The Vulcan Version 3.0 High-Resolution Fossil Fuel CO2 Emissions for the United States.

Estimates of high-resolution greenhouse gas (GHG) emissions have become a critical component of climate change research and an aid to decision makers considering GHG mitigation opportunities. The "Vulcan Project" is an effort to estimate bottom-up carbon dioxide emissions from fossil fuel combustion and cement production (FFCO2) for the U.S. landscape at space and time scales that satisfy both scientific and policy needs. Here, we report on the Vulcan version 3.0 which quantifies emissions at a resolution of 1 km2/hr for the 2010-2015 time period. We estimate 2011 FFCO2 emissions of 1,589.9 TgC with a 95% confidence interval of 1,367/1,853 TgC (-14.0%/+16.6%), implying a one-sigma uncertainty of ~ ±8%. Per capita emissions are larger in states dominated by electricity production and industrial activity and smaller where onroad and building emissions dominate. The U.S. FFCO2 emissions center of mass (CoM) is located in the state of Missouri with mean seasonality that moves on a near-elliptical NE/SW path. Comparison to ODIAC, a global gridded FFCO2 emissions estimate, shows large total emissions differences (100.4 TgC for year 2011), a spatial correlation of 0.68 (R2), and a mean absolute relative difference at the 1 km2 scale of 104.3%. The Vulcan data product offers a high-resolution estimate of FFCO2 emissions in every U.S. city, obviating costly development of self-reported urban inventories. The Vulcan v3.0 annual gridded emissions data product can be downloaded from the Oak Ridge National Laboratory Distributed Active Archive Center (Gurney, Liang, et al., 2019, https://doi.org/10.3334/ORNLDAAC/1741).

Synthesis of Urban CO2 Emission Estimates from Multiple Methods from the Indianapolis Flux Project (INFLUX).

Urban areas contribute approximately three-quarters of fossil fuel derived CO2 emissions, and many cities have enacted emissions mitigation plans. Evaluation of the effectiveness of mitigation efforts will require measurement of both the emission rate and its change over space and time. The relative performance of different emission estimation methods is a critical requirement to support mitigation efforts. Here we compare results of CO2 emissions estimation methods including an inventory-based method and two different top-down atmospheric measurement approaches implemented for the Indianapolis, Indiana, U.S.A. urban area in winter. By accounting for differences in spatial and temporal coverage, as well as trace gas species measured, we find agreement among the wintertime whole-city fossil fuel CO2 emission rate estimates to within 7%. This finding represents a major improvement over previous comparisons of urban-scale emissions, making urban CO2 flux estimates from this study consistent with local and global emission mitigation strategy needs. The complementary application of multiple scientifically driven emissions quantification methods enables and establishes this high level of confidence and demonstrates the strength of the joint implementation of rigorous inventory and atmospheric emissions monitoring approaches.

High-resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX).

Based on a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs), we developed the first comprehensive monitoring systems of CO2 emissions at high resolution over the city of Indianapolis. The urban inversion evaluated over the 2012-2013 dormant season showed a statistically significant increase of about 20% (from 4.5 to 5.7 MtC ± 0.23 MtC) compared to the Hestia CO2 emission estimate, a state-of-the-art building-level emission product. Spatial structures in prior emission errors, mostly undetermined, appeared to affect the spatial pattern in the inverse solution and the total carbon budget over the entire area by up to 15%, while the inverse solution remains fairly insensitive to the CO2 boundary inflow and to the different prior emissions (i.e., ODIAC). Preceding the surface emission optimization, we improved the atmospheric simulations using a meteorological data assimilation system also informing our Bayesian inversion system through updated observations error variances. Finally, we estimated the uncertainties associated with undetermined parameters using an ensemble of inversions. The total CO2 emissions based on the ensemble mean and quartiles (5.26-5.91 MtC) were statistically different compared to the prior total emissions (4.1 to 4.5 MtC). Considering the relatively small sensitivity to the different parameters, we conclude that atmospheric inversions are potentially able to constrain the carbon budget of the city, assuming sufficient data to measure the inflow of GHG over the city, but additional information on prior emission error structures are required to determine the spatial structures of urban emissions at high resolution.