Reconciling the Differences Between a Bottom-Up and Inverse-Estimated FFCO2 Emissions Estimate in a Large U.S. Urban Area

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The INFLUX experiment has taken multiple approaches to estimate the carbon dioxide (CO2) flux in a domain centered on the city of Indianapolis, Indiana. One approach, Hestia, uses a bottom-up technique relying on a mixture of activity data, fuel statistics,

The INFLUX experiment has taken multiple approaches to estimate the carbon dioxide (CO2) flux in a domain centered on the city of Indianapolis, Indiana. One approach, Hestia, uses a bottom-up technique relying on a mixture of activity data, fuel statistics, direct flux measurement and modeling algorithms. A second uses a Bayesian atmospheric inverse approach constrained by atmospheric CO2 measurements and the Hestia emissions estimate as a prior CO2 flux. The difference in the central estimate of the two approaches comes to 0.94 MtC (an 18.7% difference) over the eight-month period between September 1, 2012 and April 30, 2013, a statistically significant difference at the 2-sigma level. Here we explore possible explanations for this apparent discrepancy in an attempt to reconcile the flux estimates. We focus on two broad categories: 1) biases in the largest of bottom-up flux contributions and 2) missing CO2 sources. Though there is some evidence for small biases in the Hestia fossil fuel carbon dioxide (FFCO2) flux estimate as an explanation for the calculated difference, we find more support for missing CO2 fluxes, with biological respiration the largest of these. Incorporation of these differences bring the Hestia bottom-up and the INFLUX inversion flux estimates into statistical agreement and are additionally consistent with wintertime measurements of atmospheric 14CO2. We conclude that comparison of bottom-up and top-down approaches must consider all flux contributions and highlight the important contribution to urban carbon budgets of animal and biotic respiration. Incorporation of missing CO2 fluxes reconciles the bottom-up and inverse-based approach in the INFLUX domain.