Spatiotemporal Evolution and Influencing Factors of Carbon Sink Dynamics at County Scale: A Case Study of Shaanxi Province, China

To explore the spatiotemporal evolution of carbon sinks in Shaanxi Province, and their impact mechanisms, this study used panel data from 107 counties (districts) in Shaanxi Province from 2000 to 2017. First, we conducted spatial distribution directional analysis and exploratory spatial data analysis (ESDA). Then, we constructed a geographic spatial weight matrix and used the spatial panel Durbin model to analyze the driving factors of carbon sink changes in Shaanxi Province, from the perspective of spatial effects. The results showed that: (1) The temporal evolution of carbon sinks during the study period showed an overall upward trend, but the carbon sinks of counties (districts) differed greatly, and the center of gravity of carbon sinks, as a whole, showed the characteristics of “south to north” migration. (2) The carbon sinks of Shaanxi Province have a significant positive global spatial autocorrelation in geographic space. The local spatial pattern was characterized by low-value agglomeration (low-low cluster) and high-value agglomeration (high-high cluster), supplemented by high-value bulge (high-low outlier) and low-value collapse (low-high outlier). (3) The result of the spatial measurement model proved that the spatial Durbin model, with dual fixed effects of time and space, should be selected. In the model results, factors such as population, per capita gross domestic product (GDP), local government general budget expenditure, and local government general budget revenue all reflect strong spatial spillover effects. Accordingly, in the process of promoting “carbon neutrality”, the government needs to comprehensively consider the existence of spatial spillover effects between neighboring counties (districts), and strengthen the linkage-management and control roles of counties (districts) in increasing carbon sinks.

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Total-factor air environmental efficiency and its influencing factors in the areas along the Belt and Road in China: A spatial spillover perspective

Energy & Environment ◽

10.1177/0958305x211015146 ◽

2021 ◽

pp. 0958305X2110151

Author(s):

Ni-Ni Yin ◽

Ke-Liang Wang ◽

Zhen Yao ◽

Li-Li Ding ◽

Zhuang Miao

Keyword(s):

Economic Development ◽

Energy Consumption ◽

Fixed Effects ◽

Spillover Effects ◽

Environmental Efficiency ◽

Spatial Spillover ◽

Positive Effects ◽

Belt And Road ◽

Spatial Spillover Effects ◽

The Belt And Road

In order to promote sustainable economic development in the areas along the Belt and Road in China, it is of great necessity to reduce the negative impact of air pollutants resulting from industrialization and urbanization on the complex and fragile ecological environments of neighboring areas. First, this study estimated the total-factor air environmental efficiency (TFAEE) of 17 provinces along the Belt and Road in China from 2010 to 2017 using a slacks-based measure (SBM) model. Second, the global and local Moran indices were used to test the spatial correlations between TFAEEs. Finally, the spatial factors and spatial spillover effects influencing the TFAEEs were investigated using the spatial Durbin model with spatiotemporal double fixed effects. The results were shown as follows: (1) The total-factor TFAEEs of the areas along the Belt and Road were low and showed significant regional spatial differences during 2010–2017. (2) There was a positive spatial autocorrelation between the TFAEEs of the areas along the Belt and Road, and the spatial distribution generally clustered into High-High and Low-Low concentrations. (3) Economic development and technological innovation played significantly positive effects on TFAEEs of the areas in the Belt and Road, while energy consumption structure had negative effect on it. In addition, although industrial structure and environmental regulation were negatively correlated with TFAEEs, the coefficients were not significant. (4) The positive spatial spillover effect of the TFAEEs of the areas along the Belt and Road was mainly the result of significant environmental regulations and insignificant economic development factors, while the technological innovations, energy consumption structures and industrial structures showed insignificant negative spatial spillover effects.

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Agent-Based Modeling of Spatial Spillover Effects in Visitor Flows

Journal of Travel Research ◽

10.1177/0047287520930105 ◽

2020 ◽

pp. 004728752093010

Author(s):

Shan Li ◽

Yang Yang ◽

Zhangqi Zhong ◽

Xiaoli Tang

Keyword(s):

Spatial Data ◽

Spillover Effects ◽

Yangtze River Delta ◽

Agent Based Modeling ◽

Policy Implications ◽

Spatial Data Analysis ◽

Agent Based ◽

Spatial Spillover ◽

Yangtze River Delta Region ◽

Spatial Spillover Effects

In this study, we apply an agent-based modeling approach to understand individual visitors’ multidestination travel patterns and the spatial spillover effects in visitor flows as an aggregate outcome. Based on previous literature, we specify three hypothetic visitor categories (global optimizers, sequential optimizers, and radial optimizers) according to visitors’ attraction selection rules. We conduct an ABM simulation with a sample of 341 Chinese cities as destinations and 1,990 attractions to measure the degree of spillover between destinations by observing the frequency with which visitors traveling across destination boundaries visited attractions in other destinations. The simulation results demonstrate slightly different spillover effects based on visitor type and highlight three regions with particularly strong spillover effects: the Bohai Rim region, the Yangtze River Delta region, and the Sichuan and Chongqing region. These results appear consistent with those of exploratory spatial data analysis in a validation check. Lastly, policy implications are provided.

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