This paper examines the impact of green finance on urban carbon emission performance by utilizing panel data from 280 prefecture-level cities in China from 2012 to 2022. The results indicate that the development of green finance can improve carbon emission performance. Mechanism analysis reveals that green finance enhances carbon emission performance by promoting industrial structure upgrades and green technological innovation, and this conclusion is confirmed through a series of robustness tests. Heterogeneity analysis shows that the impact of green finance on carbon emission performance is more significant in non-resource-based cities and in eastern regions. Based on these findings, this paper offers relevant policy recommendations, providing useful insights for improving urban carbon emission performance in China.
Urbanization has caused a great burden in waste management, along with the introduction of Waste-to-Energy (WtE) technology and the development of related waste treatment and renewable energy production. This paper perceived global WtE technology in respect of decarbonization of the power industry by comparing incineration, anaerobic digestion, gasification, and pyrolysis. It highlighted the necessity to shift the conventional landfill practices to the use of WtE plants, which would reduce the landfill amounts and generate biogas, syngas, and digestate as by-products with a high level of nutrients. This article evaluated the energy value of waste materials and provided an account of the adoption of WtE energy infrastructure both in Europe and Asia-Pacific. It dealt with the problems of developing economies like population growth, lack of sufficient regulations, a high cost of capital markets and other technological issues. The carbon capture and life cycle analysis to sustain WtE, as well as its implications on the environment and employment were discussed. The paper concluded with recommendations on policies, research, and development by emphasizing the imperatives of well-established cooperation among stakeholders, technological adjustments as well as investments in innovations.
Against the backdrop of the “Dual Carbon” goals and the global green transformation of supply chains, the food supply chain characterized by high carbon emissions, significant losses, and stringent time-sensitive requirements imperatively transitions from the traditional “efficiency-first” model to a “dual-driven, efficiency-low carbon” approach. There is a scarcity of existing research to address the limitations encountered in the optimization of single transportation mode and the coordination of multiple constraints. In this light, the current paper focused on the two-stage location-route problem, in order to construct a collaborative optimization model that integrates the location selection of transfer stations with route planning. By dynamically determining the layouts of transfer stations via an enhanced K-means clustering algorithm and introducing capacity constraints and moment of inertia analysis, the accuracy of site selection could be improved. This approach resolved issues of random initialization and load imbalance inherent in traditional clustering. The design of an adaptive ant colony optimization (ACO) algorithm could incorporate heuristic information such as load utilization rate and time window tightness, while optimizing the pheromone update mechanism to balance transportation costs, carbon emissions, and time constraints. The proposed collaborative delivery model effectively integrated the economies of scale from trunk transportation with the flexibility of last-mile delivery, so as to achieve optimization of facility locations and route planning. Experimental validation demonstrated that the improved algorithm significantly outperformed traditional methods in the quality and stability of solutions. It also provided an optimized path for food supply chain networks that balanced economic and environmental benefits. This research offers theoretical support for the transformation of green logistics; it can also be extended to future studies by incorporating real-time data and dynamic scenarios for effective carbon reduction across the entire supply chain.
This study focused on assessing and prioritizing carbon emission reduction strategies in Quang Ngai province in Vietnam, through an integrated Strengths, Weaknesses, Opportunities, and Threats (SWOT) and Analytic Network Process (ANP) approach. SWOT factors were identified through semi-structured interviews with a panel of 12 experts with expertise in environmental management, renewable energy, sustainable development planning, and local resource governance. This method allowed the identification of internal factors (strengths, weaknesses) and external factors (opportunities, threats) of the province. It also quantified the priority level of each criterion and strategy to support strategic decision-making in a scientific and transparent manner. Based on the results of the SWOT-ANP analysis, the priority level of carbon emission reduction strategy groups in Quang Ngai province was determined by the Utility Index (U) as follows: WO = 0.2867, SO = 0.2410, WT = 0.2389, and ST = 0.2334. Among them, the WO strategy (overcoming weaknesses to take advantage of opportunities) had the highest U value, showing that this was the top priority orientation which focused on improving technological, financial, and infrastructural capacity to meet the trend of green transformation and attract international resources. Next was the SO strategy (U = 0.2410), taking advantage of natural advantages and current policies to expand renewable energy projects, low-carbon agriculture, and green industry development. The two strategic groups, WT (U = 0.2389) and ST (U = 0.2334), had lower values but still played an important supporting role, thus contributing to minimizing risks due to limited resources and enhancing adaptability to the challenges of climate change. The research not only contributes to the development of carbon emission reduction solutions in the specific context of Quang Ngai but also opens up a reference for other localities. It helps to optimize emission reduction strategies in accordance with the specific economic, social, and environmental conditions in each region.
Local knowledge plays an important role in maintaining a balance between humans and nature, especially in traditional agroforestry systems such as Repong Damar in Pekon Tanjung Setia. This study aims to analyze the system of inheriting local knowledge in the management of Repong Damar to preserve the ecology, economy, and culture of the community. A case study was adopted with a qualitative approach in the current research. The collection of data was conducted by participatory observation, in-depth interviews, and documentation. The data were then analyzed to obtain results related to the local knowledge inheritance system for managing the Repong Damar land. The sample was determined by purposive sampling with the following key criteria for informants, i.e., indigenous Tanjung Setia Village residents with profound experience and knowledge regarding Repong Damar land management. Key informants consisted of one village head, three traditional leaders, and five Damar farmers. Results of the study, based on observations from August to November 2025, showed that the inheritance of local knowledge was carried out from generation to generation through direct practice in the family and community environment. Inherited knowledge includes tapping techniques, nurseries, land management as well as social, spiritual, and ecological values. This inheritance process strengthens the attachment of the community to Repong Damar as a source of economic and cultural identity. Despite the challenges from the declining interest of the young generation in the agricultural sector, conservation is still being carried out through daily practices and informal education. The local knowledge inheritance system in Pekon Tanjung Setia is the foundation for the sustainability of Repong Damar, which maintains a balance between ecological and socio-cultural functions. These findings confirmed the importance of preserving local knowledge as an adaptive strategy in maintaining the sustainability of traditional agroforestry in Indonesia.
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