Analyzing the Carbon Footprint of the Finished Bovine Leather: A Case Study of Aniline Leather

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

Addressing the social life cycle inventory analysis data gap: Insights from a case study of cobalt mining in the Democratic Republic of the Congo

As global warming becomes increasingly severe, environmental consciousness has become critical in the design and operation of globally integrated supply chain networks. Product Carbon Footprint is defined as the life cycle Greenhouse Gas (GHG) emissions of goods and services and it can be considered as a simplified life cycle assessment restricted to a single impact category. In order for companies to better confront GHG emission issues, calculating product carbon footprint and analysing how various parameters affect the carbon footprint over the entire life cycle of a product is necessary. This paper studies the carbon footprint across supply chains and proposes a method of production carbon footprint analysis in a supply chain based on life cycle assessment, including the following: taking product life cycle as the span of carbon footprint analysis, with all kinds of complex information system as objects and then carrying out the carbon footprint knowledge extraction according to the concept model format in physical database; building a carbon footprint analysis ontology, which is related to product life cycle in supply chain environment; calculating the quantification of carbon footprint through GHG emissions over the entire life cycle, and designing a tool for product carbon footprint in supply chain environment.

Building-information-modeling enabled life cycle assessment, a case study on carbon footprint accounting for a residential building in China

PDF HTML阅读 XML下载 导出引用 引用提醒 基于生命周期评价的上海市水稻生产的碳足迹 DOI: 10.5846/stxb201304240794 作者: 作者单位: 上海市农业科学院,上海市农业科学院,上海市农业科学院,上海市农业科学院,江西农业大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技部支撑计划后世博专项资助项目（2010BAK69B18）；上海市科委崇明科技攻关专项资助项目（10DZ1960101） Life cycle assessment of carbon footprint for rice production in Shanghai Author: Affiliation: Shanghai Academy of Agricultural Sciences,Seed management station of Shanghai,,,Jiangxi Agricultural University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:碳足迹是指由企业、组织或个人引起的碳排放的集合。参照PAS2050规范并结合生命周期评价方法对上海市水稻生产进行了碳足迹评估。结果表明：（1）目前上海市水稻生产的碳排放为11.8114 t CO2e/hm2，折合每吨水稻生产周期的碳足迹为1.2321 t CO2e；（2）稻田温室气体排放是水稻生产最主要的碳排放源，每吨水稻生产的总排放量为0.9507 t CO2e，占水稻生产全部碳排放的77.1%，其中甲烷（CH4）又是最主要的温室气体，对稻田温室气体碳排放的贡献率高达96.6%；（3）化学肥料的施用是第二大碳排放源，每吨水稻生产的总排放量为0.2044 t CO2e，占水稻生产总碳排放的16.5%，其中N最高，排放量为0.1159 t CO2e。因此，上海低碳水稻生产的关键在降低稻田甲烷的排放，另外可通过提高氮肥利用效率，减少氮肥施用等方法减少种植过程中碳排放。 Abstract:Global climate change has become an urgent issue of concern. Climate change will increasingly threaten our food production, security and even the survival of the human race. It also has a serious impact on natural ecosystems and the socioeconomic system. With the increasing scale and improvement in mechanization levels, the economic linkage between agricultural production and reduction of Greenhouse Gas (GHG) emissions is even closer in the agricultural production system. Therefore, the development of a low-carbon agricultural model is one of the long-term strategies for low-carbon economic growth throughout the country.This research of carbon footprint is introduced to measure the GHG emission over the rice production cycle. The carbon footprint can be defined as the total carbon emissions caused by an organization, event, product or person. At present, carbon footprints are used to measure GHG emissions in products, services, organizations, cities and countries and offer the decision basis for the formulation of GHG emission reduction schemes.Agricultural ecological systems, every year, also produce a lot of GHG emissions. The whole process of prenatal, intrapartum and postpartum agricultural production are closely related to energy consumption and GHG emission. In the process, all the agricultural inputs, such as chemical fertilizers, pesticides, seeds, cultivation, plant protection, agricultural machinery, irrigation and harvest also produce greenhouse gas emissions.The whole cultivation of rice involves methane (CH4) emission. This study shows that rice cultivation is one of the biggest sources of GHG emissions in crop cultivation. Rice paddies emit a large amount of methane in their water logged mode. Different irrigation modes have a great influence on the emission of GHG. Straw return is another factor that promotes GHG emissions. Soil organic content increases with the return of straw, with an increase in the soil methanogen activity, leading to increased methane emissions.The current carbon footprint research is the first time it has been used to measure the carbon emissions involved in rice production. The carbon footprint for rice production in Shanghai was assessed by the PAS2050 paradigm and life cycle assessment. The study area, located in Changjiang Farm, which belongs to the Guangming Group in Chongming County Shanghai City atlatitude 121°32'22' E, longitude31°40'23' N. Chongming County, in the Yangtze River Estuary, is a typical sub tropical monsoon climate with mild climate, abundant rainfall, annual average temperatures of 15.3 ℃, and annual precipitation of 1245 mm. It is the major grain production base for Shanghai city with winter wheat and summer rice forming their main planting patterns, which are typical for the middle and lower reaches of the Yangtze River rice-wheat rotation cropping pattern.The entire carbon emission of rice production in Shanghai was 11.8114 t CO2e (CO2-equivalents)/hm2, corresponding to a 1.2321 t CO2e/t rice grain yield. GHG emissions from paddy fields were the major source, which emitted 0.9507 t CO2e/t rice and accounted for 77.1% of total carbon emissions during rice production. Moreover, CH4 was the largest source for GHG emissions with a contribution rate of 96.6%.Chemical fertilizers were the second largest emission source in rice production. Chemical fertilizers emitted 0.2044 t CO2e for each ton of rice production, contributing 16.5% of total carbon emissions in rice production. N fertilizer was the biggest emission source, which released 0.1159 t CO2e/t rice.This research investigates the GHG emissions over the whole process of the Shanghai rice production cycle and reveals the energy consumption and GHG emissions in rice production. Thus, a rice carbon footprint is calculated by assessing the GHG emissions in Shanghai rice production. The results are beneficial for producing reduction plans of reducing GHG emissions in Shanghai rice production. Furthermore, the results will supply both practicable and theoretical foundations for drafting carbon footprint formulations in other industrial areas. 参考文献 相似文献 引证文献

Food processing is a major thriving industry globally and provides livelihood to millions of workers. Food processing is an energy intensive process and often has an impact on the environment which remains undiagnosed and hence not quantified. Food processing industry comprises the organized as well as unorganized sector with varying levels of energy requirement and therefore the carbon foot prints also significantly vary. Higher energy use is often related to higher greenhouse gas (GHG) emission which is responsible for global warming and climate change. Carbon footprint (CFP) of food industry is an estimate of the energy use and GHG emissions caused due to the processing and delivery of food items to the consumer and also disposal of packaging. Recently there is a growing interest in estimating the carbon footprint of food industries to know how improved technologies can be used to make food processing less energy and carbon intensive. In this book chapter we would like to provide an overview of energy use and carbon footprint of different types of food industries. Quantification of CFP is generally done using Life Cycle Assessment (LCA) in which GHG emissions are measured from the very beginning of the production process to its final use and disposal. GHG emission from a food industry will include both direct emissions as well as indirect emissions. The CFP of different sectors like fruit and beverage industry, sugar production, dairy sector, fisheries, meat and poultry supply chains are presented. Apart from this, research gaps and possible steps to minimize the carbon footprint will be mentioned. Assessing the CFP of food industries can help in identifying the GHG sources and can be useful in developing alternative technologies which are more energy efficient and reduces GHG emission. Further, change in dietary pattern also contributes immensely to reduce the environmental impact of food consumption.

Feeding a growing, increasingly affluent population while limiting environmental pressures of food production is a central challenge for society. Understanding the location and magnitude of food production is key to addressing this challenge because pressures vary substantially across food production types. Applying data and models from life cycle assessment with the methodologies for mapping cumulative environmental impacts of human activities (hereafter cumulative impact mapping) provides a powerful approach to spatially map the cumulative environmental pressure of food production in a way that is consistent and comprehensive across food types. However, these methodologies have yet to be combined. By synthesizing life cycle assessment and cumulative impact mapping methodologies, we provide guidance for comprehensively and cumulatively mapping the environmental pressures (e.g., greenhouse gas emissions, spatial occupancy, and freshwater use) associated with food production systems. This spatial approach enables quantification of current and potential future environmental pressures, which is needed for decision makers to create more sustainable food policies and practices.

This study assessed the possibility of using wood as a building material for the construction of houses. A comprehensive method was used, which consisted of analysing environmental management regulations, applying the life cycle assessment method to minimise the carbon footprint; using software to calculate the carbon footprint of a wooden house at different stages of the life cycle. The object of study is the carbon footprint of a house built of wood. The Life Cycle Assessment method was used as a methodology for assessing the life cycle. Using the One Click Life Cycle Assessment and Life Cycle Cost software, the carbon footprint of a log house was calculated for the product life cycle stage mentioned above (A1-A3). When calculating the carbon footprint of wood-based building materials, carbon emissions were taken into account not only from the finished products, but also from all other products obtained as a result of logging. When calculating the carbon footprint, greenhouse gas emissions from all activities are estimated. We have obtained data on the life cycle cost of a wooden house in terms of electricity use. Accordingly, we obtained a value of global warming potential (A1-A3) of 0.51 kg CO2 e/kWh. We also obtained data on the life cycle cost of a wooden house in terms of diesel consumption. According to the results of the LCA, the value of the global warming potential due to meeting the water supply/sewage needs is (A1-A3) 0.69 kg CO2 e/m3. The value of the global warming potential due to meeting the heat supply needs of production needs is (A1- A3) 0.13 kg CO2 e/kWh. Based on the information obtained, we can conclude that it is advisable to use a wooden log house as a building material, as the carbon footprint is smaller than that of a brick building. The final section presents the results of calculating the life cycle cost of a wooden house by discount factor and inflation, the results of the life cycle cost of a wooden house by percentage of energy costs, and the results of assessing the life cycle cost of a wooden house (displaying parameters according to the European energy certification scale). Based on the carbon footprint assessment (using the Life Cycle Assessment methodology), economic comparison (Life Cycle Cost and total construction costs), and expert assessment (based on technical and ergonomic parameters) of the two construction technologies, the feasibility and possibility of using wood as a building material was established. The study proves the feasibility of applying the LCA method in the construction industry.

As global warming becomes increasingly severe, environmental consciousness has become critical in the design and operation of globally integrated supply chain networks. Product Carbon Footprint is defined as the life cycle Greenhouse Gas (GHG) emissions of goods and services and it can be considered as a simplified life cycle assessment restricted to a single impact category. In order for companies to better confront GHG emission issues, calculating product carbon footprint and analysing how various parameters affect the carbon footprint over the entire life cycle of a product is necessary. This paper studies the carbon footprint across supply chains and proposes a method of production carbon footprint analysis in a supply chain based on life cycle assessment, including the following: taking product life cycle as the span of carbon footprint analysis, with all kinds of complex information system as objects and then carrying out the carbon footprint knowledge extraction according to the concept model format in physical database; building a carbon footprint analysis ontology, which is related to product life cycle in supply chain environment; calculating the quantification of carbon footprint through GHG emissions over the entire life cycle, and designing a tool for product carbon footprint in supply chain environment.

New energy and renewable widely available in Indonesia. One of them is the biomass that can be used with gasification technology. Biomass is an organic matter to which derived from biological materials. This research was used integration gasification system with a gas engine, which works more properly with CO, and H2. The advantage of this biomass power plant compared the environmental impact on other types of plants such as coal-fired power plants, diesel power plants, etc. Therefore the potential of environmental impacts was generated, it is necessary to calculate quantitatively through the life cycle assessment methods. This research aimed to calculate impact assessment on electricity production from a Biomass Power Plant system through a life cycle assessment with boundary cradle to grave in Indonesia. The study revealed that greenhouse gas (GHG) emission of electricity production from an empty fruit bunch palm oil mill was 0.15 kg CO2-eq kWh–1. The gas engine was the highest GHG emission contributor during its life cycle. Empty fruit bunch as a source of biomass for electricity production was considered as climate-friendly power plant system due to its potential in reducing GHG emission from palm oil production and released lower GHG emission.

Based on Life Cycle Assessment and other related methods, this paper introduced a comprehensive model for the evaluation of the carbon footprint and greenhouse gases emission in household biogas plants including nearly all the processes of the household biogas project, such as the collection of raw materials, fermentation processing, and fermentation residue processing and so on. The carbon footprint and greenhouse gas emission from three classical household biogas plants in China were analyzed. Considering the greenhouse gases emissions in life cycle of household biogas plants, the main emission processes were investigated to be the utilization of biogas, such as biogas combustion use and transportation of materials which both accounting for more than 98%. The greenhouse gases emissions in the stages of methane leakage and construction materials production were only estimated to be 1.1% and 0.5%, respectively. As comparing to the meandering fabric digester and the precast reinforced concrete panels fabricated digester, the in-situ concrete cylindrical water pressure digester showed the lowest carbon footprint and accordingly most potential for the reduction of greenhouse gases emission. It tried to analyze three household biogas plants' carbon footprint and greenhouse gas emission during the stages. It can provide the basis for optimization low-carbon proposal and the analysis and built up a simple carbon footprint calculation model. About household digesters life cycle greenhouse gas emissions, the main emission process are biogas utilization period and transport phase , accounting for more than 98.38 percent , followed by methane leak stage and building materials production stage, about 1.11% and 0.51% .Compared to meandering fabric type digesters and precast reinforced concrete panels fabricated digesters, in-situ concrete cylinder shaped hydraulic digester's carbon footprint is minimum so greenhouse gas emission reduction potential is great.

The healthcare sector in the United States has increased its greenhouse gas emissions by 6% since 2010 and today has the highest per capita greenhouse gas emissions globally. Assessing the environmental impact and material use through the methods of life cycle assessment (LCA) and material flow analysis (MFA) of healthcare procedures, products, and processes can aid in developing impactful strategies for reductions, yet such assessments have not been performed in orthopaedic surgery. We conducted an LCA and an MFA on an ACL reconstruction (ACLR). The ACLR served as a test case on the assumption that lessons learned would likely prove relevant to other orthopaedic procedures. (1) What are the life cycle environmental impacts of ACLR? (2) What is the material flow and material circularity of ACLR? (3) What potential interventions would best address the life cycle environmental impacts and material circularity of ACLR? First, we conducted an LCA according to International Organization for Standardization standards for quantifying a product's environmental impact across its entire life cycle. One result of an LCA is global warming potential measured in carbon dioxide equivalent (CO 2 eq), or carbon footprint. Second, we conducted an MFA of ACLR. Material flow analyses are used to quantify the amount of material in a determined system by tracking the input, usage, and output of materials, allowing for the identification of where materials are consumed inefficiently or lost to the environment. To contextualize the MFA, we calculated the material circularity indicator (MCI) index. This is used to measure how materials are circulating in a system and to evaluate the extent to which materials are recovered, reused, and kept within the economic loop rather than disposed of as waste. These three methods are widely used in other fields, especially engineering, but are more limited in healthcare research. Data collection and observations of ACLRs were made during ACLRs at the University of Pittsburgh Medical Center Bethel Park Surgical Center in Pittsburgh, PA, USA, between 2022 and 2023. Three sessions of data collection and observations were needed due to complexity and scheduling, ranging from understanding the sterilization procedures to weighing individual items. Data encompassing electricity usage; surgical equipment type; the use of heating, ventilation, and air conditioning (HVAC) systems; the production and reuse of reusable instruments and gowns; and the production and disposal of single-use surgical products were collected. Following data collection, we conducted the LCA and the MFA and then calculated the MCI for a representation of a single ACLR. To identify strategies to reduce the environmental impact of ACLR, we modeled 11 possible sustainability interventions developed from prior work and compared those strategies against the impact of the baseline ACLR. Our results show that the ACLR generated an estimated life cycle greenhouse gas emissions of 47 kg of CO 2 eq, which is analogous to driving a typical gasoline-fueled passenger vehicle for 120 miles. The total mass of all products for one ACLR was estimated at 12.73 kg, including 7.55 kg for disposable materials and 5.19 kg for reusable materials. Concerning material circularity, ACLR had a baseline MCI index of 0.3. Employing LCA for the carbon footprint and the MCI for 11 sustainability interventions indicated the potential to reduce greenhouse gas emissions by up to 42%, along with an increase in circularity (how materials are recovered, reused, and kept within the economic loop rather than disposed of as waste) of up to 0.8 per ACLR. Among the most impactful interventions are the reduction in the utilization of surgical pack products, reutilization of cotton towels and surgical gowns, maximization of energy efficiency, and increasing aluminum and paper recycling. ACLR has a substantial carbon footprint, which can meaningfully be reduced by creating a minimalist custom pack without material wastage, reusing cotton towels, and maximizing recycling. Combining LCA, MFA, and MCI can provide a thorough assessment of sustainability in orthopaedic surgery. Orthopaedic surgeons and staff can immediately reduce the environmental impact of orthopaedic procedures such as ACLR by opening fewer materials-via making minimalist packs and only opening what is needed in the operating room-and by incorporating more reusable materials such as towels. Larger scale medical center changes, such as implementing recycling programs and installing energy-efficient systems, also can make a meaningful difference in reducing environmental impact.

Total Intravenous Anesthetic Versus Inhaled Anesthetic: Pick Your Poison.

The Irish dairy industry aims to increase milk production from grass-based farms following the removal of the EU milk-quota system, but is also required to minimise greenhouse gas (GHG) emissions to meet European reduction targets. Consequently, the sector is under increasing pressure to reduce GHG emissions per unit of milk, or carbon footprint (CF). Therefore, the goal of the present study was to determine the main sources of the CF of grass-based milk production and to identify mitigation strategies that can be applied to reduce farm footprints. In total, the CF of milk was estimated for 62 grass-based dairy farms in 2014. The method used to quantify GHG emissions was a life cycle assessment (LCA), independently certified to comply with the British standard for LCA (PAS 2050). The LCA method was applied to calculate annual on- and off-farm GHG emissions associated with dairy production until milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk on the basis of the economic value of dairy products and expressed per kilogram of fat- and protein-corrected milk to estimate CF. Enteric methane was the main source of the CF of milk (46%), followed by emissions from inorganic N fertilisers (16%), manure (16%) and concentrate feedstuffs (8%). The mean CF of milk from the 62 farms was 1.26 kg of CO2-eq per kilogram of fat- and protein-corrected milk, but varied from 0.98 kg to 1.67 kg as measured using the 95% confidence interval. The CF of milk was correlated with numerous farm attributes, particularly N-fertiliser, the percentage of grazed grass in the diet, and production of milk solids. Grass-based dairy farmers can significantly improve these farm attributes by increasing herd genetic merit, extending the length of the grazing season and optimising N fertiliser use and, thereby, reduce the CF of milk.

Carbon and Nitrogen Footprints of Major Cereal Crop Production in China: A Study Based on Farm Management Surveys