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Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

Recognizing the industrial sector's high energy use and vast potential for energy saving, many national governments have established voluntary or negotiated agreements that set quantitative energy-saving targets for individual industrial enterprises. The most commonly used energy-saving targets worldwide are volume and energy intensity targets. Since 2006, the Chinese government has set mandatory, enterprise-level energy-saving targets in terms of the “amount of energy saved”; this represents a unique category that differs from both volume and energy intensity targets. Based on first-hand data collected at ten case enterprises, this paper represents one of the first attempts to verify the reliability of the amount of energy saved data reported by the Chinese government and to rigorously and systematically investigate the inherent weaknesses of the amount of energy saved targets through a comparison with the mainstream categories of energy-saving targets. The ten case enterprises reported four different types of amount of energy saved. While all of the case enterprises claimed full achievement of their amount of energy saved targets, four enterprises exaggerated their performance by violating the National Standard for Calculating the Amount of Energy Saved of Enterprises. The paper thus hypothesizes that the National Top-1000 Enterprise Program's alleged achievement of performance 65% higher relative to its amount of energy saved target is likely an overestimation. Although amount of energy saved targets constitute an innovative energy-saving indicator, they do not represent a step forward from conventional volume and intensity targets because of the following four weaknesses: 1) amount of energy saved targets provide limited potential for comparison given the different types of amount of energy saved and the different calculation methods, 2) they generate uncertain environmental outcomes as it is possible to meet a portion of an amount of energy saved target through production volume expansion, 3) they are difficult to enforce due to the complexity of data verification on the part of local government agencies, and 4) they are poorly correlated with the national target for reducing energy intensity. Amount of energy saved targets should therefore be replaced with “double-control” targets that impose both volume and intensity targets on industrial enterprises. [ABSTRACT FROM AUTHOR]

Abstract: In March 2011, China’s central government set a new challenging target of reducing its energy intensity by 16% during 2011–2015, after it had achieved a reduction of 19.1% during 2006–2010. And this new target was assigned to provincial authorities in August 2011. However, China’s provincial energy-economic developments are unbalanced and different provinces have different key sectors for energy conservation. Most previous studies focused on provincial energy efficiency at the aggregate level, or the three-industry level (or one-digit level). However, whether for policy decision or academic research, it is necessary to further subdivide the sectors. In this paper, we use three indicators (Gini Coefficient, energy consumption share and energy intensity) to compare provincial energy conservation potentials at the two-digit sector level. To our knowledge, this paper is the first one to identify the keys for energy conversation across the 31 provinces×65 sectors. And the results are shown in visualized maps and matrix tables to help identify the key province×sectors for energy conservation easier. This also helps the central and provincial governments to distinguish key sectors when they monitor the energy conservation progress. [Copyright &y& Elsevier]

Abstract: Recently, energy production in China fell behind energy consumption. This poses important challenges for the rapidly growing Chinese economy. As a consequence, the causal relationship between energy consumption and GDP is an important empirical issue. This paper examines Granger causality between energy consumption and GDP in China using province-level data. The current paper extends the Granger causality analysis employed in previous studies by taking into account panel heterogeneity. Specifically, four different causal relationships are examined: homogeneous non-causality (HNC), homogeneous causality (HC), heterogeneous non-causality (HENC), and heterogeneous causality (HEC). HC and HNC hypotheses are rejected for causality in either direction, from GDP to energy or from energy to GDP, which implies that the panel made up of Chinese provinces is not homogeneous. Then, heterogeneous causality tests (HEC ad HENC) are conducted for each province. For the causality running from GDP to energy, 19 provinces exhibit HEC and 11 provinces exhibit HENC. For the causality running from energy to GDP, 14 provinces exhibit HEC and 16 provinces exhibit HENC. The results suggest that the Chinese government should incorporate a regional perspective while formulating and implementing energy policies. [Copyright &y& Elsevier]

Abstract Theses on China's low-carbon economy focus on the driving forces of carbon emissions, energy–carbon efficiency, and the carbon–economy nexus. Meanwhile, comprehensive frameworks that assess China's green economy and also analyze its driving forces are lacking. This paper constructs a green productivity index based on the Global Malmquist–Luenberger productivity index to evaluate the development of the low-carbon economy in China. A panel vector auto-regression model is adopted to further analyze the endogenous interactions and dynamic relationships among aspects of the green economy and its influencing factors. Empirical results show that China has seen a balanced development of green economic growth in 2000–2016, achieved in a series of clear stages. To maintain the sustainable growth of the low-carbon economy in the future, China must rely more on technological progress. This research also makes some important discoveries that have not been found in previous studies: the impact of China's industrial structure and energy consumption structure on the green economy are short term, having a duration of impact of approximately four years. Finally, we provide an assessment of provincial green economy development and describe the corresponding policy implications. Graphical abstract Image Highlights • A comprehensive analysis of China's green economy. • A slack-based Global Malmquist–Luenberger index is adopted to calculate the Green Productivity Index in China. • The stage characteristics of green economic development are identified. • A panel vector autoregressive model is used to analyze the interactions among aspects of the environmental economic system. • The findings that the impact duration of energy structure, industry structure, and urbanization on the green economy is about four years. [ABSTRACT FROM AUTHOR]

Highlights • The input–output model and ecological network analysis (ENA) are integrated. • The control and dependence conditions of economic sectors in China are analyzed. • The key regions and sectors for carbon mitigation of China are identified. Abstract In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions. [ABSTRACT FROM AUTHOR]

The objective of this study is to trace and quantify the sources of rebound effect for different energy sources in China. This paper decomposes the economy-wide rebound effect into 135 production sector-level rebound effects and five final demand components. The sector-level rebound is further decomposed into output effect and substitution effect. A two-stage decomposition method and a static computable general equilibrium model are developed to achieve this. Five types of energy-specific efficiency improvements are introduced, respectively, in all the production sectors. Results show that improving efficiency of using coal leads to the smallest macro-level rebound. For rebound decomposition, four findings are generalized. First, final consumption shows larger impact on the rebound of secondary energy sources than on primary energy sources. Second, production sectors that are big user of the efficiency-exposed energy source are expected to be key rebound contributor. Third, energy-producing sectors make negative rebound contribution. Results also show that, substitution effect is the predominant mechanism that triggers sector-level rebound. Policy implications are also discussed. [ABSTRACT FROM AUTHOR]

The key distinction between production-based and consumption-based accounting lies in the way in which trade-embodied emissions are allocated between producer and consumer regions. Yet, these two regions are not necessarily directly connected to each other in supply chains, due to spatial production fragmentation. To better understand the link from the production-based to the consumption-based regional carbon inventories, this paper defines the economic length of carbon transfer (ELCT) as the number of administrative border-crossing involved in the influence process of a region’s final demand on the carbon emissions of another region. Using a multi-regional input-output analysis framework for China, we propose an approach to calculating the ELCT related to a region’s production or demand for domestic consumption or international export. We find that the average ELCT in 2010 is 1.34 and that more than a quarter of interregional carbon transfer crosses provincial borders twice or more. The provincial and sectoral analysis of ELCT reveals that spatial production fragmentation is an important challenge to be conquered for successful implementation of consumption-based climate regulations. [ABSTRACT FROM AUTHOR]

There is a large amount of water consumption embodied in energy production. Driven by a growing population and economy, the energy sector will continue to expand, increasing more pressure on the fresh water demand of countries. This paper analyzes the energy–water nexus embodied in international energy trade via a combination of input–output analysis (IOA) and ecological network analysis (ENA). The energy–water element nexus is depicted based on a mixed-unit IOA to investigate the parallel relationship between energy and water. ENA is used to uncover energy–water pathways intertwined in global energy trade and identify the pair-wise relationship between countries according to the energy–water pathway nexus. Then, a case study of the international energy–water nexus of China is conducted. The results of energy–water nexus element analysis show that water use per unit of energy products in the country is much greater than those of other countries. Moreover, indirect water use during energy production deserves more attention, which is often neglected in water resource management. The results of energy–water nexus pathway analysis demonstrate that international energy trade has a positive effect on China’s water condition, mitigating serious water shortage problems but increasing dependency on other countries and regions. Mutual relationships among trading countries are described using utility and control analyses. The results show that system integrality is arguably more critical in determining system behavior than direct effects alone. Europe changes from a beneficiary in direct mutual relationships to a contributor in integral utility mutual relationships, whereas Australia has an opposite change. Although China has a dominant position in direct relationships, it becomes an equal competitor with the USA in utility mutual relationships. China depends heavily on most countries, especially those in South and Central America, the Middle East, Africa, and Australia. The network mutualism index (=0.56) and synergism index (=9.187) indicate that the current global energy trade network has negative relationships within a competitive environment. Finally, policy and economic suggestions are put forward to alleviate the potential impacts of international energy trade on water scarcity in China. [ABSTRACT FROM AUTHOR]

This paper links theoretical perspectives from energy efficiency economics with those observed from corporate environmental strategy to develop a framework for explaining energy efficiency strategies by firms in response to national policies and local regulations in China. The framework is refined through analytic generalization of 20 cases from four industries and four cities in Jiangsu Province, and reveals two strategies: 1) firms with moderate institutional pressure seek incremental competitiveness by adopting energy-saving technologies, which is reinforced by their informational, organizational, and financing capabilities, and facilitated by voluntary policies and industrial competition; 2) firms with survival risk or development constraints under regulation seek a position favored by local governments by replacing old plant and equipment with larger, more efficient ones and contributing to the local community. The Chinese case studies reveal a strong institutional impact on firms' choice of business strategies and particularly the positioning strategy. The identified business strategies shed additional light on the effectiveness and implications of different policy instruments for energy efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the temporal and spatial changes of embodied energy transfers via China’s domestic trade over 2002–2007 based on the multi-regional input–output models. Interregional trade of total embodied energy uses approximately tripled between 2002 and 2007, and the total trade volumes in it were equivalent to 38.2% of the national total direct primary energy input in 2002 and 62.9% of that in 2007, respectively. Among all the eight regions, Northwest , Central , Northeast and Southwest were the interregional net exporters and deficit receivers of embodied energy in contrast to East Coast , South Coast , North Coast and Beijing–Tianjin as interregional net importers and surplus receivers. Significant growth of net embodied energy transfers can be identified from central and western inland regions to eastern coastal regions, and the Central region partly served as a “transmission channel”. By considering the interregional embodied energy transfers, regional energy use inventories changed largely, and the spatial and temporal differences between 2002 and 2007 were expanding. Industrial positions in domestic and global supply chains and inherent economic driving factors such as increasing regional consumption level, accelerated investment in fixed assets and rapidly expanding export were the major driving forces for the embodied energy transfers among regions. To form a set of useful tool for controlling energy consumption and achieving the goals for energy saving and emission reduction, China’s governors at all levels deserve to understand the relationships between energy producers and users from the view of demand-driven energy requirements. [ABSTRACT FROM AUTHOR]

In the tourism industry, hotels and homestay facilities account for considerable amounts of energy consumption and CO 2 emissions. Unlike other types of buildings, occupancy has significant fluctuations over time, while mostly being ignored or using a simple assumption based on energy use intensity or setting the occupancy levels. Due to the lack of occupancy rate information, great uncertainties exist in hotel operations, which leads to erroneous estimates of energy consumption in existing hotel buildings. This paper examines hotel operation practices in China with real occupancy rate data which is critical for reducing the uncertainty of estimating energy consumption patterns. Specifically, this study proposes a two-stage comprehensive and quantitative performance assessment approach for the homestay hotel building considering the system's energy and economic performance simultaneously. Regarding energy performance, there are two key facets to consider: renewable energy penetration and grid impact performance. Additionally, the economic performance (annual income and extra annual investment) of various energy portfolios is evaluated using break-even analysis. The impacts of large fluctuation in occupancy rate on electrical loads are considered and assessed in typical homestay hotels. The proposed assessment approach can comprehensively quantify the impacts of the photovoltaics (PV) areas and battery capacities on the system performance in terms of energy and economics. According to the results of the occupancy-based assessment, the ideal PV area and battery capacity are 400 m2 and 16 kWh, respectively, as opposed to the optimal energy portfolios (PV area 600 m2 and battery capacity 24 kWh) determined from conventional assessment results. [ABSTRACT FROM AUTHOR]

In recent years, China has started to change its growth strategy to a more sustainable model in response to the limits-to-growth dilemma. Specifically, the national policy advocates to promote the use of green-manufacturing technologies through demonstration projects, and to incentivize Chinese manufacturers to adopt these green-technologies that are also encouraged by local governments. These green technologies can increase the economic gains of manufacturers by reducing costs on energy consumption and shift away from selling low-margin products. However, the local authorities often encounter obstacles when implementing policies for promoting these technologies among manufacturing firms. This paper explores the factors that affect the decision-making of user firms throughout the policy implementation process. Based on the econometric analysis of the survey for China's electric motors upgrading project in Guangdong Province, this study shows that three key factors are helpful in the local government's effort to implement the national project, i.e. manufacturers' awareness, the understanding of the energy-efficiency technology, and the long-term macroeconomic benefits. In addition, encouraging the participation of financial institutions is especially useful for local governments to convince small-and-medium sized firms. These findings are beneficial for local implementation of green-manufacturing technology diffusion policies in China and have worldwide policy implication as well. [ABSTRACT FROM AUTHOR]

The growing conflict between economic growth, energy and environment in China has restrained the country's economic development. In this work we investigated the interaction among the Chinese economy, energy production and consumption and the impacts of concomitant air emissions from 2000 to 2011, using an indicator system based on energy, emergy and money units. The results show that China's rapid economic growth has promoted tremendous expansion in energy production and consumption, which have led to increasing the impact of emissions in this study period. During the time examined, energy production and use efficiencies and the structure of the energy sector improved slightly; the self-sufficiency of energy use fluctuated, as petroleum took on an increasingly strong dependence on imports; fossil energy, mainly coming from coal, still has a majority share in energy production and consumption of the nation; the environmental loading intensity of energy consumption decreased slightly while that of energy production increased; most of the impacts of energy-related emissions are derived from their impact on human health; the impact of emissions from energy production made an increasing contribution to the total impact. Generally speaking, China's economic growth still heavily depends on energy-intensive industries that put great pressure on energy supply and pollution control. Although China has made obvious progress in energy mix optimization to save energy and reduce emissions, the pace of improvement still fell behind that of economic growth. Finally, this paper discussed some related issues and presented corresponding suggestions to further coordinate the relationship between the economy, energy production and consumption and the environment. [ABSTRACT FROM AUTHOR]

Abstract: Effective spatial planning is crucial for cost-effectively and sustainably developing biomass energy resources due to the diffuse nature of biomass and high transportation cost. Using the spatial analysis technology, economic models and scenario analysis, this paper presents a spatial planning framework to identify the appropriate developing areas of biomass energy at regional level. The methodology is applied in a case study of Fujian Province, China. Firstly, spatial distribution of two kinds of biomass resources and the technical potential, i.e. the amount of power generation from agricultural and forestry residues in each supply area, were estimated by incorporating the spatial data and the statistical data. The results indicate that total technical potential of agricultural and forestry residues is estimated at 25.13TWhy−1, equivalent to approximately 19% of total electricity consumption in Fujian in 2010. In the second step, the economic analysis assesses the cost of biomass generation for each supply area on the basis of current market conditions. Ranking of the supply areas is then performed by using the priority development index (PDI), which can measure the priority of each biomass supply area by combining several influencing indicators. Finally, the selection of supply areas for power plants can be carried out according to its order in PDI until the total planed capacity in the region is met. The priority of the subregions and the corresponding cost of biomass generation for different planning scenarios can be explicitly visualized. The methodology can be applied to a wide area and can support the local authorities to define and implement a strategy for future biomass energy development. [Copyright &y& Elsevier]

Abstract: To find the key impact factors of CO2 emissions to realize the carbon intensity target, this paper examined the impact factors of population, economic level, technology level, urbanization level, industrialization level, service level, energy consumption structure and foreign trade degree on the energy-related CO2 emissions in Guangdong Province, China from 1980 to 2010 using an extended STIRPAT model. We employed ridge regression to fit the extended STIRPAT model. Empirical results indicate that factors such as population, urbanization level, GDP per capita, industrialization level and service level, can cause an increase in CO2 emissions. However, technology level, energy consumption structure and foreign trade degree can lead to a decrease in CO2 emissions. The estimated elastic coefficients suggest that population is the most important impact factor of CO2 emissions. Industrialization level, urbanization level, energy consumption structure, service level and GDP per capita are also significant impact factors, but the other factors such as technology level and foreign trade degree are less important impact factors. Some policy recommendations are also given on how to mitigate the growth of CO2 emissions. [Copyright &y& Elsevier]

Abstract: The residential sector is the second largest consumer in China with great room for energy consumption growth, as well as the related carbon emissions. Thus, how to reduce the growth rate of carbon emissions is crucial for realizing the target of energy conservation and emission mitigation in the residential sector. Based on a bottom-up framework with survey data and official statistics, this paper examines the changes of aggregate residential carbon intensity, and analyzes its driving factors from an end-use perspective over the period of 1996–2008. The Adaptive Weighting Divisia with rolling base year index specification is applied to identify the quantitative effects of driving components and their further decomposing results of end-use activities. Results show that, the residential aggregate carbon intensity has grown rapidly since 2002 in both urban and rural China. The changes in primary fuel mix for electricity and heat generation have an overall negative but insignificant effect on the residential aggregate carbon intensity, while the effect of final energy structure is positive with a rising tendency. The significant impact of changes in energy intensity shift from negative to positive over time, and contribute more to a decline than to an increase. The driving force arising from the residential end-use mode has the highest contribution to the increase of aggregate carbon intensity. Finally, some policy implications are proposed to effectively slow down the accelerated rate of the residential aggregate carbon intensity. Guiding households towards energy-saving behaviors is recommended as a wise and first policy choice. [Copyright &y& Elsevier]

Abstract: Energy is a bottleneck, which restrains the development of China''s economy and society. Our government has always been attaching great importance to energy problem. In China, there exist space-time correlation and differences in energy consumption and efficiency among different areas. The purpose of this paper is to study the spatial correlation and heterogeneity in energy consumption among different provinces, as well as the mechanism of the spatial effects of economic growth on energy consumption, energy prices, and population growth by means of constructing Bayesian spatial econometric model. [Copyright &y& Elsevier]

Abstract: Low-carbon energy and constraints of resources and environment will increasingly become two important factors inhibiting China''s economic development in the future. According to the relationship and coordinating mechanisms among energy consumption, carbon dioxide emission and economic development, This paper establishes the two-dimensions evaluation indicating system based on balanced. Use data development analysis, through the fact data of some typical provinces in 2009, we make a comprehensive assessment of its historic coordination, analyze the degree of coordination and the reasons for the contradiction, strive to source the dialectical unity from similarities and differences, and finally proposed some political ideas and recommendations on promoting China''s future coordinating development among economy, energy, and environmental. [Copyright &y& Elsevier]

Abstract: Electrification level is a significant topic in energy and electric power planning. The paper sets up a LEAP model and designs three scenarios of economic growth of China, and simulates China''s electrification level by 2030. The results show that China''s electrification level has a larger increase potential in the mid-long term and rapid change of economic development pattern can help to increase the electrification level. By 2015, energy used for power generation will account for 43.3% of total primary energy consumption, while the ratio of electricity consumption to total final energy consumption will be about 23.1%; by 2020, the ratio of energy used for power generation to total primary energy consumption will increase to 44.9%, and the ratio of electricity consumption to final energy consumption will be about 25.6%; by 2030, the ratio of energy used for power generation to total primary energy consumption will be up to 47.2%, and the ratio of electricity consumption to total final energy consumption will reach about 28.9%. [Copyright &y& Elsevier]

Abstract: The early study on green architecture had the problem of “high input, low output”, and China is facing the same problem in the development of green architecture. To plumbing the depths of energy-saving architecture, China needs a complete set of industrial policy that is attractive to the industry, schools and research institutes. This paper analyzes the evolving energy policy in Japan, how it utilized a series of regulatory and policy measures, such as law, economic and financial policies, subsidy system and evaluation system, to effectively intervene and promote the gradual development of green architecture, and takes Misawa Home as an example to show the development path of green home in Japan, with the view of providing reference in policy and direction for the sustainable development of green architecture in China. [Copyright &y& Elsevier]

Abstract: In order to forecast energy demand in China in the next 20 years, this paper firstly analyzes the current situation of China''s energy consumption, and then apply LEAP model to simulate primary energy and final energy demand in 2020, 2030 under different scenario composition about economic development, energy efficiency and energy structure. The results show that: the total primary energy demand will reach 4840-5070 Mtce in 2020, 5580-5870 Mtce in 2030; the share of coal in primary energy will decrease, and that of oil, natural gas and non-fossil energy sources will increase. For all the three economic growth scenarios, 40-45% carbon emission intensity reduction target can be realized. If non-fossil energy can be further developed, carbon emission intensity can reduce more than 45% by 2020. The goal of the 15% share of non-fuel energy in primary energy is difficult to realize, unless the most development potentials of hydro power, nuclear power and wind power can be reached. [Copyright &y& Elsevier]

Abstract: China’s economy has been on a solid fast growth track since 1978. The economy expanded by an average annual rate of about 10% during the last thirty years. That is more than triple the average growth rate of the world economy during the same period. The rapid economic development has been associated with growing energy consumption and carbon dioxide (CO2) emission. Although the first phase of the Kyoto Protocol exempts China from reducing its own CO2 output, China, as the first or second largest CO2 emission country, is facing growing international political pressure. As a responsible big country, China will almost certainly have to respond to climate change in the future. China is entering unexpected fast development period of the industrialization, urbanization and motorization, in which large-scale new infrastructures will be built. This provides great opportunity to plan for longer-term CO2 mitigation—the infrastructures built today have a long life time and are not easy to upgrade the technologies involved, and decisions made now will have a major impact on energy utilization mode and CO2 mitigation technology option in coming years. Carbon Capture and Storage (CCS), as an option in the portfolio of mitigation actions to combat climate change, is expected to have far-reaching implications for China. This paper (1) explores the strategic significance of CCS for China by making an extreme scenario analysis of Chinese power sector in 2030; (2) provides an overview of the recent CCS activities in China; and (3) identifies the major challenges with respect to CCS development in China and put forwards immediate strategies. [Copyright &y& Elsevier]

Accurately forecasting energy demand can better predict future changes in energy demand. This study is aimed to develop more accurate clean energy prediction model from two perspectives of the modeling mechanisms and improvements on the model structure. For this purpose, a novel Riccati–Bernoulli differential equation is established through social practice theory, supply–demand relationship, and the preference of consumption in the energy economy. Considering the limited information in observation data, this differential equation is then transformed into a grey Riccati–Bernoulli model (GRBM(1,1)) according to the differential information principle. With the response function solved on the basis of polynomial equation theory and the power exponent optimized combining the modified flower pollination algorithm, the main process of GRBM(1,1) can be summarized. The four validation examples are provided for confirming the effectiveness and reliability of the new model by comparing with other existing models. Finally, the proposed model is employed to estimate and forecast the clean energy consumption in China and India. The results show that the proposed model demonstrates better estimation in all cases and efficiency in short-term clean energy consumption forecasting. Therefore, by using this optimum model, China's preference coefficient in total energy consumption is 0.7103, lower than that of India (0.8799), and China's preference coefficient in clean energy consumption is 0.9665, higher than that of Indian (0.7155), which means China has less interest to increase total energy consumption but more interest in popularizing the clean energy. • This paper proposed a novel grey Riccati–Bernoulli model for energy consumption prediction. • A specific solution algorithm for this Riccati–Bernoulli equation is discussed in this research. • We compared the proposed novel grey model with other 12 exiting prediction models. • The novel model also reveals China's effort in popularizing the use of clean energy. [ABSTRACT FROM AUTHOR]