Energy Consumption Intensity Research Articles

Impact of Artificial Intelligence Technology on Carbon Emission Intensity of Energy Consumption in China and Examination of Spatial Effects

<p style="text-align:justify;" align="justify"><font face="Times New Roman"><span style="font-family:宋体;font-size:10.5000pt;font-weight:normal;line-height:125%;text-justify:inter-ideograph;">This paper investigates the impact of artificial intelligence technology on energy consumption carbon emission intensity and its spatial effect in Chinese provinces. By analyzing the 2012-2021 data of 30 provinces and cities in China, this paper constructs a spatial Durbin panel model to test the direct and indirect effects of the application of AI technology on energy consumption and carbon emission intensity. The results show that artificial intelligence innovation development index, digital finance index, and the environmental regulation intensity</span></font><span style="font-family:宋体;font-size:10.5000pt;font-weight:normal;line-height:125%;text-justify:inter-ideograph;"> </span><font face="Times New Roman"><span style="font-family:宋体;font-size:10.5000pt;font-weight:normal;line-height:125%;text-justify:inter-ideograph;">reduce the provincial energy consumption carbon emission intensity, while</span></font><span style="font-family:等线;font-size:11pt;line-height:125%;text-justify:inter-ideograph;"> </span><font face="Times New Roman"><span style="font-family:宋体;font-size:10.5000pt;font-weight:normal;line-height:125%;text-justify:inter-ideograph;">Per capita GDP level, urbanization rate, and industrial energy consumption intensity significantly increase the energy consumption carbon emission intensity. In addition, industrial structure upgrading and industrial</span></font><span style="font-family:等线;font-size:11pt;line-height:125%;text-justify:inter-ideograph;"> </span><font face="Times New Roman"><span style="font-family:宋体;font-size:10.5000pt;font-weight:normal;line-height:125%;text-justify:inter-ideograph;">technological progress, as mediating variables, have a significant inhibiting effect on carbon emission intensity. The study concludes that the application of AI technology can effectively reduce provincial carbon emission intensity by optimizing energy consumption and carbon emission scenarios, thus promoting the goal of green and low-carbon development in China.</span></font></p>

Interfacial Water Regulation for Nitrate Electroreduction to Ammonia at Ultralow Overpotentials.

Nitrate electroreduction is promising for achieving effluent waste-water treatment and ammonia production with respect to the global nitrogen balance. However, due to the impeded hydrogenation process, high overpotentials need to be surmounted during nitrate electroreduction, causing intensive energy consumption. Herein, a hydroxide regulation strategy is developed to optimize the interfacial H2O behavior for accelerating the hydrogenation conversion of nitrate to ammonia at ultralow overpotentials. The well-designed Ru─Ni(OH)2 electrocatalyst shows a remarkable energy efficiency of 44.6% at +0.1V versus RHE and a nearly 100% Faradaic efficiency for NH3 synthesis at 0V versus RHE. In situ characterizations and theoretical calculations indicate that Ni(OH)2 can regulate the interfacial H2O structure with a promoted H2O dissociation process and contribute to the spontaneous hydrogen spillover process for boosting NO3 - electroreduction to NH3 at Ru sites. Furthermore, the assembled rechargeable Zn-NO3 -/ethanol battery system exhibits an outstanding long-term cycling stability during the charge-discharge tests with the production of high-value-added ammonium acetate, showing great potential for simultaneously achieving nitrate removal, energy conversion, and chemical synthesis. This work can not only provide a guidance for interfacial H2O regulation in extensive hydrogenation reactions but also inspire the design of a novel hybrid flow battery with multiple functions.

Key Problems and Strategies for Greenhouse Gas Reduction in China's Wastewater Treatment Industry

The wastewater treatment industry is an energy-intensive industry and one of the main sources of high warming potential greenhouse gases （GHG） such as CH4 and N2O. The GHG reduction in this industry is an important part of achieving global climate goals. In 2019, there were 4 359 urban wastewater treatment plants in China, with a total wastewater treatment volume of 63.26 billion m3, ranking first in scale worldwide. From 2009 to 2019, the energy consumption, GHG emissions, and GHG emissions intensity of wastewater treatment in China increased by 161.78%, 193.55%, and 41.54%, respectively. Faced with the new situation, new tasks, and new requirements of the collaborative promotion of carbon reduction, pollution reduction, green expansion, and growth, water pollutant reduction needs to be coordinated with GHG reduction. To this end, the sources and trends of energy consumption and GHG emissions in the wastewater treatment industry were identified, and the situation and challenges to GHG reduction in this industry were analyzed. The results indicated that the wastewater treatment industry in China has been facing problems such as a lack of carbon emission-related standards, insufficient energy self-sufficient technology reserves, lack of coordination between wastewater treatment levels and carbon emissions control, and inadequate infrastructure and operation and maintenance management. Based on this, it is necessary to accelerate the top-level design of GHG reduction in the wastewater treatment industry； strengthen the research and development, verification, demonstration, and integrated application of disruptive technologies； expand the natural-based solution as a technological supplement； innovate refined management in the wastewater treatment industry； and ultimately promote the reconstruction of the wastewater treatment industry.

Green supply chain management, green technology innovation and firms' energy consumption intensity

Green supply chain management, green technology innovation and firms' energy consumption intensity

Green credit policy and energy consumption intensity in China: Firm-level evidence and insights.

The transition to sustainable development has become a global priority, with energy transformation serving as a key component. In this context, green financial instruments play a crucial role in shaping corporate energy-saving behaviors and promoting sustainable development. This paper examines the impact and mechanism of China's first green credit policy (GCP) on energy consumption intensity (ECI) of manufacturing firms in China, using a difference-in-difference (DID) approach with micro-level data (2004-2009). We find that GCP significantly reduces enterprise ECI, primarily by promoting green technological innovation and capital renewal. We also learn that the effect of GCP varies with firm and industry characteristics, such as financial dependence, size, ownership, capital intensity, and industrial chain position. Moreover, the outcomes suggest that the effect of GCP is stronger in regions with higher degrees of financial development and marketization. This study contributes to the literature on green finance, environmental regulation, and energy efficiency by providing novel evidence on how GCP influences ECI from a micro perspective.

Understanding Emission Trends, Regional Distribution Differences, and Synergistic Emission Effects in the Transportation Sector in Terms of Social Factors and Energy Consumption

China’s transportation sector plays a significant role in reducing carbon dioxide (CO2) and air pollution. Previous studies have predominantly utilized scenario analysis to forecast emissions for the next 30 to 50 years based on coefficients from a base year. To elucidate the current state of gas emissions in the transportation sector, this study employed panel data for 10 types of gas emissions from 2001 to 2020, analyzing their emission characteristics, tendencies, and synergistic effects. Utilizing the Kaya equation and the logarithmic mean division index (LMDI) decomposition method, we developed a model of pollutant emissions that considers the synergistic effects, pollution emission intensity, energy mix, energy consumption intensity, and population. The results show that all pollutants in the transportation sector decreased except for NH3 and CO2. There was a synergistic effect between air pollutants and CO2 emissions, but the reduction was not significant. From 2013 to 2020, the transportation sector shifted from a high emission intensity with low synergy to a low emission intensity with high synergy. The results indicate that off-road mobile vehicles, on-road diesel vehicles, and motorcycles became the main source of emissions from transportation in certain provinces, and a key area requiring attention in policy development. Gasoline consumption was identified as the primary contributor to the significant increase in synergistic emission variability in the transportation sector. These results provide policymakers with practical ways to optimize emission reduction pathways.

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.

Spatio-Temporal Variation and Drivers of Land-Use Net Carbon Emissions in Chengyu Urban Agglomeration, China

Land-use change is an important cause of carbon emissions (CEs). In the context of achieving carbon peaking and carbon neutrality goals, understanding the coupling mechanisms between land-use change and CEs is of great significance for fostering regional low-carbon sustainable development. In this study, the land-use net carbon emissions (LCN) calculation and evaluation model was built based on the perspective of land-use change. The land-use variation matrix, standard deviation ellipse, and spatial autocorrelation analysis were used to analyze the spatio-temporal evolution of land-use and the LCN in the Chengyu urban agglomeration (CUA) from 2000 to 2020. Meanwhile, the economic contribution coefficient and ecological support coefficient were applied to evaluate the alignment among the CEs, socio-economic development, and the ecological environment. In addition, the modified Kaya and Logarithmic Mean Divisia Index (LMDI) models were used to quantitatively analyze the drivers and underlying influence mechanisms of the LCN. The results showed the following: (1) The area of built-up land and forest land expanded rapidly, mainly transforming grassland and farmland to built-up land and forest land in the CUA during the study period. The built-up land was the main source of the regional CEs. The land-use changes led to the migration of the LCN center and the variations in spatial clustering. (2) The growth rate of the LCN decreased after 2010, and the disparities in carbon productivity and the carbon compensation rate among the cities gradually narrowed from 2000 to 2020. The alignment among the regional CEs, socio-economic development, and ecological environmental governance was effectively improved. (3) The economic development level and energy consumption intensity were the primary facilitator and inhibitor of the LCN, respectively. The results could offer valuable references and insights for formulating regional carbon reduction strategies and policies.

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.

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. 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. 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. 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.