Published August 1, 2024 | Version v1
Software Open

Dataset parent CARB 19RD004: Daily pollutant concentrations of NO2, PM2.5 and O3 of 100 m resolution for California 2012-2019

  • 1. University of California, Berkeley
  • 2. Propeller Health*
  • 3. University of California, San Francisco
  • 4. University of California Los Angeles
  • 5. ResMed (United States)

Description

This study bridges gaps in air pollution research by examining exposure dynamics in disadvantaged communities. Using cutting-edge machine learning and massive data processing, we produced high-resolution (100 m) daily air pollution maps for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California from 2012 to 2019. Our findings revealed opposite spatial patterns of NO2 and PM2.5 to that of O3. We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019 though the most disadvantaged communities saw the largest NO2 and PM2.5 reductions and the advantaged neighborhoods experienced the greatest rising O3 concentrations. Further, day-to-day exposure variations decreased for NO2 and O3. The disparity in NO2 exposure decreased, while it persisted for O3. Additionally, PM2.5 showed increased day-to-day variations across all communities, due to the increase in wildfire frequency and intensity, particularly affecting advantaged suburban and rural communities.

Notes

Funding provided by: California Air Resources Board
ROR ID: https://ror.org/021h56y19
Award Number: 19RD004

Methods

This dataset was collected and processed as detailed in our Science Advances paper:

Jason G. Su, Vy Vuong, Eahsan Shahriary, Emma Yakutis, Emma Sage, Rebecca Haile, John Balmes, Michael Jerrett, Meredith Barrett. "Examining Air Pollution Exposure Dynamics in Disadvantaged Communities through High-Resolution Mapping." Science Advances, https://doi.org/10.1126/sciadv.adm9986.

Files

Google_Earth_Engine_scripts.zip

Files (243.7 kB)

Name Size Download all
md5:305e24358b7990a71086e8672be3b975
85.6 kB Download
md5:810f5c06254d7a93a16cca6bb83b4e57
23.3 kB Preview Download
md5:13435634729060de804d23a41081a9e2
103.5 kB Download
md5:befdb9333a16795d16a848c4e5b6ed0c
2.2 kB Download
md5:33c7188796c367455b17959e80d10924
2.1 kB Download
md5:fca3985723ae93ae25c11dfe6d18a564
2.0 kB Download
md5:fbbb17a216692a902f37159790846659
25.1 kB Download

Additional details

Related works

Is source of
10.5061/dryad.6djh9w18p (DOI)