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基于重庆本地碳成分谱的PM2.5碳组分来源分析
引用本文:张灿,周志恩,翟崇治,白志鹏,陈刚才,姬亚芹,任丽红,方维凯.基于重庆本地碳成分谱的PM2.5碳组分来源分析[J].环境科学,2014,35(3):810-819.
作者姓名:张灿  周志恩  翟崇治  白志鹏  陈刚才  姬亚芹  任丽红  方维凯
作者单位:重庆市环境科学研究院, 重庆 401147;城市大气环境综合观测与污染防控重庆市重点实验室, 重庆 401147;重庆市环境科学研究院, 重庆 401147;城市大气环境综合观测与污染防控重庆市重点实验室, 重庆 401147;重庆市环境科学研究院, 重庆 401147;城市大气环境综合观测与污染防控重庆市重点实验室, 重庆 401147;中国环境科学研究院环境基准和风险评估国家重点实验室, 北京 100012;重庆市环境科学研究院, 重庆 401147;城市大气环境综合观测与污染防控重庆市重点实验室, 重庆 401147;南开大学国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300071;中国环境科学研究院环境基准和风险评估国家重点实验室, 北京 100012;重庆市环境科学研究院, 重庆 401147;城市大气环境综合观测与污染防控重庆市重点实验室, 重庆 401147
基金项目:重庆市“蓝天行动(2012-2017)”计划项目
摘    要:为了解重庆主城PM2.5中碳组分特征和来源,2012-05-02~2012-05-10日在商业区、工业区和居民区进行了PM2.5采样.利用TOR方法分析了8种碳组分,对3个不同功能区大气环境PM2.5以及燃煤尘、尾气尘(机动车尾气、船舶尾气、施工机械尾气)、生物质燃烧尘、餐饮油烟尘这6类源PM2.5中的8种碳组分进行了特征分析.在源的碳成分谱基础上,利用化学质量平衡(CMB)模型得到重庆本地PM2.5的碳来源指示组分,利用因子分析法解析出各类源对不同功能区内PM2.5碳组分的贡献率.结果表明,重庆地区燃煤尘、机动车尾气尘、船舶尾气尘、施工机械尾气尘、生物质燃烧尘、餐饮油烟尘的OC/EC值分别为6.3、3.0、1.9、1.4、12.7和31.3.EC2、EC3的高载荷指示柴油车尾气排放,OC2、OC3、OC4、OPC的高载荷指示燃煤排放,OC1、OC2、OC3、OC4、EC1指示汽油车尾气排放,OC3指示餐饮业排放,OPC指示生物质燃烧排放.商业区OC/PM2.5为17.4%,EC/PM2.5为6.9%,估算得到,二次有机碳(SOC)/OC为40.0%;工业区OC/PM2.5为15.5%,EC/PM2.5为6.6%,SOC/OC为37.4%;居民区OC/PM2.5为14.6%,EC/PM2.5为5.6%,SOC/OC为42.8%.工业区PM2.5中碳组分的主要来源为燃煤和汽油车尾气、柴油车尾气;商业区PM2.5中碳组分的主要来源为汽油车尾气、柴油车尾气和餐饮业油烟;居住区PM2.5中碳组分的主要来源为汽油车尾气、餐饮业油烟、柴油车尾气.

关 键 词:碳成分谱  碳来源分析  PM2.5  分歧系数  化学质量平衡  因子分析  重庆
收稿时间:2013/7/10 0:00:00
修稿时间:2013/10/22 0:00:00

Carbon Source Apportionment of PM2.5 in Chongqing Based on Local Carbon Profiles
ZHANG Can,ZHOU Zhi-en,ZHAI Chong-zhi,BAI Zhi-peng,CHEN Gang-cai,JI Ya-qin,REN Li-hong and FANG Wei-kai.Carbon Source Apportionment of PM2.5 in Chongqing Based on Local Carbon Profiles[J].Chinese Journal of Environmental Science,2014,35(3):810-819.
Authors:ZHANG Can  ZHOU Zhi-en  ZHAI Chong-zhi  BAI Zhi-peng  CHEN Gang-cai  JI Ya-qin  REN Li-hong and FANG Wei-kai
Institution:Chongqing Academy of Environmental Sciences, Chongqing 401147, China;Chongqing Key Laboratory of Urban Atmospheric Environment for Integrated Observation and Pollution Prevention and Control, Chongqing 401147, China;Chongqing Academy of Environmental Sciences, Chongqing 401147, China;Chongqing Key Laboratory of Urban Atmospheric Environment for Integrated Observation and Pollution Prevention and Control, Chongqing 401147, China;Chongqing Academy of Environmental Sciences, Chongqing 401147, China;Chongqing Key Laboratory of Urban Atmospheric Environment for Integrated Observation and Pollution Prevention and Control, Chongqing 401147, China;State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;Chongqing Academy of Environmental Sciences, Chongqing 401147, China;Chongqing Key Laboratory of Urban Atmospheric Environment for Integrated Observation and Pollution Prevention and Control, Chongqing 401147, China;State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Nankai University, Tianjin 300071, China;State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;Chongqing Academy of Environmental Sciences, Chongqing 401147, China;Chongqing Key Laboratory of Urban Atmospheric Environment for Integrated Observation and Pollution Prevention and Control, Chongqing 401147, China
Abstract:PM2.5 was sampled from commercial, industrial and residential areas in Chongqing urban city from 2nd May to 10th May 2012 in order to find out characteristics and sources of carbon in PM2.5. Eight kinds of carbons were analyzed by the TOR method. Characteristics of carbon pollution in PM2.5 from three kinds of functional areas and six kinds of sources, including coal-combustion, exhausts (vehicle, boat and construction machine), biomass burning, cooking smoke, were analyzed. Based on carbon source profiles, local indicating components of carbon sources in PM2.5 were obtained used the chemical mass balance(CMB)model. Contribution rate of different sources to PM2.5 carbon were parsed out by factor analysis. The results showed the OC/EC of coal-combustion, vehicle exhausts, boat exhausts, construction machine exhausts, biomass burning and cooking smoke were 6.3, 3.0, 1.9, 1.4, 12.7 and 31.3, respectively. High loads of EC2 and EC3 indicated diesel vehicle exhaust emissions, high loads of OC2, OC3, OC4 and OPC indicated coal-combustion emissions, OC1, OC2, OC3, OC4 and EC1 indicated gasoline vehicle exhaust emissions, OC3 indicated cooking emissions, and OPC indicated biomass burning emissions. OC/PM2.5, EC/PM2.5, secondary organic carbon (SOC)/OC in the commercial area were 17.4%, 6.9% and 40.0%, respectively. OC/PM2.5, EC/PM2.5 and SOC/OC in the industrial area were 15.5%, 6.6% and 37.4%, respectively. OC/PM2.5, EC/PM2.5 and SOC/OC in the residential area were 14.6% 5.6% and 42.8%, respectively.In the industrial area, the main sources of carbon in PM2.5 were coal combustion, gasoline vehicle exhausts and diesel exhaust. In the commercial area, the main sources of carbon were gasoline vehicle exhausts, diesel exhausts and cooking. In the residential area, the main sources of carbon were gasoline vehicle exhausts, cooking smoke and diesel exhausts.
Keywords:carbon profiles  carbon source apportionment  PM2  5  coefficient divergence  CMB  factor analysis  Chongqing
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