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As the product of natural process, land is an essential but nonrenewable resource for humankind. Urban land use efficiency directly reflects the coupling between urban systems and land use systems. It also serves as the key indicator for measuring land productivity and regional development quality. In this study, the land use efficiency of 65 county-level cities in the Yellow River Basin has been measured by applying the Data Envelope Analysis (DEA) and Spatial Autocorrelation Analysis methods. It makes up for the deficiency and defect of the existing research. The result indicates that in 2000~2018, the overall urban land use efficiency in 65 prefecture-level cities is unbalanced, with significant gaps between cities with high efficiency and low efficiency. In 2000~2018, the average urban land use efficiency in these 65 cities shows a tendency of declining. In 2000~2018, the spatial distribution of land use efficiency of these 65 cities indicates significant positive correlation, featured by the clustering of regions with high (low) efficiency. In terms of the spatial distribution of urban land use efficiency in the Yellow River Basin, it is marked by apparent spatial clustering. Specifically, from east to west, from coastal areas to inland regions, from downstream to upstream, the urban land use efficiency differs from high value areas to low value areas. On the whole, it is featured by high value in the east and low value in the west, while declining from downstream to upstream.
Hengji Li; Jiansheng Qu; Dai Wang; Peng Meng; Chenyu Lu; Jingjing Zeng. Spatial-Temporal Integrated Measurement of the Efficiency of Urban Land Use in Yellow River Basin. Sustainability 2021, 13, 8902 .
AMA StyleHengji Li, Jiansheng Qu, Dai Wang, Peng Meng, Chenyu Lu, Jingjing Zeng. Spatial-Temporal Integrated Measurement of the Efficiency of Urban Land Use in Yellow River Basin. Sustainability. 2021; 13 (16):8902.
Chicago/Turabian StyleHengji Li; Jiansheng Qu; Dai Wang; Peng Meng; Chenyu Lu; Jingjing Zeng. 2021. "Spatial-Temporal Integrated Measurement of the Efficiency of Urban Land Use in Yellow River Basin." Sustainability 13, no. 16: 8902.
Tourism efficiency is an effective index of measuring the development quality of the tourism industry. In this study, the tourism efficiency of 30 provinces in China during the period from 2006 to 2018 was measured with the SBM model and Malmquist index. On the basis of ESDA and GWR models, we explored the spatial pattern of China’s tourism efficiency and the spatial heterogeneity of the influencing factors in depth. The results revealed that China’s tourism efficiency has been constantly enhanced with an increasingly balanced pattern. Meanwhile, the utilization degrees of various input factors have constantly been improving. Both technological efficiency and technological progress jointly promote rapid growth of total-factor productivity. Accompanied with constant enhancement of the spatial agglomeration effect, the local spatial pattern also showed obvious differentiation. In general, low-efficiency regions were mainly concentrated in northern China, while high-efficiency regions were concentrated in southern China. The distinct spatial–temporal differentiation characteristics of tourist economic efficiency can be attributed to different influencing strengths of various factors in various regions and different action tendencies. The level of economic development, traffic conditions, the professional level of tourism, and openness degree can significantly promote tourism efficiency. Tourism resource endowment and environmental cost impose slight effects and differ in action direction, thereby inhibiting the tourism efficiency of many regions.
Zhiliang Liu; Chengpeng Lu; Jinhuang Mao; Dongqi Sun; Hengji Li; Chenyu Lu. Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China. Sustainability 2021, 13, 5825 .
AMA StyleZhiliang Liu, Chengpeng Lu, Jinhuang Mao, Dongqi Sun, Hengji Li, Chenyu Lu. Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China. Sustainability. 2021; 13 (11):5825.
Chicago/Turabian StyleZhiliang Liu; Chengpeng Lu; Jinhuang Mao; Dongqi Sun; Hengji Li; Chenyu Lu. 2021. "Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China." Sustainability 13, no. 11: 5825.
Driven by economic development, the dramatic increase in carbon emissions has led to global warming and a series of environmental problems. The question of how to ensure harmonized coordination between economic development, carbon emissions and environmental protection has become increasingly important. The conflicts between the use of energy and emission reductions in China have become more intense. It is an inevitable requirement for China’s sustainable development to promote a low-carbon circular economy and the simultaneous and coordinated development of carbon emissions, the economy and the environment. The present study took 30 provinces (municipalities and autonomous regions directly under the Central Government) as the research objects (Tibet, Hong Kong, Macau, and Taiwan are not included in the study due to the lack of relevant data), and applied quantitative analysis methods, such as three-stage data envelopment analysis (DEA) models, coupling coordination degree models and spatial analysis models, to construct a measurement index system. On the basis of the measurement of its carbon emission efficiency, the level of China’s coordination degree in regard to carbon emissions, economic development, and environmental protection at both spatial and temporal dimensions was analyzed comprehensively in order to reveal its temporal and spatial characteristics. The conclusions are as follows: (1) China’s overall carbon emission efficiency displayed a gradual upward trend, although the overall level was not that high. Therefore, there is still much scope for further improvement. (2) The level of China’s coordination degree in regard to carbon emissions, economic development, and environmental protection showed a steady yet rising trend. All provinces reached different levels of coordination development, and there was no province that displayed a disorderly declining trend. However, the number of provinces that reached or went beyond the intermediate level of coordination development was quite limited. (3) The level of China’s coordination degree in regard to carbon emissions, economic development, and environmental protection displayed obvious spatial aggregation patterns at the provincial level, showing an apparent spatial dependence and heterogeneity. Over time, the level of spatial aggregation patterns in regard to coordination degree tended to weaken. Overall, the values were high in the eastern region and low in the western region, decreasing from the eastern coastal zone towards the western inland zone, thus demonstrating a contrasting east-west spatial distribution pattern.
Chenyu Lu; Dai Wang; Hengji Li; Wei Cheng; Xianglong Tang; Wei Liu. Measurement of the Degree of Coordination in Regard to Carbon Emissions, Economic Development, and Environmental Protection in China. Applied Sciences 2021, 11, 1750 .
AMA StyleChenyu Lu, Dai Wang, Hengji Li, Wei Cheng, Xianglong Tang, Wei Liu. Measurement of the Degree of Coordination in Regard to Carbon Emissions, Economic Development, and Environmental Protection in China. Applied Sciences. 2021; 11 (4):1750.
Chicago/Turabian StyleChenyu Lu; Dai Wang; Hengji Li; Wei Cheng; Xianglong Tang; Wei Liu. 2021. "Measurement of the Degree of Coordination in Regard to Carbon Emissions, Economic Development, and Environmental Protection in China." Applied Sciences 11, no. 4: 1750.
The study of the carbon emission intensity of agricultural production is of great significance for the formulation of a rational agricultural carbon reduction policy. This paper examines the regional differences, spatial–temporal pattern and dynamic evolution of the carbon emission intensity of agriculture production from 1991 to 2018 through the Theil index and spatial data analysis. The results are shown as follows: The overall differences in carbon emission intensity of agriculture production presents a slightly enlarging trend, while the inter-regional differences in carbon emissions intensity is decreasing, but the intra-regional difference of carbon emissions intensity presented an expanding trend. The difference in carbon emission intensity between the eastern and central regions is not obvious, and the difference in carbon emission intensity in the western region shows a fluctuating and increasing trend. The overall differences caused by intra-regional differences; the average annual contribution of intra-regional differences is 67.84%, of which the average annual contribution of western region differences is 64.24%. The carbon emission intensity of agricultural production in China shows a downward trend, with provinces with high carbon emission intensity remaining stable, while provinces with low intensity are expanding. The Global Moran’s I index indicates that China’s carbon emission intensity of agricultural production shows a clear trend of spatial aggregation. The agglomeration trend of high agricultural carbon emission remains stable, and the overall pattern of agricultural carbon emission intensity shows a pattern of increasing differentiation from east to west.
Jiaxing Pang; Hengji Li; Chengpeng Lu; Chenyu Lu; Xingpeng Chen. Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China. International Journal of Environmental Research and Public Health 2020, 17, 7541 .
AMA StyleJiaxing Pang, Hengji Li, Chengpeng Lu, Chenyu Lu, Xingpeng Chen. Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China. International Journal of Environmental Research and Public Health. 2020; 17 (20):7541.
Chicago/Turabian StyleJiaxing Pang; Hengji Li; Chengpeng Lu; Chenyu Lu; Xingpeng Chen. 2020. "Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China." International Journal of Environmental Research and Public Health 17, no. 20: 7541.
Since the 1990s, the notion of a circular economy has been developing globally; countries all over the world have been considering the development of a circular economy as an important means of achieving sustainable development. As the development of an industrial circular economy can help promote the efficient recycling of resources, it is an important starting point for industrial transformation and upgrading, and represents a key factor that will lead to the development of a circular economy in China. China’s varying provinces (municipalities and autonomous regions) have successively implemented circular economy practices in the industrial field. The research object of the present study is 30 provinces, autonomous regions, and municipalities directly under the control of central government (Hong Kong, Macao, Taiwan, and Tibet were not included owing to lack of data). Through the integration of geographic information systems (GIS) technology and the spatial analysis model, data envelopment analysis (DEA) model, and Tobit regression model, a measure model and index system are constructed, in order to carry out a multi-angle comprehensive study integrating the efficiency evaluation, spatial analysis, and influencing factors analysis of China’s industrial circular economy. It is an important innovation, and an important contribution to the existing research system. The conclusions are as follows: (1) In general, the overall level of China’s industrial circular economy’s efficiency was not high, and there was still a lot of room for improvement. The integrated efficiency of the industrial circular economy in the eastern region was relatively high, followed by that in the western region, and the lowest level in the middle region. (2) The efficiency of China’s industrial circular economy displayed obvious spatial aggregation characteristics at the provincial level, including clear spatial dependence and spatial heterogeneity. High-value aggregation areas were mainly distributed in the eastern coastal areas, and low-value aggregation areas were concentrated and contiguously distributed in the middle and western inland areas. (3) The four elements of economic level, openness to the outside, government regulation, and industrialization aggregation each impose a significant positive impact on the efficiency of China’s industrial circular economy, which can promote its efficiency. The level of industrialization exerts a significant negative impact on the efficiency of the industrial circular economy, which hampers its improvement. The impact of technological innovation on the efficiency of the industrial circular economy is not statistically significant.
Chenyu Lu; Yang Zhang; Hengji Li; Zilong Zhang; Wei Cheng; Shulei Jin; Wei Liu. An Integrated Measurement of the Efficiency of China’s Industrial Circular Economy and Associated Influencing Factors. Mathematics 2020, 8, 1610 .
AMA StyleChenyu Lu, Yang Zhang, Hengji Li, Zilong Zhang, Wei Cheng, Shulei Jin, Wei Liu. An Integrated Measurement of the Efficiency of China’s Industrial Circular Economy and Associated Influencing Factors. Mathematics. 2020; 8 (9):1610.
Chicago/Turabian StyleChenyu Lu; Yang Zhang; Hengji Li; Zilong Zhang; Wei Cheng; Shulei Jin; Wei Liu. 2020. "An Integrated Measurement of the Efficiency of China’s Industrial Circular Economy and Associated Influencing Factors." Mathematics 8, no. 9: 1610.
Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens’ health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens’ health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China’s various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens’ health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast–southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens’ health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens’ health status. The Engel coefficient, urban–rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens’ health levels, these three factors have played important roles in hindering the improvements of citizen health.
Chenyu Lu; Shulei Jin; Xianglong Tang; Chengpeng Lu; Hengji Li; Jiaxing Pang. Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors. Healthcare 2020, 8, 231 .
AMA StyleChenyu Lu, Shulei Jin, Xianglong Tang, Chengpeng Lu, Hengji Li, Jiaxing Pang. Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors. Healthcare. 2020; 8 (3):231.
Chicago/Turabian StyleChenyu Lu; Shulei Jin; Xianglong Tang; Chengpeng Lu; Hengji Li; Jiaxing Pang. 2020. "Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors." Healthcare 8, no. 3: 231.
The study of urban spatial structure is currently one of the most popular research fields in urban geography. This study uses Lanzhou, one of the major cities in Northwest China, as a case area. Using the industry classification of POI data, the nearest-neighbor index, kernel density estimation, and location entropy are adopted to analyze the spatial clustering-discrete distribution characteristics of the overall economic geographical elements of the city center, the spatial distribution characteristics of the various industry elements, and the overall spatial structure characteristics of the city. All of these can provide a scientific reference for the sustainable optimization of urban space. The urban economic geographical elements generally present the distribution trend of center agglomeration. In respect of spatial distribution, the economic geographical elements in the central urban area of Lanzhou have obvious characteristics of central agglomeration. Many industrial elements have large-scale agglomeration centers, which have formed specialized functional areas. There is a clear “central–peripheral” difference distribution in space, with an obvious circular structure. Generally, tertiary industry is distributed in the central area, and secondary industry is distributed in the peripheral areas. In general, a strip-shaped urban spatial structure with a strong main center, weak subcenter and multiple groups is present. Improving the complexity of urban functional space is an important goal of spatial structure optimization.
Chenyu Lu; Min Pang; Yang Zhang; Hengji Li; Chengpeng Lu; Xianglong Tang; Wei Cheng. Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China. ISPRS International Journal of Geo-Information 2020, 9, 92 .
AMA StyleChenyu Lu, Min Pang, Yang Zhang, Hengji Li, Chengpeng Lu, Xianglong Tang, Wei Cheng. Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China. ISPRS International Journal of Geo-Information. 2020; 9 (2):92.
Chicago/Turabian StyleChenyu Lu; Min Pang; Yang Zhang; Hengji Li; Chengpeng Lu; Xianglong Tang; Wei Cheng. 2020. "Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China." ISPRS International Journal of Geo-Information 9, no. 2: 92.
The issue of how to realize the coordinated development of various elements in human–land systems, or, in other words, how to achieve the coordinated development of population-economy-society-resource-environment (PESRE) systems, has become an important topic, which has received global attention. This study takes 31 provinces in China as the research objects, and carries out the research on the spatial–temporal synthetic measurement of the coordinated development of PESRE systems. The conclusions are as follows. From 1995 to 2015, the process of change of coupling coordination degree of China’s PESRE systems can be divided into two types: Rising first and then declining, and fluctuant continuously. The number of provinces of the first type was higher, and most provinces were on the verge of uncoordinated development status or in a weakly coordinated development status. The coupling degree of PESRE systems at the provincial level in China generally shows some positive spatial correlations, and the level of coordinated development displays some obvious spatial aggregation patterns. Moreover, the degree of such aggregation first increases and then weakens. The eastern parts of China represent the main “high-high” type aggregation regions. The central and western parts of China represent the main “low-low” types, account for the largest proportion, and display obvious aggregation characteristics.
Chenyu Lu; Jiaqi Yang; Hengji Li; Shulei Jin; Min Pang; Chengpeng Lu. Research on the Spatial–Temporal Synthetic Measurement of the Coordinated Development of Population-Economy-Society-Resource-Environment (PESRE) Systems in China Based on Geographic Information Systems (GIS). Sustainability 2019, 11, 2877 .
AMA StyleChenyu Lu, Jiaqi Yang, Hengji Li, Shulei Jin, Min Pang, Chengpeng Lu. Research on the Spatial–Temporal Synthetic Measurement of the Coordinated Development of Population-Economy-Society-Resource-Environment (PESRE) Systems in China Based on Geographic Information Systems (GIS). Sustainability. 2019; 11 (10):2877.
Chicago/Turabian StyleChenyu Lu; Jiaqi Yang; Hengji Li; Shulei Jin; Min Pang; Chengpeng Lu. 2019. "Research on the Spatial–Temporal Synthetic Measurement of the Coordinated Development of Population-Economy-Society-Resource-Environment (PESRE) Systems in China Based on Geographic Information Systems (GIS)." Sustainability 11, no. 10: 2877.
The theme of global sustainable development has changed from environmental management to climate governance, and relevant policies on climate governance urgently need to be implemented by the public. The public understanding of climate change has become the prerequisite and basis for implementing various climate change policies. In order to explore the affected factors of climate change perception among Chinese residents, this study was conducted across 31 provinces and regions of China through field household surveys and interviews. Combined with the residents’ perception of climate change with the possible affected factors, the related factors affecting Chinese residents’ perception of climate change were explored. The results show that the perceptive level of climate change of Chinese residents is related to the education level and the household size of residents. Improving public awareness of climate change risk in the context of climate change through multiple channels will also help to improve residents’ awareness of climate change. On the premise of improving the level of national education, improving education on climate change in school education and raising awareness of climate change risk among dependents will help to improve the level of Chinese residents’ awareness of climate change, which could be instrumental in promoting public participation in climate change mitigation and adaptation actions.
Jinjia Wu; Jiansheng Qu; Hengji Li; Li Xu; Hongfen Zhang; Suman Aryal; Jingjing Zeng; Yujie Fan; Qin Wei; Xiafei Liu. What Affects Chinese Residents’ Perceptions of Climate Change? Sustainability 2018, 10, 4712 .
AMA StyleJinjia Wu, Jiansheng Qu, Hengji Li, Li Xu, Hongfen Zhang, Suman Aryal, Jingjing Zeng, Yujie Fan, Qin Wei, Xiafei Liu. What Affects Chinese Residents’ Perceptions of Climate Change? Sustainability. 2018; 10 (12):4712.
Chicago/Turabian StyleJinjia Wu; Jiansheng Qu; Hengji Li; Li Xu; Hongfen Zhang; Suman Aryal; Jingjing Zeng; Yujie Fan; Qin Wei; Xiafei Liu. 2018. "What Affects Chinese Residents’ Perceptions of Climate Change?" Sustainability 10, no. 12: 4712.
Eco-efficiency is a tool for sustainability analysis that indicates how to carry out economic activities effectively. This paper assesses agricultural eco-efficiency using data envelopment analysis (DEA) and the Theil index approach. Using basic data of 31 provinces in China during 2003–2013, we analyzed the agricultural eco-efficiency development level and spatial pattern in China. The results show that the agricultural eco-efficiency of only four provinces has been relatively efficient in the entire study period, namely, Zhejiang, Hainan, Chongqing, and Tibet. The results also show that agricultural eco-efficiency was higher mainly in south of the Qinling Mountains-Huaihe River Line and north of the Yangtze River area, that agricultural eco-efficiency is mainly affected by pure technical efficiency, and that highly efficient areas are mainly concentrated in the densely populated areas, i.e., the economic developed areas (except Tibet). The Theil index results show that the agricultural eco-efficiency difference weakened between provinces in China, as did western and northeast regions, but eastern and central regions show a slight upward trend.
Jiaxing Pang; Xingpeng Chen; Zilong Zhang; Hengji Li. Measuring Eco-Efficiency of Agriculture in China. Sustainability 2016, 8, 398 .
AMA StyleJiaxing Pang, Xingpeng Chen, Zilong Zhang, Hengji Li. Measuring Eco-Efficiency of Agriculture in China. Sustainability. 2016; 8 (4):398.
Chicago/Turabian StyleJiaxing Pang; Xingpeng Chen; Zilong Zhang; Hengji Li. 2016. "Measuring Eco-Efficiency of Agriculture in China." Sustainability 8, no. 4: 398.
As the largest solid waste (SW) generator in the world, China is facing serious pollution issues induced by increasing quantities of SW. The sustainability assessment of SW management is very important for designing relevant policy for further improving the overall efficiency of solid waste management (SWM). By focusing on industrial solid waste (ISW) and municipal solid waste (MSW), the paper investigated the sustainability performance of SWM by applying decoupling analysis, and further identified the main drivers of SW change in China by adopting Logarithmic Mean Divisia Index (LMDI) model. The results indicate that China has made a great achievement in SWM which was specifically expressed as the increase of ISW utilized amount and harmless disposal ratio of MSW, decrease of industrial solid waste discharged (ISWD), and absolute decoupling of ISWD from economic growth as well. However, China has a long way to go to achieve the goal of sustainable management of SW. The weak decoupling, even expansive negative decoupling of ISW generation and MSW disposal suggests that China needs timely technology innovation and rational institutional arrangement to reduce SW intensity from the source and promote classification and recycling. The factors of investment efficiency and technology are the main determinants of the decrease in SW, inversely, economic growth has increased SW discharge. The effects of investment intensity showed a volatile trend over time but eventually decreased SW discharged. Moreover, the factors of population and industrial structure slightly increased SW.
Xingpeng Chen; Jiaxing Pang; Zilong Zhang; Hengji Li. Sustainability Assessment of Solid Waste Management in China: A Decoupling and Decomposition Analysis. Sustainability 2014, 6, 9268 -9281.
AMA StyleXingpeng Chen, Jiaxing Pang, Zilong Zhang, Hengji Li. Sustainability Assessment of Solid Waste Management in China: A Decoupling and Decomposition Analysis. Sustainability. 2014; 6 (12):9268-9281.
Chicago/Turabian StyleXingpeng Chen; Jiaxing Pang; Zilong Zhang; Hengji Li. 2014. "Sustainability Assessment of Solid Waste Management in China: A Decoupling and Decomposition Analysis." Sustainability 6, no. 12: 9268-9281.