Journal of Atmospheric and Environmental Optics, Volume. 16, Issue 6, 529(2021)

Temporal and Spatial Distribution Characteristics of PM2.5 in Chengdu Area Based on Remote Sensing Data and GWR Model

Hongliang JIA*, Jun LUO, and Dongsheng XIAO
Author Affiliations
  • [in Chinese]
  • show less
    References(27)

    [1] [1] Emili E, Popp C, Petittao M, et al. PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region[J]. Remote Sensing of Environment, 2010, 114(11): 2485-2499.

    [2] [2] Cheng Chunying, Yin Xuebo. Source, composition, formation and hazard of PM2.5 in haze[J]. University Chemistry, 2014, 29(5): 1-6.

    [3] [3] Suo Danfeng, Zeng Sanwu. Research on the harm of air fine particulate matter PM2.5 to various human systems[J]. Medical Information, 2019, 32(18): 32-34.

    [4] [4] Huang Wenxi. PM2.5 Quantitative Retrieval Based on the Remote Sensing and Ground-based Air Quality Measurement Data[D]. Wuhan: China University of Geosciences, 2019.

    [5] [5] Lu Debin, Mao Wanliu, Yang Dongyang, et al. Analysis on the trend and influencing factors of PM2.5 in China based on multi-source remote sensing data[J]. Resources and Environment in the Yangtze Basin, 2019, 28(3): 651-660.

    [6] [6] Shen Yang, Zhang Lianpeng, Fang Xing, et al. Correlation analysis and annual cycle characteristics of aerosol optical depth and PM2.5 concentrations in the Xuzhou City[J]. Earth and Environment, 2019, 47(1): 34-42.

    [7] [7] Li Chengcai, Mao Jietai, Liu Qihan, et al. Application of MODIS satellite remote sensing aerosol products in Beijing air pollution research[J]. Science in China, Series D: Earth Sciences, 2005, 35(SUP 1): 177-186.

    [8] [8] Yang Lijuan, Xu Hanqiu, Jin Zhifan. Estimation of ground-levelPM2.5concentrations using MODIS satellite data in Fuzhou, China[J]. Journal of Remote Sensing, 2018, 22(1): 64-75.

    [9] [9] Qin Wen, Wu Yunxia, Sheng Jie, et al. Study on quantitative inversion MODIS-AOD products and surface atmospheric particulate matter concentration in Nanchang city[J]. Guangzhou Chemical Industry, 2016, 44(23): 125-128.

    [10] [10] Lin Chuyong, Deng Yujiao, Xu Jianbo, et al. Temporal variation and spatial distribution of aerosol optical depth in Guangdong Province based on modis data[J]. Journal of Tropical Meteorology, 2015, 31(6): 821-826.

    [11] [11] Ren Yuxuan. Study on Satellite Remote Sensing Inversion Method of Ambient PM2.5 in Chengdu[D]. Chengdu: Southwest Jiaotong University, 2018.

    [12] [12] Hou Aihua, Gao Wei, Wang Zhongting, et al. Estimation of PM2.5 concentration from GF-1 data in Kaifeng City[J]. Remote Sensing for Land & Resources, 2017, 29(4): 161-165.

    [13] [13] Shi Lingzhi, Deng Qihong, Lu Chan, et al. Prediction of PM10 mass concentrations based on BP artificial neural network[J]. Journal of Central South University(Science and Technology), 2012, 43(5): 1969-1974.

    [14] [14] Ma Z, Liu Y, Zhao Q, et al. Satellite-derived high resolution PM2.5 concentrations in Yangtze River Delta Region of China using improved linear mixed effects model[J]. Atmospheric Environment, 2016, 133: 156-164.

    [15] [15] Fu Hongchen, Sun Yanling, Jing Yue. Estimating ground-level PM2.5 concentrations of Xinjiang based on geographically weighted regression model[J]. Journal of Tianjin Normal University (Natural Science Edition), 2019, 39(1): 63-70.

    [16] [16] Wu Jiansheng, Wang Xi, Li Jiacheng, et al. Comparison of models on spatial sariation of PM2.5 concentration: A case of Beijing-Tianjin-Hebei region[J]. Environmental Science, 2017, 38(6): 2191-2201.

    [17] [17] Lee H J, Liu Y, Coull B A. A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations[J]. Atmospheric Chemistry and Physics, 2011, 11(15): 7991-8002.

    [18] [18] Fu Hongchen, Sun Yanling, Wang Bin, et al. Estimation of PM2.5 concentration in Beijing-Tianjin-Hebei region based on AOD data and GWR model[J]. China Environmental Science, 2019, 39(11): 4530-4537.

    [19] [19] Chen Hui, Li Qing, Zhang Yuhuan, et al. Estimations of PM2.5 concentrations based on the method of geographically weighted regression[J]. Acta Scientiae Circumstantiae, 2016, 36(06): 2142-2151.

    [20] [20] Yi Wei, Yang Dong, Li Xirong. Inversion of PM2.5 concentration in the economic zone of northern Tianshan mountain slope based on the GWR model and the temporal and spatial characteristics[J]. Earth and Environment, 2021, 49(1): 51-58.

    [21] [21] Zhang Ying, Wang Shigong, Ni Changjian, et al. Study on an objective synoptic typing method for air pollution weather in Chengdu during winter[J]. Environmental Science & Technology, 2020, 43(5): 139-144.

    [22] [22] Li Peirong, Xiao Tiangui. The diffusion and transport of PM2.5 under the polluted weather conditions during autumn and winter seasons in Chengdu[J]. China Environmental Science, 2020, 40(1): 63-75.

    [23] [23] Zhang Yang. Inversion of Aerosol Optical Depth Based on the Multi-source Satellite Remote Sensing over Chengdu Region in Sichuan Province[D]. Chengdu: Chengdu University of Information Technology, 2015.

    [24] [24] Liang Jia. MODIS Combine Ground Monitoring Station Data to Monitor the Quality Concentration and the Diffusion of PM2.5—ShuangLiu District in Chengdu[D]. Chengdu: Chengdu University of Technology, 2018.

    [25] [25] Zhang Li, Zeng Zhiyuan. The study and implementation of extraction modis level 1B image data based on a HDF4 file[J]. Remote Sensing for Land & Resources, 2004, 16(4): 27-32.

    [26] [26] Fu Hongchen, Sun Yanling, Chen Li, et al. Temporal and spatial distribution characteristics of PM2.5 and PM10 in Xinjiang region in 2016 based on AOD data and GWR model[J]. Acta Scientiae Circumstantiae, 2020, 40(1): 27-35.

    [27] [27] McMillen D P. Geographically weighted regression: The analysis of spatially varying relationships[J]. American Journal of Agricultural Economics, 2004, 86(2): 554-556.

    Tools

    Get Citation

    Copy Citation Text

    JIA Hongliang, LUO Jun, XIAO Dongsheng. Temporal and Spatial Distribution Characteristics of PM2.5 in Chengdu Area Based on Remote Sensing Data and GWR Model[J]. Journal of Atmospheric and Environmental Optics, 2021, 16(6): 529

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Sep. 21, 2020

    Accepted: --

    Published Online: Feb. 11, 2022

    The Author Email: JIA Hongliang (jiars@foxmail.com)

    DOI:10.3969/j.issn.1673-6141.2021.06.007

    Topics