Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling

We present a city-scale inversion over Cape Town, South Africa. Measurement sites for atmospheric CO<sub>2</sub> concentrations were installed at Robben Island and Hangklip lighthouses, located downwind and upwind of the metropolis. Prior estimates of the fossil fuel fluxes were obtai...

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Main Authors: A. Nickless, P. J. Rayner, F. Engelbrecht, E.-G. Brunke, B. Erni, R. J. Scholes
Format: Article
Language:English
Published: Copernicus Publications 2018-04-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/18/4765/2018/acp-18-4765-2018.pdf
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spelling doaj-883dd6296d4e438daf74a85eacfc32dc2020-11-24T22:08:52ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-04-01184765480110.5194/acp-18-4765-2018Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modellingA. Nickless0A. Nickless1P. J. Rayner2F. Engelbrecht3F. Engelbrecht4E.-G. Brunke5B. Erni6B. Erni7R. J. Scholes8Department of Statistical Sciences, University of Cape Town, Cape Town, 7701, South AfricaNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UKSchool of Earth Sciences, University of Melbourne, Melbourne, VIC 3010, AustraliaCSIR Natural Resources and the Environment – Climate Studies, Modelling and Environmental Health, P.O. Box 395, Pretoria, 0001, South AfricaUnit for Environmental Sciences and Management, North-West University, Potchefstroom, 2520, South AfricaSouth African Weather Service c/o CSIR, P.O. Box 320, Stellenbosch, 7599, South AfricaDepartment of Statistical Sciences, University of Cape Town, Cape Town, 7701, South AfricaCentre for Statistics in Ecology, the Environment and Conservation, University of Cape Town, Cape Town, 7701, South AfricaGlobal Change Institute, University of the Witwatersrand, Johannesburg, 2050, South AfricaWe present a city-scale inversion over Cape Town, South Africa. Measurement sites for atmospheric CO<sub>2</sub> 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.</br></br>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 CO<sub>2</sub> budget needs to be better understood. Additional measurements of Δ<sup>14</sup>C and <i>δ</i><sup>13</sup>C isotope measurements would be a beneficial component of an atmospheric monitoring programme aimed at MRV of CO<sub>2</sub> for any city which has significant biogenic influence, allowing improved separation of contributions from NEE and fossil fuel fluxes to the observed CO<sub>2</sub> concentration.https://www.atmos-chem-phys.net/18/4765/2018/acp-18-4765-2018.pdf
collection DOAJ
language English
format Article
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author A. Nickless
A. Nickless
P. J. Rayner
F. Engelbrecht
F. Engelbrecht
E.-G. Brunke
B. Erni
B. Erni
R. J. Scholes
spellingShingle A. Nickless
A. Nickless
P. J. Rayner
F. Engelbrecht
F. Engelbrecht
E.-G. Brunke
B. Erni
B. Erni
R. J. Scholes
Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
Atmospheric Chemistry and Physics
author_facet A. Nickless
A. Nickless
P. J. Rayner
F. Engelbrecht
F. Engelbrecht
E.-G. Brunke
B. Erni
B. Erni
R. J. Scholes
author_sort A. Nickless
title Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
title_short Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
title_full Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
title_fullStr Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
title_full_unstemmed Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
title_sort estimates of co<sub>2</sub> fluxes over the city of cape town, south africa, through bayesian inverse modelling
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2018-04-01
description We present a city-scale inversion over Cape Town, South Africa. Measurement sites for atmospheric CO<sub>2</sub> 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.</br></br>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 CO<sub>2</sub> budget needs to be better understood. Additional measurements of Δ<sup>14</sup>C and <i>δ</i><sup>13</sup>C isotope measurements would be a beneficial component of an atmospheric monitoring programme aimed at MRV of CO<sub>2</sub> for any city which has significant biogenic influence, allowing improved separation of contributions from NEE and fossil fuel fluxes to the observed CO<sub>2</sub> concentration.
url https://www.atmos-chem-phys.net/18/4765/2018/acp-18-4765-2018.pdf
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