Dynamic Changes, Spatiotemporal Differences and Factors Influencing the Urban Eco-Efficiency in the Lower Reaches of the Yellow River

An innovative MGM-BPNN-ARIMA model for China's energy consumption structure forecasting from the perspective of compositional data

Effective forecasting of energy consumption structure is vital for China to reach its "dual carbon" objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023-2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China.

Can the digitalization level of agriculture improve its ecological efficiency under carbon constraints: Evidence from China

The interplay between digitalization and economic development constitutes a pivotal global issue, yet empirical research on agricultural ecological efficiency in developing countries remains limited. This study initially establishes a measurement system and a comprehensive index for the level of agricultural digitalization. Subsequently, it delineates the relationship between agricultural digitalization level and agroecological efficiency using the spatial Durbin model, and ultimately explores the enhancing effect of agricultural digitalization level on agroecological efficiency using China as a case study. Research reveals that the agricultural ecological efficiency across the 31 mainland Chinese provinces demonstrates a generally linear upward trajectory, embodying both agglomeration and heterogeneity. The level of agricultural digitization exerts a significant, positive direct impact and facilitates a spatial spillover effect on agricultural ecological efficiency. Other control variables, such as financial support for agriculture and local economic development, impart a positive direct impact on regional agricultural ecological efficiency, while rural household operating income propels a positive spatial spillover effect on adjacent areas. The findings furnish guidance for developing countries to adeptly execute digital rural construction, aiming to enhance agricultural ecological efficiency amidst carbon constraints.

Dynamic analysis of soil erosion in the affected area of the lower Yellow River based on RUSLE model

With the accelerated development of urbanization, the exploration and usage of land resources is becoming more and more frequent, which leads to the decline of soil quality, resulting in a series of soil ecological issues, such as soil nutrient loss, soil quality degradation and destruction. At present, the contradiction between soil erosion and sustainable development of human society has become one of the hot issues studied by scholars. The Yellow River Basin is an important experimental area for high-quality development in China, constructing the Yellow River Ecological Economic Belt play an important role in China's regional coordinated development. Although most of the affected area of the Lower Yellow River (AALYR) is in the plain, they have a large population density and are in the historical farming area. In latest years, because of the development and transformation of modern society, their ecological environment has become more fragile and soil erosion problems has become increasingly serious. Studying and analyzing soil erosion is of vital meaning for ecological protection and can provide scientific support for soil conservation work. Depending on the data of precipitation, soil properties, land use, population, etc., this paper studies and analyzes the soil erosion in AALYR from 2000 to 2020 through the RUSLE. We found that during the 20 years the proportion of very slight and slight grade area increased, and the distribution of moderate and above erosion grade was less, mainly in Zibo, Jinan, Anyang, Zhengzhou, and Tai 'an. Nearly three quarters of the regional soil erosion grade didn't change, apart from the increase of slight grade area, the other erosion grades area showed a downward trend. We take the city, county and town zoning analysis find that as the scale decreases, the area of serious erosion grades increases, and the distribution is gradually detailed. Land use is the main influencing factor of erosion except DEM. Forestland and grassland are larger of the soil erosion in various types of land use. Through these conclusions in this paper, it is promising to provide theoretical references for the ecological environment governance and high-quality and sustainable development of great river basins of the world and similar regions.

Spatio-temporal evolution characteristics of eco-efficiency in the Yellow River Basin of China based on the super-efficient SBM model

It is of great significance to study the trends and internal differences of eco-efficiency in the Yellow River Basin for ecological protection and high-quality development of the Yellow River Basin. According to the characteristics of the Yellow River Basin in China, the eco-efficiency evaluation system was constructed, and the super-efficiency slack-based measure (SBM) model and the super-efficiency SBM model of undesired output were used to calculate the eco-efficiency levels of provinces in the Yellow River Basin from 2005 to 2020, and the variation trend and internal differences were analyzed. The results show that when only the expected output was considered, the eco-efficiency of the Yellow River Basin as a whole and each province showed a fluctuating upward trend, but there were obvious differences. Qinghai Province, Sichuan Province, and Ningxia Autonomous Region had high eco-efficiency, while Shaanxi Province, Shanxi Province, and Inner Mongolia Autonomous Region had low eco-efficiency. Compared with only considering the expected outputs, eco-efficiency of Qinghai Province had improved significantly when considering non-expected outputs. The eco-efficiency of Shandong Province and Henan Province had improved significantly after 2016, while the eco-efficiency of the two provinces had decreased significantly before 2016. The eco-efficiency of Shaanxi, Shanxi, Inner Mongolia, Ningxia, and Gansu had declined to varying degrees. Finally, the reasons for the differences in eco-efficiency in various provinces in the Yellow River Basin were analyzed, and suggestions for improving the eco-efficiency of the Yellow River Basin were put forward.

Influencing factors and improvement paths of green water use efficiency in the Yellow River Basin: a new perspective based on ecogeographical divisions

Exploring the influencing factors and improvement paths of green water use efficiency (GWUE) based on different regions is very important for the protection and utilization of water resources in the Yellow River Basin (YRB). However, previous studies focused only on the external impact of water use efficiency and did not take into account both internal and external factors. For the zoning of the YRB, the traditional upper, middle, and lower zoning methods were mostly used, and they could not show the impact of climatic and geological conditions. Therefore, based on ecogeographical divisions, the dynamic evolutionary characteristics, regional differences, and internal inefficiencies of green water use efficiency for 48 cities in the YRB from 2008 to 2018 are analyzed using a data envelopment analysis-slack-based measure (DEA-SBM) model, global Malmquist‒Luenberger (GML) index decomposition, and kernel density estimation. We further use a panel Tobit model to analyze the external influencing factors of green water use efficiency and propose ways to improve the utilization of water resources in different regions from both the internal and external perspectives. The results are as follows: (1) During the study period, the GWUE fluctuated between 0.58 and 0.67 and showed a trend of improving in the arid areas and deteriorating in the humid area. (2) Exploring the sources of inefficiency from the internal perspective reveals that the labor redundancy, capital redundancy, and wastewater redundancy in the semihumid area are higher; the energy redundancy in the semiarid area is higher; and the economic output in the arid area is insufficient. (3) From the GML perspective, the absolute difference in the green water use efficiency of the cities in the YRB is expanding. Regarding the technical efficiency (EC) index, the technical efficiency of the semiarid area has a convergence effect. Regarding the technological progress (TC) index, the gap in the arid area has been widening, and the technology in the semihumid and semiarid areas is converging backward. (4) There are significant differences in the external factors affecting GWUE in different ecogeographical regions. This study can help the government consider ecogeographical factors when formulating water resource-related policies, and it provides a scientific reference for how to better utilize water resources in different regions of the YRB from both the internal and external perspectives.

Spatial-Temporal Pattern and Influencing Factors of Ecological Efficiency in Zhejiang-Based on Super-SBM Method

The traditional meaning of ecological efficiency generally considers only the ratio of economic output to environmental input. This paper expands the meaning and the evaluation system of ecological efficiency from the perspective of improving people's livelihoods. Not only are the discharge of wastewater, waste gas, and solid waste included in the undesired output, but the output index also takes full account of the overall development of the economy, innovation, society and the environment from the perspective of high-quality development. Under the assumption of variable returns to scale, a super-efficiency slack-based measure model based on the undesirable output and Malmquist index is introduced to measure the spatial and temporal variation of ecological efficiency of Zhejiang Province in China, and the panel Tobit method is used to study the key factors affecting ecological efficiency. The results include the four following findings: (1) In the past 12 years, the ecological efficiency of Zhejiang Province has steadily increased, except in 2019 and 2020, when seven cities in Zhejiang Province experienced a decline or near stagnation due to the impact of the economic slowdown and the COVID-19 epidemic. (2) The ecological efficiency of Zhejiang demonstrates a severe regional imbalance, showing a high level in the northeast and a low level in the southwest. (3) Malmquist index analysis shows that the improvement of ecological efficiency in Zhejiang Province has shifted from mainly relying on the dual drivers of pure technical efficiency and scale efficiency in the early stage to relying on technological progress in the later stage. (4) Tobit regression analysis shows that industrialization structure, Theil index, and traffic activity have a significant positive effect on ecological efficiency.

Spillover Effects of Built-Up Land Expansion Under Ecological Security Constraint at Multiple Spatial Scales

Land-use change is a global issue, and the built-up land expansion has affected the ecological landscape patterns of the major river basins in the world. However, measurement of the ecological risks of potential landscape and identification of the dynamic relationships by natural and human-driven built-up land expansion at different zoning scales are still less understood. Based on multi-period Landsat satellite image data, we combined remote sensing (RS) and geography information systems (GIS) technologies with Spatial Durbin Panel Model to quantitatively analyze the landscape ecological effects under the built-up land expansion in the Yellow River Basin. The results showed that there is spatial heterogeneity in the built-up land expansion and ecological security patterns, with the expansion gravity center gradually spreading from the downstream to the middle and upstream areas, and the most dramatic change in landscape patches of ecological safety patterns occurring around the year 2000. At different zoning scales, there is a spatial spillover effect on the interaction between built-up land expansion and ecological security, with the significance of the regression estimates decreasing from large sample sizes to small sample sizes. Our findings highlighted the importance of spatial heterogeneity at different zoning scales in identifying the dynamic relationship between built-up land expansion and ecological security, scientific planning of land resources, and mitigation of ecological and environmental crises.

Eco-Efficiency Assessment of Beijing-Tianjin-Hebei Urban Agglomeration Based on Emergy Analysis and Two-Layer System Dynamics

In the process of the economic development of the Beijing-Tianjin-Hebei urban agglomeration, ecological and environmental issues are still an important factor restricting high-quality development. The study of eco-efficiency is of great significance for coordinating the relationship between economy, resources and environment. This paper used a combinated method of two-layer system dynamics and emergy analysis to construct an emergy–system dynamics coupling model for eco-efficiency evaluation from the subsystems of resource flow, energy flow, currency flow and population flow of urban system, which is used to simulate and analyze the eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration. The results show that the overall eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration is not high, with an average value of 0.3786, and there is a trend of the value rising first and then falling from 2000 to 2035. The index values of emergy waste rate, contaminant emergy ratio, emergy output rate and environmental load rate after the decomposition of the eco-efficiency show that the high environmental pressure, the low re-use rate of pollutants and the low production efficiency of the system are important reasons for the low eco-efficiency in regional economic development. Finally, through scenario simulation, we propose that optimizing the economic structure, adjusting the population size and rationally arranging the fixed assets investment are conducive to improving the eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration.

Evolution Characters and Influencing Factors of Regional Eco-Efficiency in a Developing Country: Evidence from Mongolia

The sandstorm in 2021 in East Asia demonstrated the ecological issues that culminated for decades in Mongolia. Mongolia is facing challenges to realize green and sustainable development. This article aims to increase the understanding of eco-efficiency and its influencing factors in Mongolia and to provide a reference for similar developing countries and regions to achieve green and sustainable development. This article used the Slacks-Based Measure of Efficiency (SBM) model with advantages of dimension freedom and unit variable to estimate the economic efficiency and eco-efficiency of 22 provinces in Mongolia from 2007 to 2016; energy consumption and undesirable environmental outputs were taken as ecological/environmental indicators in the input and output system of regional eco-efficiency in Mongolia, combining traditional indicators of economic efficiency to build Mongolia's eco-efficiency input-output framework. This article applied hot spot analysis and gravity center analysis to reveal the temporal and spatial evolution characters of eco-efficiency in Mongolia. Finally, the article applied panel Tobit regression to analyze the influencing factors of eco-efficiency. We were found that Mongolia's eco-efficiency slightly improved from 0.7379 in 2007 to 0.7673 in 2016, lower than the economic efficiency. The high eco-efficiency provinces appeared in the capital Ulaanbaatar and its surrounding areas, showing an obvious spatial spillover effect. The low eco-efficiency provinces were mainly in the undeveloped western region. The relationship between per capita GDP and eco-efficiency was U-shaped and consistent with environmental Kuznets theory. Accelerating economic growth, optimizing population distribution, and improving energy structure and green technology can improve Mongolia's eco-efficiency.

Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors

Using panel data from 11 regions (9 provinces and two cities) in the Yangtze River Economic Belt (YREB) during 2002-2017, the regional differences in and spatial characteristics of the green efficiency of water resources along the YREB were analyzed. The undesirable outputs slacks-based measure-data envelopment analysis, Malmquist index, and social network analysis models were employed. A dynamic panel using a system generalized method of moments model was established to empirically examine the main factors influencing green efficiency. The results show the following. First, temporally, green efficiency fluctuates while showing an overall decreasing trend; spatially, green efficiency generally decreases in this order: downstream, upstream, then midstream. Second, the change in the total factor productivity (TFP) index shows an overall increasing trend, with TFP improvement mainly attributable to technology. Third, green efficiency shows a significant spatial correlation. All provinces are in the spatial correlation network, and the network, as a whole, has strong stability. Finally, water resource endowment, water prices, government environmental control strength, and the water resources utilization structure have a significant impact on green efficiency.