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This paper is one of the first to offer a comprehensive analysis of the impact of green finance related policies in China, utilizing text analysis and panel data from 290 cities between 2011 and 2018. Employing the Semi-parametric Difference-in-Differences (SDID) we show that overall China's green finance related policies have led to a significant reduction in industrial gas emissions in the review period. Additionally, we found that Fintech development contributes to the depletion of sulphur dioxide emissions and has a positive impact on environmental protection investment initiatives. China is poised to be a global leader in green finance policy implementation and regulators need to accelerate the formulation of green finance products and enhance the capacity of financial institutions to offer green credit. While minimizing the systemic risk fintech poses, policy makers should encourage fintechs to actively participate in environmental protection initiatives that promote green consumption.
Abstract This study investigates the impact of China’s new Environmental Protection Law on the green innovation behaviour of listed companies in high-polluting industries. The implementation of China’s strict and new Environmental Protection Law provides a quasi-natural experimental setting for examining the causal effect of environmental regulation on corporate green innovation. Based on data of the application for environmental patents of high-polluting firms listed in Shanghai and Shenzhen Stock Exchanges from 2010 to 2017, this study analyses the change in the green innovation behaviour of firms after the implementation of China’s new and stringent Environmental Protection Law using the PSM-DID approach. We find that firms tend to file more applications for environmental patents, including patents for inventions and utility models after the implementation of the new Environmental Protection Law. Further analysis shows that while this effect is stronger for state-owned enterprises, it is weaker for firms headquartered in cities where economies depend more on the secondary industry. Firms in concentrated industries have more incentive to file applications for green invention patents than those in competitive industries. The study has important implications for policy makers on better implementing the environmental protection law in developing countries.
Abstract Whether the reform of China’s environmental protection tax will exert an incentive effect or crowding-out effect on enterprises’ green innovation remains unanswered by existing research. Faced with more stringent environmental protection taxes, whether enterprises will adopt substantive or strategic green innovation activities in response is also unclear. This paper uses the implementation of China’s environmental protection tax reform as a natural experiment, based on micro-level enterprises’ green patent data, and uses the triple difference method. The findings reveal: First, the environmental protection tax reform effectively promoted enterprises’ green innovation activities, primarily stimulating green innovation activities aimed at improving fossil fuel efficiency and reducing pollutant emissions at the end of the chain. Green innovation in the new energy sector, which fundamentally reduces pollution emissions, is not significantly enhanced. Second, the green technological innovation induced by this reform is not an incentive effect built upon existing enterprises’ innovation activities but rather a crowding-out effect on other technological innovations. Third, the reform mainly stimulated substantive green innovation activities among non-state-owned enterprises and large-scale enterprises, but the path dependence of green innovation is relatively prominent. This paper provides important empirical evidence for further advancing the improvement of China’s environmental protection tax system.
Dario Cottafava, José R. Nicolás-Carlock, Marcel Llavero-Pasquina
This study investigates the interconnectivity of firms and Environmental Justice Organizations (EJOs) involved in socio-environmental conflicts worldwide, using data from the Environmental Justice Atlas (EJAtlas). By constructing a multilayer network that links firms, conflicts, and EJOs, the research applies social network analysis to evaluate the simultaneous involvement of these actors across multiple disputes. Both projected networks of firms and EJOs have been analysed by aggregating nodes by categories and countries to reveal structural differences. Findings reveal a stark contrast between the interconnectedness of firms and EJOs. Multinational corporations form a cohesive global network, enabling them to coordinate strategies and exert influence across regions. Conversely, EJOs are fragmented, often operating in isolated clusters with limited interconnection but forming a robust, decentralized and self-organized global network. Firms network present a strong dependence on pertaining conflict category while EJOs network does not depend on conflict category. This structural difference suggests a risk of systemic and structural coordination for firms towards exploitative expansion while EJOs dynamics seems to be led by a white blood cells defense-like mechanism. While fragmentation may represents a critical challenge for social movements, decentralization and self-organization show a more diffuse global networks supported by a limited number of central hub able to build stronger global alliances to effectively counter the power dynamics of transnational corporations. By providing robust evidence of these networks, this research contributes to discuss how structural differences in global coordination for companies and EJOs directly derives as emergent properties depending on the purpose of the network itself, sectorial expansion for firms while ecosystem preservation for EJOs.
Noemi Luna Carmeno, Tiago Domingos, Daniel W. O'Neill
Artificial Intelligence (AI) is changing the world, but its impacts on the environment and human well-being remain uncertain. We conducted a systematic literature review of 1,291 studies selected from 6,655 records, identifying the main impacts of AI and how they are assessed. The evidence reveals an uneven landscape: 72% of environmental studies focus narrowly on energy use and CO2 emissions, while only 11% consider systemic effects. Well-being research is largely conceptual and overlooks subjective dimensions. Strikingly, 83% of environmental studies portray AI's impacts as positive, while well-being analyses show a near-even split overall (44% positive; 46% negative). However, this split masks differences across well-being dimensions. While the impacts of AI on income and health are expected to be positive, its impacts on inequality, social cohesion, and employment are expected to be negative. Based on our findings, we suggest several areas for future research. Environmental assessments should incorporate water, material, and biodiversity impacts, and apply a full life-cycle perspective, while well-being research should prioritise empirical analyses. Evaluating AI's overall impact requires accounting for computing-related, application-level, and systemic impacts, while integrating both environmental and social dimensions. Bridging these gaps is essential to understand the full scope of AI's impacts and to steer its development towards environmental sustainability and human flourishing.
3D Gaussian Splatting (3DGS) has become a mainstream representation for real-time 3D scene synthesis, enabling applications in virtual and augmented reality, robotics, and 3D content creation. Its rising commercial value and explicit parametric structure raise emerging intellectual property (IP) protection concerns, prompting a surge of research on 3DGS IP protection. However, current progress remains fragmented, lacking a unified view of the underlying mechanisms, protection paradigms, and robustness challenges. To address this gap, we present the first systematic survey on 3DGS IP protection and introduce a bottom-up framework that examines (i) underlying Gaussian-based perturbation mechanisms, (ii) passive and active protection paradigms, and (iii) robustness threats under emerging generative AI era, revealing gaps in technical foundations and robustness characterization and indicating opportunities for deeper investigation. Finally, we outline six research directions across robustness, efficiency, and protection paradigms, offering a roadmap toward reliable and trustworthy IP protection for 3DGS assets.
Integration of AI into environmental regulation represents a significant advancement in data management. It offers promising results in both data protection plus algorithmic fairness. This research addresses the critical need for sustainable data protection in the era of ever evolving cyber threats. Traditional encryption methods face limitations in handling the dynamic nature of environmental data. This necessitates the exploration of advanced cryptographic techniques. The objective of this study is to evaluate how AI can enhance these techniques to ensure robust data protection while facilitating fair algorithmic management. The methodology involves a comprehensive review of current advancements in AI-enhanced homomorphic encryption (HE) and multi-party computation (MPC). It is coupled with an analysis of how these techniques can be applied to environmental data regulation. Key findings indicate that AI-driven dynamic key management, adaptive encryption schemes, and optimized computational efficiency in HE, alongside AI-enhanced protocol optimization and fault mitigation in MPC, significantly improve the security of environmental data processing. These findings highlight a crucial research gap in the intersection of AI, cyber laws, and environmental regulation, particularly in terms of addressing algorithmic bias, transparency, and accountability. The implications of this research underscore the need for stricter cyber laws. Also, the development of comprehensive regulations to safeguard sensitive environmental data. Future efforts should focus on refining AI systems to balance security with privacy and ensuring that regulatory frameworks can adapt to technological advancements. This study provides a foundation for future research aimed at achieving secure sustainable environmental data management through AI innovations.
In line with the United Nations' sustainable development goals (SDGs), countries are taking action to achieve their carbon reduction goals. Because countries have limited financial resources, it is important for carbon reduction policies that public expenditure is used effectively. Researchers have neglected to probe the environmental quality in European Union countries by considering environmental protection expenditure and renewable energy consumption. This study expands the literature by investigating the impact of renewable energy consumption and environmental protection expenditure on the load capacity factor, which considers both the supply and demand directions of the environment. Hence, this work contributes to the SDG 7 (affordable and clean energy), SDG 6 (clean water and sanitation), and SDG 15 (life on land) targets of European Union-22 countries. The study uses the CS-ARDL approach, which considers cross-sectional dependence, endogeneity, and heterogeneity. Empirical analysis showed that environmental protection expenditure is insufficient for European Union economies. In addition, renewable energy consumption contributed to environmental quality. Based on the outcomes, European Union countries should allocate larger budgets from their general budgets for environmental protection. Policies that can attract the attention of the private sector and not just the public sector should be implemented.
China’s economy is experiencing a rapid revival in the post Covid-19 era, while energy consumption is surging and environmental pressure is prominent. Environmental protection expenditure is an important means for local governments to improve environmental quality; it plays a crucial role in guiding market investment, providing environmental treatment funds and energy conservation and utilization. Based on a sample of 286 prefecture-level cities in China from 2007 to 2017, this study analyzes environmental governance effects of local environmental protection expenditure while considering the time duration, regional differences, and spatial spillover characteristics of industrial pollution emissions. The results reveal that local environmental protection expenditure could help reduce industrial pollution emissions in Chinese cities; however, the governance effects were heterogeneous in different clustering city groups. In addition, the effects of environmental protection expenditure at the neighborhood level varied greatly; the results showed that the stronger the spillover of pollutants, the more significant was the trans-regional governance effect of local environmental protection expenditure. Therefore, local governments should promote a cooperative mode of “joint prevention and control and cross-regional governance” when treating pollutants with strong spillover potential.
Research studies on Metal Organic Frameworks (MOF) based composites and their potential applications in environmental engineering and pollution control have recently emerged. An attractive material to form MOF composites is biochar (BC); a low-cost, highly porous carbonaceous by-product of biomass pyrolysis. This paper presents a critical review on MOF-biochar composites, focusing on fabrication, characterisation, modification, and applications in environmental protection and pollution control. The adsorption mechanisms and influential parameters are systematically examined to develop an insight into interactions between MOF and biochar in remedial process. The adsorption capacity of composites is generally doubled compared to the standalone biochar, while MOFs maintain their crystallinity, even over multiple regeneration cycles, indicating the composites' long-term applicability and sustainability. These findings highlight the potential of MOF-biochar composites for environmental applications and identify key areas for further research to enhance their sustainability in environmental protection and green energy.
Green technology innovation (GI) is a key factor in reconciling environmental protection with sustainable economic development. Routinely, GI in private companies have been delayed due to suspicious of pitfalls investments, which result in low return rates. Nevertheless, the digital transformation of Nations' Economies (DE) might be sustainably sound in terms of natural resources demands and environmental pollution. Energy Conservation and Environmental Protection Enterprises (ECEPEs) database was analyzed from 2011 to 2019 at the municipality level to measure the effect and influence of DE on GI in Chinese ECEPEs. The results suggest that DE has a significant positive influence on GI of ECEPEs. Moreover, the influencing mechanism statistical tests reveal that DE can promote GI of ECEPEs by improving internal controls and financing opportunities. Heterogeneous statistical analysis, however, indicates that the promotion of DE on GI might be constrained over the country. In general, DE can promote both high- and low-quality GI but preferably the latter.
This study aims to examine how these factors-egoistic and altruistic values and social consumption motivation-stimulus factors-influence sustainable consumption behaviour (response factor), the mediating role of pro-environmental self-identity and attitude (organism factor), and the moderating effect of environmental protection emotion. We used the stimulus organism response theory to gain a solid and holistic understanding of the concept. We collected 328 original surveys from Indian customers who recently purchased sustainable products via convenience and purposive sampling, and we analysed the data by using structural equation modelling. Intriguingly, the results show that (a) stimulus factors, such as egoistic and altruistic values and social consumption motivation, had a positive influence on pro-environment self-identity and attitude and sustainable consumption behaviour; (b) pro-environment self-identity had a positive effect on attitude; (c) mediation factors (pro-environment self-identity and attitude) had a significantly positive mediation relationship between stimulus and response factors; and (d) environmental protection emotion significantly moderated the relationship between stimulus, organism factors, and response factors. The study contributes to the current body of knowledge in the area of sustainable marketing by examining the rapidly growing phenomenon of sustainable consumer behaviour.
Abstract Low-cost particle monitors have been widely evaluated in laboratory and ambient monitoring settings, but we have less knowledge about their performance for long-term indoor and outdoor monitoring in residential settings. We seek to provide practical guidance for using a type of low-cost particle monitors that have become widespread for indoor and outdoor monitoring in community field studies, PurpleAir PA-II monitors. We base our insights on experiences in a community-led residential field study in and around homes of predominantly agricultural workers in California’s San Joaquin Valley. Our guidance spans three categories: (1) providing tools for handling and merging disparate data structures resulting from Wi-Fi-transmitted data and data collected on onboard microSD cards, (2) assessing performance metrics of PA-II monitors from laboratory co-location and field measurements, and (3) assessing data collection success rates of Wi-Fi data transmission and microSD card data acquisition from our study locations. The post-processing methods we demonstrate can successfully align data from both Wi-Fi transmission and microSD cards. Laboratory co-location measurements demonstrated that > 90% of the tested monitors performed well relative to each other (high precision), with only a few problematic monitors that warranted further investigation or exclusion from use. The application of co-location factors generated using the mean of all co-located monitors as a reference did not significantly affect distributions of field-measured indoor or outdoor PM2.5 concentrations. Relying solely on Wi-Fi data transmission in our study would have resulted in large data loss (i.e., < 50% success rate); using microSD card storage with PA-II-SD monitors increased the data collection success rate to over 80% in these settings. This work contributes to the growing body of knowledge on low-cost particle sensor performance and usability. Graphical abstract
Thomas B. Fischer, Ben Cave, Shiu Fung Hung
et al.
Abstract In this paper, how changes to environmental aspects considered in strategic environmental assessment (SEA) can affect human health is explored, based on a comprehensive and systematic literature review. Whilst health is a key aspect for consideration in SEA, how it should be approached has remained subject to discussion. There is agreement, though, that at a minimum, health impacts from bio-physical environmental changes need be assessed. What this means is elaborated on in this paper. Challenges to and opportunities for an effective consideration of health in SEA are briefly outlined.