Record Display for the EPA National Library Catalog

RECORD NUMBER: 43 OF 218

OLS Field Name OLS Field Data
Main Title Developing spatially interpolated surfaces and estimating uncertainty.
Author Eberly, S. ; Swall, J. ; Holland, D. ; Cox, B. ; Baldridge, E.
Other Authors
Author Title of a Work
Baldridge, Ellen.
CORP Author Environmental Protection Agency, Research Triangle Park, NC. Emissions, Monitoring, and Analysis Div.;Environmental Protection Agency, Washington, DC. Office of Air and Radiation.
Publisher U.S. Environmental Protection Agency, Office of Air and Radiation, Office of Air Quality Planning and Standards,
Year Published 2004
Report Number EPA-454/R-04-004
Stock Number PB2005-103146
OCLC Number 57664043
Additional Subjects Air pollution monitoring ; Uncertainity estimates ; Computer software ; Model evaluation ; Model acceptance ; Limitations ; Alternatives ; References ; Radar imagery ; Common extension ; Spatially interpolated surfaces ; Spatial interpolation models ; Ordinary Kriging model
Internet Access
Description Access URL
http://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1002QG4.PDF
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EJBD  EPA 454/R-04-004 Headquarters Library/Washington,DC 02/25/2005
EKBD  EPA-454/R-04-004 Research Triangle Park Library/RTP, NC 02/18/2005
NTIS  PB2005-103146 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 01/01/1988
Collation vi, 159 p. : ill. ; 28 cm.
Abstract
The need for spatial interpolation models in the regulatory environment has grown in the past few years. The EPA is using these models to review decisions on monitoring network design and to predict the efficacy of emission control programs. Due to the limited number of monitoring sites across the country for ambient concentrations of ozone and fine particles, there is a need to use spatial interpolation to predict ambient concentrations in unmonitored locations. Support for these methods has emerged from scientists and state/local/EPA agencies in recent workshops. The general consensus is that it is now possible to model the spatial dependence of air pollution data to reliably predict concentrations in unmonitored locations along with associated uncertainties for use in developing regulatory policy. EPA recognizes the merits of these methods, more specifically kriging, for use in the modeled attainment tests for the 8-hour ozone and PM 2.5 National Ambient Air Quality Standards attainment demonstrations. These methods provide environmental decision makers the opportunity to show important gradients of air pollution, review the location of monitoring networks and refine the definition of nonattainment boundaries. The purpose of this document is to provide an overview and better understanding of spatial interpolation methods.
Notes
Project Officer: Ellen Baldridge. "November 2004." "EPA-454/R-04-004." Includes bibliographical references. Battelle