A synoptic climatological approach to forecast concentrations of sulfur dioxide and nitrogen oxides in Hong Kong.

The objective of this study is to develop an automated synoptic climatological procedure to forecast high air pollution concentrations in the most polluted synoptic categories. The procedure is able to identify air masses historically associated with high air pollution concentrations. The arrival of air mass can be predicted 24 or 48 h in advance with the use of the weather forecast data. The development and statistical basis of the procedure are discussed, and an analysis of the procedure's ability to forecast weather conditions associated with high air pollution concentrations is presented. In addition, the dataset of 24 weather variables from 1993 to 1995 is used to validate the procedure. The procedure predicts that 70.3 and 83.3% of total high and severe SO2 concentration days fall into the identified most polluted categories, and the corresponding figures for NOx are 47.8 and 73.7%. The agreement between observed and predicted values is generally good. The prediction models can explain about 58 and 45% of total variance for NOx and SO2 with RMSEs of 42.5 and 16.5 microg m(-3), respectively. They are smaller than 1 SD of the observations.