A method of production carbon footprint analysis in a supply chain based on life cycle assessment

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.

The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran. The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N2O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat. The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO2-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO2-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of −2/3. This indicates that the carbon footprint of durum wheat production (in kg CO2-eq kg−1) typically decreases by 67% with a 100% increase in yield (in kg ha−1 year−1). Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China’s aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies.

This study assessed the techno-economic performance and life cycle greenhouse gas (GHG) emissions for various liquefied natural gas (LNG) supply chains in China in order to find the most efficient way to supply and use LNG. This study improves current literature by adding supply chain optimization options (cold energy recovery and hydrogen production) and by analyzing the entire supply chain of four different LNG end-users (power generation, industrial heating, residential heating, and truck usage). This resulted in 33 LNG pathways for which the energy efficiency, life cycle GHG emissions, and life cycle costs were determined by process-based material and energy flow analysis, life cycle assessment, and production cost calculation, respectively. The LNG and hydrogen supply chains were compared with a reference chain (coal or diesel) to determine avoided GHG emissions and GHG avoidance costs. Results show that NG with full cryogenic carbon dioxide capture (FCCC) is most beneficial pathway for both avoided GHG emissions and GHG avoidance costs (70.5–112.4 g CO2-e/MJLNG and 66.0–95.9 $/t CO2-e). The best case was obtained when NG with FCCC replaces coal-fired power plants. Results also indicate that hydrogen pathways requires maturation of new technology options and significant capital cost reductions to become attractive.

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

Carbon footprinting of electronic products

Introducing demand to supply ratio as a new metric for understanding life cycle greenhouse gas (GHG) emissions from rainwater harvesting systems

The apparel industry has a significant impact on climate change due to the substantial amount of greenhouse gas (GHG) emissions. Academic gowns commonly used in Thailand may be a significant contributor to high GHG levels due to apparel consumption. The objective of this study was to quantify the carbon footprint (CF) of an academic gown for bachelor degree students worn during the commencement ceremony at a private Thai university. The evaluation complies with the national guidelines on Carbon Footprint of Product (CFP) established by the Thailand Greenhouse Gas Management Organization (TGO) in line with ISO 14067:2018 Greenhouse gases - Carbon footprint of products - Requirements and guidelines for quantification. Considering only a single impact category: climate change, GHG emissions were calculated for the entire product life cycle, including raw material acquisition, production process, distribution, use, and the end-of-life (EoL) treatment, and relevant transportation/delivery. Data in this study were collected from the entrepreneur producing academic gowns for rental purposes. The numerical results revealed that CFP of an academic gown with a length of 40 inches, weighing 1,284.30 g, is 42.7 kgCO2-eq over its entire life cycle with 39.71% contributing from use phase and EoL treatment. The stages of raw material acquisition, use phase and production process caused most of the emissions at 41.08%, 33.69% and 18.49%, respectively. The carbon footprint of this gown serves as an important baseline data to enhance design development and the production process for emission reductions.

Impacts of alternative fuel combustion in cement manufacturing: Life cycle greenhouse gas, biogenic carbon, and criteria air contaminant emissions

Governments, environmental groups and industry associations are reducing greenhouse gas emissions to insure environmental sustainability. Manufacturing plays an important role in economic development but is a main cause of global warming since production requires energy consumption. The supply chain leadership coalition has requested all members to publish their carbon emission data and to reduce emissions. In addition, the International Standard Organization (ISO) has legislated and published ISO14064 as an industrial guideline to control global greenhouse gas emissions. The British Standards Institution developed PAS2050 as the world's first government regulation to control a product's carbon footprint. Providing carbon labelling on products increases product appeals and sales revenues, but also increases manufacturing costs. This research aims to minimise a product's carbon footprint, while controlling its manufacturing cost during collaborative green product design and production planning. An economic input–output life cycle assessment approach is used to evaluate the carbon emissions of new products. The life cycle assessment identifies problematic carbon emissions within the supply chain. Based on the input and output data, the research applies system dynamics modelling to simulate and identify green product redesigns with cost-effective carbon footprints during manufacturing. The purpose of this research is to derive optimal means to reduce the carbon footprint for green product development and production. Finally, the paper uses the case of an electronic image projector to demonstrate the application of the methodology.

We suggest a 2D-plot representation combined with life cycle greenhouse gas (GHG) emissions and life cycle cost for various energy conversion technologies. In general, life cycle assessment (LCA) not only analyzes at the use phase of a specific technology, but also covers widely related processes of before and after its use. We use life cycle GHG emissions and life cycle cost (LCC) to compare the energy conversion process for eight resources such as coal, natural gas, nuclear power, hydro power, geothermal power, wind power, solar thermal power, and solar photovoltaic (PV) power based on the reported LCA and LCC data. Among the eight sources, solar PV and nuclear power exhibit the highest and the lowest LCCs, respectively. On the other hand, coal and wind power locate the highest and the lowest life cycle GHG emissions. In addition, we used the 2D plot to show the life cycle performance of GHG emissions and LCCs simultaneously and realized a correlation that life cycle GHG emission is largely inversely proportional to the corresponding LCCs. It means that an expensive energy source with high LCC tends to have low life cycle GHG emissions, or is environmental friendly. For future study, we will measure the technological maturity of the energy sources to determine the direction of the specific technology development based on the 2D plot of LCCs versus life cycle GHG emissions.

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

Despite the ever-growing body of life cycle assessment (LCA) literature on electricity generation technologies, inconsistent methods and assumptions hamper comparison across studies and pooling of published results. Synthesis of the body of previous research is necessary to generate robust results to assess and compare environmental performance of different energy technologies for the benefit of policy makers, managers, investors, and citizens. With funding from the U.S. Department of Energy, the National Renewable Energy Laboratory initiated the LCA Harmonization Project in an effort to rigorously leverage the numerous individual studies to develop collective insights. The goals of this project were to: (1) understand the range of published results of LCAs of electricity generation technologies, (2) reduce the variability in published results that stem from inconsistent methods and assumptions, and (3) clarify the central tendency of published estimates to make the collective results of LCAs available to decision makers in the near term. The LCA Harmonization Project's initial focus was evaluating life cycle greenhouse gas (GHG) emissions from electricity generation technologies. Six articles from this first phase of the project are presented in a special supplemental issue of the Journal of Industrial Ecology on Meta-Analysis of LCA: coal (Whitaker et al. 2012), concentratingmore » solar power (Burkhardt et al. 2012), crystalline silicon photovoltaics (PVs) (Hsu et al. 2012), thin-film PVs (Kim et al. 2012), nuclear (Warner and Heath 2012), and wind (Dolan and Heath 2012). Harmonization is a meta-analytical approach that addresses inconsistency in methods and assumptions of previously published life cycle impact estimates. It has been applied in a rigorous manner to estimates of life cycle GHG emissions from many categories of electricity generation technologies in articles that appear in this special supplemental supplemental issue, reducing the variability and clarifying the central tendency of those estimates in ways useful for decision makers and analysts. Each article took a slightly different approach, demonstrating the flexibility of the harmonization approach. Each article also discusses limitations of the current research, and the state of knowledge and of harmonization, pointing toward a path of extending and improving the meta-analysis of LCAs.« less

Life cycle assessment of primary energy demand and greenhouse gas (GHG) emissions of four propylene production pathways in China

Smallholder dairy farms face enormous challenges in increasing milk production while mitigating greenhouse gas (GHG) emissions, thereby enhancing climate resilience. The carbon footprint (CF) of smallholder milk production is expected to increase with increasing demand for dairy products under the business-as-usual scenario. This study estimates the carbon footprint of smallholder milk production and examines variation across farms using data from 480 households to identify viable options for mitigating GHG emissions. We applied a cradle to farm-gate life cycle assessment (LCA) approach to examine the effects of farming systems on GHG emission intensities across intensification gradients of smallholder farms (SHF) from four potential dairy districts in the central highlands of Ethiopia. According to our findings, enteric fermentation was the primary source of GHG emissions, and methane(CH4) emissions from enteric fermentation and manure management accounted for the majority of total emissions across farms. The estimated average CF varies depending on farming systems, global warming potential (GWP), and allocation methods used. When GHG emissions were allocated to multiple products using economic allocation and based on IPCC (2007)and IPCC (2014)GWPs, the overall average CF of milk production was 1.91 and 2.35kg CO2e/kg fat and protein-corrected milk (FPCM), respectively. On average, milk accounted for 72% of total greenhouse gas emissions. In terms of farm typology, rural SHF systems produced significantly more CF per kg of milk than urban and peri-urban SHF systems. Variations in milk yield explained more than half of the variation in GHG emissions intensity at the farm level. Feed digestibility and feed efficiency had a negative and significant (P < 0.01) association with CF of SHF. Our findings suggested that improving feed digestibility and feed efficiency by increasing the proportion of concentrate and improved forage as well as chemically upgrading straw and crop residue could provide an opportunity to both increase milk yield and reduce the CF of milk production of SHF in the study area. Supporting SHF to realize strategies contributing to climate-resilient dairy development require interventions at several levels in the dairy value chain.