气候变化领域集成服务门户(CCPortal): Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore; India

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DOI	10.1016/j.atmosenv.2020.117395
	Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore; India
	Nori-Sarma A.; Thimmulappa R.K.; Venkataramana G.V.; Fauzie A.K.; Dey S.K.; Venkareddy L.K.; Berman J.D.; Lane K.J.; Fong K.C.; Warren J.L.; Bell M.L.
发表日期	2020
ISSN	13522310
卷号	226
英文摘要	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 R2, 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 (R2 = 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. © 2020 Elsevier Ltd
英文关键词	Air pollution; India; Kriging; LUR; Nitrogen dioxide; Spatial interpolation
语种	英语
scopus关键词	Air pollution; Air quality; Costs; Interpolation; Land use; Population statistics; Urban planning; India; Kriging; Leave-one-out cross validations; Low and middle income countries; Nitrogen dioxides; Pollution monitoring networks; Spatial interpolation; World Health Organization; Nitrogen oxides; nitrogen dioxide; air quality; ambient air; atmospheric pollution; human activity; interpolation; kriging; land use; model validation; nitrogen dioxide; pollution exposure; pollution monitoring; population density; prediction; sampling; urbanization; World Health Organization; air monitoring; air pollution; air quality; air sampling; ambient air; Article; autumn; concentration (parameter); cost effectiveness analysis; environmental exposure; human; human activities; India; industrial area; kriging; land use; land use regression; leave one out cross validation; population density; prediction; priority journal; rainy season; regression analysis; reliability; seasonal variation; spatial analysis; summer; urban area; winter; India; Mysore
来源期刊	Atmospheric Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145120
作者单位	Brown University School of Public Health, Providence, RI, United States; JSS Medical College, JSS Academy of Higher Education & Research, Mysore, KA, India; University of Mysore, Department of Studies in Environmental Science, Mysore, KA, India; University of Minnesota School of Public Health, Environmental Health Sciences Division, Minneapolis, MN, United States; Boston University School of Public Health, Boston, MA, United States; Yale University School of Forestry & Environmental Studies, New Haven, CT, United States; Yale University School of Public Health, New Haven, CT, United States; Department of Psychiatry, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States; Department of Environment, Government of Karawang Regency, KarawangWest Java, Indonesia
推荐引用方式 GB/T 7714	Nori-Sarma A.,Thimmulappa R.K.,Venkataramana G.V.,et al. Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore; India[J],2020,226.
APA	Nori-Sarma A..,Thimmulappa R.K..,Venkataramana G.V..,Fauzie A.K..,Dey S.K..,...&Bell M.L..(2020).Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore; India.Atmospheric Environment,226.
MLA	Nori-Sarma A.,et al."Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore; India".Atmospheric Environment 226(2020).