DOI: 10.1016/j.atmosenv.2014.05.010
Scopus记录号: 2-s2.0-84901494778
论文题名: Modeling spatiotemporal variability of intra-urban air pollutants in Detroit: A pragmatic approach
作者: O'Leary B ; F ; , Lemke L ; D
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 94 起始页码: 417
结束页码: 427
语种: 英语
英文关键词: Detroit
; GeoDHOC
; Spatial variability
; Spatiotemporal modeling
; Temporal variability
; Urban air quality
Scopus关键词: Benzene
; Nitrogen oxides
; Particles (particulate matter)
; Time series
; Detroit
; GeoDHOC
; Spatial variability
; Spatio-temporal models
; Temporal variability
; Urban air quality
; Air pollution
; benzene
; ethylbenzene
; nitrogen dioxide
; toluene
; xylene
; atmospheric pollution
; concentration (composition)
; data set
; interpolation
; particle size
; pollutant source
; pollution monitoring
; seasonal variation
; spatiotemporal analysis
; urban area
; air pollutant
; air pollution
; article
; density
; kriging
; measurement accuracy
; particulate matter
; pregnancy outcome
; priority journal
; seasonal variation
; spatiotemporal analysis
; time series analysis
; United States
; urban area
; Detroit
; Michigan
; United States
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: This study combined a three-year time series of air pollutant measurements from the Michigan Air Sampling Network (MASN) with spatially detailed datasets for two two-week periods in September 2008 and June 2009. The objective was to produce monthly pollutant concentration models for the city of Detroit, Michigan, USA from January 2008 through December 2010, in support of a related epidemiological study examining adverse birth outcomes in Detroit. Two gaseous analytes, NO2 (nitrogen dioxide) and total BTEX (benzene, toluene, ethyl-benzene, and xylene), as well as two particulate matter size fractions, PM2.5 and PM10, were investigated. The September 2008 and June 2009 datasets were modeled using ordinary kriging to produce high spatial density concentration maps with 300m by 300m resolution across the city. A weighted average was applied to these maps to generate a series of monthly spatial models for each pollutant. Temporal variability was then incorporated by adjusting each monthly spatial model using an average bulk shift derived from MASN time series measurements for the corresponding month over the three-year study period.The resulting models incorporate temporal trends while preserving neighborhood scale spatial variability. Seasonal variation was evident in NO2 models, but not readily discernable in BTEX or PM models across the three year study period. The greatest spatial and temporal variability was observed in the BTEX distributions, which are inferred to be strongly influenced by local sources. The methodology employed assumes that the interpolated monthly models adequately capture spatial variability of the air pollutants across the study area, the spatial distribution of pollutant concentrations remained consistent while their magnitude fluctuated from month to month, and that the available time series measurements reflect temporal trends across the city of Detroit throughout the three-year study period. © 2014 The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81129
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geology, Wayne State University, Detroit, MI, United States
Recommended Citation:
O'Leary B,F,, Lemke L,et al. Modeling spatiotemporal variability of intra-urban air pollutants in Detroit: A pragmatic approach[J]. Atmospheric Environment,2014-01-01,94