Urban-focused satellite CO2 observations from the Orbiting Carbon Observatory-3: A first look at the Los Angeles megacity

Matthäus Kiel, Annmarie Eldering, Dustin D. Roten, John C. Lin, Sha Feng, Ruixue Lei, Thomas Lauvaux, Tomohiro Oda, Coleen M. Roehl, Jean Francois Blavier, Laura T. Iraci

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32 Scopus citations


NASA's Orbiting Carbon Observatory-3 (OCO-3) was designed to support the quantification and monitoring of anthropogenic CO2 emissions. Its Snapshot Area Map (SAM) and target mode measurements provide an innovative dataset for carbon studies on sub-city scales. Unlike any other current space-based instrument, OCO-3 has the ability to scan large contiguous areas of emission hot spots like cities, power plants, and volcanoes. These measurements result in dense, fine-scale spatial maps of column averaged dry-air mole fractions of carbon dioxide (XCO2). For the first time, we present and analyze XCO2 distributions over the Los Angeles megacity (LA) derived from OCO-3 SAM and target mode observations. Urban XCO2 enhancements range from 0 − 6 ppm (median enhancements ≃ 2 ppm) relative to a clean background and show excellent agreement with nearby ground-based TCCON measurements of XCO2. OCO-3's dense observations reveal intra-urban variations of XCO2 over the city that have never been observed from space before. The spatial variations are mainly driven by the complex fossil fuel emission patterns and meteorological conditions in the LA Basin and are in good agreement with those from co-located TROPOMI measurements of co-emitted NO2. Differences between measured and simulated XCO2 enhancements from two models (WRF-Chem and X-STILT) are typically below 1 ppm with larger differences for some sub regions. Both models capture the observed intra-urban XCO2 gradients. Further, OCO-3's multi-swath measurements capture about three times as much of the city emissions compared to single-swath overpasses. OCO-3's frequent target and SAM mode observations will pave the way to constrain urban emissions at finer, sub-city scales.

Original languageEnglish (US)
Article number112314
JournalRemote Sensing of Environment
StatePublished - Jun 1 2021

All Science Journal Classification (ASJC) codes

  • Soil Science
  • Geology
  • Computers in Earth Sciences


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