Abstract

Abstract. We present a city-scale inversion over Cape Town, South Africa. Measurement sites for atmospheric CO2 concentrations were installed at Robben Island and Hangklip lighthouses, located downwind and upwind of the metropolis. Prior estimates of the fossil fuel fluxes were obtained from a bespoke inventory analysis where emissions were spatially and temporally disaggregated and uncertainty estimates determined by means of error propagation techniques. Net ecosystem exchange (NEE) fluxes from biogenic processes were obtained from the land atmosphere exchange model CABLE (Community Atmosphere Biosphere Land Exchange). Uncertainty estimates were based on the estimates of net primary productivity. CABLE was dynamically coupled to the regional climate model CCAM (Conformal Cubic Atmospheric Model), which provided the climate inputs required to drive the Lagrangian particle dispersion model. The Bayesian inversion framework included a control vector where fossil fuel and NEE fluxes were solved for separately.Due to the large prior uncertainty prescribed to the NEE fluxes, the current inversion framework was unable to adequately distinguish between the fossil fuel and NEE fluxes, but the inversion was able to obtain improved estimates of the total fluxes within pixels and across the domain. The median of the uncertainty reductions of the total weekly flux estimates for the inversion domain of Cape Town was 28 %, but reach as high as 50 %. At the pixel level, uncertainty reductions of the total weekly flux reached up to 98 %, but these large uncertainty reductions were for NEE-dominated pixels. Improved corrections to the fossil fuel fluxes would be possible if the uncertainty around the prior NEE fluxes could be reduced. In order for this inversion framework to be operationalised for monitoring, reporting, and verification (MRV) of emissions from Cape Town, the NEE component of the CO2 budget needs to be better understood. Additional measurements of Δ14C and δ13C isotope measurements would be a beneficial component of an atmospheric monitoring programme aimed at MRV of CO2 for any city which has significant biogenic influence, allowing improved separation of contributions from NEE and fossil fuel fluxes to the observed CO2 concentration.

Highlights

  • Cities are under pressure to reduce their carbon dioxide emissions

  • The most notable corrections to the pixel-level fluxes by the inversion were made to those with the largest industrial point sources, to pixels located on Robben Island where activities unaccounted for in the inventory were taking place, and to the areas dominated by Net ecosystem exchange (NEE) fluxes and located relatively close to the measurement sites

  • This could be due to the inversion attempting to reduce the overall flux by making the NEE fluxes more negative as the inversion had less freedom to make changes to the fossil fuel fluxes, or it could be that the NEE productivity predicted by CABLE in this location was underpredicting the amount of CO2 uptake by the vegetation on the fringes of the central business district (CBD)

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Summary

Introduction

Cities are under pressure to reduce their carbon dioxide emissions. In the last 10 years (2006 to 2015), the mean annual increase in carbon dioxide (CO2) concentrations in the global atmosphere has been 2.11 ppm per year (Dlugokencky and Tans, 2016) (NOAA/ESRL, 2016), a sharper rise in CO2 emissions than the preceding decades (IPCC, 2014). After accounting for the scaling of the uncertainty estimates to improve goodness of fit of the covariance structure, the resulting uncertainty estimates (expressed as standard deviations) ranged between 6.7 and 71.7 % of the prior fossil fuel emission estimate, with a median percentage of 34.9 to 38.4 %, depending on the month These values are in general more conservative compared with uncertainties that were determined by Bréon et al (2015) for the Airparif inventory, which were set at 20 % throughout. Innovations made to the fossil fuel fluxes were mainly made on the transect of the city running between Robben Island and Hangklip, as well as to fossil fuel emissions on Robben Island itself, similar to the month of May. The maximum percentage adjustment to the fossil fuel fluxes was 51.1 % and the mean innovation was close to zero, with almost all innovations positive, indicating that the posterior estimates were smaller relative to the priors. Robben Island itself showed a mix of positive and negative innovations, with posterior fluxes larger than the priors on the west of the island but smaller than the priors on the east of the island

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