Greenhouse gas column observations from a portable spectrometer in Uganda
Authors: Humpage Neil , Boesch Hartmut , Okello William , Chen Jia , Dietrich Florian , Lunt Mark F. , Feng Liang , Palmer Paul I. , Hase Frank 
Published: November 2023

Abstract. The extensive terrestrial ecosystems of tropical Africa are a significant store of carbon, and play a key but uncertain role in the atmospheric budgets of carbon dioxide and methane. As ground-based observations in the tropics are scarce compared with other parts of the world, recent studies have instead made use of satellite observations assimilated into atmospheric chemistry and transport models to conclude that methane emissions from this geographical region have increased since 2010 as a result of increased wetland extent, accounting for up to a third of global methane growth, and that the tropical Africa region dominates net carbon emission across the tropics. These studies rely critically on the accuracy of satellite datasets such as those from OCO-2, GOSAT, and Sentinel-5P TROPOMI, along with results from atmospheric transport models, over a geographical region where there are few independent data to test the robustness of published results. In this paper we present the first ground-based observations of greenhouse gas column concentrations over East Africa, obtained using a portable EM27/SUN FTIR spectrometer during a deployment covering the first few months of 2020 in Jinja, Uganda. We operated the instrument near-autonomously by way of an automated weatherproof enclosure, and observed total atmospheric column concentrations of the greenhouse gases carbon dioxide and methane, as well as carbon monoxide, a useful proxy for emissions from incomplete combustion processes in the region. We discuss the performance of the combined enclosure and spectrometer system that we deployed in Jinja to obtain this data, and show comparisons of our ground-based observations with satellite datasets from OCO-2 and OCO-3 for carbon dioxide, and Sentinel-5P TROPOMI for methane and carbon monoxide, whilst also comparing our results with concentration data from the GEOS-Chem and CAMS atmospheric inversions that provide a means of increasing spatial and temporal coverage where satellite data are not available. For our measurement period, we find statistically significant differences at the 95 % confidence level between the EM27/SUN and OCO-2 XCO2 (OCO-2 lower by a mean of 1.20 ppm, standard deviation 1.05 ppm), and between the EM27/SUN and Sentinel-5P XCO (Sentinel-5P lower by a mean of 3.68 ppb, standard deviation 7.00 ppb), whilst we found that the differences between the EM27/SUN and OCO-3 XCO2 (OCO-3 lower by a mean of 1.15 ppm, standard deviation 1.61 ppm), and between the EM27/SUN and Sentinel-5P XCH4 (Sentinel-5P lower by a mean of 8.33 ppb, standard deviation 10.5 ppb), were not statistically significant. With regards to the model comparisons, we also see statistically significant differences between the EM27/SUN and a global GEOS-Chem inversion for XCO2 (GEOS-Chem lower by a mean of 0.35 ppm, standard deviation 1.08 ppm), between the EM27/SUN and a high-resolution GEOS-Chem inversion for XCH4 (GEOS-Chem lower by a mean of 3.80 ppb, standard deviation 12.5 ppb), and between the EM27/SUN and CAMS global analysis XCO (CAMS lower by a mean of 11.7 ppb, standard deviation 8.94 ppb). Our results demonstrate the value of ground-based observations of total column concentrations, and show that the combined EM27/SUN and enclosure system employed would be suitable for acquisition of the longer-term observations needed to rigorously evaluate satellite observations and model calculations over tropical Africa.