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Spatial Prediction of Air Quality Data

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Abstract:Site-specific air quality monitoring data have been used extensively in both scientific and regulatory programs. As such, these data provide essential information to the public, environmental managers, and the atmospheric research community. Currently, air quality management practices use monitoring data as independent point measurements with an assumed area of representativeness (typically a county boundary). However, there is an increasing need to develop regional air quality management programs and associated regulatory policies using site measurements to make spatial statements at non-monitored locations. Based on deliberate statistical research over the past two decades and the advent of inexpensive, but powerful computing resources, there now exists well-accepted methodology for predicting pollutant values at unobserved locations across the entire spatial field of interest based on the data. This spatial information, coupled with prediction uncertainties, will enable air quality managers to construct better environmental management programs.
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Citation:Holland, D. M., W. M. Cox, R. Scheffe, A. J. Cimorelli, D. Nychka, and P. K. Hopke. Spatial Prediction of Air Quality Data. ENVIRONMENTAL MANAGER (August 2003):31-35, (2003).
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Contact: Chris Siebert - (702) 798-2234 or siebert.christopher@epa.gov
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Division: Environmental Sciences Division
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Branch: Landscape Characterization Branch (RTP)
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Product Type: Other Journl
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Published: 08/15/2003
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Related Entries:
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Bullet Item Atmospheric Ecosystem Stressor Pattern and Trend Analysis
spacer Relationship Reason:   A Project of the Product
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Bullet Item Environmental Statistics Initiative
spacer Relationship Reason:   A Project of the Product
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