You are here:
Dispersion Modeling in Complex Urban Systems
Citation:
VALLERO, D. A., A. H. HUBER, AND P. J. LIOY. Dispersion Modeling in Complex Urban Systems. 2008, Chapter A-Z, David Blumel, Stefan Malmoli, Jessa Netting (ed.), Yearbook of Science and Technology. McGraw-Hill Companies, New York, NY, , 95-101, (2008).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA′s mission to protect human health and the environment. HEASD′s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA′s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools are improved regulatory programs and policies for EPA.
Description:
Models are used to represent real systems in an understandable way. They take many forms. A conceptual model explains the way a system works. In environmental studies, for example, a conceptual model may delineate all the factors and parameters for determining how a particle moves in the atmosphere after it has been released from a power plant. A conceptual model may also help identify the major influences on where a chemical is emitted and how likely it is to be found in the environment. Such models need to be developed to help target sources of data for assessing environmental problems. In general, developing an air pollution model involves two steps. First, a model of the domain and processes being studied must be defined and mathematical algorithms selected to represent the system. Then, the model boundary conditions are defined to represent the influence of the environment and other factors associated with the study. The quality of the model study is related to the accuracy and representativeness of the actual study.