Analysis of the spatial-temporal differences and fairness of the regional energy ecological footprint of the Silk Road Economic Belt (China Section)

Yang, Yi; Fan, Mingdong

doi:10.1016/j.jclepro.2019.01.170

Cited by 52 publications

(15 citation statements)

References 40 publications

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“…Thanks to SCO and its active role positioning, China is fully realizing its export potential in the Central Asia. To maintain a leading role in Russia's import China is actively developing the "Economic belt of the great silk road" [7,8].…”

Section: Resultandanalysismentioning

confidence: 99%

Analysis of Russian Trade Relations with Shanghai Cooperation Organization

2019

2019 2nd International Conference on Contemporary Education and Economic Development (CEED 2019)

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The subject of the study are the trade relations of Russia with the countries of the Shanghai Cooperation Organization (SCO) for goods and product groups of the Foreign Economic Activity Commodity Nomenclature (FEACN)of the Federal Customs Service of the Russian Federation. The aim of the paper is to identify clusters of countries, goods and commodity groups for imports to Russia and Russian exports. The article reveals the causes of SCO formation and recognizes its role in development of international trade cooperation. The study revealed match of clusters of SCO countries in terms of imports to Russia and Russian exports-India, China, Kazakhstan and Kyrgyzstan. Among the goods and commodity groups of imports to Russia there prevail: nuclear reactors, boilers, equipment and mechanical devices; organic chemical compounds; ores, slag and ash. Wide FEACN of Russian exports was revealed-mineral fuel, oil and products of their distillation; bituminous substances; mineral waxes; wood and products thereof; ferrous metals and others. Unlike imports the hierarchy of Russian exports in terms of goods and commodity groups is not stable.

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Section: Resultandanalysismentioning

confidence: 99%

Analysis of Russian Trade Relations with Shanghai Cooperation Organization

2019

2019 2nd International Conference on Contemporary Education and Economic Development (CEED 2019)

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“…= SW 2016 SP 2016 (19) In Equation 19, SW 2012 and SW 2016 represent the added value of water conservancy in 2012 and 2016. SP 2012 and SP 2016 represent the added value of primary production in 2012 and 2016.…”

Section: Sw 2012 Sp 2012mentioning

confidence: 99%

“…Multi-region in economic sense: Silk Road Economic Belt (including 9 provinces in China section) [19].…”

Section: Index Decomposition Analysis (Ida)mentioning

confidence: 99%

Regional Disparities and Transformation of Energy Consumption in China Based on a Hybrid Input-Output Analysis

Xia

Zhang

et al. 2020

Energies

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Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings.

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“…In addition, the index of footprint depth can only represent the extent to which natural resource consumption occupies capital stock in the state of ecological deficit (EF > BC), but it cannot measure the extent to which resource consumption occupies capital flow and its balance in the state of ecological surplus (EF < BC). Therefore, Fang and his colleagues [23-25] improved the Niccolucci et al's 3D EF model by separately measuring the ecological deficit data of each biological productive land type, and further proposed the occupancy rate of natural capital flow (w f low ) and the ratio of natural capital stocks to capital flows (w stock f low ) to respectively represent the actual utilization of natural capital by human beings when the capital flow is not completely occupied (ecological surplus, EF < BC) and completely occupied (ecological deficit, EF > BC).Ningxia Province is a typical energy-rich and ecologically fragile region in China [26]. At present, more than 50 kinds of mineral resources have been discovered, including coal, gypsum, oil, natural gas, and clay quartz.…”

mentioning

confidence: 99%

“…Ningxia Province is a typical energy-rich and ecologically fragile region in China [26]. At present, more than 50 kinds of mineral resources have been discovered, including coal, gypsum, oil, natural gas, and clay quartz.…”

mentioning

confidence: 99%

Natural Capital Evolution and Driving Forces in Energy-Rich and Ecologically Fragile Regions: A Case Study of Ningxia Province, China

et al. 2020

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Ningxia Province is rich in energy but fragile in ecology. How to coordinate sustainable utilization of natural capital and the fragile ecological environment is a significant guarantee for social-economic development. This study uses the improved three-dimensional ecological footprint to characterize the utilization status of natural capital flows and stocks in Ningxia Province from 2004 to 2017. Additionally, the driving factors behind changes in the natural capital stock are revealed by the partial least squares method (PLS). The results are as follows: (1) From 2004 to 2017, ecological footprint increased rapidly in Ningxia Province at an annual rate of 4.52%, resulting in a increase of the ecological deficit from 1.64 to 3.85 gha/cap at an annual rate of 6.8%, among which, Yinchuan city and Shizuishan city had the largest ecological deficit, while Guyuan city basically maintained ecological surplus. The fossil energy land and cropland were the main components of ecological footprint. (2) The consumption of capital stock in Ningxia Province continued to grow at an annual rate of 3.12%, from a value of 2.28 times overusing the existing area in 2004, increasing to 3.41 times in 2017. While the EF size increased slightly with an annual rate of 1.95%. The capital stock consumption was concentrated in Yinchuan and Shizuishan, and the capital flow consumption was concentrated in Wuzhong, Guyuan, and Zhongwei. (3) The capital flows of forest land and built-up land basically meet consumption demand, while the capital stock occupation of grassland, water and fossil energy land was serious. By 2017, the capital flow of cropland could basically satisfy people’s consumption demand. (4) The urbanization rate, GDP, the secondary industry output value and per capita consumption expenditure of urban residents were the main influence factors on the natural capital stock consumption. These findings not only are of real significance in promoting the coordinated development between economy and natural capital utilization in Ningxia Province but also have policy implications in improving the utilization efficiency of natural capital in energy-rich ecologically fragile regions.

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Analysis of the spatial-temporal differences and fairness of the regional energy ecological footprint of the Silk Road Economic Belt (China Section)

Cited by 52 publications

References 40 publications

Analysis of Russian Trade Relations with Shanghai Cooperation Organization

Analysis of Russian Trade Relations with Shanghai Cooperation Organization

Regional Disparities and Transformation of Energy Consumption in China Based on a Hybrid Input-Output Analysis

Natural Capital Evolution and Driving Forces in Energy-Rich and Ecologically Fragile Regions: A Case Study of Ningxia Province, China

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