石家庄市采暖前后大气颗粒物及其碳组分特征

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、PM_2.5和PM₁）样品，分析采暖前后PM₁₀、PM_2.5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（质量浓度之比，下同）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（PM_2.5）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（PM_2.5）显著相关，而ρ（PM₁）分别与ρ（PM_2.5）和ρ（PM₁₀）相关性差.采暖后散煤燃烧造成ρ（PM₁₀）和ρ（PM_2.5）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（PM_2.5）分别与ρ（OC）和ρ（WSOC）强相关，而ρ（PM₁）分别与ρ（OC）和ρ（WSOC）中等相关；ρ（PM₁₀）和ρ（PM_2.5）分别与ρ（EC）弱相关，ρ（PM₁）与ρ（EC）中等相关.③采暖后PM₁₀、PM_2.5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PM_2.5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OC；PM₁₀和PM_2.5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、PM_2.5和PM₁中OC/EC平均值分别为4.5、4.5和4.3；采暖后PM₁₀和PM_2.5中OC/EC平均值分别为9.8和9.7，而PM₁中OC/EC平均值为7.4.采暖前后SOC/OC（质量浓度之比，下同）平均值的范围为0.36~0.65，石家庄市冬季大气中SOC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. 

Characteristics of Carbon Components in Atmospheric Particles before and during the Heating Period in Shijiazhuang City

In order to study the characteristics of atmospheric particles, carbon components and sources in Shijiazhuang City, atmospheric particles samples (i.e., PM₁₀, PM_2.5 and PM₁) were collected from November 1 to December 31, 2016. The concentration of PM₁₀, PM_2.5, PM₁, organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC) 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 (i.e., OC1, OC2, OC3, OC4, OPC, EC1, EC2 and EC3). (1) The results showed that ρ(PM₁₀) and ρ(PM_2.5) during heating period increased by 26.4% and 32.1% compared with those before heating period, while ρ(PM₁) was decreased by 12.2%. ρ(PM₁₀) and ρ(PM_2.5) had significant relevance, while ρ(PM_2.5) and ρ(PM₁), ρ(PM₁₀) and ρ(PM₁) had poor correlations. During heating period, ρ(PM₁₀) and ρ(PM_2.5) increased by rural residential coal combustion. While motor vehicle limited and factory shutdown decreased ρ(PM₁). (2) Through Pearson correlation coefficient calculation, ρ(OC) and ρ(EC) had strong correlation; ρ(PM₁₀) and ρ(PM_2.5) were strongly correlated with ρ(OC) and ρ(WSOC) respectively. While ρ(PM₁) was medium correlated with them. ρ(PM₁₀) and ρ(PM_2.5) were weakly correlated with ρ(EC), and ρ(PM₁) was medium correlated with ρ(EC). (3) ρ(OC) of PM₁₀, PM_2.5 and PM₁ during heating period increased by 215.1%, 97.2% and 18.5% compared with before heating. ρ(EC) of PM₁₀ and PM_2.5 were increased by 65.2% and 5.3% than that before heating period, while ρ(EC) of PM₁ decreased by 10.9%. Central heating and rural residential coal combustion emitted a large number of OC. EC of PM₁₀ and PM_2.5 mainly came from rural residential coal combustion, EC of PM₁ came from industrial and motor vehicle emissions. (4) Before heating period, OC/EC were 4.5, 4.5 and 4.3 respectively in PM₁₀, PM_2.5 and PM₁. During heating period, OC/EC were 9.8 and 9.7 respectively in PM₁₀ and PM_2.5, while OC/EC was 7.4 in PM₁. The value of SOC/OC were 0.36-0.65 indicated that the secondary pollution was very serious in Shijiazhuang City. (5) The 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 was mainly caused by coal combustion during heating period, especially rural residential coal combustion.