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石家庄市采暖前后大气颗粒物及其碳组分特征
李璇,段二红
作者单位E-mail
李璇 河北科技大学 18233138382@163.com 
段二红 河北科技大学  
摘要:
摘要:为研究石家庄市大气颗粒物、碳组分特征和污染来源,采集2016年11月1日—12月31日石家庄市大气颗粒物(PM10、PM2.5和PM1)样品,分析采暖前后PM10、PM2.5和PM1及其中OC(有机碳)、EC(元素碳)和WSOC(水溶性有机碳)浓度水平,计算颗粒物与碳组分间相关性;进行OC/EC特征比值法和8个碳组分(OC1、OC2、OC3、OC4、OPC、EC1、EC2和EC3)研究。结果表明,①采暖后ρ(PM10)和ρ(PM2.5)比采暖前分别增加了26.4%和32.1%,而采暖后ρ(PM1)比采暖前降低了12.2%。采样期间ρ(PM10)与ρ(PM2.5)显著相关,而ρ(PM1)分别与ρ(PM2.5)和ρ(PM10)相关性差。采暖后散煤燃烧造成ρ(PM10)和ρ(PM2.5)增加,区域机动车限行和工业限产/停产导致ρ(PM1)降低。②Pearson相关系数计算可知ρ(OC)与ρ(EC)强相关;ρ(PM10)和ρ(PM2.5)分别与ρ(OC)和ρ(WSOC)强相关,而ρ(PM1)分别与ρ(OC)和ρ(WSOC)弱相关;ρ(PM10)、ρ(PM2.5)和ρ(PM1)分别与ρ(EC)弱相关。③采暖后PM10、PM2.5和PM1中ρ(OC)比采暖前分别增加了215.1%、97.2%和18.5%;采暖后PM10和PM2.5中ρ(EC)比采暖前分别增加了65.2%和5.3%,而采暖后PM1中ρ(EC)比采暖前降低了10.9%。集中供热和散煤燃烧排放了大量有机碳;PM10和PM2.5中EC主要来源于散煤燃烧,PM1中EC主要来源于工业排放和机动车尾气。④采暖前PM10、PM2.5和PM1中ρ(OC)/ρ(EC)平均值分别为4.5、4.5和4.3;采暖后PM10和PM2.5中ρ(OC)/ρ(EC)平均值分别为9.7和9.8,而PM1中ρ(OC)/ρ(EC)平均值为7.4。ρ(SOC)/ρ(OC)为36%~60%,石家庄市冬季大气中二次有机碳污染严重;⑤8个碳组分分析发现,石家庄市机动车限行导致PM1中ρ(EC1)降低,而采暖后集中供暖和散煤燃烧的增加,导致ρ(OC2)明显增加。研究显示,大气颗粒物中碳组分采暖前主要来源于机动车尾气,而采暖后主要来源于燃煤燃烧,尤其是散煤燃烧。
关键词:  PM10  PM2.5  PM1.0  有机碳;元素碳;水溶性有机碳
DOI:
分类号:
基金项目:国家科技支撑计划项目(2014BAC23B04-03);河北省教育厅拔尖人才计划(BJ2014024);河北省科学技术厅大气专项项目(17273902D)
Characteristics of Carbon Components in Atmospheric Particles before and during the Heating Period in Shijiazhuang
lixuan
Abstract:
Abstract: In order to study the characteristics of atmospheric particles, carbon components and sources in Shijiazhuang, atmospheric particles samples (PM10, PM2.5 and PM1) were collected in Shijiazhuang from 01 Nov to 31 Dec 2016. The concentration of PM10, PM2.5, PM1, OC (Organic carbon), EC (Elemental carbon) and WSOC (Water-soluble organic carbon) were investigated before and during heating period. Meanwhile, the correlation between the concentration of atmospheric particles and the carbon components were calculated. The source of atmospheric particles was analyzed by OC/EC and the characteristics of the 8 carbon components (OC1, OC2, OC3, OC4, OPC, EC1, EC2 and EC3). ①The results showed that ρ(PM10) and ρ(PM2.5) during heating period increased by 26.4% and 32.1% than that before heating period, while ρ(PM1) was 12.2% lower. ρ(PM10) and ρ(PM2.5) had significant relevance, while ρ(PM2.5) and ρ(PM1), ρ(PM10) and ρ(PM1) had poor correlation. During heating period, ρ(PM10) and ρ(PM2.5) increased by rural residential coal combustion. While motor vehicle limited and factory shutdown decreased ρ(PM1). ②Through Pearson correlation coefficient calculation, ρ(OC) and ρ(EC) had strong correlation; ρ(PM10) and ρ(PM2.5) were strongly correlated with ρ(OC) and ρ(WSOC) respectively. While ρ(PM1) was weakly correlated with them. ρ(PM10), ρ(PM2.5) and ρ(PM1) were weakly correlated with ρ(EC). ③ρ(OC) of PM10, PM2.5 and PM1 during heating period increased by 215.1%, 97.2% and 18.5% than that before. ρ(EC) of PM10 and PM2.5 were increased by 65.2% and 5.3% than that before heating period, while ρ(EC) of PM1 decreased by 10.9% than that before. Central heating and rural residential coal combustion emitted a large number of OC. EC of PM10 and PM2.5 mainly came from rural residential coal combustion, EC of PM1 came from industrial and motor vehicle emissions. ④Before heating period, ρ(OC)/ρ(EC) were 4.5, 4.5 and 4.3 respectively in PM10, PM2.5 and PM1. During heating period, ρ(OC)/ρ(EC) were 9.7 and 9.8 respectively in PM10 and PM2.5, while ρ(OC)/ρ(EC) was 7.4 in PM1. The value of ρ(SOC)/ρ(OC) was 0.36~0.60 indicated that the secondary pollution was very serious in Shijiazhuang. ⑤The analysis of 8 carbon components showed that ρ(EC1) of PM1 decreased with the decrease of motor vehicle emissions, while ρ(OC2) increased significantly due to the increase of coal combustion. The research showed that the carbon aerosols mainly came from motor vehicle exhaust before heating period,but it mainly came from coal combustion during heating period, especially rural residential coal combustion.
Key words:  PM10  PM2.5  PM1.0  organic carbon  elemental carbon  water-soluble organic carbon