Science Inventory

Evaluating Regional-Scale Air Quality Models

Citation:

GILLILAND, A., J. M. GODOWITCH, C. Hogrefe, AND S.T. RAO. Evaluating Regional-Scale Air Quality Models. Chapter 4, Carlos Borrego, Ana Isabel Miranda (ed.), Air Pollution Modeling and Its Application XIX. Springer, New York, NY, , 412-419, (2008).

Impact/Purpose:

National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling Division (AMD) conducts research in support of EPA′s mission to protect human health and the environment. AMD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Description:

Numerical air quality models are being used to understand the complex interplay among emission loading meteorology, and atmospheric chemistry leading to the formation and accumulation of pollutants in the atmosphere. A model evaluation framework is presented here that considers several types of approaches, referred to here as the operational evaluation, diagnostic evaluation, dynamic evaluation, and probabilistic evaluation.

Record Details:

Record Type: DOCUMENT (BOOK CHAPTER)
Product Published Date: 08/03/2008
Record Last Revised: 10/24/2008
OMB Category: Other
Record ID: 199703

Organization:

U.S. ENVIRONMENTAL PROTECTION AGENCY

OFFICE OF RESEARCH AND DEVELOPMENT

NATIONAL EXPOSURE RESEARCH LABORATORY

ATMOSPHERIC MODELING DIVISION

APPLIED MODELING RESEARCH BRANCH