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Due to the shortage of fossil energy, environmental pollution, climate change and a series of problems, China is developing photovoltaic (PV) energy and other clean sources of energy. The flexible application of photovoltaic energy makes is an ideal choice. First, this paper clearly describes the significance of the economic value of a PV + model, analyzes its composition of, and then builds the PV + economic value evaluation model. Finally, a PV + model from the agriculture and aquaculture industry is taken as an example to evaluate its economic value. Through data calculations, the feasibility of the PV + economic value evaluation model proposed in this paper is verified. The results show that the model can not only promote the development of photovoltaic energy, but also bring a spillover value to the decentralized economy. The contributions of this paper are as follows: (1) The existence of the spillover value of a PV + model is proposed for the first time. (2) The value of the distributed PV + model is revealed from its essential attributes and characteristics, and a method for the quantitative calculation of the spillover value is proposed. (3) Three cases of the spillover value for the economic value of the PV + model are proposed, and the relationship between the spillover value and local adoption of PV + model to absorb distributed PV is discussed. [ABSTRACT FROM AUTHOR]

Accelerating the "double carbon" transformation of the manufacturing industry is the key to achieving the strategic goal of "double carbon" in China, among which the low-carbon development of the Beijing manufacturing industry is the top priority. To achieve high-quality development of the manufacturing industry in Beijing, the main task is to reduce carbon emissions and improve efficiency. Therefore, on the basis of the Global Malmquist–Luenberger (GML) index and the system dynamics (SD) method, this study analyzes the green total-factor energy efficiency trends of 25 manufacturing sub-sectors in Beijing from 2006 to 2020 and incorporates the GML index as a key variable into the construction of the SD model. It then explores the path optimization of Beijing's manufacturing low-carbon development in the 14th Five-Year Plan period via scenario simulation and offers policy recommendations for the green-oriented transition of Beijing's manufacturing industry. The study finds that Beijing's manufacturing industry needs to prioritize energy structure optimization and efficient energy utilization and give full play to the city's advantages in technological innovation and investment while supporting high-end scientific research and innovation projects to confirm the capital city's strategic position. [ABSTRACT FROM AUTHOR]

At present, the research on photovoltaic companies' financial risk early warning model mainly focuses on financial indicators and non-financial indicators from corporate governance structure and external audit opinions. There are few literature studies on the companies' internal information from their annual report. To solve the above problem, firstly, this paper aims to establish a comprehensive assessment indicators system including financial and non-financial indicators considering the companies' internal information. Secondly, this paper uses text mining and a binary logistic regression model to evaluate the financial risk for 37 listed companies in the photovoltaic industry. The results showed that profitability was the most significant factor. Probability, as well as negative sentiment ratios, are both negatively correlated with the occurrence of financial risk, while development capability is positively associated with financial risk. These findings can be used as an effective supplement for financial risk evaluation in the photovoltaic industry and provide reference strategies for developing listed companies in the photovoltaic industry. [ABSTRACT FROM AUTHOR]

For sustainable agricultural development, increasing efforts are put on promoting agricultural mechanization and green agricultural development all over the world. Based on the panel data of Chinese provincial agriculture from 2002 to 2018, the System Generalized Method of Moments model and mediation model are constructed to explore the paths of agricultural mechanization affecting green agricultural development. The results show that agricultural mechanization can not only promote the green agricultural development directly but also indirectly by transferring the agricultural labor force and increasing fertilizer input. However, because of the surge of pesticide demand, agricultural mechanization also leads to serious pollution indirectly. With the development of large-scale agricultural machinery, the direct promotion of agricultural machinery on green agricultural development will be more significant. However, it will be less efficient to substitute more agricultural labor force with machinery power. The problem of pesticide abuse will also become more serious. Therefore, it is important for green agricultural development to encourage human capital investment in agricultural mechanization. In addition, more attention should be paid to improving the input efficiency of fertilizers and pesticides so that agriculture will be sustainable in production and the ecological environment. [ABSTRACT FROM AUTHOR]

Due to severe resource and environmental constraints, agricultural green development is a vital step for the low-carbon development of China. How to achieve the goal of a win–win scenario that simultaneously improves agricultural green total factor productivity (GTFP) and farmers' agricultural income was the main focus of this study. Based on the panel dataset for 31 provinces in China from 2000 to 2018, this study calculated the agricultural GTFP using the global Malmquist–Luenberger (GML) index to measure the green development of agriculture. Furthermore, this study investigated the relationship between the agricultural GTFP and agricultural income in an environmental Kuznets curve (EKC) framework, together with the key factors affecting agricultural GTFP. The main results show that, first, driven by technical progress, the agricultural GTFP gradually increased across the country, while there existed a certain degree of heterogeneity in the growth of different regions. Second, the relationships between the agricultural GTFP and agricultural income exhibited a significant U-shape for the whole country and the four regions, indicating that a win–win scenario can be achieved between green development and income level. Third, industrialization and urbanization negatively affected agricultural GTFP, capital deepening played a positive role, and due to the mediated effect of capital deepening, the outflow of the agricultural labor force did not cause substantial harm to agricultural GTFP. The findings of our study provide useful policy implications for the promotion and development of agriculture in China. [ABSTRACT FROM AUTHOR]

The construction industry plays a crucial role in China's fulfillment of the goal of achieving "carbon neutrality" in 2060. Based on the data of energy and building materials consumption of the construction industry in China and 30 provinces from 2008 to 2018, this paper constructs a model for measuring provincial CO2 emissions of China's construction industry and establishes a Kuznets curve and elastic decoupling model of the industry's CO2 emissions. The analysis based on the models shows that: (1) the CO2 emissions of China's construction industry show a trend of increasing first and then decreasing; (2) in terms of the decoupling effects, most provinces are in a weak decoupling status of CO2 emissions; and (3) the Kuznets curve of the provincial construction industry shows an inverted "U" shape in recent years, and it is predicted that the CO2 emissions of the construction industry will reach the peak in 2034. It is possible for the construction industry to achieve "carbon neutrality", but long-term efforts must be made for strategic planning, policies and regulations, industry standards, etc. [ABSTRACT FROM AUTHOR]

Analysis of sectors' emission effects is crucial for identifying key emission sectors and reducing carbon. Current literature for calculating sectors' emission effects in China ignore intermediate demand. This might introduce inaccuracy into the analyzed results. To solve this gap, this paper used an alternative input–output method to analyze sectors' emission effects in China. Firstly, it identifies the key emission sectors and their emission effect characteristics from 2005 to 2017. Then, the reasons for the changes in these sectors' emission effects are analyzed. Lastly, emission effects were further decomposed so that the driving relationships of emissions among these sectors can be sorted out. The results show that the overall key emission sectors were metal smelting and processing and nonmetal mineral products. The backward-emission-dominant sectors were construction, chemical products, other services (such as finance, health and education), metal products, and so on. The forward-emission-dominant sectors were production and supply of electricity and heat, transportation, storage, postal, and telecommunications services. In 2017, transportation, storage, postal, and telecommunications services' own final demand emissions and forward emissions accounted for 41.7% and 58.3%, respectively, of this sector's direct emissions. Moreover, from 2005 to 2017, the main sector emission paths affecting the growth of China's emissions shifted from manufacturing and construction industries to service industries. Accordingly, strategies for emission reduction, such as substituting pollution inputs, were proposed and analyzed. The research provides an important reference for the Chinese government to adopt appropriate measures to reduce carbon. [ABSTRACT FROM AUTHOR]

China's supply-side structural reforms are facing bottlenecks in the energy and power sector, and improving energy and power efficiency and advancing reforms are urgent. To promote sustainable development, based on panel data from 30 provinces and cities in China from 2009 to 2017, this paper uses the super-efficiency DEA method to measure energy and power efficiency; explores the trend of energy and power efficiency changes before and after reform; uses the Tobit model to identify key efficiency factors; and provides policy recommendations to achieve reform goals. The research shows that China's efficiency level takes the supply-side structural reform as the turning point and presents a volatile upward trend; from the situation of the country, technological progress, the economic development level, and the opening up level are positively correlated with the energy and power efficiency, among which the correlation coefficient between technological progress and efficiency is the highest. The study can offer a reference for the sustainable comprehensive utilization of China's energy and power, and provide empirical evidence for other countries to improve the energy and power efficiency from the perspectives of theory and policies. [ABSTRACT FROM AUTHOR]