Google releases first data of its project to map air pollution data

Users are now able to see maps for Oakland, CA of nitric oxide, nitrogen dioxide and black carbon-pollutants emitted from cars, trucks and other sources.

Google releases first data of its project to map air pollution data

Google along with its project partners — Environmental Defense Fund (EDF) and Aclima — has released the first results of an endeavor they started in 2015: to measure air quality using Aclima equipment mounted on Google Street View cars. As a result, users are now able to see maps for Oakland, CA, released by EDF, of nitric oxide (NO), nitrogen dioxide (NO2) and black carbon-pollutants emitted from cars, trucks and other sources.

The map shows street-level details to illustrate how pollution can change block by block. For example, the area where the Bay Bridge meets the I-80 has sustained higher pollution levels due to vehicles speeding up to cross under I-80 and merge onto the bridge.

It is the insights like these that could help community groups like the West Oakland Environmental Indicators Project get a better understanding of local air quality and assist regulators in identifying opportunities to achieve greater air quality improvements. And consequently, similar information can be applied to other cities, who are trying to understand local air quality patterns and implement solutions that improve the local environment.

Scientists can request access to the validated data now. You can also learn more about the science behind these maps in the journal Environmental Science & Technology, authored by a scientific team led by Dr. Joshua Apte, at the University of Texas-Austin.

Google has started working with EDF in 2014 on a project to map methane leaks. Next year, it included in its environmental projects to map air quality in Los Angeles, San Francisco and the Central Valley communities.

With nearly 3 million measurements and 14,000 miles captured in the course of a year, Google and its partners have created one of the largest air quality datasets ever, demonstrating the potential of neighborhood-level air quality mapping. This map makes the invisible – visible, and helping all of us understand how clean (or not clean) our air is, so that we can make changes to improve it.

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