A study of regional sustainable development based on GIS/RS and SD model — Case of Hadaqi industrial corridor

Wan, Luhe; Zhang, Yuwei; Qi, Shaoqun; Li, Haiyan; Chen, Xiaohong; Zang, Shuying

doi:10.1016/j.jclepro.2016.09.086

Cited by 25 publications

(16 citation statements)

References 35 publications

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“…This implies that the great benefits of industrial production in Jiangxi Province are accompanied by serious environmental pollution, and improving the ecological environment can effectively raise the PIGD. This is consistent with the conclusion of Wan et al (2017) [42], who stated that environmental problems caused by industrial development deserve more attention than issues of economic development. Therefore, the most important issue of industrial development in Jiangxi province is to achieve environmentally friendly industrial production through various effective ways, e.g., develop new energy saving and environmental protection technologies.…”

Section: The Pigd and Its Decomposition Indicatorssupporting

confidence: 91%

Measuring the Performance of Industrial Green Development Using a Non-Radial Directional Distance Function Approach: A Case Study of Jiangxi Province in China

et al. 2017

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Abstract:The industrial sector is a major contributor to resource consumption and environmental pollution in China. The energy-intensive industrial development and energy structure are dominated by coal, which has produced an enormous amount of industrial pollutants in China, and put great pressure on the ecological environment. Hence, improving the performance of industrial green development (PIGD) has become an urgent task of utmost importance. This study applies a global non-radial directional distance function to estimate the PIGD for Jiangxi Province during [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015], and provides targeted policy suggestions. The empirical results show a rising trend in the PIGD in Jiangxi Province. At the city level, Nanchang and Fuzhou performed considerably better than other cities in regards to their PIGD. However, the poor environmental performance caused by the excessive discharge of industrial pollutants has also hindered its PIGD. Most cities in Jiangxi Province failed to efficiently use resources, especially energy and labor, in industrial production. The results of the influencing factor analysis show that the performance of industrial green development in Jiangxi could be improved through increasing per capita GDP, decreasing the share of coal consumption in the total industrial energy consumption, and decreasing the share of industrial GDP in the total GDP. Furthermore, a more efficient use of environmental management investment funds and timely transfer of the surplus industrial labor are needed.

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Section: The Pigd and Its Decomposition Indicatorssupporting

confidence: 91%

Measuring the Performance of Industrial Green Development Using a Non-Radial Directional Distance Function Approach: A Case Study of Jiangxi Province in China

et al. 2017

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“…The various equations in SD model are shown in Table 4. (1) Population influences the economics and environment of cities through aspects such as labor force, consumption of entertainment, and tourist recreation [46,47]. Population changes are also based on feedback principles and are influenced by economic development, environmental changes, and urban CES [48].…”

Section: Sd Modellingmentioning

confidence: 99%

“…Pollution of the air and water causes a reduction in spontaneous recreational activities, and therefore should be included in the system variables [50]. Economic investment in different CES can also have a crucial impact on CES [47,51].…”

Section: Sd Modellingmentioning

confidence: 99%

The Evolution Response of Ecosystem Cultural Services under Different Scenarios Based on System Dynamics

Zhao

Cuan

et al. 2020

Remote Sensing

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Cultural ecosystem services (CES) are a significant part of the ecosystem and are considered to be a core component of human welfare and ecosystem protection. CES have been historically difficult to quantitatively evaluate because of their subjectivity and intangibility. Additionally, their evolution over time has rarely been explored. Here, we quantitatively evaluated various CES and generated corresponding value index (VI) maps. We then further explored the evolution of CES characteristics over space and time. We selected Xi’an as the study area and applied the Social Values of Ecosystem Services (SolVES) model to evaluate CES and generate three specific VI maps. A system dynamics model based on socioeconomic and survey data of CES for each administrative division was established. Finally, we simulated four developmental scenarios in order to predict potential developmental changes of CES in 2030 under these different scenarios. This study provides a method for evaluating CES and explores the application of system dynamics to different fields. Additionally, our findings may provide guidance for the formulation of regional policies and support missions to improve civilizations within ecological systems, coordinate future economic growth with ecosystem services, and achieve sustainable development.

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“…However, during the reform and opening up, a large number of state-owned enterprises have closed down and large numbers of employees have become unemployed, resulting in a serious lag in development. Not only is its economic development gradually lagging behind the eastern coastal region, its level of sustainable development is also facing major challenges [83]. Regarding this, China has set up a plan to revitalize the old industrial base in the Northeast [84], but the imbalance in development still exists among the three provinces.…”

Section: The Northeast Regionmentioning

confidence: 99%

Evaluation of the Level of Sustainable Development of Provinces in China from 2012 to 2018: A Study Based on the Improved Entropy Coefficient-TOPSIS Method

Liao

Chen

et al. 2020

Sustainability

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Based on the definition and implication of sustainable development, this paper first constructed an evaluation indicator system for the sustainable development level of provinces in China, and performed a scientific evaluation on the sustainable development level based on official statistics from 2012 to 2018 by using the improved Entropy Coefficient-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. The evaluation results showed that the eastern region of China has the highest level of sustainable development, with its two municipalities directly under the central government, Beijing and Shanghai, achieving the full score of 1.0000 in all evaluations, both ranking first among all the provinces. There were significant differences in the level of sustainable development across provinces in the central region, which were comparatively weaker in terms of environmental sustainability and science and technology sustainability, with four provinces’ evaluation scores below 0.5000. The provinces of the western region had comparatively lower levels of sustainable development, with six of the provinces ranking among the bottom ten in the overall sustainability score. In the northeast region, Liaoning had the highest overall sustainable development level, ranking ninth in the country, with an evaluation score of 0.7726; however, there were large differences across the region, with the other two provinces ranking 19th and 21th, respectively, in the overall sustainability score. Based on the research findings, this paper has provided relevant policy recommendations for China to further improve the sustainable development level of various provinces in the future.

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A study of regional sustainable development based on GIS/RS and SD model — Case of Hadaqi industrial corridor

Cited by 25 publications

References 35 publications

Measuring the Performance of Industrial Green Development Using a Non-Radial Directional Distance Function Approach: A Case Study of Jiangxi Province in China

Measuring the Performance of Industrial Green Development Using a Non-Radial Directional Distance Function Approach: A Case Study of Jiangxi Province in China

The Evolution Response of Ecosystem Cultural Services under Different Scenarios Based on System Dynamics

Evaluation of the Level of Sustainable Development of Provinces in China from 2012 to 2018: A Study Based on the Improved Entropy Coefficient-TOPSIS Method

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