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At present, the energy and environmental crisis is increasingly prominent, and how to solve the global energy and environmental problems is one of the challenges facing the world today. China is a major producer and consumer of organosilicon, so it is necessary to explore the stage of high energy consumption and high pollution in the organosilicon industrial chain. In 2022, the proportion of submerged arc furnaces of 25000 kVA and higher in China reached 40%. Further expansion of these furnaces in the future is inevitable. However, research on the life cycle assessment of organosilicon manufactured using large-capacity submerged arc furnaces is still blank.Therefore,in this paper, the life cycle assessment method is used to evaluate the synthesis process of chemical grade silicon-organosilicon monomer prepared by large capacity (33000 kVA) submerged arc furnace, and the dominant process in various environmental impacts is defined.At the same time, the measures to improve the production process of organosilicon monomer were put forward. In the production process of 1000 kg organosilicon monomer, global warming potential (GWP) contributed the most (73.43%) to the comprehensive environmental impact, followed by chronic public health impact (HTI, 10.55%). Energy consumption (EN) accounted for 8.50%, while resource consumption (RU) accounted for 7.43%. The contributions of other environmental factors were relatively small (0.09%).The energy consumption and environmental pollution in the production of organosilicon monomer can be reduced by strictly controlling the quality of raw materials into the furnace, using heat pump technology in the distillation unit, and comprehensively utilizing the heat of reaction by-products and steam condensate. [Display omitted] • This study is the first one in China to conduct LCA for the preparation of chemical grade silicon-organosilicon monomer synthesis process in 33000 kVA submerged arc furnace. It provides the best improvement suggestions for reducing the environmental load of the product life cycle process and achieving cleaner production. • In response to the national development policy of large-scale submerged arc furnace, the dominant process of preparing organosilicon monomer based on 33000 kva submerged arc furnace in various environmental impacts was clarified. • The main technical improvement directions are: Strictly control the quality of raw materials for submerged arc furnace; Strictly control the sulfur content and nitrogen content of carbonaceous reductant, and adopt the most suitable flue gas treatment technology route; Smelt with large submerged arc furnace; Use heat pump technology for distillation unit; Optimize the monomer synthesis device. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

The industrial sector is characterized by high energy consumption and high carbon emissions. It is of great significance to clarify the determinants of industrial CO 2 emissions for emissions abatement policy making. For this purpose, a comprehensive decomposition framework that can quantify the impacts of both oriented technologies and economic factors on CO 2 emissions is developed. By applying the proposed decomposition framework, this paper investigates the determinants of China's industrial CO 2 emissions. The main findings show that, during the study period, (1) investment scale expansion was the leading factor promoting emissions growth; (2) against our expectations, efforts for energy structure adjustment failed to curb emissions but had marginal promoting effects on emissions growth; (3) energy-oriented and output-oriented technologies were indispensable contributors to emissions mitigation, followed by decreases in investment efficiency, potential energy intensity, and the CO 2 emission coefficient; and (4) energy use efficiency and production efficiency changes usually exerted moderate influences on industrial CO 2 emissions, and their influencing directions were sensitive in different sub-industries and Five-Year Plan periods. In most situations, the inhibiting effects could not counteract the promoting effects. Based on these empirical findings, policy recommendations to further reduce industrial CO 2 emissions are provided. • Empirical analysis was conducted at sub-industries and different FYPs levels. • Investment scale was the leading factor promoting industrial CO 2 emissions. • The technology progress contributed most to emission mitigation. • Driving effects distinctly differed among sub-industries and FYP periods. [ABSTRACT FROM AUTHOR]

Improving eco-efficiency is an important way to promote environmental decoupling. Based on the input-output model and data envelopment analysis (DEA), this paper evaluates the eco-efficiency of 44 sectors in China with a new DEA model considering inter-sectoral linkages, then explores how the industrial network would be optimized as inefficient sectors become efficient under constant resources supply and constant final demand. The empirical results indicate that 22 sectors are inefficient and deserve further improvement. Inefficient sectors becoming efficient will drive the industrial network to evolve in a more intensive direction, and allow the economy to achieve greater economic benefits with less energy consumption and pollution. Accounting under constant resources supply suggests that increasing external demand should be a key to promoting environmental decoupling in the economy. Accounting under constant final demand indicates more stringent environmental regulations should be used to drive technology upgrades. • A new eco-efficiency measurement combining the input-output model and DEA is built. • The eco-efficiency and potential deficiencies of 44 sectors in China are evaluated. • The impact of inefficient sectors becoming efficient on the economy is measured. • The industrial network presents significant potential for environmental decoupling. • Key constraints to environmental decoupling in the industrial network are identified. [ABSTRACT FROM AUTHOR]

The construction sector is an important industry in China's economic development and energy consumption, and research on its energy efficiency has attracted increasing attention from researchers. Currently, the traditional data envelopment analysis (DEA) model ignores the competition among regions, resulting in inaccurate estimation of efficiency. This paper employed traditional DEA, cross-efficiency DEA and game cross-efficiency DEA approaches to measure the energy efficiency of the construction industry in 30 of China's provinces from 2005 to 2016. The temporal trend and spatial distribution characteristics of energy efficiency determined through the game cross-efficiency method were then depicted by clustering analysis. Finally, the spatial heterogeneity of energy efficiency was analysed in detail. The results indicated that the efficiency calculated using the game cross-efficiency DEA model considering the competitive relationship was lower than the traditionally calculated efficiency and higher than the efficiency calculated using cross-efficiency DEA. Moreover, during the period of study, the energy efficiency showed a holistic growth trend with volatility. Clustering analysis demonstrated that the energy efficiency of eastern China was significantly higher than that of central and western China. Additionally, the spatial gaps in China's construction industry narrowed, while the spatial agglomerations strengthened. This paper also found a significant positive agglomeration in the energy efficiency of the construction sector in neighbouring provinces of China in the space dimension. In conclusion, province-specific policies based upon temporal and spatial heterogeneity were proposed to improve the energy efficiency of the construction industry in China. • Game cross-efficiency is first used in construction sector. • Provincial energy efficiencies of construction sector are examined in 2005–2016. • Spatial distribution characteristics of energy efficiency are depicted. • Energy efficiency is assessed in four agglomeration areas. • Positive spatial agglomeration exists in energy efficiency of construction sector. [ABSTRACT FROM AUTHOR]

Under the downward pressure of the economy, China's extensive economic growth that relies on factor input is difficult to sustain. Scientific analysis of the industrial restructuring and energy consumption has become the key to realizing China's economic growth from high-speed to high-quality. Based on the fully-modified least square method and panel vector error correction model, this paper explores the equilibrium relationship and Granger causality among the industrial restructuring, energy consumption and economic growth at aggregated and disaggregated levels. The results show that: (1) The effect of industrial structure rationalization on economic growth is higher than that of industrial structure upgrading. When emphasizing industrial structure upgrade, the more reliable industrial policy to achieve China's sustainable economic growth is to pay attention to the industrial structure rationalization, especially in western China. (2) The impacts of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption; more energy policies should be designed to encourage clean energy development. • The industrial structure rationalization has highest contribution to the economic growth of eastern China, followed by central and western China. • There exists unidirectional causality from industrial structure upgrading to structure rationalizing in western China and bidirectional causality between them in central China. • Effects of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption. • Unidirectional long-term causality from renewable energy to economic growth exist in each sub-region. [ABSTRACT FROM AUTHOR]

Petroleum refining is a technology complex, energy- and CO 2 emission-intensive industrial process, which is affected by the type and property of the crude oil. China has been the exploitation of crude oil to paraffinic most. This paper targets to quantify and evaluate the material or energy metabolism and environment loads of paraffin-based petroleum at refining process unit-level through the established petroleum flow and energy flow on the CO 2 emissions accounting framework, and explores energy conservation and CO 2 emission reduction pathways and policy implications, using a typical paraffin-based petroleum refining enterprise in China as a case. The results indicated that the crude oil from the inputs were fractionated in the atmospheric and vacuum distillation (AVD) unit, and its energy consumption and CO 2 emissions accounted for 14.38% and 13.2% of the total energy consumption and CO 2 emissions in the case study, respectively. With the transformation of petroleum refinery plant structure, fluid catalytic cracking (FCC), ketone benzol dewaxing (KBD), and delayed coking units dominated more energy consumption and CO 2 emissions. FCC unit was both the largest energy consumer and supplier, flue gas waste heat recovery efficiency of which was an important factor affecting energy conservation and CO 2 emission reduction for FCC unit and even enterprise. KBD unit records the largest energy and CO 2 emission intensities, which are 67.95 kgce/t product and 256.82 kgCO 2e /t product respectively, due to the high wax content of paraffin-based crude oil and the coal-dominated power generation structure. Based on these research findings, three mitigation policy recommendations were proposed, including the improvement of energy efficiency, optimization of energy consumption structure and product output structure. Carbon capture and storage can reduce CO 2 emission by about a third in the concentrated units of primary energy consumption (i.e. AVD, FCC, and DC). The results of this paper are key components of the life cycle assessment of the CO 2 emissions of petroleum fuels produced by domestic paraffin-based crude oil. [ABSTRACT FROM AUTHOR]

There is great interest in measuring energy efficiency of China's industry using data envelopment analysis (DEA) approaches. This paper proposes a new exponential transformation of undesirable outputs into desirable outputs as part of a DEA approach for calculating environmental efficiency by using all kinds of classic models. Different from the existing transformations, the exponential model should provide a more flexible way to deal with undesirable outputs, allowing the user to adjust the slope and distribution of the transformation function by setting a parameter. A strategy for maximizing the standard variance among the undesirable outputs after transformation is employed in this paper to determine the optimal parameter value for the exponential model. This paper empirically examines the energy performance of sectors in Chinese industry from 2010 to 2014 using the proposed DEA model and the results show that most sectors in Chinese industry have not performed well, especially the sectors concerned with energy extraction. Based on the results of the efficiency evaluation, this paper calculates how can each sector achieve efficiency improvement through energy conservation and emission reduction, and propose specific improvement target values for each sector accordingly. Image 106227 • Alternative approach is constructed to deal with undesirable output in DEA models. • A new transformation is provided to reflect the exponential relationship between desirable and undesirable outputs. • The slope and distribution of data under the new transformation function are controllable. • The new presented approach is applied to measure the performance of 38 industries in China. [ABSTRACT FROM AUTHOR]

PM 2.5 emissions has become a serious issue in China with enormous regional variation in economic development, resource endowment, and consumption patterns, which leads to great variations in regional PM 2.5 emissions and embodied PM 2.5 transfer among provinces. The spatial and temporal evolution pattern of PM 2.5 and its influencing factors are important issues in the study of air pollution emissions and control, which could help policy makers allocate emission responsibilities and reduction targets. Based on the perspective of final consumption, this paper uses a multiregional input-output model to estimate PM 2.5 emissions in 30 provinces in different years in China, applies a geographically weighted regression model to analyze different driving factors, and then analyzes the spatial heterogeneity of consumption-based PM 2.5 emissions. The results show that consumption-based PM 2.5 presents a significant reduction trend, although the separation of production and consumption areas of PM 2.5 emission is further intensified. The provinces with rich energy but relatively backward economies and manufacturing industries correspond to the primary net inflow of PM 2.5 , while the provinces with strong consumption ability and the most developed economies and industries present a net outflow of PM 2.5. Moreover, the slowdown of consumption growth and the improvement of consumption quality have a positive impact on PM 2.5 emission reductions. The optimization of industrial structure has a more significant impact on pollution control and haze reduction in the western region, while the improvement of energy utilization efficiency and rational use of construction land are more conducive to the reduction of consumption-based PM 2.5 emissions in the eastern region. From the perspective of temporal and spatial changes, significant spatial differences occur between regions. Energy consumption, environmental protection investment and construction land show the trend of " high value area diffusion and low value area reduction". • Explores the spatial distribution characteristics of PM 2.5 emissions in China from the perspective of consumption. • Consider and analyze the inter-annual variation of pollutant emission transfer. • Clarifies the spatial heterogeneity characteristics of influencing factors. • Emphasizes the importance of further optimizing influencing factors to reduce haze from the consumption end. [ABSTRACT FROM AUTHOR]

China launched seven emissions trading scheme (ETS) pilots in 2011, and a national ETS, at the end of 2017 in an attempt to reduce its greenhouse gas emissions (GHGs) and drive its extensive energy transition in a cost-effective way. The Hubei province pilot ETS has operated since 2014, and an analysis of its effectiveness can provide lessons for the nascent national system. This paper disaggregates Hubei's industrial carbon dioxide (CO 2) emissions from 2005 to 2018 into economic scale, economic structure, energy efficiency, and energy structure effects using the logarithmic mean Divisia index (LMDI). Difference-in-difference (DID) models then assess the implementation effectiveness of this ETS, and its impact on the main influencing factors of the LMDI. Ten cities each in the Hubei and Hunan provinces are selected as treatment and control groups, respectively, in the DID models. Results show that the change in industrial CO 2 emissions is mainly due to the economic scale and energy efficiency effects. After the ETS implementation, the energy structure effect has a limited impact on emissions, while the economic structure effect makes a negligible contribution. Moreover, the implementation of the ETS has had little demonstrable impact on industrial CO 2 emissions, gross domestic product (GDP), energy consumption intensity, and CO 2 emission intensity. This lacking of impact is caused by the GHG monitoring capacity deficits of the local Development and Reform Commission, and irrational quota allocations. Effective supervision and quota allocation should be developed to increase the impacts of the ETS. [ABSTRACT FROM AUTHOR]

Global warming and climate change have become a common concern to all countries in recent years. As an industrial sector with high energy consumption, the construction sector is facing enormous pressure to reduce carbon emissions. Given the continuous integration of the world economy, the construction sector in each country has extensive linkages with other sectors and countries. By using a multi-regional input–output (MRIO) model and hypothetical extraction method (HEM), this paper aims to further decompose the CO 2 emission linkages of the global construction sector from consumption-based and production-based perspectives in order to identify the key sectors and regions related to global trade. Based on data from the World Input–Output Database from 1995 to 2009, the results indicate that the average internationalization ratios of the net backward linkage and the net forward linkage of the global construction sector increased from 37% to 46% and from 16% to 20%, respectively. The global construction sector mainly imported CO 2 emissions from secondary industry and the transportation industry. The construction sector exported small amounts of CO 2 emissions to other sectors both domestically and internationally. The CO 2 emission flows embodied in the international trade of the construction sector mainly occurred between the USA, China, Russia, Germany, and the Rest of the World (ROW). The construction sectors of the ROW imported the largest amount of CO 2 emissions from China (32.72 Mt). The largest exported CO 2 emission flow was between the construction sectors of the USA and the ROW, with a value of 0.091 Mt. Based on these findings, some corresponding countermeasures are suggested, such as optimizing international trade structures, establishing a mechanism for both consumers and producers to share responsibility for carbon emission reduction, applying new environmental materials, and upgrading industrial structures by reducing dependence on high-pollution sectors. [ABSTRACT FROM AUTHOR]

Excessive CO 2 emissions from energy combustion are the main cause of the global greenhouse effect, while the energy consumption in China's heating and power industries account for more than a half of national energy consumption. Based on this, to more accurately implement carbon emission reduction in heating and power industries, we studied the evolution and driving factors of the carbon emission structure in these industries between 2007 and 2015 from supply-side and demand-side dual perspectives. The results indicated that: (1) From the view of supply-side, the change of energy consumption structure led to the decline driving force of high-carbon energy (washed coal, crude oil, diesel oil and raw coal) and the rising driving role of low-carbon energy (coke oven gas, other gas and natural gas) for CO 2 emissions growth. Moreover, seen from the entire sample interval, 2007–2010 and 2010–2012 were the best period and the worst period for energy consumption optimization in China's heating and power industries, respectively. (2) From the view of demand-side, the expansion of industrial scale was the responsibility of the carbon emissions growth in China's heating and power industries, and the driving force of the second industry on carbon emissions growth was stronger than that of tertiary industry and primary industry. (3) However, since the direct consumption coefficient of heating and power energies in the tertiary industry and primary industry was lower than that of the secondary industry, the optimization of industrial structure was conducive to slowing the growth of CO 2 emissions in the China's heating and power industries on the demand-side. At last, this paper provides a theoretical analysis for the carbon emission structure of the heating and power industries, and a practical guidance for the industries to carry out more accurate and efficient emission reduction from both sides of supply and demand subsequently. [ABSTRACT FROM AUTHOR]

The Environmental Kuznets Curve (EKC) is an important tool to analyze the relationship between environment and per capital income. But two significant issues have been overlooked: why some points are above the EKC while others are below it? And what factors caused this phenomenon? Based on the data of 30 provinces in China over 2005–2016, this paper aimed to solve the above two questions. For the first question, we take the point on EKC as the theoretical pollution emission value of the different economic development stages; and use the difference between the theoretical pollution emission and the actual pollution emission under the same per capita income as the pollution emission efficiency. The difference value is used to reflect whether the pollution emission of the corresponding economic development stage of each region exceeds the standard and by how much. The result shows that most of the provinces with low pollution emissions concentrated in the north of the Yangtze River. Great progress has been made in China's pollution reduction work during 2015–2016. Then, for the second question, through the analysis of multiple mediating effects, we find that Environmental regulation, industrial transfer, proportion of output value of heavy pollution industry, energy consumption structure and energy using efficiency are important determinants to the pollution emission efficiency in Chinese province. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is important to ensure economic growth while conserving energy and reducing emissions. Based on the total factor energy efficiency of China's textile industry, this paper constructs a simultaneous equation model that includes the Tobit model, and empirically analyzes whether foreign trade affects energy efficiency in the textile industry as well as the mechanism of any such influence. The empirical results demonstrate positive feedback between foreign trade and energy efficiency in the textile industry, with imports impacting energy efficiency more than do exports. The foreign trade of textile industry is divided into import trade and export trade, which have different impacts on energy efficiency. Simultaneously, the results also confirm that R&D input, ownership structure and energy price significantly impact the energy efficiency of China's textile industry. • The foreign trade of textile industry significantly affects its energy efficiency. • The import trade impacts energy efficiency more than does the export trade. • Ownership structure significantly impact energy efficiency of textile industry. • Energy efficiency of textile industry has significant positive effect on foreign trade. [ABSTRACT FROM AUTHOR]

Water and energy resource are inextricably linked. Rapid industrialization has led to severe water and energy shortage as well as environmental issues in China. In industrial sector, industrial production and wastewater treatment are two interdependent subsystems. Accordingly, understanding the internal operation performance of the two subsystems as well as assessing their coordination level are of great importance for sustainable water and energy usage. From the perspective of production efficiency, this paper aims to explore industrial water-energy nexus in China by proposing an interactive meta-frontier network DEA approach. The proposed approach is applied to assess the industrial water and energy utilization efficiency in the processes of industrial production and wastewater treatment from 2011 to 2015 in China. The results show that although eastern and central regions have high industrial production efficiency, most regions have relatively low wastewater treatment efficiency. In addition, the nexus degree of eastern region maintains a relatively high level and shows a stable improvement, while the rest two regions perform relatively worse. Comparing the central and western region, the industrial production technology of central region is better yet the wastewater treatment efficiencies of western region are higher, which results in higher nexus degree of western region. Based on the empirical results, policy implications are given in terms of national level, regional level and provincial level, respectively. [ABSTRACT FROM AUTHOR]

This paper builds an input-output model to analyze the energy and economic impacts of the 4.7 trillion-CNY investment projects of the " Three-Year Action Plan for Major Construction Projects of Transportation Infrastructure ", which was launched by the Chinese government in 2016. The results show that, from 2016 to 2018, the investment plan could increase China's GDP by 2.39%, 1.30%, and 1.24%, respectively, and the country's energy consumption by 3.98%, 2.35%, and 2.40%, respectively. The top five production sectors could contribute 55% of the GDP growth induced by the plan, and the top three sectors could contribute 83% of the energy consumption growth, indicating that the impact of the investment plan centers mainly on a limited number of sectors. From the view of supply chains, the 20 paths with the largest GDP contribution cover approximately 47% of the GDP growth induced by the plan, and the 20 paths that consume the most energy cover approximately 32% of the energy consumption growth. In these paths, the construction industry is the dominant demand sector, whereas the industry of nonmetallic mineral products, the industry of production and supply of electricity and steam, and the industry of smelting and pressing of metals are the primary supply sectors. In the future, the Chinese government should pay more attention to indirect energy consumption related to the construction industry, and policymakers will also need to set up more effective energy conservation policies for the upstream sectors of the construction industry, such as the sectors providing cement, glass, and steel. • Estimate the energy and economic impacts of China's three-year investment plan for transportation infrastructure. • Identify critical supply chains for the energy consumption and economic changes induced by the investment plan. • Propose several policy recommendations on reducing energy consumption in the construction industry. [ABSTRACT FROM AUTHOR]

The industrial sector in China is energy-intensive and accounts for more than 60% of the nation's total energy consumption (demand). Narrating the story behind the growth of China's industrial energy consumption could help us understand the past and prepare for the future. This paper aims to investigate the factors affecting China's industrial energy consumption in the 21st century by using an extended production-theoretical decomposition approach (PDA) with considering the technological gap and scale of the economy effects. The new proposed decomposition framework includes four new factors, namely, the energy technological gap, the output technological gap, energy scale efficiency, and output scale efficiency. The results show that in the 21st century, the energy consumption of China's industry increased by more than one billion tons of standard coal. The expansion of the industrial economy is a dominant driver of China's industrial energy consumption, while potential energy intensity, energy technology, and output technology are the three largest energy-saving factors. In addition to the conventional factors, the newly proposed factors also have important effects on China's industrial energy consumption. Specifically, output scale efficiency is an energy-saving factor, while the energy technological gap, output technological gap, and energy scale efficiency are drivers of energy consumption. This suggests that China's industry is at the stage of returns to scale that is beneficial to output performance but harmful to energy performance. Meanwhile, the widening of the industrial technological gaps has negative impacts on China's industrial energy conservation. The proposed decomposition approach can provide information that cannot be obtained from traditional approaches and it can also be applied to many other cases for investigating feasible paths of energy-saving and emissions reduction. • A newly extended decomposition approach was proposed in this study. • The approach can quantify the effects of technological gap and scale economy. • Drivers of China's industrial energy consumption were investigated as a case. • The newly provided factors do have impacts on China's industrial consumptions. • It can provide information that cannot be obtained from traditional approaches. [ABSTRACT FROM AUTHOR]