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

Abstract

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 CO 2 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 CO 2 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 CO 2 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 CO 2 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.

Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

“…The Indianapolis Flux Experiment (INFLUX, http://sites.psu.edu/influx/) was proposed to develop, test and improve methods to estimate anthropogenic GHG emissions from cities, using Indianapolis as a test bed . This project uses aircraft (Cambaliza et al, 2014;Heimburger et al, 2017) and a high-density surface tower network Richardson et al, 2017) combined with high-resolution atmospheric modeling Sarmiento et al, 2017) to infer CO 2 ff emissions at 1 km spatial resolution (Lauvaux et al, 2016). Figure 1 shows the distribution of instrumented towers and daytime average surface CO 2 fluxes during the first 10 days of September 2013.…”

“…Top-down methods infer quantitative information on surface CO 2 fluxes from variations in atmospheric CO 2 concentrations through inverse modeling with atmospheric tracer transport models (Ciais et al, 2011), and may include isotope composition measurements to identify fossil fuel sources (Levin et al, 2003;Miller et al, 2012;Turnbull et al, 2015;Basu et al, 2016). Uncertainties in atmospheric transport models (Peylin et al, 2002;Lauvaux et al, 2009;Peylin et al, 2011;Isaac et al, 2014), limited density of atmospheric measurements (Gerbig et al, 2009;Turner et al, 2016) and uncertainties in prior fluxes (Peylin et al, 2005;Carouge et al, 2010;Lauvaux et al, 2016) all constitute sources of error in this method (Engelen et al, 2002).…”

“…In addition, the inverse estimation of CO 2 ff emissions is constrained by atmospheric CO 2 measurements, and the trade-off between measurement density and quality is an important emerging debate for urban GHG monitoring (Wu et al, 2016;Shusterman et al, 2016;Turner et al, 2016;Martin et al, 2017). Lastly, uncertain spatial structures in prior flux errors influence the precision of inverse flux estimates (Saide et al, 2011;Lauvaux et al, 2016). Therefore, studying the impacts of CO 2 bio fluxes, atmospheric transport errors, observation deployment strategies and prior flux error structures on CO 2 ff flux estimates are important considerations for advancing our understanding of uncertainties in the estimation of anthropogenic carbon emissions in an urban environment.…”

“…Figure 1 shows the distribution of instrumented towers and daytime average surface CO 2 fluxes during the first 10 days of September 2013. The availability of a highresolution emission inventory (Gurney et al, 2012) and a high-precision atmospheric transport model Lauvaux et al, 2016) enables us to test the possible improvements and limitations of an urban atmospheric CO 2 inversion system. All towers have CO 2 mole fraction measurements, and towers 1, 2, 3, 5 and 9 have 14 C content and CO mole fraction measurements.…”

“…With the increasing interest in monitoring and verifying surface CO 2 exchange, several studies have been conducted to invert for biogenic (Peters et al, 2007;Schuh et al, 2010;Ogle et al, 2015) and anthropogenic CO 2 fluxes Bréon et al, 2015;Staufer et al, 2016;Lauvaux et al, 2016;Verhulst et al, 2017). The Indianapolis Flux Experiment (INFLUX, http://sites.psu.edu/influx/) was proposed to develop, test and improve methods to estimate anthropogenic GHG emissions from cities, using Indianapolis as a test bed .…”