摘要
为探讨2013年南昌市大气颗粒物的污染特征及分布状况,收集南昌市9个大气监测站点实时发布的PM10和PM2.5数据,分析了ρ(PM10)、ρ(PM2.5)和ρ(PM2.5)/ρ(PM10)的变化规律及其与气态污染物的相关性,并结合污染严重的秋季时段,采用PCA-MLR(主成分分析-多元线性回归)模型对大气PM2.5中化学组分来源进行解析.结果表明:①ρ(PM10)和ρ(PM2.5)的年均值分别为(115.4±39.1)(69.1±26.8)μg/m^3,均超过GB3095—2012《环境空气质量标准》二级标准限值,ρ(PM10)和ρ(PM2.5)的最高值分别出现在石化、省外办监测站点,最低值出现在林科所监测站点.ρ(PM10)和ρ(PM2.5)季节性变化特征明显,呈冬季>春、秋两季>夏季的趋势,全年ρ(PM10)超标天数占比为25.48%,ρ(PM2.5)超标天数占比为36.71%,各季度ρ(PM2.5)超标天数占比均高于ρ(PM10).②受人为活动和边界层高度的影响,ρ(PM2.5)和ρ(PM10)日变化呈双峰双谷形态,一个波峰出现在08:00—10:00,另一个波峰出现在20:00—22:00,并且晚间小时峰值高于早间,最低值出现在15:00.③ρ(PM2.5)/ρ(PM10)年均值为60.3%,在冬季最高达65.1%,相关性分析发现ρ(PM10)与ρ(PM2.5)存在较显著的线性关系,表明二者具有同源性.④ρ(PM10)、ρ(PM2.5)均与ρ(SO2)、ρ(NO2)、ρ(CO)呈显著正相关,并且冬季相关性高于夏、秋两季;而ρ(PM10)、ρ(PM2.5)均与ρ(O3)全年呈显著负相关,并且夏、秋两季相关性高于冬季,说明气态污染物的二次转化对ρ(PM2.5)和ρ(PM10)有较大影响.⑤南昌市秋季PM2.5的最大污染源为道路扬尘/机动车尾气混合污染源,其次分别为施工扬尘源、燃煤源、冶炼尘/生物质燃烧混合污染源,各污染源对PM2.5的贡献率分别为40.9%、35.8%、12.4%、10.9%.研究显示,南昌市PM2.5的污染程度较PM10严重,PM2.5已成为南昌市大气颗粒物污染的主要组分,PM2.5主要来源为城市扬尘和机动车尾气.
To investigate the pollution characteristics of the PM in Nanchang City in 2013,the mass concentration,ratio of PM and its correlation with gaseous pollutants were analyzed by collecting the air quality data in real time at 9 air monitoring stations in Nanchang City.Meanwhile,the source of chemical components in PM 2.5 was analyzed using PCA-MLR model in the severely polluted autumn.The results showed that:(1)The annual concentrations of PM 10 and PM 2.5 were(115.4±39.1)and(69.1±26.8)μg/m^3 respectively,both higher than the national secondary standard.The highest levels of PM 10 and PM 2.5 appeared at Petrochemical and Provincial Foreign Affairs Office,while the lowest PM 10 and PM 2.5 happened at Forestry Research Institute.The concentration of PM exhibited apparent seasonality,following the order:winter>spring and autumn>summer.The PM 10 and PM 2.5 levels failed to meet GradeⅡstandards in 25.48%and 36.71%of the whole year,respectively.The days of PM 2.5 level exceeding the new GradeⅡstandards in each quarter was higher than that of PM 10 level.(2)The diurnal variation of PM level was in the form of double peaks and double valleys,which was mainly influenced by human activities and boundary layer height.One peak was between 08:00 and 10:00,and the other was between 20:00 and 22:00.The hourly peak in the evening was higher than that in the morning,and the lowest occurred at 15:00.(3)The annual average ratio between the monthly mean concentration of PM 2.5 and PM 10 was 60.3%,and the highest reached 65.1%in winter.(4)Correlation analysis indicated that the monthly mean concentration of PM 2.5 had very significant linear correlation with PM 10,having the same source.There was significantly positive correlation between the daily mean concentrations of PM and NO2,SO2,CO2 and the correlation in winter was stronger than that in summer and autumn,while the correlation between the mass concentrations of PM and O3 had a significantly negative correlation throughout the year,and was stronger in summer and autumn than that in winter.This negative correlation can be explained by the reaction of O3 with NO2 which indicated that the secondary transformation of gaseous pollutants had a significant impact on the concentration of PM.(5)The largest source of PM 2.5 in autumn in Nanchang City was mixed pollution source of road dust and vehicle exhaust,followed by construction dust,fly coal combustion and smelting dust/biomass burning,with contributions of 40.9%,35.8%,12.4%and 10.9%,respectively.The overall results suggest that the pollution of PM 2.5 in Nanchang is more serious than that of PM 10,PM 2.5 has become the main component of air particulate matter pollution in Nanchang City,and the major pollution sources are urban dust and vehicle exhaust.
作者
刘小真
任羽峰
刘忠马
秦文
LIU Xiaozhen;REN Yufeng;LIU Zhongma;QIN Wen(School of Resources,Environment and Chemistry Engineering,Nanchang University,Nanchang 330031,China;Key Laboratory of Environmental and Resources Utilization of Poyang Lake,Ministry of Education,Nanchang 330031,China;Environmental Monitor Station of Nanchang City,Nanchang 330038,China)
出处
《环境科学研究》
EI
CAS
CSCD
北大核心
2019年第9期1546-1555,共10页
Research of Environmental Sciences
基金
江西省科学技术厅项目(No.20151BBE50047,20161ACG70011)
南昌大学研究生创新专项资金项目(No.CX2017079)~~
