Estimates of CO2 fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling

• Published in: Atmospheric chemistry and physics 2018-04, Vol.18 (7), p.4765-4801
• Main Authors: Nickless, Alecia, Rayner, Peter J, Engelbrecht, Francois, Ernst-Günther Brunke, Erni, Birgit, Scholes, Robert J
• Format: Article
• Language: English
• Subjects: Atmosphere; Atmospheric models; Atmospheric monitoring; Bayesian analysis; Biosphere; Capes (landforms); Carbon dioxide; Carbon dioxide atmospheric concentrations; Carbon dioxide concentration; Carbon dioxide flux; Cities; Climate; Climate change; Climate models; Corrections; Domains; Emission inventories; Emissions; Estimates; Fluxes; Fossil fuels; Frameworks; Greenhouse gases; Inversion; Isotopes; Lighthouses; Net Primary Productivity; Outdoor air quality; Pixels; Pollution monitoring; Primary production; Probability theory; Regional climate models; Regional climates; Telephone cables; Uncertainty; Urban heat islands
• ISSN: 1680-7316; 1680-7324
• DOI: 10.5194/acp-18-4765-2018

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 ofΔ14C and δ13C isotope measurements would be a beneficial component of an atmospheric monitoring programme aimed at MRV ofCO2 for any city which has significant biogenic influence, allowing improved separation of contributions from NEE and fossil fuel fluxes to the observed CO2 concentration.