西安冬季重污染过程PM_(2.5)理化特征及来源解析
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摘要
基于单颗粒气溶胶质谱仪(SPAMS)观测数据、颗粒物质量浓度数据和气象要素数据,研究了2017年11月西安市一次重污染过程中细颗粒物的化学组分特征及其成因,并使用正矩阵因子分析法(PMF)对细颗粒进行了来源解析.结果表明,西安市冬季重污染过程中细颗粒物主要类型为有机碳(OC)、元素碳(EC)、混合碳(ECOC)、富钾(K)、钠-钾(Na-K)、有机胺(amine)、矿尘(dust)和重金属(HM),其主要来源为燃煤(24.9%),二次(29.3%),工业(19.3%),交通(13.3%),生物质燃烧(5.2%)和扬尘(1.9%).通过对比分析不同污染过程细颗粒物的理化特征,发现高湿度,低风速的不利气象条件和供暖及工业生产导致的燃煤污染、二次污染,是此次重污染过程的主因.
Single Particle Aerosol Mass Spectrometry(SPAMS), combining with particulate matter mass concentration and meteorological conditions, was used to study the chemical composition characteristics and genesis of fine particles in a heavy pollution process in November 2017, Xi'an. In addition, the source apportionment of fine particulate matter was analyzed by positive matrix factor analysis(PMF). The results showed that atmospheric particulate matter was mainly divided into eight kinds of particles: organic carbon(OC), elemental carbon(EC), ECOC, K, Na-K, amine, mineral dust, and heavy metal(HM). Their possible sources include coal(24.9%), secondary(29.3%), industry(19.3%), traffic(13.3%), biomass combustion(5.2%), and dust(1.9%). By comparing and analyzing the pollution characteristics of fine particulate matter in different pollution processes, it was found that the main reasons of this heavy pollution process were unfavorable meteorological conditions of high humidity and low wind speed, coal-burning pollution and secondary pollution caused by heating and industrial production.
Single Particle Aerosol Mass Spectrometry(SPAMS), combining with particulate matter mass concentration and meteorological conditions, was used to study the chemical composition characteristics and genesis of fine particles in a heavy pollution process in November 2017, Xi'an. In addition, the source apportionment of fine particulate matter was analyzed by positive matrix factor analysis(PMF). The results showed that atmospheric particulate matter was mainly divided into eight kinds of particles: organic carbon(OC), elemental carbon(EC), ECOC, K, Na-K, amine, mineral dust, and heavy metal(HM). Their possible sources include coal(24.9%), secondary(29.3%), industry(19.3%), traffic(13.3%), biomass combustion(5.2%), and dust(1.9%). By comparing and analyzing the pollution characteristics of fine particulate matter in different pollution processes, it was found that the main reasons of this heavy pollution process were unfavorable meteorological conditions of high humidity and low wind speed, coal-burning pollution and secondary pollution caused by heating and industrial production.
引文
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[2]Huang R J,Zhang Y L,Bozzetti C,et al.High secondary aerosol contribution to particulate pollution during haze events in China[J].Nature,2014,514(7521):218-222.
[3]李瑾,李建军,吴灿,等.关中典型城市及农村夏季PM_(2.5)的化学组成对比[J].中国环境科学,2018,38(12):4415-4425.LI Jin,LI Jian-jun,WU Can,et al.Comparison on the chemical composition of PM_(2.5) in the urban and rural regions of Guanzhong plain,China[J].China Environmental Science,2018,38(12):4415-4425.
[4]李慧文,张承中,马万里,等.西安采暖季大气中多环芳烃的污染特征及来源解析[J].环境科学,2010,7:1432-1437.Li H W,Zhang C Z,Ma W L,et al.Pollution Characterizations and Source Apportionment of Polycyclic Aromatic[J].Environment Science,2010,7:1432-1437.
[5]田鹏山,曹军骥,韩永明,等.关中地区冬季PM_(2.5)中碳气溶胶的污染特征及来源解析[J].环境科学,2016,37(2):427-433.TIAN P S,CAO J J,HAN Y M,et al.Pollution characteristics and sources of carbonaceous aerosol in PM_(2.5)during winter in Guanzhong area[J].Environment Science,2016,37(2):427-433.
[6]王堃,韩永明,何世恒,等.西安市重污染与清洁天PM_(2.5)组分及其活性氧物质对比[J].环境科学,2017,38(7):2679-2687.Wang K,Han Y M,He S H,et al.Comparison of Characteristics and reactive Oxidative Species of PM_(2.5) in Xi'an,China During Haze and Clean Days[J].Environment Science,2017,38(7):2679-2687.
[7]Chen Y,Liu H,Yang F,et al.Single particle characterization of summertime particles in Xi'an(China)[J].Science of the Total Environment,2018,636:1279.
[8]Wang D,Hu J,Xu Y,et al.Source contributions to primary and secondary inorganic particulate matter during a severe wintertime PM_(2.5) pollution episode in Xi'an,China[J].Atmospheric Environment,2014,97:182-194.
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[10]王帆,刘焕武,牟国桃,等.基于单颗粒气溶胶质谱法的雾霾过程中细颗粒物组分分析及来源研究[J].环境污染与防治,2017,39(3):263-267.WANG F,LIU H W,WANG Y X,et al.Compositions and sources of particles measured by SPAMS method during a haze process[J].Environmental Pollution and Control,2017,3(39):263-267.
[11]李磊.单颗粒气溶胶质谱仪的性能表征及应用研究[D].上海:上海大学,2011.Li L.Performance Characterization and Application Study of a Single Particle Aerosol Mass Spectrometry[D].Shanghai:Shanghai University,2011.
[12]张莉.基于单颗粒气溶胶质谱信息的分类方法研究及其应用[D].上海:上海大学,2013.Zhang L.Aerosols cluster methods study and its application based on single particle aerosol mass spectra information[D].Shanghai:Shanghai University,2013.
[13]Paatero P,Tapper U.Analysis of different modes of factor analysis as least squares fit problem[J].Chemometrics and Intelligent Laboratory Systems,1993,18(2):183-194.
[14]Tan J H,Duan J C,Chai F H,et al.Source apportionment of size segregated fine/ultrafine particle by PMF in Beijing[J].Atmospheric Research,2014,139,90-100.
[15]Paatero P,Hopke P K.Rotational tools for factor analytic models[J].Chemometrics,2009,23,91-100.
[16]Paatero P,Hopke P K,Song X H,et al.Understanding and controlling rotations in factor analytic models[J].Chemometrics Intelligent Laboratory Systems,2002,60:253-264.
[17]Manousakas M,Papaefthymiou H,Papaefthymiou E,et al.Assessment of PM_(2.5) sources and their corresponding level of uncertainty in a coastal urban area using EPA PMF 5.0enhanced diagnostics[J].Science of the Total Environment,2017,574:155-164.
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[24]王琴,张大伟,刘保献,等.基于PMF模型的北京市PM_(2.5)来源的时空分布特征[J].中国环境科学,2015,35(10):2917-29.WANG Q,ZHANG D W,LIU B X,et al.Spatial and temporal variations of ambient PM_(2.5)source contributions using positive matrix factorization[J].China Environmental Science,2015,35(10):2917-2924