Record Display for the EPA National Library Catalog

RECORD NUMBER: 27 OF 31

OLS Field Name OLS Field Data
Main Title United States Meteorological Data: Daily and Hourly Files to Support Predictive Exposure Modeling.
Author Burns, L. A. ; Suarez, L. A. ; Prieto, L. M. ;
CORP Author Environmental Protection Agency, Athens, GA.
Publisher May 2007
Year Published 2007
Report Number EPA/600/R-07/053;
Stock Number PB2007-110161
Additional Subjects Meteorological data ; Pesticides ; United States ; Air pollution monitoring ; Data files ; Numerical models ; Exposure ; Spray drift ; Predictive exposure modeling ; Climatological databases ; National Weather Service (NWS) datasets
Internet Access
Description Access URL
https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1000CO0.PDF
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB2007-110161 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. 10/08/2007
Collation 397p
Abstract
ORD numerical models for pesticide exposure include a model of spray drift (AgDisp), a cropland pesticide persistence model (PRZM), a surfacewater exposure model (EXAMS), and a model of fish bioaccumulation (BASS). A unified climatological database for these models has been assembled from several National Weather Service (NWS) datasets, including Solar and Meteorological Surface Observation Network (SAMSON) data for 1961-1990 (versions 1.0 and 1.1), combined with NWS precipitation and evaporation data. Together these NWS products provide coordinated access to solar radiation, sky cover, temperature, relative humidity, station atmospheric pressure, wind direction and speed, and precipitation. The resulting hourly and daily weather parameters providea unified dataset for use in coordinated exposure modeling. The data files, which include some derived data of use to exposure modeling (e.g., short-grass crop standard evapotranspiration ET(sub 0)) are publicly available (gratis) on EPA's Center for Exposure Assessment Modeling (CEAM) web site at http://www.epa. gov/ceampubl/tools/ metdata/index.htm. By using observational data for models, trace-matching Monte Carlo simulation studies can transmit the effects of environmental variability directly to exposure metrics, by-passing issues of correlation (covariance) amongexternal driving forces. This report covers a period from May 2, 2001 toDecember 27, 2004 and work was completed as of December 27, 2004.