The Consumption-Based Carbon Emissions in the Jing-Jin-Ji Urban Agglomeration Over China's Economic Transition

Since the 2008 financial crisis, China has been undergoing an economic transition consisting of prioritizing green economic and sustainable development instead of rapid growth driven by large-scale investment. However, there is still a lack of fine print on how subregional effort can contribute to national or full supply chain mitigation plans, especially downscaling to the city level. To bridge this knowledge gap, we selected Jing-Jin-Ji urban agglomeration, one of the economic centers but also featured by intensive emission for decades, to analyze the emission variance and driving forces from 2012 to 2015 as a case study. Based on the consumption accounting framework, the carbon emissions of Jing-Jin-Ji have decreased by 11.7 Mt CO2 in total over the study period, and most cities showed the similar descending trend. The driving forces show that the emission intensity and production structure have largely reduced Jing-Jin-Ji's total due to measurements of economic transition. For instance, Beijing has decreased by 28.7 Mt of emission reduction which led by declined emission intensity. By contrast, per capita demands and growth of its population were the primary forces to increase emissions. To conclude, although the mitigation achievement is undeniable, we should also note that the economic transition has not changed the uneven pattern of selected urban agglomeration so far

The Consumption-Based Carbon Emissions in the Jing-Jin-Ji Urban Agglomeration Over China's Economic Transition

Abstract Since the 2008 financial crisis, China has been undergoing an economic transition consisting of prioritizing green economic and sustainable development instead of rapid growth driven by large‐scale investment. However, there is still a lack of fine print on how subregional effort can contribute to national or full supply chain mitigation plans, especially downscaling to the city level. To bridge this knowledge gap, we selected Jing‐Jin‐Ji urban agglomeration, one of the economic centers but also featured by intensive emission for decades, to analyze the emission variance and driving forces from 2012 to 2015 as a case study. Based on the consumption accounting framework, the carbon emissions of Jing‐Jin‐Ji have decreased by 11.7 Mt CO2 in total over the study period, and most cities showed the similar descending trend. The driving forces show that the emission intensity and production structure have largely reduced Jing‐Jin‐Ji's total due to measurements of economic transition. For instance, Beijing has decreased by 28.7 Mt of emission reduction which led by declined emission intensity. By contrast, per capita demands and growth of its population were the primary forces to increase emissions. To conclude, although the mitigation achievement is undeniable, we should also note that the economic transition has not changed the uneven pattern of selected urban agglomeration so far

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

Spatial heterogeneity and driving forces of environmental productivity growth in China: Would it help to switch pollutant discharge fees to environmental taxes?

© 2019 Elsevier Ltd Emission charge policy has recently switched from pollutant discharge fees to environmental taxes in China. Considering spatial heterogeneity, the effects of changes in emission charge policy may subject to different Chinese regions. In this study, environmental efficiencies of Chinese regions are evaluated through provincial environmentally extended input-output tables and a frontier-based optimization model. Driving factors of environmental productivity growth are identified through global Luenberger productivity decomposition approach. Moreover, spatial heterogeneity on the effects of change in emission charge policy on environment and economy are assessed. Results show that all regions experienced environmental productivity growth. Technology progress is the major driving factor in most regions with an average contribution of 90%, while technical efficiency regress slows environmental productivity growth in Southwest region. Switching from pollutant discharge fees to environmental taxes would decreases emission intensities by 1.42% on average, but it would have different negative impact on economic growth (−1.13%∼-4.90% of regional GDP) due to spatially heterogeneous trade-offs between environmental protection and economic development. Addressing such spatial heterogeneity provide not only a basis for diversified tax rate determination but also a framework for other environmental policy assessment

The target selection and quantitative evaluation for deep geothermal resource zoning of typical geothermal fields in central Hebei of North China plain

With the rapid economic development in North China, the demand for geothermal energy is increasing. It is urgent to find favorable deep geothermal resource targets in North China. Although geothermal resources in the North China Plain are widely distributed, in order to develop deep geothermal resources in North China safely, stably and efficiently, it is essential to carry out the target selection and evaluation of geothermal resource zoning. This article takes the typical geothermal fields in the central Hebei region as the research object, and through the comprehensive collation of regional geothermal geological data, constructs an optimization evaluation indicator system for geothermal resource target areas from three aspects: resource conditions, mining potential, and heating demand. On this basis, it establishes a linear relationship between the attribute values and scores of each indicator, and uses the analytic hierarchy process to assign weights to each indicator and calculate the comprehensive weight. Then, the comprehensive evaluation value is obtained by weighted calculation of the scores and comprehensive weights of each block in the grid segmentation of the evaluation area. Finally, through the spatial analysis function of GIS, the comprehensive evaluation values of all blocks in the evaluation area were analyzed using kriging difference analysis, and a comprehensive evaluation map, the geothermal resource prospective target area map, was finally obtained. Using quantitative zoning evaluation methods, the target areas for exploration and development of deep geothermal resources in central Hebei Province have been delineated within a large region. The evaluation results indicate that the Cambrian-Ordovician reservoir target area is relatively large, and there are many favorable target areas with good reservoir conditions in the Middle-Upper Proterozoic. The excellent prospective target area of the Mesoproterozoic geothermal reservoir accounts for 56%, mainly located in the Xingji uplift and Gaoyang low uplift. Xiong’an New Area, Cangzhou, and the eastern part of Hengshui are excellent prospective target areas for the evaluation of the Mesoproterozoic geothermal reservoir in a single area. This evaluation method can provide a reference for the optimization of resource exploration and development target areas in key regions

Water Demand Forecast in the Baiyangdian Basin with the Extensive and Low-Carbon Economic Modes

The extensive and low-carbon economic modes were constructed on the basis of population, urbanization level, economic growth rate, industrial structure, industrial scale, and ecoenvironmental water requirement. The objective of this paper is to quantitatively analyze effects of these two economic modes on regional water demand. Productive and domestic water demands were both derived by their scale and quota. Ecological water calculation involves the water within stream, wetland, and cities and towns. Total water demand of the research region was obtained based on the above three aspects. The research method was applied in the Baiyangdian basin. Results showed that total water demand with the extensive economic mode would increase by 1.27 billion m3, 1.53 billion m3, and 2.16 billion m3 in 2015, 2020, and 2030, respectively, compared with that with low-carbon mode

統合的な水資源管理のための水環境に対する社会的・経済的影響の分析

The water environment faces a terrible vulnerability trend. This study focused on the evaluation of the water environment in China and identified the effects of social-economic factors using recent statistical methods. Chapter 1 is the introduction. Chapter 2 is the literature review. Chapter 3 introduces water vulnerability in urban areas. The fluctuation of the indicators across provinces was larger than in previous studies that used province-level data in China. Chapter 4 used indicators that considered both development pressure and management capability. Four province-level municipalities and their neighboring provinces were studied. Vector autoregression models were used for analyzing spatial-temporal characteristics. Chapter 5 showed results from analyses of agricultural water indicators, its influencing factors, and the influence of urbanization. The study areas consisted of 30 cities in four provinces in North China. Spatial agglomerations of urban and agricultural activities affected agricultural water stress. Chapter 6 is the conclusion.北九州市立大

Secure and Sustainable Energy System

This special issue aims to contribute to the climate actions which called for the need to address Greenhouse Gas (GHG) emissions, keeping global warming to well below 2°C through various means, including accelerating renewables, clean fuels, and clean technologies into the entire energy system. As long as fossil fuels (coal, gas and oil) are still used in the foreseeable future, it is vital to ensure that these fossil fuels are used cleanly through abated technologies. Financing the clean and energy transition technologies is vital to ensure the smooth transition towards net zero emission by 2050 or beyond. The lack of long‐term financing, the low rate of return, the existence of various risks, and the lack of capacity of market players are major challenges to developing sustainable energy systems.This special collected 17 high-quality empirical studies that assess the challenges for developing secure and sustainable energy systems and provide practical policy recommendations. The editors of this special issue wish to thank the Economic Research Institute for ASEAN and East Asia (ERIA) for funding several papers that were published in this special issue