Search

The research explored the temp-spatial evolution characteristics for the spatial mismatch and vulnerability among the tourism-economy-ecosystem along the Yangtze River Economic Belt by using research methods including the spatial mismatch and vulnerability based on the panel data from 2004 to 2018. The results are as follows. (1) The overall mismatch along the Yangtze River Economic Belt presented a polarized development trend within which Shanghai, Jiangsu, and Zhejiang showed a typical positive mismatch and other provinces showed a negative mismatch; the overall spatial mismatch index tended to be more severe, the phenomenon of antagonism occurred more frequent and the situation of mismatch became more critical. (2) The overall vulnerability index along the Yangtze River Economic Belt presented a fluctuating trend and the healthy, risky, and severe development trends coexisted within the development process of each province’s vulnerability index. (3) The nine provinces and two cities could be decided into 3 typical categories of planned development regions by the comprehensive spatial mismatch and vulnerability index: Shanghai, Jiangsu, Zhejiang, and Hubei belonging to developing regions; Hunan, Chongqing, and Sichuan belonging to development and protection regions; Anhui, Jiangxi, Guizhou, and Yunnan belonging to protective regions. In the end, the paper puts forward specific suggestions on how to eliminate the spatial mismatch and vulnerability situation in the Yangtze River Economic Belt from both macro and micro perspectives, so as to provide theoretical reference for the high-quality sustainable development of the Yangtze River Economic Belt and other major river basins. The research explored the temp-spatial evolution characteristics for the spatial mismatch and vulnerability among the tourism-economy-ecosystem along the Yangtze River Economic Belt by using research methods including the spatial mismatch and vulnerability based on the panel data from 2004 to 2018. The results are as follows. (1) The overall mismatch along the Yangtze River Economic Belt presented a polarized development trend within which Shanghai, Jiangsu, and Zhejiang showed a typical positive mismatch and other provinces showed a negative mismatch; the overall spatial mismatch index tended to be more severe, the phenomenon of antagonism occurred more frequent and the situation of mismatch became more critical. (2) The overall vulnerability index along the Yangtze River Economic Belt presented a fluctuating trend and the healthy, risky, and severe development trends coexisted within the development process of each province’s vulnerability index. (3) The nine provinces and two cities could be decided into 3 typical categories of planned development regions by the comprehensive spatial mismatch and vulnerability index: Shanghai, Jiangsu, Zhejiang, and Hubei belonging to developing regions; Hunan, Chongqing, and Sichuan belonging to development and protection regions; Anhui, Jiangxi, Guizhou, and Yunnan belonging to protective regions. In the end, the paper puts forward specific suggestions on how to eliminate the spatial mismatch and vulnerability situation in the Yangtze River Economic Belt from both macro and micro perspectives, so as to provide theoretical reference for the high-quality sustainable development of the Yangtze River Economic Belt and other major river basins. [ABSTRACT FROM AUTHOR]

With rural decline becoming a global issue, the implementation of rural revitalization strategy has been turning into general starting points for many countries, especially in contemporary China. In this paper, we proposed a systematic analysis framework and a new evaluation index system for the implementation effectiveness of rural revitalization at the county scale. In addition, empirical research was conducted based on Jiangsu Province. The results indicated that the average value of the comprehensive index of implementation effects of rural revitalization in Jiangsu was 1.8198, and nearly 60% counties in the province were below this average. Also, the obvious disequilibrium and spatial differentiation laws were observed which presenting a stepwise advance from south to north, with the inland superior to the coastal. The five‐dimensional coordination status of rural revitalization in Jiangsu was relatively high, with the majority of counties reached at barely balanced state. A total of 21 counties were identified as problematic regions in Jiangsu through comprehensive overlay analysis. They were mainly located in northern Jiangsu, and could be divided into seven specific types. The proposed evaluation framework and indicator system might make up for the lack of effective reference systems and scientific quantitative indicators in the current county‐scale rural revitalization strategy practices. Moreover, the idea of identifying problem areas and the classification mode of rural revitalization goal levels proposed in this paper are also of great reference for other regions. [ABSTRACT FROM AUTHOR]

The achievement of the carbon peaking and carbon neutrality targets requires the adjustment of the energy structure, in which the dual-carbon progress of the power industry will directly affect the realization process of the goal. In such terms, an accurate demand forecast is imperative for the government and enterprises' decision makers to develop an optimal strategy for electric energy planning work in advance. According to the data of the whole social electricity consumption in Jiangsu Province of China from 2015 to 2019, this paper uses the improved particle swarm optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and establishes a metabolic FGM (1, 1) model to predict the whole social electricity consumption in Jiangsu Province of China from 2020 to 2023. The results show that in the next few years the whole social electricity consumption in Jiangsu Province will show a growth trend, but the growth rate will slow down generally. It can be seen that the prediction accuracy of the metabolic FGM (1, 1) model is higher than that of the GM (1, 1) and FGM (1, 1) models. In addition, the paper analyzes the reasons for the changes in the whole society electricity consumption in Jiangsu Province of China and provides support for government decision making. [ABSTRACT FROM AUTHOR]

With the acceleration of China’s regional integrated development, some functions of large cities have been decentralized to the peripheral areas, resulting in the increasing phenomenon of commuting to and from school or work across administrative regions. As a spatial unit of various factors flowing across regions, the metropolitan area has gradually become a significant carrier in the background of high-quality urbanization development. However, due to existing policy limitation, it has been hard to avoid administrative barriers in metropolitan area development. To fill the gap in the traditional policy system, regional spatial governance is being widely used in practice at various levels. Therefore, from the perspective of spatial governance, this paper explores a new approach to the governance of metropolitan areas with Chinese characteristics based on the analysis of the connotation evolution of metropolitan areas and the international experience of metropolitan development and governance. By taking several metropolitan areas in Jiangsu Province as examples, this paper explains that the key to metropolitan governance is to treat a metropolitan area as “policy area” and to construct a spatial governance system suitable to regional integrated development, through the combination of spatial planning and public policy, so as to propel urban development towards regional coordination. [ABSTRACT FROM AUTHOR]

In recent years, China's air quality problem is very serious. Among them, carbon dioxide emissions have been high, which has caused a series of ecological and environmental problems. In order to deeply study the relevant problems, this paper selects the information priority damping gray model to study and predict the carbon emissions of thirty-one provinces and municipalities in China. The model can give priority to new information and adjust the prediction trend, the accuracy of the model is verified by several cases. Through the data collection and data analysis of relevant provinces and cities, it is concluded that a total of twenty-one provinces and municipalities can reach the carbon peak in 2030, of which the carbon dioxide emission of Beijing is expected to drop to 51.3774 million tons by 2030. Ten provinces will not be able to reach the carbon peak by 2030. Among them, by 2030 the carbon dioxide emission of Jiangsu Province is expected to increase to 84.4668 million tons, but the growth rate is declining. The research results can be used as a reference for relevant departments. [ABSTRACT FROM AUTHOR]

[Display omitted] • The evolution of construction land expansion and space conflicts were visualized. • An index for analyzing the intensity of territorial space conflicts is constructed. • The intensity distribution of space conflicts is consistent with its dynamic changes. • Territorial space conflict changes are related to construction land expansion. • The collaboration degree between conflicts and socioeconomic factors is discussed. In rapidly urbanizing areas, intense human development activities and fierce competition for spatial resources have led to apparent territorial space conflicts. This paper selects Jiangsu Province as the study area to explore the spatiotemporal evolution characteristics and response relationship between the expansion of county-level construction land and territorial space conflicts from 1985 to 2020 to provide a reference for regional territorial space optimization. The results show that the construction land expansion intensity (CEI) at the county level showed a spatial characteristic of greater power in the southeast than in the northwest. The spatial expansion mode (SEI) was mainly characterized by spread type, with construction land experiencing marginal expansion, the emergence of new independent expansion points, and then the expansion process of agglomeration distribution. From 1985 to 2020, there was a significant increase in territorial space conflicts and an increase in spatial aggregation at the county level. The regions with high space conflicts intensity index (SCII) values and high increase in space conflicts intensity changes (SCII C) were mainly located in Xuzhou, Nanjing, and at the junction of Changzhou, Wuxi, Suzhou, and Zhenjiang. There was a positive correlation between CEI and SCII C , and the correlation of positive correlation units increased from south to north. There was a positive correlation between SEI and SCII C , and the units with a strong positive correlation were mainly located in Xuzhou, Nantong, Changzhou, and Wuxi. The changes in population density and GDP also affect SCII C. This paper strengthens the understanding of the spatiotemporal evolution characteristics and related relationships of construction land expansion and territorial space conflicts at the county level over a long time, which can provide a decision-making basis and reference for the regulation of county construction land expansion, territorial space optimization in Jiangsu Province. [ABSTRACT FROM AUTHOR]

The current research concentrated upon customers' consuming behaviors towards hydrogen vehicle in Jiangsu province, China. This paper discussed the associations between factors related to competitions in industries and customers' consuming behaviors. Different from previous literature, the present study explored whether industrial agglomeration would affect customers willingness to purchase hydrogen vehicles. Results from empirical analysis showed that industrial structure height in a city was positively associated with customers' acceptance towards hydrogen vehicles. This indicated that in addition to economic and environmental factors, the agglomeration of industrial activities from industry competition would increase customers purchase intention for hydrogen vehicle. • Industry agglomeration's impacts on hydrogen vehicle's consumption are discussed. • Housing burden is related to the degree of reluctance to buy hydrogen vehicles. • Willingness to energy-saving products and hydrogen vehicles is correlated. • The economic mechanism behind Chinese hydrogen vehicle industry is discussed. [ABSTRACT FROM AUTHOR]

Industrial structure is the result of the allocation of economic resources of a country or a region, and to a large extent determines the efficiency of the use of economic resources. The process of national or regional economic growth is the dynamic evolution process of industrial structure from uncoordinated to coordinated, from lower-level coordination to higher-level coordination, that is, the process of continuous optimization of industrial structure. The concepts of industrial structure deviation and industrial structure coordination degree are proposed in this paper. The weighted average values of the industrial structures of the developed countries such as the USA, UK, France, Germany and Japan in the year when their per capita GDP reaches US $10000, US $20000 and US $30000 was calculated respectively. Then, the standard industrial structure was calculated with the weighted average values of the industrial structures of the five developed countries as reference frame. And the definition of industrial structure deviation and industrial structure coordination degree is put forward accordingly. At last, the coordination degree of industrial structure in China. Jiangsu Province, Southern Jiangsu, Central Jiangsu and Northern Jiangsu is calculated according to the data oj actual industrial structure in 2019. And the industrial structure optimization and adjustment plan of China and Jiangsu Province is worked out according to the set target structure. [ABSTRACT FROM AUTHOR]

The excessive expansion of road transportation often has an impact on the quality of regional habitats. This paper attempts to assess the impact of road transportation on regional habitat quality in economically developed areas. A kernel density analysis was used to characterise the road transportation development in Jiangsu Province from 2000 to 2015. An Integrated Valuation of Ecosystem Services and Trade‐offs (InVEST) habitat quality model was applied to assess changes in habitat quality. Furthermore, a fixed‐effect regression model was utilised to examine the impact of road transportation development in Jiangsu Province on habitat quality. The analysis indicates that the average kernel density of road transportation in the province increased from 0.109 to 0.551 km/km2 while the habitat quality decreased from 0.51 to 0.48. The development of road transportation in Jiangsu Province has had a serious negative impact on the quality of the habitat. For every 1‐ha increase in land area for road use, the habitat quality index will decrease by 0.066; for every 1 km/km2 increase in road transportation kernel density, the habitat quality index will decline by 0.121. [ABSTRACT FROM AUTHOR]

Industry has always been an important driving force to promote social and economic development, and the development of industry is inseparable from energy consumption. In the process of modern production, more and more modern advanced equipment is put into use, and the main power source of these equipment is electricity. However, the production of electricity is limited by conditions. Therefore, the main purpose of this paper is to simulate and forecast the industrial power consumption of Jiangsu Province through the nonlinear transformation of time variables, so that the industrial enterprises in Jiangsu can reasonably arrange the next power demand and ensure the smooth progress of industrial activities. The final research results show that the time series regression prediction model proposed in this paper can effectively simulate and predict the results of industrial power consumption, with an accuracy of 1.02 %. • Consider fewer factors, which saves time and cost and can obtain higher prediction accuracy. • Only consider the impact of the current time, without considering the impact of the lag time. • Taking Jiangsu, an industrial province as an example, can better guide other provinces. [ABSTRACT FROM AUTHOR]

In this paper, GM(1,N r) model is established to improve the traditional GM(1,N) model from three aspects: (1) transforming the original sequence to satisfy the modeling conditions with particle swarm optimization algorithm; (2) introducing grey incidence analysis to obtain the grey incidence ranking and carrying out stepwise test for significant variables to determine the number of variables; and (3) predicting the related factor sequence through the improved GM(1,1) model. Empirical analysis shows that the proposed GM(1,N r) model has remarkable good prediction performance compared with the traditional grey forecasting model. It is also demonstrated that the extraction of influencing factors can significantly improve the prediction effectiveness, especially when pursuing the best fitting effect on small sample data. The findings indicate that the electricity consumptions of Jiangsu Province in the next several years will be at a high level and keep rising, with a predicted value of 9712.48 billion kilowatt-hours in 2030. The findings can help the government and energy related institutions to develop management policies on energy demand, and the proposed model can also be extended for the application in other regions. • Propose a new model to improve the traditional GM(1,N) model. • Adopt a new method to find the best value to satisfy the modeling conditions. • Use the grey incidence analysis with stepwise examination to identify factors. • Combine the improved GM(1,1) model to improve the performance of GM(1,N). • Apply this new model to analysis electricity consumption in Jiangsu Province. [ABSTRACT FROM AUTHOR]

China is currently undergoing the most influential urbanization phase in its history, and this process will probably last for a few decades to come. Along with the accelerated urbanization, the quality of development has been elevated to an equal position with the quantity. Being one of the most developed and best urbanized provinces in China, Jiangsu has achieved an urbanization rate of 57%. Dealing with large construction scales, Jiangsu is presently striving to improve the quality of its urban space, and to elevate human settlements to a higher level. By contextualizing Jiangsu's urbanization within a certain development stage and a specific historical era, the paper proposes the overall idea and action strategies for improving the quality of urban space, on the basis of the analysis on contemporary cultural pursuits. It aims at changing the current situation of "one outlook for thousands of cities," improving the quality of urban space and the competitiveness of urban culture, and eventually creating better human settlements and a harmonious society. [ABSTRACT FROM AUTHOR]

China has become the world's largest carbon emitter, and its commitment to peak carbon emissions by 2030 is important for global development. The construction industry is one of China's biggest carbon emitters, and its peak has a direct impact on China's carbon commitment. Due to the regional heterogeneity of different provinces, the carbon emission of construction industry (CECI) at provincial level is of unique significance. To accurately predict the peak of provincial CECI, a prediction model was established by system dynamics, including direct CECI, indirect CECI and operational CECI. Taking Jiangsu province as an example, the single and multiple scenario settings with increasing R&D investment, promoting energy-saving buildings and implementing carbon trading from 2016 to 2030 was carried out, indicating that: 1) Without any carbon emission reduction measures, the CECI would maintain an annual growth rate of 5.58% to reach 530.61 million tons by 2030, and the indirect and operational CECI account for the majority of total with an average annual growth rate of 8.02% and 2.79% respectively. 2) All three measures had good carbon reduction effects, which would reduce the total CECI by 26.46% 21.68% and 10.68% respectively by 2030, but only when implemented simultaneously can CECI peak before 2030, 308.77 million tons at 2029. In the end, three policy implications was put forward. The framework presented in this paper provided a basis for the prediction of peak CECI in a province or state, which can help policy makers plan a more reasonable low-carbon development roadmap. [Display omitted] • The total carbon emissions of provincial construction industry are predicted. • Direct, indirect and operational carbon emissions are predicted respectively. • The total carbon emissions will not peak before 2030 under the basic scenario. • Carbon emissions will peak at 308.77 million tons in 2029 under multiple scenario. • Encouraging R&D investment, energy-saving buildings and carbon trading are crucial. [ABSTRACT FROM AUTHOR]