Fuzzy-Sets Approach to Noise Impact Assessment (7 pp)

Background, Aims and Scope Noise impacts are rarely assessed in Life Cycle Assessment (LCA), probably due to lack of data, to the difficulty of setting up an appropriate assessment method including relevant uncertainties and vagueness and to their site-dependent nature. The evaluation, as well as for odour, cultural and aesthetic impacts, seems to be closely related to human judgements and perception based. Although fuzzy-sets have been developed for this purpose since the late '60s and their usefulness has been proven by successful applications, noise impact assessment approaches have been essentially crisp so far. The aim of this paper is to present a method for noise impact assessment based on fuzzy sets with an application to a simple example. Methods The fuzzy noise impact assessment involves: 1) the quality assessment of the site concerned by the noise impact before the occurrence of noise emissions; quality is expressed by a crisp (i.e. non-fuzzy) function depending on variables (the so-called 'primitives'), which are relevant for the evaluation (e.g. the population density, the type of land use,...); 2) the fuzzy representation of the primitives, e.g. their evaluation by means of linguistic variables (such as 'the population density is high') and by fuzzy numbers; 3) the fuzzy representation of the quality, by fuzzifying the crisp function defined in 1) and 4) the fuzzy representation of the noise impact. In the example, the noise impacts of three processes of coal mining and combustion are assessed. Results and Discussion The application example proved the operationability of the method. Primitives and noise impact assessment results are represented by fuzzy numbers and intervals that are more informative than crisp numbers for the interpretation of results The quality and impact assessment results obtained seem to be coherent with the nature of the processes involved and of the variables characterizing them. Conclusion and Outlook Fuzzy intervals and numbers could be more informative and closer to human judgements and perceptions than crisp numbers are, thus improving the pertinence and the interpretation of the results. Despite the increase in sophistication and the fact that the representation of the variables involved in calculations should be developed further (e.g. on the basis of consensus gained in an expert panel), the fuzzy approach seems to be promising for the assessment of noise impacts in LCA.     

Possibility Theory: A New Approach to Uncertainty Analysis? (3 pp)

Background, Aims and Scope The problem of the evaluation of practitioner's belief and belief-related uncertainties on LCA results obtained from different methodological choices has been addressed so far by scenario modeling, Cultural Theory perspectives and probabilistic simulation. The direct evaluation of belief and related uncertainties could be of interest, e.g. when the information available (resulting from classical uncertainty analysis or the application of the precautionary principle) do not allow one to choose between methodological alternatives leading to different LCA results and conclusions. The difficulty of modeling belief arises from the additive nature of classical measures, e.g. probabilities. Since the 1960s, non-additive measures (e.g. possibilities) have been developed and applied to model belief in real world problems. The aim of this paper is to discuss the application of possibility measures in LCA for uncertainty analysis in complement to classical approaches. Methods The nature and the meaning of possibilities are briefly introduced by comparison with probabilities (subjective or not) in order to enlighten strengths, drawbacks and complementarities. A tentative possibilistic approach based on the evaluation of a posteriori possibilities of final LCA results depending on a priori possibilities of the methodological choices behind the calculations is described, also by means of an application example. Results and Outlook. A new approach for the modeling of practitioner's belief and belief-related uncertainties in complement of classical methods of uncertainty analysis has been proposed for discussion. Uncertainty can be characterized by confidence intervals and indexes that could help practitioners in making methodological choices and could improve the interpretation and reliability of LCA results, still increasing its sophistication.     

A tool to operationalize dynamic LCA,including time differentiation on the complete background database

The International Journal of Life Cycle Assessment - The objective is to demonstrate an operational tool for dynamic LCA, based on the model by Tiruta-Barna et al. (J Clean Prod 116:198-206,...     

LCA and decision making: when and how to use consequential LCA; 62nd LCA forum,Swiss Federal Institute of Technology,Zürich, 9 September 2016

The 62nd life cycle assessment (LCA) forum was held on 9 September 2016 to discuss the state of research and application with regard to consequential life cycle assessment. This conference report presents the highlights of the LCA forum. The state of the art of consequential LCA was presented from different viewpoints. It was pointed out that consequential LCA is more than marginal mixes and avoided burdens and involves causal modelling. It was also said that social responsibility calls for consequential LCA. Currently, different models are used to support decision making. It was suggested to make use of the variety of models to check the conclusiveness of their results and thus the reliability of the LCAs. Current and future implementations of consequential LCI models in background databases and linking algorithms were presented. Several speakers presented consequential LCA case studies covering the sectors energy, transport, housing and mining. Some of the LCA models used in the case studies are complemented with general and partial computable equilibrium models and agent-based models and use environmentally extended input-output data or process-based LCA data. Some of the presentations focused on elements such as constrained production, marginal market mixes and technologies or recycling and system expansion. In three parallel workshops, the needs, contents and methodology, and implementation of consequential LCA approaches were discussed. The participants seemed to generally agree on the basic goal that LCA should be able to reflect the consequences of decisions. The inquiry among the participants showed that the demand for consequential LCA studies is hardly existent. The appropriate implementation of consequential modelling in LCA databases and on the appropriate model to be used in consequential LCA case studies was debated. It revealed a need for further and extensive discussions to be able to reach (minimum) consensus.     

How to treat uncertainties in life cycle assessment studies?

The International Journal of Life Cycle Assessment - The use of life cycle assessment (LCA) as a decision support tool can be hampered by the numerous uncertainties embedded in the calculation. The...     

On the Complexity of Life Cycle Inventory Networks: Role of Life Cycle Processes with Network Analysis

Determining the relevance and importance of a technosphere process or a cluster of processes in relation to the rest of the industrial network can provide insights into the sustainability of supply chains: those that need to be optimized or controlled/safeguarded. Network analysis (NA) can offer a broad framework of indicators to tackle this problem. In this article, we present a detailed analysis of a life cycle inventory (LCI) model from an NA perspective. Specifically, the network is represented as a directed graph and the “emergy” numeraire is used as the weight associated with the arcs of the network. The case study of a technological system for drinking water production is presented. We investigate the topological and structural characteristics of the network representation of this system and compare properties of its weighted and unweighted network, as well as the importance of nodes (i.e., life cycle unit processes). By identifying a number of advantages and limitations linked to the modeling complexity of such emergy‐LCI networks, we classify the LCI technosphere network of our case study as a complex network belonging to the scale‐free network family. The salient feature of this network family is represented by the presence of “hubs”: nodes that connect with many other nodes. Hub failures may imply relevant changes, decreases, or even breaks in the connectedness with other smaller hubs and nodes of the network. Hence, by identifying node centralities, we can rank and interpret the relevance of each node for its special role in the life cycle network.     

Application of three independent consequential LCA approaches to the agricultural sector in Luxembourg

Purpose

Consequential Life Cycle Assessment (C-LCA) is a “system modelling approach in which activities in a product system are linked so that activities are included in the product system to the extent that they are expected to change as a consequence of a change in demand”. Hence, C-LCA focuses on micro-economic actions linked to macro-economic consequences, by identifying the (marginal) suppliers and technologies prone to be affected by variable scale changes in the demand of a product. Detecting the direct and indirect environmental effects due to changes in the production system is not an easy task. Hence, researchers have combined the consequential perspective with different econometric models. Therefore, the aim of this study is to assess an increase in biocrops cultivation in Luxembourg using three different consequential modelling approaches to understand the benefits, drawbacks and assumptions linked to each approach as applied to the case study selected.

Methods

Firstly, a partial equilibrium (PE) model is used to detect changes in land cultivation based on the farmers’ revenue maximisation. Secondly, another PE model is proposed, which considers a different perspective aiming at minimising a total adaptation cost (so-called opportunity cost) to satisfy a given new demand of domestically produced biofuel. Finally, the consequential system delimitation for agricultural LCA approach, as proposed by Schmidt (Int J Life Cycle Assess 13:350–364, 2008), is applied.

Results and discussion

The two PE models present complex shifts in crop rotation land use changes (LUCs), linked to the optimisation that is performed, while the remaining approach has limited consequential impact on changes in crop patterns since the expert opinion decision tree constitutes a simplification of the ongoing LUCs. However, environmental consequences in the latter were considerably higher due to intercontinental trade assumptions recommended by the experts that were not accounted for in the economic models. Environmental variations between the different scenarios due to LUCs vary based on the different expert- or computational-based assumptions. Finally, environmental consequences as compared with the current state-of-the-art are lame due to the limited impact of the shock within the global trade market.

Conclusions

The use of several consequential modelling approaches within the same study may help widen the interpretation of the advantages or risks of applying a specific change to a production system. In fact, different models may not only be good alternatives in terms of comparability of scenarios and assumptions, but there may also be room for complementing these within a unique framework to reduce uncertainties in an integrated way.     

Analysis of the different techniques to include noise damage in life cycle assessment. A case study for car tires

Purpose

Despite that different methods for the inclusion of transport noise in life cycle assessment (LCA) have been proposed, none of them has become consensual. Leveraging a case study on car tires, this paper aims at comparing two among these characterization approaches to identify strengths and weaknesses and to investigate the relative contribution of noise to human health (in disability-adjusted life years (DALYs)) as compared to other environmental stressors.

Methods

The case study analyzed two tires showing different acoustical properties. The two methods applied are the one developed by Müller-Wenk and further improved by other authors and the recent one proposed by Cucurachi. These two methods were adapted to the case study, and a full LCA study of the car tires was carried out. Both uncertainty and sensitivity analyses were performed.

Results and discussion

Both methods highlight the potential high contribution of noise damage to the DALYs generated by car tires, even considering parameters’ uncertainties. This study shows therefore the necessity to integrate noise impact in LCA in a broader way. Both methods present coherent results regarding the environmental performance differences between the two products. However, the absolute DALY scores differ by eight orders of magnitude, probably because Cucurachi’s methods overestimate the damages. The analysis of modeling choices and parameter uncertainties could not explain this difference.

Conclusions

Noise impact on human health has to be included in LCA, and additional efforts should focus on the characterization modeling since there is not yet a consensual method for a systematic integration. The case study shows that the improvement of tire design can efficiently reduce noise impact on human health. Both methods have advantages and inconveniences. We think that it is possible to elaborate a method combining the strengths of both approaches. An incremental approach used on accurate localized and temporalized data processed with noise propagation software could provide characterization factors for a set of archetypes. This should be a good compromise for a method allowing systematic integration of noise impact in LCA.