Author/Authors :
Zou، B نويسنده School of Info-Physics and Geomatics Engineering, Central South University, Changsha, Hunan, 410086, China , , Zhan، F.B نويسنده School of Resource and Environmental Science, Wuhan University, Wuhan, Hubei, 430079, China 3 Texas Center for Geographic Information Science, Department of Geography, Texas State University, San Marcos, TX, 78666, USA , , Zeng، Y نويسنده School of Info-Physics and Geomatics Engineering, Central South University, Changsha, Hunan, 410086, China , , Yorke، Ch نويسنده Texas Center for Geographic Information Science, Department of Geography, Texas State University, San Marcos, TX, 78666, USA , , Liu، X نويسنده Texas Center for Geographic Information Science, Department of Geography, Texas State University, San Marcos, TX, 78666, USA ,
Abstract :
This study investigates the effectiveness of the Kriging interpolation model and the Emission
Weighted Proximity Model (EWPM) in assessing relative exposure risk of air pollution using results from the
American Meteorological Society/EPA Regulatory Model (AERMOD) as benchmarks. We used simulated
exposure risk to SO2
in the Dallas area in Texas in this evaluation. Results suggest that the relative exposure
risks to SO2
at different locations in the study area as estimated by EWMP are closer to estimated risks from
AERMOD when compared with the results calculated by Kriging. In addition, study results also indicate that
the relative exposure risks calculated by Kriging are similar to those from AERMOD when the density of
emission sources in the area in question is high. It is therefore concluded that relative exposure risks determined
by both the Kriging interpolation method and the EWPM are acceptable when it is not possible to use
AERMOD. In situations when the density of emission sources is low in the study area, EWPM is a better
choice than Kriging.
