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Life Cycle Inventory (life + cycle_inventory)
Selected AbstractsHybrid Framework for Managing Uncertainty in Life Cycle InventoriesJOURNAL OF INDUSTRIAL ECOLOGY, Issue 6 2009Eric D. Williams Summary Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input,output (I-O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom-up process model can be estimated via a top-down approach such as the economic I-O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long-term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method. [source] Life cycle inventory and analysis of re-usable plastic containers and display-ready corrugated containers used for packaging fresh fruits and vegetablesPACKAGING TECHNOLOGY AND SCIENCE, Issue 5 2006S. Paul Singh Abstract Today's demanding distribution challenges require engineers to choose from various types of materials, design and construction methods, to develop containers that can deliver goods with minimal damage. The challenge is even greater when packing and shipping goods which are perishable and sensitive to both physical and climatic changes in environment. In recent years the type of packaging material used to design and construct containers has undergone more scrutiny than ever, due to environmental challenges. This study focuses on two types of containers that have been designed and are being used to pack and ship fresh fruits and vegetables. The study compares the re-usable plastic containers to single-use display-ready paper corrugated trays. Results show that, based on the scope of this study and comparing 10 different produce items, such as apples, carrots, grapes, oranges, onions, tomatoes, strawberries, etc., the re-usable plastic containers require 39% less total energy, produce 95% less total solid waste and generate 29% less total greenhouse gas emissions. This study focused on the North American market. Major European nations have been using a large number of re-usable plastic containers for these types of fresh produce for the past three decades. This study was initiated by the Franklin Associates, an independent consulting firm for allowing an in-depth review of all data and results from a two year study titled: Life Cycle Inventory of Reusable Plastic Containers and Display-Ready Corrugated Containers Used for Fresh Produce Applications. Copyright © 2006 John Wiley & Sons, Ltd. [source] Hybrid Framework for Managing Uncertainty in Life Cycle InventoriesJOURNAL OF INDUSTRIAL ECOLOGY, Issue 6 2009Eric D. Williams Summary Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input,output (I-O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom-up process model can be estimated via a top-down approach such as the economic I-O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long-term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method. [source] LCAccess: A global directory of life cycle assessment resourcesENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, Issue 1 2003Mary Ann Curran LCAccess is an EPA-sponsored Web site intended to promote the use of Life Cycle Assessment (LCA) in business decision-making by facilitating access to data sources useful in developing a life cycle inventory (LCI). While LCAccess does not, itself, contain data, it is a searchable global directory of potential data sources, and serves as a central source for LCA information. [source] Integration of Life Cycle Assessment Into Agent-Based ModelingJOURNAL OF INDUSTRIAL ECOLOGY, Issue 2 2009Toward Informed Decisions on Evolving Infrastructure Systems Summary A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent-based model (ABM) as distinct instances of technologies with owners capable of making decisions based on economic and environmental information. This simulation setup allows us to explore the dynamics of assembly, disassembly, and use of these systems, which typically span decades, and to analyze the effect of using LCA information in decision making. We were able to integrate a simplified LCA into an ABM by aligning and connecting the data structures that represent the energy infrastructure and the supply chains from source to sink. By using an appropriate database containing life cycle inventory (LCI) information and by solving the scaling factors for the technology matrix, we computed the contribution to global warming in terms of carbon dioxide (CO2) equivalents in the form of a single impact indicator for each instance of technology at each discrete simulation step. These LCAs may then serve to show each agent the impact of its activities at a global level, as indicated by its contribution to climate change. Similar to economic indicators, the LCA indicators may be fed back to the simulated decision making in the ABM to emulate the use of environmental information while the system evolves. A proof of concept was developed that is illustrated for a simplified LCA and ABM used to generate and simulate the evolution of a bioelectricity infrastructure system. [source] Optimal design and planning of sustainable chemical supply chains under uncertaintyAICHE JOURNAL, Issue 1 2009Gonzalo Guillén-Gosálbez Abstract This article addresses the design of sustainable chemical supply chains in the presence of uncertainty in the life cycle inventory associated with the network operation. The design task is mathematically formulated as a bi-criterion stochastic mixed-integer nonlinear program (MINLP) that simultaneously accounts for the maximization of the net present value and the minimization of the environmental impact for a given probability level. The environmental performance is measured through the Eco-indicator 99, which incorporates the recent advances made in Life Cycle Assessment. The stochastic model is converted into its deterministic equivalent by reformulating the probabilistic constraint required to calculate the environmental impact in the space of uncertain parameters. The resulting deterministic bi-criterion MINLP problem is further reformulated as a parametric MINLP, which is solved by decomposing it into two sub-problems and iterating between them. The capabilities of the proposed model and solution procedure are illustrated through two case studies for which the set of Pareto optimal, or efficient solutions that trade-off environmental impact and profit, are calculated. These solutions provide valuable insights into the design problem and are intended to guide the decision maker towards the adoption of more sustainable design alternatives. © 2008 American Institute of Chemical Engineers AIChE J, 2009 [source] Application of life cycle assessment to improve the environmental performance of a ceramic tile packaging systemPACKAGING TECHNOLOGY AND SCIENCE, Issue 2 2006M. D. Bovea Abstract The overall goal of this study was to evaluate the environmental performance of the process currently used to package and palletize ceramic floor and wall tiles, and to propose and analyse improvements from an environmental point of view. After developing a life cycle inventory of the primary and tertiary packaging, the life cycle assessment was applied according to mandatory and optional elements of ISO 14042. The results are presented in three parts: the first quantifies the environmental behaviour of the current packaging system, the second examines strategies focused on minimizing the environmental burdens of such critical elements, and the third quantifies the environmental improvements, compared with the initial situation, that are obtained with the application of each improvement. The simultaneous incorporation of all the proposed improvements into the packaging system can reduce impact within the 18,45% range, depending on the impact method that is applied. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||