Source Sector Attribution of CO₂ Emissions Using an Urban CO/CO₂ Bayesian Inversion System

Abstract

We assimilate multiple trace gas species within a single high-resolution Bayesian inversion system to optimize CO 2 ff emissions for individual source sectors. Starting with carbon monoxide (CO), an atmospheric trace gas with fairly well-known emissions, we use emission factors of CO and CO 2 ff (called R CO ) defined for each source sector to enable us to jointly use CO and CO 2 atmospheric mole fractions to constrain CO 2 ff sectoral emissions. We first show that our combined CO-CO 2 inversion is theoretically capable of estimating the relative magnitude of sectoral emissions for two, specially defined sectors over Indianapolis, while CO 2 -only inversions failed at quantifying sectoral emissions. When assimilating hourly mole fractions collected over 4 months, inverse sectoral emissions converge toward high-resolution CO 2 ff bottom-up emissions from Hestia. The emission ratios between the two sectors agree within 15% with Hestia across various inversion configurations. The assimilation of CO mole fractions preferentially improves flux estimates from traffic emissions, because the CO levels originating from the combustion engine sector are large relative to those from other economic sectors. In a further investigation, we find that including an additional third tracer sensitive to the other sectors only slightly improves the accuracy of the inversion compared to our current two-sector inversions with CO and CO 2 mole fractions. We finally examined the impact of errors in trace gas emission factors and quantify their relative impact on sector-based inverse emissions. We conclude that multispecies inversions can constrain sectoral emissions at policy-level uncertainties if trace gas emission factors are sufficiently well known at the city level. Plain Language SummaryAs global urbanization grows rapidly, policymakers need to collect information about the relative changes in anthropogenic emissions from the different sectors of the economy in order to make informed policy decisions. However, bottom-up approaches, relying on activity data, remain the only methods able to produce emissions at the sector level. In our study, we investigate whether atmospheric inversions can help inform about CO 2 emissions from specific sectors of the economy through the inclusion of atmospheric measurements of non-CO 2 trace gases. Our results demonstrate that the joint optimization of atmospheric trace gases, here CO 2 and carbon monoxide (CO), within a single inversion framework can help characterize sector-level emissions of CO 2 over the city of Indianapolis, IN. Emissions from traffic are constrained in parallel with the other sectors of activities. City mitigation policies targeting specific sectors of the local economy can now be better evaluated by atmospheric measurements, with a nearly independent approach to provide more confidence in the effectiveness of emission reduction measures. These results will have important implications for policy makers and the carbon cycle community, reinforcing the link between policy decisi...

Policy-Relevant Assessment of Urban CO2 Emissions

“…Bottom-up emissions from the Hestia CO 2 emission product 21,32 are available for each of the eight economic sectors, merged into two main sectors of emissions 27 corresponding to low (referred to as stationary incl. residential, industrial, commercial, utility, airport, and railroad sectors) and high (ref to as mobile incl.…”

Greenhouse gas observation network design for Africa

“…A model-measurement error of 2 ppm was assigned to each three-hourly CO 2 mole fractions, similar to previous network designs for South Africa (Nickless et al, 2015(Nickless et al, , 2018b and Australia (Ziehn et al, 2014), and used in previous regional CO 2 inversions (Nathan et al, 2018). Following Ganesan et al 2015, we assigned modelmeasurement error uncertainties to each three-hourly CH 4 and N 2 O mole fraction observation of 10 ppb and 0.4 ppb, respectively.…”

Anthropogenic and natural controls on atmospheric <i>δ</i><sup>13</sup>C-CO<sub>2</sub> variations in the Yangtze River Delta: Insights from a carbon isotope modeling framework

“…As the urban population is expected to increase by 2.5 to 6 billion people in 2050, anthropogenic CO 2 emissions are projected to increase dramatically, especially in developing regions and countries (Sargent et al, 2018;Ribeiro et al, 2019). Under such a scenario, the observations of atmospheric CO 2 and 13 C-CO 2 in urban landscapes are of great importance to monitoring these potential CO 2 emissions hotspots (Lauvaux et al, 2016;Nathan et al, 2018;Graven et al, 2018;Pillai et al, 2016;Staufer et al, 2016).…”

“…By using CO 2 observations, the "top-down" atmospheric inversion approach is a useful tool to evaluate "bottom-up" inventories (Graven et al, 2018;L. Hu et al, 2019;Lauvaux et al, 2016;Nathan et al, 2018). Previous research has shown that additional information, such as data on atmospheric 14 CO 2 -CO 2 , 13 C-CO 2 , and CO, is needed to better distinguish CO 2 emissions from different sources and to assess their uncertainties (Chen et al, 2017;Graven et al, 2018;Nathan et al, 2018;Cui et al, 2019).…”

“…Hu et al, 2019;Lauvaux et al, 2016;Nathan et al, 2018). Previous research has shown that additional information, such as data on atmospheric 14 CO 2 -CO 2 , 13 C-CO 2 , and CO, is needed to better distinguish CO 2 emissions from different sources and to assess their uncertainties (Chen et al, 2017;Graven et al, 2018;Nathan et al, 2018;Cui et al, 2019). The use of hourly 13 C-CO 2 observation in urban areas remains rare in inversion studies, yet such observations contain invaluable information of anthropogenic CO 2 from different categories.…”