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Selecting appropriate locations for municipal solid waste (MSW) management facilities, such as transfer stations, is an important issue in rapidly developing regions. Multiple alternatives and evaluation attributes need to be analyzed for finalizing the locations of these facilities. Multi-attribute decision-making (MADM) approaches are found to be very effective for ranking several potential locations and hence selecting the best among them based on the identified attributes. However, conventional MADM approaches fail to find the rankings of alternatives derived from all possible combinations of these potential locations. Therefore, this study presents a two-stage MADM model that also accounts for all possible combinations of locations. This study evaluates economical, environmental, social and technical attributes based on realistic conditions of the study area, i.e., Nashik city (India). The results provide the ranks of all possible combinations along with their probabilities of rank reversibility. The mean and standard deviation of the relative closeness are further evaluated for the top-ranking locations under distinct schemes. The present study will help stakeholders in finding suitable locations for MSW management facilities while considering economic, environmental, social and technical attributes.

Despite advances in the data, models, and methods underpinning environmental life cycle assessment (LCA), it remains challenging for practitioners to effectively communicate and interpret results. These shortcomings can bias decisions and hinder public acceptance for planning supported by LCA. This paper introduces a method for interpreting LCA results, the Argumentation Corrected Context Weighting-LCA (ArgCW-LCA), to overcome these barriers. ArgCW-LCA incorporates stakeholder preferences, corrects unjustified disagreements, and allows for the inclusion of non-environmental impacts (e.g., economic, social, etc.) using a novel weighting scheme and the application of multi-criteria decision analysis to provide transparent and context-relevant decision support. We illustrate the utility of the method through two case studies: a hypothetical decision regarding energy production and a real-world decision regarding polyphenol extraction technologies. In each case, we surveyed a relevant stakeholder group on their environmental views and fed their responses into the model to provide decision support that is relevant to their perspective. We found marked differences between results using ArgCW-LCA and results from a conventional analysis using an equal-weighting scheme, as well as differentiation between stakeholder preference groups, indicating the importance of applying the perspective of the particular stakeholder group. For instance, there was a rank reversal of alternatives when comparing between an equal weighting approach for all environmental and economic dimensions and ArgCW-LCA. ArgCW-LCA provides opportunity for both public and private sector incorporation of LCA, such as in developing enlightened stakeholder value measures. This is achieved through enabling the LCA practition to provide public and private actors' interpreted LCA results in a manner that incorporates educated stakeholder perspectives. Furthermore, the method encourages stakeholder multiplicity th

The purpose of our study is to analyse how urban lifestyles impact on the environment to offer knowledge based inspiration for effective environmental policies relating to contemporary Danish consumption patterns. The application of a Personal Metabolism (PM) coupled Life Cycle Assessment (LCA) approach supported by cluster analysis facilitated the identification of consumption-related clusters based on central demographic and life style parameters such as income, diet, transport, and age. The environmental performance of the assessed consumption patterns were calculated in a full life cycle perspective and covering all relevant environmental impacts both on midpoint and endpoint levels by applying the ReCiPe 2008 Life Cycle Impact Assessment (LCIA) methodology. The results of the contribution analysis revealed that climate change, particulate matter, human toxicity, fossil depletion and ionizing radiation contribute most to the three endpoints covered by ReCiPe 2008. Results of cluster analysis indicated that demographic parameters such as income level and age of the respondents has a strong influence on the environmental impacts. The influence of lifestyle aspects such as choice of diet, use of private car and household size was also investigated. These three parameters were found to significantly influence the consumption related environmental impacts of urban Danish residents. Overall our study identify drivers and focus points of consumption and provides a contemporary picture of Danish urban consumption-related environmental impacts.

We present a second-generation wastewater treatment inventory model, WW LCI 2.0, which on many fronts represents considerable advances compared to its previous version WW LCI 1.0. WW LCI 2.0 is a novel and complete wastewater inventory model integrating WW LCI 1.0, i.e. a complete life cycle inventory, including infrastructure requirement, energy consumption and auxiliary materials applied for the treatment of wastewater and disposal of sludge and SewageLCI, i.e. fate modelling of chemicals released to the sewer. The model is expanded to account for different wastewater treatment levels, i.e. primary, secondary and tertiary treatment, independent treatment by septic tanks and also direct discharge to natural waters. Sludge disposal by means of composting is added as a new option. The model also includes a database containing statistics on wastewater treatment levels and sludge disposal patterns in 56 countries. The application of the new model is demonstrated using five chemicals assumed discharged to wastewater systems in four different countries. WW LCI 2.0 model results shows that chemicals such as diethylenetriamine penta (methylene phosphonic acid) (DTPMP) and Diclofenac, exhibit lower climate change (CC) and freshwater ecotoxicity (FET) burdens upon wastewater treatment compared to direct discharge in all country scenarios. Results for Ibuprofen and Acetaminophen (more readily degradable) show that the CC burden depends on the country-specific levels of wastewater treatment. Higher treatment levels lead to lower CC and FET burden compared to direct discharge. WW LCI 2.0 makes it possible to generate complete detailed life cycle inventories and fate analyses for chemicals released to wastewater systems. Our test of the WW LCI 2.0 model with five chemicals illustrates how the model can provide substantially different outcomes, compared to conventional wastewater inventory models, making the inventory dependent upon the atomic composition of the molecules undergo