The Bay Area Air Quality Management District has formed a partnership with Aclima to use roving air sensors that will gather detailed pollution data from across the San Francisco metro area.
Measuring air quality in California’s Bay Area is now happening block-by-block, with roving air-quality monitoring sensors that aim to drive down every publicly available street in the nine-county region.
This novel work is part of an effort to collect detailed air pollution data, which experts say can vary greatly not only block-to-block, but even within the same city block. This new project, which was announced this week, is a partnership between the Bay Area Air Quality Management District (BAAQMD) and Aclima, an air-quality monitoring tech company.
“What we’re here to celebrate today is the hyper-local air quality data in the nine-county region,” Jack Broadbent, CEO of the Air District, announced during a press event Tuesday in San Francisco. “The Air District is investing in innovation to bring an unprecedented level of visibility of air pollution and climate emissions. This project will help shine a light on the disparate health impacts faced by many in the region. And it will inform lawmakers to better guide our decision-making process to protect the health of all Bay Area residents moving forward.”
The Bay Area Air Quality Management District, which covers some 5,000 square miles and serves more than 7.5 million residents, has one of the most extensive air monitoring networks in the nation. Despite this reach, however, the BAAQMD has not previously been able to mine detailed air quality data at the neighborhood level, said Broadbent. This is poised to change.
“For the first time in our entire region, low-emission cars will be equipped with air-quality sensing devices as they drive multiple times over every publicly accessible street in the Bay Area,” said Ranyee Chiang, director of meteorology and measurements at the Air District, explaining some of the project’s details.
The data from the drives, conducted throughout 2020 and 2021, will be combined with other air district data to map out block-by-block air-quality across a range of pollutants like ozone and nitrogen dioxide. The data will ultimately be publicly available via the Air District website.
Pollution levels can vary from five to eight times from one end of a city block to another, Aclima officials say. The data is hyper-local but not necessarily real-time, since it’s averaged over several months to get a more holistic view of the air quality on a block or region. One hope is that the new data will help stakeholders identify pollution hot spots that they can then target for emissions reductions, Chiang said.
It's a first for the region, and it's generating excitement among those who work in the space.
“For the first time, we’ll have an in-depth, comprehensive picture of hyper-local air quality across all nine counties of the Bay Area,” said Davida Herzl, CEO of Aclima, in her comments.
“This new transformative visibility into the health of our environment provides a critical tool, supporting and accelerating action to reduce emissions, protect the public, and protecting the health of our planet,” she added. “Because ultimately, the emissions that are polluting the air we breathe are also changing out climate, profoundly impacting human health and creating multi-billion dollar impacts across our economies.”
Late last year the Air District and Aclima began monitoring the first community in the Richmond-San Pablo area.
“With Aclima, it was the first time that we could get data to back up the suspicions that people in the community had,” said Randy Joseph, representing the RYSE youth center in Richmond, Calif.
What is perhaps most innovative about this work is the mobility of the sensors. Numerous cities, including Chicago and others, have deployed stationary air-quality sensors on streetlights and other pieces of the urban landscape to gather detailed, neighborhood-level measurements of air pollution. The roving sensors are what set this new project apart, creating the potential to collect an unprecedented data set.
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