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Low-cost NO_2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore, India

机译:使用通用克里金法和土地利用回归模型对印度迈索尔进行低成本NO_2监测和城市暴露预测

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摘要

In Low- and Middle-Income Countries, rapid urbanization has led to poorer air quality, yet pollution monitoring networks are often sparse or non-existent. Few previous studies have sought to understand the unique predictors of air pollution exposure in Indian urban environments. Our study monitored and modeled nitrogen dioxide (NO2) in Mysore, a rapidly urbanizing city in India. NO2 sampling was conducted in four seasonal campaigns (each lasting 2 weeks) in 2016-2017, at 150 sites throughout Mysore. Seasonal spatial interpolation of NO2 levels was conducted using 2 distinct models, the first utilizing a land use regression (LUR) approach and the second using universal kriging methods. Model performance was determined using adjusted R-2, and validated using leave-one-out cross validation. Measured NO2 concentrations ranged from 0.3 to 51.9 ppb across the four seasons of the study period, with higher concentrations in the center of the city. In the LUR model (R-2 = 0.535), proximity to major roads, point sources of pollution such as industrial sites and religious points of interest (PoI), land uses with high human activity, and high population density were associated with higher levels of NO2. Proximity to minor roads and coverage of land uses characterized by low human activity were inversely associated with air pollution. Cross-validation of results confirmed the reliability of each model. Few studies have applied spatially heterogeneous sampling to assess ambient air pollution levels in India. The combination of passive NO2 sampling and LUR/kriging modeling methods allowed for characterization of NO2 patterns in Mysore. While previous work indicates traffic pollution as a major contributor to ambient air pollution levels in urbanizing centers in Asia, our results indicate the influence of other pollution factors (e.g., point sources), as well as highly localized characteristics of the urban environment (e.g., proximity to religious points of interest) in urban India. Areas of Mysore consistently experienced pollution in excess of World Health Organization (WHO) health-protective guidelines for NO2.
机译:在低收入和中等收入国家,快速的城市化导致空气质量较差,但污染监测网络通常很少或根本不存在。很少有以前的研究试图了解印度城市环境中空气污染暴露的独特预测因素。我们的研究监测和模拟了印度快速城市化城市迈索尔的二氧化氮(NO2)。在2016-2017年期间,在迈索尔的150个站点进行了四个季节性活动(每个持续2周)进行了NO2采样。使用2个不同的模型对NO2水平进行季节性空间插值,第一个模型使用土地利用回归(LUR)方​​法,第二个模型使用通用克里金法。使用调整后的R-2确定模型性能,并使用留一法交叉验证进行验证。在研究期的四个季节中,测得的NO2浓度范围为0.3到51.9 ppb,城市中心的浓度较高。在LUR模型(R-2 = 0.535)中,靠近主要道路,工业现场和宗教景点(PoI)等污染点源,人类活动频繁的土地利用和高人口密度与较高水平相关的NO2。靠近小路和以人类活动较少为特征的土地利用范围与空气污染成反比。结果的交叉验证确认了每个模型的可靠性。很少有研究应用空间异构采样来评估印度的环境空气污染水平。被动式NO2采样和LUR / kriging建模方法的结合可用于表征迈索尔中的NO2模式。虽然先前的工作表明交通污染是导致亚洲城市化中心环境空气污染水平的主要因素,但我们的结果表明其他污染因素(例如点源)的影响以及城市环境的高度局部化特征(例如,印度宗教景点附近)。迈索尔地区的污染持续超过世界卫生组织(WHO)的NO2健康保护准则。

著录项

  • 来源
    《Atmospheric environment》 |2020年第4期|117395.1-117395.11|共11页
  • 作者

  • 作者单位

    Brown Univ Sch Publ Hlth Providence RI 02912 USA;

    JSS Acad Higher Educ & Res JSS Med Coll Mysore Karnataka India;

    Univ Mysore Dept Studies Environm Sci Mysore Karnataka India;

    Univ Mysore Dept Studies Environm Sci Mysore Karnataka India|Govt Karawang Regency Dept Environm Karawang West Java Indonesia;

    JSS Acad Higher Educ & Res JSS Med Coll Mysore Karnataka India|Univ Illinois Coll Med Dept Psychiat Chicago IL USA;

    Univ Minnesota Sch Publ Hlth Environm Hlth Sci Div Minneapolis MN USA;

    Boston Univ Sch Publ Hlth Boston MA USA;

    Yale Univ Sch Forestry & Environm Studies New Haven CT 06511 USA;

    Yale Univ Sch Publ Hlth New Haven CT USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Air pollution; Nitrogen dioxide; Spatial interpolation; LUR; Kriging; India;

    机译:空气污染;二氧化氮;空间插值;LUR;克里格印度;

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