TY - JOUR
T1 - Modeling spatiotemporal variability of intra-urban air pollutants in Detroit
T2 - A pragmatic approach
AU - O'Leary, Brendan F.
AU - Lemke, Lawrence D.
N1 - Funding Information:
Funding for this project was provided by a grant from the W.K. Kellogg Foundation , P3018205 , and through a Wayne State University Career Development Grant . MASN data were provided by the Michigan Department of Environmental Quality Air Quality Division. The authors thank Gianluca Sperone and Christina Perlick at Wayne State University for technical support. We gratefully acknowledge valuable technical discussions with Xiaohong Xu at the University of Windsor and Craig Fitzner, Debbie Sherrod, and Amy Robinson at the MDEQ. This manuscript was improved by insightful comments from two anonymous reviewers. The content of this article is solely the responsibility of its authors.
PY - 2014/9
Y1 - 2014/9
N2 - 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.
AB - 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.
KW - Detroit
KW - GeoDHOC
KW - Spatial variability
KW - Spatiotemporal modeling
KW - Temporal variability
KW - Urban air quality
UR - http://www.scopus.com/inward/record.url?scp=84901494778&partnerID=8YFLogxK
U2 - 10.1016/j.atmosenv.2014.05.010
DO - 10.1016/j.atmosenv.2014.05.010
M3 - Article
AN - SCOPUS:84901494778
SN - 1352-2310
VL - 94
SP - 417
EP - 427
JO - Atmospheric Environment
JF - Atmospheric Environment
ER -
