Bayesian inverse estimation of urban CO2 emissions: Results from a synthetic data simulation over Salt Lake City, UT

Bayesian inverse estimation of urban CO2 emissions: Results from a synthetic data simulation over Salt Lake City, UT

Top-down, data-driven models possess ample power to improve the accuracy of bottom-up carbon dioxide (CO2) emission inventories, and more work is needed to explore the merger of top-down and bottom-up estimates to better inform the metrics used to monitor global CO2 fluxes. Here we present a Bayesia...

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Bibliographic Details
Main Authors: Lewis Kunik, Derek V. Mallia, Kevin R. Gurney, Daniel L. Mendoza, Tomohiro Oda, John C. Lin
Format: Article
Language:English
Published: BioOne 2019-09-01
Series:Elementa: Science of the Anthropocene
Subjects:
Salt Lake City
Urban CO2 emissions
Bayesian inverse modeling
OSSE
Error covariance parameters
Synthetic data
Online Access:https://www.elementascience.org/articles/375

Internet

https://www.elementascience.org/articles/375

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