This study focuses on the environmental cost accounting and economic benefit optimization of China’s FAW Hongqi New Energy Vehicle manufacturing enterprise under uncertain conditions, within the context of the emission permit system This study calculates the pollution situation throughout the manufacturing and production process of FAW Hongqi new energy vehicles, and constructs a multi-level environmental cost evaluation system for FAW Hongqi new energy vehicle manufacturing projects. Through the interval fuzzy model of FAW Hongqi new energy vehicle manufacturing projects, the maximum economic benefits of the enterprise are simulated. The research results indicate that the pollution emissions of enterprises are mainly concentrated in the three processes of welding, painting, and final assembly. Enterprises use their own exhaust gas and wastewater treatment devices to meet the standards for pollution emissions. At the same time, solid waste generated during the automobile manufacturing process is handed over to third-party companies for treatment. Secondly, based on the accounting results of enterprise pollution source intensity and a multi-layer environmental cost evaluation system, the environmental costs of enterprises are accounted for, and the environmental costs are represented in interval form to reduce uncertainty in the accounting process. According to the accounting results of enterprise environmental costs, the main environmental costs of enterprises are environmental remediation costs caused by normal pollution discharge and purchase costs of environmental protection facilities. Pollutant emission taxes and routine environmental monitoring costs are relatively low. Enterprises can adopt more scientific solutions from the aspects of environmental remediation and environmental protection facilities to reduce environmental costs. After optimization by the fuzzy interval uncertainty optimization model, the economic benefits of the FAW Hongqi new energy vehicle manufacturing project were [101,254.71, 6278.5413] million yuan. Compared with the interval uncertainty optimization model, the lower bound of economic benefits increased by 57.68%, and the upper bound decreased by 12.08%, shortening the results of the economic benefits interval. Clarify the current environmental pollution situation of FAW Hongqi’s new energy vehicle manufacturing enterprise, provide data support for sustainable development of the enterprise, and provide reasonable decision-making space for enterprise decision-makers.

The economic viability of a photovoltaic (PV) installation depends on regulations regarding administrative, technical and economic conditions associated with self-consumption and the sale of surplus production. Royal Decree (RD) 244/2019 is the Spanish legislation of reference for this case study, in which we analyse and compare PV installation offers by key suppliers. The proposals are not optimal in RD 244/2019 terms and appear not to fully contemplate power generation losses and seem to shift a representative percentage of consumption to the production period. In our case study of a residential dwelling, the best option corresponds to a 5 kWp installation with surplus sale to the market, with a payback period of 18 years and CO₂ emission reductions of 1026 kg/year. Demand-side management offers a potential improvement of 6%–21.8%. Based on the increase in electricity prices since 2020, the best option offers savings of up to €1507.74 and amortization in 4.24 years. Considering costs and savings, sale to the market could be considered as the only feasible regulatory mechanism for managing surpluses, accompanied by measures to facilitate administrative procedures and guarantees for end users.

The rise of fintech in the financial sector presents a transformative shift towards digitalisation and sustainability on a global scale, leveraging technologies like AI to minimise environmental footprint. Neobanks not only challenge traditional banking models but also offer innovative solutions that align with sustainable objectives. The purpose of this paper is to analyse the impact of neobanks on global sustainability from economic, environmental, and social points of view. A comprehensive literature review of existing literature and current sustainable practices of neobanks was conducted. Results reveal that neobanks significantly positively contribute towards environmental sustainability with reduced paper use and logistics requirements of banking services. By offering more accessible and affordable banking services they importantly contribute towards higher financial inclusion, and with innovative products towards more competitive and innovative financial markets. AI-based tools they employ are increasing financial literacy and social inclusion. This article also highlights concerns regarding electronic waste management, potential high energy consumption, required digital literacy and cybersecurity risks. In conclusion, despite the mentioned risks, neobanks importantly contribute to global sustainability in many ways and will even more in the future. These findings can help neobanks shape sustainable practices and guide policymaking, as well as spread awareness of the sustainable impact of banking services.

Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.

The year of 2024 marked the twelfth anniversary of the cooperative mechanism between China and Central and Eastern European countries (China-CEEC). China has repeatedly affirmed its willingness to implement the 2030 Agenda for sustainable development and the sustainable development goals (SDGs), which created many opportunities to enhance the cooperation of the two sides. The paper exemplified some cases in the process of the cooperation, which were rarely discussed previously as normally it was dominated by the large-scale investment project. The cases of the climate change and ocean issues were perceived as a package of holistic EU-China relations that demonstrates the commitments from both sides to deal with SDG 13 and SDG 14. A qualitative method of the policy-circle evaluation and the goal-setting in the global governance was applied in the paper. The findings affirm that the current China-CEEC cooperation scheme is still carrying on both opportunities and challenges and affected by various internal and external factors.

Developing “New Quality Productive Forces” (NQPFs) has been accepted as a new theory to accelerate the high-quality development in China. In current, China’s high-quality development mainly relies on the traction of the digital economy. In view of this, developing NQPFs in China’s digital economy sector requires locate and remove some obstacles, such as the insufficient utilization of data, inadequate algorithm regulation, the mismatched supply and demand of regional computing power and the immature market environment. As a solution, it is necessary to allocating data property rights in a market-oriented way, establishing a user-centered algorithm governance system, accelerating the establishment of the national integrated computing network, and maintaining fair competition to optimize the market environment.