The Abiotic Depletion Potential: Background, Updates, and Future

Industrial Ecolog

A PVC substance flow analysis for Sweden. Part IV: Spreadsheets & calculations

Industrial Ecolog

A PVC substance flow analysis for Sweden. Part II:Mass flows and emissions by PVC chain section

Industrial Ecolog

A PVC substance flow analysis for Sweden. Part I: Main report

Industrial Ecolog

Assessing the future environmental impacts of copper production in China: implications of the energy transition

Copper demand in China is expected to grow considerably over the coming decades, driving energy use and environmental impacts related to copper production. To explore the environmental impacts of copper production in China, we used a variant of Life Cycle Sustainability Analysis that combined the Life Cycle Assessment methodology with the Chinese copper demand projections from 2010 to 2050. The results indicate that the environmental impacts of pyrometallurgical copper production are expected to increase more than twofold during this period and remain the largest contributor to the environmental footprint. Secondary copper production emits the least pollutions. Increasing the share of secondary copper production is the most environmental friendly option for copper production. To this end, China may focus on improving the classification of waste copper products and recycling infrastructure for end-of-life management. Hard coal use and production are crucial contributors to climate change in the context of copper production. Cleaning up copper production processes and improving energy efficiency would also help reduce environmental impacts. Energy transition can significantly reduce the environmental impacts of copper production, but it also can increase copper requirement.It does not visibly contribute to reduce human toxicity as well. (C) 2020 The Author(s). Published by Elsevier Ltd.Industrial Ecolog

A PVC substance flow analysis for Sweden. Part III: Methodological backgrounds

Industrial Ecolog

Life cycle approaches for Conservation Agriculture

Industrial Ecolog

Abiotic resource use in life cycle impact assessment: part II - Linking perspectives and modelling concepts

Starting from a lack of consensus on how to consistently assess abiotic resource use in life cycle assessment, a structured approach was developed to enable a classification of perspectives on resource use, based on the so-called role of resources. Using this classification, this paper focusses on analysing links between perspectives and modelling concepts, i.e. the conceptual implementation. To analyse the modelling concepts for a selection of existing LCIA methods and other modelling approaches, the concept of the system model is introduced. It defines the relevant inventory flows to be assessed by the LCIA method, and, at the same time, to be considered in the characterization model, and how the flows and stocks of resources used to calculate the characterization factors are positioned in relation to environment (nature) and economy (technosphere). For consistency, they should be aligned with the position of inventory flows and, at the same time, reflect the perspective on resources taken by the method. Using this concept, we critically review a selection of methods and other modelling approaches for consistency with the perspectives on resource use, as well as for their internal consistency. As a result of the analysis, we highlight inconsistencies and discuss ways to improve links between perspectives and modelling concepts. To achieve this, the new framework can be used for the development or improvement of LCIA methods on resource use.Horizon 2020(H2020)KIC EIT Raw Materials project number 16121Industrial Ecolog

Long-term prospects for the environmental profile of advanced sugar cane ethanol

This work assessed the environmental impacts of the production and use of 1 MJ of hydrous ethanol (E100) in Brazil in prospective scenarios (2020-2030), considering the deployment of technologies currently under development and better agricultural practices. The life cycle assessment technique was employed using the CML method for the life cycle impact assessment and the Monte Carlo method for the uncertainty analysis. Abiotic depletion, global warming, human toxicity, ecotoxicity, photochemical oxidation, acidification, and eutrophication were the environmental impacts categories analyzed. Results indicate that the proposed improvements (especially no-til farming-scenarios s2 and s4) would lead to environmental benefits in prospective scenarios compared to the current ethanol production (scenario s0). Combined first and second generation ethanol production (scenarios s3 and s4) would require less agricultural land but would not perform better than the projected first generation ethanol, although the uncertainties are relatively high. The best use of 1 ha of sugar cane was also assessed, considering the displacement of the conventional products by ethanol and electricity. No-til practices combined with the production of first generation ethanol and electricity (scenario s2) would lead to the largest mitigation effects for global warming and abiotic depletion. For the remaining categories, emissions would not be mitigated with the utilization of the sugar cane products. However, this conclusion is sensitive to the displaced electricity sources.Industrial Ecolog

Top-down characterization of resource use in LCA: from problem definition of resource use to operational characterization factors for dissipation of elements to the environment

Purpose The methods for assessing the impact of using abiotic resources in life cycle assessment (LCA) have always been heavily debated. One of the main reasons for this is the lack of a common understanding of the problem related to resource use. This article reports the results of an effort to reach such common understanding between different stakeholder groups and the LCA community. For this, a top-down approach was applied. Methods To guide the process, a four-level top-down framework was used to (1) demarcate the problem that needs to be assessed, (2) translate this into a modeling concept, (3) derive mathematical equations and fill these with data necessary to calculate the characterization factors, and (4) align the system boundaries and assumptions that are made in the life cycle impact assessment (LCIA) model and the life cycle inventory (LCI) model. Results We started from the followingdefinition of the problemof using resources: the decrease of accessibility on a global level of primary and/or secondary elements over the very long term or short term due to thenetresult of compromising actions. Thesystem modeldistinguishes accessible and inaccessible stocks in both the environment and the technosphere. Human actions can compromise the accessible stock through environmental dissipation, technosphere hibernation, and occupation in use or through exploration. As abasis for impact assessment, we propose two parameters: the global change in accessible stock as a net result of the compromising actions and the global amount of the accessible stock. We propose three impact categories for the use of elements: environmental dissipation, technosphere hibernation, and occupation in use, with associated characterization equations for two different time horizons. Finally, preliminary characterization factors are derived and applied in a simple illustrative case study for environmental dissipation. Conclusions Due to data constraints, at this moment, only characterization factors for "dissipation to the environment" over a very-long-term time horizon could be elaborated. The case study shows that the calculation of impact scores might be hampered by insufficient LCI data. Most presently available LCI databases are far from complete in registering the flows necessary to assess the impacts on the accessibility of elements. While applying the framework, various choices are made that could plausibly be made differently. We invite our peers to also use this top-down framework when challenging our choices and elaborate that into a consistent set of choices and assumptions when developing LCIA methods.Industrial Ecolog