Rainwater composition analysis results

Although the measurement uncertainties limit the conclusions which can be drawn from these results, the data set proved useful for the determination of general Influences on rainwater composition In the Seattle area and for the demonstration of the application of these exploratory data analysis techniques. Current efforts to collect and analyze aerosol and rainwater samples over meteorologically appropriate time scales with precise analytical techniques are expected to provide better resolution of the factors controlling the composition of rainwater. 

The approach taken to observe the impact of the copper smelter on mesoscale variations rainwater composition was to determine the spatial, temporal, and experimental components of the variability of a number of appropriate chemical species in the rainwater. This paper presents results for 1985, during smelter operation, and includes (1) estimates of the experimental variability in chemical composition, (2) an approach for a two step chemical and statistical screening of the data set, (3) the spatial variation in rainwater composition for a storm collected on February 14-15, and (4) a principal component analysis of the rainwater concentrations to help identify source factors influencing our samples. 

Measurement of the experimental uncertainties in our rain sampling procedures and the application of these uncertainties in a screening procedure to eliminate questionable samples from the data set increases the confidence in the interpretation of spatial variations in rainwater composition and of the principal component analysis. Results presented here for a storm collected during smelter operation suggest that it was the major source of the downwind excess SO. elevation above background and the pH depress ion oelow the background value of 5. 

The probabilistic nature of a confidence interval provides an opportunity to ask and answer questions comparing a sample s mean or variance to either the accepted values for its population or similar values obtained for other samples. For example, confidence intervals can be used to answer questions such as Does a newly developed method for the analysis of cholesterol in blood give results that are significantly different from those obtained when using a standard method or Is there a significant variation in the chemical composition of rainwater collected at different sites downwind from a coalburning utility plant In this section we introduce a general approach to the statistical analysis of data. Specific statistical methods of analysis are covered in Section 4F. 

The basic idea is to reconstruct geochemical evolution of the groundwater from its chemical composition. For example, knowing the chemical composition of a well on the one hand and an analysis of the rainwater on the other, it will be possible to reconstruct which geological formation the rainwater must have passed after its infiltration to change its chemical composition as the result of reactions with mineral and gas phases (dissolution, precipitation, degassing) in a way that accounts for the composition of the water from the well. 

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