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In this study, we investigated the influence of overall financial development and its components on energy consumption using the panel data of 120 countries and the generalized method of moments (GMM). By dividing the sample into developed and developing countries, we further examined the national differences of the impact of financial development on energy consumption. The empirical results indicate that the overall financial development significantly positively impacts energy consumption from a worldwide perspective, and its two components (financial institution and the financial market) have the same effect. The analysis of national differences indicates that the financial development also positively impacts energy consumption in developing countries but with no obvious effect in developed countries. The results also suggest that financial development cannot be used to restrain the increase in energy consumption from the global perspective, and policymakers in developing countries must balance the relationship between the development of the financial sector and energy consumption.

As a relatively mature technology, biomass molded fuel (BMF) is widely used in distributed and centralized heating in China and has received considerable government attention. Although many BFM incentive policies have been developed, decreased domestic traditional fuel prices in China have caused BMF to lose its economic viability and new policy recommendations are needed to stimulate this industry. The present study built a regionalized net present value (NPV) model based on real production process simulation to test the impacts of each policy factor. The calculations showed that BMF production costs vary remarkably between regions, with the cost of agricultural briquette fuel (ABF) ranging from 86 US dollar per metric ton (USD/t) to 110 (USD/t), while that of woody pellet fuel (WPF) varies from 122 USD/t to 154 USD/t. The largest part of BMF’s cost composition is feedstock, which accounts for up 50%–60% of the total; accordingly a feedstock subsidy is the most effective policy factor, but in consideration of policy implementation, it would be better to use a production subsidy. For ABF, the optimal product subsidy varies from 26 USD/t to 57 USD/t among different regions of China, while for WPF, the range is 36 USD/t to 75 USD/t. Based on the data, a regional BMF development strategy is also proposed in this study.

This study aims to explore the application of fractional order chaotic system (FOCS), based on the T-S fuzzy model, in the design of secure communication (SC) and this SC system’s role in the construction of efficiency evaluation system for dispatching operation of energy saving and power generation under a low carbon economy (LCE). First, the definition of fractional order differential equations and the stability theory of FOCS are discussed. T-S fuzzy control is introduced to analyse the stability of FOCS. Then, based on the adaptive synchronisation theory, the combined FOCS is designed for SC, and the performance of the system constructed here is analysed in a MATLAB environment. Next, an evaluation index system of the dispatching operation effect of energy saving and power generation under LCE is constructed. The confidential communication system constructed here is used to transmit the index data. The particle swarm optimisation (PSO) algorithm is then used to optimise the back propagation neural network (BPNN) model. The BPNN algorithm based on PSO (PSO-BPNN) is obtained, and the evaluation model is constructed. After training this model, it is applied to the evaluation of the dispatching operation effect for energy saving and power generation in 10 provinces in China. The simulation results show that the FOCS based on the T-S fuzzy model can acquire the criterion of system stability. Furthermore, the constructed SC system can effectively undertake the secure transmission of square and sine waves. The performance of the PSO-BPNN model seems to be better than other algorithms. After analysing the data on energy saving and power generation from 10 provinces in China using this model, the comprehensive evaluation value of province 5 is found to be the highest and good (0.802), while that of province 4 is the lowest and general (0.600). Summarising, the FOCS based on T-S fuzzy model constructed here is applied to the design of SC. This can improve the confidentiality of data transmission and reduce the transmission error. Moreover, the BPNN evaluation model based on PSO can effectively achieve the evaluation of the dispatching operation effect of energy saving and power generation under LCE.

Exploring the sensitivity of rural households’ livelihood strategies to livelihood capital is of great significance for improving rural households’ livelihood levels. This paper selects 23 livelihood capital measurement indicators and conducts an in-depth survey of rural households. In addition, the entropy method and a weighted comprehensive model are used to explore the basic characteristics of rural households’ livelihood capital in the upper reaches of the Min River, China, in 2017. Furthermore, econometric models are used to analyze the sensitivity of rural households’ livelihood strategies to livelihood capital. As indicated from the research, the livelihood capital levels of different types of rural households in the study area are not equivalent. The types of rural households with different livelihood strategies can be ordered in terms of quantity as follows: non-agricultural type > non-agricultural dominant type > agricultural dominant type > pure agricultural type. Livelihood strategies have different sensitivities to different livelihood capital measurement indicators. Among these indicators, cash income, the number of relatives and friends available for financial assistance, and the number of civil servants have positive effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households. However, the average age of laborers, area of cultivated land and gardens, number of livestock and poultry, and present value of production tools have negative effects. These evaluation results can provide a scientific decision-making basis for the formulation of poverty alleviation policies by relevant government departments.

As an important livelihood strategy choice to promote the sustainable development of themselves and regions, returnees’ entrepreneurship has played a vital role in the governance of all-level Chinese local governments since the 21st century. The policy attention reflects the importance that the local governments attach to this issue, and the evolution process also reflects relevant policies’ internal rules and characteristics. Based on this, this paper, taking 242 policy texts related to returnees’ entrepreneurship issued by local governments from 2000 to 2021 as the research objects, uses grounded theory and social network analysis in order to explore the policy attention evolution from the aspects of time, space, specific policy domains and cooperative relationship among policy subjects. Finally, this research finds the main conclusions as follows: (1) The policy attention evolution on time dimension has the characteristic of synchronism, different levels and “reciprocal U”. (2) The policy attention evolution on space dimension is closely linked to “pull” and “push” forces of local population flow and has neighborhood effects. (3) The policy attention evolution on specific policy areas will gradually spread and diversify with the change in local governance environment and stage goals. (4) The evolution trend of collaborative social network among policy objects has the characteristic of “loose-central-loose”.

The generally adopted worldwide target is to keep the increase in the global mean temperature lower than 2 °C by 2100, which is comparable with that of the preindustrial era. It is feasible for China to realize an emission pathway that is consistent with this target, however, we need to understand the roadmap to do so. In this paper, the results of a modeling study by the Integrated Policy Assessment Model for China (IPAC) concerning the investment required to realize the 2 °C scenario by examining the penetration of low-carbon technologies including energy supply and energy efficiency improvement in end-use sectors is presented. It is found that the investment required in the energy supply sector to realize the 2 °C scenario could reach CN¥1.2 trillion by 2020, CN¥1.0 trillion by 2030, and CN¥1.4 trillion by 2050. The investment needed for energy saving could reach CN¥1.6 trillion by 2020, CN¥1.8 trillion by 2030, and CN¥1.5 trillion by 2050, which represents the additional investment as compared with the use of old technologies. If the investment required both in the energy supply sector and in energy saving in end-use sectors is considered, the total investment is estimated to be CN¥2.8 trillion by 2020, CN¥2.8 trillion by 2030, and CN¥2.9 trillion by 2050. These investments account for 2.5% of Chinas total GDP in 2020, 1.3% in 2030, and 0.6% by 2050, which represents quite a small investment percentage to realize the goal of low-carbon development.

The study investigates the nexus of CO2 emissions, tourism, fossil fuels, and GDP growth using China’s data from 1970 to 2019. The research applied the upset U-molded EKC and the ARDL -models to calculate the time series stationarity variables. The results showed that in the initial enlargement phases, a sophisticated GDP adversely impacts CO2 emissions, then a higher GDP positively influences CO2 emissions. The development of tourism, use of fossil fuels (coal and oil), and population growth show an important influence on CO2 emissions but the use of gas and electricity has little effect on CO2 emissions. In contrast, foreign direct investment besides population development had little effect on increasing CO2 emissions. Retreating foreign direct investment, strengthening the use of sustainable electricity, and improving transportation for explorers, especially the green tourism business, are excellent ways to reduce environmental degradation in China.

The optimization of the production process of metal mines has been traditionally driven only by economic benefits while ignoring resource efficiency. However, it has become increasingly aware of the importance of resource efficiency since mineral resource reserves continue to decrease while the demand continues to grow. To better utilize the mineral resources for sustainable development, this paper proposes a multi-objective optimization model of the production process of metal mines considering both economic benefits and resource efficiency. Specifically, the goals of the proposed model are to maximize the profit and resource utilization rate. Then, the fast and elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize the multi-objective optimization model. The proposed model has been applied to the optimization of the production process of a stage in the Huogeqi Copper Mine. The optimization results provide a set of Pareto-optimal solutions that can meet varying needs of decision makers. Moreover, compared with those of the current production indicators, the profit and resource utilization rate of some points in the optimization results can increase respectively by 2.99% and 2.64%. Additionally, the effects of the decision variables (geological cut-off grade, minimum industrial grade and loss ratio) on objective functions (profit and resource utilization rate) were discussed using variance analysis. The sensitivities of the Pareto-optimal solutions to the unit copper concentrate price were studied. The results show that the Pareto-optimal solutions at higher profits (with lower resource utilization rates) are more sensitive to the unit copper concentrate prices than those obtained in regions with lower profits.