Does urban form affect urban NO2? Satellite-based evidence for more than 1200 cities

Matthew J. Bechle, Dylan B. Millet, Julian D. Marshall

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Modifying urban form may be a strategy to mitigate urban air pollution. For example, evidence suggests that urban form can affect motor vehicle usage, a major contributor to urban air pollution. We use satellite-based measurements of urban form and nitrogen dioxide (NO2) to explore relationships between urban form and air pollution for a global data set of 1274 cities. Three of the urban form metrics studied (contiguity, circularity, and vegetation) have a statistically significant relationship with urban NO2; their combined effect could be substantial. As illustration, if findings presented here are causal, that would suggest that if Christchurch, New Zealand (a city at the 75th percentile for all three urban-form metrics, and with a network of buses, trams, and bicycle facilities) was transformed to match the urban form of Indio - Cathedral City, California, United States (a city at the 25th percentile for those same metrics, and exhibiting sprawl-like suburban development), our models suggest that Christchurch's NO2 concentrations would be ∼60% higher than its current level. We also find that the combined effect of urban form on NO2 is larger for small cities (β × IQR = -0.46 for cities < ∼300 000 people, versus -0.22 for all cities), an important finding given that cities less than 500 000 people contain a majority of the urban population and are where much of the future urban growth is expected to occur. This work highlights the need for future study of how changes in urban form and related land use and transportation policies impact urban air pollution, especially for small cities.

Original languageEnglish (US)
Pages (from-to)12707-12716
Number of pages10
JournalEnvironmental Science and Technology
Volume51
Issue number21
DOIs
StatePublished - Nov 7 2017

Bibliographical note

Funding Information:
This work was supported by the National Science Foundation under Grant No. 1236800, Minnesota Supercomputing Institute, and developed under Assistance Agreement No. RD83587301 awarded by the U.S. Environmental Protection Agency to Julian Marshall. It has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication.

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