Sediment records of persistent organic pollutants (POPs) in relation to regional economic development: A comparison study in both Pearl River Delta and Yangtze River Delta, China

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.

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Spatially Explicit Assessment of Social Vulnerability in Coastal China

Sustainability ◽

10.3390/su11185075 ◽

2019 ◽

Vol 11 (18) ◽

pp. 5075

Author(s):

Xuchao Yang ◽

Lin Lin ◽

Yizhe Zhang ◽

Tingting Ye ◽

Qian Chen ◽

...

Keyword(s):

Social Vulnerability ◽

Urban Areas ◽

Pearl River Delta ◽

Yangtze River ◽

Census Data ◽

Yangtze River Delta ◽

River Delta ◽

Pearl River ◽

Social Resilience ◽

Effective Measure

Social vulnerability assessment has been recognized as a reliable and effective measure for informing coastal hazard management. Although significant advances have been made in the study of social vulnerability for over two decades, China’s social vulnerability profiles are mainly based on administrative unit. Consequently, no detailed distribution is provided, and the capability to diagnose human risks is hindered. In this study, we established a social vulnerability index (SoVI) in 2000 and 2010 at a spatial resolution of 250 m for China’s coastal zone by combining the potential exposure index (PEI) and social resilience index (SRI). The PEI with a 250 m resolution was obtained by fitting the census data and multisource remote sensing data in random forest model. The county-level SRI was evaluated through principal component analysis based on 33 socioeconomic variables. For identifying the spatiotemporal change, we used global and local Moran’s I to map clusters of SoVI and its percent change in the decade. The results suggest the following: (1) Counties in the Yangtze River Delta, Pearl River Delta, and eastern Guangzhou, except several small hot spots, exhibited the most vulnerability, especially in urban areas, whereas those in Hainan and southern Liaoning presented the least vulnerability. (2) Notable increases were emphasized in Tianjin, Yangtze River Delta, and Pearl River Delta. The spatiotemporal variation and heterogeneity in social vulnerability obtained through this analysis will provide a scientific basis to decision-makers to focus risk mitigation effort.

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Comparative Analysis of Urban Competitiveness in the Yangtze River Delta and Pearl River Delta Regions of China, 2000–2010

Applied Spatial Analysis and Policy ◽

10.1007/s12061-016-9210-6 ◽

2016 ◽

Vol 10 (3) ◽

pp. 401-419 ◽

Cited By ~ 5

Author(s):

Lei Wang ◽

Jianfa Shen

Keyword(s):

Comparative Analysis ◽

Pearl River Delta ◽

Yangtze River ◽

Yangtze River Delta ◽

River Delta ◽

Pearl River ◽

The Yangtze River ◽

Urban Competitiveness ◽

The Yangtze River Delta

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Study on Dynamic Total Factor Carbon Emission Efficiency in China’s Urban Agglomerations

Sustainability ◽

10.3390/su12072675 ◽

2020 ◽

Vol 12 (7) ◽

pp. 2675

Author(s):

Fan Zhang ◽

Gui Jin ◽

Junlong Li ◽

Chao Wang ◽

Ning Xu

Keyword(s):

Pearl River Delta ◽

Yangtze River ◽

Carbon Emission ◽

Yangtze River Delta ◽

River Delta ◽

Pearl River ◽

Low Carbon ◽

Frontier Analysis ◽

Urban Agglomerations ◽

Emission Efficiency

The scale effect of urbanization on improving carbon emission efficiency and achieving low-carbon targets is an important topic in urban research. Using dynamic panel data from 64 prefecture-level cities in four typical urban agglomerations in China from 2006 to 2016, this paper constructed a stochastic frontier analysis model to empirically measure the city-level total-factor carbon emission efficiency index (TCEI) at different stages of urbanization and to identify rules governing its spatiotemporal evolution. We quantitatively analyzed the influences and functional characteristics of TCEI in the four urban agglomerations of Pearl River Delta, Beijing-Tianjin-Hebei, the Yangtze River Delta, and Chengdu-Chongqing. Results show that the TCEI at different stages of urbanization in these urban agglomerations is increasing year by year. The overall city-level TCEI was ranked as follows: Pearl River Delta > Beijing-Tianjin-Hebei > Yangtze River Delta > Chengdu-Chongqing. Improvements in the level of economic development and urbanization will help achieve low-carbon development in a given urban agglomeration. The optimization of industrial structure and improvement of ecological environment will help curb carbon emissions. This paper provides decision-making references for regional carbon emission reduction from optimizing industrial and energy consumption structures and improving energy efficiency.

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