Environmental impact of urban consumption patterns: Drivers and focus points

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

The USEtox story: a survey of model developer visions and user requirements

International audiencePurpose: USEtox is a scientific consensus model for assessing human toxicological and ecotoxicological impacts that is widely used in life cycle assessment (LCA) and other comparative assessments. However, how user requirements are met has never been investigated. To guide future model developments, we analyzed user expectations and experiences and compared them with the developers' visions. Methods: We applied qualitative and quantitative data collection methods including an online questionnaire, semi-structured user and developer interviews, and review of scientific literature. Questionnaire and interview results were analyzed in an actor-network perspective in order to understand user needs and to compare these with the developers' visions. Requirement engineering methods, more specifically function tree, system context, and activity diagrams, were iteratively applied and structured to develop specific user requirements-driven recommendations for setting priorities in future USEtox development and for discussing general implications for developing scientific models. Results and discussion: The vision behind USEtox was to harmonize available data and models for assessing toxicological impacts in LCA and to provide global guidance for practitioners. Model developers show different perceptions of some underlying aspects including model transparency and expected user expertise. Users from various sectors and geographic regions apply USEtox mostly in research and for consulting. Questionnaire and interview results uncover various user requests regarding USEtox usability. Results were systematically analyzed to translate user requests into recommendations to improve USEtox from a user perspective and were afterwards applied in the further USEtox development process. Conclusions: We demonstrate that understanding interactions between USEtox and its users helps guiding model development and dissemination. USEtox-specific recommendations are to (1) respect the application context for different user types, (2) provide detailed guidance for interpreting model and factors, (3) facilitate consistent integration into LCA software and methods, (4) improve update/testing procedures, (5) strengthen communication between developers and users, and (6) extend model scope. By generalizing our recommendations to guide scientific model development in a broader context, we emphasize to acknowledge different levels of user expertise to integrate sound revision and update procedures and to facilitate modularity, data import/export, and incorporation into relevant software and databases during model design and development. Our fully documented approach can inspire performing similar surveys on other LCA-related tools to consistently analyze user requirements and provide improvement recommendations based on scientific user analysis methods

Modeling of pesticide emissions for life cycle assessment of agricultural products.

Abstract: Brazil is the fourth largest food producer in the world. The agricultural sector contributes significantly to the Bralizian economy, representing 23% of GDP in 2016. Government and private initiatives have encouraged the adoption of more sustainable production models. The potential benefits of these models can be better estimated by tools that consider the entire production chain, such as Life Cycle Assessment (LCA). One of the main challenges of LCA applied to agricultural systems is to estimate pesticide emissions to different environmental compartments. This study evaluates the influence on the environmental impacts of two approaches to estimating the pesticide emissions of a major Brazilian agricultural product, sugarcane: 1) 100% emissions to soil, according to Nemecek & Schnetzer (2011); 2) fractionated emissions to air, surface water and groundwater, according to the PestLCI v2.0.8 model, parameterized for three Brazilian regions. The environmental life cycle impact assessment was conducted using UseTox v2.0.2 for the categories of human toxicity (HT) and freshwater ecotoxicity (ETfw) impact categories. For both impact categories, environmental impacts of sugarcane production were influenced by the methodological approach, with significant differences for ETfw (about 20% higher when applying the PestLCI modelling). In general, the main contributors to the HT and ETfw categories were heavy metals and the insecticide fipronil, respectively. The results of this work highlights the importance of developing emission models that consider the complex dynamics of pesticides in agricultural production