Can an ecological scarcity method for Germany support robust decisions? – analysing the effect of uncertain target values on the impact assessment of energy generation technologies

Abstract

Abstract Purpose Potentially contradictory indicators in Life Cycle Assessment cause ambiguity and thus uncertainty regarding the interpretation of results. The weighting-based ecological scarcity method (ESM) aims at reducing interpretation uncertainty by applying policy-based normative target values. However, the definition of these target values is uncertain due to different reasons such as questionable temporal representativeness. By means of an uncertainty analysis, this paper examines if ESMs are an appropriate approach to support robust decisions on multidimensional environmental impacts. Methods To assess the effect of uncertain target values (inputs) on environmental indicators (output), the ESM based Life Cycle Impact Assessment (LCIA) is combined with a Monte Carlo Analysis. The comprehensive uncertainty analysis includes the following steps: (1) sample generation, (2) output calculation and (3) results analysis and visualisation. (1) To generate a sample, moderate and strict limits for target values are derived from laws, directives or strategies. Random input parameters are drawn from a uniform distribution within those limits. (2) The sample is used to conduct several LCIAs leading to a distribution of total impact scores. (3) The results’ robustness is evaluated by means of the rank acceptability index to identify stable ranks for energy generation systems taken from ecoinvent v. 3.7.1. Results and discussion Applying moderate and strict target values in the ESM, results in substantial differences in the weighting sets. Even though the application of stricter target values changes the contribution of an environmental indicator to the total impact score the ranking of the energy generation systems varies only slightly. Moreover, the Monte Carlo Analysis reveals that displacement effects in ranks are not arbitrary: systems switch at most between ranks next to each other and most of the analysed systems dominate at least a single rank. Technologies with high shares of land use, global warming and air pollutants and particulate matter show a higher rank variance. Conclusions The weighting schemes, deduced from target values, provide a meaningful ranking of alternatives. At the same time, the results are not excessively sensitive to the uncertainties of the target values, i.e. the inherent uncertainty of the target values does not result in arbitrary outcomes, which is necessary to support robust decisions. The ESM is able to effectively facilitate decision making by making different environmental issues comparable.