Using a Spatial Synoptic Climatological Classification to Assess Changes in Atmospheric Pollution Concentrations

A spatial synoptic climatological classification is developed for assessing spatial and temporal changes in atmospheric pollution concentrations. Based upon surface weather data for the conterminous United States for 1984, daily maps are produced depicting areas influenced by similar weather conditions. The classification is developed by applying principal components analysis to a daily matrix of 141 stations by 24 weather elements, chosen to represent both thermal/moisture conditions and surface air flow. The principal component scores are grouped using a two-stage clustering technique. The result is a map showing lobes of air which have relatively homogeneous meteorological characteristics and correspond to surface weather map features. The classification is then related to atmospheric concentrations of sulfur dioxide and nitrogen dioxide in nine cities. High concentrations are found in stable air masses and during strong anticyclonic control, whereas low concentrations occur in moist, unstable air masses. In addition, daily changes in pollution values exhibit strong relationships to synoptic types. Increasing concentrations are found in clusters identifying transitions to a stable environment (e.g., a cold front passage), while decreasing values are associated with transitions to increasing instability (e.g., increasing maritime flow). This type of analysis has potential utility in the establishment of a climatic baseline against which temporal variations in air quality can be analyzed. [Key words: synoptic climatology, climate classification, air pollution, air quality, principal components analysis, clustering, applied climatology.]