... used an ensemble of dispersion model runs in a Bayesian inverse modeling framework to derive campaign-average posterior emission estimates for the New York–Newark, NJ, urban area of (125 ± 39) kmol CO 2 s –1 and (0.62 ± 0.19) kmol CH 4 s –1 (reported as mean ± 1σ variability across the nine flights...

... of top-down and bottom-up estimates to better inform the metrics used to monitor global CO 2 fluxes. Here we present a Bayesian inverse modeling framework over Salt Lake City, Utah, which utilizes available CO 2 emission inventories to establish a synthetic data simulation aimed at exploring model...