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Book cover Technical Challenges of Multipollutant Air Quality Management

Abstract

Air quality models simulate the atmospheric concentrations and deposition fluxes to the Earth’s surface of air pollutants by solving the mass conservation equations that represent the emissions, transport, dispersion, transformations and removal of those air pollutants and associated chemical species. Contemporary air quality models can be grouped into two major categories: (1) models that calculate the concentrations of air pollutants near a source (source-specific models) and (2) models that calculate concentrations of air pollutants over large areas ranging from an urban area, to a region, a continent and the globe (grid-based models). A few models combine both modeling approaches in a hybrid formulation. This chapter reviews the capabilities of current air quality models for estimating human exposure, ecological impact, risk assessment, and accountability. The chapter also discusses observations-based receptor models and their applications. The chapter summarizes the strengths and weaknesses of contemporary models in these application areas, and it provides recommendations for improving modeling capabilities.

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Notes

  1. 1.

    Source-specific models are Lagrangian models, which treat atmospheric dispersion as a source-specific process (i.e., the dispersion coefficients are a function of distance from the sources) whereas grid-based models are Eulerian models, which treat atmospheric dispersion as a characteristic of the ambient environment (i.e., dispersion coefficients are not related to any source characteristics). Source-specific Lagrangian models include steady-state Gaussian plume models such as AERMOD and non-steady-state puff dispersion models such as CALPUFF and SCICHEM.

  2. 2.

    Neighborhood scale calculations <1 km2 are much smaller than the resolution of grid-based models. Estimation of concentrations in this range require merging of plume models with the larger scale calculations.

  3. 3.

    The spatial resolution of the model output is typically coarser than the grid spacing because a grid model resolves horizontal features only at about four times the grid spacing.

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Acknowledgments

We acknowledge the following contributing authors: Agustin Garcia, Aron Jazcilevich, Michael Moran. Although this chapter has been subjected to the U.S. Environmental Protection Agency review and approved for publication, it does not necessarily reflect the views and policies of the Agency.

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Authors and Affiliations

  1. Université Paris-Est, 6 avenue Blaise Pascal Champs sur Marne, 77455, Marne la Vallée Cedex 2, France

    Christian Seigneur

  2. U.S. Environmental Protection Agency, 109 T W Alexander Drive, Mail Code: E243-01, 27711, Research Triangle Park, NC, USA

    Robin Dennis

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Correspondence to Robin Dennis .

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Editors and Affiliations

  1. Envair/Aerochem, Evergreen Drive 6, Placitas, 87043, New Mexico, USA

    George M. Hidy

  2. Environment Canada, Dufferin Street 4905, Downsview, M3H5T4, Ontario, Canada

    Jeffrey R. Brook

  3. , Atmospheric Sciences Research Center, University at Albany CESTM, Fuller Road 251, Albany, 12203, New York, USA

    Kenneth L. Demerjian

  4. Massachusetts Institute of Technology and Molina Center for Energy and the Environment, Holiday Court 3252, La Jolla, 92037, California, USA

    Luisa T. Molina

  5. Columbia Research and Education Associat, Pasco, 99301, Washington, USA

    William T. Pennell

  6. US Environmental Protection Agency, USEPA Mailroom, Research Triangle Park, 27711, North Carolina, USA

    Richard D. Scheffe

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© 2011 Springer Science+Business Media B.V.

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Seigneur, C., Dennis, R. (2011). Atmospheric Modeling. In: Hidy, G., Brook, J., Demerjian, K., Molina, L., Pennell, W., Scheffe, R. (eds) Technical Challenges of Multipollutant Air Quality Management. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0304-9_9

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