Detection of Local-Scale Changes in Greenhouse Gas Emissions in Urban Environments Using Micrometeorological Methods and Comparison to High-Resolution Inventory

The Monin-Obukhov Similarity Theory (MOST) scalar flux-variance relationship was used to estimate greenhouse gas fluxes from tower-based mole fraction measurements at two urban sites in Indianapolis, IN, and one urban site in Los Angeles, CA, and compared to a high-resolution emissions inventory (Hestia). CO₂ fluxes were estimated at the two Indianapolis sites from 2013 through 2022 and at the Los Angeles site from 2015 through 2021. CH₄ fluxes were estimated at one of the Indianapolis sites from 2014 through early 2021 and at the Los Angeles site from 2015 through 2021. For the year 2020, CO fluxes were also estimated using the flux-variance relationship at all sites, and were used to estimate CO₂ fluxes from fossil fuel sources (CO₂ff). CO₂ff estimates for 2020 were compared to the estimated total CO₂ fluxes and the Hestia emissions inventory, which has an hourly temporal resolution and 20m spatial resolution surrounding each of the measurement sites. At the Indianapolis sites, there is a decrease in estimated CO₂ fluxes corresponding to the COVID-19 lockdown in 2020 relative to previous years, and 2021 fluxes are also lower than previous years at one of the sites. At the Los Angeles site, estimated CO₂ fluxes also show a decrease corresponding to the COVID-19 lockdown in 2020 relative to previous years. Estimated CH₄ fluxes do not show a decrease associated with the COVID-19 lockdown at either site. At the Los Angeles site, estimated CH₄ fluxes show a distinct increase in winter for all years, but this seasonality is not shown in the estimated CH₄ fluxes at the Indianapolis site. The 2020 MOST CO₂ff estimates and Hestia emissions show good temporal agreement, but the magnitude of the estimated emissions from these methods do not agree. It is not yet clear if this indicates a bias in the high resolution Hestia product or the flux estimation methodology. This work illustrates both the promise and the limitations in a new genre of observational and modeling methods suitable for quantifying changes in urban GHG metabolism at very high spatial and temporal resolutions. The micrometeorological methods can be evaluated in near real-time and quantify changes in emissions at neighborhood scale.