scholarly journals Temporal-Spatial Structure and Influencing Factors of Urban Energy Efficiency in China’s Agglomeration Areas

2021 ◽  
Vol 13 (19) ◽  
pp. 10961
Author(s):  
Luping Zhang ◽  
Yingying Zhu ◽  
Liwei Fan
Keyword(s):  
Energy Efficiency ◽  
Influencing Factors ◽  
Network Structure ◽  
Yangtze River ◽  
Spatial Association ◽  
Urban Agglomeration ◽  
Spatial Network ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Urban Energy

Energy efficiency has proved to be effective in mitigating greenhouse gas emissions and is significant to carbon neutrality targets. Urban agglomeration is the major engine of urbanization supporting economic growth. To optimizing the spatial exchange structure to improve regional energy efficiency by integrating the total factor energy efficiency model and social network analysis, this study constructs the spatial network of energy efficiency among cities within five major urban agglomerations in China for the period 2011–2018 and investigates their spatial association characteristics. The influencing factors of each spatial network structure are also explored by the quadratic assignment procedure method. The findings show that the spatial association of energy efficiency within each urban agglomeration presents a typical network structure, but with considerable disparity among urban agglomerations. Most cities in the Yangtze River Delta and Pearl River Delta are closely connected with each other, while the surrounding cities in the areas of Beijing-Tianjin-Hebei, Chengyu and the Middle Reaches of the Yangtze River highly depend on their corresponding central cities. The spatial adjacency and GDP per capita determine the urban spatial relationship of the energy efficiency within urban agglomerations. In addition, the spatial correlation of urban energy efficiency in the Beijing-Tianjin-Hebei, Chengyu and Middle Reaches of the Yangtze River areas is also affected by the differences in energy consumption, capital stock, number of labor force and pollutant emission. Some suggestions for improving urban energy efficiency are discussed.

scholarly journals Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration

2021 ◽  
Vol 18 (5) ◽  
pp. 2577
Author(s):  
Yiyang Sun ◽  
Guolin Hou
Keyword(s):  
Network Structure ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
Spatial Network ◽  
The Yangtze River ◽  
Regional Tourism ◽  
Evolution Characteristics ◽  
The Yangtze River Delta

Based on the panel data of 41 cities in the Yangtze River Delta from 2008 to 2017, this paper constructs an evaluation indicators system for urban tourism eco-efficiency. By measuring the tourism eco-efficiency in the Yangtze River Delta urban agglomeration, we analyze its spatial-temporal evolution characteristics. Furthermore, the modified gravity model and social network analysis are introduced to explore the spatial network structure of tourism eco-efficiency and its evolution trend.The results show that:(1) The overall eco-efficiency of tourism in the Yangtze River Delta region presents a fluctuating downward trend, among which Jiangsu and Zhejiang have high eco-efficiency, Shanghai and Anhui are relatively low. The gap within the region first increased and then decreased. (2) During this decade, the spatial network structure of tourism eco-efficiency in the Yangtze River Delta has become increasingly loose. The weakening of the network connection strength has led to a decrease in the regional tourism eco-efficiency to a great extent. (3) The network centrality of cities such as Zhoushan, Huzhou, and Huangshan has always maintained a high level, and these cities have firmly occupied the core position of network. (4) The spatial association network of tourism eco-efficiency can be divided into four blocks: “two-way spillover”, “net spillover”, “net benefit” and “agent”. The synergy and spillover effect between various blocks are significant, and there is a spatial polarization trend centered on a few cities. Based on this, this paper puts forward optimization suggestions for the spatial network structure of the Yangtze River Delta urban agglomeration, in anticipation of promoting the improvement of regional tourism eco-efficiency.

scholarly journals Research on Urban Spatial Connection and Network Structure of Urban Agglomeration in Yangtze River Delta—Based on the Perspective of Information Flow

2021 ◽  
Vol 18 (19) ◽  
pp. 10288
Author(s):  
Qiaowen Lin ◽  
Mengyu Xiang ◽  
Lu Zhang ◽  
Jinjiang Yao ◽  
Chao Wei ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Network Structure ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Flow Network ◽  
The Yangtze River Delta

Exploration of urban spatial connections and network structures of urban agglomeration in the Yangtze River Delta, as well as its influencing factors, is of great significance regarding optimization of the development pattern of the Yangtze River Delta urban agglomeration and promotion of regional high-quality development. Therefore, based on Baidu index data in 2015 and 2019, this paper first analyzes the spatiotemporal variation characteristics of information-flow connections in the Yangtze River Delta urban agglomeration. Then it uses social network analysis to explore the information-flow network structure in the Yangtze River Delta urban agglomeration, and finally explores the influencing factors of information-flow intensity in the Yangtze River Delta urban agglomeration. The main conclusions are as follows: (1) The total amount of information flow in the Yangtze River Delta urban agglomeration has had no obvious change, and the coverage of information flow in the central urban circle has expanded. (2) The network hierarchy presents a relatively stable “pyramid” distribution pattern, which tends to develop into a “spindle” pattern. (3) The overall network density of the Yangtze River Delta urban agglomeration is high and is increasing. The backbone network is a “triangle” structure. The central cities in the region are stable, and the subgroups are adjacent to each other geographically. (4) Gross Domestic Product, resident population of the region and the number of Internet broadband subscribers all have important effects on the total information flow, among which the number of Internet broadband subscribers has the greatest effect on the total information flow. In addition, urban functions and their positioning, urban events, history and culture, and other factors that are difficult to quantify also have a certain impact on the information-flow network among cities.

scholarly journals Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt

2021 ◽  
Vol 18 (5) ◽  
pp. 2222
Author(s):  
Jin-Wei Yan ◽  
Fei Tao ◽  
Shuai-Qian Zhang ◽  
Shuang Lin ◽  
Tong Zhou
Keyword(s):  
Geographically Weighted Regression ◽  
Yangtze River ◽  
National Level ◽  
National Development ◽  
Urban Agglomeration ◽  
Spatiotemporal Distribution ◽  
Weighted Regression ◽  
Series Data ◽  
The Yangtze River ◽  
Urban Agglomerations

As part of one of the five major national development strategies, the Yangtze River Economic Belt (YREB), including the three national-level urban agglomerations (the Cheng-Yu urban agglomeration (CY-UA), the Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and the Yangtze River Delta urban agglomeration (YRD-UA)), plays an important role in China’s urban development and economic construction. However, the rapid economic growth of the past decades has caused frequent regional air pollution incidents, as indicated by high levels of fine particulate matter (PM2.5). Therefore, a driving force factor analysis based on the PM2.5 of the whole area would provide more information. This paper focuses on the three urban agglomerations in the YREB and uses exploratory data analysis and geostatistics methods to describe the spatiotemporal distribution patterns of air quality based on long-term PM2.5 series data from 2015 to 2018. First, the main driving factor of the spatial stratified heterogeneity of PM2.5 was determined through the Geodetector model, and then the influence mechanism of the factors with strong explanatory power was extrapolated using the Multiscale Geographically Weighted Regression (MGWR) models. The results showed that the number of enterprises, social public vehicles, total precipitation, wind speed, and green coverage in the built-up area had the most significant impacts on the distribution of PM2.5. The regression by MGWR was found to be more efficient than that by traditional Geographically Weighted Regression (GWR), further showing that the main factors varied significantly among the three urban agglomerations in affecting the special and temporal features.

scholarly journals The Evolution of the Urban Spatial Pattern in the Yangtze River Economic Belt: Based on Multi-Source Remote Sensing Data

2018 ◽  
Vol 10 (8) ◽  
pp. 2733 ◽  
Author(s):  
Yang Li ◽  
Hua Shao ◽  
Nan Jiang ◽  
Ge Shi ◽  
Xin Cheng
Keyword(s):  
Size Distribution ◽  
Urban Areas ◽  
Yangtze River ◽  
Size Structure ◽  
Urban Land ◽  
Urban Agglomeration ◽  
Spatial Distance ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Urban Size

The development of the Yangtze River Economic Belt (YREB) is an important national regional development strategy and a strategic engineering development system. In this study, the evolution of urban spatial patterns in the YREB from 1990 to 2010 was mapped using the nighttime stable light (NSL) data, multi-temporal urban land products, and multiple sources of geographic data by using the rank-size distribution and the Gini coefficient method. Through statistical results, we found that urban land takes on the feature of “high in the east and low in the west”. The study area included cities of different development stages and sizes. The nighttime light increased in most cities from 1992 to 2010, and the rate assumed an obvious growth tendency in the three urban agglomerations in the YREB. The results revealed that the urban size distribution of the YREB is relatively dispersed, the speed of urban development is unequal, and the trend of urban size structure shows a decentralized distribution pattern that has continuously strengthened from 1990 to 2010. Affected by factors such as geographical conditions, spatial distance, and development stage, the lower reaches of the Yangtze River have developed rapidly, the upper and middle reaches have developed large cities, and a contiguous development trend is not obvious. The evolution of urban agglomerations in the region presents a variety of spatial development characteristics. Jiangsu, Zhejiang, and Shanghai have entered a phase of urban continuation, forming a more mature interregional urban agglomeration, while the YREB inland urban agglomerations are in suburbanization and multi-centered urban areas. At this stage, the conditions for the formation of transregional urban agglomerations do not yet exist, and there are many uncertainties in the boundary and spatial structure of each urban agglomeration.

Government cooperation, market integration, and energy efficiency in urban agglomerations—Based on the quasi-natural experiment of the Yangtze River Delta Urban Economic Coordination Committee

2021 ◽  
pp. 0958305X2110474
Author(s):  
Da Gao ◽  
Ge Li ◽  
Yi Li
Keyword(s):  
Energy Efficiency ◽  
Yangtze River ◽  
Market Integration ◽  
Natural Experiment ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
The Government ◽  
The Yangtze River Delta

Energy efficiency is the key to green development, and the government plays a vital role in energy efficiency. This paper clarifies the mechanism by which the Yangtze River Delta Economic Coordination Committee affects the energy efficiency of urban agglomeration by promoting market integration. Based on panel data of China's prefecture-level cities from 2004 to 2017, we take the Yangtze River Delta Economic Coordination Committee as a quasi-natural experiment of government cooperation and use the difference-in-difference method to test whether this organization has enhanced the energy efficiency of urban agglomeration. The results show that the Yangtze River Delta Economic Coordination Committee can significantly improve energy efficiency in urban agglomerations. The mechanism analysis shows that it reduces the energy consumption per unit of gross domestic product by enhancing the marketization level, perfecting the relationship between the government and the market, and improving the factor market development. The heterogeneity analysis shows that cities with lower city size, lower level of innovation, and cleaner industrial structures gain more benefits in energy efficiency from government cooperation in urban agglomeration. This paper provides empirical evidence for cities to realize integrated energy conservation through government cooperation and market integration.

scholarly journals Research on the Dynamics and Evolution of Regional Blue-green Space Driven by the Development of World-class Urban Agglomerations

2021 ◽  
Author(s):  
Ziwu Pan ◽  
Jun Zhu ◽  
Zhenzhen Liu ◽  
Fen Qin
Keyword(s):  
Yangtze River ◽  
Green Space ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
Heat Island ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Island Effect ◽  
The Yangtze River Delta

Abstract In recent years, the process of urbanization in China has accelerated, and changes in the underlying surface have caused the difference in average temperature between built-up areas and suburbs to increase, resulting in an urban heat island effect, which has become an important environmental issue for today's urban sustainable development. The Yangtze River Delta urban agglomeration region is the fastest-growing region in China, with economically developed and populous cities such as Shanghai, Nanjing and Suzhou. It has become one of the six major urban agglomerations in the world, and its heat island effect is particularly prominent. The single urban heat island phenomenon gradually evolves into the urban agglomeration heat island phenomenon with urbanization. However, the dynamic transfer process of key blue-green space landscapes that can alleviate land surface temperature (LST) and regional thermal environment (RTE) is still poorly understood, especially in the context of urban agglomerations. With the approval of the State Council on the development plan of the Huaihe River Ecological Economic Belt, the construction of which has been officially upgraded to a national strategy. The Eastern HaiJiang River and Lake Linkage Zone (EJRLLZ) emphasizes strengthening the docking and interaction with the surrounding areas such as the Yangtze River Delta and the Wanjiang City Belt. With the diffusion of the heat island effect of the Yangtze River Delta urban agglomeration, as one of the areas with great potential development around the world-class urban agglomeration, the rich water body and green space in the ERLLZ area are also destroyed and affected. Therefore, we take this region as a case to further quantify the impact of urbanization and urban agglomeration development on the dynamics and evolution of blue-green space.

scholarly journals The Energy Efficiency and the Main Influencing Factors for the Logistics Industry in the Yangtze River Economic Belt in China

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xun Li ◽  
Chuan Lin
Keyword(s):  
Energy Efficiency ◽  
Technical Efficiency ◽  
Influencing Factors ◽  
Yangtze River ◽  
Scale Efficiency ◽  
Energy Structure ◽  
The Yangtze River ◽  
Service Capacity ◽  
Logistics Industry ◽  
East Central

Logistics is the booster of economic development, and it is imperative to further improve the logistics energy efficiency and adjust its development model. This paper is an attempt to investigate the logistics energy efficiency and main influencing factors of the Yangtze River Economic Belt, which is the most economically intensive region that spans East, Central, and West China. The input-oriented SBM-DEA model is employed to identify factors such as energy input, undesirable output, and service capacity output as well as the logistics energy efficiency of Yangtze River Economic Belt. Energy efficiency is then further decomposed into pure technical efficiency, scale efficiency, and technical efficiency, from the perspective of which provinces and cities are compared. The research results show that the logistics energy efficiency of Yangtze River Economic Belt needs to be further improved and that energy efficiency differs greatly among cities and provinces, indicating that the development is quite unbalanced in different areas. Therefore, the local government should develop development strategies according to the main influencing factors and constraints to the local logistics industry, so as to optimize and upgrade the energy structure of the logistics industry.

Spatial and temporal pattern evolution and influencing factors of energy–environmental efficiency: A case study of Yangtze River urban agglomeration in China

2020 ◽  
pp. 0958305X2092311
Author(s):  
Zhaoqiang Zhong ◽  
Benhong Peng ◽  
Ehsan Elahi
Keyword(s):  
Influencing Factors ◽  
Temporal Pattern ◽  
Yangtze River ◽  
Government Regulation ◽  
Polar Nucleus ◽  
Environmental Efficiency ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Tobit Regression ◽  
Positive Effects

Improving energy–environmental efficiency is prerequisite for sustainable development. In order to explore ways to improve energy–environmental efficiency, this paper uses the undesired output slack-based model to measure the energy–environmental efficiency of the Yangtze River urban agglomeration based on the input and output index data from 2008 to 2017, and its spatial and temporal pattern evolution is analyzed by using kernel density estimation, Gini coefficient, and coefficient of variation. Moreover, the Tobit regression model is used to analyze the influencing factors of the energy–environmental efficiency of the Yangtze River urban agglomeration. The results indicate that the energy–environmental efficiency of each city is increased continuously, and the regional differences are gradually narrowed. The spatial pattern is changed from polar nucleus type to valley type, and finally the distribution characteristics of “overall high” are formed. Overall, the energy–environmental efficiency presents a spatial layout of “high in the east and low in the west.” The regression results show that the level of economic development and energy–environmental efficiency are “U-type” associated characteristics, and government regulation and population density have significant positive effects on it. Industrial structure and technological progress have negative effects on it, and the effect of opening degree is not significant.

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