Many country’s greenhouse gas inventories reported to the United Nations are based on faulty, incomplete, or concealed data, according to a recent investigation published in The Washington Post. This is a hugely significant finding based on months of careful reporting, modeling, and collaboration with climate scientists and social scientists, uncovering that a significant amount of the world’s greenhouse gas emissions from land-based sources go unaccounted for. The implication of this finding is that greenhouse gas emissions may be significantly higher than we think. Global pledges to reduce emissions, such as those made at last week’s COP26 meeting in Glasgow, may therefore not be enough to meaningfully reduce actual emissions rates.
In an age of sophisticated instruments and immense scientific expertise, it may come as a surprise that we don’t always have—or can’t always get—the scientific data that we need. But uncertainty is a fundamental part of scientific research: without it, scientists wouldn’t be motivated to develop new knowledge. Uncertainty and data gaps can also be intentional, for both benign and nefarious reasons. Filling in these gaps with more data or better data, however, warrants some caution. In the case of climate change policy, the pursuit of more data might hinder action.
To understand why it’s important, one must first understand why these data gaps exist in the first place. Countries with large, subterranean land-based carbon sinks—such as peatlands—may not know exactly how deep these carbon-rich soils are and as a result, can’t accurately calculate their current and potential emissions rates. Peatlands play a significant role in the global carbon cycle because they store vast amounts of carbon underground when they are waterlogged. They also release as much carbon dioxide into the atmosphere as fossil fuel use when they are drained. Peatlands are found throughout the world but scientists are only now researching their full extent and depth in places such as the Democratic Republic of Congo and Siberia, and with that, the ongoing and potential greenhouse gas emissions from these lands.
While rough estimates of carbon storage and emissions from peatlands when they dry out and burn can be calculated relatively easily, getting more precise data about peat-based emissions is a lot harder. As I recently wrote about in relation to Indonesia’s peatlands, there are real obstacles to doing research in these places. When I asked a soil biologist working in Indonesia why there was a lack of precise data on carbon emissions from the country’s peatlands, he told me: “Because it sucks! It’s a hard ecosystem. Would you want to spend hours and hours out there making measurements? It’s a swamp!”
Measuring carbon stored in peatlands requires heavy soil coring equipment, which sinks flimsy boats and boardwalks built to traverse these wetlands, and the soil coring equipment often hits rocks or logs underground, making it difficult to accurately measure how much carbon is stored across a large landscape. This means there is ongoing uncertainty about exactly how much carbon dioxide these lands emit.
But another reason data gaps exist is that in some countries, state officials, working with corporations and scientists, have skewed or concealed their national land-based emissions data— both for economic and for geopolitical reasons. In The Washington Post’s investigation, Malaysia was found to be the most egregious example but is by no means the only one.
Malaysia and Indonesia together have most of the world’s tropical peatland. They have also staked much of their state revenue on agribusiness plantations for lucrative industrial crops like oil palm—which produces palm oil, ubiquitous in processed foods and soaps—and acacia, a fast-growing tree used for pulpwood and mass-produced furniture. In both countries, but especially in Malaysia, some of these plantations are located on peatland, which must be drained before its suitable for industrial agriculture and thus continuously release greenhouse gases.
Malaysian officials have generated their own “alternative” scientific methodologies for determining peat-based emissions, as The Washington Post described. The reason for doing so is to justify continued industrial crop production on peatlands, bolstering their lucrative agribusiness corporations. But another reason is that, as a former British colony and rising Asian “Tiger economy,” they don’t want to be told what to do by the West. One Malaysian businessman, speaking to an audience of hundreds at the 2016 International Peat Congress in Sarawak, Malaysia, drew parallels between environmental NGOs promoting peatland conservation in Malaysia and the Dutch colonization of what is now Indonesia in the 17th century, in which thousands were massacred. “We can’t sink to the level of being subservient to them,” he proclaimed, “we have to use real science and show that oil palm has a positive impact on carbon sequestration.”
What you might take away from The Washington Post investigation, and this account of deliberate misinformation by some in Malaysia that undermines global greenhouse gas inventories, is that we’re in desperate need of better data to act on climate change. I’d like to caution us away, however, from getting swept up in thinking that more or better data is a necessary precursor to reducing greenhouse gas emissions, including from peatlands. Because at the other end of data collection and reporting is what happens when the need for precise data gets, well, too precise.
In my research on carbon offset projects designed to rehabilitate peatlands in Indonesia and thus reduce carbon emissions, I found that potential investors in these offsets want highly precise data to minimize financial risk. In response, scientists generate more data, which leads to new questions and avenues of uncertainty for investors that in turn needs more data to answer. Within this feedback loop of uncertainty, it is ‘productive’ to keep collecting and refining data rather than spending money to do the rehabilitation activities, which are arguably harder to undertake for political and logistical reasons.
Social scientists have written about the role of “just good enough” data, or data that may not meet scientific standards of validation but are nonetheless useful estimates for engaging with policymakers and advancing environmental regulatory action. A similar principle can be used here. We need to account for the large gaps in global greenhouse gas inventories, and we need to hold countries skewing or under-reporting their data accountable. But we don’t need perfect, or even more, data to do so.
One successful outcome of this year’s COP26 meeting was that delegates advanced the “enhanced transparency framework” set forth in the 2015 Paris Agreement, which requires all signatory countries to report accurate national-level emissions data to the UN by 2024. In addition to supporting the emissions reductions pledges made in 2015, this is an important step towards reducing corruption and misinformation in greenhouse gas inventories. In broad strokes—billions of tons of carbon dioxide—these gaps matter, and they can be rectified by helping some governments improve their reporting capability and by holding others accountable.
Data gaps point to where the problems are, but more data does not always provide the solution. Sometimes, it can justify stalling on climate change mitigation activities through an attitude of, “let’s wait until we see the data” or “let’s refine the data before we make policy or invest in new projects.” In response to his observation of foreigners conducting research in Indonesia’s peatlands with ever-more sophisticated technology, one Indonesian scientist told me “We already have enough data. What we need is action.”
Once we know they exist, filling in the data gaps with more data doesn’t change our imperative: rapidly transitioning away from fossil fuel use and reducing land-based emissions, including from deforestation. We have good estimates about where emissions come from, and why. The Washington Post investigation provided an even fuller picture. As an ecologist working in Indonesia’s peatlands once said, “my view is, by the time you’ve accounted for every ton of carbon, the game is probably over.” Let’s not let the pursuit of more than “just good enough” data distract us now.
Jenny E. Goldstein
Jenny Goldstein is a geographer and assistant professor in the Department of Global Development at Cornell University. She has conducted fieldwork in Southeast Asia for over 10 years. Her research has been published in academic journals including Antipode, Geoforum, Environment and Planning E, and the Singapore Journal of Tropical Geography. She is also co-editor of the forthcoming book The Nature of Data: Infrastructures, Environments, Politics (University of Nebraska Press, 2022).
