Spatiotemporal Estimation of PM2.5 by Land Use Regression and Bayesian Maximum Entropy Method

被引：0
|
作者：
Yu, Hwa-Lung [1 ]
Wang, Chih-Hsin [1 ]
机构：
[1] Natl Taiwan Univ, Taipei 10764, Taiwan
来源：
EPIDEMIOLOGY | 2011年 / 22卷 / 01期
关键词：
D O I：
10.1097/01.ede.0000392214.28391.b3
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
引用
收藏
页码：S175 / S176
页数：2
相关论文
共 50 条
  • [1] Spatiotemporal analysis of PM2.5 in large coastal domains by combining Land Use Regression and Bayesian Maximum Entropy
    Jiang, Qu-Tu
    He, Jun-Yu
    Wang, Zhan-Shan
    Ye, Guan-Qiong
    Chen, Qian
    Xiao, Lu
    [J]. Zhongguo Huanjing Kexue/China Environmental Science, 2017, 37 (02): : 424 - 431
  • [2] Spatiotemporal modeling of PM2.5 concentrations at the national scale combining land use regression and Bayesian maximum entropy in China
    Chen, Li
    Gao, Shuang
    Zhang, Hui
    Sun, Yanling
    Ma, Zhenxing
    Vedal, Sverre
    Mao, Jian
    Bai, Zhipeng
    [J]. ENVIRONMENT INTERNATIONAL, 2018, 116 : 300 - 307
  • [3] Modeling of PM2.5 concentration prediction with maximum entropy method
    He, Jinqiang
    Liu, Yanna
    Li, Yang
    [J]. Journal of Computational and Theoretical Nanoscience, 2016, 13 (03) : 1861 - 1864
  • [4] The application of land use regression model to investigate spatiotemporal variations of PM2.5 in Guangzhou, China: Implications for the public health benefits of PM2.5 reduction
    Mo, Yangzhi
    Booker, Douglas
    Zhao, Shizhen
    Tang, Jiao
    Jiang, Hongxing
    Shen, Jin
    Chen, Duohong
    Li, Jun
    Jones, Kevin C.
    Zhang, Gan
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 778
  • [5] Application of Functional Principal Component Analysis in the Spatiotemporal Land-Use Regression Modeling of PM2.5
    Taghavi, Mahmood
    Ghanizadeh, Ghader
    Ghasemi, Mohammad
    Fasso, Alessandro
    Hoek, Gerard
    Hushmandi, Kiavash
    Raei, Mehdi
    [J]. ATMOSPHERE, 2023, 14 (06)
  • [6] A hybrid satellite and land use regression model of source-specific PM2.5 and PM2.5 constituents
    Rahman, Md Mostafijur
    Thurston, George
    [J]. ENVIRONMENT INTERNATIONAL, 2022, 163
  • [7] Estimation of Groundwater Radon in North Carolina Using Land Use Regression and Bayesian Maximum Entropy
    Messier, Kyle P.
    Campbell, Ted
    Bradley, Philip J.
    Serret, Marc L.
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2015, 49 (16) : 9817 - 9825
  • [8] A Land Use Regression Model for Predicting PM2.5 in Mexico City
    Texcalac Sangrador, J. L.
    Escamilla Nunez, M. C.
    Barraza Villarreal, A.
    Hernandez Cadena, L.
    Jerrett, M.
    Romieu, I
    [J]. EPIDEMIOLOGY, 2008, 19 (06) : S259 - S259
  • [9] Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5
    Wang, Meng
    Sampson, Paul D.
    Hu, Jianlin
    Kleeman, Michael
    Keller, Joshua P.
    Olives, Casey
    Szpiro, Adam A.
    Vedal, Sverre
    Kaufman, Joel D.
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2016, 50 (10) : 5111 - 5118
  • [10] Spatiotemporal Changes in PM2.5 and Their Relationships with Land-Use and People in Hangzhou
    Tian, Li
    Hou, Wei
    Chen, Jiquan
    Chen, Chaonan
    Pan, Xiaojun
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (10)
12345