Energy Consumption Intensity Research Articles

The evolution, characteristics, and driving forces of the rural-urban HCEs in China: based on the EIO-SDA model

Households' carbon emissions (HCEs) plays an important role in the overall carbon emission (CE) reduction. This study conducts a comparative analysis of the trends and characteristics of the rural and urban HCEs in China in 1997–2020, by applying the environmental input-output (EIO) model. Then, a three-stage SDA model is applied to decompose the driving forces of the rural and urban HCEs evolution into population effect, per capita HCEs effect, expenditure effect, CE intensity effect, energy structure effect, and energy consumption intensity effect. It is obtained that the rural HCEs increases before 2015 and then decreases, but its per capita HCEs has always shown an upward trend. The urban HCEs has been increasing, but its per capita HCEs starts to decrease after 2015. Indirect HCEs accounts for over 80% of both the rural and urban HCEs, and Residence, Food and Tobacco, Transportation and Communication are the three biggest contributing sectors. To reveal the driving forces of the rural and urban HCEs evolution, this study conducts phase decomposition analysis with 2015 as a turning point. For rural HCEs, in 1997–2015, rural HCEs increased due to the dominant expenditure effect; from 2015 to 2020, the driving force reversed, leading to a decline in rural HCEs. For urban HCEs, the positive population and expenditure effects have always been larger than the negative energy structure and energy consumption intensity effects, resulting growth in urban HCEs. For urban per capita HCEs, in 1997–2015, the positive expenditure effect is greater than the negative CE intensity effect, leading to an increase in urban per capita HCEs, and a positive urban per capita HCEs effect. In 2015–2020, the driving force reversed, leading to a decline in urban per capita HCEs. Based on above results, countermeasures to promote rural and urban HCEs reduction are discussed.

Research on Industrial CO2 Emission Intensity and Its Driving Mechanism Under China’s Dual Carbon Target

As global climate change becomes increasingly severe, industrial CO2 emissions have received increasing attention, but the impact factors and driving mechanisms of industrial CO2 emission intensity remain unclear. Based on panel data from 2010 to 2021 in Shandong Province, a key economic region in eastern China, the industrial CO2 emission intensity under China’s dual carbon target was analyzed using multivariate ordination methods. The results showed that (1) total CO2 emissions from industry are increasing annually, with an average growth rate of 3.74%, and electricity, coal, and coke are the primary sources of CO2 emissions. (2) Total CO2 emissions originated primarily from the heavy manufacturing, energy production, and high energy intensity industry categories, and the CO2 emission intensity of different types of energy increased by 21.24% from 2010 to 2021. (3) CO2 emission intensity is significantly positively correlated with the proportion of high energy intensive industry, energy consumption intensity, and investment intensity and significantly negatively correlated with gross industrial output. In addition, the effects of different types of energy on industrial CO2 emission intensity varied, and coal, coke, electricity, and diesel oil were significantly positively correlated with CO2 emission intensity. Therefore, to reduce the CO2 emission intensity of the industrial sector in the future and to achieve China’s dual carbon target, it is necessary to adjust and optimize the industrial and energy structure, strengthen technological progress and innovation, improve energy utilization efficiency, improve and implement relevant policies for industrial carbon reduction, and then ensure the sustainable development of the economy, society, and environment.

Local Electric Field-Incorporated In-Situ Copper Ions Eliminating Pathogens and Antibiotic Resistance Genes in Drinking Water

Background/Objectives: Pathogen inactivation and harmful gene destruction from water just before drinking is the last line of defense to protect people from waterborne diseases. However, commonly used disinfection methods, such as chlorination, ultraviolet irradiation, and membrane filtration, experience several challenges such as continuous chemical dosing, the spread of antibiotic resistance genes (ARGs), and intensive energy consumption. Methods: Here, we perform a simultaneous elimination of pathogens and ARGs in drinking water using local electric fields and in-situ generated trace copper ions (LEF-Cu) without external chemical dosing. A 100-μm thin copper wire placed in the center of a household water pipe can generate local electric fields and trace copper ions near its surface after an external low voltage is applied. Results: The local electric field rapidly damages the outer structure of microorganisms through electroporation, and the trace copper ions can effectively permeate the electroporated microorganisms, successfully damaging their nucleic acids. The LEF-Cu disinfection system achieved complete inactivation (>6 log removal) of Escherichia coli O157:H7, Pseudomonas aeruginosa PAO1, and bacteriophage MS2 in drinking water at 2 V for 2 min, with low energy consumption (10−2 kWh/m3). Meanwhile, the system effectively damages both intracellular (0.54~0.64 log) and extracellular (0.5~1.09 log) ARGs and blocks horizontal gene transfer. Conclusions: LEF-Cu disinfection holds promise for preventing horizontal gene transfer and providing safe drinking water for household applications.

Air Conditioning Energy Efficiency and Thermal Comfort in Hotel Buildings in Hot and Humid Tropical Climates

The objective of this research is to examine energy consumption efficiency strategies with respect to the type of dwelling unit, cooling load, and thermal comfort. This can be evaluated through the study of the hotel building air system, with the aim of ensuring the thermal comfort of its occupants. This research employs a quantitative methodology, using observation, measurement, and experimental techniques. The case study is situated within the context of hotels in Makassar City, South Sulawesi Province, Indonesia. The subject of this study is the Swissbel Hotel building, located in the coastal area of Makassar City. The data are analyzed in order to determine the Energy Consumption Intensity (IKE), Room Energy Intensity (REI), and occupancy rate based on the heat load inside and outside the building. The data are then processed using a parametric statistical approach. Subsequently, the building envelope is analyzed through the calculation of the Overall Thermal Transfer Value (OTTV) in accordance with the standards set out in SNI 6390: 2011. The cooling load and a thermal comfort assessment, in line with the Predicted Mean Vote (PMV) index, Predicted Percentage of Dissatisfaction (PPD) index, and effective temperature according to the ASHRAE 55-2022 standard, are then calculated, and a simulation is performed to determine the most efficient strategy for the use of air conditioning energy. The findings indicated that alterations in the dimensions of the facade (sun shading) resulted in a 16% reduction in the cooling load, with the incorporation of horizontal and vertical shading sizes of 4 m × 2.5 m, square glass openings, and 8 mm heat-absorbing glass. This led to a PMV value of 0.40, a PPD of 8%, and an effective temperature value of 26.8°C. The modification resulted in a percentage gain of 20.08%, at 10-60% occupancy load with a cooling load reduction rate of 1,912,071 kW and a thermal comfort index within the comfortable range.

Decoding carbon neutrality targets: insights from Indonesia’s economic and energy perspective

Abstract To achieve carbon neutrality, it is essential for Indonesia to promote the integrated development of its energy, environmental, and economic systems (3E). This research examines the potential integration of economic growth, energy intensity, and renewable energy consumption into efforts to reach carbon neutrality in Indonesia. Utilizing data from 1990 to 2020, the study investigates the impact of these factors on CO2 emissions through multiple linear regression analysis. The findings indicate that economic growth, energy intensity, and renewable energy consumption are pivotal in pursuing carbon neutrality. While economic growth slightly contributes to CO2 emissions, the effect is not statistically significant, although the ecological Kuznets curve is observed. On the other hand, increased energy intensity significantly raises CO2 emissions, presenting a challenge to meeting carbon neutrality goals. Conversely, greater use of renewable energy has a notable effect in reducing CO2 emissions and supporting carbon neutrality efforts. Key policy recommendations include advancing a green and digital-based economy, expanding clean energy utilization, and adopting sustainable green technologies.

Development of a universal plug tray seeder for small seeds based on electrostatic adsorption

Addressing the limitations of the traditional air suction plug tray seeder regarding versatility, clogging, noise, and energy consumption, a novel plug tray seeding method suitable for a broader range of small seed sizes has been proposed. A universal plug tray seeder has also been designed based on electrostatic adsorption for small seeds. Key factors affecting seed electrostatic adsorption were analyzed through electrostatic simulation, determining the optimal manufacturing method for the suction needle and the best range for the electrostatic voltage. Leveraging the theory of granular dynamics, a seed vibration box was designed using the principle of microphone vibration to enhance seed flowability and reduce the multiple seeding rate. Furthermore, the control system achieved seed recognition based on YOLOv8n and adaptive matching of seeding parameters, enhancing the universality of the seeder. The seeder was optimized and validated through practical experiments, with a comparative analysis of energy consumption and sound intensity conducted. The results indicated that the electrostatic suction needle, made with a single copper electrode of 1 mm diameter and coated with a 1 mm thick planar epoxy resin adsorption layer, along with an electrostatic voltage of 5 ∼ 10 kV, could effectively adsorb seeds. The vibration box significantly improved the seeding effect by vibrating seeds of tomato, pepper, and muskmelon at frequencies of 10 ∼ 25 Hz, and seeds of broccoli, cabbage, and eggplant at frequencies of 30 ∼ 50 Hz. The combined action of the electrostatic suction needle and the vibrating seed box resulted in an 83.20 % reduction in energy consumption and a significant decrease in sound intensity. Although the single seeding rate for muskmelon and cabbage seeds slightly decreased due to higher rates of leakage seeding and multiple seeding, the single seeding rate for other seeds remained around 90 %. This study provides a theoretical foundation for the universal seeding method of small seeds and offers significant reference value for the design of low-energy, low-noise plug tray seeders.

Can new-type urbanization construction policy mitigate energy consumption intensity? Evidence from Chinese listed enterprises

Can new-type urbanization construction policy mitigate energy consumption intensity? Evidence from Chinese listed enterprises

Toward the Construction of a Sustainable Society: Assessing the Temporal Variations and Two-Dimensional Decoupling of Carbon Dioxide Emissions in Anhui Province, China

This study comprehensively assessed carbon dioxide emissions over a span of two decades, from 2000 to 2020, with the decomposition and decoupling analyses considering multiple influence factors across both short-term and long-term dimensions. The results revealed great fluctuations in the decoupling analysis index (DAI) for subjected sectors such as natural resource processing, electricity, gas, water, textiles, machinery, and electronics manufacturing. Of note, significantly changed sectoral DAIs were observed in urban traffic and transportation, logistics warehousing, and the postal industry within Anhui Province. In contrast, the DAIs of other sectors and social services exhibited a weak decoupling state in Anhui Province. The industrial sectors responsible for mining and textiles and the energy structure encompassing electricity, gas, and water emerged as the primary contributors to carbon dioxide emissions. Additionally, the efficiency of the socio-economic development (EDE) was identified as the principal driver of carbon dioxide emissions during the observed period, while the energy consumption intensity (ECI) served as the putative crucial inhibiting factor. The two-dimensional decoupling of carbon dioxide emissions attributable to the EDE demonstrated a gradual transition from industrial sectors to buildings and tertiary industries from 2000 to 2020. In the future, the interaction between urban carbon dioxide emissions and the socio-economic landscape should be optimized to foster integrated social sustainable development in Anhui Province.

Analysis of Decoupling Effects and Influence Factors in Transportation: Evidence from Guangdong Province, China

In recent years, global environmental issues have become increasingly prominent. The transportation industry, as the fundamental sector of national economic development, is also characterized by high energy consumption and carbon emissions. Therefore, it is imperative to conduct research on the carbon emission problem within this industry. In light of the Tapio decoupling model, an analysis of the correlation between traffic carbon emissions and economic development in Guangdong province during 1999–2019 was carried out. With the aim of encouraging Guangdong province’s low-carbon transportation development, the factors affecting the transportation industry are analyzed utilizing the generalized Divisia index model (GDIM). We also introduced passenger and freight turnover as an influencing factor for analysis. The findings indicate that (1) Guangdong province’s traffic carbon emissions increased from 1999 to 2019; (2) the traffic carbon emissions’ decoupling effect is mainly “weakly decoupled”, and the overall decoupling effect is not strong in Guangdong province; (3) among the traffic carbon emissions’ factors, the effects of the production value of traffic and the turnover volume are at the forefront, and the effect of turnover volume has gradually exceeded the production value of traffic in recent years. The suppression of the intensity of carbon emissions is relatively large, while the suppression of the intensity of energy consumption and transport is relatively weak. Based on this, strategies were proposed to promote a cleaner energy mix, improve energy use efficiency, create energy savings, develop green technologies, and foster the restructuring of transportation.

ESG, Cohort Effect, and Energy Consumption Intensity

ESG, Cohort Effect, and Energy Consumption Intensity

Occupancy and equipment usage prototype schedules for building energy simulations of office building types in China

The accuracy of occupancy and energy-consuming equipment schedules significantly influences building energy simulations. Existing standards provide generalized schedules that do not fully capture variations across different office building types and periods. This study utilizes questionnaire data from office buildings across four Chinese cities to extract refined prototypes for occupancy and equipment usage schedules using hierarchical clustering analysis. Specific schedules are developed for summer workdays, winter workdays, summer weekends, and winter weekends, covering HVAC, lighting, and office equipment. For instance, the extracted lighting schedule increases annual energy consumption intensity by 25.35% compared to standard schedules. Additionally, XGBoost models identify key factors influencing equipment usage; for HVAC, floor number emerges as most significant. The study's prototypes offer more realistic inputs for building energy simulations, enhancing accuracy and guiding energy-efficient building design and management strategies in China.

Polymer-Injection Pilot in Colombian Field Indicates Reduced Carbon Footprint

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218169, “Carbon Footprint and Energy Intensity Assessment for Enhanced Oil Recovery (EOR) Based on Polymer Injection: A Colombian Case Study,” by Henderson I. Quintero, SPE, Pedro L. Solorzano, SPE, and Carolina Barbosa, Ecopetrol, et al. The paper has not been peer reviewed. _ Chichimene is an oil field in eastern Colombia. Since 2014, enhanced oil recovery (EOR) using a water-injection process has been performed successfully in part of this field. A polymer-injection pilot was executed over five injection patterns to optimize this process as a promising strategy for polymer-based EOR in challenging reservoir conditions with high temperatures and heavy oil. Field Background Included in Colombia’s energy-transition strategy are EOR technologies that, through the acceleration of oil production even with low energy consumption, increase the efficiency and carbon intensity of conventional oil-production processes. Several studies in the literature have reported improved energy and carbon indicators as a result of implementing EOR using thermal and chemical methods. Among these, polymer injection promises higher incremental oil production with lower energy consumption. The polymer-flooding (PF) pilot in the Chichimene field was performed to evaluate this technology’s ability to displace the heavy crude oil of the Fm1 formation (350–700 cp). The reservoir is more than 20 km long by 6 km wide and features 250–300 ft of thickness, with permeability between 100 md and 10 D and a depth of approximately 6,200 ft true vertical depth subsea. Polymer injection began at the end of 2015 in an extensive pattern (N1), followed by a smaller pattern (N2) in 2018 after a short water-injection stage. The polymer injection in medium patterns (N3 and N4) and a second small pattern (N5) began in 2019, being considered early chemical EOR because they were performed after the primary production stage. The well spacing of the patterns is 10 and 40 acres, respectively. The producer wells of each pattern are displayed in Table 1 of the complete paper. The PF project injected 21.65 thousand STB of polymer solution. At the end of 2022, incremental oil production was 4.9 billion bbl. At the time of writing, patterns show incremental recovery factors of between 4 and 9%. The reservoir showed strong signals of repressurization, gas/oil ratio reduction, water/oil ratio control, and oil incremental recovery. Energy consumption and carbon intensity were calculated for the oil production baseline case [waterflooding (WF) or primary production] and PF, considering the field’s energy matrix. The results were compared to quantify the effect of PF on these efficiency indicators. Evaluation of Product System Energy consumption was calculated for each phase involved in the processing system: lifting fluids, oil dehydration, water-clarification treatment, water reinjection, and PF. The evaluation did not include solvent or facilities to dilute the crude oil or the pumping energy used to deliver the oil to the pipeline system. Currently, the total volume of water produced is reinjected into the reservoir for pressure maintenance and oil-recovery purposes. Also, part of the produced gas is used in heaters and fire tubes for dehydration, but most is burned in a gas flare.

Assessing and gauging the carbon emission efficiency in China in accordance with the sustainable development goals

In light of the growing urgency of climate change, carbon emissions reduction has emerged as a pivotal concern within global governance. In this paper, we take carbon emission efficiency (CEE) as the research object to characterize the relationship between economic, social, and environmental development in the context of the Sustainable Development Goals (SDGs). According to the regional division standard of eight comprehensive economic zones in China, this paper analyzed the spatial differences, evolutionary characteristics, and influencing factors of CEE in 257 Chinese cities over the period 2003–2019. The analysis conducted the Dagum Gini Coefficient, Markov Transition Probability Matrix, and geographically and temporally weighted regression model (GTWR). The results demonstrate that: (1) The CEE of Chinese cities exhibits an upward trajectory. (2) The inter-differences among the eight comprehensive economic zones represent the primary spatial source of CEE divergence. (3) The CEE of Chinese cities is a staged process of gradual enhancement with spatial spillover effects. (4) Environmental regulation, energy consumption intensity, and green finances are significant factors affecting CEE, and the direction and intensity of their influence have distinct spatial heterogeneity. Ultimately, this paper proposes measures to narrow the development gap between regions and enhance the CEE across the region. Meanwhile, implementing regional refinement management and formulating differentiated regional sustainable development planning.

Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

The Energy Effect of Blockchain Technology Innovation in the Industry 5.0 Era--From the Perspective of Carbon Emissions

In the era of Industry 5.0, innovation in blockchain technology is expected to have a significant impact on energy efficiency and carbon emissions, especially in hybrid energy systems. This paper has obtained the innovation data on the blockchain patent of listed companies in China from 2010 to 2022 by machine learning and text analysis methodology of large language model. On this basis, the relationship between the enterprises’ blockchain technology innovation and the intensity of fossil energy consumption has been discussed. The study found that (1) the enterprises’ blockchain technology innovation is able to reduce the intensity of fossil energy consumption, and this conclusion remains valid via controlling for endogeneity and upon the completion of robustness test. (2) In terms of the mechanism, the enterprises’ blockchain technology innovation can achieve energy transition by reducing the cost of internal control, strengthening external supervision, improving the efficiency of resource allocation and strengthening the channels of supply chain management. (3) Further research has found that the energy effects as a result of blockchain technology innovation help to improve operational efficiency and lower the level of carbon emission. Our research provides scientific support for breaking the "technological energy paradox" in the field of energy economy while providing empirical evidence of "blockchain carbon reduction" for technologies such as blockchain BaaS alliance, cross-operator network spectrum, and shared base stations that will be applied on a large scale in the Industry 5.0 Era.

Decoupling relationship between logistics growth and carbon emissions and driving factors in Chongqing: A novel decomposition framework

A comprehensive understanding of the logistics decoupling status and driving factors is of immense theoretical and practical importance for rationally formulating low-carbon logistics policies and accelerating the realization of high-quality development. Present study introduces the logarithmic mean Divisia index method (LMDI) decomposition technique into Tapio index model, extends traditional decoupling model, and establishes a new analytical framework for the decoupling relationship between logistics growth and carbon emissions. Using long-term data from Chongqing (1997–2021), this study investigated the Chongqing logistics decoupling relationship and driving factors. The study found the following: (1) Chongqing logistics carbon emissions show phased changes and face greater pressure to reduce emissions. (2) The decoupling status of logistics growth and carbon emissions is predominantly expansive and weak decoupling, with an overall evolutionary trend of “expansive decoupling–weak decoupling–strong decoupling. The average decoupling index in 2013–2021 was 0.5523, indicating a decreasing trend; however, there was still a large gap in realizing a strong decoupling goal. (3) The energy consumption intensity effect facilitates logistics carbon decoupling, the economic scale effect has a strong inhibiting effect, and the industrial structure effect and transportation intensity effect are staged. Finally, targeted policy recommendations are proposed to expedite logistics carbon emissions decoupling in Chongqing.

ENERGY AUTOMATION SUPPORTS ENERGY CONSUMPTION INTENSITY IN CLASSROOMS

Automation of energy use to control energy consumption intensity (IKE) in classrooms is carried out using an Arduino Nano-based system. This system utilizes an IR transmitter to send signals to the air conditioning unit, a servo motor to position the IR transmitter to the appropriate air conditioning unit, a relay to control the lights, and a Real-Time Clock (RTC) module for scheduling based on a specified schedule. The main goal is to prevent energy waste and ensure comfort by turning on and off the air conditioning unit and lights according to a preset schedule. This automatic scheduling includes time setting, transmitter IR control, servo motor, relay control, and LCD. Programmed scheduling ensures that the air conditioner and lights only turn on when needed, while the LCD provides real-time information about the status of the air conditioner and lights. With this automation, the system helps reduce excessive energy consumption, drives significant energy savings, and creates a comfortable and energy-efficient learning environment. The automatic monitoring and regulation system also allows users to focus more on teaching and learning activities without having to worry about manual settings for air conditioning and lights.

Spatiotemporal Evolution Characteristics and Influencing Factors of Industrial Carbon Emissions in the Yellow River Basin

Scientific assessment of industrial carbon emissions in the Yellow River Basin and identification of its influencing factors are of great importance for promoting green transformation, ecological protection, and high-quality development of the Yellow River Basin. Considering nine provinces in the Yellow River Basin as the research objects； using relevant data on industrial development and energy consumption in the Yellow River Basin from 2000 to 2019； and with the help of IPCC carbon emission measurement, spatial autocorrelation, and LMDI decomposition, the spatial and temporal evolution characteristics and influencing factors of carbon emissions from industries and industrial sectors in the Yellow River Basin were analyzed. Reasonable suggestions were put forward for reducing the carbon emissions from industries in the Yellow River Basin. The results showed that： ① From 2000 to 2019, industrial carbon emissions in the Yellow River Basin showed a fluctuating growth trend, with a decreasing growth rate. The spatial pattern changed from "low in the upstream and high in the middle and downstream" to "high and low value distribution," and the spatial difference gradually expanded. ② The high carbon industry was the most important source of industrial carbon emissions in the Yellow River Basin, accounting for 96.35% of the carbon emissions between the industries with a continuous growth trend, which was a significant difference. The middle and low carbon industry carbon emissions and the total proportion was low, showing different fluctuations； nine provinces and nine industrial industries had significant spatial variability. ③ Energy structure intensity, economic scale, and population scale promoted the increase in industrial carbon emissions in the Yellow River Basin and energy consumption intensity had an inhibitory effect on the increase in carbon emissions. The economic scale effect was positive and significant, which offset the negative effect of energy consumption intensity. Spatial variability was observed in the contribution value of the influence effect of the factors affecting the carbon emissions of the industry in nine provinces.

Comparative Study of Energy Consumption Intensity: A Case Study of the Faculty of Electrical Engineering and Informatics (FEI) Versus the Faculty of Chemical Technology (FChT) in the City of Pardubice

Abstract The study’s comparative aspect between the Faculty of Electrical Engineering and Informatics (FEI) and the Faculty of Chemical Technology (FChT) buildings is pivotal for elucidating nuanced differences in energy consumption practices within academic institutions, facilitating targeted energy efficiency measures. The research methodology adopts a comparative case study approach to examine two focal research buildings. Analysis entails computing energy consumption intensity per unit area for both buildings and comparing energy consumption data to identify disparities. The need for understanding energy consumption patterns and improving energy efficiency in academic infrastructure is directly addressed through variables studied in the comparative analysis, including energy consumption comparison, annual and monthly variations, ratio, and intensity. The data indicates that the average heating intensity in the FChT building surpasses that of the FEI building by a factor of 2.3, signifying significant disparities in heating energy consumption trends between the two structures and suggesting potential areas for targeted energy efficiency interventions. Moreover, the average electrical intensity in the FChT building is over 1.7 times higher than in the FEI building. Interestingly, despite the FChT building being 2.6 times larger than the FEI, its intensity does not always correspond with the increase in building area, indicating additional factors influencing energy consumption.

Impacts of the sea-rail intermodal transport policy on carbon emission reduction: The China case study

China introduced the Intermodal Transport Demonstration Project Policy in 2015, spurring the rapid expansion of sea-rail intermodal transport (SRT) at coastal ports. This policy is of crucial importance as SRT is pivotal in supporting the transport sector's achievement of the “double carbon target”. Despite strong policy backing and notable growth of SRT, the impact of these SRT demonstration projects on curbing transport carbon emissions has not been comprehensively evaluated. This study addresses this gap by using panel data from hub seaports across nine provinces and applying a multi-period-continuous difference-in-differences model. The research quantifies SRT's contribution to reducing transport carbon emission reductions as a result of the policy. Key findings indicate: (1) Each 10,000 TEU increase in containerized SRT volume results in a 0.162% reduction in transport carbon emissions, with projected growth by 2025 leading to a 9.02% decrease in emissions. (2) SRT lowers transport energy consumption and carbon emission intensity, fostering a green transformation in energy use. (3) Geographical analysis indicates that policy implementation in the southern region requires further strengthening. This study enhances empirical understanding of low-carbon SRT development in hub ports, emphasizing its critical role in China's transition to decarbonized transport. It also highlights the importance of regional policy effectiveness, offering valuable insights for policymakers striving to promote sustainable transport modes.