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Detecting Urban Emissions Changes and Events With a Near-Real-Time-Capable Inversion System

Published

Author(s)

Kimberly L. Mueller

Abstract

In situ observing networks are increasingly being used to study greenhouse gas emissions in urban environments. While the need for sufficiently dense observations has often been discussed, density requirements depend on the question posed and interact with other choices made in the analysis. Focusing on the interaction of network density with varied meteorological information used to drive atmospheric transport, we perform geostatistical inversions of methane flux in the South Coast Air Basin, California, in 2015–2016 using transport driven by a locally tunedWeather Research and Forecasting configuration as well as by operationally available meteorological products. We find total-basin flux estimates vary by as much as a factor of two between inversions, but the spread can be greatly reduced by calibrating the estimates to account for modeled sensitivity. Using observations from the full Los Angeles Megacities Carbon Project observing network, inversions driven by low-resolution generic wind fields are robustly sensitive (p
Citation
Journal of Geophysical Research-Atmospheres

Citation

Mueller, K. (2019), Detecting Urban Emissions Changes and Events With a Near-Real-Time-Capable Inversion System, Journal of Geophysical Research-Atmospheres, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928110 (Accessed April 18, 2024)
Created May 16, 2019, Updated June 5, 2019