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With the fragmentation of global production, the share of intermediate trade in international trade has increased significantly. Nevertheless, more research must be done on how intermediate trade factors influence energy consumption. This paper utilized the multi-regional input-output (MRIO) model to categorize China's energy utilization into six parts based on its position within the global production chain. Additionally, it examined the impact of intermediate factors on China's energy consumption through index decomposition analysis (IDA). The results revealed that: (1) from 2000 to 2014, intermediate factors led to an increase of 1380.96Mtces in China's energy consumption, accounting for around 37% of the national total; (2) the reduction in efficiency is the primary cause of the surge in domestic intermediate energy consumption, while the increase in market proportion is the dominant driver promoting international intermediate energy consumption growth; (3) the international intermediate proportion contributed the most among all intermediate factors. Drawing upon the findings above, this paper proposed policy recommendations to regulate China's rising energy consumption, precisely the escalation of intermediate process energy usage, focusing on the global production chain. [Display omitted] • Energy consumption is divided into six parts based on the intermediate destination. • Fifteen factors is decomposed based on index decomposition analysis. • The contributions of the structure, proportion, and efficiency changes is considered. • This paper shows a way of identifying the composition of energy consumption. [ABSTRACT FROM AUTHOR]

Battery electric industrial vehicles (BEIVs) offer significant environmental protection and decarbonization potential for rapidly growing logistics and transportation sectors in China. However, the limited driving range remains a major obstacle to the widespread adoption of BEIVs. Eco-driving is an effective solution that can improve energy efficiency and extend the driving range of vehicles by controlling driving behavior and speed. Therefore, this paper introduces an energy efficient speed planning method for BEIVs, in which data-driven models are developed to estimate energy consumption. Real-world driving data collected from a BEIV are used to model the energy consumption by curve fitting, random forest, and LSTM. The speed planning process is considered a Markov Decision Process, which is solved using Dynamic Programming and Q-learning, respectively. The case study of a battery electric forklift shows that speed planning can reduce energy consumption by 13%–27% compared to time-optimal speed, while only increasing the driving time by 10%–20%. • Energy efficient speed planning methods for electric industrial vehicles are proposed. • The speed planning method uses data-driven vehicle energy consumption models. • The energy consumption models are developed using random forest and LSTM. • The speed planning problem is formulated as a Markov decision process. • The speed planning problem is solved by Dynamic Programming and Q-learning. [ABSTRACT FROM AUTHOR]

Water-energy-food (WEF) nexus system enables to examine the implications for sustainability. Inevitably, shocks from socioeconomic subsystems would impact the stability and reliability of the WEF nexus system. This paper aims to identify the reasons for changes in water withdrawal, energy consumption, and crop consumption, and uncover differentiated effects from both the national and provincial perspectives, and finally offer the main strategies in China that balance socioeconomic development and resource-saving from the consumption perspective. Empirical results in China from 2011 to 2017 show that (1) the reduction of per capita energy consumption leads to a decrease in water withdrawal, while increased population and water withdrawal intensity in energy sectors have adverse effects on diminishing water withdrawal. (2) The decrease in energy consumption mainly results from improved energy use efficiency for the whole period. (3) Reduction in national crop consumption is mainly caused by the decline in energy consumption per person over the years, which implies a positive effect of food-energy nexus effect on the decrease in crop consumption. (4) Spatially-temporarily contribution rates of drivers offer implications to the implementation of resource-saving and sustainability in the future. Directions and magnitudes of driving forces are different from the sub-nation perspective, hence, finally takes Beijing-Tianjin-Hebei (BTH) region as an example, we analyze clearly the relative planning and reports and propose several pathways to accelerate the sustainable development in the BTH region. • Comprehensively understanding demands for water-energy-food and their drivers. • Uncovering drivers' contributions dynamically from national & provincial perspectives. • Discovering distinguishable characteristics of WEF consumption variation regionally. • Assessing sustainability by coupling socioeconomic dev. with resources saving. [ABSTRACT FROM AUTHOR]

Multiple geographically dispersed data center buildings have been increasingly positioned in renewable-rich areas due to their high energy consumption. This paper proposes an optimal multi-energy portfolio for zero carbon data center buildings in the presence of proactive demand response programs. In the data center buildings, the complementarities of hydro-solar-wind hybrid renewable energy sources (RESs) are fully exploited via multi-energy conversion and storage devices, which are modeled as 100% renewable energy hubs for zero carbon multi-energy supplies. In order to exploit the hub-internal operational dispatchability and flexibility, a comprehensive energy consumption model of data center buildings is proposed to facilitate the demand response in terms of available serves, while the variable speed pumped storage (VSPS) is modeled to capture its dynamic operational characteristics. The energy‑carbon production, conversion, storage, and consumption are formulated as an energy‑carbon matrix, which are solved via a two-stage method to obtain the optimal portfolio. Case studies on southwest China data center buildings are implemented to demonstrate the effectiveness and superiority of the proposed methodology on cost-effective accommodation of RESs. Simulations results show that the system portfolio cost can be reduced by at most 17.8% with a higher operational flexibility. • A cost-effective data center building is proposed to accommodate zero carbon targets. • Hydro-solar-wind 100% renewables are formulated for multi-energy supplies. • VSPS and data center energy consumption are modeled to exploit inherent flexibility. • The energy-carbon production, conversion, storage, and consumption are optimized. [ABSTRACT FROM AUTHOR]

Based on household-level survey data collected from Qinghai Province of China, we estimated the greenhouse gas (GHG) and air pollutant emissions from spatial perspectives, including household energy consumption in pastoral, agropastoral, and agricultural zones. The findings suggest that the total annual GHG and pollutant emissions per capita in the area was 2296.32 kg per year. The highest amount of pollutants was emitted from the pastoral zones, followed by the agropastoral and agricultural zones. CO 2 is the primary GHG emitted by household energy consumption. Dung burning was the cause of the high PM 2.5 emissions in the pastoral areas, while the use of coal was the primary cause of GHG and pollutant emissions in the agropastoral and agricultural zones. • We used empirical data from rural households in Qinghai, China. • This paper indicates the reliance of local energy consumption on non-commercial energy. • We estimate greenhouse gas and pollutant emissions resulting from solid-fuel combustion. • We compare indoor pollutant emissions from pastoral, agropastoral, and agricultural zones spatially. • This paper provides policy recommendations for energy transition towards clean energy. Energy consumption in the household sector has become an important issue in China's energy consumption and an important unit of China's clean energy transformation. Currently, the potential air pollution, carbon emissions and health risks caused by energy consumption in many areas cannot be ignored, and refined and regionalized index-based research data necessary to support decision making are lacking. Based on household-level survey data collected from Qinghai Province, China, we estimated greenhouse gas (GHG) and air pollutant emissions from spatial perspectives, including household energy consumption in pastoral, agropastoral, and agricultural zones. The findings suggest that the total annual GHG and pollutant emissions per capita in the area was 2296.32 kg per year. The highest amount of pollutants was emitted from the pastoral zones, followed by the agropastoral and agricultural zones. CO 2 is the primary GHG emitted by household energy consumption. Dung burning was the cause of the high PM 2.5 emissions in the pastoral areas, while the use of coal was the primary cause of GHG and pollutant emissions in the agropastoral and agricultural zones. These findings highlight the need to integrate household energy policies with rural development to enable a complete transition towards cleaner fuels. [ABSTRACT FROM AUTHOR]

• Household indirect energy consumption is decomposed by input-output subsystem method. • Indirect consumption is 1.3 and 1.65 times of direct in 2012 and 2017 respectively. • Coal indirect consumption accounts for 50.2%, 54.6% in 2012 and 2017 respectively. • Spillover effect is the most one among the four components. • Ferrous metal smelting and rolling sector is most affected by household activities. In recent years, China's rapid economic development and steady growth of household consumption have contributed to the continuous growth of energy consumption. In addition to considering direct household energy consumption, the indirect effects of people's consumption activities on energy consumption in other productive sectors can't be ignored. According to the input-output analysis framework and consumer lifestyle analysis, this paper mainly studies the direct and indirect consumption of energy by Chinese household consumption ways and the relationship between energy structure and lifestyle. From the perspective of structural analysis, the input-output subsystem model (scale component, own internal component, feed-back component and spillover component) is used to analyze the energy supply and demand relations among 36 sectors of the national economy related to the lives of household in 2012 and 2017, revealing the change trend and transmission mechanism. This paper also focuses on the impact of household consumption ways on energy consumption of industrial sector and changing consumer lifestyles on energy saving, meanwhile it also forecasts China's future household energy consumption under four scenarios. The results show that in 2012 and 2017, total consumption of energy which is influenced by household consumption ways in China is 28461.82 PJ and 44759.96 PJ, respectively, accounting for 26.9% and 34.1% of total consumption of final energy. The indirect energy consumption is 1.3 times and 1.65 times of direct, respectively. The coal consumption accounts for the majority of indirect energy consumption. The smelting and pressing of ferrous metals is the industrial sector which is most affected by the household consumption ways. The scale component, own internal component, feed-back component and spillover component has accounted for 18.5%, 1.3%, 0.1% and 80.0%, from 17.5%, 2.0%, 0.2% and 80.3% of energy consumption in total, respectively. Under the four scenario development modes (NN, NA, LN and LA), it is predicted that the indirect energy consumption in household life in 2025 is 43740.56PJ, 34922.93PJ, 39149.37PJ and 31257.28PJ, respectively. The implementation of low-carbon consumption mode and the accelerated decline of energy intensity will help to reduce energy consumption. [ABSTRACT FROM AUTHOR]

• Clean energy consumption, haze pollution and economic growth were considered. • The interaction mechanism among three variables was explored. • The central area of Yangtze River Delta were selected. • Coal consumption has restrained clean energy development. At present, the frequent occurrence of haze in China has attracted extensive attention around the world. However, there are few researches based on simultaneous equation model to evaluate the relationship among clean energy consumption, haze pollution and economic growth. Whether the relationship among clean energy consumption, haze pollution and economic growth can be clarified correctly is the core issue to achieve the goal of both haze control and high-quality economic development. The innovation of this study is to further explore the interaction mechanism among the three variables, simultaneous equation model is used to analyze the relationship of clean energy development, haze pollution and economic growth of 27 cities in the central area of Yangtze River Delta from 2006 to 2016. The estimation results show that:(i) The development of clean energy has reduced regional haze pollution and the level of economic development significantly; (ii) During the study period of this paper, haze pollution has significantly increased the consumption of clean energy, but it has hindered the level of economic development seriously. (iii) The level of economic development has increased clean energy consumption at a 1% level of significance, while also exacerbated the degree of haze pollution. Moreover, as a core variable of this paper, coal consumption has restrained clean energy development and played a positive role in accelerating economic development and haze pollution reduction. [ABSTRACT FROM AUTHOR]

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of "power grid company - retailers - users" based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity. • Accurately identify the RE consumption of users under the unified clearing mode. • Construct a transmission mode of RPS assessment among grid, retailers, and users. • Construct a distributed training framework of multi-agent. • The research is helpful in promoting the consumption of new energy. [ABSTRACT FROM AUTHOR]

The impact of village morphology on habitats' daily spatiotemporal behavior and building energy consumption is still vague. This research aims to propose a method to reveal how and to what extent village morphology and residents' demographic structure influence farmhouses' occupancy rate and energy consumption. For this purpose, a combined time geography and building energy consumption method was proposed to disclose the relationship among residents' family roles, village morphology and household energy consumption. To explore the occupancy rate of farm-houses with different family members in different village morphology, resident types based on field research (retrospective interviews and aggregation behavior observation) were formulated. Residents with similar time-space behavior seemed as an "agent" and then a specified number of agents are combined into different families for ideal experiments. By placing different households in different villages for multi-factor cross-experiment, the occupancy rates of different households are obtained based on individual time-space behavior patterns, and then the energy consumption of each household under different scenarios is obtained by combining building energy consumption simulation. In addition, the relationship between resident's disposable personal time, local public space' quality, and the house occupancy rate was analyzed. Combined with a case study in Shanghai with 417 valid questionnaires, it can be seen that the method proposed in this paper is effective and villages with high quality public space have the potential to reduce household energy consumption from 2.17% to 38.82% for diverse families. The quantitative result indicated that the occupancy rate is mainly influenced by residents having more disposable personal time, and such space-time behavior is sensitive to village morphology. This study proposed a combined method and case evidence to systematically analyze the complex relationship between resident behavior, the village morphology, and household energy consumption, thus contributing to the sustainable plan and design of the community spatial system. [Display omitted] • Proposed systematic approach to reveal the relationship between morphology and energy. • Energy-saving effect of public space is revealed from villagers' behavior chain. • The influence of the village morphology on energy consumption is between 2.17% and 38.82%. • Alternative mode of villager's space usage in disposable personal time was proved. [ABSTRACT FROM AUTHOR]

• Sunken courtyards reduce the household energy consumption of farmers nowadays. • Policy guidance and building conditions are the main factors that affect decision-making of living modes. • Village collective and individual decisions affect the energy consumption level of the whole village system. • Vernacular architecture is the local solution of rural energy-efficient development. Vernacular architecture has been widely concerned in recent years because of its energy-efficient and environmental adaptability characteristics, and is considered as a potential method to reduce rural energy consumption and an important cultural heritage. However, under the rural modernization and urbanization, vernacular architecture is in danger of disappearing. This paper focuses on the sunken courtyard, a typical vernacular architecture that utilizes underground space, carries out field investigation and questionnaire survey in villages of Shanzhou District, China. It is found that local residents adopt a variety of spatial utilization modes for sunken courtyards, and the structural equation model is further applied to analyse the decision-making process of farmers. The result is as follows: First, the utilization of sunken courtyards still reduces the household energy consumption; Second, policy guidance (weight coefficient is 0.57) and objective building conditions (weight coefficient is 0.25) are the main factors that affect farmers' decision-making; Third, village collective and individual decisions affect the energy consumption level of the whole village system. Finally, the formulation of rural development policies should fully consider the relationship between residents, buildings and village systems, so as to form unique local solutions. This study provides insights for the development of future architectural heritage conservation and rural renewal strategies. [ABSTRACT FROM AUTHOR]

[Display omitted] The rapid development of urbanization has created high demand for central heating systems. This trend has led to an increase in energy consumption for central heating, which has made China's energy-saving transformation extremely difficult. However, the channel by which urbanization impacts and the future trends of energy consumption for central heating are still unclear. Therefore, this study employs the Logarithmic Mean Divisia Index (LMDI) method to decompose the effect of urbanization on changes in energy consumption for central heating during 2001–2019 in China. We investigate the contribution of urbanization from demographic, economic and spatial perspectives. Additionally, a scenario analysis is used to explore trends in energy consumption for central heating in different projected urbanization scenarios. The results show that urbanization has a positive impact on energy consumption for central heating, particularly in underdeveloped regions. Demographic urbanization has the strongest positive effect on energy consumption for central heating, followed by spatial urbanization and then economic urbanization. Compared with the expansion of area and economic development, population agglomeration will bring more energy consumption for central heating. The forecasting results indicate that energy consumption for central heating will reach 176–189 Mtce in 2030, which is approximately 1.4 times the current level. This work quantifies the energy consumption for central heating in the future under urbanization. The policy recommendations given at the end of the paper will provide a reference for the formulation of energy consumption for central heating. [ABSTRACT FROM AUTHOR]

• The degree of influence of residential cluster layout factors on building heating energy consumption levels in cold regions of China. • Provides an idea of residential layout optimization and design based on the energy saving objectives of residential clusters, translating quantitative indicators such as wind environment into residential layout form design problems. • Energy simulation-based residential planning and layout design method is used to quantify the relationship between residential cluster design factors and energy efficiency in Jinan, resulting in optimal design parameters for residential planning factors in Jinan. • The study of building heating energy consumption in a city in a cold region of China, with a methodology that can be used in countries or cities with similar climate characteristics. Residential heating energy consumption in China accounts for about 34% of the total building operation energy consumption in the country. The layout pattern of residential clusters is one of the most critical factors affecting building heating energy consumption, yet few scholars have studied the layout of residential clusters in a quantitative way. This paper takes Jinan, a typical city in cold region IIB of China, as an example, to quantify and analyse the residential layout parameters related to heating energy consumption: group layout, building orientation and building spacing; ECOTECT and HTB2 are used to model and simulate the energy consumption of the three types of layout residential groups selected for the study, and the relationship between residential group layout parameters and residential heating energy consumption is analysed based on multiple linear regression analysis. The relationship between residential group layout parameters and residential heating energy consumption was analysed based on multiple linear regression analysis. The study shows that, on the premise of ensuring the same building density, the group layout has the greatest influence on the building energy consumption, and the courtyard layout has lower heating energy consumption compared to the row and staggered layout; on this basis, the influence of building orientation and building spacing on heating energy consumption is discussed. The study shows that increasing the spacing between buildings to meet the daylight spacing will reduce energy consumption by 4% and that a 15° shift to the west will reduce energy consumption by 5%. This result confirms the importance of cluster layout in terms of heating energy consumption and urban energy efficiency in cities in cold regions. [ABSTRACT FROM AUTHOR]

• We estimate the energy efficiency and direct rebound effect of residential electricity consumption by using the stochastic energy demand frontier model. • The average value of efficiency is 0.491, and the average rebound effect is 48%. • We find that electricity price and household size have a negative impact on the rebound effect, while the impact of income is inverted U-shaped. • The rebound effect varies across before and after the implementation of the increasing block pricing policy, considering rural and urban residents and different regions. The rebound effect is a potential threat to energy efficiency related policies to save energy. Based on data from China family panel studies over the period 2010–2018, this paper measures the energy efficiency and direct rebound effect of residential electricity consumption by using the stochastic energy demand frontier model. The result shows that the average value of efficiency is 0.491, and the average rebound effect is 48%. It means that there is still room for improvement in China's household electricity consumption efficiency. But the expected electricity- saving after improving efficiency can only achieve 52%. Besides, we find that electricity price and household size have a negative impact on the rebound effect, while the impact of income is inverted U-shaped. Finally, the rebound effect varies between before and after the implementation of the increasing block pricing policy, considering rural and urban residents and different regions. These findings provide some policy implications for the residential electricity pricing system under the background of energy conservation and climate change. [ABSTRACT FROM AUTHOR]

This paper contributes to the large volume of literature investigating the link between awareness and pro-environmental behaviours by combining theory and empirical evidence. We first develop a simple model incorporating agents′ environmental awareness in their decision-making processes, which helps us to understand the fundamental mechanism. Using household level data taken from the 2015 China General Social Survey (CGSS), we then empirically test a number of hypotheses derived from the theoretical framework. Our results confirm that the role of awareness is important in affecting household energy consumption and pro-environmental choices. Both accessibility and affordability of using energy improves social wellbeing in terms of health status. Awareness alone does not necessarily reduce energy consumption, but subjective factors can play important roles. Moreover, household′s subjective attitude can significantly influence decisions to purchase more energy efficient products and encourage pro-environmental choices. Policy implications can be drawn from these results that government should play a more active role in raising public awareness of sustainable development. [ABSTRACT FROM AUTHOR]

China's urbanization is rapidly proceeding while bringing marked impact on the energy consumption. This paper contributes to current literature by using an improved spatial econometric model Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) to investigate the effect of urbanization on energy consumption for China's regions. The impact of urbanization is further disaggregated into direct and indirect impacts from the perspective of spatial econometrics. Results show that, if the urbanization level increases by 1.0%, energy consumption levels will correspondingly decrease by 0.089%. The spatial spillover effect on adjacent areas is positive: a 1.0% increase in one specific area's urbanization level leads to a 0.136% increase in an adjacent area's energy consumption. It is suggested that, it is essential to devote major efforts to energy conservation, in the process of improving the new-type urbanization. In particular, disaggregating China's targets for controlling energy consumption into smaller targets for different regions will contribute to controlling the growth of energy consumption. [ABSTRACT FROM AUTHOR]