Study on the Spatial-temporal Evolution Characteristics and Trajectory of the Coupling Coordination Degree between Carbon Emission Intensity and High-quality Development of Energy-intensive Industries

This paper constructs the index of high-quality development of energy-intensive industries and calculates the coupling coordination degree between high-quality development and carbon emission intensity. In this study, the dynamic evolution process, regional inequality and convergence characteristics of the coupling coordination degree are investigated using kernel density estimation, Dagum Gini coefficient, and convergence analysis. The results show that (1) the full-sample coupling coordination degree fluctuates in medium levels, showing a two-stage inverted U-shaped trend. In addition, the highest coupling coordination degree occurred in the eastern region, followed by western provinces, and the lowest in the central regions. (2) Results of kernel density estimation showed a shift in coupling coordination degree from bipolar to unipolar; (3) the Dagum Gini coefficient shows that the general, inter-regional, and intra-regional variations all show an upward trend, suggesting a significant elevated polarization effect. Additionally, the primary determinants influencing the Dagum Gini coefficient reveal a pattern of “inter-regional variation - antagonism - hypervariable density.” (4) absolute convergence exists in the overall sample and in the eastern region, while it is not significant in the central and western regions. Based on the aforementioned findings, this study proposes policy implications for different regions in China

Temporal and Spatial Evolution of Agricultural Carbon Emissions and Their Impact on Functional Zoning: Evidence from Hubei Province

Introduction: To investigate the spatiotemporal evolution of agricultural carbon emissions and carbon absorption, analyse the spatiotemporal variations in the carbon balance, delineate carbon-offsetting regions, and formulate low-carbon development strategies tailored to various major functional zones, this study aims to promote coordinated regional ecological and environmental governance. Methods: This study takes a perspective based on major functional zones, focuses on 17 cities in Hubei Province, studies the spatiotemporal variations in agricultural carbon budgets and carbon offsets in each city from the perspective of functional zoning and proposes a spatial optimization scheme for reducing carbon emissions. Results and discussion: The results show that both agricultural carbon emissions and carbon absorption in Hubei Province gradually increased, although the agricultural carbon budgets varied significantly among cities. Arable lands were the main agricultural carbon sinks in Hubei Province. Overall, carbon emissions exhibited declining core–periphery zonation, with Xiangyang, Jingzhou, and Huanggang serving as the centre (high emissions) and the cities of Shennongjia, Enshi, and Yichang serving as the periphery (low emissions). Carbon absorption displayed a U-shaped distribution, with high values in the east, south, and west and low values in the centre and north. The cities of Yichang, Jingmen, and Huanggang were the peak carbon sink areas. In recent years, the coordination between the agricultural carbon emissions and carbon budgets in Hubei Province has gradually improved, and agricultural carbon absorption and emissions have become increasingly balanced. Seven carbon-positive, five carbon-neutral, and five carbon-negative areas were identified in the province. Based on these findings, differentiated carbon emission reduction strategies were proposed to promote coordinated and low-carbon agriculture

Tourism-Related CO 2

The rapid development of the tourism industry has been accompanied by an increase in CO2 emissions and has a certain degree of impact on climate change. This study adopted the bottom-up approach to estimate the spatiotemporal change of CO2 emissions of the tourism industry in China and its 31 provinces over the period 2000–2015. In addition, the decoupling index was applied to analyze the decoupling effects between tourism-related CO2 emissions and tourism economy from 2000 to 2015. The results showed that the total CO2 emissions of the tourism industry rose from 37.95 Mt in 2000 to 100.98 Mt in 2015 with an average annual growth rate of 7.1%. The highest CO2 emissions from the tourism industry occurred in eastern coastal China, whereas the least CO2 emissions were in the west of China. Additionally, the decoupling of CO2 emissions from economic growth in China’s tourism industry had mainly gone through the alternations of negative decoupling and weak decoupling. The decoupling states in most of the Chinese provinces were desirable during the study period. This study may serve as a scientific reference regarding decision-making in the sustainable development of the tourism industry in China

Climate Change and Environmental Sustainability-Volume 4

Anthropogenic activities are significant drivers of climate change and environmental degradation. Such activities are particularly influential in the context of the land system that is an important medium connecting earth surface, atmospheric dynamics, ecological systems, and human activities. Assessment of land use land cover changes and associated environmental, economic, and social consequences is essential to provide references for enhancing climate resilience and improving environmental sustainability. On the one hand, this book touches on various environmental topics, including soil erosion, crop yield, bioclimatic variation, carbon emission, natural vegetation dynamics, ecosystem and biodiversity degradation, and habitat quality caused by both climate change and earth surface modifications. On the other hand, it explores a series of socioeconomic facts, such as education equity, population migration, economic growth, sustainable development, and urban structure transformation, along with urbanization. The results of this book are of significance in terms of revealing the impact of land use land cover changes and generating policy recommendations for land management. More broadly, this book is important for understanding the interrelationships among life on land, good health and wellbeing, quality education, climate actions, economic growth, sustainable cities and communities, and responsible consumption and production according to the United Nations Sustainable Development Goals. We expect the book to benefit decision makers, practitioners, and researchers in different fields, such as climate governance, crop science and agricultural engineering, forest ecosystem, land management, urban planning and design, urban governance, and institutional operation.Prof. Bao-Jie He acknowledges the Project NO. 2021CDJQY-004 supported by the Fundamental Research Funds for the Central Universities and the Project NO. 2022ZA01 supported by the State Key Laboratory of Subtropical Building Science, South China University of Technology, China. We appreciate the assistance of Mr. Lifeng Xiong, Mr. Wei Wang, Ms. Xueke Chen, and Ms. Anxian Chen at School of Architecture and Urban Planning, Chongqing University, China

A Nonparametric Analysis of Energy Environmental Kuznets Curve in Chinese Provinces

Energy resources are an important material foundation for the survival and development of human society, and the relationship between energy and economy is interactive and complementary. This paper analyzes the energy consumption–economic growth nexus in Chinese provinces using novel and recent nonparametric time-series as well as panel data empirical approaches. The dataset covers 30 provinces over the period of 1980-2018. The empirical analysis indicates the presence of a nonlinear functional form and smooth structural changes in most of the provinces. The nonparametric empirical analysis validates the presence of a nonlinear unit root problem in energy consumption and economic growth, and nonlinear cointegration between the variables. Additionally, the nonparametric panel cointegration test reports evidence of convergence in energy consumption and economic growth patterns across the provinces. The nonparametric regression analysis finds economic growth to have a positive effect, on average, on energy consumption in all provinces, except for Beijing. Further, the energy environmental Kuznets curve exists between economic growth and energy consumption in 20 out of 30 Chinese provinces. The Granger causality analysis reveals the presence of a mixed causal relationship between economic growth and energy consumption. The empirical findings have important implications for Chinese authorities in planning for improving energy efficiency, decoupling between economic growth and energy consumption, and reducing the environmental footprint of provinces

Regional development and carbon emissions in China

China announced at the Paris Climate Change Conference in 2015 that the country would reach peak carbon emissions around 2030. Since then, widespread attention has been devoted to determining when and how this goal will be achieved. This study aims to explore the role of China’s changing regional development patterns in the achievement of this goal. This study uses the logarithmic mean Divisia index (LMDI) to estimate seven socioeconomic drivers of the changes in CO2 emissions in China since 2000. The results show that China’s carbon emissions have plateaued since 2012 mainly because of energy efficiency gains and structural upgrading (i.e., industrial structure, energy mix and regional structure). Regional structure, measured by provincial economic growth shares, has drastically reduced CO2 emissions since 2012. The effects of these drivers on emissions changes varied across regions due to their different regional development patterns. Industrial structure and energy mix resulted in emissions growth in some regions, but these two drivers led to emissions reduction at the national level. For example, industrial structure reduced China’s CO2 emissions by 1.0% from 2013-2016; however, it increased CO2 emissions in the Northeast and Northwest regions by 1.7% and 0.9%, respectively. By studying China’s plateauing CO2 emissions in the new normal stage at the regional level, it is recommended that regions cooperate to improve development patterns

Evolution of spatial and temporal patterns of railway container transportation: A case study of China cities

The healthy development of railway container transport is an important part of railway freight transport and is key for promoting the green transformation of China's transport and supporting a new pattern of transport development. In this study, railway container handling station (RCHS) data, kernel density analysis, standard deviation ellipse, Herfindahl–Hirschman index (HHI), trend surface analysis (TSA), and R index were applied to examine the evolution characteristics of container transport patterns after the market-oriented reform of China's railway freight transport in 2013. The results are as follows: First, the overall scale growth trend is obvious, and the double-center effect of transport scale on the Bohai Rim region and Chengdu–Chongqing Economic Zone is evident, with the transport center of gravity moving northward. Second, the amount of attraction/occurrence is consistent in spatial distribution, and the aggregation effect of both is similar, essentially exhibiting a tendency of being high in the northwest and low in the southeast. Third, the pattern of “export-oriented in the north and import-oriented in the south” has taken shape; nearly half of cities in China have stable traffic functions, stable traffic supply, and demand relationships, and the change of functions shows that the industrial structure is constantly upgrading. This study elucidates the pattern of railway container transport in cities in China and provides empirical guidance for adjusting the functions of urban freight transport, thereby promoting the healthy development of urban freight transport and optimizing urban transport planning

Study on the coupling coordination and pattern evolution of green investment and ecological development: Based on spatial econometric model and China’s provincial panel data

The study determines the coupling degree of green investment and green ecology in China using kernel density estimation, spatial autocorrelation analysis, and standard deviation ellipse model to empirically evaluate the data of 30 Chinese provinces from 2005 to 2019. Moreover, the study investigates the temporal evolution trend, spatial clustering characteristics, and spatial evolution trend of coupling degree. Although the coupling coordination value of green investment and green ecology gradually increased, it is generally at a low coordination stage. At the same time, regional disparities narrowed with the most significant variability in the eastern region. Moreover, results found that the aggregation effect of the coupling and coordination of green investment and green ecology is more significant, and the high-value aggregation area extended from the lower reaches of the Yangtze River to the midstream region, while the western region is dominated by low-value aggregation. Similarly, the degree of synergy between green investment and green ecology is increased; however, the fragmentation trend is inevitable. At the same time, the center of gravity of coupling coordination shifted to the western regions, and the spatial pattern gradually weakened in the “northeast-southwest” direction. The findings of the study stress that local governments of China should improve the green investment system for green ecological development in the surrounding areas of the Yangtze River Economic Belt. Moreover, it is required to focus on the Northeast revitalization and Western development strategies to promote the synergistic development of green investment and green ecology

The spatial pattern and influencing factors of tourism eco-efficiency in Inner Mongolia, China

BackgroundTourism eco-efficiency is a performance basis for evaluating green total factor productivity and sustainable development.ObjectiveThe objective of this study was to measure tourism eco-efficiency in Inner Mongolia and explore its influencing factors. The aim was to provide an accurate reference for improving the quality and efficiency of tourism in Inner Mongolia and promoting the sustainable development of the regional economy and society.MethodsTourism eco-efficiency in Inner Mongolia from 2009 to 2019 was calculated using a super-slacks-based measure (SBM) model with an undesirable output. The spatial variation function was used to explore the spatial evolution pattern of tourism eco-efficiency in Inner Mongolia, and the influencing factors of the spatial evolution were analyzed by geographically weighted regression.ResultsTourism eco-efficiency in Inner Mongolia is relatively low. Eco-efficiency values among cities in Inner Mongolia vary, and their distribution is not balanced. The structural eco-efficiency of tourism in Inner Mongolia has been consistent from 2009 to 2019. The degree of homogenization in the overall direction is relatively good. Furthermore, its spatial distribution form and internal structure evolution show a certain regularity and continuity. The pattern evolution of tourism eco-efficiency in Inner Mongolia is jointly driven by the economic level, environmental regulation, industrial structure, traffic conditions, resource endowment, and tourism reception facilities. These influencing factors show obvious spatial heterogeneity.ConclusionFrom the perspective of Inner Mongolia, the difference in the tourism eco-efficiency value from 2009 to 2019 was relatively large, but the number of effective areas in the efficiency frontier generally showed a fluctuating growth trend. The range parameters of tourism eco-efficiency showed a decreasing trend, and the spatial correlation effect of tourism eco-efficiency in Inner Mongolia showed a decreasing trend under the influence of structural and spatial differentiation