Energy Structure Optimization Research Articles

Life cycle environmental impact assessment of green tea production in China

Tea is the second most popular beverage in the world after water, and the potential environmental problems during the entire life cycle stages of its production have not been thoroughly discussed. This study aims to investigate the overall environmental impact of green tea production as a typical perennial crop in China with the system boundary from “cradle to gate”. Scenario analysis is carried out to investigate the factors of green tea processing scales and packaging methods on the overall environmental impact level of green tea production in China. Results showed that the average overall global warming potential of procuring 1 kg dry green tea in China ranges from 10.4 to 15.6 kg CO2eq, depending on different processing scales and packaging methods. The processing stage is the dominant contributor to the overall environmental impact of producing 1 kg dry green tea product due to the use of electricity. Electricity consumption in the processing stage and chemical fertilizer application in the planting stage are identified as the environmental hotspots throughout the life cycle of green tea production in China. Optimizing energy structure and improving energy use efficiency in the processing stage, as well as reducing the amount of chemical fertilizer application are the critical measures needed to mitigate the environmental emissions of green tea throughout the life cycle.

Study on the impact of smart energy on carbon emissions in smart cities from single and holistic perspectives – Empirical evidence from China

Smart energy, as an important component of smart cities and directly related to carbon emissions, plays a crucial role in smart cities to achieve carbon neutrality, but the theoretical research and empirical evidence on the impact of smart energy on carbon emissions in smart cities are limited. This paper investigates, from single and holistic perspectives, the effect of smart energy on smart city carbon emissions and potential mechanisms. Based on the panel data of 100 smart cities in China from 2014–2019, it uses synthetic difference-in-difference mode and spatial difference-in-difference mode to estimate the carbon emission reduction effect and test the potential mechanisms. The results show that: (1) Smart energy reduces carbon emissions in smart cities by an average of 5.65 %. (2) Smart energy reduces smart city carbon emissions mainly through mechanisms including optimizing energy structure and improving energy efficiency. (3) Smart energy in smart cities has a significant spatial carbon emission reduction effect. (4) Smart energy in smart cities influences holistic regional carbon emissions through spatial mechanisms including technology spillover, peer effect, and scale effect. Finally, this study provides quantitative evidence and valuable insights for cities in developing countries with similar backgrounds to China to design emission reduction paths and adjust smart city strategies.

Oil price distortion and its impact on green economic efficiency in China’s transportation: A spatial effect perspective

China's oil prices have been supervision for a long time, which has led to oil price distortion (OPD) to some extent. To figure out whether OPD will impede the sustainability of energy, economy, and environment (measured by green economic efficiency (GEE)), this research first estimates OPD from 2003 to 2019. Then, using a non-radial direction distance function under nonconvex technology assumptions, this research calculates the provincial GEE by incorporating capital, labor, energy, and environment efficiencies into a unified framework. Furthermore, the OPD-GEE nexus and their influencing channels are analyzed using the spatial Durbin model. The results indicate that there are serious OPD and the average GEE in the transportation is relatively low. Local OPD correction can improve local GEE but OPD correction in spatially related regions will cause local GEE loss. The heterogeneity analysis implies that the GEE promotion effect resulting from local OPD correction is greater in oil-rich regions, new energy vehicle pilot regions, and regions with water transport. Furthermore, the mechanism analysis implies that OPD correction can improve local GEE through optimizing energy structure, mitigating resource mismatch, and promoting green technological progress; meanwhile, OPD correction in spatially adjacent regions can cause local GEE losses by exacerbating their resource mismatch. This study offers a new understanding of the impact of OPD on GEE and contributes to the promotion of sustainable development through market-oriented price reforms.

Climate impact of coal-to-clean-energy shift policies in rural Northern China

China has implemented the coal-to-clean-energy shift policy in rural areas of northern China to improve air quality, optimize energy structure and reduce greenhouse gas emissions, resulting in a significant increase in natural gas and electricity consumption. The policies shifts can reduce CO2 emissions, but methane emissions from switching processes may contribute to short-term climate impacts. The climate impact during the policy transition is still unclear. Thus, this paper developed a lifecycle greenhouse gas (GHG) emissions framework for coal-to-clean-energy policies in rural northern China. The GHG emissions for heating and cooking, the two most energy intensive activities, were calculated. Four scenarios were designed based on energy types and equipment. Uncertainties in estimating lifecycle GHG emissions under different scenarios were analyzed. The technology warming potential values were calculated for the conversion of scenarios. Besides, the environmental benefits of natural gas versus electricity under emission reduction targets were compared. According to our findings, the total GHG emissions reduction of coal-to-clean-energy shift policies in rural northern China under global warming potential on a 100-year scale (GWP 100) is 1.83 million metric ton CO2 equivalent (MMT CO2 eq) in 2018. Since the climate benefits of policy shifts are driven by chosen technical routes, replacing coal with natural gas should be prioritized; heating with natural gas boilers can maximize GHG emissions reduction and climate benefits. By 2038, the climate benefits of electricity will be far superior to those of natural gas, based on emission reduction targets and electrical mix. There are numerous opportunities to reduce GHG emissions in China's energy sector, and there is a need for the energy industry to obtain better emissions data as well as to increase efforts to reduce GHG emissions.

China's provincial-level sustainable energy transition requires accelerating renewable energy technological innovation

In energy economics, little attention has been paid to the impact of renewable energy technological innovation (RETI) on sustainable energy transition in a large energy-producing and consuming country such as China. Using the Chinese provincial panel dataset from 2000 to 2018, we examine the impact of RETI on sustainable energy transition. We find that RETI positively drives sustainable energy transition in Chinese provinces, but the driving effect gradually diminishes with the increase in per capita income. In the energy-poor regions, RETI has a significant driving impact on sustainable energy transition, but not in the energy-rich regions; moreover, this driving effect in the western region is significantly more potent than that in the eastern region. The mechanism identification results reveal that RETI significantly improves energy system performance and energy structure optimization. In contrast, RETI has a more significant effect on the former. In this study, we provide a novel perspective to identify the driving path of sustainable energy transition in Chinese provinces.

Calculation of Carbon Emissions and Study of the Emission Reduction Path of Conventional Public Transportation in Harbin City

As the northernmost megacity in China, the long winters, large population size, and unsustainable transport structure in Harbin determine that the city will produce relatively large carbon emissions. The transportation industry is one of the three greenhouse gas emission sources; therefore, the development of low-carbon transportation is imperative. This work compares commonly used carbon emission measurement methods and chooses a mileage method to classify the carbon emissions of conventional buses of different energy types used in Harbin in 2020. A multi-factor grey prediction model was constructed to predict the population size of Harbin and the number of conventional buses. After that, a scenario analysis method was used to analyze the fuel structure of buses in Harbin from three perspectives: a pessimistic scenario, a baseline scenario, and an optimistic scenario. The carbon emissions of conventional buses were calculated for Harbin from 2023 to 2030. Finally, by combining the prediction results and factors influencing carbon emission, a regular bus path to minimize carbon emissions is proposed. The outcome of this study shows that the carbon emission environment in Harbin will be improved by reducing vehicle energy consumption, optimizing energy structure, standardizing driving behavior, building intelligent transportation, giving priority to public transportation, and improving the road network structure.

Novel spatiotemporal graph attention model for production prediction and energy structure optimization of propylene production processes

Propylene is essential to the national economy. However, the propylene production process data have complex spatiotemporal, nonlinear and dynamic features, and the consideration of spatiotemporal effects can predict the propylene production more accurately. Therefore, a novel graph attention network (GAT) based long short-term memory network (LSTM)(GAT-LSTM) is proposed for the production prediction and energy structure optimization of propylene production processes. The GAT extracts spatial features to obtain correlations between variables, while the improved LSTM model extracts potential temporal-dependent features. The collected spatiotemporal interaction features are fused by the spatiotemporal fusion module and the adaptive control is realized. Finally, a fully connected layer maps spatiotemporal interaction features to the target domain for obtaining the output. Experimental results show that the GAT-LSTM outperforms the Conv-LSTM, the LSTM, the GAT, the Attribute-relevant distributed variational autoencoder and the Attention-LSTM. Additionally, the GAT-LSTM can provide the optimal raw material scheme for actual propylene production processes.

Path mechanism and spatial spillover effect of green technology innovation on agricultural CO2 emission intensity: A case study in Jiangsu Province, China

Green technology innovation (GTI) is one of the most important factors influencing agricultural carbon emission intensity (ACEI). Various studies have explored the impact of GTI on ACEI, but the path mechanism has not been fully explained. This study incorporates GTI and ACEI into the constant elasticity of substitution (CES) production function and constructs a theoretical model to analyse their direct impact mechanisms. Drawing on the substitution effect theory and the Marshall–Arrow–Romer (MAR) externalities theory, this study introduces two regulatory mechanisms: optimization of energy structure and agricultural industry agglomeration (AIG). Additionally, it explores the pathway mechanisms under the influence of spatial spillover effects based on Tobler’s first law of geography. Then, taking Jiangsu Province in China as a case study, empirical tests are conducted using LSDVC and dynamic spatial SAR models. The results are as follows. (1) GTI effectively inhibits ACEI directly, and has significantly positive spatial spillover effects on ACEI reduction in the short and long terms. (2) Energy structure optimization positively regulates the effect of GTI on ACEI reduction, and energy structure optimization in nearby cities may help GTI restrain ACEI in the local city in the short term. (3) AIG has a positive regulating effect on GTI reducing ACEI, and the moderating effect of AIG has positive spillover effects in the short term. (4) When both regulatory pathways are employed simultaneously, the moderating effect of AIG in local or neighbouring areas is expected to become ineffective. These findings are useful for solving the problem of ACEI reduction by managing the transfer and distribution of GTI between different regions, considering spatial spillover and moderating effects.

Driving factors and scenario prediction of carbon emission from transport sector in the Yangtze River Basin of China

IntroductionClimate change caused by carbon emission and their impact on social and economic system have garnered global attention, particularly from the world's largest emitters. Therefore, knowledge of both driving factors and reduction potential for carbon emission is crucial to revise climate policies. The transportation industry plays a major in global carbon emissions, mostly due to the excessive utilization of fossil fuels for combustion purposes.MethodsThe goal of this study is to investigate the underlying causes that drive carbon emissions in China's Yangtze River Basin. Additionally, this study seeks to anticipate the future potential reduction in carbon emission. To achieve these, our research used a combination of the LMDI method and Monte Carlo simulation.Results and discussionThe results indicate that, during 2006 to 2020, transportation carbon emission increased from 48.41 Mt to 104.37 Mt, following an annual growth rate of 5.64%, which suggests that energy strategies are not fully implemented as planned. The greatest positive impact on carbon emission is attributed to economic development, as the increase in resident income has led to the vigorous development of the transportation sector. Moreover, energy intensity and transportation efficiency have a negative influence on carbon emissions. The decrease of carbon emissions can be accomplished by the continued advancement of novel energy technologies and the optimization of energy systems. According to the baseline scenario, it is projected that carbon emissions from the transport sector will reach 198.76 Mt by the year 2030. Under the moderate scenario, there is a possibility for reducing emissions by 18.6 Mt, and under the advanced scenario, the potential reduction is estimated to be 48.84 Mt. As a view to suppress the increase of carbon emission from transportation, a set of plans and policies must be implemented from demand-side and supply-side, including improving transportation efficiency, and optimizing energy structure, etc.

The pathway of regional carbon peak in building sector: A case study of Central China

As the greenhouse effect intensifies, controlling carbon emissions has become increasingly critical. China, having the world's highest carbon emissions, sees almost half of its total emissions from the building sector. China is confronted with the challenge of different provinces having diverse timelines for achieving carbon peak in the building sector, leading to “undesirable responses”. To address this, our study expands the research scope and introduces dynamic forecasting methods through the D-STIRPAT model. The model has produced more accurate predictions for carbon emissions in the building sector of the Central China region. The research results indicate that collaborative optimization between urban and construction industries is the most effective pathway to reduce carbon emissions. Henan Province can achieve peak emissions in the building sector relatively quickly, with most scenarios reaching their peak by 2040, with the lowest peak value reaching 415.4 MtCO2e. Hubei and Hunan provinces are likely to achieve peak emissions for most scenarios between 2050 and 2060. However, the building sector in the Central China region can achieve peak emissions between 2030 and 2045, with peak values ranging from 1.235 to 1.702 BtCO2e. In terms of carbon reduction effects, the overall strategy for achieving peak emissions in the building sector in Central China should focus primarily on optimizing urban and building sector development, supported by energy structure optimization and the promotion of building energy efficiency. Henan and Hubei provinces should prioritize urban and building sector development, while Hunan Province should emphasize both urban and building sector development and energy structure optimization concurrently. This study highlights the benefits of regional carbon emissions regulation in the building sector, provides innovative solutions for achieving dual carbon targets, and offers guidance and approaches for achieving peak emissions in the building sector through regional collaboration.

China's Energy Structure Problems and Optimization Suggestions from the Perspective of Low-carbon Economy

Energy consumption, technological level, and sustainable industrial system are crucial for developing a low-carbon economy. China's excessive reliance on coal has led to low energy utilization efficiency, which has become an important factor affecting the optimization of China's energy structure and further constraining the sustainable development of the economy. In this regard, this article attempts to explore the issues of China's energy structure from the perspective of a low-carbon economy, and proposes strategies for optimizing China's energy structure from the perspective of a low-carbon economy. In the context of developing a low-carbon economy, starting from China's specific national conditions, the government should play a guiding role, optimize China's energy structure step by step, and promote the development of new energy projects. Based on China's actual technological situation, technological upgrading and industrial structure transformation, we will focus on developing low-carbon related industries and strategic emerging industries. Only by continuously innovating and applying new energy can we achieve the transformation of energy application structure in the production and living fields, gradually shifting from high pollution and high emissions to low pollution and low emissions.

How does green finance affect energy efficiency? The role of green technology innovation and energy structure

As climate warming intensifies, reducing greenhouse gas emissions has become a national consensus for many countries. Green finance plays an important role in promoting energy efficiency and lowering such emissions, but there is scant literature that analyzes the impacts and mechanisms of green finance on energy efficiency. Based on China's provincial panel data from 2010 to 2018, this research measures the green finance index using the panel entropy weighting method and systematically evaluates the relationship between green finance and energy efficiency using the fixed-effects model. The results show the following. (1) Green finance significantly contributes to energy efficiency and remains the same after a series of robustness tests such as endogeneity treatment, replacement of explanatory and interpreted variables, and replacement of regression models. (2) Green technology innovation and energy structure optimization are the transmission mechanism of green finance for energy efficiency, which means that green finance improves energy efficiency by promoting green technology innovation and energy structure optimization. (3) There is regional heterogeneity, temporal heterogeneity, and industry heterogeneity in the impact of green finance on energy efficiency. The positive effects of green finance on energy efficiency are more pronounced in resource-dependent regions, regions with irrational industrial structure, north regions, industrial sectors, and after 2013. The conclusions of this paper offer some policy recommendations, including promoting the development of green finance, building a cooperation platform for green finance and technological innovation, enhancing the depth and breadth of renewable energy utilization, and building differentiated green finance strategies according to local conditions.

Geometry and electronic properties of alkali metal (rubidium) doped boron clusters

AbstractAlkali metal‐doped boron clusters have captured much attention because of their novel electronic properties and structural evolution. In the study of RbBn0/− (n = 2–12) clusters, the minimum global search of the potential energy surface and structure optimization at the level of PBE1PBE by using the CALYPSO method and Gaussian package coupled with DFT calculation; the geometrical structures and electronic properties are systematically investigated. At n = 8, the ground‐state structures are composed of an Rb atom above B atoms, forming a structurally stable pagoda cone. By stability analysis and charge transfer calculation, the RbB8− cluster shows more stability. It found that s‐p hybridization between Rb atom and B atoms as well as s‐p hybridization between B atoms is one of the reasons for the outstanding stability exhibited in the RbB80/− clusters by using DOS and HOMO–LUMO orbital contour maps. The chemical bonding of the RbB80/− groups was analyzed by using the AdNDP method, and B atoms with larger numbers readily form multi‐center chemical bonds with the Rb atom. From the results of the bonding analysis, the interaction between the Rb atom and B atoms strengthens the stability of the RbB80/− clusters. It is hoped that this work provides a direction for experimental manipulation.

Did regional coordinated development policy mitigate carbon emissions? Evidence from the Beijing-Tianjin-Hebei region in China.

In order to promote the balanced development of regional economy, governments at all levels are constantly introducing regional coordinated development policy (hereinafter referred to as "the Policy"). However, there is an important and interesting issue, namely, with the increasingly severe environmental problems resulted from rapid regional economic growth, what kind of impact will the Policy have on carbon emissions reduction? This is attracting wide attention from relevant stakeholders. Therefore, taking the Beijing-Tianjin-Hebei (BTH) region in China for example and through constructing the difference-in-differences (DID) model, this paper evaluated the effect of the implementation of the Policy on carbon emissions reduction. Results indicated that the Policy significantly reduced the level of regional carbon emissions in the BTH region. After carrying out a series of robustness tests, this paper still found that the above conclusions were reliable. Moreover, the mediation effect test shown that the Policy indirectly lessened carbon emissions by optimizing energy structure and reducing the intensity of carbon emissions, while the expanding of economic scale would lead to an increase in carbon emissions due to the effect from the Policy. Additionally, heterogeneity analysis revealed that the Policy had a more significant effect on carbon emissions reduction in underdeveloped regions with low environmental constraints. Overall, this paper would be beneficial to understanding the environmental effects of the Policy at the urban regional scale, thus providing an important basic theoretical basis for promoting the green and sustainable development of regional economy.

Can low carbon policies achieve collaborative governance of air pollution? Evidence from China's carbon emissions trading scheme pilot policy

In the context of environmental and climate governance, the efficiency with which low-carbon policies reduce air pollution is vital for enhancing the effectiveness of environmental policy implementation. Using the emissions trading scheme (ETS), the most representative low-carbon policy in China, as an example, this study employs a panel data set of 250 Chinese cities for the period 2003–2016. Additionally, a spatial difference-in-differences (SDID) model is utilized to explore the ETS pilot policy's impact on sulfur dioxide (SO2) emissions and haze pollution (PM2.5 concentrations) and identify the mechanism underlying these effects. Our results show that the policy helps to reduce both types of air pollution, thereby having a significant collaborative-governance effect. Moreover, while the ETS pilot policy improves PM2.5 concentrations in neighboring cities significantly, it fails to curb SO2 emissions in these areas. The mechanism identification results point to a collaborative-governance effect of the policy via industrial structure upgrading, energy structure optimization, and green technology innovation. According to heterogeneity analysis, while the policy has a more evident impact on air pollution in central and western China, it does not exert a collaborative-governance effect on SO2 emissions in non-key environmental protection and energy-oriented cities.

Can clean heating effectively alleviate air pollution: An empirical study based on the plan for cleaner winter heating in northern China

The current grim situation of China's air contamination has become a grave environmental and social problem. The massive consumption of coal energy has resulted in a large amount of atmospheric pollutant emissions and consequently deteriorated air quality, making the cleaner transformation of coal energy a priority in the fight against air pollution in China. Based on this background, we used panel data with coverage for 286 Chinese cities over the time frame spanning 2013 to 2020 combined with the difference-in-differences (DID) model to investigate the impacts of the Plan for Cleaner Winter Heating in Northern Region (NCH) on air contamination and its action mechanism. The empirical evidence suggests that the implementation of the NCH policy can effectively alleviate air pollution, with a reduction in SO2 concentration of approximately 20.4%, which can be corroborated by robustness tests. Nevertheless, the policy is insufficient to significantly reduce PM2.5 pollution. Furthermore, the potential mechanisms are also examined here, revealing that energy structure optimization is a key path for the NCH policy to decrease SO2 pollution. Moreover, due to the differences in the environmental protection characteristics, geographic location, priority and marketization level, significant heterogeneity of the impacts of NCH on SO2 pollution was observed. Especially in nonlow‑carbon pilot cities, coastal cities, “2 + 26” key cities, and cities with high marketization, the policy was particularly pronounced in attenuating SO2 pollution. These results can serve as a scientific basis for systematically setting up cleaner heating projects and informing decision-making in areas threatened by air pollution.

The impact of carbon emissions trading policy on carbon emission efficiency in Chinese cities: Evidence from a quasi-natural experiment

Based on a panel dataset spanning from 2003 to 2019 and encompassing 284 prefecture-level cities in China, this study treats the implementation of the carbon emissions trading policy (CETP) as a quasi-natural experiment. In addition, it employs a spatial difference-in-differences (DID) framework to quantify both the direct and spatially mediated impacts of CETP on urban carbon emission efficiency (CEE). The investigation further delves into the underlying channels of influence and variations within this context. The findings demonstrate that CETP effectively enhances CEE within the cities chosen for piloting; however, it concurrently dampens CEE in nonpiloting neighboring cities. These conclusions remain robust across diverse sensitivity tests. The analysis of mechanisms reveals that CETP’s influence on urban CEE primarily operates through the avenues of technological innovation and optimization of energy structure. Moreover, the study of variances discloses that CETP’s direct effect significantly advances CEE in eastern, old industrial base, and central cities. In terms of indirect effects, a pronounced adverse spatial spillover effect is observed in eastern and old industrial base cities, while noteworthy positive spatial spillover effects emerge in central cities. Notably, the spatial extent of CETP’s influence on urban CEE declines after reaching a distance of 900 km. These insights furnish valuable guidance for China in refining its nationwide carbon market and expediting the shift toward a low-carbon economy.

Carbon emissions reduction potentiality for railroad transportation based on life cycle assessment

This study addresses the comparative carbon emissions of different transportation modes within a unified evaluation framework, focusing on their carbon footprints from inception to disposal. Specifically, the entire life cycle carbon emissions of High-Speed Rail (HSR), battery electric vehicles, conventional internal combustion engine vehicles, battery electric buses, and conventional internal combustion engine buses are analyzed. The life cycle is segmented into vehicle manufacturing, fuel or electricity production, operational, and dismantling-recycling stages. This analysis is applied to the Beijing-Tianjin intercity transportation system to explore emission reduction strategies. Results indicate that HSR demonstrates significant carbon emission reduction, with an intensity of only 24 %–32 % compared to private vehicles and 47 %–89 % compared to buses. Notably, HSR travel for Beijing-Tianjin intercity emits only 24 % of private vehicle emissions, demonstrating the emission reduction benefits of transportation structure optimization. Additionally, predictive modeling reveals the potential for carbon emission reduction through energy structure optimization, providing a guideline for the development of effective transportation management systems.

Green Eco-Innovation and Supply of Critical Metals: Evidence from China

Ensuring a green supply of critical metals is essential to achieve high-quality economic development and ecological security. Based on data from 2000 to 2019 on five critical metals in China (copper, aluminum, nickel, antimony, and titanium), this study employs a series of econometric methods, such as fixed-effects regression and moderating effects, to examine the influence of green eco-innovation on primary and recycling supply of critical metals, as well as the underlying mechanisms. The findings indicate: (1) Green eco-innovation has an inverted U-shaped impact on the primary supply of bulk critical metals, and it is currently in the declining phase of the curve. (2) Green eco-innovation has a U-shaped impact on the recycling supply of critical metals and the primary supply of minor critical metals. The former is currently in the rising phase of the curve, while the latter is in the declining phase. (3) The impact of green eco-innovation on the supply of critical metals is stronger in industrially underdeveloped regions. (4) The improvement of energy efficiency, optimization of energy structure, and strengthening of environmental regulations enhance the impact of green eco-innovation on the supply of critical metals. Finally, the optimization of the energy mix is conducive to securing the supply of key metals. This study provides a theoretical basis for utilizing green eco-innovation to achieve a green supply of critical metals and enriches the theoretical research on green eco-innovation.

The impact of government intervention on innovation efficiency of green technology—a threshold effect analysis based on environmental taxation and government subsidies

Research and promotion of green technology can improve energy efficiency and help to optimize energy structure, which are key considerations in achieving the “dual carbon” goals of carbon peaking and carbon neutrality. Owing to the “dual externality” arising from green technology innovation (GTI), government policies have an important impact on this area. Environmental taxes and government subsidies are important means for governments to improve GTI and optimize energy utilization, with different environmental taxes and subsidies having different impacts. This study evaluates the impact of environmental taxes and government subsidies in China from 2009 to 2019, and assesses how these policies interacted with each other to determine China’s efficiency in GTI over this period. The study’s findings based on analysis of 30 provinces and cities in China indicate that environmental taxes have a threshold effect on the development of green technologies, and that the current level of taxation is insufficient to encourage optimized development in this area. Government subsidies can also help to reduce the negative effects arising from the current environmental tax burden. To optimize government policy implementation in this area, improve the level of GTI, and improve energy use efficiency, this study proposes countermeasures based on differentiated policies, including gradually increasing the rate and scope of environmental taxation, and strengthening the supervision of government subsidies.