268616 Investigating the Relationship Between the Built Environment, Air Quality, and Individual-Level Exposure: A Land Use Regression Approach

Wednesday, October 31, 2012

Jill Johnston , Department of Environmental Sciences and Engineering, University of North Carolina - Chapel Hill, Chapel Hill, NC
Theodore Mansfield, MCRP, MSEE , Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, NC
Research Scope Transportation emissions account for a significant portion of hazardous airborne pollutants in urban areas. However, the relationship between land use patterns, transportation behavior, air quality, and human exposure to airborne pollutants is complex and poorly understood. Existing studies rely on dispersion modeling techniques to predict air quality and are limited in terms of assessing human exposure to transportation emissions. Thus, this study uses land use regression as an alternative technique to predict local air quality and expands the analysis framework to estimate human exposure to emissions and associated burden of disease.

Research Plan This research will first calibrate a land use regression model to predict air quality at a fine geographic scale within the Raleigh-Durham metropolitan area in North Carolina. The regression model will be sensitive to both land use characteristics and traffic intensity. Existing land use regression models in the literature have proven quite successful in predicting local air quality in the United States; thus, local air quality data will be used to calibrate an existing model to local conditions. European studies have shown a high degree of transferability of land use regression models. Baseline population exposure to fine particulate matter will be calculated along with an estimate of the total burden of disease associated with fine particulate matter. A set of alternative land use scenarios will then be modeled, using a regional transportation demand model to predict travel behavior. The land use regression model will then be applied to the set of alternative land use scenarios. Once more, population exposure to fine particulate matter and estimates of associated burden of disease will be calculated. Parameters from each scenario will be compared, allowing for an analysis of the relationship between descriptive statistics of the built environment, local air quality, and human exposure to fine particulate matter.

Learning Areas:
Environmental health sciences
Other professions or practice related to public health
Public health or related public policy

Learning Objectives:
Define the magnitude of the change in human exposure to hazardous air pollutants associated with changes in the built environment Compare the effectiveness of various land use interventions in reducing human exposure to particulate matter Demonstrate the effectiveness of land use regression in assessing human exposure to hazardous air pollutants

Keywords: Urban Health, Hazardous Air Pollutants

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been co-principal investigator on multiple environmental health grants and have proficiency in environmental health risk assessments.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.