Understanding the health effects associated with air pollutants requires a detailed characterization of these pollutants in time and space, both in relation to sources and in ambient air. In earlier years, epidemiological studies focused primarily on examining correlations between air pollution measured at central site monitors and health outcomes. More recently, however, epidemiologists have begun to focus on the differences in exposures and health risks associated with intra-urban gradients in air pollutant concentrations, and on differential exposures to air pollution mixtures that arise due to transport and mixing of air pollution from a variety of sources (e.g., industry, traffic, and regionally transported pollution). The resulting requirements for highly resolved characterizations of pollutant mixtures are being met through increased use of air quality models. Health scientists conducting exposure/risk assessments and epidemiological studies are actively pursuing the use of model predictions to augment or replace ambient measurements. Regulatory assessments are increasingly being expected to identify susceptible populations that are vulnerable to pollutant exposures and to guide the development of source controls that will achieve greater risk reductions and health benefits.

These needs offer opportunities for using air quality models to forge a closer connection between air quality science and environmental health sciences. However, such uses create new challenges when applying modeling capabilities that the modeling community must understand and address with future research and development activities. Likewise, the health research community needs to understand important facets of such modeling, including the important differences between (1) statistical models based on observational air pollution data (e.g., land use regression) and (2) dispersion or chemistry-transport models such as AERMOD and CMAQ. This session is intended to promote dialogue between atmospheric and health scientists to improve our understanding of the modeling needs for various types of health studies, and of what models are available or need to be developed to meet these needs. Invited speakers will provide background information along with examples of various health studies and of how they use modeling and related techniques. We seek abstracts that illustrate examples of these studies, particularly those that have identified issues and compared approaches to inform the community of best practices and future developments needed in this important area of environmental research.

Work in recent years has vastly improved the science of air quality and methodologies for modeling and analyzing the distribution of air pollutants at various temporal and spatial scales. Such advances were motivated by the results from the multitude of applications and evaluations of air quality models that addressed various research, development and regulatory modeling issues. We seek abstracts that illustrate innovative methodologies and process algorithms in air quality modeling. This Session topics include (but are not limited to):

• Indirect radiative effect of aerosols
• Adjoint modeling
• Direct Decoupled Method (DDM)
• Variable and adaptive grids
• Hybrid modeling approaches
• Coupled meteorology/chemistry modeling
• Hemispheric chemistry-transport modeling
• Downscaling and data assimilation and nudging
• Meteorological processes
• Dust models

• Updates to inventories and emissions processing
• Emissions from alternative fuel use (e.g. bio-fuels in transportation sector)
• Projection of emissions to future-year scenarios
• Inverse modeling
• Natural emission sources

• Integrated modeling systems for decision support
• Human exposure and health impacts
• Economic impacts
• Regional air quality planning
• Public outreach

• Integrated assessment models
• Air pollution decision support systems
• Air pollution-health, -agriculture, and -ecological policies
• Decision making under uncertainty and uncertainty analysis
• Air pollution economics
• Design of pollution abatement strategies
• Coordinated air pollution/climate policies

• Model intercomparison
• Statistical analyses and evaluation metrics
• Measurement networks
• Impacts on air quality that result from controlling air pollutants

• Updates to inventories and emissions processing
• Emissions from alternative fuel use (e.g., bio-fuels in the transportation sector)
• Emissions from aviation activities
• Projection of emissions to future-year scenarios
• Inverse modeling
• Natural emission sources

• Regional climate impacts on air quality
• Impacts of air pollution on climate change
• Intercontinental transport of pollutants
• The climate impacts of short-lived climate forcers
• The impacts of clouds, as carrying media of pollutants and moisture, on climate
• International applications

• Diagnostic tools
• Analyses and comparisons with data from measurement networks
• Intermodel comparisons
• Process evaluation
• Evaluation of meteorological models

• Conventional measurement networks
• Field measurement studies
• Satellite data
• Data assimilation techniques

• Operational and computational needs
• Model performance evaluation and forecasting skills
• Objective analysis methods
• Accuracy and Spatial Resolution
• Public and media dissemination