Low-carbon Transformation Research Articles

Analysis of the influence and coupling effect of environmental regulation policy tools on industrial green and low-carbon transformation

Industrial green and low-carbon transformation plays a crucial role in China’s efforts to achieve its Carbon peaking and Carbon neutrality objectives. The implementation of environmental regulation policies is a key institutional framework that facilitates this transformation. Therefore, it is of great importance to explore the impact and interplay of these policies on industrial green and low-carbon transformation to foster high-quality economic development. This study categorizes environmental regulation policy instruments into three types: command-type, investment-type, and expense-type. Using industrial panel data from 30 provinces in China spanning the period from 1997 to 2021, both theoretical analysis and empirical testing are conducted to investigate the effects of these different policy instruments on industrial green and low-carbon transformation. The benchmark regression results show that the impact of command-type environmental regulation and investment-type environmental regulation on industrial green and low-carbon transformation shows an inverted U-shaped feature of rising first and then declining. The impact of cost-based environmental regulation on industrial green and low-carbon transformation shows a U-shaped feature of decreasing first and then increasing. The coupling of command-type environmental regulation and investment-type environmental regulation, command-type environmental regulation and expense-type environmental regulation, and the coupling of the three kinds of environmental regulation can promote industrial green and low-carbon transformation. The mechanism test results show that the impact of formal environmental regulation on industrial green and low-carbon transformation has a transmission mode of “formal environmental regulation–green technology innovation path–green and low-carbon transformation.”

Multi-Depot Electric Vehicle–Drone Collaborative-Delivery Routing Optimization with Time-Varying Vehicle Travel Time

This paper presents an electric vehicle-drone (EV–drone) collaborative-delivery routing optimization model that leverages the time-varying characteristics of electric vehicles and drones across multiple distribution centers (i.e., central depots) to address the logistics industry’s low-carbon transformation in the last-mile delivery. The model aims to minimize total delivery costs by formulating a mixed-integer programming (MIP) model that accounts for essential constraints such as nonlinear charging time, time-varying EV travel time, delivery time window, payload capacity, and maximum range. An improved adaptive large-neighborhood search (ALNS) algorithm is developed to solve the model. Experimental results validate the effectiveness of the proposed algorithm and highlight the impact of EV and drone technology parameters, along with the time-varying EV travel times, on the economic efficiency of delivery distribution and route planning.

Green Financing, Energy Transformation, and the Moderating Effect of Digital Economy in Developing Countries

AbstractThe energy sector in many developing nations faces the difficulty of insufficient financing throughout the low-carbon transition, highlighting the importance of international green financing in alleviating financial constraints. The advancement of digital technology could facilitate green financing for energy transition in the digital economy, but this statement lacks empirical evidence. The primary objective of this research is to investigate the impact of international green financing on low-carbon energy transformation in developing nations. Additionally, we investigate the moderating role of digital economy between the two. Our findings validate the favorable impact of international green financing on low-carbon energy transformation, and this impact is particularly evident for hydro and wind energy consumption. We show that this beneficial effect is greater for low-income countries or regions with high levels of energy transition. We also provide evidence of the positive moderation effects of digital economy and find that its effects are still present in the transition to hydro and wind energy. This research helps to broaden green financing channels for the energy sector in developing countries, especially from the perspective of digital economy.

Research and Suggestions on Improving the Carbon Emission Management Capacity of Coal-fired Power Plants

This paper discusses how coal-fired power plants can improve their carbon emissions management capabilities in the context of the 2030 carbon peak policy. The article first outlines the current status of implementing carbon peak policies in China’s energy sector, analyzes the current status of carbon emissions from coal-fired power plants, including carbon emission intensity, progress in low-carbon transformation, and the operation of the carbon emissions trading market. Subsequently, the article proposes six suggestions for improving the carbon emissions management capabilities of coal-fired power plants, and provides typical cases for each suggestion. Finally, the article looks forward to the challenges and opportunities faced by coal-fired power plants in carbon emissions management in the future, and emphasizes the importance of improving carbon emissions management capabilities for coal-fired power plants.

Green Finance: An Emerging Driving Force for Low-Carbon Transformation of China’s Energy Structure

Green Finance: An Emerging Driving Force for Low-Carbon Transformation of China’s Energy Structure

Decarbonization pathways analysis and recommendations in the green steel supply chain of a typical steel end user-automotive industry

China's automotive industry, the world's largest producer and consumer, has reached a crucial stage in its transition from rapid expansion to high-quality and low-carbon development. Considering the decarbonization of the whole automotive industry, in addition to reducing the CO2 emissions from fuel supply and exhaust pipes, which account for 65–80 % of the total value chain CO2 emissions, the automotive industry should also accelerate the decarbonization of raw materials, which contribute to 18–22 % of these CO2 emissions. Many automotive manufacturers are collaborating with steel producers on green steel initiatives due to the high CO2 emissions from steel production, the integrated nature of the steel supply chain, and the need for early planning in low-carbon steel production routes transformation. To clarify the carbon emission characteristic of the automotive steel supply chain, this research establishes a mathematical method for calculating cradle-to-gate carbon footprint of automotive steel product based on BF (Blast furnace)-BOF (Basic oxygen furnace), Scrap-EAF (Electric arc furnace), and DRI (Direct reduced iron)-EAF steel production routes. The cradle-to-gate carbon footprints of BF-BOF, Scrap-EAF, and DRI-EAF steel production routes are 1711.84 kgCO2/t-sp (steel product), 916.39 kgCO2/t-sp, and 2738.53 kgCO2/t-sp. A projection of CO2 emissions in automotive steel supply chain from 2020 to 2060 has been investigated, taking into account production structure adjustment, scrap recycling, and low-carbon electricity adoption, as well as the demand for automotive steel products. Projections from 2020 to 2060 indicate that the CO2 emission intensity of the automotive steel supply chain will decrease by 28.25 % by 2030 and 93.99 % by 2060, with total emissions dropping by 28.47 % and 96.92 %, respectively. This research identifies effective decarbonization measures in the automotive steel supply chain, including internal and end-of-life (EOL) steel scrap recycling, which offer significant CO2 emissions reduction without increased costs, demonstrating high cost-effectiveness. In a word, this research provides a technical framework and data foundation for decarbonizing the automotive steel supply chain.

A negative-carbon planning method for agricultural rural industrial park integrated energy system considering biomass energy and modern agricultural facilities

Biomass energy, recognized as a “zero-carbon” energy, has gradually become a crucial approach to promoting the low-carbon transformation of agricultural rural industrial parks (ARIP). Meanwhile, modern agricultural facilities (MAF) can play a significant role in adjusting agricultural load. Therefore, this paper proposes a negative-carbon planning method for the ARIP integrated energy system (IES). Firstly, carbon activities occurring during the operation of ARIP are sorted out and modeled based on the life cycle assessment (LCA) method, especially modeling the “zero-carbon” and “negative-carbon” benefits of biomass energy. At the same time, the models of both agricultural irrigation systems and straw bundling direct combustion heating are constructed in the ARIP planning. Then, a negative-carbon planning model for ARIP IES is established with the goal of minimizing the annualized total cost, where carbon emission reduction is integrated into the optimization objectives through carbon trading. On this basis, a two-stage distributionally robust optimization (DRO) planning model is constructed, where a box-like set and comprehensive norm constraints are used to model the seasonal differences of agricultural industry loads and the uncertainty of probability distribution in photovoltaic (PV) scenarios. Especially, a box set with adjustable uncertainty coefficients is introduced to simulate fluctuations of output in PV scenario. Finally, the CPLEX solver is used to solve the planning model. verify the effectiveness of the proposed planning method in enhancing the economic and environmental effects of ARIP. Results indicate that the proposed planning model can reduce the total cost by 49.584 × 104 $. Besides, the annual carbon emissions can be reduced from 37533.98 t CO2-eq to −15834.5 t CO2-eq. Especially, the carbon sequestration effect of biochar is the key link in achieving “negative carbon” in ARIP.

Research on the Practical Path of Green Finance in the Low-carbon Transformation of Smart Cities: A Case Study of the Transformation and Development of European Smart Cities

This study aims to explore the practical path of green finance in promoting low-carbon transformation of smart cities by taking the transformation of smart cities in Europe as a case study. The successful experience of smart city transformation in Europe is deeply studied through case analysis, and the application of green finance and its impact mechanism on urban transformation are discussed. The study found that green finance plays an important role in the transformation of smart cities in Europe, which promotes the transformation of cities to lowcarbon and smart direction through the practice path of policy formulation, technological innovation and sustainable development planning. This study provides a reference for the low-carbon transformation of smart cities in other regions, and has certain theoretical and practical significance for promoting sustainable urban development.

Fintech’s role in carbon emission efficiency: dynamic spatial analysis

Against the backdrop of digitization and global warming, fintech plays a crucial role in accelerating the growth of green finance, driving innovation in the financial industry, and catalyzing the low-carbon transformation of economic activities. This paper utilizes city panel data from 2007 to 2019 to examine the direct impact of fintech on carbon emission efficiency (CEE), the transmission channels of green technological innovation and green finance, and the spatial spillover effects, using dynamic panel models, mediation effect models, and dynamic spatial Durbin models (SDM). The study finds that: (i) Fintech significantly improves CEE, and this conclusion remains robust after accounting for potential endogeneity issues and conducting robustness tests. (ii) Mechanism analysis reveals that green finance and green technological innovation are the primary channels through which fintech influences CEE. (iii) Results from the dynamic SDM model indicate that fintech has a significant positive spatial spillover effect on CEE, with the long-term spillover effect being smaller than the short-term spillover effect. (iv) Heterogeneity analysis reveals that fintech’s improvement effect on CEE is mainly evident in eastern regions, emerging first-tier and first-tier cities, and non-resource-based cities. Our research provides new insights for policymakers on achieving China’s dual-carbon goals through the promotion of fintech development, green finance, and green technological innovation. It also aids in the coordinated development of fintech among cities and the formulation of differentiated policies, providing a theoretical foundation and empirical support for future research.

The impact of a low-carbon transport system policy on total factor carbon emission performance: Evidence from 283 cities in China

Reducing carbon emissions from the transport sector is crucial to achieve “carbon neutrality” and is an important component of a low-carbon policy system. In response to the uncertainty of evaluating current low-carbon transport policies, we provide an in-depth analysis and examination of low-carbon transport system (LCTS) policies implemented in China. Using data from 283 Chinese cities between 2006 and 2020, we provide evidence on the policy effects, potential mechanisms, and heterogeneity of LCTS policies on carbon emission performance. Results showed that LCTS policies significantly improved carbon emission performance in pilot regions. The main ways to achieve this policy's objective were to reduce energy consumption in pilot cities, to promote the development of green technologies, and to implement low-carbon transformation of public transport. Moreover, there was heterogeneity in the policy's effects, with the implementation of a LCTS being more effective in eastern and central regions of China and in larger and more compact cities. By analysing the policy's mechanisms and heterogeneity of effects, this article provides a reference for the formulation and selection of low-carbon transport policies.

Research on the Impact of Labor Resource Allocation on Green Technology Innovation

Facing increasingly severe environmental pollution and resource scarcity, China has accelerated its pace of green and low-carbon transformation. Green technological innovation helps economic development by reducing ecological pollution and lowering resource consumption. As an important factor of production for social development, the labor force plays a very significant role in optimizing the economic development structure of our country and achieving high-quality leapfrog development. This article explores the relationship between the allocation of labor resources and green technology innovation based on the aforementioned practical motivations, from both theoretical mechanisms and empirical perspectives. Using provincial panel data from China between 2000 and 2021, a spatial Durbin model was constructed to empirically test the spatial spillover effects of labor resource allocation on green technology innovation and to draw relevant conclusions. Subsequently, to further investigate the heterogeneous impact of labor resource allocation on green technology innovation, China was divided into three major regions—eastern, central, and western—and empirical model tests were conducted on separate samples. The following conclusions have been drawn: Over time, during the 22 years from 2000 to 2021, China's overall labor resource allocation has shown an overall upward trend; China's green technology innovation capability has significantly improved, but regional development is uneven, with a large gap in development between the eastern, central, and western regions; through the study of the spatial Durbin model on the impact of labor resource allocation efficiency on green technology innovation, the results indicate that labor resource allocation has a significant main effect and spillover effect on green technology innovation, meaning that the improvement in labor resource allocation efficiency will promote the increase in the level of local green technology innovation, while the decline in labor resource allocation efficiency will inhibit the increase in the level of local green technology innovation; the impediment effect of the decline in labor resource allocation efficiency on regional green technology innovation varies significantly across different regions, with the central region being the most prominent, followed by the western region, and then the eastern region. Based on the conclusions, the following suggestions are made: Regions should strengthen cooperation and exchanges to promote the coordinated development of green technology innovation. Eastern provinces and cities with a higher level of green technology innovation should lead the surrounding provinces and cities with weaker development, actively engage in cooperation and exchanges in infrastructure and green technology, and establish a more orderly and open green technology trading market, thereby promoting the coordinated development of green technology innovation between regions; adopt market-oriented approaches to remove barriers to the autonomous and orderly flow of labor factors. Give the market a decisive role in resource allocation, reasonably play the role of the government, promote the rational and orderly flow of capital and labor resources between regions, and improve the efficiency of resource allocation.

Low-carbon development vector in circular economy

Within the framework of the Industry 4.0 concept, transition from a linear economy model to a circular economy model aimed at energy saving, regenerative green production, circulation, and consumption is becoming increasingly relevant. The purpose of the study is to substantiate the low-carbon development model consistency with the goals and objectives of circular economy (hereinafter referred to as CE) for subsequent development of a green growth strategy. Objectives of the study: to use the criteria and methods of CE to develop a toolkit for transition to low-carbon economy and to formulate its development strategy. The study used general scientific methods, in particular, analysis, synthesis, and periodization. In the course of the study the criteria for green economy growth have been identified, and in accordance with them the stages of CE have been established such as conceptual, institutional, and regulatory. The author’s variant of the combined regulatory system based on a combination of administrative and economic measures has been proposed. Matrices of problem situations by individual types of activity have been formed. As the study result, the authors outlined the circular economy stages, substantiated the possibility of low-carbon transformation within the framework of CE, relying on carbon emissions management, low-carbon technologies and a system of financing “green” projects implementation. The tools to stimulate “green” growth have been defined: a tax on greenhouse gas emissions, emissions trading system, subsidizing alternative energy, environmental projects, energy-saving technologies development and their implementation into the production process. The novelty of the study lies in a scheme development for building a low-carbon economic development strategy aimed at achieving the goals of reducing greenhouse gas emissions at the level of both the region and industrial enterprises.

Characterization of Industrial Carbon Emission Dynamics and Network Structure Evolution in China

Given that industry is the major source of carbon emissions, clarifying the carbon transfer regularity triggered by industry production linkage is of great importance in realizing the synergistic development of industry to reduce pollution and carbon emissions. Based on the perspective of responsibility allocation, the study accounted for the industry carbon emissions and constructed a carbon transfer weighted directed network model and applied the social network analysis method to explore the structure of the industry carbon transfer network and its evolution characteristics from 2005 to 2020. The results showed that： ① The overall carbon emissions of industries from 2005 to 2020 presented a rapid growth trend and large differences occurred in emissions between industries. ② The scale of the carbon transfer network was expanding rapidly and the characteristics of the small-world network were significant. ③ The community structure of the carbon transfer network was obvious, including four optimal associations： high carbon emission, carbon transmission, carbon endogenous, and high spillover. ④ The construction industry and the metal smelting and rolling processing industry were the core of the carbon transfer network structure, with strong network control. In view of the above characteristics, we proposed countermeasures and suggestions in terms of implementing the allocation of carbon emission reduction responsibilities and differentiated emission reduction measures for associations as well as focusing on the management of core nodes of the network, with the intent of providing cross-sectoral synergistic emission reduction ideas for the development of sustainable low-carbon transformation in China's industry sector.

From ancient philosophy to modern governance: Confucian culture shaping low-carbon corporate transformation in China’s listed companies

Confucianism has been passed down for thousands of years, naturally turning into a research hotspot. Considering the goal of green development, this study examines the role of Confucian culture in low-carbon corporate transformation. This study shows that Confucian culture can effectively promote a low-carbon transformation and the development of companies. The greater the influence of Confucianism on a company, the higher its level of low-carbon transformation. Confucian culture takes effect in three ways: by improving corporate environmental awareness, by promoting social responsibility, and by strengthening corporate governance. Heterogeneity research shows that state-owned and low-capital-intensity companies, low-competition and high-attention industries, non-low-carbon pilot programs, and low-marketization areas all increase the extent of influence. The findings shed light on the influence of Confucians on low-carbon transformation at the firm level and enrich the ideas surrounding Confucian culture and corporate development.

A novel two-stage optimal layout model of hydrogen refueling facility network based on green electricity hydrogen production: Beijing-Tianjin-Hebei region of China as case study

Green electricity hydrogen production(GEHP) is fundamental support for developing new-type power system and achieving the green and low-carbon transformation in the transportation sector. It is key issue to build a hydrogen refueling facility network(HRFN) to link hydrogen production and consumption. Firstly, the framework of HRFN is proposed including hydrogen production points(HPP), hydrogen refueling stations(HRS) and hydrogen demand points(HDP). Secondly, a two-stage model is built. In the first stage, the siting model of HRS cluster is constructed considering the service capacity, service radius, and construction, operation and penalty costs. In the second stage, the bi-objective planning model of HRFN is constructed considering network stability, hydrogen storage and transportation forms and producing total costs. Finally, the Beijing-Tianjin-Hebei region of China(BTH) is taken as case study to verify the effectiveness. Sensitivity analyses are conducted on four factors:HRSs’ service radius, service capacity, GEHP’s efficiency and HDPs’ scope. The key findings are: 1)the service radius and capacity of HRSs and HDPs’ scope all affect the layout of HRSs, with HDPs’ scope further influencing HPPs’ number; 2)the construction and operation costs are more impacted by changes in GEHP's efficiency compared to network stability;3)the network should be strengthened to cover the whole processes from hydrogen production to consumption.

Cross-border capital flows and low-carbon economic development: Examining the impact of foreign shareholding

This study utilizes data from Shanghai and Shenzhen A-share listed companies from 2011 to 2021 to explore the impact of foreign shareholding on the development of a low-carbon economy and the underlying mechanisms. Findings show that foreign shareholding significantly reduces corporate carbon emissions and promotes corporate environmental responsibility and low-carbon transformation. The paper further investigates how foreign shareholding reduces carbon emissions by increasing corporate investments in environmental protection and driving green innovation. Foreign participation is found to improve the efficiency of corporate resource allocation and innovation capabilities, allowing for continuous improvements in low-carbon technologies and production processes. The study also examines the effect of corporate environmental strategies and green technology advancement on the relationship between foreign shareholding and carbon emissions, revealing the heterogeneity of foreign investment impacts on low-carbon development under different corporate environments and capabilities.

A multi-objective robust dispatch strategy for renewable energy microgrids considering multiple uncertainties

The demand for low-carbon transformations and the uncertainty of renewable energy sources and loads present significant challenges for the optimal dispatch of microgrid. This study proposed a multi-objective robust dispatch strategy to reduce the risks associated with the uncertainty of renewable energy source output and loads while promoting low-carbon and economical microgrid operation. The economic emission dispatch problem for a microgrid was formulated as a multi-objective robust dual-layer optimization model. Consequently, a high-dimensional adjustable linear polyhedral uncertainty set was proposed to describe the uncertainty of renewable energy sources and loads. This study transformed the original model into an easy-to-solve single-layer second-order cone programming optimal power flow optimization model by employing second-order cone relaxation and duality transformation. Thereafter, a synthetic membership function was proposed to determine the optimal compromise solution. To determine the charging and discharging statuses of the battery storage system and the electricity traded between the microgrid and the external power grid, a battery storage system control strategy based on time-of-use electricity prices and real-time power flow calculations was proposed. Simulations conducted on a modified IEEE-30 bus system demonstrated that the proposed strategy effectively reduced the economic costs and carbon emissions of the microgrid by 8.23 % and 2.43 %, respectively.

Experimental and kinetic modeling investigation of NOx control in coal combustion by ammonia reburning

The carbon peaking and carbon neutrality goals present urgent demands for the green low-carbon transformation of the energy system. As a potential alternative energy, ammonia (NH3) used as reburning fuel in the coal-fired boilers will achieve both low-carbon and low-NOx emissions. To investigate ammonia reburning, experimental and chemical kinetic modeling were conducted in a tube flow reactor at 1023–1573 K under both ammonia and coal combustion conditions. Factors are researched including the combustion atmospheres of NH3/N2/O2 (PM-NH3) and coal/N2/O2 (PM-Coal), different inlet CO concentrations, reburning temperatures and reburning fuel ratios. The results indicate that ammonia reburning can effectively reduce NO emissions by about 95 %. The C-N reaction exhibits a positive effect on NO reduction at low temperature and a negative effect at high temperatures. As the CCO increases from 0 % to 4 % at 1573 K, the optimum temperature window size increases from 225 K to 413 K, and NO reduction rises from 31.25 % to 97.5 %. The whole ammonia reburning process includes NO rapid reduction stage (NRS), NO oxidation stage (NOS), and NO slowly re-reduction stage (NRRS) at high temperature. The chemical kinetic modeling indicates that the C-N reaction obviously shortens the residence time of the NRS and increases the ROP in the NOS, which together undercut NO reduction compared to PM-NH3 case. The promotion of the oxidation path of NH3-NH2-HNO-NO results in the NOS appearance and NRS ending. Moreover, this path affected by C-N reaction is primarily responsible for NO reduction cutoff in the PM-coal case.

Life cycle carbon emission assessment and carbon payback period analysis for the regeneration of old residential areas in cold regions: Case study in Qingdao, China

Communities urgently need to explore green and low-carbon transformation pathways due to high energy consumption and carbon emissions. However, existing studies lack a comprehensive assessment of carbon emissions and analysis regarding carbon reduction during renovation of old residential areas in cold regions. Therefore, this study employs a Life Cycle Assessment (LCA) and the payback period method to evaluate carbon emissions throughout the life cycle comprehensively. It constructs a carbon-emission calculation model based on LCA, specifically tailored to the retrofitting of old residential areas in cold cities. Additionally, it investigates the effectiveness of three typical retrofit measures undertaken in Qingdao, a region located in the cold A zone, focusing on whole-life-cycle energy savings and carbon reduction. The findings reveal that the average annual carbon emission intensity per unit area for Cases 1, 2, and 3 is 12.59 kg-CO2 e/(m2·a), 27.05 kg-CO2 e/(m2·a), and 23.39 kg-CO2 e/(m2·a), respectively. Their corresponding carbon payback periods were 6.06, 7.23, and 16.00 years, respectively, which could be further shortened through material recycling. The environmental impact assessment of typical retrofitting measures contributes to the promotion of sustainable development. Furthermore, this study offers guidance for establishing an effective assessment system that supports the design of energy-saving retrofits.

Low-Carbon Transformation of Chinese Steel Enterprises Under the Dual Carbon Goals: Taking Baowu Group as An Example

The profound changes in the environment have led to increasing global concerns about the negative impacts of carbon emissions. Against the backdrop of the environmental crisis, the concept of “dual carbon” emerged in China, aiming to achieve carbon peaking and carbon neutrality and mitigate the adverse effects of climate change. The establishment of these goals in 2020 marked a significant milestone in global efforts towards a more sustainable future. The paper initially delves into a comprehensive macro and micro analysis, reviewing significant policy measures introduced since the "dual carbon" goals were established in 2020. It pays particular attention to documents that have had a profound impact on the steel industry, emphasizing the urgency of low-carbon transformation among steel enterprises. Amidst the challenges posed by the macroeconomic environment and within the framework of the "dual carbon" policy, the paper takes Baowu Group, China's leading steel enterprise, as the focal point of this analysis. The paper meticulously scrutinizes seven specific measures implemented by Baowu Group in its journey towards low-carbon transformation, adopting a multifaceted perspective. It provides a comprehensive assessment of the effectiveness of Baowu Group's transformation from diverse perspectives, highlighting the successful outcomes of both Chinese government policies and corporate efforts. In conclusion, the paper presents tailored policy recommendations and transformation strategies tailored specifically for the steel industry.