Efficient Carbon Research Articles

The War of the Efficiencies: Understanding the Tension between Carbon and Energy Optimization

Major innovations in computing have been driven by scaling up computing infrastructure, while aggressively optimizing operating costs. The result is a network of worldwide datacenters that consume a large amount of energy, mostly in an energy-efficient manner. Since the electric grid powering these datacenters provided a simple and opaque abstraction of an unlimited and reliable power supply, the computing industry remained largely oblivious to the carbon intensity of the electricity it uses. Much like the rest of the society, it generally treated the carbon intensity of the electricity as constant, which was mostly true for a fossil fuel-driven grid. As a result, the cost-driven objective of increasing energy-efficiency --- by doing more work per unit of energy --- has generally been viewed as the most carbon-efficient approach. However, as the electric grid is increasingly powered by clean energy and is exposing its time-varying carbon intensity, the most energy-efficient operation is no longer necessarily the most carbon-efficient operation. However, the recent focus on exploiting the flexibility of computing's workloads---along temporal, spatial, and resource dimensions---to reduce carbon emissions, comes at the cost of either performance or energy efficiency. In this paper, we quantify the trade-offs between energy efficiency and carbon efficiency in exploiting computing's flexibility and show that blindly optimizing for energy efficiency is not always the right approach. 1

Applications of Titanium Dioxide (TiO2) Nanoparticles in Photocatalysis

Titanium dioxide nanoparticles (TiO2 NPs) are conspicuously preferred as photocatalyst among the transition metal oxide nanoparticles. It exhibited in three polymorphisms of steady state rutile phase while brookite and anatase sustaining in metastable phase. The mixed phases of anatase phase and rarely found brookite phase mostly preferred for the photodegradation applications. The economically affordable along with nontoxic nature on top of excellent opto-electronics and catalytic properties of TiO2 NPs are eminently favorable for the photocatalytic degradation of chemically complex structured numerous organic and inorganic dyes, phenol and phenol-based derivatives, passive microplastics as well as suspended matters, non-biodegradable cytostatic drugs, acetaminophen, pharmaceutical organic waste compounds in addition to water pollutants. The photocatalytic capability of these NPs enhanced by upgrading the structural and morphological nature by opting different synthesis techniques as well preparing the nanocomposites of TiO2 incorporation with other metals. The hydrothermally prepared polymeric membranes of polyvinylidene with TiO2 NPs effectively (more than 90%) removed 17 α–ethinylestradiol from the contaminated water compared to Diclofenac under Uv irradiation. As it fronting the issue of electrostatic repulsion to all other membranes surface. The grafted membrane recorded highest degradation efficiency of 95.4% and best reusability of 90% saturated at fifth recycle for Methylene Blue azo dye compared with blending and dip coating membranes. The TiO2 modified ultrafiltration membranes of Polyvinylidene Fluoride with Dopamine illustrated the 92.6% photocatalytic degradation of Sulfadiazine which is most hazardous and highly resistant to biodegradation. 100% degradation of phenol derivative by TiO2 NPs hybrid polymeric films in visible light irradiation. The degradation efficiency of heterogenous photocatalyst Carbon–TiO2 contained anatase and brookite phased for Methylene Blue dye was 100% while for Rhodamine–B higher than 99% in solar and more than 78% in LED light irradiation. The recent trends for improvisation of photocatalytic ability of TiO2 NPs to enhance the quality of water and hence the mankind are elaborated.

An Agile Pathway Towards Carbon-Aware Clouds

Climate change is a pressing threat to planetary well-being that can be addressed only by rapid near-term actions across all sectors. Yet, the cloud computing sector, with its increasingly large carbon footprint, has initiated only modest efforts to reduce emissions to date; its main approach today relies on cloud providers sourcing renewable energy from a limited global pool of options. We investigate how to accelerate cloud computing's efforts. Our approach tackles carbon reduction from a software standpoint by gradually integrating carbon awareness into the cloud abstraction. Specifically, we identify key bottlenecks to software-driven cloud carbon reduction, including (1) the lack of visibility and disaggregated control between cloud providers and users over infrastructure and applications, (2) the immense overhead presently incurred by application developers to implement carbon-aware application optimizations, and (3) the increasing complexity of carbon-aware resource management due to renewable energy variability and growing hardware heterogeneity. To overcome these barriers, we propose an agile approach that federates the responsibility and tools to achieve carbon awareness across different cloud stakeholders. As a key first step, we advocate leveraging the role of application operators in managing large-scale cloud deployments and integrating carbon efficiency metrics into their cloud usage workflow. We discuss various techniques to help operators reduce carbon emissions, such as carbon budgets, service-level visibility into emissions, and configurable-yet-centralized resource management optimizations.

PRODUCTION OF COMPOSITE CARBON ADSORBENTS BASED ON TEXTILE CORD OBTAINED FROM CAR TIRE RESIDUES

Carbon chemistry opens up very wide prospects in obtaining compositions based on carbon-containing raw materials, due to the achievements of recent years in this field. Due to their unique properties, extremely high chemical resistance, thermal resistance, heat resistance and specific strength, carbon materials have found application for the manufacture of carbon-containing refractory, high-temperature composite materials, modified electrodes as fillers for the tire and rubber industry, catalytic systems based on carbon-containing raw materials, etc. Frequently used carbon materials do not meet the requirements of the technological process, in some cases their use is economically unjustified, since they are expensive and have a small raw material base. Therefore, obtaining new efficient and cheap natural carbon materials from available types of industrial raw materials is one of the urgent tasks currently facing scientists and technologists. Textile wire, a product of processing rubber organic waste, can become a promising new raw material for the production of carbon-containing materials. Porous carbon materials were obtained in a laboratory installation, optimal parameters were determined, and the physico-chemical properties of the feedstock and the obtained adsorbents (ash content, humidity, volatility, density, sumar pore volume, elemental composition) were studied.

Fate of Ca2+ and metal impurities of a typical coal fly ash in amino acid mediated CO2 mineralization and simultaneous CaCO3 recovery

CO2 mineralization is a promising technology to achieve a waste-to-resource chain by integrating CO2 sequestration and alkaline solid waste utilization. Amino acids as a multifunctional reagent was proposed to avoid the extensive consumption of acid and alkaline reagents in traditional processes. However, the detailed interaction between Ca-bearing minerals and amino acids are still not fully understood, as well as migration pathways of metal impurities. To fill these gaps, this paper investigated the leaching and carbonation behaviors of Ca2+ and metal impurities of a typical coal fly ash (CFA) at various reagent types, reagent concentrations and leaching temperatures, thereby exploring the fate of these metal impurities. Results showed that the leaching and carbonation of Ca2+ was influenced by various aspects such as initial pH, reagent pKa, complexation, and pH buffering. The CaCO3 products obtained from glycine (Gly) and alanine (Ala) were vaterite due to the stabilizing effect of these amino acids on vaterite preventing it from converting to calcite. The optimal reaction conditions were 1.0 M Gly and leaching temperature of 35 °C with 26.63 % leaching efficiency, 56.08 % carbonation efficiency, and 42.6 g/kg vaterite yield. In addition, Ala induced an unexpected high leaching efficiency of Cd (75.79 %), Pb (76.08 %), and Zn (41.62 %), respectively, indicating promising mitigation of the environment risk of leached residue and valuable metal recovery from CFA. Although Gly displayed limited metal leaching efficiency at 1.0 M and 25 °C, increasing leaching temperature induced a remarkable enhancement of Cd and Pb leaching, which were 88.54 % and near 100 % at 35 °C, indicating promising mitigation of the environment risk of leached CFA. However, the high binding affinity of amino acids to impurity metals led to the low purity of CaCO3 product. This study derives the migration pathways of various metal ions during the mineralization and utilization of CFA, making it of great significance for the resource management and utilization of solid wastes.

Multiscale Equation-Oriented Optimization Decreases the Carbon Intensity of Shale Gas to Liquid Fuel Processes.

Shale gas is revolutionizing the U.S. energy and chemical commodity landscape and can ease the transition to a sustainable decarbonized economy. This work develops an equation-oriented (EO) multiscale modeling framework using the open-source IDAES-PSE platform that tractably incorporates microkinetic detail in process design via reduced-order kinetic (ROK) models. Using multiobjective optimization with embedded heat integration and life-cycle analysis, we simultaneously minimize the minimum selling price of liquid hydrocarbons (e.g., liquid fuels/additives from shale gas) and process emissions (via a CO2 tax). Optimization reduces greenhouse gas emissions per MJ of fuel produced by over 35% compared to the literature and achieves a carbon efficiency of 87%. The optimizer changes the recycling rate, temperatures, and pressures to mitigate the effect of ROK model-form uncertainty on product portfolio predictions. Moreover, we show that the optimal process design is insensitive to changing CO2 tax rates. Finally, the EO framework enables a fast sensitivity analysis of shale gas composition variability across 12 regions of the Eagle Ford basin. These results highlight the benefits of the open-source EO framework: fast, scalable, customized, and reproducible system analysis and optimization for sustainable energy technologies beyond shale utilization.

A review of carbon-based adsorbents for the removal of organic and inorganic components

Abstract Carbon-based adsorbents like graphene and its derivatives, carbon nanotubes, activated carbon, and biochar are commonly used for removing heavy metals from water solutions. The changeable exterior functional groups of efficient carbon adsorbents for HMs are one of their key features. Detailed documentation of the synthesis and interactions of functionalized carbon adsorbents with metals in an aqueous solution is crucial for advancing the utilization of these materials in HM exclusion. This paper reviews the carbon-based adsorbent for material removal. It examines several carbon adsorbents’ exterior functional groups to better understand how they eliminate HMs from aqueous solutions. First, the controlling mechanisms for the deletion of aqueous HMs by carbon adsorbents are described, with a particular emphasis on the functions of exterior functional groups. The following section lists and organises the numerous synthetic techniques that are frequently employed to add heteroatoms to carbon surfaces, particularly oxygen, nitrogen, and sulphur, to increase their exterior properties and their sorptive capabilities towards HMs in aqueous solutions. Following that, the impact of dissimilar functional groups on the adsorption characteristics of HMs on carbon adsorbents is examined. While the adsorption capacity and metal removal efficiency of the changed carbonaceous materials are high, the alteration operation is complicated, particularly chemical modification. This review analyses the shortcomings that are now present and offers ideas for future research while emphasising the removal of inorganic and organic components utilising carbon-based materials as adsorbents. In summary, there is room for additional study on the efficacy of functional carbon adsorbents for the removal of heavy metals and their potential uses in various fields. This includes the development of new materials and techniques to enhance adsorption efficiency and selectivity for specific heavy metals, along with the investigation of additional functionalities for these carbon adsorbents in various industrial processes. There is a need for continued innovation and collaboration in this field to address the growing concerns regarding heavy metal pollution and to explore the full capabilities of functional carbon adsorbents.

An efficient tool for real-time global carbon neutrality with credibility of delicacy management: A Modelx + MRV + O system

Current carbon neutralization systems are time-consuming, which generally require at least one to two months. We propose a highly efficient real-time carbon neutralization mechanism, a Modelx+MRV + O system based on the Internet of Things and blockchain technology for all the carbon reduction scenarios. This mechanism includes an accounting model for a certain distributed carbon reduction scenario, and real-time M, RV, and O systems, enabling enterprises, products, or individuals to reliably reach carbon neutrality in real time. We demonstrated how to build a real-time model (Modelx) by proposing a carbon emission reduction methodology for the returnable packaging scenario and a photovoltaic power generation scenario combining IoT technology for a traditional methodology for polar electricity. We found that the proposed system can achieve real-time analysis based on the monitored turnover number and electricity generated and avoid falsified values. Because carbon neutrality is essential to reduce carbon emissions and combat climate change globally, this system can accelerate the sustainable transformation by managing carbon neutrality globally.

Regional differences of agricultural total factor carbon efficiency in China

China’s agriculture has struggled over the past century to produce more food to feed the country’s expanding population while also contending with high-intensity pollution. In order to support China’s transition to low-carbon agriculture more efficiently, it is important to improve the efficiency of agricultural carbon emissions. This study employs the biennial weight modified Russell model to investigate China’s agricultural total factor carbon efficiency (ATFCE) during 1999–2018 and its differences between the three agricultural functional zones (AFZs), including the grain-producing zone (GPZ), the grain balance zone (GBZ), and the main grain-selling zone (GSZ). The study found that the ATFCE in China was 0.761, a high value. GSZ (0.9865) had the highest ATFCE, followed by GBZ (0.7201) and GPZ (0.6666). ATFCE in China fell by approximately 25%, from 0.825 in 1999 to 0.6983 in 2018. Further, the provinces with the highest ATFCE included Tibet (0.9997), Hainan (0.9981), Shanghai (0.997), Beijing (0.9937), and Jiangsu (0.9924). Provinces with the lowest ATFCEs included Hubei (0.4743), Yunnan (0.4645), Hunan (0.441), Anhui (0.4295), Heilongjiang (0.4130), and Jiangxi (0.3354). In addition, the difference in ATFCE within the whole of China, GPZ, and GBZ generally widened during 1999–2018. There was a rise in all three inequalities between the three AFZs. The difference between GPZ and GBZ was the greatest among the three interregional differences. Finally, the difference between subregions was the largest source of the total difference (43.66%), followed by the difference within subregions (30.04%) and the intensity of transvariation (25.94%).

Utilization of shea butter waste-derived hierarchical activated carbon for high-performance supercapacitor applications

In this work, carbonization and subsequent activation procedures were adopted to synthesize waste shea butter shells into oxygen-rich interconnected porous activated carbon (SAC_x, x is the mass ratio of KOH used for activation). The SAC_1.5 electrode material showed outstanding electrochemical performance with high specific capacitance (286.6 F/g) and improved rate capability, owing to various synergistic effects originating from a high specific surface area (1233.5 m2/g) and O-rich content. The SAC_1.5-based symmetric device delivered an impressive specific capacitance of 91.6 F/g with a high energy density of 12.7 Wh/kg at 0.5 A/g. The device recorded 99.9 % capacitance retention after 10,000 charge-discharge cycles. The symmetric supercapacitor device successfully lit an LED bulb for more than 1 h, signifying the potential of bio-waste as an efficient carbon precursor for electrode material in practical supercapacitors. This work offers an efficient, affordable, and environmentally friendly strategy for potential renewable energy storage devices.

Renewable methanol production based on in situ synergistic utilization of excavated waste and landfill gas: life cycle techno-environmental-economic analysis

Excavated waste (EW) and landfill gas (LFG), as the two main landfill products, are essential objects of Enhanced landfill mining (ELFM). In this study, for the in situ synergistic utilization of LFG and the residue-derived fuel (RDF) from EW, an RDF-LFG to methanol (MeOH) unit with high exergy efficiency and low carbon emission is proposed. Then, to evaluate the environmental impacts and economic feasibility comprehensively, the life cycle assessment (LCA) and life cycle cost (LCC) are conducted on the EW-LFG to MeOH system based on the Aspen Plus simulation data of the RDF-LFG to MeOH unit. The system using EW landfilled in 2005 & 2015 as feedstocks are named Scheme A & B, respectively. The results show that both schemes have an exergy efficiency of more than 70 %. Regarding environmental impacts, RDF-LFG to MeOH, EW pretreatment, Storage and transport of products, and EW Mining are the main contributors. This study pays particular attention to global warming (GW) potential. The direct and indirect carbon emission of the RDF-LFG to MeOH unit are about 35 and 650 kg CO2 eq/ton MeOH, and the life-cycle GW of the EW-LFG to MeOH system is between 707 to 874 kg CO2 eq/ton MeOH. Levelized cost (LC) and levelized profit (LP) are about 452 $/ ton MeOH and 94 $/ton MeOH. With the transformation of the power grid, the decrease in carbon emission factor of power grids can improve both the environmental, and economic performance of the EW-LFG to MeOH system. Methanol selling price, carbon tax and electricity cost are the major sensible factors to the economic feasibility.

Hydrothermal Carbonization Technology for Wastewater Treatment under the “Dual Carbon” Goals: Current Status, Trends, and Challenges

Hydrothermal carbonization (HTC) technology transforms organic biomass components, such as cellulose and lignin, into valuable carbon materials, gases and inorganic salts through hydrolysis, degradation and polymerization, with significant advantages over traditional methods by reducing energy consumption, lowering pollutant emissions and enhancing carbonization efficiency. In the context of global climate change, HTC plays a critical role in water environment management by addressing industrial, agricultural, and domestic wastewater challenges. The application of HTC extends to wastewater treatment, where hydrochar effectively adsorbs heavy metals, organic compounds, and anions, thereby improving water quality. However, challenges remain, such as optimizing the process for diverse raw materials, managing economic costs, and addressing environmental and social impacts. Future research and policy support are essential for advancing HTC technology. By enhancing reaction mechanisms, developing catalysts, and promoting international cooperation, HTC can significantly contribute towards achieving carbon neutrality goals and fostering sustainable development.

Machine learning prediction and optimization of CO2 foam performance for enhanced oil recovery and carbon sequestration: Effect of surfactant type and operating conditions

Foam flooding handles the challenges of gas injection constituting a high viscosity medium that sweeps oil more efficiently meanwhile creating a barrier that prevents leakage of gas phase. Therefore, it is a promising enhanced oil recovery (EOR) method, simultaneously an efficient carbon dioxide (CO2) storage technology. The foam's performance displays susceptibility to various reservoir and operational parameters. Numerous laboratory experiments would need to be carried out to study foams and find the optimum foam formulation for the given core conditions. Data-driven approaches can be an alternative method to the time-consuming experimental and conventional modeling techniques, which often face challenges to incorporate the effect of important related parameters such as temperature and type of surfactant to the performance of foam. In the current study, machine learning (ML) models were constructed to predict the CO2 foam apparent viscosity in carbonate and sandstone formations focusing on experimental data from the literature for CO2 foams stabilized by different surfactants. Various anionic, cationic, and nonionic surfactants were considered and characterized based on the hydrophilic-lipophilic balance (HLB) number. Predictive models were developed using ML algorithms based on the data available for eight key process parameters. Artificial neural networks and extra randomized tree algorithms provided the most precise prediction among the applied algorithms. Various predictions for foam apparent viscosity on hypothetical case studies were made on altered input parameters, enabling CO2 mobility to co-optimize EOR and CO2 sequestration while selecting the optimum surfactant for each case.

Novel spherical InVO4/floral Bi2MoO6 Z-scheme heterojunction for efficient photocatalytic carbon dioxide reduction

The development of efficient CO2 reduction photocatalysts is of great significance to improving the global greenhouse effect and alleviating the energy crisis. In this paper, spherical InVO4/floral Bi2MoO6 (IVO/BMO) Z-scheme heterojunction was prepared by a hydrothermal method, and the surface structure, chemical composition, and photovoltaic properties of the samples were characterized and tested for their CO2 reduction performance. The experimental results show that 1.5 %-IVO/BMO exhibits excellent photocatalytic activity for CO2 reduction under the irradiation of 300 W Xenon lamp, with a CO yield of 34.08 µmol/g/h and a CH4 yield of 4.49 µmol/g/h, which are 2.55 and 1.05 times higher than that of the pure Bi2MoO6, respectively. The enhanced photocatalytic activity can be attributed to the formation of an IVO/BMO Z-scheme heterojunction, which promotes electron separation and reduces charge recombination at the interface, facilitating the reaction process. This study provides a novel Z-scheme photocatalyst for efficient carbon dioxide reduction.

Impact of Vertex Functionalization on Flexibility of Porous Organic Cages.

Efficient carbon capture requires engineered porous systems that selectively capture CO2 and have low energy regeneration pathways. Porous liquids (PLs), solvent-based systems containing permanent porosity through the incorporation of a porous host, increase the CO2 adsorption capacity. A proposed mechanism of PL regeneration is the application of isostatic pressure in which the dissolved nanoporous host is compressed to alter the stability of gases in the internal pore. This regeneration mechanism relies on the flexibility of the porous host, which can be evaluated through molecular simulations. Here, the flexibility of porous organic cages (POCs) as representative porous hosts was evaluated, during which pore windows decreased by 10-40% at 6 GPa. POCs with sterically smaller functional groups, such as the 1,2-ethane in the CC1 POC resulted in greater imine cage flexibility relative to those with sterically larger functional groups, such as the cyclohexane in the CC3 POC that protected the imine cage from the application of pressure. Structural changes in the POC also caused CO2 adsorption to be thermodynamically unfavorable beginning at ∼2.2 GPa in the CC1 POC, ∼1.1 GPa in the CC3 POC, and ∼1.0 GPa in the CC13 POC, indicating that the CO2 would be expelled from the POC at or above these pressures. Energy barriers for CO2 desorption from inside the POC varied based on the geometry of the pore window and all the POCs had at least one pore window with a sufficiently low energy barrier to allow for CO2 desorption under ambient temperatures. The results identified that flexibility of the CC1, CC3, or CC13 POCs under compression can result in the expulsion of captured gas molecules.

An adaptive control system based on spatial–temporal graph convolutional and disentangled baseline-volatility prediction of bellows temperature for iron ore sintering process

The temperature within the sintering furnace is a decisive factor influencing the quality of the sintered ore in the iron ore sintering process. In practical operations, the temperature at the bellows directly linked to the bed layer indirectly signifies the internal furnace temperature. Maintaining a stable temperature at the bellows, particularly at the burn-through point, is vital for minimizing gas emissions, improving carbon efficiency, and enhancing the quality of the sintered ore. This paper proposes an intelligent temperature control system based on Spatial–Temporal Graph Convolutional and Disentangled Baseline-Volatility (STGCDBV) prediction. The STGCDBV network comprises three parallel modules: Adaptive Graph Convolution Network (AGCN), Baseline and Volatility Disentangler (BVD), and a residual link, along with a Temporal–Nodal Encoder–Decoder (TNED) module. The AGCN constructs a graph reflecting the characteristics of bellows temperature, effectively merging static spatial data with dynamic thermal information. The BVD module captures the nonlinear trend data inherent in the sintering process. In contrast, the TNED synergizes the insights from the parallel modules using cross encoding and decoding functionalities. For controlling the sintering gas flow rate, a Model Reference Adaptive Control (MRAC) system is implemented, which utilizes a control scheme founded on a temperature reference model and iterative parameter adjustments. Extensive experiments using actual time-series data from a steel plant have been conducted. Moreover, comparisons between the performance of pre- and post-control interventions demonstrate that the STGCDBV-MRAC system can stabilize temperature fluctuations and exhibit exemplary control proficiency.

Controlling the coverage of intermediates on the active site enables efficient carbon dioxide electroreduction to hydrocarbons

The electrochemical CO2 reduction reaction (ECO2RR) has the capability to convert CO2 molecules into high-value products, offering a feasible pathway aligned with carbon cycling and emission reduction. Nevertheless, significant efforts are required to achieve highly active and selective catalysts tailored for specific products. Herein, a facile synthesis route is proposed, wherein copper, phosphorus, and carbon precursors are mixed and subsequently calcined at different temperatures to obtain a series of copper-based catalysts (CPC-300, 500, 700) containing various copper components with different phases and oxidation states. And further performance tests show their differentiated product distributions. Specifically, CPC-300, which contains more high-valence Cu, is more inclined to produce C2 products, while CPC-700 possessing low-valence Cu as its phase is more keen to produce C1 products. In particular, the CPC-700 catalyst presents a high FECH4 of 52.2 % with a CH4 partial current density of −167.8 mA cm−2 at −1.447 V vs. RHE. Combining the results of in-situ Raman and electrochemical characterizations confirms the effect of valence state and composition on the adsorbed intermediates containing *CO and *H during the reaction. This work achieves the design and development of highly selective and active Cu-based catalysts from the strategies of valence state and component engineering.

Effects of temperature and CO2 concentration on the early stage nucleation of calcium carbonate by reactive molecular dynamics simulations.

It is significant to investigate the calcium carbonate (CaCO3) precipitation mechanism during the carbon capture process; nevertheless, CaCO3 precipitation is not clearly understood yet. Understanding the carbonation mechanism at the atomic level can contribute to the mineralization capture and utilization of carbon dioxide, as well as the development of new cementitious materials with high-performance. There are many factors, such as temperature and CO2 concentration, that can influence the carbonation reaction. In order to achieve better carbonation efficiency, the reaction conditions of carbonation should be fully verified. Therefore, based on molecular dynamics simulations, this paper investigates the atomic-scale mechanism of carbonation. We investigate the effect of carbonation factors, including temperature and concentration, on the kinetics of carbonation (polymerization rate and activation energy), the early nucleation of calcium carbonate, etc. Then, we analyze the local stresses of atoms to reveal the driving force of early stage carbonate nucleation and the reasons for the evolution of polymerization rate and activation energy. Results show that the higher the calcium concentration or temperature, the higher the polymerization rate of calcium carbonate. In addition, the activation energies of the carbonation reaction increase with the decrease in calcium concentrations.

Decomposing Carbon Intensity Trends in China’s Civil Aviation: A Comprehensive Analysis from 1998 to 2019

Carbon emission intensity is an important index reflecting an entity’s low-carbon competitiveness. This paper presents an extended logarithmic mean divisia index (LMDI) model to dissect carbon intensity within China’s civil aviation from 1998 to 2019, revealing a significant reduction in CO2 emissions per air transport revenue. It attributes this decrease to technological advancements, optimized fleet structures, and improved operational efficiencies, highlighting the impact of larger, more efficient aircraft and enhanced load factors. The study also explores economic factors influencing carbon efficiency, suggesting a comprehensive approach encompassing technological innovation and strategic operational improvements for sustainable aviation development.

The Significance of Agricultural Modernization Development for Agricultural Carbon Emission Efficiency in China

Agricultural production contributes to the increase in global carbon emissions. It is crucial to improve output and reduce carbon emissions in the context of agricultural modernization, for which improved carbon emission efficiency is key. However, the role of agricultural modernization in promoting agricultural carbon emission efficiency is not clear. Hence, the aim of this article is to analyze the spatiotemporal evolution of agricultural modernization and agricultural carbon emission efficiency in China from 2000 to 2019 and to reveal the relationship between agricultural modernization and agricultural carbon emission efficiency. The results showed that (1) in China, the overall level of agricultural modernization has been steadily increasing, and the regional differences are widening, showing a spatial pattern characterized by a gradual decline from the eastern and central regions to the western region. (2) China’s agricultural carbon emission efficiency continues to grow but has not achieved a data envelopment analysis (DEA) effect, with the eastern and western regions having higher agricultural carbon efficiency than the central region. The regional differences first narrow and then expand. (3) Agricultural modernization significantly promotes agricultural carbon emission efficiency in both the province and the neighboring provinces, and the interprovincial spillover effect exceeds the direct effect within the province. A nonlinear correlation exists between agricultural modernization and agricultural carbon emission efficiency.