Industrial Energy Consumption Research Articles

Study on urban green development efficiency of Jiangsu, Zhejiang and Fujian in China: a mixed network SBM approach

PurposeBy studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.Design/methodology/approachFirst, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.FindingsSubsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.Originality/valueThis study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

Experimental Study on Calcination of Portland Cement Clinker Using Different Contents of Stainless Steel Slag

In order to increase the utilization rate of stainless steel slag, reduce storage needs, and mitigate environmental impacts, this study replaces a portion of limestone with varying amounts of stainless steel slag in the calcination of Portland cement clinker. The study primarily examines the influence of stainless steel slag on the phase composition, microstructure, compressive strength, and free calcium oxide (ƒ-CaO) content of Portland cement clinker. The results show the following: (1) Using stainless steel slag to calcine Portland cement clinker can lower the calcination temperature, reducing industrial production costs and energy consumption. (2) With an increase in the amount of stainless steel slag, the dicalcium silicate (C2S) and tricalcium silicate (C3S) phases in Portland cement clinker initially increase and then decrease; the C3S crystals gradually transform into continuous hexagonal plate-shaped distributions, while the tricalcium aluminate (C3A) and tetracalcium aluminoferrite (C4AF) crystal structures become denser. When the stainless steel slag content is 15%, the dicalcium silicate and tricalcium silicate phases are at their peak; the C3S crystals are continuously distributed with a relatively dense structure, and C3A and C4AF crystals melt and sinter together, becoming distributed around C3S. (3) As stainless steel slag content increases, the compressive strength of Portland cement clinker at 3 days, 7 days, and 28 days increases and then decreases, while ƒ-CaO content decreases and then increases. When the stainless steel slag content is 15%, the compressive strength at 28 days is at its highest, 64.4 MPa, with the lowest ƒ-CaO content, 0.78%. The test results provide a basis for the utilization of stainless steel slag in the calcination of Portland cement clinker.

Low-carbon scheduling of electricity consumption in wastewater treatment plant by using photovoltaic system

Sewage treatment as a high energy consumption industry, its electricity consumption accounts for 3 % of the total electricity consumption of society. That means significant greenhouse gas emissions. In the context of China's goal of “reaching carbon peak by 2030 and achieving carbon neutrality by 2060”, reducing the energy consumption of wastewater treatment systems has emerged as an important issue in recent years. In this paper, the GPS-X simulation software was employed to conduct a simulation study of a modified Anoxic-Aerobic-Oxic wastewater treatment plant (WWTP) in Wuhan, and the response surface methodology (RSM) was utilized to ascertain the interactive effects of DO, IRF, ERR, and SD on the effluent quality, thereby identifying the operational parameters that minimize energy consumption while maintaining satisfactory effluent quality. Additionally, the PVsyst software was employed to design the solar power generation system of the WWTP and analyze its power generation potential. On this basis, through the coupling of photovoltaic power, electricity load, time-of-use pricing, and the water quality simulation model, and taking the WWTP data in September as a case study, the electricity usage strategies under various illumination conditions were formulated. The aim is to maximize the use of photovoltaic power to reduce the cost and carbon emissions of the WWTP. The results show that the optimal combination of operational parameters, including an external reflux ratio of 0.3, the internal recycle flow of 50,000 m3/d, and the sludge discharge of 448 m3/d, resulted in a reduction in power of 208.5 kW, and after the combination optimization of operational parameters and electricity utilization, the operation cost of the WWTP in September was reduced by 40 % ∼ 60 %, and the carbon emission attributable to electricity was reduced by 30 % ∼ 50 %.

Exploring the mechanisms affecting energy consumption in the construction industry using an integrated theoretical framework: Evidence from the Yangtze River economic Belt

Significant environmental challenges remain due to growing construction industry energy consumption (CIEC). Most existing studies focus on energy consumption at the city level, neglecting industry-level perspectives. To clearly explain the CIEC mechanism in the Yangtze River Economic Belt (YREB), this study adopts panel data from the YREB collected by the Chinese government from 2004 to 2020 and constructs an analytical model of the CIEC impact mechanism. Through Granger causality, impulse response function, and variance decomposition analyses, we found that technological innovation has an inverted U-shape and the greatest impact on CIEC, with a contribution rate gradually increasing with the cycle, finally reaching 0.4 %. The impact of urban development and foreign direct investment on CIEC shows a gradual upward trend, with a final contribution rate of 0.3 %; and the impact of urban resident population on CIEC is very small, with a contribution rate of only 0.1 %. Therefore, this study provides a new theoretical framework for future research on energy consumption and a theoretical basis for CIEC management from a government and construction industry manager perspectives.

Occurrence, removal, and risk assessment of polycyclic aromatic hydrocarbons and their derivatives in typical wastewater treatment plants

Wastewater treatment plants (WWTPs) have a certain removal capacity for polycyclic aromatic hydrocarbons (PAHs) and their derivatives, but some of them are discharged with effluent into the environment, which can affect the environment. Therefore, to understand the presence, sources, and potential risks of PAHs and their derivatives in WWTPs. Sixteen PAHs, three chlorinated polycyclic aromatic hydrocarbons (ClPAHs), three oxidized polycyclic aromatic hydrocarbons (OPAHs), and three methylated polycyclic aromatic hydrocarbons (MPAHs) were detected in the influent and effluent water of three WWTPs in China. The average concentrations of their influent ∑PAHs, ∑ClPAHs, ∑OPAHs, and ∑MPAHs ranged from 2682.50 to 2774.53 ng/L, 553.26–906.28 ng/L, 415.40–731.56 ng/L, and 534.04–969.83 ng/L, respectively, and the effluent concentrations ranged from 823.28 to 993.37 ng/L, 269.43–489.94 ng/L, 285.93–463.55 ng/L, and 376.25–512.34 ng/L, respectively. The growth of heat transport and industrial energy consumption in the region has a significant impact on the level of PAHs in WWTPs. According to the calculated removal efficiencies of PAHs and their derivatives in the three WWTPs (A, B, and C), the removal rates of PAHs and their derivatives were 69–72%, 62–71%, and 68–73%, respectively, and for the substituted polycyclic aromatic hydrocarbons (SPAHs), the removal rates were 41–49%, 31–40%, and 33–39%, respectively; moreover, the removal rates of PAHs were greater than those of SPAHs in the WWTPs. The results obtained via the ratio method indicated that the main sources of PAHs in the influent of WWTPs were the combustion of coal and biomass, and petroleum contamination was the secondary source. In risk evaluation, there were 5 compounds for which the risk quotient was considered high ecological risk. During chronic disease evaluation, there were 11 compounds with a risk quotient considered to indicate high risk. PAHs and SPAHs with high relative molecular masses in the effluent of WWTPs pose more serious environmental hazards than their PAHs counterparts.

Energy intensity constraints and corporate investment strategies: Evidence from Chinese listed enterprises

This study theoretically analyzes and empirically tests the impact and mechanism of energy intensity constraints on corporate investment strategies. The results find that energy intensity constraints significantly increase corporate green investment, particularly in front-prevention investment. Heterogeneity analysis indicates that the optimization effect of energy intensity constraints on corporate investment strategies is stronger in state-owned enterprises and high energy-consuming industries. Mechanism analysis reveals that energy intensity constraints optimize corporate investment strategies by increasing policy incentives and policy restraints. The findings provide important implications for policymakers to promote corporate sustainability and potential directions for future related research.

Efficiency measurement and inefficiency analysis of low-carbon logistics in the Beijing–Tianjin–Hebei region, China

Under the dual-carbon goals, enhancing the green development level of logistics industry and realizing its low-carbon transformation are important issues that need to be solved urgently. Amidst the continuous escalation in the total energy consumption of the national logistics industry, the Beijing-Tianjin-Hebei (BTH) region has exhibited a favorable descending trajectory in this respect. It is necessary to investigate the underlying reasons. Based on the panel data from 2012 to 2021, the DEA and Malmquist index are employed to analyze the low-carbon logistics efficiency of the BTH region from both static and dynamic perspectives. Furthermore, the inefficiency analysis is conducted to identify the deficiencies of low-carbon logistics industry in this region. Results show that (1) from the static perspective, the development of low-carbon logistics industry in the BTH region is relatively unbalanced. Compared to Tianjin and Hebei, Beijing's low-carbon logistics efficiency is significantly lower, becoming the focal area for attention; (2) from the dynamic perspective, technological progress is the main reason for the fluctuation of total factor productivity in the BTH region and a constraining factor for further improvements; (3) from the results of inefficiency analysis, the forthcoming emphasis on low-carbon logistics in Beijing should be on optimizing the number of logistics practitioners, transportation efficiency, and energy efficiency. Economic output and energy efficiency are relatively vulnerable aspects in Tianjin and Hebei, respectively, warranting due consideration. The research results of this paper have important practical implications for better developing low-carbon logistics in the BTH region and leveraging its leading role nationwide.

Evolution characteristics, carbon emission effects and influencing factors of production-living-ecological space in Taihang Mountain poverty belt, China

The rapid advancement of urbanization and industrialization in China has gradually spread to the poor mountainous areas, which has not only brought about rapid economic development but has also caused the increasing competition for production-living-ecological spaces (PLES) and many ecological and environmental problems, carbon emissions have also increased. As an economically less developed and ecologically fragile area in China, whether the transition of the PLES in the mountain poverty belt has unique characteristics? How the PLES transition in mountainous areas affects carbon emissions and what are the important factors affecting carbon emissions? To explore these issues in depth, we studied the Taihang Mountain area in Shijiazhuang (TMS) using remote sensing image interpretation data from 2000, 2010, and 2020, and we analyzed the PLES evolution characteristics, carbon emission changes, carbon emission effects and its influencing factors of PLES. The results are as follows: 1) The TMS was dominated by ecological and production space. From 2000 to 2020, the production space decreased by 384.66 km2, the ecological space increased by 123.80 km2, and the living space increased by 260.86 km2. Agricultural production space was mainly converted to ecological and rural living space. Industrial and mining productive space was mainly converted to agricultural productive space and urban living space. 2) The study area was in a state of carbon deficit, the transition of ecological space and agricultural productive space to industrial and mining productive space and living space were the main transition types caused the carbon emissions increasing, and that of industrial and mining productive space to agricultural productive space was the main type caused the carbon emissions decreasing. 3) The proportion of construction land, urbanization rate and proportion of secondary industry are the main factors leading to the increase of carbon emissions. Per capita energy consumption, forest coverage and proportion of tertiary industry are the main factors leading to the decrease of carbon emissions. This can provide new ideas for research on carbon emissions from land-use changes and a theoretical basis for the optimization of territorial space in the mountainous areas of China.

Scenario analysis of energy consumption and related emissions in the transportation industry-a case study of Shaanxi Province.

In the context of pursuing carbon neutrality and balancing the use of fossil fuels with renewable energy, the transportation industry faces the challenge of accurately predicting energy demand, related emissions, and assessing the effectiveness of energy technologies and policies. This is crucial for formulating energy management plans and reducing carbon dioxide (CO2) and atmospheric pollutant emissions. Currently, research on energy consumption and emission forecasting primarily relies on energy consumption quantities and emission factors, which lack precision. This study employs the low emissions analysis platform (LEAP) model, utilizing a "bottom-up" modeling approach combined with scenario analysis to predict and analyze the energy demand and related emissions in the transportation industry. Compared to previous studies, the methodological framework proposed in this research offers higher precision and can explore energy-saving and emission-reduction pathways for different modes of transport, providing a valuable energy forecasting tool for transport policy formulation in other regions. The forecast results indicate that under the business-as-usual (BAU) scenario, by 2049, the energy consumption and related emissions in Shaanxi Province's transportation industry are expected to increase by 1.15 to 1.85 times compared to the baseline year. In the comprehensive (CP) scenario, the industry is projected to reach a carbon peak around 2033. The study also finds that energy consumption and emissions predominantly originate from private passenger vehicles, highway freight, and civil aviation passenger, which have the greatest potential for emission reduction under the transport structure optimized (TSO) scenario. Therefore, policymakers should consider regional development characteristics, combine different transportation modes, and specifically analyze the emission reduction potential of the transportation industry in various regions, formulating corresponding reduction policies accordingly.

Benzoic acid catalyzed production of xylose and xylooligosaccharides from poplar

The proficient synthesis of xylose and xylooligosaccharides (XOS) from lignocellulosic biomass proved to be a formidable undertaking, particularly in the absence of preliminary hemicellulose isolation. In this study, the potential of benzoic acid (BZA), a non-toxic and edible acidic catalyst, was assessed for the pretreatment of poplar in order to produce xylose and xylooligosaccharides (XOS). At low temperatures (< 160°C) or low acid concentrations (< 2%), the main product obtained from the depolymerization of hemicellulose was XOS, and no significant depolymerization occurred on a large scale. The results showed that the highest extraction yield of hemicellulose was 93.1% with 2% BZA at 160°C for 0.75 h, hemicellulose was mainly converted into xylose and XOS, with xylose accounting for 27.1% and XOS accounting for 46.7%. Meanwhile, the results of the process simulation of industrial energy consumption indicated that the amount of water added was the main factor affecting energy consumption in industrialization, followed by temperature. This study presented a promising approach for the industrial-scale manufacturing of xylose and XOS from poplar as a primary resource.

Rural household nonagricultural income and energy transition: Evidence from central China

Promoting China's energy transition is essential for achieving low-carbon development and achieving the nation's carbon neutrality target. Previous research has primarily focused on industrial production energy consumption transition paths, and rural household energy consumption has rarely been investigated. This study focuses on the impact of nonagricultural income on rural household energy consumption in the Huang-Huai-Hai region using questionnaire data, examining the contribution of rural households' nonagricultural income to the energy consumption transition (i.e., from dirty energy sources such as firewood to clean energy sources such as liquified petroleum gas (LPG)). Instrumental variable two-stage least squares (IV-2SLS) estimation and IV-tobit models are applied to solve potential endogeneity problems. The results demonstrate that nonagricultural income can promote rural households' energy structure transformation, increase spending on clean energy such as LPG and electricity, and decrease expenditure on dirty energy sources such as coal and firewood. Further examination reveals that nonagricultural income can enable rural households to afford modern necessities and transition to cleaner, more efficient energy. The study proposes promoting rural energy structure transformation to boost sustainable development and increase nonagricultural income. Strengthening skills training, encouraging more off-farm employment, and other approaches will diversify rural households' income.

Understanding the Dynamics of Polymer Extrusion: Simulation of Thermoplastics Processing with Planetary Roller Extruders

Resource efficient processing of polymers is of paramount importance to minimize energy consumption, processing time, and material losses in the polymer industry. This study is concerned with polymer processing in planetary roller extruders. A three-dimensional numerical flow simulation was tailored to understand the polymer flow through the extruder in detail. Using the simulation software ANSYS Polyflow, we quantified both directly measurable process parameters, such as pressure build-up, and more intangible parameters, such as material shear. By varying operational and material parameters in a sensitivity analysis, we showed that the dynamics, material stress and pressure build-up are controlled primarily by the number of spindles and their rotational speed. Notably, this work provides the first successful validation of a 3D simulation of a polymer flow in a planetary roller extruder against actual experimental data. The simulation showed robust agreement between the simulated and experimental values, provided that a critical backpressure length is reached. This computational approach minimizes labor-intensive experimental testing in polymer processing.

Sustainable utilization of alkali-activated steel slag material: Effects of silicate modulus and GBFS on fresh, mechanical and pore structure properties

To improve the sustainable utilization of alkali-activated steel slag material, experiments were conducted to systematically investigate effects of sodium silicate modulus and GBFS content on the setting time, workability, mechanical properties and pore structure of alkali-activated steel slag cementitious material. Results show that the setting time is prolonged and workability is reduced as silicate modulus increases. The setting time is first shortened and then prolonged and workability is slightly reduced as GBFS content increases. Increasing silicate modulus and adding GBFS have positive effects on the development of elastic modulus, compressive and splitting tensile strength of alkali-activated steel slag material due to more refined pore structure. The highest compressive strength at 28 d can reach C35 strength level. Manufacturing alkali-activated steel slag material can achieve low energy consumption and carbon emission. If chemical activators can be replaced by some industrial wastes, cost, energy consumption and carbon footprint will be further decreased.

CO2 synergistic emission reduction and health benefits of PM2.5 reaching WHO-III level in Pearl River Delta

Protecting human health is one of the fundamental goals of continuous air quality improvement. Considering the same sources of CO2 and air pollutants emissions, their emission control measures often have a certain degree of synergistic emission reduction effects To balance the costs and policy efficiency, policy makers should assess the synergistic benefits of CO2 emission reduction when formulating air quality improvement strategies. Aimed at the air quality improvement strategy targeting WHO-III level (i.e. 15 μg/m3) for PM2.5 in the Pearl River Delta (PRD) region, this study evaluates the synergistic CO2 reduction effects and the associated health benefits from this strategy which includes a range of air pollution prevention and control measures. The results of the study show that promoting the attainment of WHO-III for PM2.5 in the PRD region can bring about 74 Mt of synergistic CO2 emission reduction, resulting in an 18% reduction of CO2 emissions in the PRD compared to 2017. Among various measures considered, industrial restructuring, power supply transition and industrial energy consumption transformation exhibit the most pronounced synergistic effects. Therefore, these measures are recommended to be prioritized and promoted in the next stage of air pollution prevention and CO2 emission reduction. Furthermore, when the PM2.5 concentration in the PRD region reaches the WHO-III level, the number of PM2.5-related deaths will be estimated to reduce approximately 5.5 thousand compared to that in the current policy scenario. Through continuous structural transformation and emission reduction efforts, it not only facilitates the decline in regional PM2.5 concentration but also helps more regional residents to live in an environment with a relatively low PM2.5 concentration. In addition, in order to reduce the health impacts of PM2.5, it is recommended that the government should guide people to change their production and living styles in order to reduce pollutant emissions from anthropogenic activities.

A novel foaming-sintering technique for developing eco-friendly lightweight aggregates for high strength lightweight aggregate concrete

To address the scarcity of natural aggregates and reduce energy consumption in the concrete industry, a sustainable lightweight aggregate (LWA) was prepared with a self-foaming and sintering method by utilizing waste glass powder as the primary precursor and incineration bottom ash as a foaming agent. The effect of NaOH content (0 M, 2 M, and 8 M) on the physical properties of LWA was investigated. Replacing manufactured sand with sintered LWA (0 M-LWA and 2 M-LWA) by 50 vol% and 100 vol% to investigate their impact on the physical properties, mechanical properties, shrinkage, and alkali-silica reaction of high strength LWA concrete. The high strength LWA concrete prepared with 0 M-LWA possessed a density of 2127 kg/m3 and compressive strength of 108.7 MPa, which were slightly lower than that with manufactured sand. Due to the porous and lightweight nature of 2 M-LWA, the density and compressive strength of LWA concrete significantly decreased with the increased 2 M-LWA volume. Nevertheless, 100%-2M showed satisfying density of 1835 kg/m3 and compressive strength of 50 MPa. The internal curing effect of 2 M-LWA effectively mitigated the autogenous shrinkage of LWA concrete. The alkali-silica reaction expansion of all LWA was innocuous.

The “energy rebound effect” within the framework of environmental sustainability

AbstractThe energy rebound effect, characterized by increasing energy use despite enhanced efficiency, has emerged as a complex interdisciplinary topic in the literature, reflecting its significance in both production and consumption sustainability. Recognizing the pivotal role of academic research in shaping energy management strategies and policies, this study conducted a comprehensive bibliometric review, accessing 530 articles from major citation indexes. This analysis provides insights into the evolution of the energy rebound field and potential future directions. Understanding the existing literature on the rebound effect serves as a valuable foundation for forthcoming research endeavors, addressing the intricate challenge of reconciling energy efficiency with sustainable energy consumption and production. The review explores the extensive literature on the energy rebound effect, highlighting a predominant focus on residential (e.g., cooling, heating, lighting, transportation) and industrial energy consumption in the majority of studies. Empirical applications primarily emphasize the measurement of the energy rebound effect, with a notable trend of increasing research concentration in China in recent years. Additionally, there is a growing body of economy‐wide analyses in this field. However, the literature exhibits complexity in both the analyses conducted and the methods employed for measuring the rebound effect. Research gaps are apparent, numerous studies tend to concentrate solely on the rebound effect at the overall energy consumption level, neglecting variations in energy types and the behavioral patterns of economic actors. Furthermore, despite consistent findings of a higher rebound effect in developing nations, there is a noticeable lack of scholarly literature addressing this issue about these countries.This article is categorized under: Sustainable Energy &gt; Energy Efficiency Human and Social Dimensions &gt; Behavioral Science Policy and Economics &gt; Governance and Regulation

Electrochemical synthesis in company with hydrogen production via renewable energy: Opportunities and challenges

Organic electromechanical synthesis is an eco-friendly and efficient method for material synthesis, effectively addressing the high energy consumption and pollution problems in the traditional chemical industry. By combining hydrogen production from water electrolysis with organic electromechanical synthesis, the reactive oxygen/hydrogen from water hydrolysis can be utilized to oxidize/reduce organic compounds, reducing energy consumption and producing valuable organic products. However, this strategy still faces challenges when implemented in the industry. This paper addresses major technical challenges in the field, providing new insights for future advancements. Firstly, when selecting anode reactions for hydrogen production, it is important to consider the value and market demand of the oxidation product to match the production scale. Secondly, the development of efficient electrocatalysts and electrodes is required to enhance the oxidation kinetics and mass transfer of organics at the current density levels of industrial hydrogen production (500–2000 mA cm−2). Thirdly, it is essential to improve the selectivity and Faraday efficiency of the anode target product to lower the cost of subsequent separation and purification. Fourthly, existing anion and oxygen ion exchange membranes lack corrosion resistance to organic matter, and new separator materials with high ion conductivity and stability are crucial for the electrolytic coupling system. Finally, when combining organic oxidation and water electrolysis, the complexity of product separation increases, and it is recommended to integrate distillation, extraction, membrane separation, and electrochemical reactions to improve process efficiency.

ENERGY INTENSITY OF THE POLISH AGRI-FOOD SECTOR IN THE LIGHT OF INPUT-OUTPUT TABLES

The purpose of this paper is to assess the energy intensity of production in the Polish agri-food (agribusiness) sector, split into agriculture, food industry and supply subsectors, in the light of input-output tables. The study relies on input-output tables and physical energy flow accounts. Energy plays a key role in today’s society as it affects economic growth and the standards of living, while also being at the core of international conflicts, mainly caused by its limited resources. Compared to other sectors, agribusiness demonstrates particularly high levels of energy consumption. Agriculture, which is part of it, has a large share in the consumption of fuels derived from crude oil. This paper presents the consumption of energy in each of the four aggregates of agribusiness, as well as their GDP (in PPS) and energy consumption mix (split into 6groups of energy carriers). The authors found that between2014 and2019, energy consumption in the agribusiness industry increased by ca.9% and was accompanied by ca.8% growth in GDP. The sector’s energy intensity was half more than the average level for the economy as a whole, and remained at ca.5.6TJ per EUR1million of GDP in PPS. Only the food industry was at a level of energy efficiency similar to that of the economy as a whole, whereas the agricultural supply subsector was the only one to demonstrate lower levels. Both the economy as a whole and the agribusiness sector clearly tend to reduce the share of coal and related products in the energy mix.

How population aging promotes carbon emission reduction in Chinese cities: The chain mediating role of industrial upgrading and energy conservation

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities.

Deep Learning-Based Carbon Emission Forecasting and Peak Carbon Pathways in China’s Logistics Industry

As a major energy-consuming industry, energy conservation and emission reduction in the logistics industry are critical to China’s timely achievement of its dual-carbon goals of “carbon peaking” by 2030 and “carbon neutrality” by 2060. Based on deep learning, Random Forest (RF) was used to screen out the key factors affecting carbon emissions in the logistics industry, and the Whale Algorithm-optimized Radial Basis Function Neural Network (WOA-RBF) was proposed. The Monte Carlo simulation predicted the future evolution trends of each key factor under the three scenarios of baseline scenario (BAU), policy regulation scenario (PR), and technological breakthrough scenario (TB) and accurately predicted the carbon emission trends of the logistics industry from 2023 to 2035 by using the most probable future values of each influencing factor as inputs to the WOA-RBF prediction model. The results of the study demonstrate that fixed asset investment (LFI), population (P), total energy consumption (E), energy consumption per unit of value added of the logistics industry (EIL), share of oil consumption (OR), and share of railway freight turnover (RTR) are the key factors influencing the logistics industry’s carbon emissions. Monte Carlo simulations can effectively reflect the uncertainty of future changes in these key factors. In comparison to the BAU and PR scenarios, the TB scenario, with the combined incentives of national policy regulation and technology innovation, is the most likely for the logistics industry to meet the “Peak Carbon” goal baseline scenario.