Evaluation of Long-Term Impacts in LCA

When looking at a product's life cycle, emissions and resource uses, as well as the resulting impacts, usually occur at different points in time. For instance, construction materials are often ‘stored' in buildings for many decades before they are recycled or disposed of. The goal of the LCA Discussion Forum 22 was to present and discuss arguments pro and contra a temporally differentiated weighting of impacts. The discussion forum started with three talks that illustrated the importance of temporal aspects in LCI and LCIA. The following two presentations discussed the economical principles of discounting, the adequacy of this concept within LCA, and the ethical questions involved. After one further short presentation, three groups were formed that discussed questions about temporally-differentiated weighting, and consequences for LCI as well as LCIA (damage assessment and final weighting). The discussion forum ended with the following conclusions: (a) long-term impacts should be considered in LCA, and (b) long-term emissions should be inventoried separately from short-term emissions. There was no consensus on whether short-term and long-term impacts should be weighted equally. Some prefer to weigh short-term emissions higher, because they are considered to be closer. Consistent and approved forecasts should be used when considering future changes in environmental conditions in LCI and LCI

Life cycle impact assessment of pesticides: When active substances are spread into the environment

Pesticides are biologically active substances that are directly released to the environment during the use phase of their life cycle. Pesticides are widely used and play an important role in the production of vital goods such as food, feedstuffs and cotton. The Discussion Forum 19 focused on the impact assessment of pesticides applied in agriculture. The discussion forum started with three talks about new approaches to estimate pesticide emissions and to assess their fate in the environment. The following short presentations illustrated the application of some of these methods in case studies and highlighted the problem of data availability. The last two presentations provided insight into risk assessment models used for pesticide registration from a company perspective and from the viewpoint of the authoritie

Uncertainty Analysis in Life Cycle Assessment (LCA): Case Study on Plant - Protection Products and Implications for Decision Making (3 pp)

Goal, Scope, and Background: Uncertainty analysis in LCA is important for sound decision support. Nevertheless, the actual influence of uncertainty on decision making in specific LCA case-studies has only been little studied so far. Therefore, we assessed the uncertainty in an LCA comparing two plant-protection products. Methods: Uncertainty and variability in LCI flows and characterization factors (CML-baseline method) were expressed as generic uncertainty factors and subsequently propagated into impact scores using Monte-Carlo simulation. Uncertainty in assumptions on production efficiency for chemicals, which is of specific interest for the case study, was depicted by scenarios. Results and Discussion: Impact scores concerning acidification, eutrophication, and global warming display relatively small dispersions. Differences in median impact scores of a factor of 1.6 were sufficient in the case study for a significant distinction of the products. Results of toxicity impact-categories show large dispersions due to uncertainty in characterization factors and in the composition of sum parameters. Therefore, none of the two products was found to be significantly environmentally preferable to the other. Considering the case study results and inherent characteristics of the impact categories, a tentative rule of thumb is put forward that quantifies differences in impact scores necessary to obtain significant results in product comparisons. Conclusion: Published LCA case-studies may have overestimated the significance of results. It is therefore advisable to routinely carry out quantitative uncertainty analyses in LCA. If this is not feasible, for example due to time restrictions, the rule of thumb proposed here may be helpful to evaluate the significance of results for the impact categories of global warming, acidification, eutrophication, and photooxidant creatio

A tiered approach to estimate inventory data and impacts of chemical products and mixtures

Purpose: Mixtures of organic chemicals are a part of virtually all life cycles, but LCI data exist for only relatively few chemicals. Thus, estimation methods are required. However, these are often either very time-consuming or deliver results of low quality. This article compares existing and new methods in two scenarios and recommends a tiered approach of different methods for an efficient estimation of the production impacts of chemical mixtures. Methods: Four approaches to estimate impacts of a large number of chemicals are compared in this article: extrapolation from existing data, substitution with generic datasets on chemicals, molecular structure-based models (MSMs, in this case the Finechem tool), and using process-based estimation methods. Two scenarios were analyzed as case studies: soft PVC plastic and a tobacco flavor, a mixture of 20 chemicals. Results: Process models have the potential to deliver the best estimations, as existing information on production processes can be integrated. However, their estimation quality suffers when such data are not available and they are time-consuming to apply, which is problematic when estimating large numbers of chemicals. Extrapolation from known to unknown components and use of generic datasets are generally not recommended. In both case studies, these two approaches significantly underestimated the impacts of the chemicals compared to the process models. MSMs were generally able to estimate impacts on the same level as the more complex process models. A tiered approach using MSMs to determine the relevance of individual components in mixtures and applying process models to the most relevant components offered a simpler and faster estimation process while delivering results on the level of most process models. Conclusions: The application of the tiered combination of MSMs and process models allows LCA practitioners a relatively fast and simple estimation of the LCIA results of chemicals, even for mixtures with a large number of components. Such mixtures previously presented a problem, as the application of process models for all components was very time-consuming, while the existing, simple approaches were shown to be inadequate in this study. We recommend the tiered approach as a significant improvement over previous approaches for estimating LCA results of chemical mixture

Discounting and the environment should current impacts be weighted differently than impacts harming future generations?

Background: In Life-Cycle Assessment (LCA), decision makers are often faced with tradeoffs between current and future impacts. One typical example is waste incineration, where immediate emissions to the air from the incineration process have to be weighted against future emissions of slag landfills. Long-term impacts are either completely taken into account or they are entirely disregarded in case of a temporal cut-off. Temporal cutoffs are a special case of discounting. Objective: In this paper, discounting is defined as valuing damages differently at different points of time using a positive or negative discount rate. Apart from temporal cut-offs, discounting has rarely been applied in LCA so far. It is the goal of this paper to discuss the concept of discounting and its applicability in the context of LCA. Methods: For this purpose, we first review the arguments for discounting and its principles in economic sciences. Discounting in economics can be motivated by pure time preference, productivity of capital, diminishing marginal utility of consumption, and uncertainties. The nominal discount rate additionally includes changes in the price level. These arguments and their justification are discussed in the context of environmental impacts harming future generations. Results and Discussion: It is concluded that discounting across generations because of pure time preference contradicts fundamental ethical values and should therefore not be applied in LCA. However, it has to be acknowledged that in practice decision makers often use positive discount rates because of pure time preference — either because they might profit from imposing environmental damage on others instead of themselves or because people in the far future are not of immediate concern to them. Discounting because of the productivity of capital assumes a relationship between monetary values and environmental impact. If such a relationship is accepted, discounting could be applied. However, future generations should be compensated for the environmental damage. It is likely that they would demand a higher compensation if the real per capita income increases. As both the compensation and the discount rate are related to economic growth, the overall discount rate might be close to zero. It is shown that the overall discount rate might even be negative considering that the required compensation could increase (even to infinite) if natural assets remain scarce, whereas the utility of consumption diminishes with increasing income. Uncertainties could justify both positive and negative discount rates. Since the relationship between uncertainties and the magnitude of damage is generally not exponential, we recommend to model changes in the magnitude of damage in scenario analysis instead of considering it in discounting (which requires an exponential function of time in the case of a constant discount rate). We investigated the influence of discounting in a case study of heavy metal emissions from slag landfills. It could be shown that even small discount rates of less than 1 % lead to a significant reduction of the impact score, whereas negative discount rates inflate the results. Conclusions and Recommendations: Discounting is only applicable when temporally differentiated data is available. In some cases, such a temporal differentiation is necessary to take sound decisions, especially when long emission periods are involved. An example is the disposal of nuclear or heavy metal-containing waste. In these cases, the results might completely depend on the discount rate. This paper helps to structure arguments and thus to support the decision about whether or not discounting should be applied in an LC