With economic globalization, the supply-and-demand gap of China’s minerals is becoming increasingly sharp, and the degree of dependence on imports is climbing, which poses a severe threat to the resource security for the country. From the perspectives of system and sustainable development, this paper develops a conceptual framework of mineral security, which is composed of five dimensions: availability, accessibility, technology and efficiency, sociability and governance, and environmental sustainability. Based on this framework, it constructs the evaluating metrics for measuring mineral security. Moreover, it employs the hybrid multiple criteria decision-making methods of Fuzzy analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) to assess the security performance for China’s several critical minerals, namely iron, copper, aluminum, lead, zinc, and nickel, with respect to the period of 2001 to 2015. The result indicates that the critical minerals of China were at a low to moderate level of security. Iron, copper, and nickel were in an unsecure situation for their short supply in China, and showed a downswing trend. On the other hand, as the preponderant minerals, lead and zinc were at a relatively secure position and uprising; however, they were exhausting their superiority for the huge and rapid-growth economic demand. Aluminum, as a mineral that China seriously depends on for imports, also demonstrated an upward trend due to the successful management of diversity of importing sources.

Biomass is viewed as one of the critical renewable energies and it widely exists in nature. Developing bioenergy has been promoted as a viable mean of dealing with environment issues that are related to the utilization of fossil fuel. However, due to many obstacles, the biomass and bioenergy technology has not won widespread support in developing countries, like China, with vast land area, particularly in rural area. Furthermore, most existing researches just focused on the description of the influence factors, along with the solution to the technical problems, while many social factors are overlooked. In fact, the process of developing biomass is indeed complicated due to the need for consensus and active participation of the various stakeholders, such as the government, the industry, and the local residents. Therefore, while integrating the intuitionistic fuzzy logic and fuzzy cognitive map, this study constructs an intuitionistic fuzzy cognitive map (IFCM) that is in line with experts’ suggestions and the current literature to investigate how to promote the development of biomass through enhancing public acceptance. We conduct several simulations from the perspective of different stakeholders, according to the IFCM. The analysis results reveal the influence mechanism in the system and illustrate the effect of various factors that are stressed by every stakeholder. The research design also provides a reference for future studies.

In China, absolute poverty has been effectively eliminated, but this does not signify the complete eradication of poverty. Instead, poverty persists in the forms of relative and secondary poverty. More concerningly, regions or households lifted out of poverty continue to face numerous risks of returning to poverty. In this context, measuring poverty solely based on monetary metrics is no longer adequate. Furthermore, the primary focus of grassroots governance has shifted from merely assessing poverty to accurately predicting the multifaceted risks associated with falling back into poverty. A multidimensional poverty indicator system is constructed to measure and predict the risk of multidimensional returning to poverty in China. Then, the Alkire–Forster counting method is applied to measure the risk of multidimensional poverty return and demonstrate the contribution of various indicators to multidimensional poverty return using tracking survey data from the China Family Panel Studies (CFPS). The results show that the multidimensional poverty return in China is mainly caused by the factors in two or three dimensions, where the social development capability dimension has the highest contribution to the multidimensional poverty return index with 43.12 %, followed by the health and education dimensions. Moreover, according to the finding that the identification of multidimensional poverty varies with the values of the poverty cut-off, a novel and practicable method is proposed to classify the risk into three levels, noted as the high, medium and low levels. Consequently, a hybrid model is constructed to predict the risk of multidimensional poverty return by integrating the Archimedes optimization algorithm (AOA), variational mode decomposition (VMD) and Bi-directional long short-term memory (BiLSTM) neural networks. Finally, the performance of the constructed model is validated with an accuracy up to 99.81 %. The constructed model's efforts outperform the traditional BiLSTM and several prevalent machine learning algorithms through extensive comparative experiments. These results illustrate that the proposed model can accurately and stably predict the potential risk of poverty return for multidimensional poverty groups and regions. In conclusion, drawing from the analysis of factors contributing to the risk of relapsing into poverty in this study, policy suggestions have been formulated focusing on education, social capacity enhancement, and healthcare system advancement. In summary, this paper provides new insights into the factors contributing to multidimensional poverty recurrence and the methods for assessing its risk levels, while also introducing a more precise approach to predicting these levels.

According to the strategic plan for rural revitalization and the consolidation of poverty alleviation achievements, this research has developed an evaluation indicator system encompassing three dimensions: environment, social support, and economic resilience, viewed through a sustainable development lens. This system is designed to gauge the capacity to forestall a relapse into poverty in ecologically fragile regions and can also serve as a foundation for the government to establish a comprehensive early-warning and monitoring system. An integrated approach, combining the TOPSIS and entropy methods, was employed to assess the capability to prevent a recurrence of poverty based on data from Enshi Tujia and Miao Autonomous Prefecture spanning 2016 to 2022. Subsequently, the obstacle degree model was utilized to pinpoint critical barriers to enhancing its capability to mitigate the risk of reverting to poverty. The findings clearly indicated that, compared to other regions, Enshi City and Lichuan City maintained the most robust comprehensive capabilities to avert poverty recurrence between 2016 and 2022. Furthermore, the evaluation of capabilities across various dimensions revealed that, with the exception of Enshi City, other counties and cities demonstrated lower capacities in the environmental, social support, and economic resilience dimensions. Moreover, in 2020, the capabilities of all counties and cities deteriorated, and the capabilities under the dimensions of social support and economic resilience had not returned to their former levels by 2022, suggesting that the social and economic systems are susceptible to emergency public crises. A spatiotemporal analysis of the factors impeding the enhancement of capabilities in the counties and cities of Enshi Prefecture showed that the inhibiting factors varied by region, with the most prevalent obstacles stemming from economic resilience. In terms of environmental dimensions, the total regional water supply played a pivotal role in Enshi Prefecture. There was a pronounced regional disparity in the development of capabilities to prevent the recurrence of poverty, and the evolution of systems, such as the environment, social support, and economic resilience, was markedly uncoordinated. Finally, strategic recommendations and measures were formulated to bolster the capabilities to avert returning to poverty in ecologically fragile areas across these three dimensions.

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices.