北京APEC期间不同颗粒物源解析方法的结果比较

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摘要

2014年10月8日~11月25日，在北京城市点位采用颗粒物多组分在线监测技术与单颗粒气溶胶质谱（SPAMS）两种方法测定颗粒物化学组分.基于颗粒物在线多组分监测技术得到的受体数据，采用ME2模型进行解析（OC-ME2）；基于SPAMS的观测数据，采用ART-2a和ME2两种方法进行来源解析.SPAMS-ART2a方法解析得到6种颗粒物污染源，而SPAMS-ME2和OC-ME2均确定了5种来源.每种方法都识别出了扬尘源、机动车尾气、燃煤源、工艺过程源和二次源.结果表明：3种方法的解析结果均显示机动车尾气（25.43%~28.84%）和二次源（22.55%~33.50%）是颗粒物的主要来源，其次是燃煤源（20.16%~21.21%）和工艺过程源（12.01%~15.17%）；不同方法解析出的同种源在对颗粒物（PM）的分担率与贡献时间变化上存在较大的差异，这可能与采样方法、化学分析方法和数据分析方法等有关.对APEC会议期间主要污染源类特征进行研究，3种方法解析结果中的首要污染源均是机动车尾气（29.17%~44.18%），其贡献均高于非会议期间（23.59%~28.79%），表明在此期间机动车尾气对颗粒物的产生具有重要影响.

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	刘佳媛
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关键词 ：颗粒物, 在线监测, 单颗粒气溶胶质谱, 化学组成, 来源解析, 北京市

Abstract：

During October 8 to November 25, 2014, the particulate matter multi-component online monitoring technology and single particle aerosol mass spectrometry (SPAMS) were used to determine the particulate matter and its chemical species at an urban site in Beijing. The receptor data obtained based on particulate matter online multi-component monitoring technology was analyzed by ME2model (OC-ME2). Source apportionment was separately conducted using two ways, ART-2a and ME2, based on the dataset of SPAMS. The SPAMS-ART2a identified six sources, while SPAMS-ME2 and OC-ME2 both identified five factors. Each method identified crustal dust, vehicle exhaust, coal combustion, industrial process, and secondary source. The results show that the main sources of particulate matter were vehicle exhaust(25.43%~28.84%) and secondary source(22.55%~33.50%), followed by coal combustion(20.16%~21.21%) and industrial process(12.01%~15.17%) by three methods. The same source from different methods had a large difference in the source contribution to particulate matter (PM) and contribution temporal trends, which might be related to sampling methods, chemical analysis methods and data analysis methods. The characteristics of main pollution sources during the APEC summit and non-summit period were studied. The primary source in the analysis results of the three methods during the APEC was vehicle exhaust(29.17%~44.18%), and the contribution was higher than non-summit period(23.59%~28.79%), indicating that vehicle exhaust had an important impact on the generation of PM during this period.

Key words： particulate matter online monitoring single particle aerosol mass spectrometry chemical composition source apportionment Beijing

收稿日期: 2019-08-09

PACS:

X513

基金资助:

大气重污染成因与治理攻关项目（DQGG0107，DQGG0107-03）

通讯作者: 高健,研究员,gaojian@craes.org.cn E-mail: gaojian@craes.org.cn

作者简介: 刘佳媛(1993-),女,河北秦皇岛人,助理工程师,硕士,主要从事大气污染控制,颗粒物来源解析研究.发表文章10余篇.

引用本文:

刘佳媛, 高健, 张岳翀, 马彤. 北京APEC期间不同颗粒物源解析方法的结果比较[J]. 中国环境科学, 2020, 40(3): 938-947. LIU Jia-yuan, GAO Jian, ZHANG Yue-chong, MA Tong. Results comparison of different source apportionment methods during APEC summit in Beijing. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(3): 938-947.

链接本文:

http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2020/V40/I3/938

[1]	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.
[2]	Zhang R, Jing J, Tao J, et al. Chemical characterization and source apportionment of PM2.5 in Beijing:seasonal perspective[J]. Atmo. Chem. Phys., 2014,13(14):7053-7074.
[3]	田莎莎,张显,卞思思,等.沈阳市PM2.5污染组分特征及其来源解析[J]. 中国环境科学, 2019,39(2):487-496. Tian S S, Zhang X, Bian S S, et al. Characteristics of PM2.5 pollution components and their sources in Shenyang[J]. China Environmental Science, 2019,39(2):487-496.
[4]	王杰,张逸琴,高健,等.2016~2018年采暖季太行山沿线城市PM2.5污染特征分析[J]. 中国环境科学, 2019,39(11):4521-4529. Wang J, Zhang Y Q, Gao J, et al. Characteristics of PM2.5 in cities along the Taihang Mountains during the heating season of 2016~2018[J]. China Environmental Science, 2019,39(11):4521-4529.
[5]	Peng X, Liu X X, Shi X R, et al. Source apportionment using receptor model based on aerosol mass spectra and 1h resolution chemical dataset in Tianjin, China[J]. Atmos. Environ., 2019,198:387-397.
[6]	Yang S, Dong J Q, Cheng B R. Characteristics of air particulate matter and their sources in urban and rural area of Beijing, China[J]. J. Environ. Sci. (China), 2000,12(4):402-409.
[7]	Zhang W, Guo J H, Sun Y L, et al. Source apportionment for, urban PM10 and PM2.5 in the Beijing area[J]. Chin. Sci. Bull., 2007,52(5):608-615.
[8]	Timonen H, Aurela M, Carbone S, et al. Seasonal diurnal changes in inorganic ions, carbonaceous matter mass in ambient aerosol particles in an urban, background area[J]. Boreal. Environ. Res., 2014,19:71-86.
[9]	Matawle J L, Pervez S, Deb M K, et al. PM2.5 pollution from household solid fuel burning practices in Central India:2. Application of receptor models for source apportionment[J]. Environ. Geochem. Hlth., 2018,40(1):145-161.
[10]	Cesari D, Donateo A, Conte M, et al. Inter-comparison of source apportionment of PM10 using PMF and CMB in three sites nearby an industrial area in central Italy[J]. Atmos. Res., 2016,182:282-293.
[11]	迟伟伟,李秋红,冯春丽.徐州市大气细颗粒物在线来源解析研究[J]. 能源环境保护, 2017,31(5):45-48. Chi W W, Li Q H, Feng C L. Study on PM2.5 online source analysis within Xuzhou municipality[J]. Energy Environmental Protection, 2017,31(5):45-48.
[12]	高健,李慧,史国良,等.颗粒物动态源解析方法综述与应用展望[J]. 科学通报, 2016,61(27):3002-3021. Gao J, Li H, Shi G L, et al. Overview of the development and application of multi-time resolution source apportionment for particulate matters[J]. Chin Sci Bull, 2016,61(27):3002-3021.
[13]	喻义勇,王苏蓉,秦玮.大气细颗粒物在线源解析方法研究进展[J]. 环境监测管理与技术, 2015,27(3):12-17. Yu Y Y, Wang S R, Qin W. Progresses and perspectives of on-line source apportionment of PM2.5[J]. Adm. Techn. Envir. Monit., 2015, 27(3):12-17.
[14]	Li Y J, Sun Y, Zhang Q, et al. Real-time chemical characterization of atmospheric particulate matter in China:A review[J]. Atmos. Environ., 2017,158:270-304.
[15]	王晓浩,赵倩彪,崔虎雄.基于在线监测的上海郊区冬季PM2.5来源解析[J]. 南京大学学报(自然科学), 2015,51:517-523. Wang X H, Zhao Q B, Cui H X. PM2.5source apportionment at suburb of shanghai in winter based on real time monitoring[J]. Journal of Nanjing University (Natural Sciences), 2015,51:517-523.
[16]	Toner S M, Shields L G, Sodeman D A, et al. Using mass spectral source signatures to apportion exhaust particles from gasoline and diesel powered vehicles in a freeway study using UF-ATOFMS[J]. Atmos. Environ., 2018,42:568-581.
[17]	姜国,袁明浩,李梅,等.沙尘天气细粒子污染快速来源解析初步研究[J]. 绿色科技, 2017,16:35-38. Jiang G, Yuan M H, Li M, et al. A preliminary study on quick source apportionment of fine particle pollution in sand-dust weather[J]. Journal of Green Science and Technology, 2017,16:35-38.
[18]	闫璐璐,刘焕武,黄学敏,等.利用SPAMS研究西安市重污染天气细颗粒物污染特征及来源[J]. 环境科学研究, 2018,31(11):1841-1848. Yan L L, Liu H W, Huang X M, et al. Characteristics and Source Apportionment of Fine Particles in Xi'an Using a Single Particle Aerosol Mass Spectrometer (SPAMS) during Heavy Pollution[J]. Research of Environmental Sciences, 2018,31(11):1841-1848.
[19]	曹宁,黄学敏,祝颖,等.西安冬季重污染过程PM2.5理化特征及来源解析[J]. 中国环境科学, 2019,39(1):32-39. Cao N, Huang X M, Zhu Y, et al. Pollution characteristics and source apportionment of fine particles during a heavy pollution in winter in Xi'an City[J]. China Environmental Science, 2019,39(1):32-39.
[20]	Gao J, Peng X, Cheng G, et al. Insights into the chemical characterization and sources of PM2.5 in Beijing at a 1-h time resolution[J]. Sci. Total. Environ., 2016,542:162-171.
[21]	Crilley L R, Lucarelli F, Bloss W J, et al. Source apportionment of fine and coarse particles at a roadside and urban background site in London during the 2012 summer Clearf Lo campaign[J]. Environ. Pollut., 2017, 220:766-778.
[22]	Compendium Method IO-3.3. Determination of metals in ambient particulate matter using X-ray fluores cence(xrf) spectroscopy[Z]. US-EPA, 1999.
[23]	Li L, Li M, Huang Z X, et al. Ambient particle characterization by single particle aerosol mass spectrometry in an urban area of Beijing[J]. Atmos. Environ., 2014,94:323-331.
[24]	Su Y X, Sipin M F, Furutani H, et al. Development and characterization of an aerosol time-of-flight mass spectrometer with increased detection efficiency[J]. Anal. Chem., 2004,76:712-719.
[25]	Paatero P. The multilinear engine:a table-driven, least squares program for solving multilinear problems, including the n-way parallel factor analysis model[J]. J. Comput. Graph. Stat., 1999,8:854-888.
[26]	Ramadan Z, Eickhout B, Song X H, et al. Comparison of positive matrix factorization and multilinear engine for the source apportionment of particulate pollutants[J]. Chemometr. Intell. Lab. Syst., 2003,66:15-28.
[27]	GB 3095~2012环境空气质量标准[S]. GB 3095~2012 Ambient air quality standards[S].
[28]	Chow J C, Lowenthal D H, Antony Chen L W, et al. Mass reconstruction methods for PM2.5:a review[J]. Air. Qual. Atmos. Hlth., 2015,8(3):243-263.
[29]	魏星.煤燃烧和机动车排放对空气质量的影响[D]. 上海:复旦大学, 2011. Wei X. Effects of coal combustion and vehicle emissions on air quality.[D]. Shanghai:Fudan university, 2011.
[30]	Clements A L, Jia Y L, Denbleyker A, et al. Air pollutant concentrations near three Texas roadways, part II:Chemical characterization and transformation of pollutants[J]. Atmos. Environ., 2009,43(30):4523-4534.
[31]	Wang S B, Yin S S, Zhang R Q, et al. Insight into the formation of secondary inorganic aerosol based on high-time-resolution data during haze episodes and snowfall periods in Zhengzhou, China[J]. Sci. Total. Environ., 2019,660:47-56.
[32]	Chandra S, Kulshrestha M J, Kumar B, et al. Investigating daytime and night-time differences with the seasonal trend and sources of inorganic fine aerosols in Indo-Gangetic plain[J]. J. Earth. Syst. Sci., 2019,128(2).
[33]	吴瑕,曹芳,翟晓瑶,等.长春秋季细颗粒物中有机气溶胶组成特征及来源[J]. 环境科学, 2019,40(8):1-16. Wu X, Cao F, Zhai X Y, et al. Molecular composition and source apportionment of fine organic aerosols in autumn in Changchun[J]. Environmental Science, 2019,40(8):1-16.
[34]	Cabada J C, Pandis S N, Subramanian R, et al. Estimating the secondary organic aerosol contribution to PM2.5 using the EC trace method[J]. Aerosol. Sci. Tech., 2004,38(S1):140-155.
[35]	Nguyen Q T, Skov H, Sorensen L L, et al. Source apportionment of particles at station nord, north east Greenland during 2008~2010 using COPREM and PMF analysis[J]. Atmos. Chem. Phys., 2013,13:35-49.
[36]	Canepari S, Pietrodangelo A, Perrino C, et al. Enhancement of source traceability of atmospheric PM by elemental chemical fractionation[J]. Atmos. Environ., 2009,43:4754-4765.
[37]	Cao J J, Chow J C, Tao J, et al. Stable carbon isotopes in aerosols from Chinese cities:Influence of fossil fuels[J]. Atmos. Environ., 2011,45:1359-1363.
[38]	Yuan Z B, Lau A K H, Zhang H Y, et al. Identification and spatiotemporal variations of dominant PM10sources over Hong Kong[J]. Atmos. Environ., 2006,40(10):1803-1815.
[39]	杨佳美,戴启立,刘保双,等.关中地区背景点位环境空气PM2.5来源解析与多模型结果对比[J]. 环境科学研究, 2017,30(2):184-192. Yang J M, Dai Q L, Liu B S, et al. Source apportionment of ambient PM2.5 at background sites in Guanzhong Area, China:Comparison of results obtained by multiple models[J]. Research of Environmental Sciences, 2017,30(2):184-192.
[40]	Pant P, Harrison R M. Critical review of receptor modelling for particulate matter:a case study of India[J]. Atmos. Environ., 2012, 49:1-12.
[41]	Zhang Z S, Gao J, Zhan, L M, et al. Observations of biomass burning tracers in PM2.5 at two megacities in North China during 2014 APEC summit[J]. Atmos. Environ., 2017,169:54-64.