Comparison of the Space-Time Signatures of Air Quality Data From Different Monitoring Networks
Ambient air quality in the United States is measured by several regional air quality monitoring networks. Yet, differences in sampling protocol between the networks may not allow joint use of the data reported by different networks. In this study, we compare the space-time signatures of sulfate and nitrate fine particle mass concentrations reported by the Clean Air Status and Trend Network (CASTNet) and the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE). First, a spectral decomposition technique was used to separate the low and high frequency variations in time series of pollutant concentrations at collocated IMPROVE and CASTNet sites. Through Principal Component Analysis (PCA) and Varimax orthogonal rotation, we determined the number of significant sulfate and nitrate modes of variation identifiable with both networks, and identify the mode of variation characterizing each monitoring site. In the case of sulfate, both networks allow identification of seven distinct modes of variation, each of which corresponds to a well-defined geographic area. PCA also suggests the existence of seven modes of variation for nitrate but, in contrast to sulfate, these modes of variations could not be linked to any unified geographic area. A combination of spectral decomposition and PCA reveals that the long-term fluctuations in sulfate at both networks are virtually identical — when they are averaged in homogeneous regions defined by PCA — between both networks.
KeywordsSpectral Decomposition Improve Network Great Smoky Mountain Improve Data Varimax Orthogonal Rotation
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