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Applications of a simple regression model to acid rain data
Authors:Michael L Stein  Xiaotong Shen  Patricia E Styer
Abstract:This paper addresses two vital and seemingly simple questions concerning wet deposition of sulfates, a major contributor to acid rain. The first is to estimate the annual wet deposition of sulfate at a monitoring site under emissions that existed during the 1980s. This problem is complicated by missing data. The second is to estimate accurately the effect of a change in pollution emissions on concentrations of sulfate in precipitation. This problem is made difficult by the substantial natural variations in sulfate concentrations due to weather variations between years. As a tool for addressing both of these problems, we develop a regression model for the sulfate concentration of precipitation on a particular day as a function of amount of precipitation and time of the year. The model is used as a basis for imputing missing sulfate concentrations to handle the missing-data problem. It is also used to explain some of the variability in annual sulfate concentrations due to meteorology and hence provide more accurate estimates of the effect of changes in emissions.
Keywords:Missing data  imputation  nonlinear regression  pollution monitoring
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