| Main Title |
Hierarchical Bayesian Model (HBM)-Derived Estimates of Air Quality for 2006, Annual Report. |
| Author |
E. S. Hall ;
F. Dimmick ;
J. Tikvart
|
| CORP Author |
Environmental Protection Agency, Research Triangle Park, NC. National Exposure Research Lab.; Environmental Protection Agency, Research Triangle Park, NC. Office of Air Quality Planning and Standards.; Environmental Protection Agency, Washington, DC. Office of Air and Radiation. |
| Year Published |
2010 |
| Report Number |
EPA/600/R-10/021; EPA-RW75922615-01-0; CDC-07FED63951 |
| Stock Number |
PB2010-107596 |
| Additional Subjects |
Mathematical models ;
Air quality ;
Hierarchical Bayesian model ;
Air quality monitors ;
Concentration values ;
Statistical fusion ;
Measured values ;
Predicted values
|
| Holdings |
| Library |
Call Number |
Additional Info |
Location |
Last
Modified |
Checkout
Status |
| NTIS |
PB2010-107596 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
| Collation |
168p |
| Abstract |
This report describes EPA's Hierarchical Bayesian model-generated (HBM) estimates of O(sub 3) and PM(sub 2.5) concentrations throughout the continental United States during the 2006 calendar year. HBM estimates provide the spatial and temporal variance of O(sub 3) and PM(sub 2.5), allowing estimation of their concentration values across the U.S., independent of where air quality monitors are physically located. HBM estimates are generated through the statistical fusion of measured air quality monitor concentration values and air quality model predicted concentration values from EPA's Community Multiscale Air Quality (CMAQ) computer model. Information on EPA's air quality monitors, CMAQ model, and HBM model is included to provide the background and context for understanding the data output presented in this report. The appendices provide detailed information on air quality data and the hierarchical Bayesian statistical modeling system. |
