SEMINAR: Mapping urban air pollution at high resolution using Google Street View cars
Air pollution exposures vary sharply within cities, but conventional air quality measurement techniques provide little information on spatial patterns of air quality. This presentation explores how new approaches to making routine air pollution measurements using fleet vehicles offer the potential to map urban air quality at much higher spatial resolution than previously possible.
Using two Google Street View cars equipped with the fast-response Aclima Ei instrumentation platform, we measured air pollution on the streets of Oakland, CA for over 1 year, resulting in perhaps the largest mobile dataset of on-road air quality ever collected for a single city. We developed data reduction algorithms to estimate annual-average daytime pollution concentrations for Oakland's streets at 30-meter resolution. Repeated measurements reveal remarkably sharp and persistent spatial variability in concentrations of primary air pollutants within individual neighborhoods and city blocks. This scalable technique offers the potential to dramatically increase the resolution with which we understand intra-urban variability in pollution exposures, with potential application to US cities and low-income countries that currently struggle with poor ambient air quality.
Affiliate, Sustainable Energy Systems Group, Indoor Environment Group, Sustainable Energy & Environmental Systems Department, Energy Analysis & Environmental Impacts Division
Joshua Apte is an Assistant Professor of Environmental Engineering at the University of Texas, Austin. His research group uses field measurements and models to understand the relationships between urban emissions, population exposure, and human health. Previously, Dr. Apte was an ITRI-Rosenfeld Postdoctoral Fellow at Lawrence Berkeley National Laboratory and a Fulbright-Nehru fellow at the Indian Institute of Technology, Delhi. He holds a Ph.D. in Energy and Resources from UC Berkeley.