Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban NeighborhoodsInternational Journal of Environmental Research and Public Health
SponsorFor financial assistance on this project, we are grateful to the United States Forest Service’s Urban and Community Forestry program (2011-DG-11062765-016), and the Institute for Sustainable Solutions at Portland State University.
- Trees in cities -- Oregon -- Portland,
- Urban forestry -- Oregon - Portland,
- Forests and forestry
AbstractReducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice.
Citation InformationShandas V, Voelkel J, Rao M, George L. (2016). Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods. International Journal of Environmental Research and Public Health. 13(8):790.