REEs resources are not only ranking atop in the global key minerals list, but also one of China's dominant minerals in the world.For a purpose of boosting China's REEs industry, this paper uses global REEs data to analyze their global resources and global markets.REEs are not rare.The major REEs deposit types, characterized by low mineralization and whole rock mineralization, are distribution globally with their reserves up to 110 million metric tonnes on land, more in the oceans.Exploration, production, process and trading of REEs resources shall be determined by pricing rules, rather that by geopolitics.The only direction to make a stronger global REEs industry is focus on globalization and marketization.Separation of REES has always been China's core technologies, making China's REEs concentrates dominate the most global market share.China may cancel refining restriction policies of imported REEs products when appropriate in the future, which cannot indirectly limit our competitors, but also maintain China's leading role in REEs separation technologies in the global REEs industry.China has huge amounts of scrapped vehicles, wind turbines, computers and cell phones containing REEs each year.In order to strengthen the recycling and reuse of mineral resources and promote high-quality economic and social development, China can adopt measures such as tax reduction and exemption for waste refining and recycling enterprises, and increase investment in research of waste refining and recycling technology, so as to achieve the purpose of continuously improving the secondary recycling rate of China's REEs resources.To catch up with the developing opportunities of the fourth industrial revolution and to continue China's dominance on global REEs industry, this paper puts forward suggestions on developing new REEs products as one growing approach to enlarging China's REEs industrial scale, developing new rare earth functional materials as a strong driving force to enhance the strength of China's REEs industry.

To study how to push sustainable development of resource-based cities, this paper uses DPSIR model with 17 UN-issued SDGs as evaluation indicators to establish an evaluation index system of sustainable development of resource-based cities, which is applied to study the sustainable development of resource-based cities and the evaluation of DPSIR model based on a case study of Xuzhou constructing national sustainable development agenda innovation demonstration zone, and to study their coupling coordination among five sub-systems in DPSIR model.During constructing national sustainable development agenda innovation demonstration zone, Xuzhou boosts a green industrial upgrading, actively implements expansion of new industries and increment of traditional industries under a dual-powered strategy of advanced manufacturing and modern servicing, which escalates Xuzhou's new industrial system and enhances its industrial competitiveness.Sustainable development of resource-based cities is a compound system composed of interrelated economy, society and environment, and requires a good coupling coordination between the sub-systems and their indicators of the DPSIR model.In the driving force subsystem (D) and pressure subsystem (P) of DPSIR model, the evaluation indexes of output energy consumption and unemployment rate have a negative effect on the sustainable development of Xuzhou city, which can be offset by reducing unit energy consumption and increasing employment in Xuzhou.

In order to study the relationship between digital transformation, green innovation and green total factor productivity of heavily polluting enterprises, as well as the moderating role of corporate governance among the three, this paper, based on the 2010-2022 data of China's A-listed heavily polluting enterprises, uses SBM-Malmquist index to estimate green total factor productivity of enterprises, and establishes a quantitative model to study the impacts of digital transformation on green total factor productivity of enterprises.A mediation test model and an adjustment test model are constructed to explore the mediating role of green innovation level between digital transformation level and green total factor productivity of enterprises, and the moderating effect of corporate governance level between digital transformation level, green innovation level and green total factor productivity of enterprises.This paper also verifies heterogeneity in enterprises' ownership, financing constraints and sectors.A positive correlation exists between digital transformation and green total factor productivity of enterprises, suggesting digital transformation can largely improve green total factor productivity of heavily polluting enterprises.Digital transformation can improve the green innovation level of enterprises, and the green innovation level plays a partial mediation role between the digital transformation level and the green total factor productivity of enterprises.The level of corporate governance plays a positive moderating effect between the level of digital transformation and the level of green innovation, that is, improving the level of corporate governance can strengthen the role of digital transformation in improving the level of green innovation, which can also improve the green total factor productivity of heavily polluting enterprises.The digital transformation of state-owned heavily polluting enterprises will play a greater role in improving green total factor productivity of enterprises than that of non-state-owned heavily polluting enterprises, and the digital transformation of heavily polluting enterprises with low financing constraints will play a greater role in improving green total factor productivity of enterprises than that of heavily polluting enterprises with high financing constraints.The digital transformation of non-manufacturing heavily polluting enterprises will play a greater role in improving the green total factor productivity of enterprises than that of manufacturing heavily polluting enterprises.

To study the impacts of environmental regulation on enterprise green innovation and roles/mechanism of artificial intelligence between environmental regulation and enterprise green innovation, this paper, based on 2000 to 2019 data of China's A-listed manufacturers, uses bi-directional fixed effect model to their relation among environmental regulation, artificial intelligence and enterprise green innovation.Environmental regulation can dramatically improve enterprise green innovation, which also can be boosted by applying artificial intelligence through mitigating enterprise financing constraints, increasing whole element productivity and saving laboring costs.Environmental regulation cannot improve the green innovation level of state-owned enterprises, but the application of artificial intelligence can enhance the role of environmental regulation in improving the green innovation level of state-owned enterprises.Environmental regulation can improve the green innovation level of non-state-owned enterprises, and the application of artificial intelligence can enhance the role of environmental regulation in improving the green innovation level of non-state-owned enterprises.Environmental regulation cannot improve the green innovation level of small-scale enterprises, and the application of artificial intelligence cannot enhance the role of environmental regulation in improving the green innovation level of small-scale enterprises.Environmental regulation can improve the green innovation level of large-scale enterprises, and the application of artificial intelligence can enhance the role of environmental regulation in improving the green innovation level of large-scale enterprises.Environmental regulation cannot improve the level of green innovation of labor-intensive enterprises, and the application of artificial intelligence cannot enhance the role of environmental regulation in improving the green innovation level of labor-intensive enterprises.Environmental regulation can improve the green innovation level of capital-intensive enterprises, and the application of artificial intelligence can enhance the role of environmental regulation in improving the green innovation level of capital-intensive enterprises.Environmental regulation cannot improve the green innovation level of technology-intensive enterprises, but the application of artificial intelligence can enhance the role of environmental regulation in improving the green innovation level of technology-intensive enterprises.

Cities‘ roles on value chain resilience of integrated circuit industry vary with their sizes.To understand their relationship, this paper establishes a linkage between urban size and value chain resilience of integrated circuit industry, based on a case study of the Beijing-Tianjin-Hebei urban agglomeration, and uses fixed effect least squares estimation model to deeply elucidate impacts of urban size on value chain resilience of integrated circuit industry.Impact coefficients of urban size on  value chain resilience of integrated circuit industry are at 0.278 4 in ultra-large cities, 0.243 7 in large cities, and 0.146 0 in type I cities, significant at the 5% or 10% level, suggesting a larger urban size can increase value chain resilience of integrated circuit industry.Impact coefficients of enterprise scale, profitability and operational capabilities are at 0139 5, 0.074 3 and 0.043 1, respectively, significant at the 1% or 10% level, indicating they all play a positive impacting role on the value chain resilience of the integrated circuit industry.Ultra-large cities’ interaction with enterprise scale produces a positive role with coefficient at 0.144 1 on value chain resilience of integrated circuit industry, while large cities and type I cities are at 0.193 5 and 0.215 2,  it is indicated that the positive impact of the interaction term between the urban size and the enterprise scale on the resilience of the value chain of the integrated circuit industry will gradually weaken as the urban size expands. Ultra-large cities‘ interaction with enterprise profitability plays a positive role at 0.145 6 on value chain resilience of integrated circuit industry, while large cities and type I cities are at -0.214 5 and -0.287 3,  it shows that the positive impact of the interaction term between the urban size and the profitability of enterprises on the resilience of the value chain of  the integrated circuit industry will gradually increase as the urban scale expands.

The Yangtze River Economic Belt, as one of China‘s vital agricultural producing bases, impacts the performances of China’s “dual carbon” strategy by its low carbon agricultural development.To study the developing status and issues of low carbon agriculture in China’s Yangtze River Economic Belt so as to provide references for China‘s low carbon agriculture, this paper establishes an evaluation system index and uses entropy method to estimate its low carbon agricultural development in the Yangtze River Economic Belt, and applies fixed effect model to reveal the influencing factors.Low carbon agricultural development level in the Yangtze River Economic Belt shows a fluctuating rising trend from 2012 to 2021, with continuously climbing carbon index gaining a highest score among three tier 1 indicators, suggesting a good control over carbon emission from agriculture.The Yangtze River Economic Belt has gained a relatively low output index from 2012 to 2021, still in rising trend, meaning a growing agricultural producing efficiency and outputs.Its energy index gained a declining trend from 2012 to 2021, indicating that fossil energy consumption has been rising, renewable energy has been used less, leading to a negative impact on low carbon agricultural development.Among all factors impacting low carbon agricultural development in the Yangtze River Economic Belt, economic development, planting productive structure, scientific and technological innovation input, agricultural producing efficiency and urbanization play a positive role, but agricultural staffing amount plays negatively.

To explore the coupling relationship between ecological security and food security, this paper, taking the Three Gorges Reservoir Area（Chongqing Section）as a case, establishes an evaluation index system of coupling coordination between ecological security and food security and an evaluation model, which is used to estimate ecological security index and food security index and to study their temporal-spatial evolution.A driving factor model is built to measure gray correlation of indicators in ecological security system and food security system, and to analyze their impacts in their systems.A coupling coordination model and relative development model are constructed to study the temporal-spatial evolution and relative development of coupling coordination between ecological security system and food security system.Ecological security level in the Three Gorges Reservoir Area（Chongqing Section）shows a fluctuating declining trend from 2000 to 2020, with its index dropping to 0.379 in 2020 from 0.411 in 2000, suggesting a growing pressure on its ecological security.The food security index also dropped from 0.363 in 2000 to 0.314 in 2020, indicating food security in an unfavorable status.Among evaluation indicators of ecological security system, farmland per capita and urbanization rate largely impact ecological security, GDP per capita and agricultural/forests/water expenditure play a secondary role.Among evaluation indicators of food security system, GDP of the first industry and gross crops production greatly affect food security, unit farmland pesticide use and unit food farmland consumption are the secondary factors.Their coupling coordination degree between ecological security system and food security system in the Three Gorges Reservoir Area（Chongqing Section） shows a fluctuating decreasing trend from 2000 to 2020, from 0.419 in 2000 to 0.405 in 2020 with the development stages of coupling coordination are grinding-in stage >in confliction state >in coordinated stage.The relative development types of ecological security system and food security system of the Three Gorges Reservoir Area（Chongqing Section） have five categories from 2000 to 2020, low coordination, low grinding-in, high coordination, high confliction, and high grinding-in, and relative development is characterized by ecological security synchronous with, behind or preceding food security.

To study the spatial correlation network of ecological efficiency in the Yangtze River Delta Area, this paper, based on 2010 to 2021 spatial panel data of 41 cities in the Yangtze River Delta Area, uses Super-EBM model to measure their ecological efficiency from 2010 to 2021, and analyzes the spatiotemporal evolution characteristics of ecological efficiency in the Yangtze River Delta Area in 2010, 2015 and 2021, and applies calibrated gravity model to estimate cities' eco-efficiency correlating strength in the Yangtze River Delta Area, not only analyzes the evolution characteristics of the spatial correlation network of eco-efficiency in this area, but also explores the structural characteristics of the correlation network of the whole space and the individual space of eco-efficiency in the Yangtze River Delta Area by using social network analysis method.This paper also uses QAP regression analysis to study the factors that affect the spatial correlation network of eco-efficiency in the Yangtze River Delta Area.Temporal-spatial evolution of ecological efficiency shows that ecological efficiency value of the Yangtze River Delta Area cities did not reach the effective status in 2010 with a diminishing distribution from margin to inner geographically.It climbs a bit in most cities in 2015, but still leaving a gap to effectiveness, geographically distributing east-high-west-low, north-high-south-low.Ecological efficiency value had commonly been increased in the Yangtze River Delta Area cities in 2021, in terms of space, the cities with high ecological efficiency value are converging to Shanghai and Nanjing.From 2010 to 2021, the spatial correlation intensity of ecological efficiency in the Yangtze River Delta Area has been improved to a certain extent, and the spatial correlation network of ecological efficiency has shown a trend of change from non-equilibrium to equilibrium development on the whole, and formed a spatial correlation network pattern with cities in southern Jiangsu as the core.Degree centrality value of southern Jiangsu cities has always been high in 2010 and in 2021, but low in northern Anhui, northern Jiangsu, and southwestern Zhejiang cities.Closeness centrality value centralities of southern and central Jiangsu cities have been high in 2010 and in 2021, but low in northern Anhui, northern Jiangsu and eastern Zhejiang cities.Betweenness centrality value of southern Jiangsu and southern Anhui cities have always been high in 2010 and in 2021, but low in northern and southern Yangtze River Delta cities. Geographic proximity and urbanization positively affect the spatial correlation network of ecological efficiency in the Yangtze River Delta Area, but economic development level, technological innovation level play a negative role, and local financial expenditures have no impacts.

Aiming at the hidden electricity transfer in industrial sectors in the Yangtze River Delta Area, this paper uses the electrical consumption data in the Yangtze River Delta Area to establish a multiple-regional input-output table in 2017, and applies input-output and structural path analysis methods to study the hidden electricity transfer in provinces and in industrial sectors, and hierarchical path decomposition of the industrial chain of hidden electricity transfer.In 2017, Jiangsu is the major province both receiving and outputting hidden electricity, ranking it at the core in the hidden electricity network in the Yangtze River Delta Area playing a crucial role in allocating and transferring electricity. In 2017, Anhui is the main output province of hidden electricity in the Yangtze River Delta Area，Zhejiang is the input province of hidden electricity in the Yangtze River Delta Area. In 2017, Shanghai is the transfer station of hidden electricity in the Yangtze River Delta Area, and its output and input of hidden electricity are basically equal.In 2017, the most important hidden electricity transfer path between provinces in the Yangtze River Delta Area was from Jiangsu to Zhejiang, with an electrical transfer volume of 3.724 17 billion kW·h，next is from Anhui to Jiangsu, with an electrical transfer volume of 2.285 51 billion kW·h.In 2017, among industrial sectors, construction is the largest hidden electricity consuming sector in the Yangtze River Delta Area with a hidden electrical consumption up to 111.954 billion kW·h, followed by manufacturing with 88.576 billion kW·h.The hidden electrical input-output across the four provinces forms a complementary relation that supports the economy with hidden electricity, and helps their industrial division and cooperation, favorable for driving an industrial synergy among the four provinces in the Yangtze River Delta Area and reducing the economic gaps, and further for boosting regional economic integration.In 2017, the ultimate demand for hidden electricity in Jiangsu, Zhejiang and Anhui was gross fixed capital formation, but Shanghai was urban residents' consumption.

To explore the ecological restoration measures and comprehensive development of China's abandoned mines, this paper, based on a case study of Xingrong shale mine, in Wangcang county, Guangyuan city, Sichuan province, studies its ecological restoration and comprehensive development.The mine had been ecologically restored in a way of “site harness+slope hazards harness+vegetation” that not only cleared the piled wastes, but also conducted geological hazards prevention on slopes with anchored nesting, beaming and slope draining, and vegetation had also been restored via slope backfilling and hole filling.Now the mine has a restored mine area up to 25.05 hm², basically reaching the restoration objectives.The abandoned brick kiln within the mine had been transformed into an industrial heritage resort with cultural exhibition & innovation, featured foods and entertainments，which not only boosts the growth of industrial heritage tourism, but also drives the picking events in Hongya village's Xianju bayberry industrial park in every June.Its abandoned factory buildings located at mine slope had been converted into 12 bayberry frozen-storage warehouses with an area of 420 square meters.The mine heritage site now has become a comprehensive servicing center of bayberry whole industrial chain with freezing logistics, featured foods, bayberry products exhibition and cultural innovation, which largely powers the growth of Hongya village's bayberry industry.The case of Xingrong shale mine's ecological restoration and comprehensive development which combines industrial heritage tourism with featured agricultural planting forms a localized cultural resort with touring, picking and cultural innovation, and dramatically improves Wangcang county's tourism attraction and reputation as well, a showcase of interaction between ecological construction and economical development.

A combination of B/S structure with quantitative identification of multiple dimensional features can not only effectively quantify multiple dimensional features of environmental protection capabilities of power grid enterprises, but also improve their constituting elements.This paper uses B/S structure to construct a technical framework for power grid enterprises in quantitative identification of environmental protection capabilities and a multiple dimensional features system, and studies the multiple dimensional features quantitative  identification method for power grid enterprises' environmental protection capabilities, whose feasibility is validated through a case study of Fujian Power Company. This method can not only clearly show the using status of multiple dimensional features data of power grid enterprises' environmental protection capabilities, but also let users download, rename or delete data, proving that the research method created in this paper can effectively manage multiple dimensional features data of environmental protection capabilities of power grid enterprises.In this paper, fuzzy clustering algorithm is used to construct a multiple dimensional features system of power grid enterprises' environmental protection capabilities.Through multiple dimensional features cluster analysis, it is tested that the system has a good advantage in the comprehensiveness of the definition of the feature indicators of power grid enterprises' environmental protection capabilities, and a good construction effect is obtained.Analytic Hierarchy Process (AHP) can be used to measure the weights of each feature of the environmental protection capabilities of power grid enterprises.Then, after combining the weight of each feature with the fuzzy comprehensive evaluation model, through the environmental protection capabilities identification unit of the application layer of the power grid enterprises' environmental protection capabilities identification technology framework constructed in this paper, this method can not only divide the quantitative identification level of multiple dimensional features of the environmental protection capabilities of power grid enterprises, but also identify the multiple dimensional features quantitatively.This paper takes State Grid Fujian Power Company as an example to carry out the verification of the B/S feature quantitative identification method created.Its four tier 1 features, environmental protection investing capability, profitability, developing capability and managing capability, reach the premium level by their quantitative scores, suggesting that Fujian Power Company has a high capability in environmental protection, and validating the method's effectiveness and practicability as well.

China's provincial geological exploration funds were established by provinces aiming at exploration discoveries with focusing on key minerals and in major metallogenetic zones at their initial exploitation.Since their establishment in 2004, provincial geological exploration funds have been focused on guaranteeing national minerals security, dramatically financially aided geological exploration works on key minerals and in major metallogenetic zones, which plays a critical role in China's exploration discoveries and increasing resources. This paper takes the provincial geological exploration funds in China as the starting point, sorts out and studies its establishment, adjustment, operation, results and benefits.Provincial geological exploration funds greatly promote China's geological exploration, mainly including implementing the national mining work deployment, promoting China's mining industry to achieve fruitful results, attracting social capital to diversify investments in provincial geological exploration funds, playing a guiding role in China's geological exploration, and bearing exploration risks.Some issues also exist pending for improvements, mainly including provincial geological exploration funds have been decreased largely，and disadvantages in the current resources administrative system result in a lagging “commercial following” of geological exploration projects funded by provincial geological exploration funds, thus blocking social capital into geological exploration.China's budget managing ways of geological exploration funds and other factors make profits of provincial geological exploration funds hard to be converted into reinvestments in a short term, constraining the recycling and sustainability of provincial geological exploration funds. Uncertainties in supports, investing sizes and investing modes of provincial financial authorities on provincial geological exploration funds lead to lack of stable fund sources in provincial geological exploration funds.