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The Chinese electric power industry, including its coal industry and other energy industries that are not efficient, contributes to China’s serious energy shortages and environmental contamination. The governing authority considers energy conservation to be one of the most prominent national targets, and has formulated various plans for decarbonizing the power system. Applying the trans-log cost function, this paper examined the trans-log cost function to analyze the potential inter-factor substitution among energy, capital and labor. We also investigated what role human capital played in energy substitution for the electric power sector during the period from 1981 to 2017. Three key results were derived: (1) energy is price-insensitive, (2) there exists large substitution sustainability between both capital and labor with energy, and (3) human capital input not only enhances the extent of energy substitutability with capital and labor but also is a substitute to energy itself. These findings imply that the liberalization of the electric price mechanism is conducive to lessening energy use and augmenting non-energy intensiveness, and that energy conservation technology could become more sustainable by investing more capital in the electricity sector, thereby achieving a capital–energy substitution and a decrease of CO2 emissions. We further suggest that the priority for the Chinese electric power industry should be to attach more importance to increasing human capital input.

Abstract To alleviate the shortage of natural gas resource and ease carbon emissions, a novel solar-driven combined cooling, heating and power (CCHP) system is designed and optimized using the genetic algorithm in the work. Different from the process of direct combustion in a conventional CCHP system, natural gas is firstly converted into syngas by a solar-driven natural gas reforming step, which is consumed in an efficient tri-generation system. Energy, economic and environmental evaluations on five office buildings in different climate zones in China are implemented to validate the advantages of the proposed system. Results show that the annual maximum primary energy saving, total cost saving, and CO2 emission reduction are 69.76%, 49.80%, and 71.55%, respectively. The system located in severe cold zones, where solar energy is abundant and building requires more heat load in whole year, achieves the highest benefits in comparison with separate systems. Furthermore, the sensitivities on the price fluctuations of electricity, natural gas and solar field to the system profits are investigated, which indicates that the influence of electricity price on the system performance is the most significant. Thus, a promising method for reducing the natural gas consumption and improving the utilization efficiency of solar energy is provided.

In this study, Myriophyllum elatinoides growth under different nitrogen (N) concentrations (2, 250, 300, 350 and 400 mg L-1) and changes in rhizosphere bacterial community structure were investigated. High N (>300 mg L-1) concentrations caused reduction in M. elatinoides biomass. Growth tended to stabilize at 49 days. N concentration in roots were higher than that in stems and leaves under high N conditions. TN and NH4+ removal efficiencies reached 84.0% and 87.2%, respectively, in M. elatinoides surface flow constructed wetlands (SFCWs). Rhizosphere bacterial diversity increased over time. Proteobacteria, Firmicutes, Cyanobacteria, and Bacteroidetes dominated at the phylum level. Genera Turicibacter, Allochromatium, and Methylocystis increased at low N (<300 mg L-1) concentrations, while Pseudomonas increased at high N concentrations over the experimental period. Redundancy analysis showed that pH was strongly correlated with changes in rhizosphere bacterial community structure. These findings helped to insight into N removal mechanism in M. elatinoides.

Societal relations in rural areas have entered into a new stage of adjustment over the past decade. However, the adjustment, which might bring about profound societal changes in countryside as well as in China as a whole, have not been paid much attention and very few studies have been conducted from the perspective of ecological resource crises. We use the case of a village as an example to show how water pollution, as one of the contributory factors, possibly affect the transition of clans and societal changes in Chinese villages. Through observation and interviews, we find that there is an apparent rise of “New Clanism” within clans, which gradually abandons the tradition of supremacy of clan interests and places family or individual interests at top priority. We also find that clan boundaries get increasingly obscure since the integrity of clans is undermined by the rise of new interest groups across clans, but the boundaries remain relatively clear due to the consistency (albeit incomplete) of clan interests. Some new clan élites and representatives of new interest groups get involved in village governance, which indicates that their goals have shifted from natural resources to social or political capital. The significance of our findings is that they provide not only a unique perspective for the interaction between society and resources, but also some new ideas for the future study of rural China at the environment-social interface.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

In recent years, the energy consumption structure has been accelerating towards clean and low-carbon globally, and China has also set positive goals for new energy development, vigorously promoting the development and utilization of renewable energy, accelerating the implementation of renewable energy substitution actions, and focusing on improving the consumption capacity of new energy. However, due to the intermittent and unstable characteristics of renewable energy, it is difficult to meet the demands of the power load side in practical applications. Energy storage is an important link for the grid to efficiently accept new energy, which can significantly improve the consumption of new energy electricity such as wind and photovoltaics by the power grid, ensuring the safe and reliable operation of the grid system, but energy storage is a high-cost resource. Therefore, this paper focuses on the energy storage scenarios for a big data industrial park and studies the energy storage capacity allocation plan and business model of big data industrial park. Firstly, based on the characteristics of the big data industrial park, three energy storage application scenarios were designed, which are grid center, user center, and market center. On this basis, an optimal energy storage configuration model that maximizes total profits was established, and financial evaluation methods were used to analyze the corresponding business models. Finally, taking an actual big data industrial park as an example, the economic viability of energy storage configuration schemes under two scenarios was discussed, and an energy storage system construction plan was proposed to promote the zero-carbon target of the big data industrial park.

Virtual water flows have a profound impact on the natural water system of a country or region, and they may help conserve local water resources or exacerbate water scarcity in some areas. However, current research has only focused on the measurement of virtual water flows, without analysis of the causes of virtual water flow patterns. This study first obtained virtual water flow patterns across provinces by constructing a multi-regional input–-output (MRIO) model of the Yellow River basin in 2012 and 2017, and then analyzed its driving factors by applying the extended STIRPAT model to provide directions for using virtual water trade to alleviate water shortages in water-scarce areas of the basin. We found the following: (1) The Yellow River basin as a whole had a net virtual water inflow in 2012 and 2017, and the net inflow has increased from 2.14 billion m3 to 33.67 billion m3. (2) Different provinces or regions assume different roles in the virtual water trade within the basin. (3) There is an obvious regional heterogeneity in the virtual water flows in different subsectors. (4) Per capita GDP, tertiary industry contribution rate, consumer price index, and water scarcity are the main positive drivers of virtual water inflow in the Yellow River Basin provinces, while primary industry contribution rate, per capita water resources, and water use per unit arable area promote virtual water outflow. The results of this paper present useful information for understanding the driving factors of virtual water flow, which could promote the optimal allocation of water resources in the Yellow River basin and achieve ecological protection and high-quality development in this area.

Abstract Uncertainties of cooling load may make cooling system oversized. Most of previous studies implement probabilistic-based uncertainty analysis, intending to achieve optimization and reliability simultaneously. However, how to reduce the load uncertainty has received little attention. This paper investigates the impact of water storage on the design of cooling system considering load uncertainty. Information entropy is used as a convergence index of load uncertainty and used to determine how many random simulations should to be performed. A cooling system configured with water storage (system B) and another system without water storage (system A as a comparation system) are investigated in this paper. In this paper, the configure of system A and system B are optimized respectively. The result shows that the capacity distribution of system A is consistent with the distribution of extreme loads. But, the capacity distribution of system B is more concentrated as the water storage can reshape the load curve. Water storage improves the flexibility of system B. Therefore, system B is more reliable and economical than system A.