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Observational Needs for Four-Dimensional Air Quality Characterization
Citation:
SCHEFFE, R., R. Philbrick, C. MacDonald, T. Dye, M. Gilroy, AND A. G. CARLTON. Observational Needs for Four-Dimensional Air Quality Characterization . EM: AIR AND WASTE MANAGEMENT ASSOCIATION'S MAGAZINE FOR ENVIRONMENTAL MANAGERS. Air & Waste Management Association, Pittsburgh, PA, (10/2009):5-12, (2009).
Impact/Purpose:
The 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:
Surface-based monitoring programs provide the foundation for associating air pollution and causal effects in human health studies, and they support the development of air quality standards and the preparation of emission reduction strategies. While surface oriented networks remain a key tool for addressing traditional single pollutant human exposure challenges, these networks in isolation arc not capable of adequately addressing emerging assessment challenges that consider linkages across pollutant categories, spatial scales, and environmental media. This increasing complexity of air quality assessments will gradually accelerate the reliance on environmental modeling systems featuring multi-dimensional descriptions in time and space. Accordingly, our design perspectives on observation systems must adapt complementary observation and modeling approaches. Paralleling this increased importance of models are major concerns about the adequacy of existing observation systems to provide the observations needed to support model evaluations and data assimilations for day-to-day operational assessments of the environment. For example, a model's ability to characterize surface air quality and deposition depends on properly characterizing physical and chemical processes throughout the atmospheric column, as well as the larger scale regional transport into the area. Because most pollutants and precursors for chemical and aerosol production reside above the immediate surface where point sensors provide measurements, it becomes important to examine the spatial and temporal heterogeneity through the atmospheric column. This article provides an overview of observation systems in use today to address comprehensive characterization of the planetary boundary layer, air quality and meteorological variables, and puts forth a series of recommendations to be considered in addressing important observations gaps.
URLs/Downloads:
Observational Needs for Four-Dimensional Air Quality Characterization (PDF, NA pp, 4093 KB, about PDF)EM
