High Energy-consuming Industries Research Articles

Low-carbon scheduling of electricity consumption in wastewater treatment plant by using photovoltaic system

Sewage treatment as a high energy consumption industry, its electricity consumption accounts for 3 % of the total electricity consumption of society. That means significant greenhouse gas emissions. In the context of China's goal of “reaching carbon peak by 2030 and achieving carbon neutrality by 2060”, reducing the energy consumption of wastewater treatment systems has emerged as an important issue in recent years. In this paper, the GPS-X simulation software was employed to conduct a simulation study of a modified Anoxic-Aerobic-Oxic wastewater treatment plant (WWTP) in Wuhan, and the response surface methodology (RSM) was utilized to ascertain the interactive effects of DO, IRF, ERR, and SD on the effluent quality, thereby identifying the operational parameters that minimize energy consumption while maintaining satisfactory effluent quality. Additionally, the PVsyst software was employed to design the solar power generation system of the WWTP and analyze its power generation potential. On this basis, through the coupling of photovoltaic power, electricity load, time-of-use pricing, and the water quality simulation model, and taking the WWTP data in September as a case study, the electricity usage strategies under various illumination conditions were formulated. The aim is to maximize the use of photovoltaic power to reduce the cost and carbon emissions of the WWTP. The results show that the optimal combination of operational parameters, including an external reflux ratio of 0.3, the internal recycle flow of 50,000 m3/d, and the sludge discharge of 448 m3/d, resulted in a reduction in power of 208.5 kW, and after the combination optimization of operational parameters and electricity utilization, the operation cost of the WWTP in September was reduced by 40 % ∼ 60 %, and the carbon emission attributable to electricity was reduced by 30 % ∼ 50 %.

Energy intensity constraints and corporate investment strategies: Evidence from Chinese listed enterprises

This study theoretically analyzes and empirically tests the impact and mechanism of energy intensity constraints on corporate investment strategies. The results find that energy intensity constraints significantly increase corporate green investment, particularly in front-prevention investment. Heterogeneity analysis indicates that the optimization effect of energy intensity constraints on corporate investment strategies is stronger in state-owned enterprises and high energy-consuming industries. Mechanism analysis reveals that energy intensity constraints optimize corporate investment strategies by increasing policy incentives and policy restraints. The findings provide important implications for policymakers to promote corporate sustainability and potential directions for future related research.

Does industrial relocation affect green total factor energy efficiency? Evidence from China's high energy-consuming industries

Over the past decades, China's vast regional disparities in resource endowment, economic development, and industrial structure have driven large-scale relocations of high energy-consuming industries (RHEIs). Despite extensive research on broad-based industrial relocation and emission transfer, the trend, structure and environmental impact of China's RHEIs need further investigation. This paper employs the multi-regional input-output model (MRIO) to calculate the trend, scale, and structure of the RHEIs among China's 30 provinces. Additionally, we investigate the RHEIs' effect on green total factor energy efficiency (GEE) and its heterogeneity. Our results indicate that the net inflow of high energy-consuming industries decreases GEE, with a more noticeable effect observed in central provinces and after the execution of the Belt and Road Initiative (BRI). However, the positive effect of RHEIs on GEE in outflow areas is more substantial than their negative impact in inflow areas, suggesting that RHEIs can enhance overall efficiency. This study contributes to the understanding of China's industrial relocation by providing valuable insights into China's RHEIs.

Air Contamination and Ecological Information Disclosure from South Africa’s High Energy Consumption Industries

Globally, South Africa is currently amongst the countries with the poorest air pollution. Organizational ecological information disclosure has recently become a progressively more prevalent method for ecological by-laws. However, at the moment, there needs to be empirical confirmation of the organization's ecological information disclosure effects of air contamination. This research investigates the relationship between air contamination and organization ecological information disclosure by applying cross-sectional data gathered from listed South African companies in high-energy consumption sectors from 2015 to 2021. The findings disclose that the link between air contamination and organizational ecological information disclosure is substantially adverse. The Northern Province significantly affects organizational ecological information disclosure compared to the Eastern Province. Furthermore, the effect air contamination has on organization ecological information disclosure also varies in companies situated in the provinces with various corporate ecological information disclosure transparency. This study portrays the interaction between air contamination and ecological information disclosure expansion in emerging economies such as South Africa.

Exploring the Transformation Path of High Energy-consuming Industries in A Low-carbon Economy

In recent years, under the background of "double carbon", reducing carbon emission and realizing green transformation and green development have become the necessary way for high energy-consuming enterprises to achieve sustainable development. However, the green transformation of high energy-consuming enterprises faces the problems of high investment cost and slow transformation, which makes it difficult for many high energy-consuming enterprises to take the step of green transformation. Based on the above background, this paper analyzes the concepts and theories related to low carbon economy and proposes the transformation path of high energy-consuming industries under low carbon economy environment.

Green fiscal policy and enterprise green innovation: evidence from quasi-natural experiment of China.

We aim to study the impact of green fiscal policy on enterprise green innovation by applying a time-varying difference-in-difference (DID) model, and treat the comprehensive demonstration city of fiscal policy for energy conservation and emission reduction (CPEE) in China as a quasi-natural experiment. The results show that the CPEE can significantly improve enterprise's green innovation performance of pilot area. This net policy effect is valid after a series of robustness tests to control for various potential confounding factors. Heterogeneity analysis reveals that the effect of CPEE is stronger for state-owned enterprises and enterprises in high energy consumption industries or industries with higher industrial concentration. In addition, the effect of CPEE is various among different categories of green patents, which is stronger for the types of alternative energy production category, waste management category, administrative supervision and design category. The mechanism test indicates that the CPEE can improve the green innovation performance by increasing enterprise' investment in research and development, promoting territorial industrial transformation and upgrading, and enhancing enterprise executives' environmental awareness. To achieve the carbon peaking and carbon neutrality goals, the green enabling role of fiscal reform pilot policy in transition economies and the applicability of localized policies should be excavated.

Embodied energy intensity of global high energy consumption industries: A case study of the construction industry

Embodied energy intensity of global high energy consumption industries: A case study of the construction industry

Impact of intelligence on the carbon emissions of energy consumption in the mining industry based on the expanded STIRPAT model

The intelligent construction of the mining industry has become an emerging trend in its future development plans. As a traditional high energy consumption industry, its energy conservation and emissions reduction have become particularly urgent concerns. Therefore, it is of great significance to study the impact of intelligence on the carbon emissions from energy consumption in the mining industry. This paper first uses dynamic indirect energy emissions factors to build an accounting model for carbon emissions from energy consumption in the mining industry and calculates the related carbon emissions from 2001 to 2020 by sector. Then, an expandable stochastic environmental impact assessment (STIRPAT) model is established to analyze the impact of intellectualization on the carbon emissions intensity of China’s mining industry. At the same time, many other important factors are included in the model, and the model is fitted using ridge regression. The results show that the order of influence, from large to small, is as follows: energy intensity, industrial output value, per capita output value, the proportion of output value of large and medium-sized enterprises, per capita stock of fixed assets, average enterprise output value, R&D intensity and proportion of indirect energy. Each 1% increase in the above factors will increase the corresponding carbon emissions intensity by 0.2005%, −0.1271%, −0.1207%, 0.7467%, −0.0595%, −0.09813%, 0.1143% and −0.1419%, respectively. Then, the prediction values of the independent variables are obtained by using the scenario analysis method and grey prediction model, and 12 scenarios are set up to predict the carbon emissions intensity of the mining industry energy consumption from 2021 to 2035 by using the expanded STIRPAT model. By analyzing the prediction results, we conclude that Scenario 8, Scenario 9, Scenario 10, Scenario 11 and Scenario 12 can achieve the emissions reduction goals of the mining industry in 2025 and 2030; the optimal path of emissions reduction is given for various scenarios. Finally, a development strategy for emissions reduction in China’s mining industry is proposed.

Charting China’s Export Trajectories: Energy Factors and the Evolution of Competitive Advantage in Relation to the U.S.

Accompanied with energy price fluctuating frequently, energy-saving technology updating rapidly, energy factor plays an important role in China’s export trade to US via energy relative price and energy consumption technology differentiation. According to industry energy consumption density, the paper classifies industries into high and low energy consumption industry, combining Costinot et al. productivity method with forward linkages increase export value added, calculates Chinese high and low energy consumption industries export comparative advantage index to US during 2000-2014, as well as using Kernel density method to evaluate the transition of them, finds that comparative advantage of China’s high/low energy consumption industry to U.S. has a trend of weaken/strength which shows extreme phenomena. furtherly, utilizing Probit method to estimate the factors which affects the comparative advantage, the results turn out that the gap of energy consumption technology between two countries is the main reason which contributes to China’s comparative advantage of both high and low energy consumption industry to U.S. The energy relative price just has significant impact on high energy consumption industry, which will affect the achievement of China’s carbon emission reduction targets in ‘Responding to Climate Change: China’s Policies and Actions’.

Research on the Structural Optimization of the Clean Energy Industry in the Context of Dual Carbon Strategy—A Case Study of Sichuan Province, China

As a major province for hydroelectric power in China, Sichuan Province has witnessed a great amount of seasonal characteristics in its hydroelectric power, endowing the clean energy industry in Sichuan with the characteristics of unstable supply in different seasons, strong power transmission capacity, and low production capacity of other non-fossil energy sources (except hydroelectric power). In this study, the mathematical model method was used to construct a structural optimization model of the clean energy industry in Sichuan Province, and to enable a quantitative analysis of the rationalization of the clean energy industrial structure in Sichuan Province. The results are proved from the cost-effectiveness of low carbon emission that hydroelectric power > wind power > photovoltaic power > natural gas > coal > oil. This study shall find the theoretical structure of the clean energy industry in Sichuan Province in 2030 with a prediction of Sichuan Province’s total future energy output and a constraint of its industrial structure model of clean energy. This paper suggests that Sichuan Province should give priority to the development of non-fossil energy sources, increase the development and utilization of power transmission channels in wet seasons, and develop clean energy and high energy consumption industries and the construction of pumped storage power stations, so as to reduce and avoid the waste of energy resources. It is also suggested that Sichuan Province should focus on developing clean energy with the capability of peak shaving, such as hydrogen energy and natural gas, while developing smart grid and long-distance transmission technology to strengthen energy conservation and emissions-reduced power generation. On this basis, Sichuan will focus on the development and utilization of natural gas as an alternative to high-carbon energy, with a view to optimizing its industrial structure of clean energy and helping China achieve the dual-carbon goals.

Basic Characteristic Analysis of Self-provided Power Plant in Iron and Steel Industry

Self-provided power plants are set up in order to maintain normal operation in some high energyconsuming industries in the era of power shortage in China. In a specific historical period, it effectively alleviated the problems of insufficient power supply and low reliability of the power grid, and promoted the rapid development of the national economy. The construction of self-provided power plants in the steel industry is to save electricity costs and improve the operational reliability of important units. This paper analyzes the basic production electrical characteristics and equipment load characteristics of the self-provided power plant in iron and steel industry, and summarizes the adjustment ability of the equipment from two aspects of power generation side and load side.

Research on Carbon Emission Management of Electric Power Enterprises Based on Blockchain Technology

As a high energy-consuming industry, it is especially important for electric power companies to manage carbon emissions well. This study analyzes the main problems of electric power companies in carbon asset management, and investigates the methods of intelligent, digital and transparent management of carbon emission situation using intelligent Internet of Things and blockchain technology. Carbon emission management based on blockchain technology can improve the accuracy and openness of carbon asset data and promote electric power companies to move forward to the low-carbon ecological era.

The relationship between carbon performance and financial performance: evidence from China.

Under the severe situation of global warming, low-carbon development is gaining more and more attention. Due to the different research methods, research samples, and the selection of performance indicators, there is greater disagreement on the relationship between carbon performance and financial performance. The study covers the dataset starting from 2013 to 2020 regarding 352 Chinese-listed companies with high energy consumption industries. The study uses the System GMM to explore the association between carbon performance and financial performance. The results we provided show that (1) carbon performance can significantly improve financial performance, but this effect is intertemporal. (2) Financial performance enhances carbon performance, and this effect is not lagged. (3) In terms of ownership structure heterogeneity, non-state-owned firms have a more significant effect of carbon performance on their financial performance, while the positive impact of financial performance on carbon performance is more pronounced in state-owned firms. The above findings provide a theoretical basis to motivate enterprises to improve their carbon performance and help China achieve the carbon neutrality goal as soon as possible.

How does manufacturing haze pollution decrease in China: a decomposition study of structural model based on general equilibrium framework.

Based on the annual mean PM2.5 concentration data of 30 provinces and cities in China from 2006 to 2020, this paper constructs a structural model of manufacturing haze pollution, expounds the main mechanisms affecting haze pollution, then statistically decomposes the main factors affecting the change of pollution emissions, and examines the direct and indirect impact paths of the change of haze pollution emissions in China. The study found that (1) the inhibitory effects of latent variables on manufacturing haze pollution is from strong to weak in order: industrial structure upgrading, environmental regulation, trade opening, productivity improvement, and economic scale expansion, while the optimal path for the indirect effect of exogenous latent variables on haze pollution is to rely on environmental regulation and opening up to achieve the improvement of productivity, so as to achieve the purpose of reducing haze pollution. (2) The analysis based on the PVAR model found that industrial structure adjustment is the key factor of haze decline in both the short and long term. Environmental regulation has an obvious effect on haze control in the short term, but in the long run, it still needs to rely on industrial structure adjustment, production efficiency improvement, and trade opening to achieve the goal of reducing haze. (3) There is an inverted U-shaped nonlinear relationship between output scale and environmental regulation. In addition, trade openness has a long-term effect on productivity. Technology spillovers from opening up can reduce haze pollution in the long run by improving productivity. (4) The environmental regulation policy in the central region is characterized by "race to the bottom," while the eastern region shows the characteristic of "race to the top" in the policy game of improving productivity and optimizing the industrial structure. Therefore, haze control requires an appropriate intensity of environmental regulation to reduce the proportion of high pollution and high energy consumption industries. Make full use of the international cooperation platform of the "the Belt and Road Initiative" and the pilot free trade zone to promote substantive cooperation between Chinese enterprises and developed countries in the field of environmental protection technology, increase investment in research and development of clean equipment and cleaner production technology, improve productivity, help China's green manufacturing, and contribute Chinese wisdom and Chinese solutions to global environmental governance and climate change.

Does the Belt and Road Initiative facilitate China’s corporate overseas investment: Based on a sustainable development perspective

Corporate overseas investment is a pivotal element of the Belt and Road Initiative (BRI). As an all-round opening-up strategy, the BRI has brought new ideas to international cooperation, and Chinese enterprises should seize this opportunity to promote global sustainable development. Adopting the data of Chinese listed enterprises from 2011-2020, this paper investigates the impact of the BRI on corporate overseas investment (COI) and its mechanisms via exploiting the difference-in-differences model (DID). Results show that the BRI has significantly facilitated the COI along the routes. We observe that the findings still hold after a series of robustness tests. Mechanism analysis verifies that tax incentives and credit environment improvement are the main channels by which BRI enhances COI. Heterogeneity results reveal that this initiative is more prominent for small and medium-sized enterprises and enterprises in dominant industries. The extensive analysis suggests that from a sustainable development perspective, the BRI facilitates more overseas investment of enterprises in polluting or high energy-consuming industries; the COI is more affected by BRI in regions with more stringent environmental regulations. This study provides empirical evidence for BRI construction and regional development.

Air Contamination and Ecological Information Disclosure From South Africa’s High Energy Consumption Industries

Globally, South Africa is currently amongst the countries with the poorest air pollution. Recently, organization ecological information disclosure has turned out to be a progressively more prevalent method for ecological by-laws. However, at the moment, there is an absence of empirical confirmation on the organization ecological information disclosure effects of air contamination. This research investigates the relationship between air contamination and organization ecological information disclosure applying cross sectional data gathered from listed South African companies in high energy consumption sectors from 2015 to 2021. The findings disclose that the link between air contamination and organization ecological information disclosure is substantially adverse. The Northern province has huge effects on organization ecological information disclosure in comparison with the Eastern province. Furthermore, effect air contamination has on organization ecological information disclosure also varies in companies situated in province with various corporate ecological information disclosure transparency. This study makes available a portrait of the interaction between air contamination and ecological information disclosure expansion in emerging economies such as South Africa.

Study on high energy-consuming industrial agglomeration, green finance, and carbon emission.

Based on the relationship between industrial agglomeration, green finance development, and carbon emissions, some relevant theoretical hypotheses are proposed, and this paper employs the combination of spatial Durbin model and panel threshold model to empirically test data from 30 provincial regions in China from 2006 to 2019. The results show that the agglomeration of high energy-consuming industries has an inverse U-curve relationship with carbon emission intensity, and the development of green finance will inhibit the growth of carbon emission intensity. There are significant spatial characteristics of high energy-consuming industrial agglomeration, green financial development, and carbon emissions. And the intensity of local carbon emissions will be influenced by the agglomeration of high energy-consuming industrial agglomeration and green financial development in local and neighboring areas. Moreover, green financial development plays a moderating role in the relationship between high energy-consuming industrial agglomeration and carbon emissions, and the role of high energy-consuming industrial agglomeration and green financial development on carbon emissions has a threshold effect due to the mismatch between the two developments. Under different levels of green financial development, the influence of high energy-consuming industrial agglomeration on carbon emissions varies widely, and green financial development helps to suppress the negative impact of high energy-consuming industrial agglomeration on carbon emissions. Accordingly, we argue that inter-regional joint prevention and control mechanism should be established for pollution control. And China should build more effective high energy-consuming industrial clusters to make them play an active role in reducing emissions. At the same time, China should accelerate the construction of green finance, strengthen the disclosure and transparency of green financial information, and establish a joint mechanism for the development of inter-regional green finance, so that it can contribute to regional industrial transformation and pollution control.

Carbon emission quota allocation of high energy consumption industries in undeveloped areas – A case study of Inner Mongolia Autonomous Region

With the approaching of the target year of carbon peak, all world countries have gradually strengthened carbon emission reduction actions. However, most of the undeveloped countries or regions do not belong to the Annex I countries in the Kyoto Protocol, and the development of carbon emission trading mechanisms is relatively slow. Therefore, setting emission quota standards for industries in underdeveloped regions is necessary. Considering the principles of fairness, efficiency, and sustainability, we establish a “multi-objective information entropy allocation model” (i.e., IEMMA method) for underdeveloped areas. Take China's Inner Mongolia Autonomous Region as an example, and the allocation results show that: (1) The “historical emissions”, “carbon emission intensity”, “cumulative emissions”, “energy structure”, and “energy intensity” are assigned higher weights. Such industries will carry a higher responsibility for emissions reductions, they should gradually transfer emission quotas to industries with smaller historical emissions to increase enthusiasm for reducing emissions. (2) Compared with the historical emissions allocation scheme, the IEMMA model can increase the emission limits for industries with large historical emissions. For industries with relatively small emissions, their emission quotas can be appropriately relaxed to promote the sustainable development of the industry. (3) Under the allocation scheme of the IEMMA model, the difference in the reduction of carbon emission intensity of different industries is small. Carbon emission intensity becomes a relative emission reduction indicator, which reflects the fairness of allocation while maintaining economic development. (4) The “quota gap” formed by the allocation plan of the IEMMA model is large, which is conducive to promoting the active emission reduction of high-emission enterprises. Larger “allowance gaps” are conducive to increasing the activity of the carbon trading market. In summary, the IEMMA model is conducive to achieving long-term emission reduction goals in underdeveloped regions and is more suitable for the allocation of quotas to high energy-consuming industries.

Energy Consumption Analysis of a Diesel Hydrotreating Unit Using an Aspen Simulation

The petrochemical industry is traditionally a high energy consumption industry, thus energy saving in this industry is of great significance in terms of trying to achieve the national goal of “carbon-peak and carbon neutrality” in China. Diesel is one of the main products of petrochemical enterprises. The energy consumption of a diesel hydrotreating (HDT) unit is relatively high due to the high reaction temperature and pressure of HDT reactors. In order to further explore the energy consumption of diesel HDT units under different operating conditions, this paper establishes a full-process simulation based on the kinetics of hydrodesulfurization, hydrodenitrogenation, and aromatics saturation, in Aspen Plus to discuss the effect of different operating conditions on the electricity, steam, and fuel gas consumptions. The results show that with the increase of reaction temperature or reaction pressure, the sulfur content in diesel oil decreases, but the consumption of related utilities and comprehensive energy consumption increases. In addition, this paper also analyzes the energy consumption changes under the operating condition boundaries when the diesel quality is unchanged. When the reaction pressure is 8 MPa and the reaction temperature is 317.5 °C, the comprehensive energy consumption is 5% lower than the energy consumption with the reaction pressure of 6 MPa and the temperature of 320 °C. Therefore, on the premise of satisfying the diesel product quality, the comprehensive energy consumption of the diesel HDT unit can be reduced by increasing the reaction pressure and decreasing the reaction temperature.

The Impact of Carbon Quota Benchmark Allocation on Cement Company Competitiveness: A System Dynamics Approach

The cement industry, as a high energy-consuming industry, has been included in the carbon emissions trading system (ETS) in the context of the carbon neutrality goals. Benchmark allocation of carbon quotas may have a significant impact on cement companies. To study this impact, we constructed a system dynamics (SD) model for a cement company with the three subsystems of “demand and production”, “economic efficiency”, and “carbon emission and carbon trading” based on company competitiveness theory. A company competitiveness index was established from the SD model. Through computer simulation, the influence of the annual decline coefficient of the benchmark value and the innovation investment rate on a cement company’s competitiveness under different circumstances were compared and analyzed. This study puts forward suggestions for low-carbon development, such as setting a reasonable range of annual decline coefficient of the benchmark value (0.97–0.99) and promoting investment in emission-reduction technologies in multiple phases.