Evaluating metrics for quantifying the climate-change effects of land-based carbon fluxes

Abstract

Purpose Growing concern over climate change has increased interest in making use of the biosphere to reduce net greenhouse gas emissions by replacing fossil energy with bioenergy or increasing land-based carbon storage. An assessment of the effectiveness of these options requires detailed quantification of their climate-change mitigation potential, which must employ appropriate metrics to translate biophysical changes into climate-change impacts. However, the various currently available metrics use different proxy measures (e.g. radiative forcing, temperature changes, or others) as surrogates for climate-change impacts. Use of these different proxies can lead to contradictory conclusions on the most suitable policy options. We aim to provide criteria for the objective evaluation of metrics to build understanding of the significance of choice of metric and as a step towards building consensus on the most appropriate metric to use in different contexts. Methods We compared fifteen available metrics that represent conceptual differences in the treatment of biospheric carbon fluxes and the proxies used to approximate climate-change impacts. We proposed a set of evaluation criteria related to the metrics’ relevance, comprehensiveness, ease of application and acceptance by the research and policy community. We then compared the different metrics against these criteria. Results and conclusions The different metrics obtained scores from 10 to 21 (out of 30). The Climate-Change Impact Potential scored highest against the criteria, largely because it relates climate-change impacts to three different aspects of temperature changes; thus, it most comprehensively covers the different aspects of climate-change impacts. Therefore, according to our evaluation criteria, it would be the most suitable metric for assessing the effect of different policy options on marginal climate-change impacts. We demonstrated that the proposed evaluation criteria successfully differentiated between the fifteen metrics and could be used as a basis for selecting the most appropriate metric for specific applications.