Student Research: Stephanie Wong
MS, , 2010
Faculty Advisor: Joel D. Kaufman
A Spatial Model to Assess the Impact of Major Roadways on a Low Income Seattle Neighborhood using an Intensive NOx Sampling Campaign
Rationale: Traffic-related air pollutants are associated with several acute and chronic health effects. The Seattle Housing Authority plans a complete re-development of the Yesler Terrace neighborhood, immediately adjacent to, and downwind from, the I-5 highway; Yesler Terrace also has three other arterial roadways. The purpose of this study is to characterize the exposure to traffic related pollutants and assess the impacts of major roadway on the neighborhood in Seattle, WA, using oxides of nitrogen as surrogates for traffic-related air pollutants. This project can inform planners in creating healthier living environment for the residents.
Methods: In two separate snapshot campaigns, we deployed 125 passive sampling badges for two weeks duration, in an array to capture spatial variation and roadway impacts across this 2.5 square mile area. Samples were analyzed for NO2 and NOx and we calculated average ambient concentrations at each location for NO, NO2, and NOx. These data were entered into a Geographic Information System along with other geographic and meteorological information. The California Line Source Model (CALINE) was used to predict NO2 concentrations based on traffic information. The predicted values were used as a covariate to create a spatial model of the area and estimate roadway impacts with typically prevailing seasonal and annual wind patterns.
Results: Ambient concentrations of NO, NO2, and NOx ranged from 29.3-135.5 ppb, 18.3-42.4 ppb, and 47.7-175.0 ppb, across the area sampled during our monitoring campaigns. Spatial models are being finalized to determine impact of roadway line sources on these concentrations.
Conclusions: We anticipate being able to estimate effects of roadways on traffic-related air pollutant concentrations over the small scale present in an urban neighborhood. This information will be useful in identifying hotspots in pollutant concentrations, which can be used in planning locations of residential and recreational features during re-development of the neighborhood.