J]. Atmospheric Environment, 2005, 39(9): 1695-1710. [34] Wang Z S, Li Y T, Chen T, et al. Ground-level ozone in urban Beijing over a 1-year period: Temporal variations and relationship to atmospheric oxidation [J]. Atmospheric Research, 2015, 164-165: 110-117. [35] Zhang J, Wang T, Chameides W L, et al. Ozone production and hydrocarbon reactivity in Hong Kong, Southern China [J]. Atmospheric Chemistry and Physics,2007,7(2):557-573. [36] 王占山, 李云婷, 陈添,等.北京市臭氧的时空分布特征 [J]. 环境科学, 2014, 35(12): 4446-4453. [37] Wang Y S, Yao L, Wang L L, et al. Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China [J]. Science China(Earth Sciences), 2015, 57(1): 14-25. [38] Lu K D, Rohrer F, Holland F, et al. Observation and modelling of OH and HO2 concentrations in the Pearl River Delta 2006: a missing OH source in a VOC rich atmosphere [J]. Atmospheric Chemistry and Physics, 2012, 12(3): 1541-1569. [39] Parrish D D, Zhu T. Clean Air for Megacities [J]. Science, 2009, 326(5953): 674-675. [40] Zhang Y H, Hu M, Zhong L J, et al. Regional integrated experiments on air quality over Pearl River Delta 2004 (PRIDE-PRD2004): Overview [J]. Atmospheric Environment, 2008, 42(25): 6157-6173. [41] 张宇静, 赵天良, 殷翀之,等. 徐州市大气PM2.5与O3作用关系的季节变化[J].中国环境科学, 2019, 39(06): 2267-2272. [42] 王艳秋,杨晓丽. 哈尔滨市降水形势对大气污染物浓度稀释的影响[J].自然灾害学报,2007(5):65-68. [43] Nowak D J, Hirabayashi S, Bodine A, et al. Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects [J]. Environmental Pollution, 2013, 178: 395-402. [44] 徐家骝,朱毓秀. 气象因子对近地面臭氧污染影响的研究[J].大气科学,1994, 18(6): 751-757.
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