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The freight transport sector is a critical sector for achieving carbon peak and carbon neutrality targets. However, there are many uncertainties regarding the e-commerce development, promotion speed of low-carbon measures, and freight transport technologies. Existing research lacks considering the multiple uncertainties on the low-carbon technological pathway for freight transport. Consequently, a bottom-up National Energy Technology-Transport (NET-Transport) model is developed based on the principle of cost minimization for optimizing the low-carbon transition pathway of the freight transport. The study comprehensively evaluates the sustainable technological pathway, energy saving and carbon emission reduction of various measures, including shifting to low-carbon transport modes, improving transport energy efficiency and promoting clean energy. Results show that the freight transport demand will reach 24.1–60.5 trillion ton-kilometers by 2060. CO 2 emission would peak at 0.8–1.0 billion tons in 2030–2041 if the breakthrough technologies are not developed on a large scale. Carbon neutrality in the freight sector is difficult to achieve by relying on the low-carbon transition of the energy system alone, with 57–555 million tons of remaining CO 2 emissions in 2060. The advanced technologies have significant effects on energy saving and emission reduction. The research, development, and application of hydrogen-fueled heavy trucks should be accelerated. • A National Energy Technology model is established for China's freight transport. • The freight demand under the influence of e-commerce development is forecasted. • The uncertain impacts of various low-carbon measures are investigated. • China's freight transport is difficult to achieve carbon neutrality in 2060. • A low-carbon development pathway is proposed for China's freight transport. [ABSTRACT FROM AUTHOR]

Concerns over supply risks of critical metals used in electric vehicle (EV) batteries are frequently underscored as impediments to the widespread development of EVs. With the progress to achieve carbon neutrality by 2060 for China, projecting the critical metals demand for EV batteries and formulating strategies, especially circular economy strategies, to mitigate the risks of demand-supply imbalance in response to potential obstacles are necessary. However, the development scale of EVs in the transport sector to achieve China's carbon neutrality is unclear, and it remains uncertain to what extent circular economy strategies might contribute to the reduction of primary raw materials extraction. Consequently, we explore the future quantity of EVs in China required to achieve carbon neutrality and quantify the primary supply security levels of critical metals with the effort of battery cascade utilization, technology substitutions, recycling efficiency improvement, and novel business models, by integrating dynamic material flow analysis and national energy technology model. This study reveals that although 18%–30% of lithium and 20%–41% of cobalt, nickel, and manganese can be supplied to EVs through the reuse and recycling of end-of-life batteries, sustainable circular economy strategies alone are insufficient to obviate critical metals shortages for China's EV development. However, the supplementary capacity offered by second-life EV batteries, which refers to the use of batteries after they have reached the end of their first intended life, may prove adequate for China's prospective novel energy storage applications. The cumulative primary demand for lithium, cobalt, and nickel from 2021 to 2060 would reach 5–7 times, 23–114 times, and 4–19 times the corresponding mineral reserves in China. Substantial reduction of metals supply risks apart from lithium can be achieved by the cobalt-free battery technology developments combined with efficient recycling systems, where secondary supply can satisfy the demand as early as 2054. [Display omitted] • Circular economy strategies alone are insufficient to obviate metals shortages. • China's electric vehicle development might face shortage risks of Li, Co, and Ni. • 1/5–2/5 of critical metals can be supplied through reuse and recycling. • Cobalt-free battery technology should be combined with efficient recycling systems. [ABSTRACT FROM AUTHOR]

China has proposed the Renewable Portfolio Standard (RPS) policy to advance the stable development of renewable energy. The RPS requires each province to achieve a stated minimum share of renewable energy power in the total provincial power generation. However, there is an obvious mismatch between the actual capability of generating renewable power and the assigned responsibility for the share of renewable energy power based on the RPS in some provinces. Therefore, this study aims to optimize the renewable power dispatching strategy across provinces for satisfying the RPS requirements in China and to assess the corresponding pressure for each province. A renewable energy power dispatching model is developed, and an economically feasible strategy for dispatching renewable energy power in Chinese provinces in 2020–2022 was obtained. The results indicate that it is necessary to dispatch 395.2 and 140.4 TWh of hydropower and non-hydropower nationwide, respectively, in 2022 to fulfill the RPS target when the COVID-19 is effectively controlled worldwide. If COVID-19 cannot be effectively controlled, 376.6 and 127.8 TWh of hydropower and non-hydropower must be dispatched nationwide to fill the gap. Beijing, Tianjin, Shanghai, and Zhejiang are faced with a relatively high pressure under the RPS target. Finally, a path for each province to achieve its RPS target is proposed. [ABSTRACT FROM AUTHOR]

Abstract Time is an absolutely scarce resource for humans. Considering the fact that people consume goods and services to fulfill their daily activities in 24 hours a day, a new perspective based on time use might be more intuitive for understanding why and how people allocate their time and consumption to different activities, and what the energy demand and emissions will be in the future when time-use patterns shift. Accordingly, the policy implications for reducing carbon dioxide emissions could be extended to more fundamental dimensions related to people's activity structures, activity duration, and consumption patterns of activities. This study attempts to transform the energy and emissions problems into a finite time-use problem, by investigating the change of energy consumption and emissions building on a time-use-based approach. To that end, we take China as the empirical context, and investigate potential time-use patterns for Chinese residents. Scenario analyses assuming that Chinese residents may shift to time-use patterns in developed countries are further conducted to give a general picture of future carbon dioxide emissions and meanwhile to explore a low-carbon time-use pattern for Chinese residents. We find that, a potential Chinese residents' low-emissions route may involve shifting to the activity patterns of American residents and the hybrid consumption patterns of activities composed of patterns found in Finland, Japan and UK. And six main time-use activities, including Travel , Personal care , Repairs, Gardening and Pet care , Sleep and Rest , Eating and Drinking , and Recreation and Leisure , will make a greater contribution to increasing daily emissions from residents if they shift their time-use patterns in the future. Highlights • A time-use based approach to carbon emissions accounting is proposed. • Impact of change in non-work time on carbon emissions are investigated. • Carbon intensities of various time-use activities are estimated for 7 countries. • Daily carbon emissions per capita are evaluated with changes in time-use patterns. • Suitable time-use pattern for achieving a low-carbon society in China is explored. [ABSTRACT FROM AUTHOR]

Abstract China's power sector has become the largest contributor to China's carbon emissions because of its coal-dominated power structure. Replacing fossil fuels with renewable energy is an effective way to reduce carbon emissions and, therefore, a series of targets for renewable electricity generation have been put forward in national plans. However, how these targets will be reached is unclear. This paper uses a Long-range Energy Alternative Planning system (LEAP) model to explore the optimum development path of China's power sector from 2015 to 2050, taking into consideration the impacts of the renewable energy targets. Three scenarios are designed to examine the costs and benefits of developing renewable energy and improving the technologies for renewable power generation, comprising a base scenario, a renewable energy policy scenario and a technological progress scenario. The results show that the power generation cost would increase by at least 2.31 trillion RMB and that CO 2 emissions would be reduced by 35.8 billion tonnes during 2015–2050 if power generation follows current planning. Furthermore, every 1% increase in the capacity factors of renewable electricity would on average result in the cumulative CO 2 emissions decreased by 979 million tonnes and average CO 2 abatement cost decreased by 5.56 RMB/tCO 2 during 2015–2050. Based on this study, several policy implications are proposed for the development of power sector in China. Firstly, government may reconsider the current planning for gas-fired power and nuclear power to reach low-carbon electricity generation. Secondly, adjusting the carbon price can offset the additional cost of renewable electricity generation. Thirdly, promoting advanced technologies to match renewable electricity generation can obtain greater economic and environmental benefits. Finally, from the perspective of development potential, reducing the costs of solar power would be the emphasis at this stage. Highlights • Effects of renewable energy development plan in power sector are evaluated for China. • The optimal development path with minimum cost for the power sector are given. • National plans for renewable electricity can reduce 35.8 billion tonnes of CO 2 until 2050. • Average CO 2 abatement cost for promoting renewable power is 64.53 RMB/tCO 2 during 2015–2050. • Every 1% increase of the capacity factors of renewable power would decrease the average CO 2 abatement cost by 5.56 RMB. [ABSTRACT FROM AUTHOR]

Highlights • Spatial heterogeneous impacts of households on CO 2 emissions are analyzed. • Clarify the responsibility of CO 2 emissions reduction in Chinese provinces. • Unequal impacts on CO 2 emissions among different income households are identified. • The Chinese provinces demanding high-income household specific policies are listed. • Key sectors for shrinking unequal impacts of households on emissions are identified. Abstract As unequal carbon dioxide emissions exist among households with diverse consumption patterns resulting from different income and spatial contexts, the same carbon emission reduction policies for households will go against the principle of social equality. Though a lot of attention has been paid to estimating the emissions from different income households in previous literature, the full impacts of households on carbon emissions of production sectors through changing income are not well captured. Therefore, for better supporting the fair but different carbon emission reduction policy design for households and provinces, this paper investigates the unequal impacts of households on total emissions and sectoral emissions by specifically taking into account the heterogeneity among different income households in different provinces under the empirical context of China. A combination of semi-closed input-output model and hypothetical extraction method is used here to quantify the unique effect of each income class of households. We find five aspects of seriously unequal impacts of different income households among Chinese provinces: (1) the more responsibility for reducing carbon emissions should be allocated to Shandong, Hebei, Jiangsu, Inner Mongolia, Henan, Guangdong, Shanxi and Liaoning; (2) more unequal impacts on total provincial emissions between urban and rural households in Beijing, Tianjin, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Shanghai, Zhejiang, Guangdong and Chongqing; (3) unequal impacts of urban (or rural) households on total provincial emissions exist among provinces; (4) unequal impacts of households on total provincial emissions exist among income classes and among provinces; (5) unequal impacts of urban households on emissions of sectors exist among provinces. These pictures of the inequality can provide more evidence for making fair but distinguishing carbon emission reduction policies for different income households across Chinese provinces. [ABSTRACT FROM AUTHOR]

The iron and steel industry plays an important role in mitigating global climate change. As the largest steel producer and consumer, China bears the primary responsibility for energy savings and CO 2 emission reduction in the iron and steel industry. In this study, taking China as the empirical context, we analyze the effectiveness of the following four strategies on the potential of energy savings and emission reduction: phasing out backward production capacity in accordance with the current major policies, adjusting the production structure to increase electric arc furnace steelmaking, promoting low-carbon technologies, and switching to clean fuels. Under the principle of cost minimization, the mitigation potential of different strategies until 2030 and the technological development paths for reducing energy and CO 2 emissions in China’s iron and steel industry are identified via an established National Energy Technology model. The results show that promoting low-carbon technologies is the most effective strategy for energy savings and emission reduction alongside cost minimization. Compared with existing policies, these strategies could lead to a cumulative reduction of 818.3 MtCO 2 (4.1%) during the period 2015–2030. Therefore, policy makers should provide financial or administrative support to promote the development of specific production and low-carbon technologies such as non-blast furnace iron-making and endless strip production. [ABSTRACT FROM AUTHOR]

As China gradually completes the process of industrialization, its industrial energy consumption growth is now slowing and even decreasing. Meanwhile, household energy consumption in the residential sector has seen steady growth. This paper aims to explore the mechanisms of factors affecting urban household energy-saving behavior including the habitual energy-saving behaviors and purchasing energy-saving behaviors. A structural equation model is built to analyze the influencing routes and effects of individual objective and subjective characteristic factors, external influencing factors, and energy-saving intentions on shaping energy-saving behaviors. The empirical results drawing on the survey data collected in Shandong province show that external influencing factors that have two kinds of mediating effects through energy-saving intentions and individual subjective characteristic factors are the most crucial factors to energy-saving behaviors. Values included in individual subjective factors and quality of energy-saving products included in external influencing factors have greatest effects on energy-saving behaviors. [ABSTRACT FROM AUTHOR]

Urban transportation in China is undergoing a revolution due to ride-sourcing. The strong growth in ride-sourcing travel requires the government and the industry to adopt strategies for reducing environmental impact. Here, we address a key gap in knowledge on the emerging ride-sourcing travel model by designing a roadmap for realizing low-emission ride-sourcing drawing from an analysis of raw big trip data for Beijing. We found that adopting the most effective low-emission strategies requires joint efforts involving governance and management, enterprise operations, and consumer behavior change. With respect to issues of feasibility and effectiveness, the enterprise operation strategy, involving polices that shorten the pick-up time and increase the vehicle occupancy, is the best option, offering approximately 44% CO2 and NOx emission reductions compared with the current situation. Promoting ride-sourcing usage among car users or potential car users could help reduce emissions attributing to less cars being manufactured (26% CO2 and 24% NOx) but with uncertainty. To achieve low-emission ride-sourcing travel, governments, enterprises, and consumers must collaborate closely and define clear roles, responsibilities, and relationships. [ABSTRACT FROM AUTHOR]

From a behavioral viewpoint, people choose where to live based on various factors, including their current situations, past experience, and plans for the future. Some aspects of residential preference might be constant over time, inherited from the initial stage of life, and other parts might be responses to residential biography or other biographical domains like household structure, employment/education, and travel. Capturing these intertemporal dependences needs a life course analysis of residential location choices. However, a serious methodological gap exists between the perceived importance of dynamic life course analyses and quantitative modeling approaches. This study developed a dynamic choice model with cross-sectional and longitudinal heterogeneities as well as discounted utility (called the DU-DCLH model) to describe the decision-making process for residential relocation by incorporating various intertemporal dependences over the life course. Model parameters were estimated using data collected from a life history survey conducted in Japan in 2010. The estimation results firstly confirm the effectiveness of the DU-DCLH model for portraying the dynamics of residential mobility over a life course. Next, it was found that previous experiences dominate decisions on residential location choice and can explain more than 75% of the total variations in choice. It was also revealed that as the mobility age increases, the influence of the past on their choices increases continuously. In contrast, the influence of the present situation is small and almost negligible. Furthermore, the study empirically confirmed not only the influence of time-constant and time-varying preference for residential neighborhoods but also the specific influence of household biography, employment/education biography, and travel biography. This study enriches the existing research by providing a systematic modeling framework incorporating broader behavioral mechanisms for residential location choice over the life course. [ABSTRACT FROM AUTHOR]

Sustained increase in Chinese household income has exerted positive impact on the consumption of goods and services. This paper aims to analyze the unequal impacts of household consumption across different income households on the whole CO 2 emissions, by utilizing a semi-closed input-output model and hypothetical extraction method. The semi-closed input-output model moves household consumption activities into the intermediate use along with dividing urban and rural households to several groups by their income levels, and the hypothetical extraction method (HEM) is used to estimate the reductions of CO 2 emissions relative to total emissions after extracting the consumption of each household group. The results show that: (1) the impact on CO 2 emissions generated by urban households’ consumption are 1.8 times as much as that of rural ones; (2) excluding consumption of higher-income households from the economy would cause greater CO 2 emission reductions than lower ones. Specifically, urban highest-income households have the most relative reductions of CO 2 emissions, which are −12.2% in 2007 and -13.8% in 2012, while for rural highest-income households are −5.1% in 2007 and -5.1% in 2012. And urban and rural highest-income households are respectively 3.8 and 1.8 times on the relative reductions of the lowest-income ones; (3) the relative reductions of household CO 2 emissions from food sectors is the most, while from residence sectors is the least. Based on the above conclusions, this paper puts forward consumption-based policy implications. [ABSTRACT FROM AUTHOR]

Emerging ridesharing travel could be an effective way in China to reduce travel demand by cars, which can further seek to shift personal transportation choices from an owned asset to a service used on demand and lessen the traffic jam and emissions. Drawing on the raw observed ridesharing trip data provided by DiDi Chuxing company, this study evaluated the direct environmental benefits of ridesharing resulted from the travel mode shift and the indirect environmental benefits resulted from the attitude change towards car purchase behavior. The megacity Beijing is taken as the empirical context given its more serious situation of traffic congestion and difficulties for car purchase. Estimation results show that direct annual energy savings made by ridesharing are approximately 26.6 thousand tce, and annual emission reductions of CO 2 and NOx are approximately 46.2 thousand tons and 253.7 tons, respectively. Besides, using ridesharing service will lead to substantial energy savings and emission reductions from the long-term perspective attributing to the weakening willingness on purchasing new cars. Promoting EVs among ridesharing vehicles and switching to clean electricity generation as well as improving vehicle efficiency can further enhance the environmental benefits of ridesharing, with maximum effects amounting to 67% of energy savings and 57% of CO 2 emission reductions compared to 2016 level of the fuel-related energy consumption and emissions made by ridesharing. [ABSTRACT FROM AUTHOR]

• Develop a cost-optimal model towards carbon neutrality in the iron and steel industry. • Explore the cost-effective carbon neutral pathway in the iron and steel industry. • Promoting energy-saving technologies is the most effective strategy to reduce CO 2. • Stable scrap supply would assist carbon neutrality in the iron and steel industry. The iron and steel industry is a critical sector for achieving China's carbon neutrality goal. However, existing studies lack considering the multiple constraints including limited resources, technology diffusion and carbon emissions reduction on design of carbon neutral pathway for iron and steel industry. A broader analysis that can integrate resources-technologies-emissions in to a united framework is necessary. To further explore the feasible paths and challenges faced by the iron and steel industry, this study developed the C3IAM/NET-IS (China's Climate Change Integrated Assessment Model/National Energy Technology-Iron and Steel) model to select the optimal technology portfolios. By incorporating 11 measures such as technological innovation, structure adjustment of raw material, clean energy, etc., the integrated impact on CO 2 emissions, energy consumption, raw materials, and costs is analyzed, while the carbon neutral pathway for the iron and steel industry is further investigated. The results show that CO 2 emissions of China's iron and steel industry would peak at about 1514.14–1530.86 million tonnes before 2023. And there would be more than 72.78 million tonnes of CO 2 in 2060, requiring carbon sinks to absorb to achieve carbon neutrality. During 2020–2060, the most effective measure would be the promotion of energy-saving technologies, which would contribute about 22.07% of CO 2 emission reduction. Compared to the EAF (Electric Arc Furnace) with 50% scrap, promoting EAF with 100% scrap would result in cumulative total costs savings of about 4361.04 billion CNY while consuming 15.14 billion tonnes of scrap. To coordinate the goals of carbon neutrality and raw material security, it is necessary to support domestic iron ore enterprises through tax relief and to accelerate the large-scale construction of the scrap recycling industry. [ABSTRACT FROM AUTHOR]

This study explores the direct rebound effect, which indicates the degree of increase in travel demand caused by the increasing vehicle efficiency in the private passenger transport sector. Different from the usual effect, here the direct rebound effect is not assumed to be the same for the entire population. To determine when rebound occurs and who is suffering, two types of triggers, which may lead to different rebound effects among the population, are investigated: vehicle efficiency and travel demand. The quantile regression method is adopted to measure the rebound effect and differentiate it with respect to vehicle efficiency and travel demand. Considering that the rebound effect might have diverse performance in different cities, a comparative analysis between Beijing and Tokyo is conducted. Drawing on the data collected in a household energy consumption survey in Beijing and Tokyo in 2009, the models are estimated and the results reveal significant heterogeneity of the direct rebound effect both in Beijing and Tokyo, but with a much more complicated form in Beijing. For travelers in Beijing, rebound only occurs to those people whose cars are less efficient than 15–18 km/L, and the magnitude of the rebound effect is between 31.8% and 60.2%, varying across travelers with different travel demands. In comparison, in Tokyo, only travelers with low and medium kilometers traveled have the rebound effect, and the effect is inversely related to their travel demand, ranging between 17.1% and 92.3%. The above-identified inter-city and intra-city difference in the rebound effect could contribute to the population and a spatially specific policy scheme in practice. [ABSTRACT FROM AUTHOR]

To reduce the continuously increasing energy consumption in the household sector, including residential and private transport sectors, it is important to design a proper policy scheme to regulate household energy demand. However, determining how to evaluate the collective effect of multiple countermeasures in one policy scheme on household energy related behavior is very challenging; furthermore, the potential interactions between policies due to the timing effect cannot be overlooked. Under these concerns, this study provides a quantitative methodology by developing a DAEDMS (dynamic active energy demand management system) that can evaluate the overall effects of urban planning, soft policies for improving household/individual awareness, technology-improvement/rebate policies, market end-use diffusion control, and social-interaction oriented policies. The timing effect is directly incorporated by allowing the free setting of the execution period for each policy. Building on this demand management system, the quantified policy schemes and the pathways that can reach the target of energy conservation become straightforward, providing helpful support for policy planning. Besides, the variant effectiveness of policy schemes due to different policy timings admonishes the policy makers to realize that the current fragmented regime of policy making between different departments is undesirable for capturing the genuine effect of all of the policies. [ABSTRACT FROM AUTHOR]

Household decisions on the energy consumption behavior are with regard to the situations that multiple end-uses (e.g., domestic appliances and vehicles) are simultaneously hold and consumed. To deal with this issue, the multiple discrete–continuous models are the best choices from the behavioral perspective. This study compared two types of utility theory-based multiple discrete–continuous models, which are widely applied in the literature: multiple discrete–continuous extreme value (MDCEV) model and the improved resource allocation model based on the multi-linear function (RAM-MLF). A household energy consumption survey was carried out in Beijing in 2010, and the comparative analysis on the performance of these two models is carried out based on the survey data. Results show that the overall performance of RAM-MLF is slightly superior to the MDCEV model due to the incorporation of the inter-end-use interaction and the relative importance of end uses. Moreover, the utility structure by using the satiation parameters to represent the diminishing marginal utility with the increasing consumption shows better fitness than the structure only using the logarithmic function. These findings can be contributed to understand the household energy consumption behavior, while suggest the potential improvement of the model structure, which is mainly focused on the utility form and the decision making mechanism. [ABSTRACT FROM AUTHOR]

Smart home, is expected to bring great changes to people's lifestyles. By shifting the timing of residents' electricity consumption, smart home can improve the flexibility of the power load, and provide significant potential for power demand responses. These responses can substantially mitigate peak-to-valley power demand gaps and household electricity costs. However, the extent of the likely impacts from smart home participating in power demand response remains unknown, and very limited research has been conducted thereon. Therefore, this study attempts to explore the potential changes in peak-to-valley electricity consumption and electricity costs owing to smart home, by developing a multi-objective smart home integrated management model with the consideration of appliances and household electricity consumption behavioral heterogeneity. The survey data collected in China was employed in the empirical analysis. Results show that smart home participating in power demand response can reduce peak load by 29.3%–49.3%, which is up to 149 GW, and the peak-to-valley difference could be decreased by 37.5%–78.2%. However, significant variance exists for the smart home impacts among households with different structures and individual occupations. Teachers, freelancers, and homeworkers contribute more to this reduction. In addition, the peak-to-valley difference after introducing smart home would shrink from -80.7%–-68.5% to -29.2%–-23.9% for areas with the time-of-use price policy, which performs better than the areas without time-of-use price policy. Regarding the economic benefits, smart home participating the demand response could reduce the investments in the power supply and power grid by 1.13–1.19 trillion RMB in China. • The impacts of smart home participating in power demand response is evaluated. • A smart home integrated management model is established for power demand response. • The heterogeneous characteristics of different in-home devices and behaviors are considered. • Smart home optimization can reduce peak load by 29.3%–49.3%. • Smart home optimization can reduce investment by up to 1.2 trillion RMB. [ABSTRACT FROM AUTHOR]

Highlights: [•] A life history survey of Japanese’s four types of biographies is implemented. [•] Residence, household structure, job/education and car ownership are targeted. [•] An exhaustive CHAID analysis is done to capture biographical interdependences. [•] Both intra-domain and inter-domain biographical interdependences are observed. [•] Both short- and long-term state dependence and future expectations are identified. [ABSTRACT FROM AUTHOR]

Highlights: [•] Direct and indirect rebound effects for private vehicle in Japan are investigated. [•] SP-off-RP method is used to identify the existence and distribution of rebounds. [•] 34% of respondents have the reallocation choices which cause rebound effect. [•] Rebound effects from vehicles are more possible to occur in domestic sector. [ABSTRACT FROM AUTHOR]

The Paris Agreement calls for countries to pursue efforts to limit global-mean temperature rise to 2 °C compared to the pre-industrial level. To achieve this, it is essential to accelerate the low-carbon transition of energy system. China is the largest carbon emitter and plays a decisive role in mitigating global climate change. The transition pathways for China to contribute to meeting the global 2 °C target, however, have not been extensively explored. Here we develop a bottom-up national energy technology model (C3IAM/NET), a linear optimization model, to reveal the energy consumption, carbon emissions and technology pathway at the national and sectoral levels in line with the 2 °C climate target. Results show that China's carbon emissions need to peak at the year 2023 and reduce to 3.56 GtCO 2 by mid-century. During the 2020–2050 planning horizon, the remaining carbon budget is estimated to be controlled within 234 GtCO 2 , with a cumulative emission reduction of 165.3 GtCO 2 , of which the power sector bearing the largest share of responsibility, followed by the industry, transportation and building sectors. We project that China's primary energy consumption needs to peak before 2040 and the proportion of non-fossil energy in energy structure needs to reach 76% by 2050, and about 88.4% of electricity production comes from renewables and nuclear energy. [Display omitted] • The economically low-carbon transition pathway of China's energy system is discovered. • The optimal carbon emissions pathway at national and industrial levels is analyzed. • China's CO 2 emissions need to peak at the year 2023 to achieve 2 °C target. • The power sector bearing the largest share of CO 2 emission reduction responsibility. • The proportion of non-fossil energy in total energy needs to reach 76% by 2050. [ABSTRACT FROM AUTHOR]

Promoting electric vehicles (EVs) is an important measure to ensure energy security, improve air quality, and mitigate global climate change. However, the emission reduction impacts of EVs in China have been widely debated and the conclusions of existing studies are still controversial. In this study, we adopted the life cycle assessment (LCA) method to evaluate the carbon dioxide (CO 2) and air pollutant emissions from the stage of vehicle production, vehicle use and vehicle end-of-life. We further compared the emissions of three types of passenger vehicles in China, including internal combustion engine vehicle (ICEV), plug-in hybrid electric vehicle (PHEV), and battery electric vehicle (BEV). Compared with ICEV, BEV and PHEV were found to reduce the emissions of CO 2 , VOCs, and NO X , but increase the emissions of PM 2.5 and SO 2. These differences were primarily caused by EV's high fuel efficiency and high fuel consumption of ICEV. Additional findings indicate that the emissions of PM 2.5 and SO 2 of BEV were 2.6 and 2.1 times that of ICEV, respectively; and the emissions of PM 2.5 and SO 2 of PHEV were 1.8 and 1.5 times that of ICEV, respectively. Moreover, we found the emissions of PM 2.5 and SO 2 of EV will be higher than that of ICEV in high renewable energy scenario with higher biomass share if keeping the emission factor of electricity constant. [ABSTRACT FROM AUTHOR]

Energy is essentially consumed to support residents' productive and consumptive activities arranged in their timeline. Hence, analyzing residential energy consumption from the perspective of how people use their time for participating different activities would provide more underlying insights. However, the relationship between time-use behavior and energy consumption has not been comprehensively and accurately quantified. Here, we go beyond pervious literature to investigate the causal effect from the initial generation of activity to the final energy consumption and explore the potential energy changes in the residential sector by shedding light on residents' time-use behavior. To fulfill this research, we improve the time-use survey framework used worldwide by including the equipment dimension. The results show that the average residential energy consumption in a Chinese household was approximately 1570.5 kgce in 2015, among which cooking consumed most of the energy. Through promoting energy-efficient equipment and eliminating the equipment usage during non-primary activities would lead to 3.5–13.2% energy reductions; however, the increasing popularity of online activities and services (E -life) might increase the residential energy consumption by approximately 18.1% even after avoiding the energy consumption of related travel. • Investigate the causal effect of time-use behavior on residential energy consumption. • Explore the potential energy changes in the residential sector from the view of time use. • Average residential energy consumption in a Chinese household was 1570.5 kgce. • Energy-intensive activities, time periods, groups and equipment are identified. • E -life is likely to increase the residential energy consumption by 18.1% in China. [ABSTRACT FROM AUTHOR]

Blood pressure variability (BPV) is significantly associated with cardiovascular diseases (CVD) and mortality in hemodialysis patients. However, the relationship between blood pressure and CVD in hemodialysis patients is complex and affected by many factors. The present study aimed to assess the association of long‐term predialysis BPV with all‐cause mortality and major adverse cardiovascular events (MACE). One thousand seven hundred twenty‐seven patients receiving maintenance hemodialysis were recruited in nine hemodialysis centers. Predialysis BPV was assessed over 1‐year intervals. Outcomes included all‐cause mortality and MACE during follow‐up periods. The mean age of the final cohort was 59 years, of which 57% were males. Greater predialysis systolic BPV was associated with an increased risk of all‐cause mortality (adjusted hazard ratio, 1.101; 95% confidence intervals 1.064–1.140) and MACE (adjusted hazard ratio, 1.091; 95% confidence intervals 1.059–1.125). Results were similar when systolic BPV was stratified by baseline systolic blood pressure. In conclusion, greater predialysis BPV among hemodialysis patients was associated with all‐cause mortality and MACE. Strategies to reduce blood pressure variability might be beneficial for hemodialysis patients. [ABSTRACT FROM AUTHOR]

Ridesharing is becoming popular in many cities in China where transportation alternatives are easily accessible. Individuals typically access services by smartphone app developed by ridesharing company to join a trip offered by other private vehicle's drivers who share same or geographically close destination. However, there are some internal differences within this region indicating the service heterogeneity of ridesharing. In order to discover this regional heterogeneity, this paper chooses Beijing–Tianjin–Hebei (BTH) region as research target and uses BTH regional ridesharing data provided by DiDi Chuxing Company. Then, this paper conducts an in-depth study by summarizing the travel pattern characteristics and evaluating the environmental impacts that result from individuals participating in ridesharing services. Lifecycle analysis of fuel and environmental input–output are applied to estimate the direct and indirect environmental impact separately. The results reveal heterogeneous spatial heterogeneous of ridesharing, including travel pattern and environmental influence caused by service demand and supply, which results from the unbalance of regional development and infrastructure construction condition of the transportation system, and other travel behavior differences. [ABSTRACT FROM AUTHOR]

App-based ride-hailing is a newly emergent mode of travel that is expected to influence passengers' travel behavior significantly. In this study, we define app-based ride-hailing services to include hailing of taxis through smartphone apps and sharing of private vehicles (car sharing is not included). This paper is one of the first quantitative studies to examine how app-based ride hailing would impact passengers' choice of travel mode and change car-purchasing behaviors. China is taken as the empirical context, and the data are from a large-scale app-based survey conducted via the largest app-based ride-hailing platform in the world. Drawing on these rich survey data, the investigation covers both the short-term travel mode choices and long-term car-purchasing behaviors of app-based ride-hailing users. The research findings are helpful in understanding changes in urban residents' travel behaviors under in context of app-based ride hailing, and provide valuable in-depth insights for both governments and app-based ride-hailing service providers (i.e., enterprises) for the management and regulation of ride hailing. [ABSTRACT FROM AUTHOR]

The low-carbon transition of power industry plays a vital role in China's energy system revolution. Both policy support and cost reductions have greatly driven the development of renewable energy technologies, especially wind and solar power generation technologies. Considering the cost uncertainty of renewables, we developed a National Energy Technology-Power model to assess the possible low-carbon transition pathways for six regional power industries using four renewable energy cost change scenarios. Resource endowments and technology developments trends were also considered to achieve an effective and coordinated utilization of various resources. The results show that declining renewable energy costs have a great impact on the spatial and temporal development of power generation technologies, and on the interregional clean power transmission. If the investment costs of renewable energy technologies continue to decline at a high speed and the renewables could be dramatically developed, the CO 2 emissions of China's power industry is expected to peak at 3.12 GtCO 2 in 2026. Accordingly, the capacity share of renewable energy technologies in regional power industries would exceed 50% except in East China, and the total installed coal-fired technology capacity would fall to 760.2 GW in 2050. In addition, to promote the optimal allocation of resources, the total amounts of interregional clean power transmission are suggested to be 416 TWh in 2035 and 587 TWh in 2050, i.e., 4.9% and 5.5% of the total amount of power generation, respectively. 106 TWh of wind power is expected to be exported from Northwest to Center and East regions in 2050; and 112 TWh of solar power is suggested to be exported from North to Center, East and South regions. The Northwest region is the largest exporter of clean power while the East region is the main importer. These conclusions could support the regional plan of power transmission network. • Explore the impacts of cost uncertainty of renewables on China's power industry. • Develop a NET-Power model to combine power supply and transmission optimization. • Propose technological pathways for regional power industries with endowments. • The CO 2 emissions of China's power industry are likely to peak at 2026. • The cost decline of renewables will affect interregional clean power transmission. [ABSTRACT FROM AUTHOR]

Background: Clear cell renal cell carcinoma (ccRCC), as the commonest type among renal cell cancers, is featured with easy relapse and metastasis. Despite mounting achievements on its treatment and diagnosis, the identification of new biomarkers remains urgent. Purposes: Present study aimed to explore the role of microRNA-4429 (miR-4429) in ccRCC. Methods: The expression of miR-4429 and cyclin-dependent kinase 6 (CDK6) was evaluated by real-time polymerase chain reaction and Western blot. Cell proliferation, migration and invasion was evaluated by MTT and transwell assays. The interaction between miR-4429 and CDK6 was assessed by luciferase reporter assay. Prognostic significance of miR-4429 was evaluated by Kaplan-Meier analysis. Correlation between miR-4429 and CDK6 was determined by Spearman's correlation analysis. Results: Firstly, the downregulation of miR-4429 and upregulation of CDK6 in ccRCC tissues and cells were uncovered by quantitative real-time polymerase chain reaction. The prognostic significance of miR-4429 in ccRCC patients was proved by Kaplan-Meier analysis. Gain- and loss-of-function assays validated the suppressive effect of miR-4429 on cell proliferation, migration, invasion, as well as epithelial-mesenchymal transition (EMT) progression. The interaction between miR-4429 and CDK6 was predicted by bioinformatics tool and confirmed by luciferase reporter assay. And the negative expression correlation between miR-4429 and CDK6 was verified by Spearman's correlation analysis. Rescue assays confirmed the role of miR-4429/CDK6 in proliferation, metastasis and EMT progression in ccRCC. Conclusions: Present study revealed that miR-4429 suppressed ccRCC tumor progression and EMT by targeting CDK6. [ABSTRACT FROM AUTHOR]

Purpose: To explore the association between circulating mononuclear cell mitochondrial DNA copy number and the prognosis of sepsis patients based on the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3 definition). Methods: A total of 200 adult patients who had recently devoloped sepsis were prospectively recruited as the study cohort. Demographic and clinical data were recorded along with a 28-day outcome. Mononuclear cell mtDNA copy number was assessed by quantitative PCR. Results: The 28-day outcome of sepsis patients was significantly associated with circulating mononuclear cell mtDNA copy number. The median mononuclear cell relative mtDNA copy number of survivors was significantly higher than that of nonsurvivors (406.68, range 196.65–625.35 vs. 320.57, range 175.98–437.33, p = 0.001). The Cox proportional hazard survival model analysis indicated that mononuclear cell relative mtDNA copy number was significantly negative associated with the 28-day outcome. For every additional unit of mononuclear cell mtDNA relative copy number, the risk of death falls by 0.1% (HR = 0.999, 95% CI = 0.998 to 1.000, p = 0.017). Conclusions: Our data indicate first that circulating mononuclear cellular mtDNA copy number might be helpful for outcome predictions in sepsis patients, and second that lower mtDNA copy number implied poor prognosis. [ABSTRACT FROM AUTHOR]

Cement production is the main source of industrial process-related CO 2 emissions, taking up approximately half of total industrial process-related CO 2 emissions. However, limited research has investigated the process-related CO 2 emissions from global cement production, in particular, has not taken into account the impacts of dynamic socio-economic development context. This study aims to explore the trajectory of industrial process-related CO 2 emissions in the cement industry under different Shared Socioeconomic Pathways (SSPs), to provide more evidence for the existing climate change integrated assessment analysis. By investigating the relationship between per capita GDP and per capita cement production process-related CO 2 emissions drawing on the historical data during 1950–2014 in 31 developed countries, the cement production process-related CO 2 emissions from 175 countries in 12 regions in the world during 2015–2100 under five SSP scenarios are given here. The results show that the largest amount of global cumulative cement process-related CO 2 emissions would be 45.45 billion tons under SSP3 scenario. The countries that contribute the most to the global cumulative cement production process-related CO 2 emissions from 2015 to 2100 are India, China, Nigeria, United States of America and Pakistan. [ABSTRACT FROM AUTHOR]

• Develop an hourly-resolution, multi-region model with total system cost optimized. • Energy storage technology can meet 85.8%-by-2050 renewable energy penetration. • UHVDC transmission technology is the most economical way for RES integration. • Optimal combination of UHVDC grid and ES can achieve 74.2% renewables penetration. • The cost-optimal operation strategy varies among six regions in planning period. High renewable energy penetration is an effective way to decarbonize the power system. However, many studies focus on the economics of integrating renewables at the generation-side rather than system-wide. This paper aims to explore the cost-optimal operation strategies of a renewable-dominant power system. Considering both cost reduction potential of energy storage technology and regional investment cost variance of ultra-high voltage direct current grids, an hourly-resolution, multi-region model with total system costs minimized is proposed. Moreover, energy storage-based, ultra-high voltage direct current-based, and mixed scenarios are taken into consideration to investigate the economics of high renewables penetration. The results show that energy storage technology can achieve maximum penetration of renewable energy at 85.8% while the total system cost is 11.8% higher than that of ultra-high voltage direct current transmission technology. Although ultra-high voltage direct current grid is the most economical option to integrate renewables, the penetration is 13 percentage points lower than that of energy storage technology. The combination of energy storage technology and ultra-high voltage direct current grid can achieve 74.2% renewable energy penetration, saving 9.4% of total system costs compared to that of energy storage technology only. The cost-optimal option for East and South China is to promote both energy storage and ultra-high voltage direct current technologies. Energy storage technology is preferred among North, Northwest and Northeast China, while ultra-high voltage direct current grid is the optimal option for Center China. [ABSTRACT FROM AUTHOR]

The large-scale application of hydrogen steelmaking technology is expected to substantially accelerate the decarbonization process of the iron and steel industry. However, hydrogen steelmaking projects are still in the experimental or demonstration stage, and scientific investment decision-making methods are urgently needed to support the large-scale development of the technology. When assessing the investment value, existing studies usually only consider the intrinsic project value under a specific pathway, while ignoring the option value under realistic multiple uncertainties in terms of technology, market, and policy, leading to an underestimation of the investment value. To address this issue, this study constructs a real options model to explore the optimal investment timing and revenue of the hydrogen steelmaking project, by taking into account multi-dimensional uncertainties stemming from price fluctuations in the steel market, the development of the carbon market, and technological advances. Additionally, the impacts of various subsidy policies on the investment strategy are also investigated. Least Squares Monte Carlo method is applied to overcome computational challenges posed by dynamic programming under multi-dimensional uncertainties. The results show that: (i) Investment is not recommended based on current crude steel price and hydrogen price. (ii) When the annual reduction rate of hydrogen price reaches 5%, the optimal investment timing would advance to 2036. (iii) On this basis, with the introduction of a 20% green hydrogen subsidy policy, the optimal investment timing would be further brought forward to 2033. The implementation of tax incentives would significantly increase the investment value. The investment value would surge from 170 million CNY to 262 million CNY as the tax rate decreases from 20% to zero. The findings could provide reasonable suggestions for investment decisions under realistic volatile environments, as well as scientific references for policy design, thus facilitating the large-scale and high-level development of hydrogen-based steelmaking technology. • Considering multiple uncertainties in hydrogen steelmaking project decision making. • Building Real Option Model for investment strategy of hydrogen steelmaking project. • Best time to invest is 2036 at 5% decline rate of H 2 price and current steel price. • Analyzing incentive effects of one-time subsidy, H 2 incentives and tax incentives. • Subsidy for H 2 is the most effective incentive to advance the investment timing. [ABSTRACT FROM AUTHOR]

• The share of ground source heat pump needs to be raised 3% annually for 1.5 ℃ goal. • Demands for geothermal and solar need to increase by 138% and 72% in 2 ℃ scenario. • The cost reduction of key technologies can reduce total investment costs by 37%. • Achieving 1.5 ℃ target can obtain 137 trillion CNY net incomes until 2050. To achieve the long-term climate targets of limiting global warming to well below 2 ℃ and 1.5 ℃ relative to pre-industry levels, China's building sector must be deeply decarbonized considering its potential of substantial emissions increase. However, how to deploy the energy technologies and how much we need to pay for China's building sector for achieving the global warming targets remain unknown. Here, we develop a bottom-up national energy technology model for building sector (NET-Building) to explore the optimal energy technology pathways, energy demands as well as costs and benefits for decarbonizing China's building sector under 2 ℃ and 1.5 ℃ targets. The results show that to meet the 2 ℃ target, most of fossil fuel-fired end-use devices and all traditional biomass-fired end-use devices need to be significantly reduced for the whole building sector. To pursue a more aggressive 1.5 ℃ climate goal, both proportions of the ground source heat pump and solar thermal water heater need to be drastically boosted and reach 100% in commercial sector by 2050. The decarbonization of China's building sector under 2 ℃ and 1.5 ℃ targets can obtain 44 and 137 trillion CNY net incomes until 2050, respectively. [ABSTRACT FROM AUTHOR]

Currently, more than 70% of the heated floor area in northern China is heated by coal, which severely burdens energy consumption and the environment. Hence, heating in this area is in urgent need of a shift to cleaner approaches. However, current progress is mainly attributed to the generous and unsustainable subsidies of the government, which have become a considerable financial burden. This paper develops a linear recursive dynamic model to identify economical, clean heating pathways in northern China. Different heating demands and clean technology promoting advances are considered. The results show that rapid promotion of clean heating technologies would save 1161–3026 Mtce (million tons of standard coal equivalent) of energy and avoid 7692–8843 Mt CO 2 , 12–13 Mt CH 4 , 8–9 Mt SO 2 and 7–8 Mt BC emissions cumulatively from 2020 to 2050. For rural residential buildings, biomass pellet furnaces, air source heat pumps and air conditioning should each contribute to about 30% of the heating demands in 2050 to achieve clean heating. However, coal-fired cogeneration should be the major method of coal heating, and mainly serve urban residential buildings and commercial buildings. The consequent energy cost savings of a faster clean heating transition would exceed the increase in investment costs and operational costs. Therefore, promoting clean heating as early as possible is the economical and environmentally friendly choice for northern China in the long run. [ABSTRACT FROM AUTHOR]

China's power sector consumes large amounts of water for its cooling every year, which has increased water stress in many regions and caused the vulnerability in electricity generation. Current plans for power sector mainly focus on the clean and low-carbon development, while it is unclear how to reconcile CO 2 -reduction target with water-saving target. In this paper, an optimization model named NET-Power (National Energy Technology-Power) is developed to simulate the deployment of power generation technologies, and to further answer whether there is a conflict or not between water-saving target and CO 2 -reduction target in the power sector. The result shows that peaking carbon emissions before 2030 in the power sector may increase the water consumption by 34.85Gt. In addition, to further meeting the water constraint on the basis of peaking carbon emissions would lead to a higher carbon intensity of thermal power. These findings indicate that low-carbon transition will cause significant water-carbon contradiction, which mainly lies in nuclear power technology and dry-cooling technology. Finally, the optimal technology layout path that can meet the dual constraints of water and carbon for the power sector in China is proposed. Unlabelled Image • The water-carbon nexus of China's power sector is analyzed. • Low-carbon development of power sector will consume more water. • Nuclear power and Dry-cooling system cause the main contradiction. • Optimal power technology layout under water-carbon dual constraints is identified. [ABSTRACT FROM AUTHOR]

• A National Energy Technology model for transport sector is established. • China's intercity passenger transport demand and structure is projected up to 2050. • The impacts of low carbon policy on each intercity mode of transport is evaluated. • Intercity passenger transport could peak its CO 2 emissions at 448.7 MtCO 2 in 2030. • A sustainable development path for intercity passenger transport is proposed. The transportation sector is responsible for a major share of energy-related greenhouse gas (GHG) emissions worldwide. There is already great concern about the fast-growing energy demand and carbon emissions from China's transportation sector. This study focuses on intercity passenger transport and aims to simulate its future energy demand and carbon emissions pathway by optimizing its technology portfolio based on a developed C3IAM/NET-Transport model. The energy-saving and carbon emission-reduction potential of countermeasures, such as optimizing the transportation structure, improving energy efficiency and promoting alternative fuels were investigated thoroughly and a sustainable development pathway for vehicle technologies and fuels in China's intercity passenger transport was identified. The model results show that by taking joint countermeasures, intercity passenger transport could save 2515.5 Mtce energy consumption and lead to a cumulative reduction of 8447.4 MtCO 2 between 2015 and 2050. China's intercity passenger transport would peak at the total CO 2 emissions of 448.7 MtCO 2 in 2030. [ABSTRACT FROM AUTHOR]