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「人民日報」の行間を読む : 現代中国研究と「人民日報（People’s Daily）」

Excessive carbon emissions seriously threaten the sustainable development of society and the environment and have attracted the attention of the international community. The Yellow River Basin is an important ecological barrier and economic development zone in China. Studying the influencing factors of carbon emissions in the Yellow River Basin is of great significance to help China achieve carbon peaking. In this study, quadratic assignment procedure regression analysis was used to analyze the factors influencing carbon emissions in the Yellow River Basin from the perspective of regional differences. Accurate carbon emission prediction models can guide the formulation of emission reduction policies. We propose a machine learning prediction model, namely, the long short-term memory network optimized by the sparrow search algorithm, and apply it to carbon emission prediction in the Yellow River Basin. The results show an increasing trend in carbon emissions in the Yellow River Basin, with significant inter-provincial differences. The carbon emission intensity of the Yellow River Basin decreased from 5.187 t/10,000 RMB in 2000 to 1.672 t/10,000 RMB in 2019, showing a gradually decreasing trend. The carbon emissions of Qinghai are less than one-tenth of those in Shandong, the highest carbon emitter. The main factor contributing to carbon emissions in the Yellow River Basin from 2000 to 2010 was GDP per capita; after 2010, the main factor was population. Compared to the single long short-term memory network, the mean absolute percentage error of the proposed model is reduced by 44.38%.

Carbon Emission Prediction Model and Analysis in the Yellow River Basin Based on a Machine Learning Method

Improving green total factor productivity (GTFP) is the inherent requirement for practicing the philosophy of green development and achieving regional high-quality development. Based on panel data for 68 prefectural-level-and-above cities in the Yellow River Basin of China from 2006 to 2019, we measured their GTFPs and degrees of productive-services agglomeration using the non-radial directional distance function and industrial agglomeration index formulas, respectively. Furthermore, we empirically investigated the interactive relationship between agglomeration of productive services, industrial-structure upgrading, and GTFP using the dual fixed-effects model, the mediating-effect model, and the moderating-effect model. The findings were as follows. (1) Both specialized and diversified agglomeration of productive services significantly improved the GTFPs of cities in the Yellow River Basin, and the promoting effect of specialized agglomeration was stronger than that of diversified agglomeration. (2) The diversified agglomeration of productive services (hereinafter referred to as diversified agglomeration) made a significant contribution to GTFP in all sample cities of the Yellow River Basin, while the specialized agglomeration of productive services (hereinafter referred to as specialized agglomeration) only significantly improved GTFP in the upstream cities and had no significant effect on the midstream and downstream cities. (3) When examined according to city size, specialized agglomeration was found to have a positive impact on the GTFPs of small and medium-sized cities in the Yellow River Basin but a non-significant negative impact on large cities, while the effect of diversified agglomeration on GTFP was found not to be significant. (4) Industrial-structure upgrading played partially mediating and negative moderating roles in the process of specialized agglomeration affecting the GTFPs of cities in the Yellow River Basin, but it did not become a mediating channel and moderating factor that influenced diversified agglomeration in relation to GTFP.

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Agglomeration of Productive Services, Industrial Structure Upgrading and Green Total Factor Productivity: An Empirical Analysis Based on 68 Prefectural-Level-and-Above Cities in the Yellow River Basin of China

Digital economy, industrial structure, and carbon emissions: An empirical study based on a provincial panel data set from China

This paper employs the slack-based model directional distance function to measure the green total factor productivity of each city, using the panel data of 284 prefecture-level cities in China from 2004 to 2019 and considering the unexpected output. The results are as follows: ① Foreign direct investment significantly suppresses the improvement of urban green total factor productivity, and the negative impact on the green technology progress index is the main reason to inhibit the increase of the green total factor productivity. The results are still significant through a series of robustness tests such as replacing variables and eliminating outliers; the positive intermediary effect of scientific and technological innovation exists, and the Sobel test and bootstrap random sampling test are passed. The upgrading of industrial structure has a positive regulating effect on the improvement of urban green total factor productivity. ② The impact of foreign direct investment on urban green total factor productivity has regional heterogeneity. The inhibitory effect of foreign direct investment on resource-based cities and non-coastal cities is greater than that on non-resource-based cities and coastal cities, and the negative impact on China-Europe train opening cities is greater than that on non-opening cities. Accordingly, the paper puts forward policy suggestions from the aspects of improving the quality of foreign direct investment and implementing differentiated management.

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The Impact of Foreign Direct Investment on Urban Green Total Factor Productivity and the Mechanism Test

Carbon emission reduction is becoming a global issue. Methods of reducing carbon emissions in developing countries have become a hot topic of discussion. Based on the obvious structural transformation in developing countries, this paper discusses the logical mechanisms among industrial structure upgrading, green total factor productivity improvements, and carbon emission reduction. In addition, this paper empirically tests these relationships with provincial data from 2000 to 2017 in China. The conclusions are as follows: (1) industrial structure upgrades have a significant impact on carbon emissions. The industrial structure rationalization remains a noteworthy inhibition on carbon emissions. The industrial structure’s advancement has obvious features of development at the current stage, and its effect on carbon emissions shows an inverted “V” trend, which is initially accelerating but then restraining. (2) Upgrades to industrial structures will decrease carbon emissions by raising green total factor productivity. (3) The rise of green total factor productivity in a certain region will have a relatively obvious inhibitory effect on carbon emissions, but it will exhibit a negative spatial spillover effect on the adjacent areas.

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Industrial Structure Upgrading, Green Total Factor Productivity and Carbon Emissions

In the socio-hydrological system, the social processes, ecological processes and hydrological processes coupled together and interacted. The base of the analysis and modeling of socio-hydrological processes is the quantitative analysis of the social processes. The construction of the middle route of the South-To-North Water Diversion Project in China and the implementation of the Dan River ecological management project will have an important impact on the socio-economic development of the upper Han River basin in China. In order to reveal the changing laws of social and economic indicators in the Upper Reach of Han River, The social and economic processes in the Upper Reach of Han River are quantitatively analyzed. In this study, 12 socio-economic indicators, such as Total population, Gross domestic product (GDP), Per capita net income of farmers, Fiscal revenue, Common cultivated land area and Total grain output of the 29 counties in the upper reach of the Han River Basin are utilized. Based on the year of Han River Ecological Comprehensive Management, the indicators and their growth rates are analyzed by methods of one-dimensional linear regression, Mann-Kendall comprehensive test and cumulative departure. Economic indicator curves and mutation analysis shows that before and after the Han River Ecological Management, the total grain output changed from the decline trend to significantly decreased, the common cultivated land area has experienced from the reduction to the significant reduction, then to the relatively stable change, the oil-bearing crops output showed a slight upward trend, and the other economic indicators changed from the slow upward trend to a significant upward trend. Growth rates curves of socio-economic indicators and mutation analysis shows that, during and especially after the period of Dan River Comprehensive Management, all of growth rates of the socio-economic indicators showed a downward trend in different ranges. According to the analysis results, some relevant ecological compensation suggestions are put forward for the Upper Reach of Han River Basin.

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Analysis of the Changing Laws and Influencing Factors of Social and Economic Indicators in the Upper Reach of Han River Basin

The Han River is the water source of the South-to-North Water Diversion Project and the “Han River to Wei River Water Diversion Project” in China. In order to ensure that the water quality and quantity are sufficient for the water diversion project, the natural forest protection project, river chief system and other measures have been implemented in the Han River by the government. At the same time, several large reservoirs have been built in the Han River basin and perform the functions of water supply and hydropower generation, which is an important type of clean power. Under the influence of human activities, the coupling interaction between humans and water in the upper reach of the Han River drives the socio-hydrological evolution process. In this study, from the perspective of socio-hydrology, a model of socio-hydrological evolution (SHE) in the Han River in southern Shaanxi was built to simulate the potential evolution path of the socio-hydrological system and determine possible measures for the sustainable governance of the river basin. By adjusting the model parameters, four future scenarios were established: natural continuation, economic development, environmental protection and industrial adjustment scenarios. Taking 2018 as the base year, the evolution of socio-hydrology in the upper reaches of the Han River was predicted under the four scenarios from 2019 to 2045. The simulation results show that: (1) In the entire study area, except for domestic water, the water consumption of other departments show an upward or stable trend. There are differences in water consumption changes in the upper and lower sections, which are related to the different socio-economic conditions. (2) Comparing different development scenarios, the industrial adjustment and environmental protection scenarios are superior to the other scenarios. Natural continuation and economic development scenarios appear to be unfavorable for the sustainability of water resources and the economy. (3) In addition, based on the development scenarios, some policy suggestions are put forward, such as reducing the irrigation water quota, appropriately adjusting the industrial structure and promoting the growth of the urban population and the development of urbanization.

Analysis of Socio-Hydrological Evolution Processes Based on a Modeling Approach in the Upper Reaches of the Han River in China

The invention discloses a kinetic equation-based basin social eco-hydrological evolution process simulation method The method comprises the following steps of: 1, carrying out simulation unit division; 2, establishing a social eco-hydrological evolution simulation model: 21, setting a state variable in a modeling unit, and 22, establishing a system dynamic process equation; 3, determining a simulation period and preparation model input data; 4, determining a main parameter value; 5, solving the model and using a history data calibrated parameter; and 6, carrying out simulation to obtain anevolution process The method is capable of solving the problems that the society more focuses on the value of ecological environment along with the highlighting of ecological environment problems asadaptation to water lack conditions is not considered, interaction among social economy, ecological environment and hydrography is not considered, and social economy-natural environment-hydrological state evolution processes cannot be obtained

Xiu Wei

Papers

Industrial Structure Upgrading, Green Total Factor Productivity and Carbon Emissions

Analysis of the Changing Laws and Influencing Factors of Social and Economic Indicators in the Upper Reach of Han River Basin

Analysis of Socio-Hydrological Evolution Processes Based on a Modeling Approach in the Upper Reaches of the Han River in China

Kinetic equation-based basin social eco-hydrological evolution process simulation method

Analysis of socio-economic driving forces of cultivated land area and its forecast in the upstream of Han River of China