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Scale Issues in Air Quality Modeling Policy Support
Citation:
Rao, S., H. Luo, M. Astitha, AND R. Mathur. Scale Issues in Air Quality Modeling Policy Support. Air Quality 2016, Milan, ITALY, March 14 - 18, 2016.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Description:
This study examines the issues relating to the use of regional photochemical air quality models for evaluating their performance in reproducing the spatio-temporal features embedded in the observations and for designing emission control strategies needed to achieve compliance with the relevant air quality standards. It is well known that various atmospheric processes, operating on different time and space scales, affect the pollutant concentration levels. In this study, we apply a spectral decomposition method to observed and modeled pollutant concentration time series spanning a 21-year period from 1990 to 2010 for discerning the scales of most interest for policy-making. The results reveal that the long-term component (i.e. the sum of seasonal and inter-annual variations) and the synoptic component (i.e. weather-induced variations) are particularly relevant to the air quality management decisions.
