A new generation of satellite-based methane datasets is transforming how countries track greenhouse gas emissions, offering unprecedented detail on sources and trends. But for coal-dependent economies in southern Africa, scientists warn these advances expose a different problem: emissions that are too low and inconsistent to measure reliably — and therefore difficult to verify.
The issue has implications beyond science. As climate finance increasingly shifts toward results-based models, countries must demonstrate measurable emissions reductions to access funding. Where methane cannot be reliably quantified, mitigation efforts risk going unrecognised.
Recent global analyses combining satellite observations with atmospheric modelling are improving the detection of methane plumes and attribution to specific sectors.1,2 These tools are improving national inventories and informing policy decisions, particularly in regions with large, concentrated emission sources.
“Methane release depends on geology, pressure and mining practices, and can vary over very short distances,” says Rosemary Falcon, Chair of Coal Research at the University of the Witwatersrand, Johannesburg. “Monitoring systems are designed for safety thresholds, not for capturing very low concentrations relevant to climate reporting.”
Coal mining releases methane trapped during the geological formation of coal, which is emitted during extraction. But in southern Africa, emissions are often diffuse rather than concentrated, making them harder to detect using current remote sensing technologies.
Satellite instruments are best suited to identifying large emission plumes. Where methane is released in smaller quantities or dispersed over wider areas, signals may fall below detectable thresholds. Even when detected, satellite observations require ground-based measurements to confirm sources and quantify emission rates accurately.
This creates a reliance on estimation. Across much of the region, methane inventories are based on standardised emission factors derived from limited datasets, often outside Africa. While these models provide a baseline, they may not reflect local geological conditions or operational practices.
Alan Cook, a methane specialist at the South African mining and engineering consultancy Latona, says this introduces significant uncertainty. “Generic emission factors can diverge substantially from site-specific realities,” he says, making it difficult to establish credible baselines or assess changes over time.
That uncertainty is becoming more consequential as international climate policy evolves. The Global Methane Pledge, launched in 2021, commits signatories to cutting methane emissions by 30% by 2030. Major funding channels, including those linked to the World Bank and the Green Climate Fund, are increasingly tied to verified emissions reductions.
For countries with robust monitoring systems, this shift creates opportunities to access finance by demonstrating measurable progress. But where measurement capacity is limited, it may have the opposite effect.
“Verification is becoming central to how climate finance is allocated,” says Cook. “If you cannot measure emissions accurately, it becomes very difficult to prove reductions, even if mitigation is happening.”
Mitigation options themselves are constrained. In some regions, methane from coal mining is captured and used as a fuel. In southern Africa, methane concentrations in ventilation air are typically too low for current recovery technologies to operate efficiently. Although higher concentrations can occur in specific locations, they are not widespread enough to support large-scale projects.
As a result, measurement rather than capture may be the most immediate pathway for engagement. Yet monitoring infrastructure across the region remains limited, particularly outside South Africa.
This raises concerns that global methane accounting could systematically underrepresent emissions from some African coal operations, while also limiting access to funding designed to reduce them.
At the same time, improvements in satellite coverage and modelling are continuing. New datasets are increasing spatial resolution and frequency of observations, gradually enhancing the ability to detect smaller emission sources.
"Combining these data with targeted ground measurements could help close current gaps, if investment in monitoring systems is made. Without that, the transition to verification-based climate action risks reinforcing existing inequalities,” Cook says.
From lab to field
In controlled environments, microbial fertilisers can perform well, but in open-field conditions, their effectiveness is far less consistent.2 “In pot trials, these things work great,” Jacobs says. “But as soon as you put them in the field, they tend to disappear.” Scale is part of the challenge. Increasing application rates raises costs, making products less accessible to farmers.
Korsten adds that the gap between research and deployment remains significant. “We are seeing promising results in research settings,” she says, “but scaling those solutions into farming systems requires robust field validation across different environments.”
MeerKAT’s sensitivity is central to this new picture. Many of these diffuse structures escaped earlier detection not because they were rare, but because previous instruments lacked the sensitivity to detect them.
Regulation adds further delays. In South Africa, biological fertilisers must undergo multi-year field trials before approval, slowing deployment. For small companies and emerging technologies, these timelines can be prohibitive. The result is a gap between scientific promise and practical adoption.
No quick fix
As fertiliser supply risks grow, the idea that microbial systems could replace synthetic inputs has gained traction. But researchers caution against expecting rapid solutions. “There is no way you can successfully just switch over,” Jacobs says. “Biological fertiliser is not going to cover that. It’s not a replacement.”
Modern crop systems have been built around synthetic inputs. Removing them without changing the system can lead to sharp yield declines. Korsten emphasises that any transition will take time. “These systems need to be developed, tested and adapted locally,” she says. “You cannot expect an immediate solution to a structural problem.”
Practices such as crop rotation, reduced tillage and organic amendments can rebuild soil microbiomes, but these processes unfold over years rather than seasons.3
“The question is not adding microbes,” Jacobs says. “It’s feeding the microbes that are already there.”
Instead of treating soil as a passive medium, research is increasingly focused on managing it as a living system, one where plants and microbes interact to regulate nutrient cycles.
A narrowing window
Africa’s fertiliser dependence is unlikely to disappear in the near term. Microbial fertilisers, while promising, are not yet capable of replacing synthetic inputs at scale. But the pressure to find alternatives is increasing.
As much as the challenge is scientific, it is also very temporal. Building resilient, biologically driven systems takes time, and supply shocks do not allow for time.
For now, microbes may help reduce fertiliser use. But they are not yet ready to carry Africa’s food systems on their own.