Environmental impacts associated with the production, use, and end-of-life of a woollen garment

The carbon cost of impaired welfare on sheep farms.

A life cycle assessment (LCA) study of a transition from semiintensive to semi-extensive Mediterranean dairy sheep farm suggests that the latter has a strong potential for offsetting greenhouse gas (GHG) emissions through the soil C sequestration (Cseq) in permanent grasslands. The extensification process shows clear environmental advantage when emission intensity is referred to the area-based functional unit (FU). Several LCA studies reported that extensive livestock systems have greater GHG emissions per mass of product than intensive one, due to their lower productivity. However, these studies did not account for soil Cseq of temporary and permanent grasslands, that have a strong potential to partly mitigate the GHG balance of ruminant production systems. Our LCA study was carried out considering the transition from a semiintensive (SI) towards a semi-extensive (SE) production system, adopted in a dairy sheep farm located in North-Western Sardinia (Italy). Impact scope included enteric methane emissions, feed production, on-farm energy use and transportation, infrastructures as well as the potential C sink from soil Cseq compared to emission intensity. In order to provide a more comprehensive analysis, we used the following FUs: 1 kg of fat and protein corrected milk (FPCM) and 1 ha of utilised agricultural area (UAA). We observed that the extensification of production system determined contrasting environmental effects when using different FUs accounting for soil Cseq. When soil Cseq in emission intensity estimate was included, we observed slightly lower values of GHG emissions per kg of FPCM in the SI production system (from 3.37 to 3.12 kg CO2 equivalents – CO2-eq), whereas a greater variation we observed in the SE one (from 3.54 to 2.90 kg CO2-eq). Considering 1 ha of UAA as FU and including the soil Cseq, the emission intensity in SI moved from 6257 to 5793 kg CO2-eq, whereas values varied from 4020 to 3299 kg CO2-eq in SE. These results indicated that the emission intensity from semi-extensive Mediterranean dairy sheep farms can be considerably reduced through the soil Cseq, although its measurement is influenced by the models used in the estimation. Highlights - Extensification of dairy sheep systems provides an environmental benefit when soil C sequestration is considered. - Extensification of dairy sheep systems determines lower environmental impact per hectare of utilized agricultural area. - Enteric methane emissions are the main source of GHG emissions of the sheep milk life cycle. - Carbon sequestration in permanent grasslands can considerably contribute to climate change mitigation.

Food losses and waste (FLW) reduction and mitigating climate impact in food chains are priorities in achieving sustainable development goals. However, many FLW-reducing interventions induce additional greenhouse gas (GHG) emissions, for example, from energy, fuel, or packaging. The net effect of such interventions (expressed in GHG emissions per unit of food available for consumption) is not obvious, as is illustrated in a number of case studies. We recommend that in the decision to take on FLW-reducing interventions, the trade-offs on sustainability impacts (such as GHG emissions) are taken into consideration. Since FLW induce demand and extra operations in all stages along a supply chain, adequate representation of cumulative GHG emissions along the production and supply chain, including ‘hidden parts’ of the chain, is required, which is challenging in full LCA studies. As a workaround, the case studies in this paper are based on a generic tool, the Agro-Chain greenhouse gas Emission (ACE) calculator that includes metrics and data for common food product categories and supply chain typologies. The calculator represents the structure of a generic (fresh food) supply chain and offers data sets for, amongst others, crop GHG emission factors and FLW in different stages of the production and distribution chain. Through scenario calculations with different chain parameters (describing pre and post-intervention scenarios), the net effects of an intervention on GHG emissions and FLW per unit of food sold to the consumer can be compared with little effort. In the case studies, interventions at the production stage as well as in post-harvest operations, are analyzed. Results show that post-harvest activities (especially FLW) contribute substantially to the carbon footprint of supplied food products. The FLW-reducing interventions are considered to induce additional GHG emissions. In most case studies, FLW-reducing interventions lower total GHG associated with a unit of food supplied to a client or consumer. However, in one case study, the extra emissions due to the intervention were higher than the prevented emission from lowering food losses. Consequently, in the latter case, the intervention is not an effective GHG emission reduction intervention.

Commercial‐scale liquid‐biofuel production utilizing forest‐based biomass would require feedstock supply from a large geographical area. Feedstock composition, supply chains' arrangements, and the resulting greenhouse gas (GHG) emissions are location dependent, and case‐specific assessments are needed if one is to guarantee the fulfillment of GHG reduction requirements by a specific biofuel product. This work assessed GHG emissions derived from the feedstock supply and transportation chain to three possible commercial‐scale biodiesel plant locations in Finland (Rauma, Porvoo, and Kemi) at site‐specific level. The supply of 7.2 PJ yr−1 (approximately 1 million m3solid) of forest biomass (harvesting residues, stumps, and small‐diameter energy wood) was assessed for each location, including four distinct scenarios for truck and railway transportation and two scenarios for biomass availability. Biomass availability and transportation‐network assessments were conducted through utilization of geographical information system methods, and the GHG emissions were assessed by means of life‐cycle assessment. The results showed that the GHG emissions of the supply chains can be effectively reduced through use of railway transportation from distant supply areas. Furthermore, even though the supply‐chain GHG emissions differed by up to 30% between the case‐study locations, the GHG emissions of the feedstock supply chain, from roadside stores of uncomminuted biomass to comminuted biomass delivered to the plants, were relatively low (2–4%) when compared with the GHG emissions of fossil diesel.

PurposeClimate change requires the reduction of direct and indirect greenhouse gas (GHG) emissions, a task that seems to clash with increasing supply chain complexity. This study aims to analyse the upstream supply chain complexity dimensions suggesting the importance of understanding the information processing that these may entail. Reducing equivocality can be an issue in some dimensions, requiring the introduction of written guidelines to moderate the effects of supply chain complexity dimensions on GHG emissions at the firm and supply chain level.Design/methodology/approachA three-year panel data was built with information obtained from Bloomberg, Trucost and Compustat. Hypotheses were tested using random effect regressions with robust standard errors on a sample of 394 SP500 companies, addressing endogeneity through the control function approach.FindingsHorizontal complexity reduces GHG emissions at the firm level, whereas vertical and spatial complexity dimensions increase GHG emissions at the firm and supply chain level. Although the introduction of written guidelines neutralises the negative effects of vertical complexity on firm and supply chain GHG emissions, it is not sufficient in the presence of spatial complexity.Originality/valueThis paper offers novel insights by suggesting that managers need to reconcile the potential trade-off effects on GHG emissions that horizontally complex supply chain structures can present. Their priority in vertically and spatially complex supply chain structures should be to reduce equivocality.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Even though biomass is characterised as renewable energy, it produces anthropogenic greenhouse gas (GHG) emissions, especially from biomass logistics. Lifecycle assessment (LCA) is used as a tool to quantify the GHG emissions from logistics but in the past the majority of LCAs have been steady-state and linear, when in reality, non-linear and temporal aspects (such as weather conditions, seasonal biomass demand, storage capacity, etc.) also have an important role to play. Thus, the objective of this paper was to optimise the environmental sustainability of forest biomass logistics (in terms of GHG emissions) by introducing the dynamic aspects of the supply chain and using the geographical information system (GIS) and agent-based modelling (ABM). The use of the GIS and ABM adds local conditions to the assessment in order to make the study more relevant. In this study, GIS was used to investigate biomass availability, biomass supply points and the road network around a large-scale combined heat and power plant in Naantali, Finland. Furthermore, the temporal aspects of the supply chain (e.g., seasonal biomass demand and storage capacity) were added using ABM to make the assessment dynamic. Based on the outcomes of the GIS and ABM, a gate-to-gate LCA of the forest biomass supply chain was conducted in order to calculate GHG emissions. In addition to the domestic biomass, we added imported biomass from Riga, Latvia to the fuel mixture in order to investigate the effect of sea transportation on overall GHG emissions. Finally, as a sensitivity check, we studied the real-time measurement of biomass quality and its potential impact on overall logistical GHG emissions. According to the results, biomass logistics incurred GHG emissions ranging from 2.72 to 3.46 kg CO2-eq per MWh, depending on the type of biomass and its origin. On the other hand, having 7% imported biomass in the fuel mixture resulted in a 13% increase in GHG emissions. Finally, the real-time monitoring of biomass quality helped save 2% of the GHG emissions from the overall supply chain. The incorporation of the GIS and ABM helped in assessing the environmental impacts of the forest biomass supply chain in local conditions, and the combined approach looks promising for developing LCAs that are inclusive of the temporal aspects of the supply chain for any specific location.

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

The real estate sector and its supply chains, i.e. up- and downstream processes, are responsible for a significant share of the greenhouse gas (GHG) emissions in most countries. The GHG emissions from the Swiss building stock are quantified and the hotspots identified along its supply chain using the multiregional, environmentally extended input–output tables Exiobase v3. Biodiversity impacts caused by land use, water stress due to water consumption, air pollution and eutrophication impacts are also quantified. The environmental impact-reduction requirements were estimated based on global planetary boundaries assuming that each economic sector will reduce its impacts according to the required global reduction. The Swiss real estate sector causes more than 24 Mt CO2e/year, which is 480 ppm of global emissions, while its gross value-added share is 200 ppm. Hence, the GHG emissions per US dollar gross value added of the Swiss real estate sector are above average. Two-thirds of the emissions are caused during the use stage of buildings, whereas 30% are caused by the supply chains. A reduction to net zero is needed within the next two to three decades to comply with the 1.5°C limit. The real estate sector must address its supply chains, but also must its tenants and users. Policy relevance The Swiss real estate sector building-related GHG emissions are analysed, taking into account the full building life cycle. The requirements for environmental impact reduction are estimated based on global planetary boundaries, assuming that each economic sector reduces its impacts with the same global percentage. The Swiss real estate sector is found to be environmentally inefficient: it causes more GHG emissions compared with its gross value-added share. Two-thirds of the emissions are caused during the use phase of buildings, with the remainder caused by the supply chain. A reduction to net zero is needed at the latest by 2050 in order to comply with the 1.5°C limit. The real estate sector should thus further increase the energy efficiency of buildings, phase out the use of fossil fuels and address its supply chains (particularly the construction materials and products) to develop zero emission products.

In recent years, sustainable supply chain management has gained increasing attention, and greenhouse gas (GHG) emissions throughout supply chains have been identified as one of the most important sustainability issues. This paper presents an investigation of the problem of transshipment among distribution centers (DCs) in a cold supply chain to achieve sustainable inventory cross-filling. Although transshipment is an effective tool for supply chain pooling, the possibility of increased GHG emissions raises environmental concerns. This study establishes a sustainable cold-chain logistics model that considers GHG emissions from DC storage and transshipment trucks. The new sustainable cold-chain model also reflects laden status and cargo weights of trucks for accurate emission assessment. An optimization model is also developed to minimize both GHG emissions and costs in the cold chain. Numerical simulations are conducted for diverse problem cases to examine important problem characteristics. The result analysis identifies that inventory service levels and demand variability have a strong impact on GHG emissions in transshipment; small p-values in the statistical analysis verify the significance of this effect. The different effects of demand variability and service levels on each emission source are also analyzed. The results demonstrate that transshipment among DCs can effectively reduce both GHG emissions and costs in cold supply chains. This study provides useful models and tools to assess GHG emissions and optimize decisions for the design and operation of transshipment. The proposed models will enable the assessment of sustainable alternatives and achieve sustainability objectives effectively for cold supply chains.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Purpose Methodology of co-product handling is a critical determinant of calculated resource use and environmental emissions per kilogram (kg) product but has not been examined in detail for different sheep production systems. This paper investigates alternative approaches for handling coproduction of wool and live weight (LW, for meat) from dual purpose sheep systems to the farm-gate. Methods Seven methods were applied; three biophysical allocation (BA) methods based on protein requirements and partitioning of digested protein, protein mass allocation (PMA), economic allocation (EA) and two system expansion (SE) methods. Effects on greenhouse gas (GHG) emissions, fossil energy demand and land occupation (classified according to suitability for arable use) were assessed using four contrasting case study (CS) farm systems. A UK upland farm (CS 1) and a New Zealand hill farm (CS 2) were selected to represent systems focused on lamb and coarse-textured wool for interior textiles. Two Australian Merino sheep farms (CS 3, CS 4) were selected to represent systems focused on medium to superfine garment wool, and lamb. Results and discussion Total GHG emissions per kilogram total products (i.e. wool+LW) were similar across CS farms. However, results were highly sensitive to the method of coproduct handling. GHG emissions based on BA of wool protein to wool resulted in 10–12 kg CO2-e/kg wool (across all CS farms), whereas it increased to 24–38 kg CO2-e/kg wool when BA included a proportion of sheep maintenance requirements. Results for allocation% generated using EA varied widely from 4 % (CS 1) to 52 % (CS 4). SE using beef as a substitution for sheep meat gave the lowest, and often negative, GHG emissions from wool production. Different methods were found to re-order the impacts across the four case studies in some instances. A similar overall pattern was observed for the effects of co-product handling method on other impact categories for three of the four farms. Conclusions BA based on protein partitioning between sheep wool and LW is recommended for attributional studies with the PMA method being an easily applied proxy for the more detailed BA methods. Sensitivity analysis using SE is recommended to understand the implications of system change. Sensitivity analysis using SE is recommended to investigate implications of choosing alternative products or systems, and

Health Care and Climate Change: Challenges and Pathways to Sustainable Health Care.

Well-to-wheel greenhouse gas emissions of electric versus combustion vehicles from 2018 to 2030 in the US

In recent years, global warming has become a serious problem in a global supply chain which is a series of cross-border transaction including custom duty that is a tax imposed for imported goods. In order to prevent the global warming, Green House Gas (GHG) emissions needs to be reduced throughout the supply chain. Moreover, procurement costs, material-based GHG emissions, tariff in countries are different by each country. In addition, the Trans-Pacific Partnership (TPP), which is a free trade agreement signed between 11 countries, including Japan and Malaysia, have promoted the trade in parts and products among the TPP participant countries without customs duty. Thus, the network on the global supply chain affects not only costs but also GHG emissions. On the other hand, the disruption by COVID-19 caused adverse impacts to redesign supply chains all over the world, where parts or materials are not provided from current suppliers by the disruption. Thus, the network may be reconfigured, which brings different GHG emissions in the global supply chain network before and after the disruption across TPP countries. The purpose of this study is to evaluate material-based GHG emissions under COVID-19 disruption on redesigning global supply chain network across TPP countries. Firstly, global supply chain network is modeled and formulated. Next, numerical experiments are conducted for evaluating material-based GHG emissions under disruption scenarios. Finally, the results are analyzed in terms of GHG emissions and costs. The result shows that the highest reduction ratio of the total GHG emission on a global supply chain is 58.4% compared to the baseline.KeywordsGreen supply chainEconomic partnershipLifecycle inventory databaseBill of Materials0–1 integer programming