AP-42道路交通扬尘排放模型评估及其在北京市的应用

樊守彬, 张东旭, 田灵娣. AP-42道路交通扬尘排放模型评估及其在北京市的应用[J]. 环境工程学报, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180
引用本文: 樊守彬, 张东旭, 田灵娣. AP-42道路交通扬尘排放模型评估及其在北京市的应用[J]. 环境工程学报, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180
Fan Shoubin, Zhang Dongxu, Tian Lingdi. Assessment for AP-42 model of road dust emissions and its application in Beijing, China[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180
Citation: Fan Shoubin, Zhang Dongxu, Tian Lingdi. Assessment for AP-42 model of road dust emissions and its application in Beijing, China[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180

AP-42道路交通扬尘排放模型评估及其在北京市的应用

  • 基金项目:

    国家科技支撑计划项目(2013BAC17B03)

    国家环保公益性行业科研专项(201409004)

    北京市环境保护科学研究院科技基金项目(2013-B-04)

  • 中图分类号: X701

Assessment for AP-42 model of road dust emissions and its application in Beijing, China

  • Fund Project:
  • 摘要: 对EPA推导AP-42模型的源数据划分范围,评估不同积尘负荷范围的线性回归模型的模拟效果。结果显示,在不同积尘负荷范围内(0~0.5、0.5~1、0~1、0~4和5~400 g/m2),线性回归模型参数以及方程R2值均有差异。对182个北京市道路积尘样品进行频数分布分析,发现积尘负荷主要分布在0~0.5 g/m2或0~1 g/m2范围内,分别运用道路积尘负荷0~0.5、0.5~1和0~1 g/m2范围的模拟回归模型,评估北京市铺装道路PM10的排放特征,尽管3个不同模型评估结果的平均值的比例是4:2:1,但是3个模型评估不同类型道路PM10排放因子的大小顺序是:支路> 次干道> 主干道> 快速路。
  • [1] Norman M., Johansson C. Studies of some measures to reduce road dust emissions from paved roads in Scandinavia. Atmospheric Environment, 2006, 40(32): 6154-6164
    [2] EPA. Emission factor documentation for AP-42, section 13.2.1 paved roads. Washington, DC: Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 2011: 1-13
    [3] Gaffney P., Bode R., Murchison L. PM10 emission inventory improvement program for California. 2020L Street, Sacramento, CA: Patrick Gaffney, Air Resources Board, 1995: 95814
    [4] Song Yu, Zhang Minsi, Cai Xuhui. PM10 modeling of Beijing in the winter. Atmospheric Environment, 2006, 40(22): 4126-4136
    [5] Song Yu, Zhang Yuanhang, Xie Shaodong, et al. Source apportionment of PM2.5 in Beijing by positive matrix factorization. Atmospheric Environment, 2006, 40(8): 1526-1537
    [6] Kuhns H., Etyemezian V., Green M., et al. Vehicle-based road dust emission measurement: Part II: Effect of precipitation, wintertime road sanding, and street sweepers on inferred PM10 emission potentials from paved and unpaved roads. Atmospheric Environment, 2003, 37(32): 4573-4582
    [7] Green M. C., Chow J. C., Chang M. C. O., et al. Source apportionment of atmospheric particulate carbon in Las Vegas, Nevada, USA. Particuology, 2013, 11(1): 110-118
    [8] Rutter A. P., Snyder D. C., Schauer J. J., et al. Contributions of resuspended soil and road dust to organic carbon in fine particulate matter in the Midwestern US. Atmospheric Environment, 2011, 45(2): 514-518
    [9] Karanasiou A., Moreno T., Amato F., et al. Road dust contribution to PM levels:Evaluation of the effectiveness of street washing activities by means of Positive Matrix Factorization. Atmospheric Environment, 2011, 45(13): 2193-2201
    [10] US EPA. National air pollutant emission trends, 1900-1998. Research Triangle Park, NC: Office of Air Quality Planning and Standards, USEPA, 2000: 2-11
    [11] CARB. 1996 Emission inventory. Sacramento, CA: CARB, 1998: 1-10
    [12] Kuhns H., Etyemezian V., Landwehr D., et al. Testing re-entrained aerosol kinetic emissions from roads: A new approach to infer silt loading on roadways. Atmospheric Environment, 2001, 35(16): 2815-2825
    [13] Pant P., Harrison R. M. Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: A review. Atmospheric Environment, 2013, 77: 78-97
    [14] Venkatram A. A critique of empirical emission factor models: A case study of the AP-42 model for estimating PM10 emissions from paved roads. Atmospheric Environment, 2000, 34(1): 1-11
    [15] Airborne Particles Expert Group. Source Apportionment of Airborne Particulate Matter in The United Kingdom. Wokingham: Transport Research Laboratory, 1999: 1-10
    [16] Düring I., Jacob J., Lohmeyer A., et al. Estimation of the "non exhaust pipe" PM10 emissions of streets for practical traffic air pollution modelling//Sturm P., Minarikp S. Proceedings of the 11th International Symposium, Transport and Air Pollution. Graz, Austria: Graz University of Technology, 2002: 309-316
    [17] 樊守彬, 田刚, 李钢, 等. 北京铺装道路交通扬尘排放规律研究. 环境科学, 2007, 28(10): 2396-2399 Fan Shoubin, Tian Gang, Li Gang, et al. Emission characteristics of paved roads fugitive dust in Beijing. Environmental Science, 2007, 28(10): 2396-2399(in Chinese)
    [18] 许妍, 周启星. 天津城市交通道路扬尘排放特征及空间分布研究. 中国环境科学, 2012, 32(12): 2168-2173 Xu Yan, Zhou Qixing. Emission characteristics and spatial distribution of road fugitive dust in Tianjin, China. China Environmental Science, 2012, 32(12): 2168-2173(in Chinese)
    [19] 彭康, 杨杨, 郑君瑜, 等. 珠江三角洲地区铺装道路扬尘排放因子与排放清单研究. 环境科学学报, 2013, 33(10): 2657-2663 Peng Kang, Yang Yang, Zheng Junyu, et al. Emission factor and inventory of paved road fugitive dust sources in the Pearl River Delta region. Acta Scientiae Circumstantiae, 2013, 33(10): 2657-2663(in Chinese)
    [20] Cowherd Jr C., Englehart P. J. Paved road particulate emissions. Washington DC: U.S. Environmental Protection Agency, 1984: 8-30
    [21] Nicholson K. A critique of empirical emission factor models: A case study of the AP-42 model for estimating PM10 emissions from paved roads. Atmospheric Environment, 2001, 35(1): 185-186
    [22] EPA. Emission factor documentation for AP-42, section 13.2.1, Paved Roads. Research Triangle Park, NC: Midwest Research Institute, 1993: 1-12
    [23] Zimmer R. A., Reeser W. K., Cummins P. Evaluation of PM10 emission factors for paved streets//Chow J. C., Ono D. M. PM10 Standards and Nontraditional Particulate Source Controls. Pittsburgh, PA: Air Waste Management Association, 1992: 311-323
    [24] Kantamaneni R., Adams G., Bamesberger L., et al. The measurement of roadway PM10 emission rates using atmospheric tracer ratio techniques. Atmospheric Environment, 1996, 30(24): 4209-4223
    [25] Ashbaugh L., Chang D., Flocchini R. G., et al. Traffic Generated PM10 "Hot Spots". Davis, CA: Air Quality Group, Crocker Nuclear Laboratory, University of California, 1996
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出版历程
  • 收稿日期:  2015-01-06
  • 刊出日期:  2016-06-03
樊守彬, 张东旭, 田灵娣. AP-42道路交通扬尘排放模型评估及其在北京市的应用[J]. 环境工程学报, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180
引用本文: 樊守彬, 张东旭, 田灵娣. AP-42道路交通扬尘排放模型评估及其在北京市的应用[J]. 环境工程学报, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180
Fan Shoubin, Zhang Dongxu, Tian Lingdi. Assessment for AP-42 model of road dust emissions and its application in Beijing, China[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180
Citation: Fan Shoubin, Zhang Dongxu, Tian Lingdi. Assessment for AP-42 model of road dust emissions and its application in Beijing, China[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2501-2506. doi: 10.12030/j.cjee.201412180

AP-42道路交通扬尘排放模型评估及其在北京市的应用

  • 1.  北京市环境保护科学研究院, 北京 100037
  • 2.  国家城市环境污染控制工程技术研究中心, 北京 100037
  • 3.  首都师范大学资源环境与旅游学院, 北京 100048
基金项目:

国家科技支撑计划项目(2013BAC17B03)

国家环保公益性行业科研专项(201409004)

北京市环境保护科学研究院科技基金项目(2013-B-04)

摘要: 对EPA推导AP-42模型的源数据划分范围,评估不同积尘负荷范围的线性回归模型的模拟效果。结果显示,在不同积尘负荷范围内(0~0.5、0.5~1、0~1、0~4和5~400 g/m2),线性回归模型参数以及方程R2值均有差异。对182个北京市道路积尘样品进行频数分布分析,发现积尘负荷主要分布在0~0.5 g/m2或0~1 g/m2范围内,分别运用道路积尘负荷0~0.5、0.5~1和0~1 g/m2范围的模拟回归模型,评估北京市铺装道路PM10的排放特征,尽管3个不同模型评估结果的平均值的比例是4:2:1,但是3个模型评估不同类型道路PM10排放因子的大小顺序是:支路> 次干道> 主干道> 快速路。

English Abstract

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