• Journal of Atmospheric and Environmental Optics
  • Vol. 17, Issue 3, 347 (2022)
Mingliang YANG* and Zongjiu ZHU
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3969/j.issn.1673-6141.2022.03.007 Cite this Article
    YANG Mingliang, ZHU Zongjiu. Simulation analysis of spatial distribution of PM2.5 concentration based on LUR model[J]. Journal of Atmospheric and Environmental Optics, 2022, 17(3): 347 Copy Citation Text show less
    References

    [1] Guo X B, Wei H Y. Progress on the health effects of ambient PM2.5 pollution[J]. Chinese Science Bulletin, 2013, 58(13): 1171-1177.

    [2] Sui W X, Wang H Y, Tang X, et al. Spatial-temporal distribution characteristics of PM2.5 and O3 over Shandong Province in 2015[J]. Environmental Monitoring in China, 2019, 35(2): 59-69.

    [3] Wu J S, Wang X, Li J C, et al. Comparison of models on spatial variation of PM2.5 concentration: A case of Beijing-Tianjin-Hebei region[J]. Environmental Science, 2017, 38(6): 2191-2201.

    [4] Zhang D, Woo S S. Real time localized air quality monitoring and prediction through mobile and fixed IoT sensing network[J]. IEEE Access, 2020, 8: 89584-89594.

    [5] Zhao X, Hou L L, Wang X L, et al. Simulation of spatial distribution of PM2.5 and PM10 concentrations in Beijing in 2019 based on LUR model[J]. Acta Scientiae Circumstantiae, 2020, 40(11): 4060-4069.

    [6] Briggs D J, Collins S, Elliott P, et al. Mapping urban air pollution using GIS: A regression-based approach[J]. International Journal of Geographical Information Science, 1997, 11(7): 699-718.

    [7] Luo Y Q. Critical Issues in Land Use Regression Modeling of PM2.5 Concentration[D]. Changsha: Central South University, 2014.

    [8] Hoek G, Beelen R, de Hoogh K, et al. A review of land-use regression models to assess spatial variation of outdoor air pollution[J]. Atmospheric Environment, 2008, 42(33): 7561-7578.

    [9] Tang R, Blangiardo M, Gulliver J. Using building heights and street configuration to enhance intraurban PM10, NOX, and NO2 land use regression models[J]. Environmental Science & Technology, 2013, 47(20): 11643-11650.

    [10] Li J. LUR-based Analysis and Simulation of the Temporal-Spatial Characteristics of AQI in Wuhan, China[D]. Wuhan: Central China Normal University, 2017.

    [11] Yang H O, Chen W B, Liang Z F. Relationship of PM2.5 concentration and land use type in Nanchang City based on LUR simulation[J]. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(6): 232-239.

    [12] Wang J J, Xia X S, Cheng, et al. Temporal and spatial distribution characteristics and influencing factors of PM2.5 concentration in Hefei City[J]. Resources and Environment in the Yangtze Basin, 2020, 29(06): 1413-1421.

    [13] Xu G, JiaoL M, Xiao F T, et al. Applying land use regression model to estimate spatial distribution of PM2.5 concentration in Beijing-Tianjin-Hebei region[J]. Journal of Arid Land Resources and Environment, 2016, 30(10): 116-120.

    [14] Gong P, Zhang W, Yu L et al. New research paradigm for global land cover mapping[J]. National Remote Sensing Bulletin 2016, 20(5): 1002-1016.

    [15] Wang R Z, Hu R M, Li P F et al. Monitoring and analysis of PM2.5 concentration spatial distribution based on LUR model[J]. Chinese Journal of Environmental Engineering, 2020, 14(10): 2843-2852.

    [16] Hoek G, Beelen R, Kos G, et al. Land use regression model for ultrafine particles in Amsterdam[J]. Environmental Science & Technology, 2011, 45(2): 622-628.

    [17] Henderson S B, Beckerman B, Jerrett M, et al. Application of land use regression to estimate long-term concentrations of traffic-related nitrogen oxides and fine particulate matter[J]. Environmental Science & Technology, 2007, 41(7): 2422-2428.

    [18] Wu J S, Li J C, Peng J, et al. Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China[J]. Environmental Science and Pollution Research International, 2015, 22(9): 7045-7061.

    [19] Wu J S, Liao X, Peng J, et al. Simulation and influencing factors of spatial distribution of PM2.5 concentrations in Chongqing[J]. Environmental Science, 2015, 36(3): 759-767.

    [20] Du B Q, Yang M L, Zhang J R. Simulation analysis of spatial distribution of PM2.5 concentration in Beijing based on the LUR model[J]. Journal of Langfang Normal University (Natural Science Edition), 2021, 21(04): 51-55.

    [21] Jiang X W, Ren ZY, Sun YJ. Spatial distribution simulation and influencing factors of PM2.5 in Xi'an City based on LUR and GIS[J]. Journal of Shaanxi Normal University (Natural Science Edition), 2017, 45(3): 80-87.

    [22] Han L, Zhao J Y, Gao Y J, et al. Spatial distribution characteristics of PM2.5 and PM10 in Xi'an City predicted by land use regression models[J]. Sustainable Cities and Society, 2020, 61: 102329.

    [23] Shi Y, Bilal M, Ho H C, et al. Urbanization and regional air pollution across South Asian developing countries—A nationwide land use regression for ambient PM2.5 assessment in Pakistan[J]. Environmental Pollution, 2020, 266: 115145.

    [24] Wang M, Beelen R, Bellander T, et al. Performance of multi-city land use regression models for nitrogen dioxide and fine particles[J]. Environmental Health Perspectives, 2014, 122(8): 843-849.

    [25] Song W Y, Yang Z, Wang P P, et al. Spatial distribution stimulation and population exposure of PM2.5 based on Land Use Regression—A case study of Hubei Province[J]. Journal of Central China Normal University (Natural Sciences), 2019, 53(3): 451-458.

    [26] Li J H, Zhu S W. Cautions about R2[J]. The Journal of Quantitative & Technical Economics, 2013, 30(9): 152-160.

    [27] Yuan X Y, Ye Z X, Yang H J, et al. Characteristics of fine particles in urban road atmospheric environment in Chengdu[J]. Chinese Journal of Environmental Engineering, 2015, 9(9): 4598-4602.

    [28] Wang Z S, Fu X, Wang Z S, et al. Research progress of the hygroscopicity of atmospheric Particles[J]. Research of Environmental Sciences, 2013, 26(4): 341-349.

    [29] Gao Z X, Ye J, Zhou H G, et al. The spatial-temporal characteristics of PM2.5 and PM10 and their relationships with meteorological factors in Jiangsu Province[J]. Environmental Science & Technology, 2020, 43(7): 51-58.

    [30] Luan T, Guo X L, Zhang T H, et al. The scavenging process and physical removing mechanism of pollutant aerosols by different precipitation intensities[J]. Journal of Applied Meteorological Science, 2019, 30(3): 279-291.

    [31] Zheng Y J, Wang M M, Sun M, et al. Pollution trend and correlation analysis of PM2.5 and PM10 in Qiqihar[J]. Environmental Monitoring in China, 2018, 34(1): 60-68.

    [32] Liang Z F, Chen W B, Zheng J, et al. Simulation of the distribution of main atmospheric pollutants and the influence of land use on them in central urban area of Nanchang City, China[J]. Chinese Journal of Applied Ecology, 2019, 30(3): 1005-1014.

    [33] Zhang H X, Cheng X F, Chen R H. Analysis on the spatial-temporal distribution characteristics and key influencing factors of PM2.5 in Anhui Province[J]. Acta Scientiae Circumstantiae, 2018, 38(3): 1080-1089.

    [34] Liu Y, Wang R S Zhang Y, et al. Dust concentration distribution patterns of different particulate matter in atmosphere in a surface coal mine of Wuhai City near the Yellow River during spring[J]. Science of Soil and Water Conservation, 2020, 18(3): 1-11.

    [35] Qiu Y, Wang J Q, Hu S H. Spatial-temporal distribution of PM2.5 and PM10-2.5 in Anhui Province, 2015-2016[J]. Journal of Hefei University of Technology (Natural Science), 2020, 43(1): 113-118.

    [36] Chen X, Du P, Guan Q, et al. Application of ICP-MS and ICP-AES for studying on source apportionment of PM2.5 during haze weather in urban Beijing[J]. Spectroscopy and Spectral Analysis, 2015, 35(6): 1724-1729.

    YANG Mingliang, ZHU Zongjiu. Simulation analysis of spatial distribution of PM2.5 concentration based on LUR model[J]. Journal of Atmospheric and Environmental Optics, 2022, 17(3): 347
    Download Citation