scholarly journals The Moderating Effect of Innovation on the Relationship between Urbanization and CO2 Emissions: Evidence from Three Major Urban Agglomerations in China

2019 ◽  
Vol 11 (6) ◽  
pp. 1633 ◽  
Author(s):  
Yanwen Sheng ◽  
Yi Miao ◽  
Jinping Song ◽  
Hongyan Shen
Keyword(s):  
Co2 Emissions ◽  
Spillover Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Policy Implications ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
The Yrd ◽  
The Relationship ◽  
Spatial Spillover Effect

This study investigates the relationship between urbanization, innovation, and CO2 emissions, with particular attention paid to the issue of how innovation influences the effect of urbanization on CO2 emissions in urban agglomerations, considering the spatial spillover effect between cities. Therefore, based on panel data on 48 cities in the three major urban agglomerations in China from 2001–2015, a spatial econometric model is used to estimate the effect of urbanization and innovation on CO2 emissions. The empirical results indicate that the relationship between urbanization and CO2 emissions follows a U-shaped curve in the Beijing-Tianjin-Hebei (BTH), an N-shaped curve in the Yangtze River Delta (YRD) and an inverted N-shaped pattern in the Pearl River Delta (PRD). Additionally, innovation shows a significantly positive effect on reducing CO2 emissions in the YRD, but does not exert a significantly direct effect on CO2 emissions in the BTH and the PRD. More importantly, innovation played an important moderating role between urbanization and CO2 emissions in the YRD and PRD, suggesting that reducing the positive impacts of urbanization on CO2 emissions depends on innovative development. In addition, urban CO2 emissions presented a clearly negative spatial spillover effect among the cities in the three urban agglomerations. These findings and the following policy implications will contribute to reducing CO2 emissions.

scholarly journals Reexamining the Impact of Industrial Structure on Haze Pollution Based on the Yangtze River Delta

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 613
Author(s):  
Lu Wang ◽  
Shumin Jiang ◽  
Hua Xu
Keyword(s):  
Yangtze River ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Inhibitory Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatial Spillover ◽  
Haze Pollution ◽  
The Impact ◽  
Spatial Spillover Effect

In this study, the static and dynamic spatial Durbin model between industrial structure and haze pollution in Yangtze River Delta is constructed. Later, the spatial spillover effect and time lag effect of haze pollution in Yangtze River Delta are analyzed. The impact of rationalization and upgrading of industrial structure on haze pollution and its spatial spillover effect are discussed. The results show that: (i) PM2.5 has a significant positive spatial spillover effect and time lag effect; (ii) in the short run, the rationalization and upgrading of industrial structure has no inhibitory effect on haze pollution, while the rationalization and upgrading of industrial structure of surrounding cities has an inhibitory effect on local haze pollution; (iii) in the long run, the rationalization and upgrading of industrial structure of surrounding cities have an inhibitory effect on local haze pollution; (iv) economic growth, FDI, the number of Industrial Enterprises above Designated Size, and population density also have spatial spillover effects on haze pollution. Therefore, considering the spatial spillover effect of haze pollution from the perspective of urban agglomeration and long-term, strengthening the joint prevention and control and comprehensive treatment among cities, further promoting the rationalization and upgrading of industrial structure is conducive to reducing haze pollution.

scholarly journals Impact of Financial Development and Its Spatial Spillover Effect on Green Total Factor Productivity: Evidence from 30 Provinces in China

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Junhao Zhong ◽  
Tinghui Li
Keyword(s):  
Total Factor Productivity ◽  
Financial Development ◽  
Spillover Effect ◽  
Policy Implications ◽  
Pollutant Emissions ◽  
Factor Productivity ◽  
Spatial Spillover ◽  
Surrounding Areas ◽  
The Relationship ◽  
Spatial Spillover Effect

The relationship between financial development and green economic growth has received much attention in recent years. Research on the relationship between financial development and green total factor productivity (GTFP) is of great importance to China and other countries. This study has attempted to reveal the spatial distribution of China’s provincial GTFP and impact of financial development on GTFP by using the method of GML index based on SBM-DDF and the spatial Durbin model (SDM) during the period 1996–2015. Innovation is added to the SDM to reflect the influencing mechanism of financial development on GTFP. The empirical results show the following: (1) The mean of China’s provincial GTFP showed a U-shaped curve in 1996–2015. (2) China’s provincial financial development promotes the growth of GTFP through innovation channel. The reason is that financial development boosts eco-friendly innovation and the introduction of energy saving technology, leading to a decrease in energy consumption and pollutant emissions. (3) Increasing the level of financial development in the surrounding areas will restrain local GTFP. Our results provide new evidence that China’s regional financial development has a spatial spillover effect. (4) China’s provincial GTFP has a significant spatial positive correlation. Finally, several policy implications can be summarized to China’s 30 provinces.

Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

2021 ◽  
pp. 135481662110211
Author(s):  
Honghong Liu ◽  
Ye Xiao ◽  
Bin Wang ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Tourism Development ◽  
Spillover Effects ◽  
Policy Implications ◽  
Long Term Effects ◽  
Spatial Spillover ◽  
Domestic Tourism ◽  
Inbound Tourism ◽  
Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

scholarly journals Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

2021 ◽  
Vol 13 (14) ◽  
pp. 8032
Author(s):  
Chengzhuo Wu ◽  
Li Zhuo ◽  
Zhuo Chen ◽  
Haiyan Tao
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
Search Index ◽  
Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

scholarly journals Integrating Sustainability Assessment into Decoupling Analysis: A Focus on the Yangtze River Delta Urban Agglomerations

2020 ◽  
Vol 12 (19) ◽  
pp. 7872
Author(s):  
Yijia Huang ◽  
Jiaqi Zhang ◽  
Jinqun Wu
Keyword(s):  
Environmental Sustainability ◽  
Yangtze River ◽  
Sustainability Assessment ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Decoupling Analysis ◽  
The Yrd ◽  
The Yangtze River Delta

Rapid urbanization has led to a growing number of environmental challenges in large parts of China, where the Yangtze River Delta (YRD) urban agglomerations serve as a typical example. To evaluate the relationship between environmental sustainability gaps and urbanization in 26 cities of the YRD, this study revisited the environmental sustainability assessment (ESA) by combining the metrics of environmental footprints and planetary boundaries at the city level, and then integrated the footprint-boundary ESA framework into decoupling analysis. The results demonstrated considerable spatiotemporal heterogeneity in the environmental sustainability of water use, land use, carbon emissions, nitrogen emissions, phosphorus emissions and PM2.5 emissions across the YRD cities during the study period 2007–2017. Decoupling analysis revealed a positive sign that more than half of the 26 cities had achieved the decoupling of each category of environmental sustainability gaps from urbanization since 2014, especially for nitrogen and phosphorus emissions. On the basis of ESA and decoupling analysis, all the cities were categorized into six patterns, for which the optimal pathways towards sustainable development were discussed in depth. Our study will assist policy makers in formulating more tangible and differentiated policies to achieve decoupling between environmental sustainability gaps and urbanization.

scholarly journals Spatial-Temporal Differences and Influencing Factors of Tourism Eco-Efficiency in China’s Three Major Urban Agglomerations Based on the Super-EBM Model

2020 ◽  
Vol 12 (10) ◽  
pp. 4156
Author(s):  
Yiyang Sun ◽  
Guolin Hou ◽  
Zhenfang Huang ◽  
Yi Zhong
Keyword(s):  
Pearl River Delta ◽  
Yangtze River ◽  
Eastern China ◽  
Yangtze River Delta ◽  
Tourism Industry ◽  
External Factors ◽  
River Delta ◽  
Policy Implications ◽  
Pearl River ◽  
Urban Agglomerations

On the background of climate change, studying tourism eco-efficiency of cities is of great significance to promote the green development of tourism. Based on the panel data of the three major urban agglomerations in China’s Yangtze River Delta, Pearl River Delta, and Beijing–Tianjin–Hebei region from 2008 to 2017, this paper constructed an evaluation index system and measured the tourism eco-efficiency of 63 cities by using a hybrid distance model called Super-EBM (epsilon-based measure). We compared the spatial and temporal evolution characteristics of tourism eco-efficiency in the three urban agglomerations. Furthermore, the internal factors influencing tourism eco-efficiency were explored through input–output redundancy, and the external factors were analyzed by a panel regression model. The results indicate that the tourism eco-efficiency of the three urban agglomerations in China generally shows a decreasing-rising-declining trend. Among them, the Yangtze River Delta has the highest eco-efficiency, followed by the Pearl River Delta, and the lowest in the Beijing–Tianjin–Hebei region. Moreover, there is a certain gap within each urban agglomeration. The redundancy input of labor and capital is the main internal cause of low eco-efficiency. Among the external factors, the status of the tourism industry and the level of urbanization have a positive effect on eco-efficiency, while the level of tourism development, technological innovation and investment have a negative impact on it. In the future, we must attach great importance to the development quality and overall benefit value of the tourism industry so as to achieve green and balanced development of the three major urban agglomerations in eastern China. Based on the above conclusions, this paper puts forward targeted policy implications to improve the tourism eco-efficiency of cities.

scholarly journals Does Environmental Regulation Repress the International R&D Spillover Effect? Evidence from China

2019 ◽  
Vol 11 (16) ◽  
pp. 4353
Author(s):  
Chengliang Liu ◽  
Tao Wang ◽  
Qingbin Guo
Keyword(s):  
Environmental Regulation ◽  
Open Economy ◽  
Spillover Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Policy Suggestions ◽  
Economic Regions ◽  
Relationship Of ◽  
Import Trade ◽  
The Relationship

The inconsistent direction between environmental regulation and technological progress is receiving increasing attention, but scholars have neglected the relationship between the two in the open economy. Against this background and based on the panel data of 30 provinces in China from 2003 to 2015, we examined the effect of environmental regulation on the international research and development (R&D) spillover effect and its regional differences in three economic regions: The Bohai Rim, Pan-Yangtze River Delta, and Pan-Pearl River Delta economic regions. The results show that (1) at China’s macro level, and at that of the three economic regions, the level of environmental regulation and international R&D spillover from import trade or foreign direct investment channels show an inverted N relationship; that is, in all provinces the weak environmental regulation initially inhibited the international technology spillover. However, as the intensity of environmental regulation increased, the level of international R&D spillovers continually rose, but overly harsh environmental regulation was not conducive to the overflow of international technology; (2) the adoption of different environmental regulations will affect the international R&D spillover effect and the inverted N relationship of environmental regulation, thus changing the inflection point of environmental regulation; and (3) currently, the level of environmental regulation is relatively low, as most provinces have not yet broken through the first turning point of the inverted N, and only a few provinces are within the rising stage of the inverted N curve. This paper provides corresponding policy suggestions according to the above conclusions.

scholarly journals Anthropogenic and natural controls on atmospheric <i>δ</i><sup>13</sup>C-CO<sub>2</sub> variations in the Yangtze River delta: insights from a carbon isotope modeling framework

2021 ◽  
Vol 21 (13) ◽  
pp. 10015-10037
Author(s):  
Cheng Hu ◽  
Jiaping Xu ◽  
Cheng Liu ◽  
Yan Chen ◽  
Dong Yang ◽  
...  
Keyword(s):  
Carbon Isotope ◽  
Co2 Emissions ◽  
Inverse Modeling ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Anthropogenic Co2 ◽  
The Yrd ◽  
The Yangtze River Delta

Abstract. The atmospheric carbon dioxide (CO2) mixing ratio and its carbon isotope (δ13C-CO2) composition contain important CO2 sink and source information spanning from ecosystem to global scales. The observation and simulation for both CO2 and δ13C-CO2 can be used to constrain regional emissions and better understand the anthropogenic and natural mechanisms that control δ13C-CO2 variations. Such work remains rare for urban environments, especially megacities. Here, we used near-continuous CO2 and δ13C-CO2 measurements, from September 2013 to August 2015, and inverse modeling to constrain the CO2 budget and investigate the main factors that dominated δ13C-CO2 variations for the Yangtze River delta (YRD) region, one of the largest anthropogenic CO2 hotspots and densely populated regions in China. We used the WRF-STILT model framework with category-specified EDGAR v4.3.2 CO2 inventories to simulate hourly CO2 mixing ratios and δ13C-CO2, evaluated these simulations with observations, and constrained the total anthropogenic CO2 emission. We show that (1) top-down and bottom-up estimates of anthropogenic CO2 emissions agreed well (bias < 6 %) on an annual basis, (2) the WRF-STILT model can generally reproduce the observed diel and seasonal atmospheric δ13C-CO2 variations, and (3) anthropogenic CO2 emissions played a much larger role than ecosystems in controlling the δ13C-CO2 seasonality. When excluding ecosystem respiration and photosynthetic discrimination in the YRD area, δ13C-CO2 seasonality increased from 1.53 ‰ to 1.66 ‰. (4) Atmospheric transport processes in summer amplified the cement CO2 enhancement proportions in the YRD area, which dominated monthly δs (the mixture of δ13C-CO2 from all regional end-members) variations. These findings show that the combination of long-term atmospheric carbon isotope observations and inverse modeling can provide a powerful constraint on the carbon cycle of these complex megacities.

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