Green Development Research Articles

Can urban digital intelligence transformation promote corporate green innovation? Evidence from China

Can urban digital intelligence transformation (DIT) facilitate corporate green innovation (CGI)? This research uses the staggered difference-in-differences (DID) approach to study how urban DIT, represented by the Artificial Intelligence Innovation Development Pilot Zones (AIIDPZs), affects CGI. Regression results indicate that urban DIT promotes both the quantity and quality of CGI. Mechanisms analysis reveals that urban DIT promotes CGI by facilitating digital transformation, increasing firms’ investment in R&D, and facilitating information sharing. Heterogeneity analysis shows that urban DIT has a more significant effect on promoting green innovation in non-SOEs, industries with lower pollution levels, and enterprises in regions with high intellectual property protection (IPP). This study offers new perspectives on the role of urn promoting green development and provides empirical support for policy-making.

Can audit committees’ environmental background promote corporate green innovation? Evidence from China

ABSTRACT Identifying potential driving factors for corporate green innovation is vital in promoting global green development. This study aims to examine whether the environmental background of the audit committee promotes corporate green innovation and the mechanisms involved. Based on this perspective, we empirically test a research sample of Chinese A-share market-listed companies from 2007 to 2022. The results reveal that, first, the audit committee’s environmental background can significantly promote green corporate innovation. Second, the audit committee promotes green innovation by enhancing the environmental awareness of the management, increasing substantial environmental investments, and fostering environmental compliance; this effect is more pronounced in companies characterized by significant media attention and considerable involvement of the audit committee in governance. Third, green innovation can significantly enhance economic and environmental performance, although it delays its impact on short-term economic performance. The conclusions of this study provide new empirical evidence for corporate governance optimization and green innovation, and offer decision-making insights for enterprises to implement green innovation strategies for sustainable development.

Research on the Coupling and Coordination Relationship between Digital Economy and Green Development in Guangdong Province

Green development enabled by the digital economy is an important engine for economic growth. The article empirically investigates the spatial and temporal evolution of the coupling and coordination between the digital economy and green development by constructing an index system of the digital economy and green development, and by selecting the panel data of 21 prefectural cities in Guangdong Province in the period of 2012-2022. The study finds that, in terms of external spatial distribution, there is a large gap between the level of digital economy and green development in each city, and the development is not balanced; the gap between the two major coupling levels in each city is more obvious, presenting an uneven pattern of “center-edge”. In terms of intra-city development, the level of coupling and coordination between the digital economy and green development of each city from 2012 to 2022 shows an upward trend, reaching the level of primary coordination to good coordination, but the overall level is still not high, and there is still a certain gap from realizing high-quality coordination. Accordingly, in order to promote the interconnection of digital economy and green development, the article puts forward a series of policy recommendations to promote the deep integration of industrial digitization and greening among cities, adhering to the innovation-driven, and facilitating the coordinated development based on the differentiated resources of cities.

Development of novel mortar using fine river sand and pretreated waste flue gas desulfurization gypsum powder and pond fly ash

The objective of this study is to investigate the potential of combined pond fly ash (PFA) and flue gas desulfurization gypsum (FGDG) as a partial replacement for cement by mixing them with fine river sand for green mortar development. We studied the physical, mechanical, and microstructural properties of mortars by using techniques such as scanning electron microscopy equipped with energy-dispersive X-ray spectroscopy (SEM-EDXS) and X-ray diffraction (XRD) for chemical component identification of the hydrated phase. These experimental results show that mortar containing pond fly ash, FGDG, and cement concentrations of 5 wt%, 5 wt%, and 90 wt% yields the maximum compressive strength (8.9 MPa) and flexural strength (3.4 MPa) after 28 days. This mortar has 12.6% higher compressive strength and 48% lower shrinkage in comparison with control specimens. A reduction in shrinkage is attributed to the denser structure of the mortar, as the calcium silicate hydrate (C–S–H) gel is found to exist in the SEM image and also identified through XRD studies. It is also concluded that excessive ettringite formation causes expansion in the volume of mortar, voids formation, and results in the reduction of strength. The application of this mortar can be in the internal plaster, bricks, and masonry.

ESG performance and green innovation in commercial banks: Evidence from China

Environmental, Social, and Governance (ESG) is closely related to commercial banks’ promotion of "dual-carbon" goals and the concept of sustainable development. The impact of ESG performance on commercial banks’ support for green innovation remains an issue for in-depth study. This paper studies 36 Chinese commercial banks in China from 2010 to 2021 and finds that the ESG performance of commercial banks can promote green innovation, and this promotion is more obvious when bank remuneration incentives are effective. Meanwhile, this paper verifies the mediating role of the non-performing loan ratio and the Lerner index in it, which provides channel support for ESG to effectively promote green innovation development. This study enriches the existing literature on environmental, social, and governance performance and green innovation in commercial banks and provides new perspectives and directions for future research.

Evaluation of Digital Technology Integration into University Teaching Acceptance in the Context of Green and Sustainable Development

Evaluation of Digital Technology Integration into University Teaching Acceptance in the Context of Green and Sustainable Development

Digital Economy, Marine Industrial Structure Upgrading, and the High-Quality Development of Marine Economy Based on the Static and Dynamic Spatial Durbin Model

Achieving marine sustainable development goals requires improving the quality of the marine economy. In this study, we constructed a multi-dimensional evaluation index system to quantify the high-quality development of the marine economy (HDME) and digital economy for China’s 11 coastal regions between 2012 and 2020, and systematically explored the mechanisms between the digital economy, marine industrial structure upgrading, and high-quality development of the marine economy. We further empirically analyzed the influence of the digital economy and marine industrial structure upgrading on the HDME by using the static and dynamic spatial Durbin model and threshold model. We found that the digital economy improved the HDME of local and neighboring regions, and the sub-dimensional indicators had a significant heterogeneous effect. The marine industrial structure upgrading only positively affected the quality of the marine economy in neighboring areas. Furthermore, the digital economy and marine industrial structure upgrading also had synergistic effects on improving the marine economy, which mainly depended on digital infrastructure and digital industrialization. There also existed digital infrastructure and digital industrialization thresholds within marine industrial structure upgrading, affecting the HDME. Our results provide new insights for the green and sustainable development of the marine industry and marine economy from a broader technical perspective in the digital age. Governments should recognize the spatial spillover and synergistic effects of the digital economy and marine industrial structure between different regions and implement policies considering their impacts to achieve the marine sustainable development goals.

The Effect of Corporate Social Responsibility Characteristics on Employee Green Behavior: A Moral Emotions Perspective

Shaping green employees is a source of sustainable competitive advantage for enterprises. However, previous studies have lacked consideration of the moral aspects of employee green behavior (EGB), thus ignoring the mechanism of employee moral psychology, especially the important impact of moral emotions on EGB. Based on the affective events theory, we built a moderated mediation model to test how corporate social responsibility characteristics (CSRCs) affect EGB and to explore the role of organizational pride (OP) and the environmental passion climate (EPC) in this process. SPSS25.0 and Mplus8.0 were used to analyze data from 267 valid questionnaires. The results show that CSRCs' positive effect required EGB and OP to play a mediating role in the relationship between them. In addition, EPC had a negative moderating effect on the effect of OP on required EGB. These results expand the theoretical territory of EGB from the perspective of moral emotions. In practice, the results provide a moral motivation for cultivating employees’ ecological literacy and stimulating EGB as well as management strategies for organizational environmental protection practice and green sustainable development.

Renewable energy waste recycling

Broad field of technologies is related to the countries’ green hydrogen goals, with renewable energy technology (RE) being a significant part. RE’s ability to support green hydrogen industry is now being hindered by the waste issue. By 2050, the world will have accumulated up to 60–70 million tons of waste photovoltaic (PV) modules, 43.4 million tons of wind turbine blades and up to 1 million tons of lithium batteries. Existing technologies and recycling capacities are not capable of recycling these volumes, since the readiness levels of most of the applicable technologies is assessed as TRL3 - TRL8 and their economic efficiency is below the profitability level. The purpose of this work is to substantiate the need and calculate the amount of state support for the development of RE waste recycling technologies. It has been determined that the sum of economic losses in the absence of recycling by 2050 will amount to up to 215 billion dollars, including in the RE leading regions: in China 81 billion dollars, in the EU 42 billion dollars, in the USA 26 billion dollars. The regional distribution of waste volume is presented, grouped by energy price level: 30% of waste in countries with the highest energy tariffs, mainly in Europe, 20% in regions with an average price, including all of North America, 50% in regions with the lowest price - most Asian countries. The dynamics of the increase in the number of patents for the selected IPCs for the period 2000–2024 was obtained, and the leading countries were identified. It is shown that the effect of state support for recycling will be obtained in three industries: firstly, a cost-effective industry for recycling renewable energy waste will be formed, secondly, the availability of scarce materials for renewable energy producers will increase, and thirdly, unconstrained RE deployment will back the green hydrogen development. The timeframe of the countries’ hydrogen goals and the RE waste accumulation trends jointly indicate the urgency of the waste issue, when the analysis proves the reasonable request for the state involvement.

A novel corrosion inhibitor for copper in sulfuric acid media: Complexation of iodide ions with Benincasa Hispida leaf extract

In the context of green and low-carbon development, the rapid development of industry brings the problem of metal corrosion costs increase, metal corrosion protection methods are of great concern. Extracts from Benincasa hispida leaves (BHLE), which were obtained through pressurised liquid extraction, were employed as a inhibitor for copper corrosion in 0.5 M H2SO4. Their composition and anti-corrosion properties were subsequently analyzed and evaluated. The electrochemical analysis results indicated that BHLE functions as a cathodic-type corrosion inhibitor. The anti-corrosion performance intensifies with the increase in concentration but diminishes gradually as the temperature rises, when the concentration of BHLE is 400 mg/L, the corrosion inhibition efficiency can reach 91.82 %, when the concentration of added potassium iodide reaches 16 mg/L the slow-release efficiency of the compounded corrosion inhibitor reaches 96.92 %. The addition of I− strengthens the inhibition efficiency through the adsorption form dominated by competitive adsorption. The adsorption of BHLE onto the surface of copper follows the Langmuir monolayer adsorption model.

Progress and Hotspot Analysis of Bibliometric-Based Research on Agricultural Irrigation Patterns on Non-Point Pollution

With the constant advancement of irrigation technology and the continuous expansion of irrigation areas, non-point source pollution (NPS) caused by agricultural activities has posed a persistent threat to ecosystems and biological safety. Against this backdrop, it is imperative to lay scientific foundations for green, sustainable, and high-quality agricultural development through a thorough review of the relevant research progress. In this study, bibliometric methods are adopted to comprehensively analyze and visualize the current state and key literature on agricultural irrigation and NPS pollution from 2010 to July 2024. The focus of this study is specifically on summarizing the research hotspots and development trends of different irrigation methods and the mechanisms behind their impacts on NPS pollution. The results indicate that publications from the United States and China account for 63.8% of the total, but the fragmentation of research efforts remains, suggesting a necessity to strengthen international and regional collaboration. There are three institutions with the highest publication output, namely Northwest A&F University, Hohai University, and the Chinese Academy of Sciences. The subjects identified as the key areas of research on irrigation-related NPS pollution (IRR-NPS) include precision irrigation, rapid water pollution response, spatiotemporal management, interdisciplinary integration, wastewater treatment, and crop models. Regarding future research, it is necessary to focus attention on real-time precision irrigation, standardized crop models, data accuracy, spatiotemporal pollution coordination, pollution purification technology development, interdisciplinary integrated governance, and the innovative applications of soil improvement technologies. In addition to offering theoretical support and practical guidance for the management of agricultural NPS pollution, this study also provides management and technical support for policymakers, which is beneficial for advancing agricultural irrigation technology and environmental preservation.

Application and Prospect of Artificial Intelligence Technology in Low-Carbon Cities—From the Perspective of Urban Planning Content and Process

In the era of digital transformation, artificial intelligence (AI) technology—one of the swiftest growing emerging technologies—when integrated with urban planning, can introduce innovative approaches for low-carbon city development and foster the attainment of dual carbon objectives: carbon neutrality and peak carbon emissions. Current research predominantly investigates the influence and alterations of emerging technologies on urban elements, yet it overlooks a comprehensive examination of the applicable procedures of these technologies and their potential synergy with urban planning. Consequently, this study employs a systematic literature review to delve into the application of AI in sectors such as architecture, transportation, land use, and green space development. It categorizes the specific impact processes into monitoring, identification, simulation, and prediction. By offering an exhaustive analysis of urban planning’s content and methodology, this paper elucidates the role of AI technology in the creation of low-carbon cities. The study found that: (1) Due to the varying degrees of application and integration with professional technologies in different fields, the current research focuses more on architecture, land use, and transportation. (2) Combining the four steps of urban planning, artificial intelligence can be divided into monitoring, recognition, simulation, and prediction types, each with its own characteristics. (3) Overall, AI technology is mainly applied in the identification and simulation of architecture, transportation, and land use. (4) There is still room for improvement in the application of AI technology in waste emissions and other algorithms.

Mineral resource dependence and green transformation: the impact and challenges of green finance in Chinese cities

Overcoming the resource curse while balancing environmental protection and economic growth presents significant challenges. We developed an evaluation system to measure the green economic efficiency (GEE) of 262 cities and introduced the concept of the mineral resource curse. This study investigates both linear and non-linear relationships between mineral resource dependence (MRD) and GEE, as well as the role of green finance in this context. To address the endogeneity issue arising from the bidirectional causality between MRD and GEE, we used the interaction of relief degree of land surface and time as instrumental variables (IV). The empirical results indicate that a city’s MRD significantly inhibits GEE. Specifically, an increase in MRD hinders GEE by reducing green investment and crowding out green credit. By categorizing cities according to resource cycle theory, we found that non-resource-based and regenerative cities effectively avoided the mineral resource curse. However, resource-based, growing, mature, and declining cities did not benefit from their mineral resources. This conclusion remains robust even after changing IV and using various estimation methods such as IVTOBIT. Furthermore, this study discusses the practical effects of green finance. We found that green investment has a limited impact, failing to offset the negative influence of MRD on GEE. Under the influence of green credit, the relationship between MRD and GEE exhibits an inverted U-shape. This finding highlights the limitations of green finance policies at the municipal level in China. Overall, this study provides new evidence for improving China’s green finance system and promoting green economic development. It offers a fresh perspective for China and other developing countries in their green transformation efforts and avoidance of the mineral resource curse.

Spatial benefit difference of fertilizer reduction and substitution policy based on grid scale: A case study of the Heihe River Basin

Agriculture green development faces the challenge of balancing the application of both organic and chemical fertilizers. Formulating effective policies to harmonize these applications is essential for ensuring food security and environmental sustainability. However, there is a lack of studies investigating the economic and environmental benefits of policy implementation at the grid scale, and insufficient research has been conducted on the subsequent impacts these policies have on diverse crops. Therefore, this paper develops the SIMPLE-G-Heihe model to simulate the impacts of green agricultural policies on multiple crops planting in arid regions. This model addresses limitations found in the SIMPLE-G model, which supported a single crop and lacked organic fertilizer substitution simulation. The results show that: (1) Merely increasing subsidies for organic fertilizers is insufficient to significantly enhance yields, and improving the efficiency of fertilizer utilization should also be emphasized. (2) Combining improvements in fertilizer technology with subsidies for organic fertilizers can concurrently support economic advancement and environmental mitigation. Research indicates that integrating a 3% organic fertilizer subsidy with an 8% improvement in chemical fertilizer technology increases vegetable output value by 0.27% and reduces N2O emissions by 1.09%. (3) The upstream areas of the Heihe River Basin show a significant reduction in fertilizer use. Fertilizer input is mainly reduced for vegetables in the upstream areas, while for wheat and maize, the reduction is primarily in the midstream and upstream areas. The findings discuss the spatial heterogeneity and flexibility of policy impacts, providing valuable insights for the implementation of green agriculture strategies in China.

Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network

AbstractThe study utilizes the RBF neural network model to evaluate the green development of the Pearl River Delta urban agglomeration, revealing a consistent increase in development levels from 2005 to 2020 despite notable inter‐city variations. The model adeptly handles complex interactions within urban green development, offering insights into comprehensive impacts and aiding in policy evaluation and optimization. It provides urban planners and decision‐makers with data‐driven support, enhancing the scientific basis and stability of policy‐making.

The Impact of National Big Data Pilot Zones on the Persistence of Green Innovation: A Moderating Perspective Based on Green Finance

Enhancing the persistence of corporate green innovation is crucial for promoting sustainable societal development. As big data technologies and related policies advance, digitalization emerges as an effective enabler of green innovation in enterprises. This study, grounded in resource-based theory and corporate ecology theory, examines the impact of national-level big data pilot zone reforms on the persistence of corporate green innovation, utilizing data from China’s A-share-listed companies from 2011 to 2021. It also explores the moderating effect of green finance development. Empirical results indicate that (1) the implementation of national-level big data pilot zones positively influences the persistence of green innovation, with robustness and endogeneity tests confirming these findings. (2) The development of regional green finance positively moderates this relationship. (3) A mediation analysis reveals that national-level big data policies enhance innovation persistence by alleviating financing constraints, promoting talent aggregation, and facilitating industrial upgrading. (4) The heterogeneity analysis shows that the positive impact of these reforms is more pronounced in non-state-owned, non-heavy polluting firms, those receiving high subsidies, and in regions with stringent environmental regulations. This study offers a novel theoretical perspective on and empirical evidence for digital transformation from the angle of national policy, supporting societal green development and contributing to policy enhancement aimed at achieving sustainable growth.

Use Efficiency, Reduction Potential, and Effects of Fertilizers on Carbon Emissions in China’s Major Citrus Regions

Enhancing the efficiency of fertilizer utilization and advancing fertilizer reduction efforts constitutes a pivotal initiative for augmenting the quality and productivity of the citrus industry; this constitutes an indispensable prerequisite for attaining green and sustainable development. Utilizing panel data from seven prominent mandarin-producing regions and seven prominent tangerine-producing regions in China spanning from 2002 to 2022, this study employed the stochastic frontier analysis (SFA) method to develop a translog production function model for precisely measuring the fertilizer use efficiency for mandarins and tangerines. Employing the calculated optimal fertilizer use rates, we further ascertained the fertilizer reduction potential for mandarin and tangerine; then, we estimated the associated carbon emission reduction potential within these key citrus regions. The research revealed the following findings: the overall level of citrus fertilizer use efficiency in China is comparatively low, with the mean values for mandarin and tangerine fertilizer use efficiency being merely 0.4403 and 0.3887, respectively, indicating substantial room for improvement by approximately 60%; substantial potential exists for decreasing fertilizer use in China’s citrus industry, with average reduction potentials of 66.27% for mandarins and 64.83% for tangerines, signifying a notable redundancy in fertilizer application within major citrus-producing areas. The magnitude of carbon emission reduction potential through the diminution of citrus fertilizer use is tremendous. When optimal fertilizer rates are applied, the average carbon emission reductions resulting from fertilizer reduction in mandarins and tangerines amount to 815.8681 kg/hm2 and 602.3551 kg/hm2, respectively. The average carbon reduction potential for mandarins and tangerines reach levels of 55.9673% and 61.1299%, respectively, both surpassing the threshold of 55%. Significant differences exist in the technical efficiency of fertilizer input, reduction potential, and carbon emission mitigation potential among major citrus-producing regions. Citrus orchards in Guangdong exhibit higher potential for fertilizer reduction but demonstrate a relatively low level of technical efficiency. In contrast, Hunan Province shows an opposite trend, necessitating the development of region-specific strategies. Therefore, to minimize citrus fertilizer use and augment the technical efficiency of citrus fertilizer, it is imperative to comprehensively integrate and promote the “three new” technologies aimed at reducing fertilizer use and enhancing its efficiency within the citrus industry; implement a regional coordinated development strategy for citrus fertilizer reduction; and intensify policy guidance, publicity, and training efforts related to citrus fertilizer reduction, efficiency enhancement, and carbon emissions reduction.

Dynamic Integrated Scheduling of Production Equipment and Automated Guided Vehicles in a Flexible Job Shop Based on Deep Reinforcement Learning

The high-quality development of the manufacturing industry necessitates accelerating its transformation towards high-end, intelligent, and green development. Considering logistics resource constraints, the impact of dynamic disturbance events on production, and the need for energy-efficient production, the integrated scheduling of production equipment and automated guided vehicles (AGVs) in a flexible job shop environment is investigated in this study. Firstly, a static model for the integrated scheduling of production equipment and AGVs (ISPEA) is developed based on mixed-integer programming, which aims to optimize the maximum completion time and total production energy consumption (EC). In recent years, reinforcement learning, including deep reinforcement learning (DRL), has demonstrated significant advantages in handling workshop scheduling issues with sequential decision-making characteristics, which can fully utilize the vast quantity of historical data accumulated in the workshop and adjust production plans in a timely manner based on changes in production conditions and demand. Accordingly, a DRL-based approach is introduced to address the common production disturbances in emergency order insertions. Combined with the characteristics of the ISPEA problem and an event-driven strategy for handling dynamic events, four types of agents, namely workpiece selection, machine selection, AGV selection, and target selection agents, are set up, which refine workshop production status characteristics as observation inputs and generate rules for selecting workpieces, machines, AGVs, and targets. These agents are trained offline using the QMIX multi-agent reinforcement learning framework, and the trained agents are utilized to solve the dynamic ISPEA problem. Finally, the effectiveness of the proposed model and method is validated through a comparison of the solution performance with other typical optimization algorithms for various cases.

Exploration of the advantages of targeted isolation of deep-sea microorganisms and genetically engineered strains.

Oil, mineral processing and environmental restoration can be dangerous processes. Attempts are often made to apply microorganisms to reduce the risks, but the adaptability of terrestrial organisms is often weak. Although genetically engineered strains can improve their environmental adaptability through targeted modification, there are problems such as metabolite accumulation, poor plasmid stability and potential pathogenicity. Screening of extremophiles from the natural environment has become an inevitable choice. The special environment in the deep sea (high pressure, low temperature, low nutrition, high salinity) is a natural place for extremophiles to grow and survive, thus screening of extremophiles from the deep sea is conducive to the green and sustainable development of industry. In this paper, the application status and problems of genetically engineered strains are reviewed based on the microorganisms needed for extreme industry. This paper focuses on the application status and advantages of deep-sea microorganisms. It is found that their advantages are strong adaptability, stable gene, friendly environment, simple and convenient technology (compared with genetic engineering), which has a broad industry processes application prospect. This review broadens the scope of microbial applications.

Bank-firm common ownership, green credit and enterprise green technology innovation: Evidence from Chinese credit markets

Bank-firm common ownership can tackle the innovation dilemma of bank loans on firms' green development. This paper constructs indicators of common ownership and green technological innovation and then investigates the impact of bank-firm common ownership on corporates' green technological innovation using Chinese A-share listed enterprises samples from 2004 to 2021. Our conducted experiments reveal that bank-firm common ownership shareholders not only make banks and lending firms have the same goal, promote the total level, quantity, and quality of technological innovation for the green development of lending firms, and profit from the firms' short- and long-term market responses. Our findings are prominent in private enterprises, small-capitalization enterprises, and bull market cycles. In addition, we discover that shareholder reduction restrictions and policies restricting corporate shareholding in financial institutions enhance bank-firm common ownership shareholders on corporate green technological innovation development. Common ownership shareholders reduce information asymmetry between banks and lending enterprises and provide green loans to support enterprise green technology innovations. Furthermore, alleviating financing constraints and strengthening the supervisory role are important influence mechanisms. In this regard, carried PSE analysis indicates the direct effect of bank-firm common ownership shareholders to promote enterprise green development of technological innovation accounts for about 14 % of the total effect, the intermediary effect of “financing mechanism” and “supervision mechanism” account for about 82 % and 4 %, and the “financing mechanism” is more important than the “supervision mechanism.” The findings of this paper can optimize the credit market to serve the green and high-quality development of Chinese enterprises better.