Industrial Carbon Emissions Research Articles

Optimization and Modelling of the Physical and Mechanical Properties of Grass Fiber Reinforced with Slag-Based Composites Using Response Surface Methodology.

The construction industry's high energy consumption and carbon emissions negatively impact the ecological environment; large-scale construction projects consume much energy and emit a significant amount of CO2 into the atmosphere. Statistics show that 30% of energy loss and 40% of solid waste in the construction industry are generated during construction. Therefore, reducing emissions during construction has significant research potential and value. Many scholars have recently studied eco-friendly building materials to facilitate the use of high-carbon emission materials like cement. Adding fibers to composite materials has become a research hotspot among these studies. Although adding fibers to composite materials has many advantages, it mainly reduces the compressive strength of the composite material. This research used the response surface methodology (RSM) to optimize the raw material ratios and thus improve the performance of plant fiber composite materials. Single-factor experiments were conducted to analyze the effects of grass size, grass content, and quicklime content on the composite materials' compressive strength, flexural strength, and water absorption. The influencing factors and levels for the response surface experiment were determined based on the results of the single-factor analysis. Using the response surface methodology (RSM), a second-order polynomial regression model was established to analyze the interaction effects of the three factors on the composite materials' compressive strength, flexural strength, and water absorption rate. The optimal ratio was determined: the optimized options for grass size, grass content, and quicklime content are 2.0 mm, 8.2 g, and 38 g, respectively. The actual values of compressive strength, flexural strength, and water absorption rate of the composite materials made according to the predicted ratio are 11.425 MPa, 2.145 MPa, and 21.89%, respectively, with a relative error of 8% between the actual and predicted values. X-ray diffraction and scanning electron microscopy were also used to reveal the factors contributing to the relatively high strength of the optimized samples.

How Does Digital Inclusive Finance Policy Affect the Carbon Emission Intensity of Industrial Land in the Yangtze River Economic Belt of China? Evidence from Intermediary and Threshold Effects

Digital inclusive finance (DIF) is a strategic tool that fosters the green transformation of the industrial economy. Based on the data from the 11 provinces and municipalities in the Yangtze River Economic Belt of China between 2012 and 2021, This paper utilizes the Tobit, intermediary effect, and threshold effect models to empirically study the impact of DIF on the industrial land carbon emission intensity (ILCEI). This paper reaches the following conclusions: (1) The ILCEI in the region revealed a downward trend during the study period. There are substantial differences in carbon ILCEI; higher upstream and lower downstream. The average ILCEI in the lower reach provinces is 0.5829 ton/m2 during the research period, while that in the upper reach region is 1.0104 ton/m2. (2) DIF has a significantly inhibitory effect on the ILCEI; this effect has nonlinear characteristics. The impact of DIF on ILCEI exhibits a marginally diminishing trend as the industrial land economic agglomeration degree improves. (3) Regarding the transmission mechanism, the level of industrial R&D investment plays a primary intermediary role in the impact of DIF on ILCEI. (4) Concerning control variables, foreign investment dependence and trade contribute significantly to inhibiting ILCEI. Lastly, this paper proposes a series of measures to promote DIF to fully utilize the emission reduction effect. The research outcomes have substantial implications for the sustainable development of industrial land.

Coupling and Coordinated Development of Carbon Emission Efficiency in Industrial Enterprises and the Digital Economy: Empirical Evidence from Anhui, China

To delve into the interrelationship between the green transformation of industry and the economy’s high-quality development, to promote the coordinated development of industrial carbon emission efficiency and digital economy, to expand the scope and research ideas related to economic and social sustainable development, and to provide scientific reference for the low-carbon sustainable development of regional economy, this article introduced a data-centric methodology for evaluating the collaborative advancement of both industrial enterprises’ carbon emission efficiency and the digital economy. To accurately gauge the carbon footprint of industrial enterprises, models focusing on carbon emissions as well as carbon emission intensity were employed. To enhance the precision of evaluation outcomes and mitigate biases stemming from subjective weighting factors, we employed the entropy weight method to objectively assign weights to each indicator. Furthermore, the super-efficient slack-based model (SBM) can solve the problem that the conclusions are biased, due to the different radial. Subsequently, a carbon-emission efficiency slack-based measure model, and models for coupling degree and coupling-coordination degree were formulated. Anhui, as a central province in China, is also an important province in the Yangtze River Delta integration development. Coordinated development of its carbon emission efficiency and digital economy has important implications for the sustainable economy advancements of other regions in China, and even other countries or regions in the world. Therefore, Anhui was selected to be the empirical research sample. The results showed that the comprehensive levels of these two systems followed an increasing trend, while the digital economy lagged. Their coupling degree fluctuated and reached its highest point in 2021, whereas their coupling-coordination degree increased, showing high coupling and low coordination overall. This study proposes specific countermeasures and suggestions for the relevant decision-makers.

Quantifying environmental impact: carbon emissions analysis of cut and fill work in construction

The construction industry plays a pivotal role in global development, but it also significantly contributes to carbon emissions, necessitating urgent measures to mitigate its environmental impact. The main objective of this research is to analyse and estimate the carbon emissions resulting from cut and fill work in construction projects. This research conducted three comprehensive case studies focusing on heavy equipment excavation, material transport, material spreading, and compaction stages in the construction industry to analyse carbon emissions. The findings reveal that material transport emerges as a prominent source of CO2 emissions within the construction life cycle. This underscores the urgent need for transformative measures to optimize transportation logistics and adopt eco-friendly alternatives, such as electric or hybrid vehicles, for material transport. Additionally, the study highlights the importance of integrating intermodal transportation options to maximize efficiency while minimizing emissions during material movement. The research emphasizes that mitigating carbon emissions in the construction industry requires a comprehensive approach encompassing technological advancements, logistical optimization, and the adoption of sustainable practices. By embracing the strategies highlighted in this study, construction projects can significantly contribute to the global fight against climate change and align with international efforts to achieve a more sustainable future. The insights provided by this research underscore the imperative for collaboration among stakeholders to drive meaningful change and foster a more sustainable and environmentally conscious construction industry.

Analysis on the spatial correlation network and driving factors of carbon emissions in China's logistics industry

Promoting the green development of the logistics industry has become a focal point of attention in China. This study combines an improved gravity model and social network analysis method, focusing on the nineteen provinces of the Yangtze Economic Belt and Yellow River Basin. It constructs a spatial correlation network of carbon emissions in the logistics industry from 2010 to 2021, exploring its formation mechanism and spatial evolution characteristics. The study utilizes a quadratic assignment procedure model to investigate internal driving factors. Building upon this, the study employs an improved STIRPAT model to predict the emission reduction path of the future logistics industry. Results are as follows: (1) Carbon consumption is most pronounced in Shandong, Jiangsu, and Shanghai. The carbon emission shows the characteristics of larger downstream; (2) The bridges of carbon emission-related networks gradually shift from Shandong to Shanxi, Anhui, and Sichuan. Carbon emissions in each sector and spatial spillover effects exhibit dynamic correlations and interactive influences; (3) Energy intensity, freight volume, and the spatial correlation network of the logistics industry are highly correlated; (4) The overall carbon emissions from the logistics industry show a decreasing trend in the future. Anhui and Shaanxi provinces will have high carbon emissions in 2035. The conclusions aim to provide policy suggestions for the region's low-carbon transformation.

Study on Interprovincial Equity and the Decoupling of Carbon Emissions in the Construction Industry—A Case Study in China

Interprovincial disparities in carbon emissions from the construction industry (CECI) are an important challenge for future emissions reductions. Based on the CECI data of 30 provinces in China from 2010 to 2020, the interprovincial equity and decoupling of CECI were examined in this study. The conclusions are as follows: (1): The main CECI growth regions were the eastern Bohai Rim region and the Pearl River Delta region. Heilongjiang basically achieved a CECI carbon peak in 2016. (2) The three northeastern provinces and western provinces were the main high–high and low–low aggregation areas, respectively. The greatest degree of inequality was found in the western provinces. The inequality between the eastern and western areas was the largest, while the inequality between the central and western areas was the smallest. The inequality in CECI in the north–south region decreased year by year. (3) The decoupling status of Shandong and some western provinces has significantly worsened, while the decoupling status of Sichuan, Yunnan, and some eastern developed provinces has been improving. These conclusions will contribute to the improvement of regional emission reduction strategies.

Decoupling and decomposition analysis of industrial carbon emissions and economic growth in China from a dynamic perspective

Decoupling and decomposition analysis of industrial carbon emissions and economic growth in China from a dynamic perspective

The Impact of Global Value Chain Embedment on Energy Conservation and Emissions Reduction:Theory and Empirical Evidence

Abstract An in-depth investigation into the effect of embedment in global value chain (GVC) on energy conservation and emissions reduction is of great significance for scientifically assessing the environmental impact of GVC participation, and promoting high-quality development in China. This paper incorporates GVC embedment, energy consumption and carbon emissions into the same analysis framework for the first time. Based on the WIOD database, this paper theoretically and empirically examines the impact and mechanism of global value chain embeddedness on carbon emission reduction from two dimensions: energy consumption intensity and energy consumption structure. The study found that GVC embedment significantly reduced the industry’s carbon emission intensity; developing economies’ embedment in GVC helped reduce their carbon emission intensity, while the effect was not obvious in developed economies. GVC embedment had a significant inhibitory effect on the carbon emissions in both upstream and downstream industries, but not conducive to carbon reduction of low-tech manufacturing. The mechanism test shows that the GVC embedment not only exhibits the dual effects of energy conservation and emissions reduction, but also has a significant impact on carbon emissions by reducing the energy consumption intensity and improving the energy consumption structure.

Analysis of the Measurement of Transportation Carbon Emissions and the Emission Reduction Path in the Yangtze River Economic Belt under the Background of “Dual Carbon” Goals

Carbon emissions from the Yangtze River Economic Belt are an important element of China’s carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country’s overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios.

O-175 Ethical practices and policies for ART carbon reduction

Abstract Background The carbon emissions of global health care activities make up 4-5% of total world emissions, placing the health care industry on par with the food sector. Health care contributes to climate change and climate change health hazards. Safe amounts of carbon in the atmosphere have been exceeded—in part because of medical lifestyles in the industrialized world. A significant proportion of health care carbon comes from pharmaceuticals and clinical services in the developed world, including reproductive technologies. Since 1978, approximately 12 million babies have been born through IVF alone. Problem statement Reproductive technologies have an exceptional impact on the environment as they 1. expend carbon in the medical process, 2. increase population growth in mostly high-carbon countries, 3. impact earth’s carrying capacity, and 4. create a carbon legacy. This would not necessarily be ethically problematic, but in a climate crisis carbon emissions must be reduced in all areas of life. Objectives This presentation by an ethicist (PhD) will: 1. Highlight aspects of environmental ethics for reproductive technologies 2. Offer practices and policies to make reproductive technologies more sustainable. Takeaways • Prevention of infertility fits within basic health care. • Carbon emissions from reproductive technologies can be reduced by life cycle assessments (LCA) of the procedures and components. • Clinical evidence can inform ethical policies to reduce the number and kind of reproductive technologies, thereby lowering fertility industry carbon emissions. • New scientific and technological developments in reproduction must consider sustainability proactively, not reactively, thus putting ethics in the pipeline of reproductive medicine. Further Reading Bhopal A, and Norheim O. Priority setting and net zero healthcare: how much health can a tonne of carbon buy?. BMJ 2021; 375:e067199. Pichler, P.-P. et al., “International Comparison of Health Care Carbon Footprints,” Environmental Research Letters 14, no. 6 (2019): 064004. Richie, Cristina. Environmental Ethics and Medical Reproduction (Oxford University Press, 2024.

The Impact and Mechanism behind the Effect of a Digital Economy on Industrial Carbon Emission Reduction

The Impact and Mechanism behind the Effect of a Digital Economy on Industrial Carbon Emission Reduction

Promoting Decarbonization in China: Revealing the Impact of Various Energy Policies on the Power Sector Based on a Coupled Model

The carbon emissions of the power industry account for over 50% of China’s total carbon emissions, so achieving carbon peak and carbon neutrality in the power sector is crucial. This study aims to simulate the impacts of three energy policies—carbon constraints, the development of a high proportion of renewable energy, and carbon trading—on China’s energy transition, economic development, and the power sector’s energy mix. Through the construction of a dynamic computable general equilibrium (CGE) model for China and its integration with the SWITCH-China electricity model, the impact of diverse energy policies on China’s energy transition, economic progress, and the power mix within the electricity industry has been simulated. The integration of the SWITCH-China model can address the limitations of the CGE model in providing a detailed understanding of the specific intricacies of the electricity sector. The results indicate that increasing the stringency of carbon restrictions compels a reduction in fossil energy use, controlling the output of coal-fired power units, and thereby reducing carbon emissions. The development of a high proportion of renewable energy enhances the cleanliness of the power sector’s generation structure, further promoting the national energy transition. Implementing a carbon trading policy, where the entire industry shares the burden of carbon reduction costs, can effectively mitigate the economic losses of the power sector. Finally, the policies to further enhance the implementation of carbon trading policies, strengthen effective governmental regulation, and escalate the deployment of renewable energy sources are recommended.

Consequences of increasing greenhouse gas emissions: case study on the impact of the food industry

The global carbon footprint has increased to frightening heights due to rising greenhouse gas emissions, mainly from the energy and industrial sectors, which include the food industry. This case study examines how the industry's carbon emissions have changed over time, highlighting the sector's major environmental impact and the pressing need to implement decarbonization plans. The particularity of the study lies in the analysis of the crucial role that emissions from the food industry play in global emissions. An overview of the global industrial carbon footprint was created through an analysis of carbon emissions data from multiple sources, with a particular focus on the food industry. Since the Industrial Revolution, carbon dioxide emissions have increased dramatically worldwide, reaching a record high of 36.3 billion tons in 2019. With around 23% of global emissions coming from industry, the energy sector is the largest emitter. The main cause of emissions is the use of fossil fuels in heavy industries such as steelmaking, cement, and chemicals; the two largest emitters are China and the United States. Achieving the goals outlined in the Paris Agreement and halting climate change requires reducing carbon emissions from the food industry. The adoption of low-carbon technologies, increased energy efficiency and a shift to cleaner energy sources are essential remedies. The industrial sector needs to decarbonize faster, and this can only be achieved through international cooperation and strong government regulations.

Digital economy's role in shaping carbon emissions in the construction field: Insights from Chinese cities

Achieving net-zero greenhouse gas emissions in the construction sector is essential to sustainable development policy. Previous studies have ignored the impact of the digital economy on carbon emissions in the construction industry. Using relevant city-level data from China from 2011 to 2021 and employing ArcGIS and Stata software, this study examines the current status of carbon emissions from the construction industry and investigates the impact of the digital economy on these emissions. The findings reveal that (1) from 2011 to 2021, carbon emissions of the construction industry have a pattern of decreasing-increasing-decreasing-increasing across the country. There is an increasing concentration of areas with high and relatively high carbon discharges in Heilongjiang, Jilin, Ningxia, Inner Mongolia, Shanxi, Guangxi, and Guizhou. (2) The standard deviation ellipse indicates the core area of carbon emissions in China's construction industry is moving northeast and becoming more decentralized. (3) Through a series of robustness tests, the digital economy has been proven to effectively reduce carbon emissions from the construction sector in municipal areas. (4) In severely cold regions, mild regions, and high-population-density cities, the digital economy reduces building sector's carbon output. However, it stimulates carbon emissions in the hot summer and cold winter regions. (5) Mechanism tests show that the digital economy reduces China's urban construction carbon emissions by fostering technological progress and green innovation. Urban resilience further strengthens the contribution of the digital economy to reducing carbon discharges in the urban construction sector of China. This article presents empirical evidence demonstrating how the digital economy empowers the construction industry to curtail emissions.

Prediction of Carbon Emissions Level in China’s Logistics Industry Based on the PSO-SVR Model

Adjusting the energy structure of various industries is crucial for achieving China’s carbon peak and carbon neutrality goals. Given the significant proportion of carbon emissions from the logistics industry in the tertiary sector, the research on predicting the carbon emissions of the logistics industry is of great significance for China to achieve its “Dual carbon” target. In this paper, the gray relational analysis (GRA) methodology is adopted to screen the influencing factors of carbon emissions in the logistics industry firstly. Then, the particle swarm optimization (PSO) algorithm was used to optimize the penalty coefficientand kernel function range parameter of the support vector regression (SVR) model (i.e. PSO- SVR model). The data from 2000 to 2021 regarding carbon emissions and related influencing factors in China’s logistics industry are analyzed, and the mean absolute percentage error (MAPE) of the PSO-SVR model is 0.82%, which shows that the proposed PSO-SVR model in this paper is effective. Finally, instructive suggestions are provided for China to achieve the “Dual Carbon” goal and upgrading of the logistics industry.

Environmental Regulation, Industrial Structure and Low-Carbon Development

<p>In this paper, the provincial panel data of china from the year 2006 to 2019 are used to analyze the association among environmental regulations, industrial structure od industries and low-carbon development. The results show that regional industrial CO2 emissions in China's east, center, and west were greatly decreased by environmental restrictions. The most significant deterrent to carbon emissions in the central region was, notably, environmental regulatory measures. By encouraging improvements in industrial structure and increasing its efficiency, the study shows that these rules helped to lower industrial carbon emissions. The examination of the sub-sample mechanism reveals significant regional variations: an advanced industrial structure was a major force behind low-carbon development in the western region, whereas high-efficiency industrial structures were critical in the eastern region. Through structural changes in the business, environmental restrictions can effectively promote low-carbon economic growth, as this study highlights. Across a range of control factors, environmental regulation considerably decreased regional industrial carbon emissions by about 0.196 to 0.033. Trade openness, urbanization, and the development of human capital all helped to reduce carbon emissions by roughly 1.057 to 4.104. The efficacy of regulatory tools was verified by endogeneity tests, which yielded coefficients varying between -0.891 and -0.156 for distinct factors. The results offering actual proof of the varying effects of environmental laws in various geographical areas and highlight the necessity of specialized policy strategies to promote sustainable development.</p>

A knowledge-driven memetic algorithm for the energy-efficient distributed homogeneous flow shop scheduling problem

The reduction of carbon emissions in the manufacturing industry holds significant importance in achieving the national ”double carbon” target. Ensuring energy efficiency is a crucial factor to be incorporated into future generation manufacturing systems. In this study, energy consumption is considered in the distributed homogeneous flow shop scheduling problem (DHFSSP). A knowledge-driven memetic algorithm (KDMA) is proposed to address the energy-efficient DHFSSP (EEDHFSSP). KDMA incorporates a collaborative initialization strategy to generate high-quality initial populations. Furthermore, several algorithmic improvements including update strategy, local search strategy, and carbon reduction strategy are employed to improve the search performance of the algorithm. The effectiveness of KDMA in solving EEDHFSSP is verified through extensive simulation experiments. KDMA outperforms many state-of-the-art algorithms across various evaluation aspects.

Emission Reduction Effects of China’s National Carbon Market: Evidence Based on the Power Sector

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China’s national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries.

Investigating the driving factors of carbon emissions in China's transportation industry from a structural adjustment perspective

Promoting the transport industry to achieve a carbon peak and controlling carbon emissions in various regions of China through structural adjustment are important means to significantly reduce CO2 emissions. To explore the drivers of carbon emissions from China's transportation sector from 2006 to 2021. And constructs the IPAT-S (IPAT model considering structural adjustment) model, the structural equation is combined to explore the carbon emission reduction path of China's transportation industry from the perspective of structural adjustment. The results show that the structural adjustment is beneficial to alleviate the pressure of emission reduction, carbon emissions from the national transportation sector show a pattern of “low in the north and high in the south”, with the trend gradually shifting to the central region, and the spatial structural effect on carbon emissions has been significantly strengthened, the industrial structure, energy structure and transportation structure still contribute to the carbon emissions of the transportation industry. From the regional level, there are some differences in the impact of structural adjustment on carbon emission reduction in different regions, but optimizing the energy structure will be conducive to carbon emission reduction. In the case of the Northeast region, the energy consumption structure, industrial structure, and transportation structure do not inhibit carbon emissions, and the structural emission reduction in the Central region has begun to bear fruit. The structural adjustment in the eastern and western regions has yet to be improved, which will also provide the government with policy recommendations for structural emission reduction based on regional differentiation.

Research on copper flow and environmental load in China's new infrastructure industry for carbon neutrality

With the rapid development of new infrastructure in China, the demand for copper has increased significantly. In 2021, copper consumption in this sector accounted for 9.1% of China's total consumption, becoming a new driving force for copper demand. This study analyzed copper flow characteristics and primary driving factors in China's new infrastructure sectors using the material flow analysis method, quantified the environmental loads of the metabolic processes, and predicted copper demand in the new infrastructure sectors by 2030 through scenario analysis. The primary conclusions drawn are as follows: In 2021, copper consumption in new infrastructure sectors was 1,225,700 tons, with the rail transportation sector accounting for 59.6% and the artificial intelligence sector accounting for 0.6%. The rail transportation sector had the largest total environmental load, with carbon emissions of approximately 3,513,372 tons. From the perspective of tons of copper products, the 5G sector had the highest environmental load, while the big data centers had the lowest. In the seven sectors of new infrastructure, the environmental load contribution rates across the four stages showed little variation, with their proportions being 49.0, 29.8, 15.8, and 5.4%, respectively. Recycling of discarded copper products can effectively reduce industrial energy consumption and carbon emissions. Under the three scenarios set in this study, the copper demand in the new infrastructure sector by 2030 will be 3.856, 3.233, and 2.625 million tons, respectively. Using wind energy to replace coal in copper production can reduce carbon emissions by approximately 43.2%.