Atmospheric inversion for cost effective quantification of city CO2 emissions
Authors: Wu L. , Broquet G. , Ciais P. , Bellassen V. , Vogel F. , Chevallier F. , Xueref-Remy I. , Wang Y. 
Published: November 2015

Abstract. Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44 % of global energy-related CO2, and are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25 m a.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (~ 12 million inhabitants and 11.4 Tg C emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5 % (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by ~ 42 % but still corresponds to an annual uncertainty that is two times larger than the target of 5 %. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32 % for commercial and residential buildings, by 33 % for road transport and by 18 % for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15 % 2-sigma annual uncertainty for dispersed building emissions, and 18 % for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus deliver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments).