DOI: 10.1016/j.atmosenv.2014.08.015
Scopus记录号: 2-s2.0-84905670734
论文题名: GIS based assessment of the spatial representativeness of air quality monitoring stations using pollutant emissions data
作者: Righini G ; , Cappelletti A ; , Ciucci A ; , Cremona G ; , Piersanti A ; , Vitali L ; , Ciancarella L
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 97 起始页码: 121
结束页码: 129
语种: 英语
英文关键词: Air pollution
; Emissions
; GIS
; Monitoring networks
; Spatial representativeness
Scopus关键词: Air pollution
; Air quality
; Geographic information systems
; Image resolution
; Particulate emissions
; Pollution
; Geographic information systems
; Particulate emissions
; Air quality modeling
; Air quality monitoring stations
; Horizontal variability
; Long term exposure
; Monitoring network
; Monitoring stations
; Pollutants emissions
; Spatial representativeness
; Gis-based
; Pollutant emission
; Monitoring
; Air pollution
; concentration (composition)
; environmental quality
; GIS
; parameterization
; pollution monitoring
; spatial distribution
; air quality
; long-term change
; pollution exposure
; spatial analysis
; spatial resolution
; territory
; air monitoring
; air pollutant
; air pollution
; air quality
; article
; concentration (parameters)
; geographic information system
; Italy
; methodology
; neighborhood
; priority journal
; rural area
; statistical distribution
; urban area
; air pollutant
; air quality
; algorithm
; Article
; histogram
; hydrography
; industrial area
; long term exposure
; particulate matter
; population density
; spatial analysis
; Italy
; polycyclic aromatic hydrocarbon
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: Spatial representativeness of air quality monitoring stations is a critical parameter when choosing location of sites and assessing effects on population to long term exposure to air pollution. According to literature, the spatial representativeness of a monitoring site is related to the variability of pollutants concentrations around the site.As the spatial distribution of primary pollutants concentration is strongly correlated to the allocation of corresponding emissions, in this work a methodology is presented to preliminarily assess spatial representativeness of a monitoring site by analysing the spatial variation of emissions around it. An analysis of horizontal variability of several pollutants emissions was carried out by means of Geographic Information System using a neighbourhood statistic function; the rationale is that if the variability of emissions around a site is low, the spatial representativeness of this site is high consequently.The methodology was applied to detect spatial representativeness of selected Italian monitoring stations, located in Northern and Central Italy and classified as urban background or rural background. Spatialized emission data produced by the national air quality model MINNI, covering entire Italian territory at spatial resolution of 4×4km2, were processed and analysed.The methodology has shown significant capability for quick detection of areas with highest emission variability. This approach could be useful to plan new monitoring networks and to approximately estimate horizontal spatial representativeness of existing monitoring sites. Major constraints arise from the limited spatial resolution of the analysis, controlled by the resolution of the emission input data, cell size of 4×4km2, and from the applicability to primary pollutants only. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81035
Appears in Collections: 气候变化事实与影响
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作者单位: ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy
Recommended Citation:
Righini G,, Cappelletti A,, Ciucci A,et al. GIS based assessment of the spatial representativeness of air quality monitoring stations using pollutant emissions data[J]. Atmospheric Environment,2014-01-01,97