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Developing Spatially Interpolated Surfaces and Estimating Uncertainty.

PB2005103146

Publication Date	2004
Personal Author	Eberly, S.; Swall, J.; Holland, D.; Cox, B.; Baldridge, E.
Page Count	169
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.
Keywords	Air pollution monitoring Uncertainty estimates Computer software Model evaluation Model acceptance Limitations Alternatives References Radar imagery Common extension Spatially interpolated surfaces Spatial interpolation models Ordinary Kriging model
Source Agency	Air Quality Planning and Standards
Corporate Authors	Environmental Protection Agency, Research Triangle Park, NC. Emissions, Monitoring, and Analysis Div.; Environmental Protection Agency, Washington, DC. Office of Air and
Supplemental Notes	This document is color dependent and/or landscape layout. It is currently available on CD-ROM and paper only. CD-ROM contains a 169 page document. Sponsored by Environmental Protection Agency, Washington, DC. Office of Air and Radiation.
Document Type	Technical Report
NTIS Issue Number	200511

Developing Spatially Interpolated Surfaces and Estimating Uncertainty.

Developing Spatially Interpolated Surfaces and Estimating Uncertainty.
PB2005103146

Publication Date	2004
Personal Author	Eberly, S.; Swall, J.; Holland, D.; Cox, B.; Baldridge, E.
Page Count	169
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.
Keywords	Air pollution monitoring Uncertainty estimates Computer software Model evaluation Model acceptance Limitations Alternatives References Radar imagery Common extension Spatially interpolated surfaces Spatial interpolation models Ordinary Kriging model
Source Agency	Air Quality Planning and Standards
Corporate Authors	Environmental Protection Agency, Research Triangle Park, NC. Emissions, Monitoring, and Analysis Div.; Environmental Protection Agency, Washington, DC. Office of Air and
Supplemental Notes	This document is color dependent and/or landscape layout. It is currently available on CD-ROM and paper only. CD-ROM contains a 169 page document. Sponsored by Environmental Protection Agency, Washington, DC. Office of Air and Radiation.
Document Type	Technical Report
NTIS Issue Number	200511