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Wang X, Liu G, Zhang C, Liao Y. Spatial-temporal pattern and urban-rural gradient of comprehensive ecological security in urban agglomeration in South China from 2000 to 2020. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:102474-102489. [PMID: 37668775 DOI: 10.1007/s11356-023-29460-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 08/18/2023] [Indexed: 09/06/2023]
Abstract
The ecological security (ES) of urban agglomeration and surrounding environmental system is related to the sustainable development of cities, which is a hot spot that we must pay attention to. In this study, four subsystems composed of natural base, landscape structure, ecosystem stability, and anthropogenic interference were used to evaluate the comprehensive ecological security (CES) of Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA) in 2000, 2010 and 2020. The results show that CES of the region was generally well. The central urban region of GHMGBA was unsafety with an area proportion of about 24.5%, the periphery was safety with an area proportion of about 43.5%, and the others are transitional zone. From 2000 to 2020, the CES change first slightly decreases and then relatively stable, and the transfer of different safety levels mainly occurs in the transitional zone. In 2010-2020 the transfer of different levels of CES is more frequent than in 2000-2010, indicating that the spatial-temporal pattern of CES fluctuated sharply during 2010-2020. The urban-rural gradient showed that with the increase of distance, CES fluctuations increase, but decreases at about 20-40km, 60-80km and 120-140km away from the city center, which may be sub-urban regions. The overall CES change range gradually decreases with increasing distance from urban centers. This study helps to understand the temporal and spatial distribution of ecological environment and urban-rural gradient in typical urban regions, and provides a reference for the collaborative planning of urban agglomeration.
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Affiliation(s)
- Xiaojun Wang
- Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Guangxu Liu
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, Jiangxi, China
| | - Churan Zhang
- School of Geography Sciences, South China Normal University, Guangzhou, 510631, China
| | - Yiling Liao
- Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing, 100091, China
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Tang H, Hou K, Wu S, Liu J, Ma L, Li X. Interpretation of the coupling mechanism of ecological security and urbanization based on a Computation-Verification-Coupling framework: Quantitative analysis of sustainable development. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 263:115294. [PMID: 37499388 DOI: 10.1016/j.ecoenv.2023.115294] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 07/16/2023] [Accepted: 07/21/2023] [Indexed: 07/29/2023]
Abstract
In recent decades, China's rapid urbanization has produced numerous economic benefits while simultaneously creating substantial risks to ecological security. China's 14th Five-Year Plan and the United Nations Sustainable Development Goals (SDGs) have recently explicitly called for the coordinated development of ecological security and urbanization. Given this context, it is important to explore the mechanism by which ecological security and urbanization are coupled and coordinated to promote sustainable development. In this study, an index of the relationship between ecological security and urbanization was established via high-resolution data, and a "Computation-Verification-Coupling" (CVC) framework was constructed. The accuracy of the ecological security index was verified using a linear regression model, and the coordination level between ecological security and urbanization was analyzed via a coupled coordination model (CCM). The results revealed a steady increase in the ecological security index from 2010 to 2020; the proportion of the area above the medium level increased from 63.1 % to 74.1 %. The urbanization index in core counties exhibited rapid growth, with level V urbanized areas expanding from 5.5 % to 9.9 %. The ecological security verification model produced a coefficient of determination (R²) of 0.75685, indicating a satisfactory degree of predictive capability. From 2010-2020, the coupled coordination improved, with the high coordination area accounting for 48.8 % and the extreme discoordination area decreasing from 1.8 % to 1.0 %. Coordinated development exhibited a stable progression, characterized by a cyclical evolution from initial coupling to antagonistic coupling and finally to coordinated development. This framework can be used not only to investigate the relationship between ecological security and urbanization but also to provide a quantifiable measure of progress toward achieving the SDGs.
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Affiliation(s)
- Haojie Tang
- School of Environmental and Chemical Engineering, Xi'an Polytechnic University, Xi'an 710048, China
| | - Kang Hou
- School of Environmental and Chemical Engineering, Xi'an Polytechnic University, Xi'an 710048, China.
| | - Siqi Wu
- School of Environmental and Chemical Engineering, Xi'an Polytechnic University, Xi'an 710048, China
| | - Jiawei Liu
- School of Environmental and Chemical Engineering, Xi'an Polytechnic University, Xi'an 710048, China
| | - Lixia Ma
- School of Environmental and Chemical Engineering, Xi'an Polytechnic University, Xi'an 710048, China
| | - Xuxiang Li
- School of Human Settlements and Civil Engineering, Xi'an Jiao Tong University, Xi'an 710049, China
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Zhang J, Chen H, Ma Y, Liu D, Liang X, Chen W. Identification of priority areas for ecological restoration based on ecological security and landscape elements. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:35307-35325. [PMID: 36527548 DOI: 10.1007/s11356-022-24711-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
Accurate identification of priority areas for ecological restoration is an important prerequisite for ecological protection and restoration, but it is a current challenge in landscape planning. Northern Shaanxi, which is located in the middle of the Loess Plateau in China, was selected as a study area in this paper. A three-dimensional framework including natural potential, human disturbance, and landscape pattern factors was used to construct an ecological security evaluation index system, and spatial principal component analysis (SPCA) was used to quantitatively evaluate the ecological security levels of the study area. The ecological security assessment result was used as a resistance surface, and landscape elements were identified by morphological spatial pattern analysis (MSPA), minimum cumulative resistance (MCR) model and the gravity model. On this basis, priority areas for ecological restoration were identified by considering ecosystem security and the matching degree of landscape elements. The resulting area with low and moderately low security levels was 27,574.87 km2 in size, accounting for 34.48% of the total study area, and the ecological security situation was not ideal. We identified seventeen ecological sources with an area of 5789.36 km2, and the important ecological sources were mainly distributed in the south of the study area. We identified one hundred and thirty-six potential ecological corridors with a total length of 7431.12 km, including 16 important ecological corridors with a length of 1279.43 km. We also identified 83 ecological nodes, including 17 important ecological nodes. We found that the high matching degree of landscape elements included four watersheds with an area of 7571.17 km2, mainly distributed in the southern part of the study area. Fifty-one basins with a low matching degree of landscape elements were identified, covering an area of 50,399.44 km2 and mainly distributed in the west and north of the study area. We identified three levels of areas to be restored, of which the level I ecological restoration priority area was the smallest, at 7047.61 km2. The areas of the level II ecological restoration priority area and the level III ecological restoration priority area were 20,379.35 km2 and 27,866.35 km2, respectively. The two areas were large and mainly distributed in the west and north of the study area. We discussed ecological restoration strategies for different levels of ecological restoration priority areas and provided new methods for identifying priority ecological restoration areas in the future.
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Affiliation(s)
- Jie Zhang
- College of Urban and Environmental Sciences, Northwest University, Xuefu Ave. 1, Xi'an, 710127, China
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi'an, 710127, China
| | - Hai Chen
- College of Urban and Environmental Sciences, Northwest University, Xuefu Ave. 1, Xi'an, 710127, China.
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi'an, 710127, China.
| | - Yuhe Ma
- College of Urban and Environmental Sciences, Northwest University, Xuefu Ave. 1, Xi'an, 710127, China
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi'an, 710127, China
| | - Di Liu
- College of Tourism, Henan Normal University, Xinxiang, 453007, China
| | - Xiaoying Liang
- College of Urban and Environmental Sciences, Northwest University, Xuefu Ave. 1, Xi'an, 710127, China
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi'an, 710127, China
| | - Wenting Chen
- College of Urban and Environmental Sciences, Northwest University, Xuefu Ave. 1, Xi'an, 710127, China
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi'an, 710127, China
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Huang L, Zhang Y, Hong Z, Xu X. Influencing factors on ecological efficiency: Based on 11 cities in Zhejiang Province, China. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2023; 19:139-151. [PMID: 35338683 DOI: 10.1002/ieam.4610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 03/09/2022] [Accepted: 03/24/2022] [Indexed: 06/14/2023]
Abstract
Ecological efficiency (eco-efficiency) is the effectiveness of ecological resources in meeting human needs and is a good representation of the quality of a region's development. The traditional concept of improving eco-efficiency refers to maximizing economic benefits by minimizing resource costs and environmental loads. This article argues that the goal of eco-efficiency evaluation is not only to maximize economic benefits but also to achieve high-quality and coordinated development in many aspects so that more people can enjoy the fruits of development. Therefore, in the evaluation system of eco-efficiency, the input indexes take into account the consumption of human, energy resources, and the environmental load caused by them in a region. The output indexes take into account the four dimensions of "economy, innovation, social harmony, and openness." This study first establishes the nonexpected output superefficiency slacks-based measure model under the assumption of variable returns to scale to measure eco-efficiency in 11 cities of Zhejiang Province, China. Second, the spatial and temporal trends of eco-efficiency are studied with the help of the Malmquist index model. Moreover, regression analysis was conducted using the panel Tobit method to discuss the influencing factors of eco-efficiency. Several key results were obtained in this study: (1) The overall eco-efficiency in Zhejiang Province is rising steadily, but there are serious regional imbalances. (2) The improvement of eco-efficiency mainly relied on the scale efficiency from 2008 to 2013, but on pure technical efficiency from 2013 to 2018. (3) The share of tertiary industry, the number of scientific researchers, and the foreign trade dependence positively affect the improvement of eco-efficiency, but highway transportation mileage has a negative impact on the improvement of eco-efficiency. Integr Environ Assess Manag 2023;19:139-151. © 2022 SETAC.
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Affiliation(s)
- Lizhen Huang
- School of Mathematics and Physics, Wenzhou University, Wenzhou, Zhejiang, China
- School of Business, Institute of Public Health & Emergency Management, Taizhou University, Taizhou, Zhejiang, China
| | - Yixiang Zhang
- The University of Waikato Joint Institute at Zhejiang University of City College, Zhejiang University City College, Hangzhou, Zhejiang, China
| | - Zhenjie Hong
- School of Computers and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang, China
| | - Xu Xu
- School of Mathematics and Physics, Wenzhou University, Wenzhou, Zhejiang, China
- School of Business, Wenzhou University, Wenzhou, Zhejiang, China
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Su J, Shen T, Jin S. Ecological efficiency evaluation and driving factor analysis of the coupling coordination of the logistics industry and manufacturing industry. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:62458-62474. [PMID: 35397729 DOI: 10.1007/s11356-022-20061-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 03/29/2022] [Indexed: 06/14/2023]
Abstract
The coupling coordination of the logistics industry and manufacturing industry is conducive to the sustainable development of logistics and manufacturing and the stability of sustainable supply chain. The logistics and manufacturing industries are not only the basic industries that support social development, but also the industries with high carbon emissions. This paper constructs the measurement system of coupling coordinating ecological efficiency of two industries based on carbon emission constraints and finds out the driving factors affecting ecological efficiency, which is of great significance to the low-carbon coordinated development of the two industries in the future. Firstly, this paper classifies the carbon emissions from the logistics industry and manufacturing industry as undesirable outputs and evaluates the ecological efficiency of the logistics industry (LEE) and manufacturing industry (MEE) in the three urban agglomerations from 2006 to 2019 by using the unexpected slacks-based measure (SBM) model. Secondly, the coupling coordination method is used to analyze the coupling coordination scheduling of industrial ecological efficiency (MLCC). Finally, the spatial econometric model is used to analyze the driving factors of the MLCC. The results show that during the study period, the coupling coordination of the three urban agglomerations continued to grow, the Pearl River Delta coupling coordination is the highest, the Yangtze River Delta coupling coordination grew the fastest, and the Beijing-Tianjin-Hebei coupling coordination grew slightly slower. The development during the 13th Five-Year Plan period is obviously faster than that during the 11th and 12th Five-Year Plan. The empirical analysis results of spatial econometrics show that the driving factors have an impact on the coupling coordination degree of the three urban agglomerations, but the significance of each factor is different. The driving factors have significant spatial heterogeneity. The three urban agglomerations should formulate low-carbon industry development policies in line with local development according to the actual situation of each region and local conditions.
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Affiliation(s)
- Juan Su
- Key Laboratory of Transport Industry of Management, Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area, College of Transportation Engineering, Chang'an University, Xi'an, 710064, China
| | - Tong Shen
- College of Equipment and Support, Engineering University of PAP, Xi'an,, 710086, China
| | - Shuxin Jin
- School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, 510006, China.
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Land Use Dynamics and Optimization from 2000 to 2020 in East Guangdong Province, China. SUSTAINABILITY 2021. [DOI: 10.3390/su13063473] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Anthropogenic land-use change is one of the main drivers of global environmental change. China has been on a fast track of land-use change since the Reform and Opening-up policy in 1978. In view of the situation, this study aims to optimize land use and provide a way to effectively coordinate the development and ecological protection in China. We took East Guangdong (EGD), an underdeveloped but populous region, as a case study. We used land-use changes indexes to demonstrate the land-use dynamics in EGD from 2000 to 2020, then identified the hot spots for fast-growing areas of built-up land and simulated land use in 2030 using the future land-use simulation (FLUS) model. The results indicated that the cropland and the built-up land changed in a large proportion during the study period. Then we established the ecological security pattern (ESP) according to the minimal cumulative resistance model (MCRM) based on the natural and socioeconomic factors. Corridors, buffer zones, and the key nodes were extracted by the MCRM to maintain landscape connectivity and key ecological processes of the study area. Moreover, the study showed the way to identify the conflict zones between future built-up land expansion with the corridors and buffer zones, which will be critical areas of consideration for future land-use management. Finally, some relevant policy recommendations are proposed based on the research result.
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