DOI: 10.1016/j.atmosenv.2015.04.029
Scopus记录号: 2-s2.0-84927733717
论文题名: Spatial distribution of vehicle emission inventories in the Federal District, Brazil
作者: Réquia W ; J ; , Koutrakis P ; , Roig H ; L
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 112 起始页码: 32
结束页码: 39
语种: 英语
英文关键词: Air pollution
; Spatial patterns
; Vehicle emission inventories
Scopus关键词: Air pollution
; Airships
; Autocorrelation
; Cluster analysis
; Health risks
; Pollution
; Spatial distribution
; Vehicles
; Air pollution monitoring
; Heavy duty vehicles
; Light duty vehicles
; Pollutant concentration
; Spatial autocorrelation analysis
; Spatial patterns
; Vehicle emission
; Vehicular emission
; Spatial variables measurement
; carbon dioxide
; carbon monoxide
; hydrocarbon substituent
; methane
; nitrogen oxide
; atmospheric pollution
; autocorrelation
; bottom-up approach
; carbon monoxide
; cluster analysis
; emission control
; emission inventory
; health risk
; policy development
; pollution monitoring
; prediction
; public health
; spatial distribution
; traffic emission
; urban region
; air monitoring
; Article
; Brazil
; controlled study
; exhaust gas
; motorcycle
; priority journal
; suspended particulate matter
; urban area
; Brazil
; Federal District [Brazil]
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p<0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81721
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Environmental Health, Harvard School of Public Health, 401 Park Drive, Landmark Center West, Boston, MA, United States; Geoscience Institute, University of Brasília, Campus Darcy Ribeiro, Brasília, Distrito Federal, Brazil
Recommended Citation:
Réquia W,J,, Koutrakis P,et al. Spatial distribution of vehicle emission inventories in the Federal District, Brazil[J]. Atmospheric Environment,2015-01-01,112