基于聚类方法下的柴油车排放颗粒物无机元素谱分析

齐靖宇, 杨柳, 冯谦, 殷小鸽, 陆凯波, 金陶胜. 基于聚类方法下的柴油车排放颗粒物无机元素谱分析[J]. 环境化学, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502
引用本文: 齐靖宇, 杨柳, 冯谦, 殷小鸽, 陆凯波, 金陶胜. 基于聚类方法下的柴油车排放颗粒物无机元素谱分析[J]. 环境化学, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502
QI Jingyu, YANG Liu, FENG Qian, YIN Xiaoge, LU Kaibo, JIN Taosheng. Study and review on inorganic elements spectrum of diesel particulate matter: Cluster analysis[J]. Environmental Chemistry, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502
Citation: QI Jingyu, YANG Liu, FENG Qian, YIN Xiaoge, LU Kaibo, JIN Taosheng. Study and review on inorganic elements spectrum of diesel particulate matter: Cluster analysis[J]. Environmental Chemistry, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502

基于聚类方法下的柴油车排放颗粒物无机元素谱分析

    通讯作者: 金陶胜, E-mail: jints@nankai.edu.cn
  • 基金项目:

    国家重点研发计划专项(2017YFC0212100)和国家自然科学基金面上项目(21477057)资助.

Study and review on inorganic elements spectrum of diesel particulate matter: Cluster analysis

    Corresponding author: JIN Taosheng, jints@nankai.edu.cn
  • Fund Project: Supported by National Key Research and Development Program of China (2017YFC0212100) and National Natural Science Foundation of China (21477057).
  • 摘要: 近年来在大气污染的防治工作中,柴油车污染防治的重要性日渐凸显.本文通过测试和文献检索等方法收集了97组与柴油车排放颗粒物无机元素排放有关的数据,采用k-means均值聚类分析的方法对数据进行分类并对分类结果进行分析,得出柴油车无机元素排放占颗粒物比例的大致区间为:Si(0—4.62%)、Al(0—1.53%)、Ca(0—4.09%)、Na(0—2.61%)、Mg(0—2.68%)、K(0—0.85%)、Fe(0—3.4%)、Zn(0—0.54%)、Cu(0—1.49%)、Ni(0—0.06%),且所得无机元素的排放区间的置信水平均大于94%.同时得到的柴油车排放颗粒物无机元素分析结果,可以为后续柴油车排放颗粒物无机元素数据分析以及相关污染治理提供参考,进而促进我国大气环境质量的改善、更好地保障人们身体健康.
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  • [1] 李晓丽, 戴培赟, 张吉亮,等.柴油机颗粒物的形成、危害及其控制方法[J]. 机电设备,2018,35(4):6-15.

    LI X L, DAI P Y, ZHANG J L, et al. The formation, harmness of diesel particulate matter and its control strategy[J]. Mechanical and Electrical Equipment, 2018, 35(4):6-15(in Chinese).

    [2] LIM M, AYOKO G A, MORAWSK L, et al. The effects of fuel characteristics and engine operating conditions on the elemental composition of emissions from heavy duty diesel buses[J]. Fuel, 2007, 86(12-13):1831-1839.
    [3] JIN T S, QU L, LIU S X, et al. Chemical characteristics of particulate matter emitted from a heavy duty diesel engine and correlation among inorganic and PAH components[J]. Fuel, 2014, 116:655-661.
    [4] GANGWAR J N, GUPTA T, AGARWAL A K. Composition and comparative toxicity of particulate matter emitted from a diesel and biodiesel fuelled CRDI engine[J]. Atmospheric Environment, 2012, 46:472-481.
    [5] 黄震, 李新令, 吕田,等.燃料特性对柴油机排放颗粒物理化特性影响的研究[J]. 内燃机学报,2016,34(2):97-104.

    HUANG Z, LI X L, LU T, et al. Effect of fuel properties on physicochemical characteristics of diesel engine exhaust PM[J]. Transactions of CSICE, 2016, 34(2):97-104(in Chinese).

    [6] MANPREET S S, MURARI M R. Glycerine emulsions of diesel-biodiesel blends and their performance and emissions in a diesel engine[J]. Applied Energy, 2018, 230:148-159.
    [7] KHALEK I A, BOUGHER T L, MERRITT P M, et al. Regulated and unregulated emissions from highway heavy-duty diesel engines complying with US Environmental Protection Agency 2007 emissions standards[J]. Journal of the Air & Waste Management Association, 2011, 61(4):427-442.
    [8] 邵忠瑛, 张仲荣, 高俊华.SCR后处理系统对柴油机颗粒物成分的影响研究[C]. 2010中国汽车工程学会年会论文集, 2010:375-378. SHAO Z Y, ZHANG Z R, GAO J H. Analysis of compounds in particulates from diesel engine using SCR post processing technology[C]. SEA-C2010P192

    ,2010:375-378(in Chinese).

    [9] 于涛.基于GM(1,1)模型预测柴油机润滑油金属元素含量的变化趋势[J]. 内燃机与动力装置,2016,33(3):34-36.

    YU T. Predicting the trend of metal element content in diesel engine lubricating oil based on GM(1,1) Model[J]. Internal Combustion Engine & Powerplant, 2016, 33(3):34-36(in Chinese).

    [10] 王燕军, 吉喆, 尹航,等.重型柴油车污染物排放因子测量的影响因素[J]. 环境科学研究,2014,27(3):232-238.

    WANG Y J, JI Z, YIN H, et al. Study of parameters influencing measurement on heavy duty diesel vehicle's emission factors[J]. Research of Environmental Sciences, 2014, 27(3):232-238(in Chinese).

    [11] 张延峰, 宋崇林, 成存玉,等.车用柴油机排气颗粒物中有机组分和无机组分的分析[J]. 燃烧科学与技术,2004,10:197-201. ZHANG Y F, SONG C L, CHENG C Y, et al. Analysis of the organic and inorganic components in the emission particulates from diesel engine[J]. Journal of Combustion Science and Technology, 2004

    , 10:197-201(in Chinese).

    [12] KIM O N T, THIANSATHI W, BOND T C, et al. Compositional characterization of PM2.5 emitted from in-use diesel vehicles[J]. Atmospheric Environment, 2010, 44(1):15-22.
    [13] 宋崇林, 王玉秋, 范国梁,等.柴油机排气颗粒中有机组分的分离方法及微量金属的测定[J]. 天津大学学报,2000,33(6):707-710.

    SONG C L, WANG Y Q, FAN G L, et al. Fractionation method of the soluble organic fraction of diesel exhaust particulates and the measurement of trace metal in diesel exhaust particulates[J]. Journal of Tianjin University, 2000, 33(6):707-710(in Chinese).

    [14] SCHAUER J J, KLEEMAN M J, CASS G R, et al. Measurement of emissions from air pollution sources.2. C1 through C30 organic compounds from medium duty diesel trucks[J]. Environmental Science & Technology, 1999, 33(10):1578-1587.
    [15] 黄成, 楼晟荣, 乔利平,等.重型柴油公交车实际道路颗粒物排放的理化特征[J]. 环境科学研究,2016,29(9):1352-1361.

    HUANG C, LOU S R, QIAO L P, et al. Physicochemical characteristics of real-world PM emissions from heavy-duty diesel buses[J]. Research of Environmental Sciences, 2016, 29(9):1352-1361(in Chinese).

    [16] United States Environmental Protection Agency. SPECIATE version 4.4.[DB/OL].[2019-03-07].https://www3.epa.gov/ttn/chief/software/speciate/index.html#speciate
    [17] CARIOU V, QANNARI E M, Statistical treatment of free sorting data by means of correspondence and cluster analyses[J]. Food Quality and Preference, 2018, 68:1-11.
    [18] JI X R, LU F H. K-means clustering analysis and evaluation for internet of acoustic environment characteristics[J]. Cognitive Systems Research, 2018, 52:603-609.
    [19] 石爱军, 马俊文, 耿春梅,等.北京市机动车尾气排放PM10组分特征研究[J]. 中国环境监测,2014,30(4):44-49.

    SHI A J, MA J W, GENG C M, et al. Characteristics of chemical composition of particulate matter (PM10) from Beijing Vehicle[J]. Environmental Monitoring in China, 2014, 30(4):44-49(in Chinese).

    [20] 张仲荣, 高俊华, 陈翠萍. ICP-MS研究柴油机排气颗粒物中的无机元素[C]. 2009中国汽车工程学会年会论文集, 2009. ZHANG Z R, GAO J H, CHEN C P. Investigation of inorganic elements in particulates from diesel engine emission by ICP-MS[C]. 2009 SAE-China Congress PROCEEDINGS, 2009(in Chinese).
    [21] MARIUSZ K, MIROSLAW P. Similarity and provenance of underpainting chalk grounds based on their nannofossil assemblages cluster analysis[J]. Journal of Cultural Heritage, 2018, 34:13-22.
    [22] DAYANA M A, ELBA C T, MARCEL F B, et al. Cluster analysis of urban ultrafine particles size distributions[J]. Atmospheric Pollution Research, 2019, 10:45-52.
    [23] JACOB J C, AHMED A M, SOPHIA E R B, et al. Parcellating cognitive heterogeneity in early psychosis-spectrum illnesses:A cluster analysis[J]. Schizophrenia Research, 2018, 202:91-99.
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  • 收稿日期:  2019-07-05
齐靖宇, 杨柳, 冯谦, 殷小鸽, 陆凯波, 金陶胜. 基于聚类方法下的柴油车排放颗粒物无机元素谱分析[J]. 环境化学, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502
引用本文: 齐靖宇, 杨柳, 冯谦, 殷小鸽, 陆凯波, 金陶胜. 基于聚类方法下的柴油车排放颗粒物无机元素谱分析[J]. 环境化学, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502
QI Jingyu, YANG Liu, FENG Qian, YIN Xiaoge, LU Kaibo, JIN Taosheng. Study and review on inorganic elements spectrum of diesel particulate matter: Cluster analysis[J]. Environmental Chemistry, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502
Citation: QI Jingyu, YANG Liu, FENG Qian, YIN Xiaoge, LU Kaibo, JIN Taosheng. Study and review on inorganic elements spectrum of diesel particulate matter: Cluster analysis[J]. Environmental Chemistry, 2020, (5): 1368-1374. doi: 10.7524/j.issn.0254-6108.2019070502

基于聚类方法下的柴油车排放颗粒物无机元素谱分析

    通讯作者: 金陶胜, E-mail: jints@nankai.edu.cn
  • 1. 南开大学环境科学与工程学院, 天津市城市交通污染防治研究重点实验室, 国家环境保护城市大气颗粒物污染防治重点实验室, 天津, 300350;
  • 2. 中交公路规划设计院有限公司, 北京, 100088;
  • 3. 中国汽车技术研究中心有限公司, 天津, 300300;
  • 4. 天津港保税区环境监测站, 天津, 300308
基金项目:

国家重点研发计划专项(2017YFC0212100)和国家自然科学基金面上项目(21477057)资助.

摘要: 近年来在大气污染的防治工作中,柴油车污染防治的重要性日渐凸显.本文通过测试和文献检索等方法收集了97组与柴油车排放颗粒物无机元素排放有关的数据,采用k-means均值聚类分析的方法对数据进行分类并对分类结果进行分析,得出柴油车无机元素排放占颗粒物比例的大致区间为:Si(0—4.62%)、Al(0—1.53%)、Ca(0—4.09%)、Na(0—2.61%)、Mg(0—2.68%)、K(0—0.85%)、Fe(0—3.4%)、Zn(0—0.54%)、Cu(0—1.49%)、Ni(0—0.06%),且所得无机元素的排放区间的置信水平均大于94%.同时得到的柴油车排放颗粒物无机元素分析结果,可以为后续柴油车排放颗粒物无机元素数据分析以及相关污染治理提供参考,进而促进我国大气环境质量的改善、更好地保障人们身体健康.

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