Carbon Footprint Of Production Research Articles

Factors influencing the carbon footprint of rice production in Northeastern Vietnam

Factors influencing the carbon footprint of rice production in Northeastern Vietnam

Validation of genomic tools to improve production efficiency, health resilience and the carbon footprint of beef production

Genomic tools and accuracy of molecular breeding values (MBVs) for economically important traits continue to improve and are being applied in commercial crossbred beef cattle. Ge­nomic breed composition and retained heterozygosity of an individual animal can be used to further improve female fertil­ity, stayability, lifetime productivity and calf health resilience. But this is just the first step. Within specific crossbred popula­tions, researchers at Livestock Gentec have used large numbers of cattle phenotypes and genotypes, combined with advanced statistical genomic analyses to generate MBVs for 18 traits with moderate to moderately-high accuracy (0.35 to 0.60). This accu­racy is equivalent to 10 to 20 progeny records. These MBVs are economically balanced into multi-trait profit indices such as the Replacement Heifer Profit Index Score and the Feeder Profit In­dex. The use of these genomic tools will improve the sustainabil­ity of beef production by improving profitability, lowering the carbon footprint, and improving an animal’s ability to adapt to changing environments. The following paper outlines the valida­tion of these genomic tools and their potential benefits.

Incorporating pruning into the carbon footprint of tree production based on terrestrial laser scanning

Pruning is a major source of carbon emissions from urban trees. The high cost of evaluating pruning quantities by destructive measurements has limited the research on pruning. By combining terrestrial laser scanning and quantitative structure models, pruning quantities can be assessed non-destructively. This study focuses on the impact of pruning during tree production, as it is intense and has been rarely evaluated. Using Sophora japonica from a nursery in Beijing as an example, point cloud data were collected from 181 uneven-aged Sophora japonica for the simulation of pruning at a single tree level. All pruning stages were incorporated into the assessment of the carbon footprint of Sophora japonica production for 15-year-old trees. The results show that previous studies have underestimated the tree carbon footprints of pruning, leading to a severe underestimation of the carbon footprint of tree production. Crown reduction removes the most above-ground woody biomass during tree production, over half, while the decomposition of pruning waste is the most significant source of carbon emissions. The removal ratio from pruning of individual trees is consistent within the same pruning pattern. The tree volume can serve as a good predictor for estimating pruning quantities, but crown diameter sometimes needs to be considered. Implementing pruning interventions, harvesting in advance, and choosing appropriate methods for pruning waste disposal can reduce carbon emissions from pruning.

Analysis of the Carbon Footprint of Academic Gowns: A Case Study of Thai University

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.

A comparison of deflation methods for carbon footprint calculations using Japanese data

An embodied CO2 emissions intensity database estimated from input–output data at current prices is now available in Japan. This study compares two non-survey methods: The double-deflation (DD) method and an elaborated approach combining the DD method with the generalized RAS method to deflate an input–output table (IOT). We used these methods to estimate new datasets of embodied CO2 emission intensity data in Japan, utilizing Japan's IOTs for 2005, 2011, and 2015 at constant prices in 2015. Furthermore, we compare the estimated data of 367 commodity sectors for a specific year (2005 or 2011). The results reveal that the intensity for certain aggregated sector groups, such as non-ferrous metals and finance and insurance, exhibits higher uncertainty owing to the extreme price homogeneity assumption associated with the DD method. Consequently, we recommend that life-cycle-assessment practitioners use an open database when analyzing changes in the carbon footprint of products over time.

The influence of disclosing product lifecycle carbon footprint information on consumer purchase intentions based on the APE model perspective: An ERP and questionnaire study

BackgroundCarbon emissions are increasingly becoming the primary cause of climate change, and carbon information disclosure can affect consumer purchase intentions. However, existing studies only focus on the disclosure of carbon information for a single lifecycle stage, gnoring consumers' overall perception process. MethodsThis study uses scenario experiments and event-related potential experiments in combination, based on the associative-propositional evaluation (APE) model, to explore the differences in the impact of disclosing product information with high carbon emissions in different lifecycle stages (production stage, use stage, recycling stage) on consumers' purchase intentions. ResultsThe questionnaire results found that consumers' willingness to purchase products with high carbon emissions in the use stage was the lowest; The behavioral results found that the purchase rate of products with high carbon emissions in the recycling stage was the lowest; The brain electricity results found that products with high carbon emissions in the use stage induced the largest P2 component; Products with high carbon emissions in the recycling stage induced the largest N2 component. ConclusionThe attitudes of evaluation with proposition dominance among consumers tend to attribute carbon emissions in the use stage to their own behavioral choices. The attitudes of evaluation with association dominance among consumers reflect the cognitive conflicts existing in consumers' understanding of carbon emission information during recycling. This study expands the perspective of researching the disclosure effects of product carbon footprints and provides references for corporate marketing strategies and policy formulation.

Spatiotemporal variation of the carbon footprint of tobacco production from 2004 to 2017 in China

Spatiotemporal variation of the carbon footprint of tobacco production from 2004 to 2017 in China

Enhancing durability and sustainability in concrete with fibre-reinforced composites

This paper presents a study focused on two pivotal innovations in the field of fibre-reinforced concrete (FRC) to significantly enhance its durability and sustainability in construction. First, our research investigates the application of advanced self-healing mechanisms in FRC. By embedding microcapsules containing healing agents within the concrete matrix, we achieved a remarkable reduction in crack propagation and improved structural integrity. Our results demonstrate that the self-healing FRC exhibited a 30% increase in compressive strength and a 40% reduction in crack width, leading to a longer service life for concrete structures. Second, we explore the integration of sustainable materials in FRC production. By incorporating locally sourced and recycled materials, we successfully reduced the environmental impact associated with FRC manufacturing. Our findings reveal a substantial reduction in carbon emissions, with a 25% decrease in the overall carbon footprint of FRC production. This innovation not only contributes to a greener construction industry but also aligns with sustainability goals and regulations. This research underscores the transformative potential of self-healing mechanisms and sustainable material integration in FRC, offering tangible results in terms of increased durability and reduced environmental impact. These innovations promise to reshape the construction landscape, aligning it with the principles of sustainability and long-term structural resilience.

Assessing the impact of climate action mitigation strategies from livestock production: A review – Solution for greenhouse gases mitigation

Abstract The main sources of greenhouse gas (GHG) emissions are enteric fermentation from ruminants and manure management. An integrated strategy-combination approach incorporating nutrition and manure management is necessary to dramatically reduce GHGs and the carbon footprint of milk production. The aim of this review was to assess the effect of climate action mitigation strategies on the GHG production of ruminant animals. This review was based on the different references, which are textbooks, journals, proceedings, conferences, and abstracts accessed through Agricola, Agris, CAB Abstracts, Embase, MEDLINE, and the Web of Science. The research findings were done by using dairy cattle, sheep, and goat; the numbers of animals used in each experiment were given the majority of attention, and decisions were also made based on the method used to quantify methane (CH 4 ) and nitrous oxide. Enteric CH 4 per unit of milk was reduced by 6–8% when higher-starch corn silage was used in place of barley or alfalfa silage. Cows fed seaweed (1.77–2%, on dry matter [DM] basis) experienced a linear drop in enteric CH 4 emission from 383 to 400 g/d. Supplementation of vegetable fats (6%) and coconut oil (12 g/day) to ruminant diets can decrease CH 4 emissions by 21–40% and 50–61.2%, respectively. Similarly, the addition of 21.5 g nitrate/kg DM reduces CH 4 yield (17%) in sheep. Bovaer can reduce methane emissions (30%) for dairy cows. Feed processing and additives are alternative strategies to minimize GHG production in ruminants, but further studies on additives and their residual effect on livestock output is needed.

Biochar application reduced carbon footprint of maize production in the saline−alkali soils

The amendment of biochar to cropland has been recommended as a potential strategy to mitigate climate change and increase soil fertility by enhancing carbon (C) storage. Quantifying the environmental benefits and resulting carbon footprint (CF) of integrating biochar and fertilizer treatments is paramount in facing intensified human activities of agricultural land expanding under climate change, especially in fragile inland catchments for saline-alkalis soils. A three−year field experiment was conducted with maize in the Tarim River Basin to monitor greenhouse gas (GHG) emissions, maize yield, soil organic carbon (SOC), and CF from 2020 to 2022. This study involved seven treatments that varied in nitrogen (N) fertilizer, irrigation, and biochar applications: (i) 0N0W (0 kg N ha−1, 0 mm, 0 t ha−1 biochar), (ii) LNLW (100 kg N ha−1, 140 mm, 0 t ha−1 biochar), (iii) LNLWB (100 kg N ha−1, 140 mm,10 t ha−1 biochar), (iv) MNMW (200 kg N ha−1, 220 mm, 0 t ha−1 biochar), (v) MNMWB (200 kg N ha−1, 220 mm, 10 t ha−1 biochar), (vi) HNHW (300 kg N ha−1, 320 mm, 0 t ha−1 biochar) (conventional treatment), and (vii) HNHWB (300 kg N ha−1, 320 mm, 10 t ha−1 biochar). The results showed that biochar amendment (LNLWB, MNMWB, HNHWB) reduced CO2 emissions by (7%, 8%, 7%), accumulative emission of CH4 and N2O (AE) (19%, 15%, 15%), greenhouse gas intensity (GHGI) (32%, 24%, 22%) and CF (77%, 61%, 56%), and increased SOC sequestration (47%, 46%, 46%), maize yield (19%, 12%, 12%) compared to no biochar (LNLW, MNMW, HNHW) CO2 emission (3355, 4141, 4619 kg CO2−C ha−1), AE (148, 221, 469 kg CO2−eq ha−1), GHGI (16.3, 21.2, 40.6 kg CO2−eq t−1 yield), CF (1373, 1990, 2784 kg CO2−C ha−1), SOC (14.2, 15.1, 15.6 Mg C ha−1), maize yield (9.1, 10.6, 11.5 t ha−1). Furthermore, compared to HNHW, LNLWB reduced 32% CO2, 74% N2O, 89% CF, and increased 39% SOC. Overall, the biochar application (10 t ha−1) with reduced N (100 kg N ha−1) input in the Tarim River Basin, is a win−win strategy for reducing CF, enhancing C sequestration, and supporting stable food production, and it is a low–carbon agricultural strategy for farmland in saline−alkali soils.

Life cycle assessment and product carbon footprint for SHG zinc production

The industry’s environmental impact has moved into focus at global level. Regulators, supply chains, and the financial sector need credible, standardized, and transparent information for multiple reasons. These include regulatory targets for limiting emissions, downstream user optimizations, and developing science-based emission reduction strategies. By characterizing environmental impacts, companies can satisfy stakeholder demands and measure progress towards goals. In this paper, an introduction to life cycle assessment (LCA) for reporting on environmental impacts, including the product carbon footprint as global warming potential is given. Average results from the most recent global LCA update for special high-grade zinc production are summarized. Resulting carbon footprint information is then used to derive the zinc industry’s baseline carbon footprint as the starting point for the decarbonization roadmap for the global zinc industry.

A simplified machine learning product carbon footprint evaluation tool

On the way to climate neutrality manufacturing companies need to assess the Carbon dioxide (CO2) emissions of their products as a basis for emission reduction measures. The evaluate this so-called Product Carbon Footprint (PCF) life cycle analysis as a comprehensive method is applicable, but means great effort and requires interdisciplinary knowledge. Nevertheless, assumptions must still be made to assess the entire supply chain. To lower these burdens and provide a digital tool to estimate the PCF with less input parameter and data, we make use of machine learning techniques and develop an editorial framework called MINDFUL. This contribution shows its realization by providing the software architecture, underlying CO2 factors, calculations and Machine Learning approach as well as the principles of its user experience. Our tool is validated within an industrial case study.

Techno-economic analysis of small-scale ammonia production via sorption-enhanced gasification of biomass

Biomass gasification is a green and efficient pathway for lowering the carbon footprint of ammonia production. Decentralized, small-scale biomass gasification plants (<150 t NH3/day output) are more practical than large plants due to sustainable large-scale biomass supply constraints. Small-scale biomass gasification for ammonia production faces the challenges of high energy consumption and production costs. Process intensification through sorption-enhanced gasification (SEG) integrates steam gasification and in-situ CO2 separation using regenerable CaO sorbents, directly producing hydrogen-rich syngas (∼70 vol%), which streamlines syngas conditioning and increases cost-effectiveness. Two SEG process configurations for small-scale biomass-to-ammonia (∼45000 t of agricultural residues/year) were proposed: SEG process A, which produced low-carbon ammonia without air separation, and SEG process B, which employed an air separation unit to deliver carbon-negative ammonia by capturing CO2. The two processes were compared against a dual fluidized bed gasification (DFBG) process, which generated green ammonia without an air separation, like SEG process A. Of the three cases, SEG process B showed the lowest biomass (2.14 t biomass/t NH3) and water consumption (0.47 t H2O/t NH3) and avoided 2.8 t CO2/t NH3, making it carbon-negative. While the DFBG process and SEG process A had higher energy efficiencies, SEG process B posted the lowest net energy consumption (36.6 GJ/t NH3). Furthermore, SEG process B had the lowest ammonia production cost ($692/t NH3) and payback time (9.4 years), making it the most economically viable. Sensitivity analysis showed that favorable carbon credit policies could boost the economics of SEG process B to match large-scale plants.

Toward Low-Carbon Rice Production in China: Historical Changes, Driving Factors, and Mitigation Potential.

Under the "Double Carbon" target, the development of low-carbon agriculture requires a holistic comprehension of spatially and temporally explicit greenhouse gas (GHG) emissions associated with agricultural products. However, the lack of systematic evaluation at a fine scale presents considerable challenges in guiding localized strategies for mitigating GHG emissions from crop production. Here, we analyzed the county-level carbon footprint (CF) of China's rice production from 2007 to 2018 by coupling life cycle assessment and the DNDC model. Results revealed a significant annual increase of 74.3 kg CO2-eq ha-1 in the average farm-based CF (FCF), while it remained stable for the product-based CF (PCF). The CF exhibited considerable variations among counties, ranging from 2324 to 20,768 kg CO2-eq ha-1 for FCF and from 0.36 to 3.81 kg CO2-eq kg-1 for PCF in 2018. The spatiotemporal heterogeneities of FCF were predominantly influenced by field CH4 emissions, followed by diesel consumption and soil organic carbon sequestration. Scenario analysis elucidates that the national total GHG emissions from rice production could be significantly reduced through optimized irrigation (48.5%) and straw-based biogas production (18.0%). Moreover, integrating additional strategies (e.g., advanced crop management, optimized fertilization, and biodiesel application) could amplify the overall emission reduction to 76.7% while concurrently boosting the rice yield by 11.8%. Our county-level research provides valuable insights for the formulation of targeted GHG mitigation policies in rice production, thereby advancing the pursuit of carbon-neutral agricultural practices.

Research on enterprise production decision‐making considering consumer heterogeneity under carbon labeling system

AbstractThe article focuses on consumers with heterogeneous preferences for product carbon footprints under two carbon labeling systems: carbon reduction labels and carbon footprint labels. Using mathematical models, the study explores the optimal decision‐making behavior of enterprises under the carbon labeling system based on consumer utility theory at the enterprise level. It also investigates consumer surplus, environmental improvement, and social welfare under different production modes of the carbon reduction label and carbon footprint label systems at the societal level. The research findings are as follows: (1) At the level of economic benefits for enterprises, choosing to produce products with carbon reduction labels is more favorable when the investment costs for emission reduction are high, while choosing to produce products with carbon footprint labels is more favorable when the investment costs for emission reduction are low. The optimal prices of products under the two carbon labeling systems show opposite trends compared to the investment costs for emission reduction. (2) At the level of environmental benefits for enterprises, under the carbon reduction labeling system, whether through full production or a mixed production mode, enterprises are only willing to reduce the carbon footprint of products to the standard value. However, under the carbon footprint labeling system, especially in the mixed production mode, enterprises show a stronger willingness to overachieve in emission reduction target. (3) At the level of social benefits, compared to the situation under the carbon reduction labeling system, when the investment costs for emission reduction are low, the carbon footprint labeling system is more favorable in terms of consumer surplus and social welfare. However, this advantage gradually diminishes as the investment costs for emission reduction increase. (4) Excessive investment costs for emission reduction are detrimental to the implementation of both carbon reduction and carbon footprint labeling systems. The research conclusions suggest that companies should develop appropriate production strategies based on actual circumstances. Additionally, it is necessary for both the government and companies to reduce investment costs in emissions reductions by improving the system and optimizing emission reduction methods in order to better implement carbon labeling policies.

Spatiotemporal Trends of the Carbon Footprint of Sugar Production in China

Sugar is the main nutrient source of human beings and the basic raw material of the food industry. It is of great practical significance for China to find out the current situation and future trend of Greenhouse Gas (GHG) emissions from sugar production, and explore measures for reducing GHG emissions from sugar planting and processing. The IPCC GHG emissions accounting method is applied to analyze the carbon footprint of sugar production based on planting management and industrial development data, in which the GHG emissions per unit of sugar product are calculated and analyzed. According to Carbon Peak and Carbon Neutrality targets, the total GHG emissions of China's sugar industry in 2030 and 2060 are predicted and discussed. The results show that: (1) The average GHG emissions per unit yield of sugar show a downward trend from 2004 to 2021. The total GHG emissions of sugar production in China have reached 1319.9 × 104 t CO2eq in 2021, which has not yet reached its peak due to the growth of consumption demand. (2) The average GHG emissions per unit of Beet Sugar (1.477 tCO2eq/t) is higher than that of Cane Sugar (0.825 tCO2eq/t). It is more meaningful to enlarge the planting area of sugarcane than that of sugarbeet in the future. (3) Overall, in 2021 the GHG emissions of sugar production reached 0.91 tCO2eq/t in China, which would decline 15 %–87 % until 2030 and 2060. There is great potential for sugar production to reduce GHG emissions in the future.

Assessing the Carbon Footprint of Plastic Bottle Blow Mold Based on Product Life Cycle for Managing the Mold Industry’s Carbon Emission

Calculating the carbon footprint (CF) holds paramount importance in today’s world as it provides a tangible measure of our impact on the environment. In the corporate realm, businesses armed with CF data can optimize operations, reduce waste, and adopt greener technologies, leading to both environmental and economic benefits. In this study, carbon emissions—a significant global issue—are investigated through the lens of the ISO 14067-ISO Product Based Carbon Footprint (CF) standard, focusing on the operations of a mold company. The primary innovation lies in meticulously tracing every stage of plastic bottle blow mold production, the most prevalent product in the mold industry, from its raw material input to its final form as a mold in the factory. Subsequently, detailed calculations and analysis are conducted to quantify the carbon footprint associated with this process and its impact on the environment. The calculated CF for one ton of PBBM produced by Petka Mold Industry is presented. This study fills a critical gap in the literature by providing a holistic understanding of the carbon footprint of plastic bottle blow mold (PBBM) production, thereby offering valuable insights for managing carbon emissions and promoting sustainability within the mold industry. By integrating a life cycle product carbon footprint thinking into industrial practices, a greener, more sustainable future can be paved, mitigating the ecological footprint of the PBBM.

81 Effect of thymol on intake and digestion in beef cattle

Abstract Reducing enteric methanogenesis has been an area of focus and significance as methane emissions from cattle contribute to climate change and represent a loss of dietary-derived energy. Methane mitigation strategies have been widely researched, but most are limited in practical value due to associated diminishments in animal performance. One strategy, dietary supplementation of essential oils, has demonstrated variable reductions in enteric methane production in ruminants. The efficacy of using essential oils to reduce enteric methanogenesis likely varies due to inconsistent concentrations of bioactive components. Therefore, it is justified to investigate the effects of these individual bioactive components on methanogenesis and animal performance. Thymol, a terpene and main bioactive component in many essential oils, has effectively reduced methane production in vitro but in vivo data are limited. The objective of this study was to assess thymol fed at levels that correspond with effective in vitro doses on intake and digestion in beef steers consuming forage. This study was approved by the Texas State University IACUC (#8693). The project was a 4×4 Latin Square where four steers were provided one of four levels of thymol (0, 120, 240, and 480 mg thymol/kg forage intake) soaked on alfalfa cubes fed at 20% of the intake from the previous day, and ad libitum hay and water daily. Periods were 28-d with 8-d to adapt steers to treatments, 5-d to measure intake and digestion, 2-d to collect additional samples (i.e., ruminal microbiome and fat tissues), and a 14-d washout period for thymol depletion from the animal system. Diet, refusal, and fecal samples were analyzed for dry matter, organic matter, and fiber. Acid detergent insoluble ash was used to calculate total fecal production for digestibility estimates. Data were analyzed using the MIXED procedure in SAS 9.4. There was no effect of thymol dose on forage OMI (4.61 kg/d ± 0.31; P ≥ 0.48), total OMI (5.65 kg/d ± 0.38; P ≥ 0.44), or total digestible OMI (3.18 kg/d ± 0.18; P ≥ 0.26). Further, organic matter and neutral detergent fiber digestibility were not affected by treatment (56.70% ± 2.81, and 63.04% ± 2.49 respectively; P ≥ 0.14). These data indicate that thymol supplementation at doses that suppress in vitro methane production do not negatively impact intake and digestion in beef cattle. Future project activities include whole genome sequencing of rumen microbial communities to evaluate the impact of thymol on populations, with an emphasis on the methanogen archaea. These data have value for establishing a novel methane-mitigating feed additive to lower the carbon footprint of cattle production without sacrificing performance.

Process-based life cycle inventory framework for assessing the carbon footprint of products from complex production paths: Case of dual-phase automotive strip steel

The production paths of industrial products are usually complex, leading to difficulties and a large workload when conducting traditional process-based life cycle assessment (P-LCA). Existing studies on reducing LCA workload have focused mainly on simplifying the process or combining LCA with correlation methods. For complex production paths that cannot be simplified or changed, the methods have weak generality. To fill in these research gaps, a process-based life cycle inventory (P-LCI) framework for complex production paths is proposed. P-LCI contains accurate classification and definition methods for input, output and unit processes, and an interconnection model for calculating process coefficients according to the complexity of the linkages among processes is proposed. Based on the proposed framework, a case study of the dual-phase automotive strip steel (DP) production process is performed. The results show that the production of 1 kg of DP steel consumes 0.679 kg of molten steel from a basic oxygen furnace plant and 0.557 kg from the another. Coke plants produce the largest carbon footprint (CF) per unit of coke, which is 0.889–1.231 kgCO2e/kg-coke. For the cradle-to-gate lifecycle of DP steels, the BFP has the largest CF at 0.614 kgCO2e/kg-DP, accounting for 26.32%. Through the proposed P-LCI framework, unit processes can be clearly defined, and the interconnection model can be used as the basis for environmental impact analysis. When the production path changes, the model can be flexibly adjusted, and the workload of repeated model construction can be reduced.

Getting Support for Adoption of Climate‐Smart 4R Practices

AbstractNutrient management, particularly for nitrogen, plays an important role in improving the carbon footprint of crop production. Many programs have recently expanded their offerings or funding levels of incentives to farmers to adopt more climate‐smart nutrient management practices. These programs provide opportunities for crop advisers to accelerate adoption among their clients of 4R practices that reduce greenhouse gas emissions and support soil carbon sequestration. The intent of this article is to provide a broad description of the programs available and the practices most likely to be effective. Earn 1.5 CEUs in Nutrient Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.