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Purpose The metal and mining industry routinely conducts life cycle assessment studies to monitor and document the potential environmental impacts of their products. These studies are typically conducted independently by the various commodity associations. To facilitate alignment of these methodologies, a working group comprised of interested industry organizations and their representatives was formed to propose uniform recommendations for key methodological choices. Methods Existing methodologies used by the participating associations were reviewed to identify areas of alignment as well as areas which could benefit from discussions and alignment. Recommendations for selected topics were then developed through a series of moderated discussions among the participating organizations throughout 2012 and 2013. Efforts were taken in the creation of the document to ensure alignment with the international standards ISO 14040 ( 2006 ) and ISO 14044 ( 2006 ). Four methodology issues were chosen to be addressed with respect to industry alignment: system boundary, recycling allocation, co-product allocation, and impact assessment categories. Results and discussion Recommendations for system boundary conclude that boundaries should include end-of-life disposal and recycling and, whenever possible, the product use phase, particularly for material and product comparison. For co-product allocation methods, the recommendations were based on the type of co-products being produced and included a range of options to guide practitioners’ decisions. It was recommended for recycling allocation that practitioners use the avoided burden methodology. Lastly, for the life cycle impact assessment stage, it was recommended that life cycle assessments (LCAs) on metal and mining products should report the following impact categories: global warming potential, acidification potential, eutrophication potential, photochemical oxidant creation potential, and ozone depletion potential. It was recommended that inclusion of other impact categories will be periodically re-evaluated by the metal industry. Further, the recommendation is that, while impact categories included are limited to the five above, all life cycle inventory (LCI) datasets themselves should contain accurate and comprehensive inventory data, given reasonable accessibility and data collection cost constraints. Conclusions Methodological alignment for LCA studies in the metal and mining industry will lead to improved consistency and applicability of the LCA data and results. Specifically, these recommendations improve the consistency of decisions regarding system boundary, recycling allocation, co-product allocation, and impact assessment categories. Further research is suggested to improve the specificity of certain recommendations (e.g., allocation), as well as expand the scope of the harmonization efforts to include other methodological decisions.

Background The introduction of renewable jet fuel (RJF) is considered an important emission mitigation measure for the aviation industry. This study compares the well-to-wake (WtWa) greenhouse gas (GHG) emission performance of multiple RJF conversion pathways and explores the impact of different co-product allocation methods. The insights obtained in this study are of particular importance if RJF is included as an emission mitigation instrument in the global Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA). Results Fischer-Tropsch pathways yield the highest GHG emission reduction compared to fossil jet fuel (86-104%) of the pathways in scope, followed by Hydrothermal Liquefaction (77-80%) and sugarcane- (71-75%) and corn stover-based Alcohol-to-Jet (60-75%). Feedstock cultivation, hydrogen and conversion inputs were shown to be major contributors to the overall WtWa GHG emission performance. The choice of allocation method mainly affects pathways yielding high shares of co-products or producing co-products which effectively displace carbon intensive products (e.g., electricity). Conclusions Renewable jet fuel can contribute to significant reduction of aviation-related GHG emissions, provided the right feedstock and conversion technology are used. The GHG emission performance of RJF may be further improved by using sustainable hydrogen sources or applying carbon capture and storage. Based on the character and impact of different co-product allocation methods, we recommend using energy and economic allocation (for non-energy co-products) at a global level, as it leverages the universal character of energy allocation while adequately valuing non-energy co-products.

Purpose Several new “biophysical” co-product allocation methodologies have been developed for LCA studies of agricultural systems based on proposed physical or causal relationships between inputs and outputs (i.e. co-products). These methodologies are thus meant to be preferable to established allocation methodologies such as economic allocation under the ISO 14044 standard. The aim here was to examine whether these methodologies really represent underlying physical relationships between the material and energy flows and the co-products in such systems, and hence are of value. Methods Two key components of agricultural LCAs which involve co-product allocation were used to provide examples of the methodological challenges which arise from adopting biophysical allocation in agricultural LCA: (1) the crop production chain and (2) the multiple co-products produced by animals. The actual “causal” relationships in these two systems were illustrated, the energy flows within them detailed, and the existing biophysical allocation methods, as found in literature, were critically evaluated in the context of such relationships. Results and discussion The premise of many biophysical allocation methodologies has been to define relationships which describe how the energy input to agricultural systems is partitioned between co-products. However, we described why none of the functional outputs from animal or crop production can be considered independently from the rest on the basis of the inputs to the system. Using the example of manure in livestock systems, we also showed why biophysical allocation methodologies are still sensitive to whether a system output has economic value or not. This sensitivity is a longstanding criticism of economic allocation which is not resolved by adopting a biophysical approach. Conclusions The biophysical allocation methodologies for various aspects of agricultural systems proposed to date have not adequately explained how the physical parameters chosen in each case represent causal physical mechanisms in these systems. Allocation methodologies which are based on shared (but not causal) physical properties between co-products are not preferable to allocation based on non-physical properties within the ISO hierarchy on allocation methodologies and should not be presented as such.

Background, aim and scope Different ways of performing a life cycle assessment (LCA) are used to assess the environmental burden of milk production. A strong connection exists between the choice between attributional LCA (ALCA) and consequential LCA (CLCA) and the choice of how to handle co-products. Insight is needed in the effect of choice on results of environmental analyses of agricultural products, such as milk. The main goal of this study was to demonstrate and compare ALCA and CLCA of an average conventional milk production system in The Netherlands. Materials and methods ALCA describes the pollution and resource flows within a chosen system attributed to the delivery of a specified amount of the functional unit. CLCA estimates how pollution and resource flows within a system change in response to a change in output of the functional unit. For an average Dutch conventional milk production system, an ALCA (mass and economic allocation) and a CLCA (system expansion) were performed. Impact categories included in the analyses were: land use, energy use, climate change, acidification and eutrophication. The comparison was based on four criteria: hotspot identification, comprehensibility, quality and availability of data. Results Total environmental burdens were lower when using CLCA compared with ALCA. Major hotspots for the different impact categories when using CLCA and ALCA were similar, but other hotspots differed in contributions, order and type. As experienced by the authors, ALCA and use of co-product allocation are difficult to comprehend for a consequential practitioner, while CLCA and system expansion are difficult to comprehend for an attributional practitioner. Literature shows concentrates used within ALCA will be more understandable for a feeding expert than the feed used within CLCA. Outcomes of CLCA are more sensitive to uncertainties compared with ALCA, due to the inclusion of market prospects. The amount of data required within CLCA is similar compared with ALCA. Discussion The main cause of these differences between ALCA and CLCA is the fact that different systems are modelled. The goal of the study or the research question to be answered defines the system under study. In general, the goal of CLCA is to assess environmental consequences of a change in demand, whereas the goal of ALCA is to assess the environmental burden of a product, assuming a status-quo situation. Nowadays, however, most LCA practitioners chose one methodology independent of their research question. Conclusions This study showed it is possible to perform both ALCA (mass and economic allocation) and CLCA (system expansion) of milk. Choices of methodology, however, resulted in differences in: total quantitative outcomes, hotspots, degree of understanding and quality. Recommendations and perspectives We recommend LCA practitioners to better distinguish between ALCA and CLCA in applied studies to reach a higher degree of transparency. Furthermore, we recommend LCA practitioners of different research areas to perform similar case studies to address differences between ALCA and CLCA of the specific products as the outcomes might differ from our study.

PurposePlant-based alternatives to dairy milk have grown in popularity over the last decade. Almond milk comprises the largest share of plant-based milk in the US market and, as with so many food products, stakeholders in the supply chain are increasingly interested in understanding the environmental impacts of its production, particularly its carbon footprint and water consumption. This study undertakes a life cycle assessment (LCA) of a California unsweetened almond milk.MethodsThe scope of this LCA includes the production of almond milk in primary packaging at the factory gate. California produces all US almonds, which are grown under irrigated conditions. Spatially resolved modeling of almond cultivation and primary data collection from one almond milk supply chain were used to develop the LCA model. While the environmental indicators of greatest interest are global warming potential (GWP) and freshwater consumption (FWC), additional impact categories from US EPA’s TRACI assessment method are also calculated. Co-products are accounted for using economic allocation, but mass-based allocation and displacement are also tested to understand the effect of co-product allocation choices on results.Results and discussionThe GWP and FWC of one 48 oz. (1.42 L) bottle of unsweetened almond milk are 0.71 kg CO2e and 175 kg of water. A total of 0.39 kg CO2e (or 55%) of the GWP is attributable to the almond milk, with the remainder attributable to packaging. Almond cultivation alone is responsible for 95% of the FWC (167 kg H2O), because of irrigation water demand. Total primary energy consumption (TPE) is estimated at 14.8 MJ. The 48 oz. (1.42 L) PET bottle containing the almond milk is the single largest contributor to TPE (42%) and GWP (35%). Using recycled PET instead of virgin PET for the bottle considerably reduces all impact indicators except for eutrophication potential.ConclusionsFor the supply chain studied here, packaging choices provide the most immediate opportunities for reducing impacts related to GWP and TPE, but would not result in a significant reduction in FWC because irrigation water for almond cultivation is the dominant consumer. To provide context for interpretation, average US dairy milk appears to have about 4.5 times the GWP and 1.8 times the FWC of the studied almond milk on a volumetric basis.

PurposeCalifornia’s Central Valley produces more than 75% of global commercial almond supply, making the life cycle performance of almond production in California of global interest. This article describes the life cycle assessment of California almond production using a Scalable, Process-based, Agronomically Responsive Cropping System Life Cycle Assessment (SPARCS-LCA) model that includes crop responses to orchard management and modeling of California’s water supply and biomass energy infrastructure.MethodsA spatially and temporally resolved LCA model was developed to reflect the regional climate, resource, and agronomic conditions across California’s Central Valley by hydrologic subregion (San Joaquin Valley, Sacramento Valley, and Tulare Lake regions). The model couples a LCA framework with region-specific data, including water supply infrastructure and economics, crop productivity response models, and dynamic co-product markets, to characterize the environmental performance of California almonds. Previous LCAs of California almond found that irrigation and management of co-products were most influential in determining life cycle CO2eq emissions and energy intensity of California almond production, and both have experienced extensive changes since previous studies due to drought and changing regulatory conditions, making them a focus of sensitivity and scenario analysis.Results and discussionResults using economic allocation show that 1 kg of hulled, brown-skin almond kernel at post-harvest facility gate causes 1.92 kg CO2eq (GWP100), 50.9 MJ energy use, and 4820 L freshwater use, with regional ranges of 2.0–2.69 kg CO2eq, 42.7–59.4 MJ, and 4540–5150 L, respectively. With a substitution approach for co-product allocation, 1 kg almond kernel results in 1.23 kg CO2eq, 18.05 MJ energy use, and 4804 L freshwater use, with regional ranges of 0.51–1.95 kg CO2eq, 3.68–36.5 MJ, and 4521–5140 L, respectively. Almond freshwater use is comparable with other nut crops in California and globally. Results showed significant variability across subregions. While the San Joaquin Valley performed best in most impact categories, the Tulare Lake region produced the lowest eutrophication impacts.ConclusionWhile CO2eq and energy intensity of almond production increased over previous estimates, so too did credits to the system for displacement of dairy feed. These changes result from a more comprehensive model scope and improved assumptions, as well as drought-related increases in groundwater depth and associated energy demand, and decreased utilization of biomass residues for energy recovery due to closure of bioenergy plants in California. The variation among different impact categories between subregions and over time highlight the need for spatially and temporally resolved agricultural LCA.

PURPOSE: There are methodological questions concerning life cycle assessment (LCA) and carbon footprint evaluation of road pavements, including allocation among co-products or at end-of-life (EOL) recycling. While the development and adoption of a standard methodology for road pavement LCA would assist in transparency and decision making, the impact of the chosen method on the results has not yet been fully explored. METHODS: This paper examines the methodological choices made in UK PAS 2050 and asphalt Pavement Embodied Carbon Tool (asPECT), and reviews the allocation methods available to conduct road pavement LCA. A case study of a UK inter-urban road construction (cradle-to-laid) is presented to indicate the impact of allocation amongst co-products (bitumen and blast furnace slag); a typical UK asphalt production (cradle-to-gate) is modelled to show the influence of allocation at EOL recycling. RESULTS AND DISCUSSION: Allocation based on mass is found to consistently lead to the highest figures in all impact categories, believed to be typical for construction materials. Changing from industry chosen allocation methods (Eurobitume, asPECT) to 100 % mass or economic allocation leads to changes in results, which vary across impact categories. This study illustrates how the allocation methods for EOL recycling affect the inventory of a unit process (asphalt production). CONCLUSIONS AND RECOMMENDATIONS: Sensitivity analysis helps to understand the impact of chosen allocation method and boundary setting on LCA results. This initial work suggests that economic allocation to co-products used as secondary pavement materials may be more appropriate than mass allocation. Allocation at EOL recycling by a substitution method may remain most appropriate, even where the balance of credits between producers and users may be hampered by an inability to confidently predict future recycling rates and methods. In developing sector-specific guidelines, further sensitivity checks are recommended, such as for alternative materials and traffic management during maintenance.

In this paper, a new model supporting decisions about product allocation in an order-picking shelf warehouse is presented. Industry 4.0 pays attention to inciting the processes, self-analysis and self-optimization of the short response time to market changes, and the maximum use of related data. Methods for solving the product allocation problem (PAP) are not enough to meet the requirements of Industry 4.0. The authors present a new approach for solving PAP. The novelty introduced in the model is based on correlated data—products parameters, clients’ orders and warehouse layout. The proposed model contains elements of intelligence. The model, after product classification and allocation, analyzes its effectiveness by a simulation of the order-picking process. The application of artificial neural networks (ANN) as a part of the computing model enables the analysis of large data sets in a short time. The presented study has proved the proposed model, both for practical and scientific purposes. Relying on the research results, the total warehouse cost could be reduced by 10 to 16 per cent. With the use of the proposed model, it is possible to predict the effect of future actions before their execution. The model can be implemented in most conventional warehouses to raise the throughput performance of the order-picking process.

Although, according to the ISO 14044 standard, economic allocation should be the solution of last resort, it is frequently used in LCA studies of agri-food systems because of the inadequacy of solutions preferred by ISO. We propose a new way of allocating impacts to plant co-products according to the underlying physical relationships between the co-products. We compare this method to two current allocation methods. (i) We surveyed 24 LCA studies from peer-reviewed scientific journals and scientific reports for the 2000-2013 period that attributed impacts to plant co-products used as animal feed to establish the prevalence of allocation methods in recent LCA studies. (ii) We calculated allocation factors for 21 plant co-products used as ingredients for animal feeds according to three methods: energy allocation based on lower heating values (En), economic allocation based on average prices for a 5-year period (Ec), and allocation based on plant physiological construction cost of plant compounds (Cc). (i) In the studies surveyed, Ec was used in 19 out of 24 cases. En was used in three studies, system expansion and mass allocation were used in two studies, while nitrogen content was used in one study. (ii) Compared to En and Ec, Cc yielded higher allocation factors for protein-rich co-products and lower factors for lipids. Whereas the difference between En and Cc was modest (up to 5 percentage points), the difference between Ec and Cc was more variable and sometimes large (up to 18 percentage points). Although, according to the ISO 14044 standard, Ec should be the solution of last resort, it is frequently used in LCA studies of agri-food systems because of the inadequacy of solutions preferred by ISO. For plant co-products, Cc is an attractive option, as it is based on the physiological mechanisms involved in plant growth rather than on a common property of the co-products.

Since 2016, hospitals in France have met to form Territorial Hospital Groups (THGs) in order to modernize their health care system. The main challenge is to allow an efficient logistics organization to adopt the new collaborative structure of the supply chain. In our work, we approach the concept of logistics pooling as a form of collaboration between hospitals in THGs. The aim is to pool and rationalize the storage of products in warehouses and optimize their distribution to care units while reducing logistics costs (transportation, storage, workforce, etc.). Besides, due to the unavailability and the incompleteness of data in real-world situations, several parameters embedded in supply chains could be imprecise or even uncertain. In this paper, a Fuzzy chance-constrained programming approach is developed based on possibility theory to solve a network design problem in a multi-supplier, multi-warehouse, and multi-commodity supply chain. The problem is designed as a minimum-cost flow graph and a linear programming optimization model is developed considering fuzzy demand. The objective is to meet the customers’ demand and nd the best allocation of products to warehouses. Different instances were generated based on realistic data from an existing territorial hospital group, and several tests were developed to reveal the benefits of collaboration and uncertainty handling.