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Spatial Analysis Of Air Pollution And Development Of A Land-Use Regression Model In An Urban Airshed
Shaibal Mukerjee1*, Luther Smith2, Xiaojuan Liao2, Lucas Neas3, Casson Stallings2, and Mary Johnson3
1 - U.S. EPA/ORD/NERL E205-02, Research Triangle Park, NC, USA
2 - Alion Science & Technology, Durham, NC, USA
3 - U.S. EPA/ORD/NHEERL, Research Triangle Park, NC, USA
Introduction
All sampling in Detroit, Michigan, USA area during Summer 2005. Passive sampling of VOC & NO2 at 25 local elementary (PK-6) schools in Detroit and Dearborn Public Schools. Sampling also done at 2 State of Michigan regulatory (reg) sites. This poster presents the exposure component of the EPA/ORD Detroit Children’s Health Study (DCHS). Overall spatial assessment & development of land-use regression (LUR) model will be discussed. Approach based on spatial approach in El Paso Children’s Health Study (Smith et al., Atmos Environ 40 (2006) 3773-3787.
Discussion
Overall spatial analysis results suggested mobile source effect
throughout study area for VOCs. Only NO2 exhibited coarse spatial
difference between traffic/industrial-dominated city district versus a more residential district. In this study, regulatory sites were representative of neighboring locations. Regressions were not as successful as hoped a priori. Highest R2 values obtained for NO2. The relatively poor R2 values (and the overall spatial results) may be due to the fact that the hourly winds were found to be blowing in roughly equal proportions from each
compass quadrant during each week of the study. Winds were almost
always light to calm for the entire six-week period. Thus, the sites
were subjected to multiple influences for every measurement period.
Siting issues may have also contributed to these findings.
Collinearity present in some of the regressions; suggested by
coefficient values and collinearity diagnostics. Next efforts will address
collinearity and cross-validation will be applied to the final predictive
equations.
Based on tabulated results, traffic influences were important predictor variables for the Detroit/Dearborn area. In El Paso, traffic intensity (Int_1000) was only important for predicting NO2 (Smith et al., Atmos Environ 40 (2006) 3773-3787). In addition, distance from border crossing showed a consistent decline with increasing distance in El Paso; in Detroit, this was only the case for NO2. These preliminary findings from the Detroit area suggest possible local differences should be factored in when attempting to derive common exposure metrics from data collected in different urban air sheds.
Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.