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Energy infrastructure connectivity is a key implementation area for the success of the Belt and Road Initiative. In the current complex international environment, China's energy infrastructure investment in the countries along the Belt and Road is often restricted due to varying degrees of heated disputes with the host countries, thus facing the political risk of investment loss or even failure. This paper used the Heckman two-stage selection model to overcome the sample selection problem in traditional literature and systematically studied the political risks to China's energy infrastructure investment in countries along the Belt and Road within a unified framework. The results showed that Chinese energy infrastructure investments exhibited market-seeking and energy resource-seeking features; while political risks had a significant impact on choosing the locations of energy infrastructure investments, socio-environmental factors were not given sufficient attention. At the national level, the implementation of the Belt and Road Initiative was beneficial to China's foreign energy infrastructure investments under certain regulatory levels and environmental policy performance. [ABSTRACT FROM AUTHOR]

Copyright of China Quarterly is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Large-scale clean-heating renovations are being carried out in northern China as part of important measures to optimize energy infrastructure, improve the atmospheric environment, and minimize peak CO2 emissions. Because rural areas in the urban–rural fringe are close to the city center, they have several advantages in centralized heating reforms, but there are no effective means to measure whether a transformation is economical or has good environmental effects. In this paper, based on an actual reconstruction project, 100 typical households were selected for a related test. These typical households evinced convergence and possessed certain regional characteristics; therefore, the applicability of the models had certain limitations. To make sure that the relevant factors were fully considered in establishing the model, a prediction model group was established regarding heat consumption in winter (four models in total) that could predict the actual effect well. Lastly, the authors used the model group to calculate economic effects and CO2 emission reduction in rural heating transformations in Beijing under different heating methods. [ABSTRACT FROM AUTHOR]

At present, two subsidy policies, which are based on electric vehicle (EV) consumers and EV charging station firms, have been widely implemented in different areas in China to promote EV adoption. However, the effectiveness of subsidy policies is significantly influenced by the indirect network and herd effects, depicting the positive impacts of the numbers of energy infrastructure firms and the sales of vehicles on consumers' utilities, respectively. Taking the aforementioned effects into consideration, this study examines the optimal subsidy policies by developing a Stackelberg game model. The game model analyzes the interaction and decisions of multiple stakeholders (i.e., consumers, energy infrastructure firms, EV and gasoline vehicle manufacturers, and the government). Interestingly, we find that a stronger herd effect will promote EV sales when the unit production cost of EVs is low; however, it will hinder EV sales when the unit production cost is high. Besides, we compare the effectiveness of the two subsidy policies for promoting EV adoption, reducing environmental impacts, and increasing the social welfare. Findings show that the effectiveness of subsidy policies highly depends on the extent of the indirect network and herd effects. Specifically, compared with EV consumers-based subsidy policy, EV charging station firms-based subsidy policy will be more effective in only two conditions: a weak indirect network effect and a strong herd effect. Otherwise, the EV consumers-based subsidy policy will be more effective. The findings of the paper are helpful in enhancing the effectiveness of subsidy policy in China. • Government subsidy cannot always promote electric vehicle adoption. • The indirect network and herd effects affect the effectiveness of subsidy policy. • A stronger herd effect will not always promote electric vehicle sales. • Either consumers or charging station investors can be the best subsidy object. [ABSTRACT FROM AUTHOR]

As China's Belt and Road Initiative (BRI) has emerged as the largest public financier for energy infrastructure projects worldwide, concerns about the environmental and climate impacts of such projects have led to mounting international pressure on the Chinese government to 'green' its investment practices. This paper examines the understudied role of international engagement, and of specific international actors, in greening China's BRI. We propose two discrete models of engagement which serve as a means of understanding the role that international actors have played in greening China's BRI: (1) through direct engagement that influences individual project outcomes; and (2) through indirect engagement that shapes China's broader policies and investment practices. We also identify factors that have constrained the role of international influence, including the absence of an influential Chinese international development agency. Finally, we propose opportunities for international engagement with China regarding its overseas investment practices. [ABSTRACT FROM AUTHOR]

In the Xi Jinping era, China is actively implementing the Belt and Road Initiative (BRI) around the globe. Under the BRI, infrastructure development has become the main agenda for China to create connectivity. One of the infrastructure projects in the energy sector is the Nam Ou Cascade Hydropower Project. The Nam Ou River is a tributary of the Mekong River located in Laos and borders China. For Laos, this project is part of their vision to be "The battery of Southeast Asia." Therefore, this article attempts to explain that Nam Ou Hydropower has implications for China's dominance in the Mekong region. The circle hydro-hegemony is used as the conceptual framework for analyzing the phenomenon. This article also applies a qualitative method with secondary data. The article shows that the Nam Ou Cascade Hydropower Project in Laos elevates China's influence in the Mekong region. By actively pulling and pushing its neighbors into cooperation, China exercises its power as an upstream country. [ABSTRACT FROM AUTHOR]

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals. • The current study analyses the role of green factor productivity in zero carbon transition. • We use 30 chinese provincial datasets from 2005 to 2020. • Energy transition is the most effective channel to improve green total factor productivity. [ABSTRACT FROM AUTHOR]

Low-carbon transition stands as a vital strategy for the global community to address the challenge of climate change, inevitably affecting residents' daily lives. However, there is a notable gap in the quantitative analysis of the low-carbon transition's impact on energy poverty in developing countries, limiting policymakers' understanding of the inherent mechanism and their ability to take informed actions. This study investigates the low-carbon city pilot (LCCP) policy, China's key low-carbon initiative, as a quasi-natural experiment, using the difference-in-differences (DID) method to examine its impact on residents' energy poverty conditions. Utilizing panel data from 4807 households in the CHARLS dataset, this study effectively integrated household-level and city-level data. Benchmark regression indicates that the LCCP policy exacerbates energy poverty among residents. Further analysis reveals the pivotal role of energy infrastructure and expenditure in bridging the nexus between the LCCP policy and energy poverty, providing crucial insights into the potential pathways through which this policy impacts energy poverty. Additionally, heterogeneity analysis indicates that the impacts of LCCP policy are more pronounced in eastern cities, non-resource cities, and high administrative-level cities, as well as in the communities suffering from subpar governance quality. By leveraging reliable survey data and robust quantitative methods, this study not only broadens the methodology of energy poverty studies but also offers valuable insights for developing countries to safeguard residents' energy welfare amid low-carbon transitions. [ABSTRACT FROM AUTHOR]

Whether constructing more transportation infrastructure can be helpful for the achievement of energy conservation is a long-running and debatable issue. To answer this question, the relationship between transportation infrastructure and energy efficiency must first be clarified. Nonetheless, the existence of the endogeneity problem poses a challenge to defining the relationship. In this paper, an endogenous stochastic frontier analysis method is used to investigate the influence of transportation infrastructure on energy efficiency. Based on the prefecture-city level panel data in China, we find that after addressing the endogeneity problem, the impact of transportation infrastructure on energy efficiency increases dramatically. Moreover, this impact is more pronounced in small-scale cities compared to large and medium-scale cities. Regardless of the measurement of transportation infrastructure, instrumental variable, or production function form, we get the similar conclusions, demonstrating the robustness of our findings. Additional simulation analysis shows that the energy conservation potential would be 1222–2935 million kilowatt hours if the level of transportation infrastructure could be optimized. We recommend accelerating the transportation infrastructure construction, particularly in the small-scale cities so as to boost the energy efficiency and achieve energy conservation targets. • The relationship between energy efficiency and transportation infrastructure is investigated. • The endogeneity of transportation infrastructure is addressed. • A novel framework to analyze the relationship between energy efficiency and transportation infrastructure is proposed. • Accelerating the construction of transportation infrastructure to increase energy efficiency is proposed. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, renewable energy, especially wind power, solar PV and hydropower, will become the most important power sources in the future low-carbon power system. Since wind power and solar PV are specifically intermittent and space-heterogeneity, an assessment of renewable energy potential considering the variability of wind power and solar PV with high temporal resolution in different regions will facilitate more accurate identification of the decarbonization pathway of power system. In this paper, the complementary output potential of wind-solar-hydro power every 15 min in 31 Chinese provinces is evaluated by developing a multi-objective optimization model based on Nondominated Sorting Genetic Algorithm II. The results show that the total annual complementary power generation potential in China is 17.57 PWh, of which the three components account for 47.8%, 25.3% and 26.9%, respectively. Inner Mongolia and Tibet are the major renewable energy source provinces with annual complementary power generation potential of 5330 TWh and 3907 TWh, accounting for 30.3% and 13.7% of the total power generation potential, respectively. The temporal potential of wind-solar-hydro power varies greatly, with daily potential is more volatile than monthly. Seasonal and spatial heterogeneity of the complemental renewable potential makes some provinces suffer power shortage during long-hours period especially in winter. Our findings will encourage a higher penetration of renewable energy, the promotion of multi-energy complementarity, and the development of inter-provincial power transmission and energy storage infrastructure in China's future power sector. • A multi-objective wind-solar-hydro complementary optimization model is developed. • Electricity supply and demand have gaps at different temporal and spatial scales. • Wind-solar-hydro complementary potential shows great temporal and spatial variation. • Renewable complementarity can improve China's future power system stability. [ABSTRACT FROM AUTHOR]

This study examines the impact of energy poverty on internal immigration based on the current situation in which reducing energy poverty is a necessary condition for ensuring sustainable development. The threshold effects model is applied to verify the significance of energy poverty in the prediction of internal immigration. The main results suggest that energy poverty significantly and negatively affects internal immigration. A heterogeneity analysis between coastal and non-coastal regions shows that the effects are more pronounced in non-coastal regions than in coastal regions. Further analysis reveals that there exists a kink in the threshold effects. The results remain robust using the specification of the kink threshold effects model. The policy implication is that a balanced development of energy infrastructure in different regions is required to achieve better social welfare for migrants. [ABSTRACT FROM AUTHOR]

Copyright of Automotive Digest is the property of Automotive Digest Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to examine the national risk governance mechanism of critical infrastructure in China from a cross-section perspective. The first research objective is to identify whether horizontal collaboration exists in the risk governance of critical infrastructure. Building on this, the second research objective is to investigate the extent of cross-section collaboration in the transportation and energy domains. The third research objective is to identify the pathways of horizontal collaboration at various levels. The data for this research consists of policy documents retrieved from the official websites of the Ministry of Transport of the People's Republic of China, the National Energy Administration, and the Peking University Legal Information Website. A total of 127 documents were collected using specific search keywords. To analyze data, content analysis is adopted to generate a co-word matrix so that semantic network centrality can be explored. The result indicates that in the transportation domain "engineering" and "road" feature in the top 10 for both standardized degree and degree proportion, while "administration" ranks third highest in share proportion. In the energy infrastructure risk governance keyword network, the fourth highest closeness centrality value is 54.762, associated with keywords such as "administration" and "engineering". These findings suggest that horizontal collaboration is evident at both institutional and personal levels. Moreover, the results imply that the inner collaboration within national risk governance is intricate and interdependent. The study reveals interconnections between different industries and administration levels, contributing a fresh perspective to urban risk governance theory exploration. [ABSTRACT FROM AUTHOR]

As urbanization accelerates and an increasing number of people move from rural to urban areas, changes in household energy consumption have become a major symptom of typical human-land relationship activities in different regions, i.e., labour migration is affecting household energy consumption, especially household cooking energy. Based on household data from the China Health and Nutrition Survey (1989–2015), this paper employs a panel multinomial logit model and mathematical statistics to reveal structural changes in urban and rural Chinese households cooking energy consumption and the driving factors of these changes over the past 30 years and provides suggestions for the structural upgrade of household cooking energy consumption. The research shows that household cooking energy consumption in China has undergone a substantial transition since the 1980s, displaying diverse trends in urban and rural households. The shift from coal to natural gas in urban areas and from solid fuels to electricity in rural areas was driven by a range of factors such as per capita disposable income, government policies, energy prices and availability. Among these, household income was found to be the most influential factor. Additionally, migration had a notable effect on household cooking energy consumption in rural areas. The reduction of solid fuel usage and the electrification of cooking are proven methods of lowering household energy emissions, as natural gas releases 60% less CO 2 compared to coal when producing the same amount of heat. The government must implement a focused strategy for the transition towards cleaner energy sources for household cooking, prioritizing rural areas by strengthening energy infrastructure and fostering the development of solar and wind energy. In urban areas, efforts should be directed towards enhancing income, stabilizing energy costs, and popularizing the use of natural gas. [Display omitted] • Household cooking energy consumption in China has undergone a significant transition since the 1980s. • Cooking energy transition has been influenced by various factors and has urban-rural differences. • Rural-urban migration is an important driver of rural household cooking energy transition. • The energy transition has a good effect on emission reduction and ecological improvement. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources can be supported by the digitalization of energy systems, which increase dependability and lower costs of energy production and consumption. However, the energy digitalization support energy infrastructures and technologies currently in place are insufficient. This research presented the study results by using the generalized least square estimates (GLS) model and the international sample of China regions from 2003 to 2017. Main results of the dynamic fixed effect (DFE) estimator for the autoregressive distributed lag (ARDL) method, establishing ES goals for lowering energy consumption and pollution emission fosters a country's renewable energy business sector's digital transformation in the short term, while encouraging the use of renewable energy sources fosters a country's long-term digitalization efforts. Based on this, the direct effects and dynamic effects of digitalization and financial development on environmental are explored, respectively, using the panel data regression model and panel vector autoregression (PVAR) model. The threshold regression model is then used to examine the two parameters' threshold effects on eco-efficiency. An accurate estimate of the resource consumption in smart factories is made possible by the digital twin that is created using the product's and its attributes as well as manufacturing data. The results suggests the future directions for the associated stakeholders. [ABSTRACT FROM AUTHOR]

As Earth's primary energy source, surface downward solar radiation (R s) determines the solar power potential and usage for climate change mitigation. Future projections of R s based on climate models have large uncertainties that interfere with the efficient deployment of solar energy to achieve China's carbon-neutrality goal. Here we assess 24 models in the latest Coupled Model Intercomparison Project Phase 6 with historical observations in China and find systematic biases in simulating historical R s values likely due to model biases in cloud cover and clear-sky radiation, resulting in largely uncertain projections for future changes in R s. Based on emergent constraints, we obtain credible R s with narrowed uncertainties by ∼56% in the mid-twenty-first century and show that the mean R s change during 2050–2069 relative to 1995–2014 is 30% more brightening than the raw projections. Particularly in North China and Southeast China with higher power demand, the constrained projections present more significant brightening, highlighting the importance of considering the spatial changes in future Rs when locating new solar energy infrastructures. [ABSTRACT FROM AUTHOR]

In the post-pandemic era, there is a need to achieve the dynamic and coordinated development of growth in the logistics industry, energy consumption, and carbon dioxide (CO2) emissions in China's four major economic regions to ensure the high-quality development of green logistics in China. Using the data indicators of growth in the logistics industry, energy consumption, CO2 emissions, and fixed asset investment in 30 Chinese provinces from 2004 to 2018, a panel vector autoregressive model was established for the four major economic development regions of central, east, west, and northeast China. The model coefficients were estimated using the systematic generalized matrix estimation method (System-GMM), which was evaluated by a Granger causality test. The model coefficients were estimated using the System-GMM method, and the dynamic relationships between growth in the logistics industry, energy consumption, and CO2 emissions was obtained through a Granger causality test, impulse response analysis, and variance decomposition. The results showed that the growth of the logistics industry in the four major economic regions had a positive impact on energy consumption and CO2 emissions, with the degree of contribution being smaller in the east and central regions, and larger in the west and northeast regions. Fixed asset investment had a negative impact on energy consumption and CO2 emissions, with the degree of contribution being largest in the northeast, larger in the east than in the central region, and smallest in the west. Finally, according to the conclusion and analysis of the results, from the aspects of government guidance and policy support, low-carbon logistics technology innovation, and infrastructure investment, we propose the need to pay attention to the role of government guidance, accelerate the pace of energy adjustments using the structure of the logistics industry, and increase the investment in renewable energy infrastructure, while focusing on strengthening the cooperation between regions and exploring new models of low-carbon logistics development between regions. This will ensure that the country achieves its goal of reaching peak carbon by 2030 and carbon neutrality by 2060. [ABSTRACT FROM AUTHOR]

The Chinese government identifies the renewable energy sector as a core strategic industry. Since 2009, China is the country with the highest annual investment into renewable energy, predominantly wind and solar photovoltaic projects. Due to rapid cost decline, industrial transformation, and policy support, the relative share of solar project investment is growing at a disproportionate rate. However, there is no systematic analysis of how efficiently these investments are allocated; or the underlying risk and return characteristics. Based on structured interviews with 69 market participants, this paper identifies severe cash-flow uncertainty, unreliable supply chains and a weak regulatory environment as most prominent risk factors that currently inhibit sustainable and demand-driven market development. Expanding on the interview results, this study discusses the origins of risk in China and how the institutional response to investment risk currently fails to address the core problems. [ABSTRACT FROM AUTHOR]

Although China attempts to present itself as a leader of the fight against climate change - and, in some aspects, is taking initiative in this respect - through the Belt and Road Initiative the country has lent support to many 'dirty' projects in the energy infrastructure sector. This is also the case in the Western Balkans, where Chinese banks and energy companies have invested in coal power plants. Western Balkan countries need to improve their energy infrastructure and build new capacities. An obvious solution to this issue is the extension of their coal mines and plants, but this comes with complications. They do not have the capital to invest in these projects themselves, and international monetary institutions do not support these types of investments. In contrast to this, China can offer soft loans and expertise to realise the projects. Although many of the projects that Chinese banks have invested (or intend to invest) in are delayed or only in the planning phase, it seems that some of them can be realised despite the resistance of the Energy Community and various environmentalist groups. [ABSTRACT FROM AUTHOR]