Search

China is the top emitter of greenhouse gases in the world. Pulp and paper industry is one of eight the strictly regulated industries about carbon emission in China. However, estimates of carbon emissions from China's pulp and paper industry have been suffered from remarkable uncertainty. It is summarized that is aroused by the inaccuracy of factors evaluating energy consumption, and the huge gap between the calculation standards for assessing energy consumption in the production process and the actual level recorded in the factories. This paper re-evaluated the carbon emission of China's pulp and paper industry from the perspective of life cycle assessment, and applied more accurate emission factors, taking account of the actual energy consumption of the production process in factories, to estimate the actual carbon emissions in maximum. It is found that the national standards about the energy consumption quota of China's pulp and paper industry is no longer applicable, and the actual energy consumption regulated in the production process is far better than the advanced level given by the national standards. The greenhouse gas emission have been seriously overestimated approximately 12.00%–56.17% by international organizations. • Life Cycle Analysis of the China's pulp and paper Industry is conducted thoroughly. • The pulp flow of China's pulp and paper Industry is analyzed. • Energy regulated in factory is far better than the national standards' required. • Carbon emissions of China's pulp and paper Industry are overestimated. [ABSTRACT FROM AUTHOR]

Guiding industries to produce in an effective and environmentally sustainable manner has become a key issue for governments around the world. Over the past 15 years, series of regional and industrial development policies have been introduced by the Chinese government. This has influenced the geographical distribution and energy efficiency performance of China’s industries. This paper quantifies the influence of enterprises geographical distribution on energy efficiency improvement in the paper industry and aims at providing some helpful suggestions on industrial development to policy makers. The main results show that, firstly, the paper industry in eastern China shows obvious characteristic of agglomeration. The average location quotient is 1.2278. However, following the industrial and regional development policies, the characteristic of agglomeration is weakening. Secondly, only when agglomeration reaches a certain level (location quotient is above 0.5447) will industrial agglomeration positively impact on industrial energy efficiency improvement (a 1% increase in agglomeration will increase dynamic energy efficiency by at least 0.23%). Thirdly, the regional development policies carried out by the government slow the pace of energy efficiency improvement in China’s paper industry. The empirical results indicate that the government needs to consider regional characteristics and consciously guide industrial enterprises to concentrate in the dominant area. [ABSTRACT FROM AUTHOR]

China’s paper industry consumes a lot of energy and emits huge amounts of pollutions. The Chinese government over the past decades has done a lot to promote energy efficiency of the industry. This paper studies the impact of industrial polices to improve energy efficiency. The energy efficiency change is firstly studied under a framework of total factor efficiency. On this basis, different econometric models are built to discuss the detailed energy efficiency characteristics of the paper industry. The main results are as follow: (i) ownership structure did influence the energy efficiency, but the influence is different in different conditions; (ii) energy efficiency of the paper industry can be improved by economies of scale; (iii) market competition can to some extent overcome the motivation and supervision problem that often occur in state-owned companies; (iv) energy price cannot play the role of resource allocation well in China. Finally, based on our findings, some suggestions are provided. [ABSTRACT FROM AUTHOR]

China's paper industry accounts for a larger proportion of the global paper industry and consumes large amounts of energy. Energy conservation and pollution reduction of the industry have become the focus of China's national development strategy. Energy efficiency is an important index which directly determines the amounts of energy consumption and pollution emissions. To understand the energy efficiency evolution of China's paper industry, this paper establishes an input-output data of the paper industry for 29 provinces in China and applies DEA method and econometric models to estimate and comprehensively discuss the energy efficiency issues based on the framework of total factor efficiency. Our results indicate that China's paper industry has a large energy saving potential even though its energy efficiency has improved during the period 1990–2013. The saving potential is about 65% under the meta-frontier and 44% under the group-frontier. Moreover, there are significant differences between different regions in production technology and energy efficiency. The performance of eastern China is better than other regions. But the technology gaps between the different regions are shrinking and converging over time. Finally, some policy recommendations are proposed to improve the energy efficiency of the industry. [ABSTRACT FROM AUTHOR]

China has become the world largest paper and paperboard producer. However, pulp and paper industry has involved high resource consumption and severe pollution especially for water. This research has assessed the eco-efficiency of China's pulp and paper industry at the national level and provincial level. An overview regarding the cleaner production of China's pulp and paper industry was presented to reveal the measures for reducing environmental impact in the last two decades. Slacks-based measure was used to analyze the efficiency levels of 16 provinces' pulp and paper industries. To uncover the underlying causes of eco-efficiency performance, Malmquist–Luenberger index was calculated to discover the drivers of productivity growth of pulp and paper industries. Our results showed that the pollution treatment of China's pulp and paper industry has made progress in terms of water consumption and water pollution, although the absolute amount of pollution discharge is still large. Chemical oxygen demand emissions are still the first critical influencing factor of pulp and paper industry's inefficiency. Furthermore, efficiency progress was the dominating contribution of the industry's productivity growth between 2010 and 2013. The policies for adjusting the industrial structure of pulp and paper industry have resulted in the scale effects through eliminating backward production capacity and accelerating merger and acquisitions. Moreover, the productivity of pulp and paper industry was underestimated when the undesirable outputs were ignored. It indicates that the stricter environmental regulations have positive effects on paper companies to internalize environmental pressures in the production activities through environmental management. In the future, pulp and paper companies should further internalize the cost of pollution treatment through scale effects and technology improvement. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this paper is to estimate the energy saving potential in China's paper industry by determining energy intensity under different scenarios. Cointegration model and stability test are applied to formulate the equilibrium equation. Results show that energy price, industry structure, profit margin and technology have significant impact as they are negatively correlated to changes in energy intensity. Three scenarios (BAU (business as usual), intermediate and active) are designed to estimate the future trend of energy intensity in paper industry. In 2010, the energy intensity (energy consumption per unit of value added) was 4 tce/10,000 RMB, and by the scenarios it is expected to considerably decline. According to the BAU (business as usual) scenario, the energy intensity will decrease to 2.56, 1.43 and 0.70 tce/10,000 RMB by 2015, 2020 and 2025, respectively. With respect to the intermediate scenario it is expected to drop further to 0.44 tce/10,000 RMB. Yet by the active scenario, the energy intensity is expected to considerably decline to 0.36 tce/10,000 RMB by 2025. Using the BAU forecast as a baseline, the quantity of energy savings is estimated to be 185.6 billion tce by 2025. Considering this important potential, we also provided some policy suggestions. [Copyright &y& Elsevier]

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]

To reduce energy use and achieve a low carbon production in pulp and paper industry (PPI), it is essential to improve energy efficiency in pulp and paper production. In this study, the energy savings from the PPI were estimated based on a techno-economic analysis by EAGER tool for PPI at the factory level. The structure and implement procedure were introduced initially. Two typical pulp and paper mills from China were determined to estimate the impact of selected energy efficiency technologies (EETs) on energy savings as the cases in the base year. One Factory (A) only produced paper products (i.e. corrugated paper and Kraft linerboard) while the other Factory (B) also produced market pulp besides sack paper. In totally 22 selected EETs were applied to assess their saving potential in Factory A, and 29 measures were applied in Factory B. The results show that 2290 TJ and 1179 TJ of final energy could be saved annually in Factory A and B, corresponding to reduction of 29.4% and 13.6% total energy consumption respectively for the case factories. The CO 2 reduction potential was 32.3% for Factory A compared with that of 16.6% in Factory B. It suggests that the pulp and paper mills should encouraged to use this method estimating energy saving potential, and improve their energy efficiency with suggested measures in order to reduce energy consumption and related carbon emissions further in the coming years. • Energy savings of pulp and paper production were estimated at the factory level. • A techno-economic evaluation tool was applied to access the energy savings and carbon emission reductions. • Two typical pulp and paper factories from China were investigated to estimate their energy savings in the base year. • It is useful to assess energy savings and select feasible EETs in achieving energy saving and emission reduction targets. [ABSTRACT FROM AUTHOR]

Papermaking is a water intensive industry. The growth of paper demand will further intensify the need of fresh water resources. Papermaking involves complex processing routes. Previous investigations of water consumption in papermaking industry have focused primarily on key processes and pathways, ignoring the impacts of many intermediate and inter-related processes in paper production cycles and there underestimating the sustainability impacts. Herein, the results of a life cycle analysis of water consumption for papermaking industry in China using an extensive system boundary that includes the water embedded in intermediate processing are presented. The results show the life cycle water consumption and water saving potentials for different papermaking pathways. The advocacy of "forest pulp and paper integration" may have few practical contribution to reducing water consumption due to the low indirect water consumption of raw materials and energy for transportation. [ABSTRACT FROM AUTHOR]

Daytime subambient radiative cooling is a most promising alternative to electricity-free building cooling. However, optical performance degradation arising from surface contamination and inevitable parasitic heat gain still pose unprecedented challenges to cool building at subambient temperatures. This paper proposed a superhydrophobic cellulose aerogel cooler (SHB-CAC) as building envelope by integrating self-cleaning capacity, passive daytime radiative cooling and thermal insulation to reduce environmental heat gain. The SHB-CAC demonstrates high solar reflectance (93%) and long-wave infrared emittance (91%), accomplishing a temperature drop of 8.5 °C lower than the ambient under sunlight of 800 W/m2 in the outdoor experiment. Notably, the SHB-CAC possesses low thermal conductivity (28 mW/(m∙K)) that suppresses parasitic heat gain from warmer surrounding and reduces cooling energy consumption. The self-cleaning property resulting from superhydrophobicity protects SHB-CAC from water wetting and dust contamination but also maintains its good surface radiation capacities under different humidity environment. A building energy simulation was conducted and results showed that 43.4% of cooling energy on average could be saved compared to the building baseline consumption, if SHB-CAC was widely used in China, indicating that the strategy of optical and thermal conductivity management of cooler has the potential to reduce the energy consumption of buildings. [Display omitted] • Waste paper is converted into aerogel cooler for building cooling. • High R solar and ε IR , thermal insulation, and self-clean are achieved in one design. • The aerogel achieves a high sub-ambient temperature drop of ∼8.5 °C on daytime. • The aerogel shows that 43.4% of cooling energy could be saved. [ABSTRACT FROM AUTHOR]

• A simple, large-scale fabrication of cooling paper via pulping and papermaking technology. • The cooling paper is facilely deconstructed and regenerated to architect the secondary cooler. • The cooling paper features a high solar reflectance of 94% and emissivity of 0.95. • The cooling paper shows the sub-ambient temperature drop of 6 ∼ 8.8 °C under directly solar radiation at daytime. Passive radiative cooling materials provide coldness without energy consumption for all-day thermal comfort by reflecting solar irradiation and emitting heat into the 3 K universe. However, the conventional radiative cooling materials involve complex multilayer structures and unsustainable polymers, showing the non-recyclable disadvantage, which induces resource waste and environmental issues. Herein, we reported a low-cost, scalable, and eco-friendly radiative cooling material (namely cooling paper), consisting of the delignified, fibrillated cellulose fibers and nano-sized hydroxyapatite (HA) via the mature pulping and papermaking process. The resulting cooled paper can be recycled, and it can be easily deconstructed to harvest cellulose fibers and HA, individually. The recovered source materials can be reused to prepare secondary products that show comparable performance to the original cooling paper, including a high solar reflectance of ∼94% and an infrared emissivity of ∼0.95 in the atmospheric transparency window. Such cooling paper enables superior cooling performance with the temperature drop of 6 ∼ 8.8 °C under directly solar radiation. Based on the EnergyPlus simulation, our cooling paper shows a average cooling energy saving of ∼29 % in buildings across China. The recyclable cooling paper with high cooling capability and scalability, as well as environmental friendliness, shows promising potential for sustainable energy-efficient buildings. [ABSTRACT FROM AUTHOR]

The current approaches to study the coupling mechanism between economy and environment seem to fall into self-circulation, failed to reveal "economy–environment interdependence". In this context, an exogenous variable is introduced into these models for better understanding the relationship. Benzo[a]pyrene (Bap) environment inventories in different cities in China were estimated by fugacity model based on Bap concentration data collected from previous studies. An extended model, stochastic impacts by regression on population, affluence and technology (STIRPAT), generated from original IPAT (a model that expresses the idea that environmental impact (I) is the product of three factors: population (P), affluence (A) and technology (T)) was used to study the relationship between Bap environment inventory and anthropogenic factors including population, vehicle amount, affluence and energy consumption. A ridge regression has been applied to optimize the model parameters. Overall, there exist good relationships between Bap inventories and economic factors. Specifically, population and affluence are the most significant factors that influence Bap inventory. Rise of the scale of population and vehicle amount increases the Bap inventory, as growth of GDP per capita and the efficiency of energy utilization have inhibitory effect on Bap inventory. Apparently, the influences of anthropogenic factors on Bap inventory are different between north and south China. Bap inventory in north China is more sensitive to the change of population and energy consumption, while is highly correlated to GDP per capita in south China. Further, according to social-economic development prediction, with assist of the result from STIRPAT model, we find out that Bap inventory drop 31% from 2001 to 2020 in China. Our estimates are comparable with the published data and confirmed that Bap can be regarded as a chemical indicator of social-economic development in China. Image 1 • An extended STIRPAT model derived from original IPAT was developed. • Population and affluence are the key factors that influence Bap inventory. • Advance of affluence and technology level curbs Bap environmental exposure. • We predict Bap environmental inventory drop 31% from 2001 to 2020 in China. • Bap can be used as an indicator of social-economic development in China. [ABSTRACT FROM AUTHOR]

• We study the relationship between GVC embedding and carbon emission density. • A mediation effect model was established to test the mechanism. • There is a U-shaped relationship between urban GVC embedding and carbon emission density. To achieve its carbon peak and neutrality plan, whether China's global value chain (GVC) embedding has a carbon emission reduction effect is a question worthy of attention. This paper measures the GVC embedding degree of 218 Chinese cities from 2000 to 2016, and constructs a panel data model to investigate the impact and its mechanism of GVC embedding on carbon emission intensity. This study finds that there is a significant U-shaped relationship between GVC embedding and carbon emission intensity, and a series of robustness test results support this conclusion. Export scale, energy consumption structure and technological innovation play a mediation role in the impact path of GVC embedding on carbon emission intensity. Based on this, this paper proposes that while participating in GVC, China needs to actively utilize the emission reduction effect of GVC, promote the transformation of export mode to high quality, reduce the use and dependence on high-carbon resources such as coal, and encourage companies to innovate. [ABSTRACT FROM AUTHOR]

Based on the evidence from listed company microdata and data from 285 cities in China, this paper studies the coordinated development of two-way FDI (CDFDI) in improving green energy efficiency (GEE). In particular, this paper examines the spatial heterogeneity effects of CDFDI on GEE. The results showed that CDFDI had a positive impact on the GEE of local and surrounding cities. Mechanistic examinations show that the effects of CDFDI on GEE are mediated by technological diffusion, nationalization, and environmental regulation. After dividing different city types, the impact of CDFDI is also different. By constructing a spatial decay weight matrix, this paper also finds that the positive spatial spillover effect of CDFDI is limited to 1050 KM. Finally, different investment motive portfolios also has a heterogeneous impact on the local and surrounding cities' GEE. After dividing the time nodes, the effect of this heterogeneity is more prominent. • We use multiple undesired output indicators covering eight pollutants to measure green energy efficiency (GEE). • CDFDI has a significant boost to GEE in local and surrounding cities. • The impact of CDFDI on GEE is moderated by technological diffusion, nationalization, and environmental regulation. • The spatial spillover effects of CDFDI are heterogeneous by city category and geographic distance. • CDFDI with different investment motives has heterogeneous effects on local and surrounding cities' GEE. [ABSTRACT FROM AUTHOR]

To cope with the severe challenges related to traditional economic-centered urbanization, the Chinese government has proposed a people-oriented new-type urbanization strategy, which focuses on promoting the coordination and sustainable development of the environment, economy, and society. The existing literature has studied the impact of traditional urbanization on energy use but has not yet revealed the mechanisms and effects of the new transformation of urbanization on energy efficiency. Based on socio-economic-natural complex ecosystem theory, this paper systematically explains how new-type urbanization affects energy efficiency. By adopting a newly developed dynamic panel threshold model, the paper examines the complex impact of new-type urbanization on energy efficiency using panel data of 285 cities in China from 2003 to 2017. The results show that new-type urbanization has a significant double-threshold effect on energy efficiency. As the new-type urbanization level increases, the improvement effect of new-type urbanization on energy efficiency presents the change features of "strong-weakened-stronger." The heterogeneity analysis shows that under the constraints of multiple factors, such as new-type urbanization stages, geographic regions, economic development levels, and resource endowment, the impact of new-type urbanization on energy efficiency varies significantly. Targeted and differentiated policy recommendations for promoting new-type urbanization and energy efficiency are proposed. [ABSTRACT FROM AUTHOR]

Regional integrated energy systems (RIES) can economically and efficiently use regional renewable energy resources, of which energy storage is an important means to solve the uncertainty of renewable energy output, but traditional electrochemical energy storage is only single electrical energy storage, and the energy efficiency level is low. Hydrogen energy storage has the advantages of large energy storage capacity, long storage time, clean and pollution-free, and can realize the synergistic and efficient utilization of electricity and thermal power. Based on this, this paper proposes a synergistic planning method for an integrated energy system with hydrogen storage taking into account the coupled use of electric-thermal energy, which effectively reduces the system carbon emission and improves the comprehensive energy efficiency level. Firstly, this paper constructs an electric-thermal coupling model of the hydrogen energy storage unit and proposes an optimization strategy for the integrated energy system containing hydrogen storage taking into account the utilization of electricity and thermal power. Secondly, a planning optimization model with the lowest economy and carbon emission and the highest comprehensive energy efficiency was constructed. Third, the CSPO-GE optimization algorithm is proposed for solving the problem, which significantly improves the solution efficiency. Finally, a planning optimization simulation of RIES for a residential community W in northern China verifies the effectiveness of the model and method proposed in this paper. The comparative analysis of the three schemes shows that compared with the integrated energy system with conventional electrochemical energy storage and heat storage tank as the main form of energy storage and the integrated energy system with only hydrogen storage, the integrated energy system with hydrogen storage and heat storage tank can reduce carbon emissions by 43.8% and 7.61%, respectively, and improve the integrated energy efficiency level by 337.14% and 14.44%. • An electrothermal coupled production strategy based on dynamic equilibrium feedback regulation is proposed. • A hydrogen-containing RIES planning and optimization model considering economy-environment-efficiency is constructed. • A multi-objective chaotic particle swarm algorithm (CPSO-GE) based on greedy and elite retention strategies is proposed • The impact of cost variation of hydrogen storage devices on the economics of integrated energy systems is considered. [ABSTRACT FROM AUTHOR]

In the context of low carbon economy development, controlling fossil energy consumption and promoting development in renewable energy are important paths for energy transition in various countries. Taking China as an example, this paper investigates the green finance policy coupling effect of fossil energy use rights trading (FET), renewable energy certificates trading (RECT), and renewable energy subsidies (RES) on the low carbon economy using a dynamic recursive computable general equilibrium (CGE) model. The main findings of this paper are as follows. (1) When using a game equity fixed-cost allocation model (Game-EFCAM) to allocate fossil energy use rights quotas among sectors, allocations differ in only a few sectors compared to the base period, and most sectors have relatively stable allocations compared to the base period. (2) The implementation of FET and RECT has a negative impact on per capita GDP. In the short term, RES can mitigate the negative impact of FET and RECT on per capita GDP, but eventually, the government needs to guide the enterprise innovation to improve the industrial structure to realize the double benefits of green finance policy. (3) The implementation of FET and RECT limits fossil energy consumption and also reduces the production possibility frontier of the secondary industries with higher levels of fossil energy consumption. The implementation of FET and RECT increases the proportions of tertiary industry and renewable energy. (4) The implementation of FET and RECT reduces carbon emissions. In other words, the implementation of FET and RECT mitigates the negative environmental externality. RES can enhance the carbon reduction efforts of FET and RECT. This research not only provides policy analysis for the development of the low carbon economy in China, but also gives a reference for other developing countries' low carbon economy transition. [ABSTRACT FROM AUTHOR]

• A distribution dynamics approach is employed to examine the converge of TFEE across Chinese PAA level cities. • The findings show a clear convergence in TFEE. • Convergence comes more from efficiency drops in high TFEE cities than from efficiency gains in low TFEE cities. • The environmental protection polices in key cities improved energy efficiency. • Large-sized cities show better performance in energy efficiency than small- and medium-sized cities. Improving energy efficiency is considered the most direct route to reducing carbon emissions on a massive scale. To examine the long-run trend of China's energy efficiency, this paper employs a distribution dynamics approach to analyze the convergence of total-factor energy efficiency (TFEE) across 286 Chinese cities between 2002 and 2014. The result suggests the existence of convergence, which comes more from the efficiency declines in the high TFEE cities rather than the efficiency gains in the low TFEE cities. Despite the fact that a few cities have performed well in energy efficiency, the majority of cities have converged to a low-efficiency point. Further analyses show that the inefficiency was attributed to inefficient energy use in small- and medium-sized cities. Our analysis provides strong scientific support for China's ongoing energy conservation and environmental protection policies. [ABSTRACT FROM AUTHOR]

With rapid industrialization, rising fossil fuel consumption, and environmental concerns, developing clean and green energy is an inescapable option. Hydrogen has emerged as a significant potential energy carrier and a viable future replacement fuel for fossil fuels due to its renewable and pollution-free properties. Previous review papers have significantly contributed to the body of literature on the various technologies for producing hydrogen by revealing key insights into their working principles and conditions, as well as the economic and environmental aspects. In addition, they also highlighted the potential pathways to enable the application of these technologies in the context of carbon neutrality. However, these studies have not broken down the evolutionary patterns and developmental progress of either fossil fuel-based or renewable energy-based technologies used to produce hydrogen. In addition, the currently available literature does not contain the most recent research that focuses on the evolution and life cycle of each technology category from a chronological point of view. The key drivers, countries/regions, and their contributions to the field's development have received little attention. As a result, it is critical to monitor technological advances in hydrogen energy production and investigate the key enablers of these advancements. Against this backdrop, the current study employs patent analysis tools to achieve four primary goals: (1) to track the development trends in the field of hydrogen production from 2000 to 2019; (2) to identify and compare the recent development trends in the last five years according to the feedstock, i.e., fossil fuel, water, and biomass-based technologies; (3) to predict the technology life cycle of the two main groups of hydrogen production technologies (fossil and renewable); (4) to identify and compare the key drivers of hydrogen production technologies from a statistical standpoint. The findings of the study may aid in identifying technical prospects in the field of fossil and renewable-based hydrogen production, and decision-makers may use them as a reference in developing a strategic plan for future technological growth. • Patent review on hydrogen production technologies from 2000 to 2019. • Japan, US, China are the leading countries in the field. • Recent developments are focused on renewable energy-based technologies especially water. • Technology maturity rate of renewable-based technologies is about 57%. • R&D expenditure strongly promotes hydrogen production innovations. [ABSTRACT FROM AUTHOR]

The main contradictions in Chinese society have changed as China enters a new era, and the people's pursuit of the better life has become more intense. This study explores how energy poverty can be addressed from a digital perspective in the context of the booming digital economy. This study analyzed the impact of mobile phone use on energy poverty by constructing an OLS model using micro data from Tibetan farming and pastoral areas. We also conduct tests for endogeneity, robustness, heterogeneity, and influence mechanisms. The results indicate that mobile phone use has a significant negative impact on energy poverty, and the results remain robust after instrumental-variable regression. In terms of economic utility, mobile phone use reduces energy poverty by increasing household consumption or off-farm income. In terms of social utility, mobile phone use can also alleviate energy poverty by raising social capital. Heterogeneity analysis shows that mobile phone use contributes to energy poverty alleviation in a way that benefits the poor and the less educated. The authors investigate the impact of mobile phone use on Energy Poverty, a topic that has previously been little addressed in academia. The findings of this paper enrich the literature on the digital technology and energy poverty and provide a new perspective for alleviating energy poverty in rural areas and improving farmers' well-being. Finally, this paper offers some policy recommendations. • The use of mobile phones by farmers and herdsmen can alleviate energy poverty. • mobile phone use contributes to energy poverty alleviation in ways that benefit the poor and the less educated. • The social and economic utility brought by the use of mobile phones can help farmers and herdsmen alleviate energy poverty. [ABSTRACT FROM AUTHOR]

Although energy poverty has obtained wide focus in recent years, there is no consensus on the measurement of energy poverty. Given that China is experiencing socio-economic transformation as well as energy transition, this paper employed a total of 28 indicators, which representing three categories (energy service availability, energy consumption and generation cleanliness, and residential energy affordability and efficiency) that capture China's features as well as consider policy factors, to develop a new multi-dimensional energy poverty index by using entropy weight method. The result reveals that the energy poverty level has been improved nationwide for the period 2014–2019; three sub-indices also show downward trends while household energy affordability and efficiency suggests the fastest improvement; however, significant differences exist in energy poverty not only between urban and rural areas but also across provinces in China. Policy recommendations are as follows: continue to promote rural power grid renovation and upgrading and the construction of natural gas pipelines, increase clean energy support; encourage diversified development of rural energy supply methods, and provide more innovative and diversified green energy and financial products. • An integrated energy poverty index system for China was established. • A total of 28 indicators used in this paper are applicable to China's features as well as considering policy factors in China. • The energy poverty level has been improved nationwide from 2014-2019, and all three sub-indices show downward trends, but varies greatly between urban and rural areas and across geographic regions [ABSTRACT FROM AUTHOR]

This paper explores opportunities for effective policy intervention for residential energy savings in southern China, by analyzing achievable potential of residential energy savings in the city of Xiamen as a case study. In contrast to static technical and economic potential analyses, the achievable potential analysis is based on dynamic energy consumption projections, which consider two real-world factors: (1) gradual ramping-up adoption process of advanced technical measures; and (2) consumers’ adoption of these measures. A bottom-up type Residential Energy Consumption (REC) projection model specifically tailored for southern China was developed in this paper, based on the general logic and calculation principles utilized in the U.S. EIA’s “National Energy Modeling System (NEMS),” and the adoption theory of advanced technical measures proposed by Kastovich. This REC projection model was then used as a policy analysis tool to quantitatively evaluate the impact of various policies on residential energy savings in the case study city of Xiamen. The analysis of the Xiamen case shows that although there is a significant technical potential for residential energy savings in the city (about 20.9–24.9%), the maximum achievable potential (MAP) in 2020 is only about 8.3–8.4% of that year’s business-as-usual baseline consumption. Moreover, with existing policies only about one-fourth to half of the calculated MAP is likely to be achieved by 2020. These findings indicate that in order to realize a larger share of achievable potential for residential energy savings in China, additional and more effective polices are needed. [ABSTRACT FROM AUTHOR]

Renewable energy is regarded as an effective method to alleviate environmental pollution and accelerate the green transition in China. This paper systematically investigates the impact of financial inclusion on renewable energy demand by using S-GMM model based on provincial data in the green finance era. This paper also analyzes the asymmetry, heterogeneity, and mediating mechanism in the nexus between financial inclusion and renewable energy demand, and highlights the following findings: (1) Improved financial inclusion can promote renewable energy development in China and present the characteristics of green finance; (2) the impact of financial inclusion on renewable energy demand is asymmetric and heterogeneous; specifically, this impact is much higher in northern China and the regions with higher renewable energy development; and (3) wind and photovoltaic power generation are effective mediators between financial inclusion and renewable energy industry, while the mediation effects of hydropower and nuclear power are not significant. New evidence in this study is presented for the achievement of green transition in China, as well as practical policy implications for improving financial inclusion and increasing renewable energy consumption. For instance, fiscal and tax incentives and green investment subsidies in the renewable energy sector need to be further improved. • This study explores the impact of financial inclusion (FI) on renewable energy demand (RED) in China. • Asymmetry, heterogeneity, and the mediating mechanism are further discussed. • Increased FI can promote RED , which presents the characteristics of green finance. • The impact of FI on RED is asymmetric and heterogeneous. • Wind and photovoltaic power are effective mediators between FI and RED. [ABSTRACT FROM AUTHOR]

• The informal sector can play a role in sustainable development. • Competition from the informal sector can significantly improve the energy efficiency of formal firms, and this result is robust. • Instrumental variable and property score matching method are used to address possible endogeneity issues. • Innovation has a significant mediating effect. Based on micro-evidence, this paper investigates the role of the informal sector in sustainable development. In particular, this paper examines the impact of competition from the informal sector on the energy intensity of firms based on Chinese manufacturing enterprise data. The results indicate that firms reduce their energy intensity in the face of fiercer competition from the informal sector. Competition from the informal sector has a more obvious effect on reducing energy intensity especially for firms with higher energy intensity. The subsample regression results imply prominent regional and enterprise ownership heterogeneity. The mechanism test indicates that competition from the informal sector reduces firm energy intensity by promoting the product innovation, production cost innovation, R&D (Research and Development) activities of formal firms. However, there is no evidence of a crowding-out effect, that is, competition from the informal sector has not been found to squeeze out firms' output and reduce energy intensity. [ABSTRACT FROM AUTHOR]

The problem of global warming is getting more serious, and vehicle emission is the main cause. In recent years, the number of locomotives in China has been increasing at a rate of more than 20% per year, and the problem of automobile pollution is becoming more serious. The transportation industry is the main source of fossil fuel combustion and environmental pollution. Therefore, in this paper, we propose a multi-view deep neural network (MVDNN) to analyze the key factors affecting the fuel consumption of automobiles. The experiments show that the introduction of human input improves the prediction accuracy and the root mean square error (RMSE) achieves 0.993. In addition, this paper also finds that for drivers, driving habits, driving frequency, and safety awareness are the most important factors affecting the fuel consumption of vehicles by combining Lasso regression with MVDNN. Finally, by comparing the prediction accuracy of different experiments, relevant policy suggestions are made. [ABSTRACT FROM AUTHOR]

Single-rate pipeline prices have resulted in low competitive flexibility and have led to high costs and consumption in China's refined oil logistics system. This study aims to propose a framework for multi-product pipelines supplementary pricing strategy that creates a win-win situation for both shippers and pipeline carriers while quantifying economic, energy and environmental performance. Based on the objective of cost minimization, a lower limit constraint on pipeline transportation quantity is added, and a discount coefficient is introduced for pipeline prices, thus improving the transportation optimization model. Moreover, this paper develops an implementation approach for a supplementary pricing strategy that can ensure that the discounted price is not lower than the sum of cost and minimum profit. This framework usability is confirmed using a Chinese oil company as an example. The results show that the optimal scheme can increase pipeline revenue by ¥79.8 million while reduce shipper's logistics costs by ¥1.68 million during the practice cycle. Meanwhile, this work reduces energy consumption by 1.37 tce, CO 2 emission by 444 tons, SO 2 emission by 5.65 tons, and NO X emission by 7.07 million tons for the logistics system. Compared with past studies, this study is more economical or more in line with market-oriented behavior. • A framework for 3E performance improvement of multi-product pipelines is proposed. • The improved transportation optimization model is used as a pricing tool. • A supplementary strategy implementation approach is defined. • Total economic benefit to shippers and pipeline carriers is ¥9.66 million. • The energy and environmental benefits of the logistics system are quantified. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of import competition on energy efficiency among firms in China. Using a difference-in-differences approach that exploits industry- and firm-level tariff reductions following China's accession to the WTO, we examine the effects of reduced output tariffs on coal intensity, measured as coal use per output, of Chinese manufacturing firms. Our findings indicate that higher levels of import competition lead to significant reductions in coal intensity, without negatively affecting firm production levels. We also find evidence that these effects are primarily driven by multi-product firms adjusting their product mix to prioritize energy-saving options. [ABSTRACT FROM AUTHOR]

It is well known that energy forecasts play an important role in guiding energy policy, economic development and technological progress. Therefore, based on the purpose of energy consumption and production forecasting, this paper proposes a novel structure adaptive discrete grey Bernoulli model, which is innovative in terms of both accumulated generating operator and model structure. In terms of accumulated generating operator, a new fractional order accumulated generating operator is proposed in this paper. The new accumulated generating operator has a different information priority by adjusting the values of the parameters. In terms of model structure, a novel discrete grey Bernoulli model is proposed in this paper. The novel model is well adapted to time series data containing nonlinear information, and can well mine and utilize the information contained in the original data. In addition, the Particle Swarm Optimization (PSO) algorithm was chosen to optimize the model parameters based on algorithm comparison experiments. This enables the model to flexibly adapt to a variety of complex data and has the ability of structure adaptive. Moreover, this paper conducts comparative experiments between the novel model and eight other forecasting algorithms for time series data. The numerical results show that the novel model has better forecasting performance for the data of China's total energy consumption, China's total electricity generation and China's total domestic electricity consumption. In addition, for the model reliability problem caused by the optimization algorithm, the stability and accuracy of the model are verified by Monte Carlo simulation and probability density visualization analysis. Finally, the proposed model predicts the future development trend of energy consumption and production in China. • A novel structural adaptive discrete grey Bernoulli model is established. • The proposed model can grasp nonlinear and fluctuant in various datasets. • The robustness analysis of the novel model is established. • Comparative study shows that the novel model is superior to other models. • Relevant suggestions are put forward according to the prediction results. [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

Solid fuel use is harmful to the health of human beings and hinders the sustainable development of society. Although a considerable literature has sufficiently researched the negative consequences of solid fuel use, fewer studies have explored the determinants of residential polluted energy use in the framework of culture and socioeconomics by focusing on ethnic diversity groups. This paper fills this gap by investigating the impact of religion on the decision to use solid fuel for rural households in ethnic minority regions of China. In particular, we argue that to a large extent, religion provides spiritual support in ethnic minority regions, and it is positively associated with solid fuel use. We examine the issue by employing a large-scale dataset, namely, the China Household Ethnic Survey. Furthermore, this paper identifies two channels of the above finding. First, a pension is regarded as a living support that has a moderate effect in shifting towards clean energy adoption. Second, households located in less remote regions are able to counteract the sole spiritual support of religion, which also mitigates solid fuel use. The results are robust after addressing endogeneity and applying recent developments of alternative models. This paper further confirms that households with various religious activities turn out fewer working hours and have larger related expenditures, which results in less disposable income for energy use. In terms of policy implications, this article suggests the importance of recognizing the role of substantial living support and social inclusion in mitigating the negative impact of religion on clean energy use among rural households of ethnic minority regions. [ABSTRACT FROM AUTHOR]

Promoting energy transformation in rural areas, building a Rural Integrated Energy System, and developing multi-energy complementary and comprehensive utilization of rural energy in accordance with local conditions are important paths to support global low-carbon transformation and rural revitalization. However, how to consider the coupling synergy of multiple devices and plan the capacity of multiple devices in rural energy systems in an economical, low-carbon, and reliable manner is an urgent issue facing the development of Rural Integrated Energy System. This paper proposes a bi-level programming optimization method of Rural Integrated Energy System based on coupling coordination degree of energy equipment. Firstly, a multi-dimensional rural user energy utilization framework is designed that comprehensively considers agriculture, animal husbandry, industry, and lifestyle. Secondly, the bi-level optimization model of the Rural Integrated Energy System based on the coupling coordination degree of energy equipment is constructed. The upper-level planning model puts forward the equipment coupling coordination degree, and determines the equipment selection scheme for different types of Rural Integrated Energy System planning. The lower-level planning model considers economy, low carbon, and reliability, and uses the improved multi-objective Harris Hawk optimization algorithm to solve the capacity of different energy equipment in the Rural Integrated Energy System. Finally, the effectiveness and scientific nature of the model and method proposed in this paper are verified by the Integrated Energy Systems of a rural area in the north of China. In addition, by comparing the equipment selection scheme with the traditional method, it can be found that the optimization scheme in this paper that considers the coupling coordination of energy equipment reduces the annualized total cost by 29.34 %, reduces the annual carbon emissions by 60.43 %, and increases the reliability by 15.85 %. The collaborative planning of energy economy, low carbon energy and reliable energy has been realized. • A framework for the utilization of energy by multiple users in rural areas was designed. • A bi-level programming optimization method of RIES based on coupling coordination degree of energy equipment was proposed. • An improved multi-objective Harris Hawk optimization was constructed. [ABSTRACT FROM AUTHOR]

To identify the influence of digital transformation on energy consumption, this paper introduces digitalization and energy elements into the multi-sector energy efficiency analysis model. Furthermore, this paper empirically tests the influence of digital transformation on energy efficiency from the micro level. The results show that the digital transformation indeed improves the enterprises energy efficiency, in which enterprises with higher energy efficiency are more affected. The improvement effect of digital transformation on enterprise energy efficiency continues to increase over time. In comparison, digital transformation shows more effective improvement effect on energy efficiency in enterprises that substantive transformation priority, with same group and maturity stage. Mechanism analysis shows that digital transformation can improve the energy efficiency of enterprises by reducing costs, increasing income, improving production efficiency and promoting technological innovation. In addition, the digital inclusive finance, government subsidies, intellectual property protection and service industry opening show positive regulatory effects. This paper proposes that, with the goal of peak carbon dioxide emissions and carbon neutrality, enterprises should actively increase digital investment and strengthen digital management of energy utilization. [Display omitted] • Digital transformation indeed improves the enterprises energy efficiency. • The promotion effect of digital transformation increases over time. • Digital transformation drives efficiency improvement and technological innovation. • Digital transformation contributes to cost reduction and benefit increase. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the water-energy-food nexus (WEFN) system, focusing on its interlinked structure and dynamic characteristics. This paper proposes a dynamic series-loop data envelopment analysis (DEA) model with a directional distance function for measuring WEFN efficiency in China. A spatial Durbin model is constructed to investigate the impact of extreme temperatures on WEFN efficiency. The results are as follows. (1) Compared with the black-box DEA model and series network DEA model, a series-loop network DEA model can reflect the "networking effect" and "looping effect" in the WEFN system. (2) The WEFN system performs well with an average series-loop efficiency of 0.875, but the efficiency of the water subsystem scores low and needs improvement. (3) At the national level, extremely high and low temperatures have no significant effect on the WEFN efficiency in local or adjacent provinces, whereas average temperature promotes the WEFN efficiency in local provinces but hinders it in neighboring provinces. In the regions with a low temperature difference, average temperature has no impact on the WEFN efficiency of both the province itself and its neighboring provinces. Overall, this study provides valuable insights into the complex interlinkages within the WEFN system and highlights the importance of considering these relationships when improving the system efficiency. [ABSTRACT FROM AUTHOR]

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

Using panel data of 11 provinces in the western region of China, the paper empirically analyzes the influence of public environmental participation on the effectiveness of pollution governance. Based on documents from provincial governments in Western China, the paper uses Nvivo software to extract keywords about local governments' attention to the environment and examines its mediating effect between public environmental participation and pollution governance. Furthermore, a classifiable analysis of government environmental attention is carried out, and the effect of local governments' attention to the environment on pollution governance is studied. The results show that public environmental participation promotes pollution governance by increasing the governments' attention to the environment. Additionally, local governments' environmental attention also has a promotive effect on pollution governance, and the increase in environmental decision-makers' attention to environmental pollution and energy consumption is conducive to the improvement of environmental quality, but the effect of environmental protection and collaborative attention on environmental quality improvement still needs to be explored further. • Local governments' attention to the environment is estimated. • Public environmental participation promotes pollution governance. • Local Governments' Environmental Attention plays mediating role. • Local Governments' Environmental Attention has a promotive effect on environmental quality. • The effect of collaborative attention on environmental quality improvement still needs to be explored further. [ABSTRACT FROM AUTHOR]

Cities have emerged as critical and challenging places for promoting the green and low-carbon transformation of the economy and society in the context of the "dual carbon" targets. Meanwhile, fiscal policy is also an indispensable component of the public policy framework supporting the green and low-carbon transformation. This paper uses the pilot project of "Comprehensive Demonstration Cities for Energy Conservation and Emission Reduction Fiscal Policies" ("ECER-CD" policy) implemented in China since 2011 as a quasi-natural experiment. This research theoretically analyzes and empirically tests the energy conservation and emission reduction effects of fiscal policies supporting green and low-carbon transformation utilizing methodologies such as time-varying DID and multiple periods and multiple groups of DID. The study finds that the pilot cities effectively reverse the behavioural bias of local governments and promote energy conservation and emission reduction efforts. This conclusion holds after undergoing robustness tests such as parallel trend analysis and heterogeneity treatment effects. The effectiveness of the pilot policy is attributed to the upgrade of industrial structure, improvement of energy efficiency, and the effects of green technology innovation. However, cities' geographic location and resource dependency can interfere with the effective implementation of policies. This paper also further explores the environmental dividends and economic consequences of the policy and finds that the pilot cities have certain environmental dividends and do not significantly restrain economic and social development. This study broadens the research perspective on fiscal policies in energy conservation and emission reduction and clarifies the pathways through which fiscal policies promoting green, low-carbon transformation drive energy conservation and emission reduction in cities. Moreover, it also improves the use of the Difference-in-Differences method in evaluating policy effects in scenarios such as the overlapping implementation of pilot policies and policy withdrawal. Finally, this paper proposes policy recommendations to provide more empirical evidence for China to accelerate the green and low-carbon transformation of the economy and society. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

The safety of production and the health of on-site workers are greatly affected by dust pollution in metal mines. In recent years, wet-type and bag-type dust collectors with high efficiency have been widely used for dedusting. However, a series of problems exist, such as high resistance, and high energy consumption. This paper presents a review of the research and development regarding occupational hazards and dust control/removal methods in metal mines in China. First, it introduces the occupational hazards of dust in metal mines and discusses the pathogenic mechanism and sources of dust. Then, several dust control methods, including ventilation, sealed, spray, dust suppressant, and curtain dust isolation are examined. Additionally, this paper discusses the difficulties in the development of dust control in China. Finally, some valuable suggestions are made for future development on dedusting measures in metal mines. This review provides references for scientific and green mining in China. [Display omitted] [ABSTRACT FROM AUTHOR]

• The solar potential in different residential blocks is simulated. • The influences of block morphological parameters on solar potential are varified. • Four parameters that impact on the block solar potential more than 70% are verified. • The facade PV capacity in high-rise and hybrid residential blocks is more than 66%. • The average PV installation rate of roof, south and west facade is 96%, 32% and 39%. Block-scale application of photovoltaic technology in city is becoming a viable solution for renewable energy utilization. Rapid urbanization process has made urban buildings have huge development potential for solar energy in China, especially in residential areas that occupy large parts of the city. However, the residential blocks in China show differences in the morphological layout and parameters, which means they have diverse potential for solar energy development. This paper studies the effect of quantified morphological parameters on solar potential for residential blocks in Wuhan, China. The distribution characteristics of solar potential in different block environments are discussed. Various strategies are evaluated in terms of the installation position and height of PV modules. The results showed that floor area ratio, building density, average building height and building interval have significant impact on solar potential for residential block, and their correlation can reach 75%, 71%, 78% and 72% respectively. The average PV installation ratio of roof, south facade and west facade can reach 96%, 32% and 39% respectively. The results of this paper not only provide a reference to the block-scale application of PV technology in urban environment, but also stimulate the implementation of photovoltaic policies on various residential blocks in China. [ABSTRACT FROM AUTHOR]

The rapid development of China's economy has driven the growth of energy consumption. However, the domination of the energy structure by fossil energy not only increases carbon emissions but is also an important source of fog and haze in China. This will cause global warming and increase people's lung diseases. To alleviate these problems, renewable energy (RE) development is crucial in reducing CO 2 emissions, promoting economic development, and reducing fog and haze in China. Industry accounts for the highest proportion of energy consumption, so an efficient adjustment of the industrial structure will greatly contribute to overall energy development, economic development, and environmental protection. By analyzing the sales output value of China's industrial subsectors, together with energy consumption and CO 2 emissions, this paper determines which industries should be encouraged and which industries should be restricted in China. Finally, RE strategies and industrial policies are proposed for Chinese government references. The contributions of the paper are three-fold: (1) propose a novel framework for the development of China in the aspects of energy, economy, and environmental policies; (2) provide valuable information for the Chinese government to enable it to understand which industries should be encouraged to improve its economic competitiveness; and (3) use hybrid methods (e.g., entropy method and weighted sum method) to rank the energy and CO 2 productivity, and the recommendations will provide strategic guidance for China's energy development. [Display omitted] ● China's Renewable Energy Strategy and Industrial Policy. ● Which industries should be encouraged or discouraged in China. ● Energy Productivity and CO 2 Productivity. [ABSTRACT FROM AUTHOR]

The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected. Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors. [ABSTRACT FROM AUTHOR]

The essence of industrial chain structure optimization is to strengthen the synergy and division ability among sectors. It is a crucial factor in reducing energy intensity and achieving carbon neutrality goals. This paper completed the China's non-competitive input-output table from 2000 to 2020, constructed industrial synergy and division index using structural path analysis method and examined its development trend. Combining with a two-way fixed effects model, we explored the influence of industrial synergy and division on energy intensity. The research found that China's industrial synergy and division development level shows an upward trend. The proportion of the low-layer industrial chain decreases, and the peak contribution rate moves to the high-layer industrial chain. Secondly, industrial synergy and division significantly reduces sectoral energy intensity, the results are robust after endogeneity test. Finally, heterogeneity analysis showed that industrial synergy and division can reduce the energy consumption intensity of all sectors, and it is more obvious for sectors with high energy dependence. This research can provide targeted policy suggestions for China to optimize its industrial structure. It also has a reference significance for other countries. • The impact of industrial synergy and division on energy intensity is explored. • This paper extracts China's non-competitive IO table from the global MRIO table. • SPA is applied to construct industrial synergy and division index. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [ABSTRACT FROM AUTHOR]

Under the background of "carbon neutrality" and "carbon peak" concepts, China desires to develop a new power system based on renewable energy sources (RES), which will be the primary energy support in prospective China. Thus, it is imperative to improve the peak shaving capability of power system to address the problem of random fluctuation and intermittency of RES by developing various energy storage systems. An innovative approach to enhance the flexibility of the conventional thermal power unit (TPU) through the utilization of flywheel energy storage array (FESA) is presented, simulated, and evaluated in this paper. Using the relatively practical and specific model of TPU and FESA, modified frequency modulation and automatic generation control (AGC) instruction tracing operation scenario models are constructed. A comprehensive control strategy of FESA and a well-designed operation coordinated control method for TPU with FESA are proposed and applied. The simulation results are distinctively processed and evaluated by the methods in "two documents", aiming to assess the real-world operation performance of the model proposed in this paper. The comprehensive analysis of the indicators demonstrates that the FESA can improve the flexibility and economy of the units. This research may guide the usage of FESA to improve the operational flexibility of TPU. • Composition and Control Methods of the flywheel energy storage array are provided. • A coordinated control scheme for the thermal power unit with flywheel energy storage array is proposed. • Frequency modulation and AGC instruction tracking scenario models are constructed and simulated. • AGC regulation indicators are conducted and analyzed to evaluate the unit's performance. [ABSTRACT FROM AUTHOR]

Addressing energy poverty and promoting energy equity are crucial for China to eradicate poverty comprehensively and achieve shared prosperity. Through a combined dynamic evaluation approach to accurately measure the extent of energy poverty, this paper analyzes the staged time series, spatial distribution characteristics of energy poverty applies the Dagum Gini coefficient and variance decomposition to observe the imbalance characteristics of energy poverty and identify the sources of variation. The objective of this paper is to mitigate the influence of spatial disparities on coordinating efforts to eradicate energy poverty across different regions. Consequently, provides valuable insights for decision-making to effectively eradicate energy poverty and expedite the achievement of energy equity. The results indicate: The reduction process of energy poverty in China exhibit phased characteristics from 2000 to 2020, with significant variations in reduction levels among provinces. Different sources of energy poverty exhibits imbalanced spatial distribution and evolution. The overall disparity in energy poverty widens as the phases progress, with characteristic nodes experiencing a temporal delay of 2–3 years compared to the policy nodes. Inter-regional disparities are the primary spatial source of energy poverty differences, while energy use capacity is the main factor contributing to variation. [ABSTRACT FROM AUTHOR]

The operation of tidal pumping station has an energetic impact on energy course of massive water pumping for a long time. Thus, a multi-objective optimal operation model was developed to optimize the operation scheme and reduce the energy consumption of the tidal pumping station. In the model, a day is divided into several sub-periods according to the regulation of water level in tidal reach. The partition of sub-periods, the number and blade angle of operating units in each sub-period are adjusted to minimize daily operation energy consumption. And the less switching times, the better the reliability and durability of the unit, the lower the failure rate. Therefore, the reduction of wearing parts' service life is quantified for each switching time in the form of cost. A case study is performed with the tidal pumping station of the South-to-North Water Transfer Project in China. In this paper, energy consumption and switching times are quantified as costs respectively, and the result shows that the daily energy consumption could be saved about 2.28%–6.56%, and the switching times reduced at least 60%. Therefore, this paper could provide an effective optimal operation scheme for the tidal pumping station whose operation is affected by tides. [ABSTRACT FROM AUTHOR]

• Integrated and flexible carbon capture power plants (IFCCPPs) are analyzed. • A system model is established that connects the IFCCPP, power-to-gas, and wind farms. • A two-stage low-carbon scheduling model is constructed considering demand response. • Reward and punishment ladder-type carbon trading has stricter limits on emissions. • The proposed model has advantages in reducing abandoned wind, emissions and cost. At present, coal-fired thermal power still dominates in China, and as the environmental pollution problem worsens, it is critical to find the optimal combination of coal and new energy to reduce CO 2 emissions and promote new energy consumption. Based on this, this paper considers a reward and punishment ladder-type carbon trading mechanism, firstly, unit transformation of the conventional coal power plant (CPP) on the power side, forming the integrated and flexible carbon capture power plant (IFCCPP), and constructing a coupling model of the IFCCPP with power to gas (P2G) equipment and wind farms(WFs), forming an IFCCPP-P2G-WF system; secondly, introducing a price demand response mechanism on the load side, and establishing a two-stage scheduling model for the IFCCPP-P2G-WF system, with the first stage model aiming at the minimum sum of squared load fluctuations and the second stage model aiming at the minimum operation cost. Finally, the effectiveness of the scheduling model proposed in this paper is validated by comparing and analyzing the scheduling results under eight scenarios. When compared to other models, the proposed model significantly increases wind power consumption, reduces carbon emissions, and lowers operation cost, all of which have advantages. [ABSTRACT FROM AUTHOR]

Building integrated photovoltaic (BIPV) is a promising solution for providing building energy and realizing net-zero energy buildings. Based on the developed mathematical model, this paper assesses the solar irradiation resources and BIPV potential of residential buildings in different climate zones of China. It is found that roofs are the first choice for BIPV installation, followed by south façades, especially in high-latitude cities, and then east and west facades. North façades could be recommended in some cities with frequent clouds. The photovoltaic (PV) contribution of a combined rooftop and south façade BIPV system to building energy is highlighted, where the PV covers 50 % of the roof and 40 % of the south façade area. The system can meet the net load of a 4, 8, 7, 6, 4, and 4-storey building in Harbin, Urumqi, Beijing, Shanghai, Chengdu, and Guangzhou, respectively. In areas with sufficient irradiation and low demand, such as Lhasa and Kunming, the proposed system is most likely to achieve net-zero energy consumption in high-rise residential buildings. Different from previous study, this study proposes a comprehensive research framework for assessing the potential of residential BIPV system in various regions of China, considering partial shading effects. Since many provinces have issued relevant policies to promote distributed PVs, the findings can provide guidance for BIPV deployment in China. [Display omitted] • The solar irradiation resources of building façades including the north façade are examined. • The photovoltaic contributions to net zero energy residential buildings are assessed in China. • Partial shading is considered for modeling the building integrated photovoltaic (BIPV) system. • A research framework for assessing the potential of residential BIPV system is proposed. [ABSTRACT FROM AUTHOR]

China is facing the challenge of high building energy consumption, especially for rural housing, because of the backward construction technology. This issue could be solved by net-zero energy rural housing. Therefore, the passive energy-saving procedures and energy-efficient building service systems of rural housing are needed to be studied apart from renewable energy adoption. Older people with unique thermal acceptability and adaptability become the primary residents in Chinese rural buildings, which calls for the redefinition of the indoor environment. This paper firstly conducted an overall questionnaire about the indoor environment sensation and expectations of the rural elderly in Sichuan province. Field surveys and measurements were carried out in a typical self-built rural house to investigate the thermal comfort of the local order people and the indoor thermal environment variations. Furthermore, the fuzzy analytic hierarchy process was used to propose a three-layer assessment model for the rural elderly living environment to find retrofit strategies. Results showed that: (1) the thermal environment of rural buildings could not meet the thermal comfort range of older people in summer. (2) The adaptive coefficient (λ) in the adaptive Predicted Mean Vote model was 0.065 for the rural elderly, which was lower than the value of 0.21 in the Chinese standard, indicating their poor thermal adaptability. (3) The summer living environment evaluation was "A little bad", and the most effective optimization method was to decrease the indoor temperature. (4) Based on the thermal comfort of older people, architectural and construction optimizations were proposed, which could achieve an energy-saving of 52.15 %, contributing to net-zero energy rural housing. • Environment improvement and energy saving of rural housing were studied. • The age-based metabolic rate of the elderly was proposed in aPMV. • The adaptive coefficient for the rural elderly was 0.065. • The evaluation model of rural living environment satisfaction was built by FAHP. • Passive retrofit procedures were proposed to achieve NZERH. [ABSTRACT FROM AUTHOR]