Greenhouse gas observation network design for Africa

Abstract

An optimal network design was carried out to prioritise the installation or refurbishment of greenhouse gas (GHG) monitoring stations around Africa. The network was optimised to reduce the uncertainty in emissions across three of the most important GHGs: CO 2 , CH 4 , and N 2 O. Optimal networks were derived using incremental optimisation of the percentage uncertainty reduction achieved by a Gaussian Bayesian atmospheric inversion. The solution for CO 2 was driven by seasonality in net primary productivity. The solution for N 2 O was driven by activity in a small number of soil flux hotspots. The optimal solution for CH 4 was consistent over different seasons. All solutions for CO 2 and N 2 O placed sites in central Africa at places such as Kisangani, Kinshasa and Bunia (Democratic Republic of Congo), Dundo and Lubango (Angola), Zo et el e (Cameroon), Am Timan (Chad), and En Nahud (Sudan). Many of these sites appeared in the CH 4 solutions, but with a few sites in southern Africa as well, such as Amersfoort (South Africa). The multi-species optimal network design solutions tended to have sites more evenly spread-out, but concentrated the placement of new tall-tower stations in Africa between 10 N and 25 S. The uncertainty reduction achieved by the multi-species network of twelve stations reached 47.8% for CO 2 , 34.3% for CH 4 , and 32.5% for N 2 O. The gains in uncertainty reduction diminished as stations were added to the solution, with an expected maximum of less than 60%. A reduction in the absolute uncertainty in African GHG emissions requires these additional measurement stations, as well as additional constraint from an integrated GHG observatory and a reduction in uncertainty in the prior biogenic fluxes in tropical Africa.

Opportunities for an African greenhouse gas observation system

“…Thus, the SEACRIFOG consortium ran optimization algorithms coupled to top-down inversion techniques to identify the best locations for new observations, such that they reduced the uncertainty in the GHG budget of Africa by the greatest amount (Fig. 3, Nickless et al 2020). In order to minimise the costs, various technologies that meet the required standards were considered for each of the essential variables (López-Ballesteros et al 2018Beck et al 2019).…”

“…The analysis considered each of the three major GHGs separately and provided a solution which optimised across all three gases. The largest amount of uncertainty in the total African GHG budget was due to biogenic GHG emissions, and therefore sites were located near the regions of greatest biogenic activity (Nickless et al 2020), predominantly tropical rainforest, subtropical and tropical dry forest and grass savanna biomes. The regions/countries which were most frequently included in the network design under various configurations included Angola, the Congo basin and Botswana.…”

“…This emphasizes the need for an integrated network to reach higher levels of uncertainty reduction. It would include atmospheric measurements sites, such as proposed in the network design study by Nickless et al (2020), as well as satellite observations, and ecosystem measurements of GHG fluxes which can improve models predicting biogenic GHG fluxes in African ecosystems. Furthermore, it is important to note that some of the tropical African stations that were used in the study are already active.…”

Reviews and syntheses: Enhancing research and monitoring of land-to-atmosphere greenhouse gases exchange in developing countries

“…A simple parameter measured in a place (e.g., CO2 concentration, decomposition of organic matter) may not be useful to understand complexity of GHG dynamics. However, if the parameter can be measured in different places at the same time the potential of the data in term of contribution to scientific advance can be far beyond a simple parameter itself (Nickless et al, 2020;Morawska et al, 2018;Chandler et al, 2017;Keuskamp et al, 2013). The integration on multiple measurements can also fill the gap of each approach and also can create synergies.…”

Ideas and Perspectives: Enhancing research and monitoring of carbon pools and land-to-atmosphere greenhouse gases exchange in developing countries

“…4). As already said, low-cost technology can see the issue of low accuracy and precision (Arzoumanian et al, 2019;Marley et al, 2019) and it can be partially solved by increasing sampling replication and frequency combining them with participatory and networking based research approaches (Peltier, 2021;Riddick al., 2020;Nickless et al, 2020;Morawska et al, 2018). Beside these technical aspects, through the integration, local actors take on expanded roles within the 350 projects (e.g.…”