Aug 20 2019
National or other emissions inventories of greenhouse gases (GHGs) that are used to create policies and monitor the progress in emissions reductions for mitigating climate change involve some amount of ambiguity, which unavoidably affects the decisions they inform.
(Image credit: © Jeffrey Banke|Dreamstime.com)
IIASA scientists contributed to a number of studies in a newly published series that aims to improve understanding of ambiguity in emissions inventories.
GHG emission estimates are significant for numerous reasons, but it is critical to recognize that these values have a specific level of ambiguity that has to be taken into consideration. For instance, if two emission estimates from a country are dissimilar, it does not certainly suggest that one or both are wrong—it just means that there is an ambiguity that must be acknowledged and handled.
A special issue of the Springer journal Mitigation and Adaptation Strategies for Global Change aims to improve understanding of ambiguity in estimating GHG emissions and to offer guidance on tackling the subsequent challenges.
IIASA scientists and colleagues from other international institutions, including the Lviv Polytechnic National University in Ukraine, the Systems Research Institute at the Polish Academy of Sciences, and Appalachian State University in the United States, contributed to the 13 papers featured in the publication, answering questions such as the size of the ambiguity dealt with, how to manage this, and how ambiguity might be reduced.
The research team reports that there are ways to reduce ambiguity, but these are often hard and eventually expensive. In their respective papers, they highlight that there are seven critical issues that presently rule a researcher’s understanding of ambiguity: (1) verification, (2) avoidance of systemic surprises, (3) ambiguity informing policy, (4) reducing the impact of ambiguity, (5) complete GHG accounting, (6) compliance versus reporting, and (7) variations in emissions versus variations in the atmosphere.
With regards to how ambiguity in observations and modeling results can impact policy decisions on climate change mitigation, a few of the papers also analyzed how decision-making procedures can be enhanced to yield more fair rules for scrutinizing compliance and how information around emission inventories can be communicated to make it more open and easier to comprehend.
The researchers explain that understanding the ambiguities is very crucial both for those who perform the calculations or modeling and for the consumers of this information, like consultants or policymakers, as it offers a clue of how much they can depend on the data, in other words, how “strong” the conclusions are and how undisputable the decisions resulting from the data can be.
Uncertainty is higher for some GHGs and some sectors of an inventory than for others. This raises the option that, when future policy agreements are being designed, some components of a GHG inventory could be treated differently from others. The approach of treating subsystems individually and differently would allow emissions and uncertainty to be looked at simultaneously and would thus allow for differentiated emission reduction policies.
Matthias Jonas, Researcher, Advanced Systems Analysis Program, IIASA
Matthias Jonas is one of the editors of the special issue.
He continued, “The current policy approach of ignoring inventory uncertainty altogether (inventory uncertainty was monitored, but not regulated, under the Kyoto Protocol) is problematic. Being aware of the uncertainties involved, including those resulting from our systems views, will help to strengthen future political decision making.”
The authors all concur that tackling ambiguity is usually not a quick exercise but instead involves an elaborate and long-term commitment. Correct treatment of ambiguity can be expensive in relation to both time and effort as it requires taking the step from “simple” to “complex” so as to understand a wider and more holistic systems view. Only after that step has been finalized, is it possible to look into simplifications that may be necessary.
Decision makers want certainty, the public wants certainty, but certainty is not achievable. We can work with the best information available and we have to keep moving forward and learning. I think that we need to convince data users such as policymakers or the public that uncertainty in these kinds of numbers is normal and expected and does not mean that the numbers are not useful.
Gregg Marland, Study Author, Appalachian State University
Special edition co-editor Rostyslav Bun from Lviv Polytechnic National University in Ukraine reaffirms this sentiment.
The presence of uncertainties in estimates of GHG emissions may suggest that we have to devote more energy to decreasing uncertainties or it may simply mean that we need to be prepared to deal with a future that includes a certain measure of uncertainty.
Rostyslav Bun, Special Edition Co-Editor, Lviv Polytechnic National University