A three-stage parameter prediction approach for low-carbon gear hobbing

Does new energy consumption conducive to controlling fossil energy consumption and carbon emissions?-Evidence from China

Bridges are special infrastructures that emit large amounts of carbon dioxide from construction. Attention should be given to the carbon cost generated by the bridge, which includes its direct economic cost; the carbon cost is the largest driving force encouraging the enterprise to implement carbon emission reduction measures. In this study, the life cycle assessment (LCA) method is applied to carbon emissions in the bridge construction stage, which include emissions from material production, transportation and on-site construction; then, a carbon emission calculation model for the construction stage is established. Next, the carbon cost calculation model for the bridge in the construction stage is determined by combining the carbon pricing mechanisms of carbon emission taxing and trading to monetize carbon emissions. Finally, by taking a bridge in Beijing as an example, the carbon emissions in the bridge construction stage are calculated, and the carbon cost is calculated. The results show that carbon emission monetization is beneficial for clarifying the environmental impact of bridge construction; these calculations should be included in cost accounting.

Debates on carbon costs and carbon pricing to accelerate the reduction of greenhouse gas (GHG) emissions are emerging as cities develop local policies and programs to achieve carbon neutrality. This paper focuses on how cities formulate economic instruments and adopt carbon pricing experiments to support their climate objectives. Extensive literature is available on science-policymaking interface Integrated Assessment Models (IAM) and on the two mainstream approaches of carbon cost formulation—Social Cost of Carbon (SCC) and Marginal Abatement Cost (MAC). Although, the literature on how governments develop climate policy instruments, particularly towards a local carbon cost, is recent. We start by reviewing these essential concepts and tools for carbon cost formulation. We then critically review a set of local carbon pricing experiments, totaling fourteen international cities, and confirm a great demand for scientifically robust, verifiable, and transferable carbon cost methodologies at the local level. We thus propose an approach to assess the short-term technology cost of CO2 emission reduction in the mobility sector in Matosinhos municipality, Portugal. Our approach shows that a carbon cost methodology at the local level with robust, verifiable, and transferable results is possible. We advocate for a methodological advance to estimate versatile CO2 prices suitable for local conditions.

Are energy consumption and carbon emission caused by Bitcoin? A novel time-varying technique

Low carbon research has currently become the most discussed environmental issue. Current comprehensive evaluation methods for low carbon consider carbon emission, cost, process parameters, and resource utilization, but the realization of low carbon may lead to cost fluctuations and functional changes and lack consideration of product functional requirements. Hence, this paper developed a multidimensional evaluation method for low-carbon research based on the association among three dimensions, namely, carbon emission, cost, and function. This multidimensional evaluation method was named life cycle carbon efficiency (LCCE), which is defined as the ratio between the value in the life cycle and the carbon emissions generated. The LCCE model was established, and then carbon emission calculation, cost assessment, and function quantification of the life cycle were performed according to the three dimensions. Case study and sensitivity analysis verified the feasibility of the proposed method. The method had comprehensive and accurate evaluation results, which provided theoretical support and optimized the low-carbon design.

Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This article highlights the potential conflict between electricity prices and carbon emissions and the resulting tradeoffs in carbon-aware and cost-aware load scheduling. To address this tradeoff, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.

Based on the estimation of carbon cost from afforestation in project boundary and carbon leakage out of boundary in the construction period of "Grain for Green" Program (GGP) (2000-2010), the annual variance and composition of the carbon cost and carbon leakage, as well as characters of variance of net carbon sequestration were analyzed for GGP and respective program regions. Results showed that the carbon costs in northwest region, southwest region, northeast region, north region and central south and east region were 3.38, 3.64, 1.03, 1.66 and 4.38 Tg C, respectively, totaling 14.09 Tg C. Meanwhile the carbon leakages of the above regions were 21.33, 4.60, 5.50, 1.32 and 3.78 Tg C, respectively, and 36.53 Tg C in total. The composition characters of the carbon costs of the GGP and the respective regions were similar. Carbon emissions from afforestation were the largest carbon cost, and afforestation on converted farmland was the main carbon emission source. Accordingly, among the materials consumed, fertilizer brought about the largest carbon cost, followed by building materials, while carbon emissions from fuels, irrigation, herbicides and pesticides only accounted for about 10% for respective regions. The carbon cost and carbon leakage of the GGP were 50.62 Tg C in total, which counteracted 19.9% of the sequestered carbon in the program. In northwest region, southwest region, northeast region, north region and central south and east region, carbon emissions (including cost and leakage) accounted for 38.9%, 10.4%, 26.1%, 8.9% and 15.5% of the carbon sequestration, respectively. The net carbon sequestration of the GGP was 203.50 Tg C with an annual average of 18.50 Tg C·a-1. The carbon cost and leakage offset a minor part of the carbon sequestration of the GGP. Therefore, the GGP contributed significantly to greenhouse gas mitigation in China as well as global climate warming mitigation. Adopting precision fertilization in economic forest afforestation and supplying alternative livelihoods to farmers in the program could be the potential measures to reduce carbon cost and carbon leakage.

After more than two decades of negotiation, the China–Russia gas deal represents a new era of energy cooperation between China and Russia. In total, this is a win–win deal for both sides. For China, the deal will decrease energy consumption and carbon emission but will not significantly influence air quality; for Russia, it will provide a new market for its gas resources. In this study, we calculated the energy consumption, carbon emission, and particulate matter pollution (PM2.5 and PM10) in China in 2020, 2030, 2040, and 2050 under four IPCC representative concentration pathways (RCPs 8.5, 6.0, 4.5, and 2.6). We found that energy consumption and carbon emission decreased under the gas deal in RCPs 8.5, 6.0, and 4.5, although the rate of decrease slowed over time; however, in RCP 2.6, the rate of decrease of energy consumption and emission increased over time. PM2.5 and PM10 emission showed similar trends but with increasing rate, although the gas deal would mitigate air pollution in the short term. Although China’s government hopes to reduce carbon and pollutant emission under the deal, our results suggest that additional mitigation measures will be necessary to achieve this goal. Nonetheless, the reduction in carbon emission suggests that the China–Russia gas deal provides a model that other countries can follow to slow climate change.

Machine tools constitute the backbone of the industrial sector, representing the largest global inventory of equipment. The carbon emissions resulting from the production of each machine tool merit attention. Effective management of carbon emissions in the machine tool manufacturing process is crucial. This paper introduces a novel method for early carbon emission warnings in the machine tool manufacturing process, utilizing an adaptive dynamic exponentially weighted moving average (EWMA) approach. This method addresses the challenges in identifying and monitoring abnormal carbon emissions, emerging from uncertainties and dynamic correlations. Utilizing dynamic sampling techniques and adaptive principles, this method constructs an adaptive dynamic EWMA control chart. The EWMA control chart incorporates a multi-objective optimization design model, concentrating on carbon emissions in the machine tool manufacturing process, and incorporates statistical, economic, and environmental objectives. To mitigate slow convergence rates and enhance optimization accuracy in complex control chart multi-objective optimization algorithms, this study proposes an enhanced Harris hawks optimization (HHO) algorithm as the solving algorithm. Finally, the application of this method is demonstrated through the monitoring of carbon emissions in the manufacturing process of a five-axis machine tool (EOC), as a case study. The results validate the method's rapid responsiveness to abnormal carbon emissions, providing alerts. This further confirms the efficacy and feasibility of the proposed approach. Ultimately, this approach offers a viable strategy for fostering environmentally conscious and high-quality growth in the machine tool industry.

Compared to general public and residential buildings, large public buildings are often difficult to construct and have a long construction period, creating greater construction energy consumption and carbon emissions on the one hand, while generating a large amount and many types of difficult-to-track process data on the other. As such, it is difficult to measure carbon emissions and analyze various influencing factors. By realizing the simple calculation of energy consumption and carbon emissions, as well as discerning the degree of influence of various factors based on the results of influencing factors research, it is of considerable practical significance to propose energy savings and emission reductions in a targeted manner. In view of the above, this work aimed to establish a more practical calculation method to measure energy consumption and carbon emissions in the construction of large public buildings, as well as to identify the multiple influencing factors related to energy consumption and carbon emissions during the construction process. To demonstrate the practicality of our approach, quantitative calculations are carried out for a new terminal building in a certain place and from the perspective of sustainable urban construction; thus, the driving factors of the traditional STIRPAT model are extended to seven. Based on the calculation results, a modified STIRPAT model is used to analyze the comparative study of impact factors, such as population and construction machinery performance, on energy consumption and carbon emission intensity. The results show the following: (1) The energy consumption value per square meter of this terminal building is 3.43 kgce/m2, and the average carbon emission per square meter is about 13.88 kgCO2/m2, which is much larger than the national average of 6.96 kgCO2/m2, and (2) the type of energy used in the construction process has the greatest degree of influence on energy consumption and carbon emission, and the local GDP, population factor, construction machinery performance specifications, and shift usage also show a positive correlation with the growth of total energy consumption and carbon emissions. Moreover, while the government’s continuous investment in energy conservation and environmental protection has reduced the total energy consumption and carbon emissions in construction, there is still considerable room for improvement. Finally, according to the results, we provide theoretical references and constructive suggestions for the low-carbon construction of large public buildings in the construction stage. Thus, the results of our study will allow policy makers to formulate appropriate policies.

Purpose – The current study focuses on determining the carbon cost of a company which operates in iron and steel sector within the scope of cost accounting. As a result of approval of Kyoto Protocol by several countries, carbon focused inquires such as; carbon trade, carbon tax, investing in low carbon technologies, decreasing carbon emission and calculation of carbon cost have been essential issues that companies must concentrate on. Within this context, “Carbon Accounting” which is considered as a new concept has increasingly been significiant for the companies. Design/methodology/approach – In this study, case study method were used in a company which operates in iron and steel sector for carbon accounting. By means of this case study, first, company’s existing production and accounting systems were examined then carbon emissions, carbon footprint and share of carbon emissions in total production cost were calculated for 2016 and 2017 years. Findings – By means of this case study, emissions from the process and combustion were determined. Emissions from the process were examined by total value ,not detailed sub group, and emissions from combustion were composed of coal and natural gas. Mass balance method has been used by company to determine carbon foot print and it was determined that carbon footprint is 4,78 ton CO2 emission for year 2016 but 4,22 ton CO2 emission for year 2017. Beside, it was calculated that unit carbon cost is 128,04 TL/ton for year 2016 but 117,95 TL/ton for year 2017. Additionally, in this company emission cost were comprised of % 99 of total environmental cost for 2016 and 2017 years. However the percentage of carbon emission cost in unit production cost was approximately % 9 for year 2016 while this percentage was decreased to approximately % 8 for year 2017 in this company. Discussion – By this case study which was performed in a company operating in iron and steel sector it was explored that carbon foot print and unit carbon emission cost decreases and also the percentage of unit carbon cost in unit production cost decreases in 2016-2017. Beside, carbon cost constitute a significiant part of environmental cost. Therefore determining, recording, classificiation and reporting of carbon cost are crucial for companies. This study may be a referance for companies and another studies to determine carbon cost.

The Beijing–Tianjin–Hebei region (BTH) is a key area with large carbon emissions in China and a demonstration area for renewable energy development, facing the dual test of energy structure transformation and the achievement of carbon peak and neutrality goals. This study analyzes the main influencing factors of carbon emissions based on Kaya’s identity, establishes a socio-economic-energy-carbon emission coupled with system dynamics (SD) model, and designs five scenarios to predict and compare the future trends of energy consumption, renewable energy development and carbon emissions in BTH, respectively. The results show that (1) under the baseline scenario, energy carbon emissions in BTH will peak around 2034, and the intermediate development scenario, the transition development scenario and the sustainable development scenario all show that the region can achieve the emission peak target around 2030. (2) The renewable energy output value of BTH will reach CNY 486.46 billion in 2050 under the baseline scenario, and the share of renewable energy consumption will exceed 50% under the sustainable development scenario. (3) Increasing energy tax regulation and scientific and technological investment and adopting more stringent policy constraints can guarantee the lowest emission intensity while maintaining the current social and economic development level. This study predicts the development of a renewable energy industry and carbon emissions in BTH under different scenarios and provides policy recommendations for the future energy transition in the region.

To develop a low-carbon construction model for bituminous pavement construction, this study divides the fieldwork construction of bituminous pavement into aggregate stacking, aggregate supply, and other stages. This study also reviews a list of previous works that investigate energy consumption during bituminous pavement construction and proposes a quantitative method for CO2 emissions. Based on this method, the proportion of carbon emissions in each stage is analyzed, and the weight coefficient of carbon emissions is calculated. An analytic hierarchy process is used to establish the judgment matrix within the system of bituminous pavement construction, which in turn facilitates the calculation of the weight coefficient in each stage. Moreover, the stages of aggregate heating, bitumen heating, and bituminous mixture mixing are identified as the key stages in quantifying the carbon emissions. The carbon emissions in these three stages account for approximately 64.19%, 14.56%, and 14.02% of the total carbon emissions, respectively. Following the energy evaluation of the key stages, this study proposes a low-carbon building technology scheme that considers both emission reduction and economic benefits. Through the two low-carbon reduction projects of changing the type of energy and reducing the water content, the carbon emissions and costs of bituminous pavement construction are significantly reduced. The proposed energy-saving and emission reduction scheme therefore provides a theoretical basis and technical support for the low-carbon development of bituminous pavement construction.

Hierarchical Harris hawks optimizer for feature selection

The use of bio-based insulations in buildings serves several purposes, including reducing energy consumption and carbon emissions. Considering the many factors that determine the decision to use these insulations, this paper aims to analyse the financial and carbon cost and carbon intensity impacts of different bio-based insulation materials. Through comparing the carbon intensity of the insulations after performing a Life-cycle assessment (A-C); Global warming potential (incl.+A2), followed by calculating the financial and carbon cost per functional unit. This comparison included insulations based on cellulose, wood fibre, wood wool, cork, straw, hemp, jute, sheep wool, reeds, cotton, paper wool, and prairie grass among others. The results show that cellulose had lower Carbon intensity impacts (0.38-23.95 kgCO2e) and moderate financial and carbon cost (avg.19 €/m2) in most countries produced in. Whilst Wood wool presented the highest carbon intensity (10.40-111.60 kg CO2e) in the countries where it was produced. The higher carbon intensity is mostly attributed to the use of inorganic fire retardants and binders. The need to balance the lowest carbon intensity of the options with relatively low financial cost means that cellulose is the most efficient alternative followed by wood fibre, and wood wool the least eff icient. A further comprehensive understanding of the environmental and economic impacts of different insulation materials helps stakeholders make sustainable decisions. Hence, it may lead to improved insulation performance to ensure diversity and competitiveness.