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The issue of achieving sustainable livelihoods (SL) is a persistent problem that has gained significant interest for all countries. Even though contexts of vulnerability have been highlighted to be critical to SL, the difference of SL under vulnerability contexts, particularly disaster, has been ignored. As one disaster-prone area, there is an urgent need to conduct studies on SL in Shenzha, within the context of the construction of a national park. This paper proposes to address this research gap by evaluating SL under various disaster contexts in Shenzha, China. According to the frequency of natural disasters, towns in Shenzha can be divided into three groups: Snowstorm and windstorm-dominated towns (SWT), mixed towns (MT) and drought-dominated towns (DT). The results showed that (1) a great disparity of SL can be observed among the three vulnerability groups. The scores of these SL were sorted into descending order as: DT > SWT > MT. (2) In detail, herdsmen in DT have a high value of SL because they have high livelihood assets, livelihood strategies and disaster management capabilities. (3) Herdsmen in SWT have high livelihood assets, particularly human and financial assets, and livelihood strategies. (4) The low livelihood assets and livelihood strategies have restricted the SL of herdsmen in MT. An analysis of SL under various disaster contexts helped to depict the characteristics of SL. Accordingly, targeted policies were developed for the development of SL under various disaster contexts.

The rapid increase in urbanization has brought about a great deal of ecological problems, and thus the systematic protection of the environment is vital. Ecological security patterns are important for maintaining regional ecological stability and sustainable urban development. Human disturbance is a key factor affecting the stability and sustainable development of ecosystems. This paper constructs an ecological security pattern and evaluates the degree of human disturbance in Fuzhou City. Through a comprehensive analysis of both of these factors, the ecological priority restoration areas in Fuzhou were identified. The study shows that (1) there are 40 ecological source areas in Fuzhou, with a total area of 4556.48 km2; 83 ecological corridors, with a total distance of 179.33 km; and 30 ecological nodes. (2) The human disturbance degree score in the study area is between 0 and 0.8. The degree of human disturbance forms two larger major cores in Cangshan District, Gulou District, and Fuqing City. (3) The scores for the degree of human disturbance with ecological sources range from 0 to 0.42. The high-priority areas in the study area are distributed at the edges of ecological sources and form two high-scoring aggregation areas in Fuqing City and Jinan District. These corridors have a high degree of human disturbance with scores between 0 and 0.56. The I and II priority areas are mostly found in longer corridors in Fuqing City and Cangshan District near coastal or urban centers, and the III priority areas are mainly distributed in ecological corridors near the inland. The human disturbance degree scores of the nodes range from 0.01 to 0.27, and the nodes with higher grades were mainly distributed in the northeast, southeast, northwest and southwest of the study area.

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.

Abstract This paper investigates the impact of urbanization on energy consumption by applying the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) in case of Malaysia. The study covers the time period of 1970Q1–2011Q4. The unit root test and the ARDL bounds testing approach have been applied to examine integrating properties and long run relationship in the presence of structural breaks. Our results validated the existence of cointegration and exposed that urbanization is a major contributor in energy consumption. Affluence raises energy demand. Capital stock boosts energy consumption. Trade openness leads to affluence and hence increases energy consumption. The causality analysis finds that urbanization Granger causes energy consumption. The feedback effect is found between energy consumption and affluence and, energy consumption and capital. The bidirectional causality exists between trade openness and energy consumption.

Renewable energy technological innovation (RETI) is an important way to reduce carbon emissions and achieve sustainable development. Exploring whether RETI is beneficial to the improvement of carbon emission efficiency and how the market environment affects the role of RETI on carbon emission efficiency is critical to the design of effective policies. Therefore, based on the data from 25 provinces in China from 2002 to 2015, the Tobit fixed-effect model and the panel threshold model are used to investigate the impact and the mechanism of RETI on total factor carbon performance index (TCPI) from a market perspective. The results show that: (1) RETI can effectively improve TCPI, but this effect is affected by market factors; (2) With the reduction of market segmentation or the increase of market potential, the improvement effect of RETI on TCPI is significantly enhanced; (3) The panel threshold model further verifies that the impact of RETI on TCPI has a significant single threshold effect in terms of market segmentation and market potential; (4) There is an inverted "U-shaped" relationship between market segmentation and TCPI, and the increase of market potential is conducive to the improvement of TCPI. This paper provides corresponding policy implications for China to achieve the dual goals of economic transformation and carbon emission reduction.

Abstract An overview for energy use in Chinese economy is presented in this study by means of a systems cross-scale input-output analysis. To concretely reflect the cross-scale effect between China and the rest of the world, embodied energy intensity of foreign imports is provided on the basis of our recent work on the world economy, in contrast to the conventional assumption of the same intensity for both the foreign and domestic trade. In 2012, the energy embodied in gross fixed capital formation is found to constitute nearly half of the total energy use in China, three-quarters larger than the total household consumption. Approximately 40% of energy resources embodied in final use turn out to be imported from foreign regions, twice the share of the direct energy imports in total energy consumption recorded by traditional direct accounting. The trade imbalance in energy use is illustrated with the support of the law of comparative advantage. In addition to economic benefits, hidden social impacts, including indirect external dependence and health costs associated with non-energy trade, should also be considered by the government in industrial structure adjustment. The present embodiment study is expected to be remarkably supportive for sustainable energy policy making in China.

As the volume and scale of urban expressways continue to increase, renewal remains a concern for urban development. The renewal and decision-making of an urban expressway need to be endowed with new concepts to adapt to the rapid development of cities. Nevertheless, in addition to considering road factors such as facility conditions, driving conditions, and environmental protection, the existing evaluation system lacks comprehensive consideration of factors that improve resilience and adapt to future urban development, and it lacks a quantifiable general update evaluation system. Thus, the establishment of a comprehensive renewal indicator system and a mixed evaluation framework is a challenge. This study proposes an evaluation framework of expressway renewal indicators that integrates the three dimensions of macro, meso, and micro based on the fuzzy Delphi method, the fuzzy AHP method, and the TOPSIS method. A q-rung orthopair fuzzy linguistic set was used to handle expert uncertainty information in the process of conducting fuzzy evaluations. The indicators were refined into general and quantifiable evaluation indicators to improve their versatility. Moreover, the renewal value of expressways was measured and calculated using the TOPSIS method, and four renewal intervals were divided according to the calculation results. As a result, 28 renewal indicators were screened out, and the five factors with the greatest impact on renewal were the demand for transport development, the renewal of facility and service functions, the upgrading of institutional resilience, structural renewal, and economic development. The model was applied to eight expressways in Shanghai to calculate the renewal degree value and divide the renewal status. The model could identify the renewal needs of each road to guide the renewal decision. This study proposes an evaluation model to measure urban expressway renewal studies and provides a reference for urban renewal in the area of sustainable 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.

Despite the large quantities of secondary materials flowing within the built environment, their actual volume and respective waste management processes are not accurately known and recorded. Consequently, various sustainability and material efficiency policies are not supported by accurate data and information-reporting associated with secondary materials’ availability and sourcing. Many recent studies have shown that the integration of digital technologies such as city information management (CIM), building information modeling (BIM), and blockchain have the potential to enhance construction waste management (CWM) by classifying recycled materials and creating value from waste. However, there is insufficient guidance to address the challenges during the process of CWM. Therefore, the research reported in this paper aims to develop a blockchain-enhanced construction waste information management conceptual framework (BeCW). This paper is the first attempt to apply the strengths of integrated information-management modeling with blockchain to optimize the process of CWM, which includes a WasteChain for providing a unified and trustworthy credit system for evaluating construction-waste-recyclability to stakeholders. This is enabled through the use of blockchain and self-executing smart contracts to clarify the responsibility and ownership of the relevant stakeholders. As a result, this study provides a unified and explicit framework for referencing which quantifies the value-contribution of stakeholders to waste-recovery and the optimization of secondary construction materials for reuse and recycling. It also addresses the issue of sustainable CWM through information exchange at four levels: user, application, service, and infrastructure data levels.