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成都市西南郊区春季大气PM2.5的污染水平及来源解析
摘要点击 3444  全文点击 1137  投稿时间:2015-08-11  修订日期:2015-12-25
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中文关键词  成都  PM2.5  有机碳  元素碳  水溶性无机离子  无机元素  来源解析
英文关键词  Chengdu  PM2.5  organic carbon  elemental carbon  water-soluble inorganic ions  inorganic elements  source apportionment
作者单位E-mail
林瑜 成都信息工程大学资源环境学院, 成都 610225 540954930@qq.com 
叶芝祥 成都信息工程大学资源环境学院, 成都 610225
大气环境模拟与污染控制四川省高校重点实验室, 成都 610225 
yzxiang@cuit.edu.cn 
杨怀金 成都信息工程大学资源环境学院, 成都 610225
大气环境模拟与污染控制四川省高校重点实验室, 成都 610225 
 
张菊 成都信息工程大学资源环境学院, 成都 610225
大气环境模拟与污染控制四川省高校重点实验室, 成都 610225 
 
殷蔚雯 成都信息工程大学资源环境学院, 成都 610225  
李晓芬 成都信息工程大学资源环境学院, 成都 610225  
中文摘要
      为了解成都市西南郊区大气中PM2.5污染特征,于2015年3月1~31日对成都西南郊区大气PM2.5进行膜样品采集,并分析其中的化学组分.结果表明,3月成都市西南郊区大气PM2.5的日均质量浓度为121.21μg·m-3,采集的31个有效PM2.5样品中有24个样品日均浓度在75μg·m-3以上,日超标率为77%,该地区3月PM2.5污染严重.在与大气气象要素的关系研究中发现,大气颗粒物PM2.5与大气能见度有着较好的指数关系,与温度、湿度有一定的正相关关系,但相关性并不明显.水溶性阴阳离子中NH4+(16.24%)、SO42-(12.58%)、NO3-(9.91%)占PM2.5的主导地位,NO3-/SO42-的比值是0.77,表明成都西南郊区固定源的污染要大于移动源的污染,燃煤排放的污染相对于汽车尾气较多.有机碳(OC)/元素碳(EC)比值均大于2.0,表明有二次有机碳(SOC)产生.利用OC/EC比值法估算SOC的质量浓度发现,成都西南郊区3月PM2.5中SOC的平均浓度水平为3.49μg·m-3,对OC的贡献率达20.6%,说明成都市西南郊区的OC主要来源于一次排放,且OC与EC的相关性分析显示,其相关系数达0.95,说明OC、EC来源相似且相对稳定,成都市西南郊区春季受局地源排放影响较大,一次排放占主导地位,二次有机碳对OC贡献相对较小,与估算所得的SOC性质一致.利用主成分分析(PCA)方法对成都西南郊区大气中PM2.5进行来源解析,发现成都西南郊区PM2.5的主要污染源为燃煤、生物质的燃烧、二次硝酸盐或硫酸盐、土壤和扬尘源、汽车尾气源、电子生产源以及机械加工源.
英文摘要
      In order to understand the characteristics of PM2.5 pollution in the atmosphere of Chengdu southwest suburb, PM2.5 particles in Chengdu southwest suburb were collected and analyzed from March 1st to March 31st, 2015. The results showed that the daily average concentration of PM2.5 in the southwest suburb of Chengdu reached 121.21 μg·m-3, and the average daily concentration of 24 samples in 31 PM2.5 samples was over 75 μg·m-3, the daily excessive rate was 77%, indicating the PM2.5 pollution in the study area was serious in March. When studying the relationship between atmospheric and meteorological factors, it was found that there was a significant index correlation between PM2.5 concentration and atmospheric visibility, and it had a positive correlation with temperature and humidity, but the correlation was not obvious. NH4+ (16.24%), SO42- (12.58%) and NO3- (9.91%) were dominant in PM2.5. The ratio of NO3-/SO42- was 0.77, which indicated that the pollution of stationary sources in the southwest suburb was more severe than that of mobile sources. Organic carbon (OC)/elemental carbon(EC) ratios were higher than 2, which indicated the existence of second organic carbon (SOC). Using OC/EC ratio method to estimate the concentration of SOC, it was found that the average concentration of SOC in the southwest suburb of Chengdu in March was 3.49 μg·m-3, and the contribution rate of OC was 20.6%, which showed that the main source of OC in the southwest suburb of Chengdu was primary discharge. The correlation analysis of OC and EC showed that the correlation coefficient reached 0.95, indicating that the OC and EC sources were similar and relatively stable, and there was a great impact of local source emissions on Chengdu southwest suburb in spring, and primary discharge played a dominant role, while the contribution of SOC to OC was relatively small, which was consistent with the SOC characteristics obtained by estimation. Using principal component analysis method to analyze the sources of PM2.5 in the southwest of Chengdu, it was found that the main pollution sources of PM2.5 in southwest suburb of Chengdu were coal burning and biomass burning, secondary nitrate/sulfate, soil and dust, vehicle emissions, electronic production source, and mechanical processing source.

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