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The structure of renewable energy (RE) development varies substantially across China's provinces, and the spatio-temporal pattern evolution is too pronounced to allow direct comparisons. Therefore, a reasonable method for RE efficiency estimation is important. Markov and spatial Markov chains can be used to analyze the evolution of the temporal and spatial patterns of provincial RE. Simultaneously, data envelopment analysis game cross-efficiency evaluation can quantify the RE generation efficiency of each province from the perspective of competition. Nine factors were selected to identify the key influencing factors the RE generation efficiency. From the perspective of spatio-temporal heterogeneity, a geographically and temporally weighted regression model was combined for spatial modeling. Results show a significant change in the categories of wind and solar power installations, a medium change in biomass installations, and a small change in hydropower installations. Two-thirds of the provincial RE generation efficiency increased from 2015 to 2020. There is spatio-temporal heterogeneity regarding the impact of various factors on the RE generation efficiency: The impact of technology market transactions exhibits the greatest inter-provincial variation and the impact of electricity industry investment exhibits the smallest inter-provincial variation. [ABSTRACT FROM AUTHOR]

• Establishing HWPS investment limitation and suitability assessment indicator systems. • Determination of expert weights using dynamic social networks. • TIFN was used to quantify the qualitative indicators. • Combining BWM and CRITIC combination weighting and TODIM to rank the alternatives. • Investment suitability assessment of 62 completed hydropower plants in China. The hydropower-wind-photovoltaic-storage (HWPS) complementary system is one of the essential ways for China to build a new type of power system and to realize the dual-carbon goal. However, China's HWPS complementary system is still in the exploratory stage, and it is important to propose a rational multi-attribute decision-making (MADM) framework for investment suitability assessment based on completed hydropower plants. Therefore, this study first established a limitation indicator system for preliminary screening hydropower plants and an HWPS investment suitability assessment indicator system containing six dimensions: nature, market, infrastructure, land, society, and environment. Second, the weights among experts were determined based on the dynamic social network, and a mechanism for updating expert weights was proposed. Again, triangular intuitionistic fuzzy number (TIFN) was used to quantify the qualitative indicators and combined the weights according to the best-worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) methods. Finally, the TODIM (an acronym in Portuguese for interactive and MADM) method was used for scheme suitability assessment with sensitivity analysis and method comparison. The results show that 62 eligible hydropower plants were preliminarily screened out of 647 completed medium- and large-scale hydropower plants in China by combining GIS technology. Natural factors are the most important of the six dimensions, followed by social factors. According to the suitability assessment results of TODIM, #23 hydropower station has the highest suitability for HWPSCS investment, which provides a reference for the layout of China's HWPS complementary system. With different decision makers' risk preferences and different MADM methods, #23 hydropower plant is still the best investment option, which proves the effectiveness of the MADM framework proposed in this study. [ABSTRACT FROM AUTHOR]

Increasing carbon emissions efficiency (CEE) is essential for Chinese cities to achieve their dual carbon goals. For cities with higher CEE, it is crucial to comprehensively evaluate their carbon emissions reduction potential (CERP) and develop targeted carbon reduction paths. This study first determined the input, expected output, and non-expected output indicators and used the super-efficiency Slack Based Measure model to calculate the CEE of 336 cities. Secondly, we evaluated the urban development level, structural optimization space, and natural resource endowment using the BWM-CRITIC-TOPSIS method and combined them with CEE to evaluate the CERP. Finally, we used K-means clustering to group cities according to the carbon emissions level and CERP and proposed targeted emission reduction recommendations. The results showed that cities in the northern part of China had lower CEE, while the coastal areas had higher CEE. In the primary indicators of CERP, structural optimization space was the most important, followed by efficiency improvement space. The eastern region has a greater potential for carbon reduction, with an average score of 63.71 points (out of 100 evaluation points) for the 336 cities. The cities could be classified into nine types, with the ninth category being the key focus cities for achieving the 2030 carbon peak goal with high carbon emissions and CERP. [ABSTRACT FROM AUTHOR]

To promote renewable energy consumption and achieve China's low-carbon energy transition, in 2019, China proposed the weight of consumption responsibility (WCR) for renewable energy in each province. This study aims to explore the micro-market behavior of new energy manufacturers in the context of WCR policy. A two-market bidding model for new energy manufacturers is first proposed, and a two-stage compound differential evolutionary game algorithm is proposed for solving the multi-party game problem. By selecting typical electricity demand scenarios, the evolution of new energy manufacturers' strategies in the electricity market and green certificate market as well as under different WCR and different thermal power unit parameters are analyzed. The research results show that when the non-hydropower WCR is relatively low, new energy manufacturers tend to adopt a low-price strategy for generation quotation and a low volume high price strategy for green certificate sales. Other conditions being unchanged, with the increase in non-hydropower WCR, all new energy manufacturers will still adopt a low-price strategy in the electricity market. New energy manufacturers with high installed capacity will increase progressively their certificate quotation. The higher output lower limit for thermal units is not conducive to electricity market bidding by new energy manufacturers. • A two-market bidding model for new energy manufacturers is established. • A two-stage compound differential evolutionary game algorithm for new energy manufacturers is proposed. • The optimal strategy of two-market bidding for new energy manufacturers is empirically analyzed. • The bidding strategies under different consumption responsibility weights are discussed. [ABSTRACT FROM AUTHOR]

Research on container port development is of great theoretical and practical significance because of the port's crucial role in the local economic system and regional transportation system. Understanding the development dynamics of container ports is important when formulating related operational and management strategies in the future. Hence, this article investigates the club convergence of 25 coastal ports in mainland China spanning from 2006 to 2020 in terms of container throughput, which signals the development of a port to some extent. The study finds three clubs in China's coastal container port system, with various transitional behaviors indicating that the whole system has shown a tendency toward a slight centralization since 2013 and that small and medium-sized ports are regressing. On this basis, analysis on the container port system is conducted by employing an allometric model. The result shows that allometric relations indeed exist not only among three factors linked with port development, namely, port container throughput, port city's import-export volume, and port maritime connectivity, but also among the three port clubs. Moreover, the allometric relations slightly differ and vary over time for the three port clubs, thus implying that large ports may have different growth mechanisms from small and medium-sized ports. Based on the findings mentioned above, several general policy implications are proposed, which may impact port production, construction, and operations management in mainland China. • Combined club convergence and the allometric model to analyze the development dynamics of coastal container ports of different scales. • The allometric relations between port container throughput, port city's import-export volume, and port liner shipping connectivity are analyzed. • The container port system in mainland China shows a trend of concentration, with the development momentum of small and medium-sized ports being insufficient. • Useful managerial and operational insights for the development of port with different scales are given. [ABSTRACT FROM AUTHOR]

• There was a significant positive spatial correlation between provincial CO 2 emissions in China. • Spatio-temporal heterogeneity analysis of driving factors of CO 2 emissions was carried out using GTWR model. • Inter-provincial differences in the impact of industrial structure on CO 2 emissions were minimal. • Energy intensity is a key factor in achieving dual reduction in provincial CO 2 emissions, followed by trade openness. To achieve the 2060 carbon neutrality target, each province in China needs to ensure rapid reduction in carbon dioxide (CO 2) emission according to its own developmental characteristics. Meanwhile, to achieve sustainable emission reduction, it is important to explore the development path of dual reduction of total CO 2 emissions and CO 2 emission intensity in each province. Based on the data of 30 provinces in China for the period 2005–2019, in this study, we analyzed the spatial and temporal evolution trends of CO 2 emissions in each province and determined the spatial autocorrelation of provincial CO 2 emissions. We used the geographically and temporally weighted regression (GTWR) model to analyze the spatio-temporal evolution of the driving factors of provincial CO 2 emissions. The results showed that CO 2 emission intensity of each province gradually decreased, and the CO 2 emissions between provinces were spatially autocorrelated. Energy intensity had the highest influence on total CO 2 emissions, and the influence of trade openness on CO 2 emission intensity had the largest inter-provincial differences. At present, reducing energy intensity and the proportion of secondary industries, improving trade openness, and using electricity alternatives are the key for some provinces to achieve dual reduction of total CO 2 emissions and CO 2 emission intensity. [ABSTRACT FROM AUTHOR]

The Baishaziling greisen-type tin deposit is located in the Dayishan ore field, Nanling Range, Southern China. In this study, for the first time, we present both zircon and cassiterite U Pb dating, whole-rock elements, zircon Lu Hf and apatite Nd isotopic compositions to better constrain the petrogenesis of granite and its genetic link with Sn mineralization. Zircon U Pb ages of fine-grained granite and coarse-grained granite are 154 ± 1.8 Ma and 153 ± 2.1 Ma, respectively, which are consistent with the cassiterite U Pb dating of 154 ± 5.4 Ma, implying genetic relationship between the Baishaziling granite and tin metallogenesis. The Baishaziling granites exhibit high SiO 2 , K 2 O + Na 2 O, Zr + Nb + Ce + Y contents, low P 2 O 5 and Sr contents, and high ratios of Ga/Al, TFeO/(TFeO + MgO), implying A-type granite affinity with characteristics of high-K calc-alkaline and weakly peraluminous. The zircon ε Hf (t) values and apatite ε Nd (t) values of the granite vary from −4.46 to −1.81 and −8.37 to −7.10, with two-stage Hf and Nd model ages of 1.40 to 1.50 Ga and 1.52 to 1.64 Ga, indicating that they were generated by the partial melt of the Proterozoic basement with the involvement of mantle magma. In addition, formation of Dayishan granite was likely associated with an intraplate extensional setting caused by the subduction of the Palaeo-Pacific plate. The Baishaziling reduced granites have high stannum and boron contents, which are in favor of the tin mineralization. • Zircon and cassiterite U–Pb dating confirm a Yanshanian granitic magmatism and associated Sn mineralization event. • The Baishaziling granites are A-type granite and were likely originated from the mixing of crust-mantle components. • Reduced granites are in favor of Sn mineralization. [ABSTRACT FROM AUTHOR]

• There is spatial autocorrelation of CO 2 emissions in China's 336 cities. • Quantitative analysis of the coordination level between CO 2 emissions level and urban development. • The carbon emissions in China's cities are reclassified into six categories using cluster analysis. • The influencing factors of CO 2 emissions have spatial heterogeneity. Cities play a critical role in achieving China's carbon emissions peak and carbon neutrality goals, but the policies of cities should be tailored to their developmental levels and local conditions. This study first analyzed the spatial autocorrelation of CO 2 emissions in 336 cities in 2019. The coupling degree and coupling coordination degree were used to measure the coordination level between the CO 2 emissions level and urban development by contemplating the urban development indicators. Depending on the coordination level and historical CO 2 emissions of the city, the urban regions were reclassified with the density peak (DP) clustering algorithm. Finally, a multiscale geographically weighted regression (MGWR) model was used to explore the spatial heterogeneity of the influencing factors of the total CO 2 emissions. The results showed that the coordination level of CO 2 emissions in Shenzhen, Chengdu, and Guangzhou is relatively high; China's urban carbon emissions can be divided into six categories; and the impact on GDP per capita, population, and the proportion of secondary industries on CO 2 emissions is spatially heterogeneous. In conclusion, this study divides China's cities and analyzes the key influencing factors of CO 2 emissions into different categories, providing a reference for cities to achieve CO 2 emissions reduction. [ABSTRACT FROM AUTHOR]

The coordinated development of upstream, midstream, and downstream of wind power industry chain is the key to solve the problem of wind power consumption. Therefore, this paper firstly constructs the performance evaluation index system of the upstream, midstream, and downstream of the wind power industry chain, and evaluates the performance of the upstream, midstream, and downstream of the wind power industry based on entropy weight-TOPSIS. Secondly, the coupling coordination degree (CCD) model between subsystems of wind power industry chain is established to dynamically evaluate the CCD between upstream and midstream, midstream and downstream, and among three subsystems of wind power industry chain. Finally, taking the development data of China's wind power industry from 2010 to 2019 as an example, the coupling coordination degree between subsystems is empirically studied. The results show that: the overall performance of wind power industry chain has a tortuous upward trend; the coupling degree (CD) of each subsystem is better than that of 2011 and 2012; The CCD of upstream and midstream of wind power industry chain fluctuates more than that of midstream and downstream and that of three subsystems. • The performance evaluation index of the upstream, midstream and downstream of the wind power industry chain is established. • Entropy weight-TOPSIS method is used to evaluate the performance of wind power industry chain. • The coupling coordination degree model between subsystems of wind power industry chain is established. • The coupling coordination degrees between subsystems of wind power industry chain are dynamically evaluated. [ABSTRACT FROM AUTHOR]