Lagrangian meteorology and measurements of acidic precipitation at Washington, DC

Abstract

Measurements of pH from daily rainwater samples collected around the Washington, DC area during 1975 are compared to Lagrangian averages of temperature, rainfall, relative humidity and normalized concentration from a multiple source trajectory model. A linear regression procedure in which pH depends upon the previous four parameters was used to determine likely source regions during the year. The most consistent acidic rainfall occurred during an extended period from May to June when the flow as from the north. Some investigators have suggested that the rainfall at the receptor is a better predictor of pH than the Lagrangian precipitation. Tests of the four independent variables indicated that the most important predictor of pH during the summer was average rainfall along the trajectory (slope 0). The variability of the meteorological conditions along the pollutant trajectories was able to explain half of the variance of pH, suggesting that at least during summer complex chemical models may not be necessary to simulate acidic precipitation. During the winter, the results were more ambiguous, with the normalized concentration appearing to be the best predictor of pH.