Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

Shandas, Vivek; Voelkel, Jackson; Rao, Meenakshi; George, Linda

doi:10.3390/ijerph13080790

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Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

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Toulan School of Urban Studies and Planning, Portland State University, 1825 SW Broadway, Portland, OR 97201, USA

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Academic Editor: Jason Corburn

Int. J. Environ. Res. Public Health 2016, 13(8), 790; https://doi.org/10.3390/ijerph13080790

Received: 30 April 2016 / Revised: 21 July 2016 / Accepted: 27 July 2016 / Published: 5 August 2016

(This article belongs to the Special Issue Urban Place and Health Equity)

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Abstract

Reducing 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. View Full-Text

Keywords: air pollution; dasymetric; urban; tree-planting

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Shandas, V.; Voelkel, J.; Rao, M.; George, L. Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods. Int. J. Environ. Res. Public Health 2016, 13, 790. https://doi.org/10.3390/ijerph13080790

AMA Style

Shandas V, Voelkel J, Rao M, George L. 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. 2016; 13(8):790. https://doi.org/10.3390/ijerph13080790

Chicago/Turabian Style

Shandas, Vivek, Jackson Voelkel, Meenakshi Rao, and Linda George. 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, no. 8: 790. https://doi.org/10.3390/ijerph13080790

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Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

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