Abstract
This paper presents an analysis of trends in atmospheric concentrations of sulfur dioxide (SO 2 ) and particulate sulfate (SO 4 2− ) at rural monitoring sites in the Clean Air Act Status and Trends Monitoring Network (CASTNet) from 1990 to 1999. A two-stage approach is used to estimate regional trends and standard errors in the Midwest and Mid-Atlantic regions of the US. In the first stage, a linear regression model is used to estimate site-specific trends in data adjusted for the effects of season and meteorology. In the second stage, kriging methodology based on maximum likelihood estimation is used to estimate regional trends and standard errors. The method is extended to include a Bayesian analysis to account for the uncertainty in estimating the spatial covariance parameters. For both pollutants, significant improvement in air quality was detected that appears similar to the large drop in SO 2 power plant emissions. Spatial patterns of trends in SO 2 and SO 4 2− concentrations vary by location over the eastern US. For SO 2 , trends at monitoring sites in the Midwest and Mid-Atlantic were in the −30% to −42% range with smaller changes in the South. Across most of the US, trends in SO 4 2− were smaller than for SO 2 . Both spatial prediction techniques produced similar results in terms of regional trends and standard errors.
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