Carbonization Temperature Research Articles

Performance of activated carbon derived from tea twigs for carbon dioxide adsorption

Activated carbon from agro-industrial waste, namely tea twigs derived from the processing of Camellia Sinensis branches, using a potassium hydroxide activator for CO2 adsorption has been conducted in this study. Various carbonization temperatures (4000C and 5000C) and heating times of 1 hour and 3 hours were used in this study. The concentration of potassium hydroxide (40% and 60%) and the ratios of activator solutions to carbon precursor made from pyrolysis of tea twigs (2:1 and 4:1) were varied for the chemical activation process. The effectiveness results of the obtained activated carbon were characterized through using Brunauer-Emmett-Teller analyzer and Temperature Programme Desorption-CO2 to determine the surface area and capacity maximum of CO2 adsorption. The optimum condition for the synthesis of activated carbon that produces high surface area was obtained at sample CCS 400/1 A2B1 where biochar carbonized at temperature of 400°C kept for 1 hour with a ratio of activator solution and precursor 4:1 using KOH concentration of 40%. The highest surface area was obtained 1,403 m2 g-1 with pore volume 0.9 m2 g-1 and pore size 1.11 nm and proved the presence of microporous areas in produced activated carbon. The maximum CO2 adsorption capacity obtained in this study was 5.1573 mmol g-1. This result could be related to the higher amount of microporous present in the activated carbon that facilitates the access of CO2 to the active sites at the pores of activated carbon.

Turning municipal food organic waste into activated carbon: A step towards circular economy

Finding a suitable way of managing the growing problem of municipal organic waste is a pressing issue worldwide. Unsorted municipal food waste (FW) was utilized for the first time as an activated carbon (AC) precursor. Varying pyrolysis conditions such as generation steps and carbonization temperature appeared to have a minor impact on AC characteristics compared to higher activation temperature, particularly 800 °C as indicated by a series of physicochemical characterizations. Selected FW-derived ACs were tested as an adsorbent under different experimental conditions to explore their efficacy in removing methylene blue (MB) from water. The adsorption of MB on FW-derived AC occurred in multilayers on heterogenous surfaces whereas the adsorption of MB on commercial AC occurred on a homogenous surface in a monolayer fashion which can be explained by chemisorption. The maximum MB adsorption by FW-derived AC was 47.72 mg/g under the conditions tested, although results indicated that the adsorption capacity had not been reached. Importantly, the kinetics of MB adsorption onto FW-derived AC was substantially faster than adsorption onto commercial AC. The findings of this study suggest that AC prepared from a diverse mixture of municipal FW is a promising, novel, and cost-effective adsorbent to eliminate MB.

Bamboo waste derived hard carbon as high performance anode for sodium-ion batteries

Biomass-derived hard carbon stands out as one of the most promising anode materials for advancing the commercial viability of sodium-ion batteries (SIBs). In this study, we harnessed a straightforward and eco-friendly two-step carbonization approach to fabricate high-performance hard carbon materials, ingeniously repurposing industrial bamboo waste. Concurrently, we delved into the impact of carbonization temperature on the microstructure and properties of the hard carbon derived from bamboo waste. The findings revealed that the as-prepared hard carbon at 1400 °C (HCB-1400) showcased the most desirable sodium-ion storage capabilities. The HCB-1400 material not only can deliver a substantial reversible capacity of 328.4 mAh g−1 at 30 mA g−1 in its maiden charge-discharge cycle but also display remarkable cycling stability. Moreover, the HCB-1400//Na3V2(PO4)3 full cell, when assembled, exhibited an impressive energy density of 249.25 Wh kg−1, with a capacity retention rate of 93 % after enduring 200 cycles at a current density of 1.0 C. This research underscores the potential of transforming biomass waste into high-performance hard carbon, heralding a sustainable path for SIB applications.

Computational molecular dynamic analysis of the interfacial characteristics of carbon nanotube/epoxy nanocomposites

The mechanical properties of nanocomposites depend on the interfacial characteristics between the reinforcements and the matrix, but these interfacial behaviours and the associated molecular structures need more understanding. This study investigates the impact of diameter and chirality of carbon nanotube (CNT) and temperature on the interfacial interaction, bonding, and pullout energy, as well as the shear strength between CNT and epoxy, using molecular dynamics (MD) and molecular mechanics (MM). The modelling technique utilised a reactive force field (ReaxFF) and a new high-throughput approach to pullout energy calculations that provide an understanding of the interfacial behaviours of CNT/epoxy composites. The analyses showed that these interfacial energies and the shear strength increase with temperature. In addition, the smaller the diameter of CNT, which is a function of chirality, the greater is the interfacial bonding and shear strength. While interfacial interaction and pullout energy increase with CNT diameter.

Properties evolutions during carbonization of carbon foam using lignin as sole precursor

Lignin has been proved to be a promising precursor for producing carbon foam. The thermal and chemistry properties of lignin during its thermal conversion make it quite unique comparing with other precursors, and the conversion parameters can clearly affect the properties of the derived products. Therefore, this study systematically investigated the effects of key carbonization parameters on the properties of the resulting carbon foam materials. The findings demonstrate that the performance of the self-shaping lignin-derived carbon foam is simultaneously influenced by the factors that carbonization temperature, heating rate, and carbonization duration. Specifically, the carbonization temperature and carbonization duration have a significant impact on the mechanical performance, where higher temperatures and long carbonization time improve compressive strength and specific strength. Moreover, the data revealed that elevated temperatures, rapid heating rates, and shortened carbonization periods collectively promoted the development of higher porosities and larger pore diameters within the carbon foam structure. Conversely, lower carbonization temperatures, slower heating rates, and extended carbonization durations facilitated the formation of microporous in the carbon foam. This study provides a scientific foundation for optimizing the production of lignin-derived carbon foam with tailored properties and performance characteristics.

Preparation of high performance microwave absorbing materials based on waste peanut shells

Abstract The emergence of advanced wave-absorbing materials has led to a growing interest in biomass-derived porous carbon due to its abundant availability, low density, and eco-friendly nature. This study utilized peanut shell biomass waste to produce porous carbon material (KPS) through a two-step carbonation-activation process. We investigated the influence of varying ratios of carbonized peanut shells (CPS) to potassium hydroxide (KOH) activator on the pore structure and morphology of KPS. The comprehensive analysis of the electromagnetic parameters revealed that KPS sample achieved a remarkable reflection loss of −42.38 dB and an effective bandwidth of 2.58 GHz with the thickness of 2.5 mm when the quality ratio of CPS to activator KOH was 1:3 and the carbonation temperature was 600 °C. Notably, the KPS material demonstrated substantial specific surface area of 1037.589 m2 g−1 and complex pore architecture, facilitating the development of conductive network and promoting multiple reflections of electromagnetic waves. This research highlighted the potential of efficiently utilizing recyclable resources to create microwave-absorbing materials that are not only simple to produce but also environmentally sustainable.

Heterogeneous Carbon Designed with Disorder-in-Ordered Nanostructure toward High-Rate and Ultra-stable Sodium Ion Storage.

The rate performance of biomass-based hard carbon has always been one of the obstacles to its large-scale use. There are various challenges in improving the rapid conduction of sodium ions at the interface and realizing the efficient utilization of inactive carbon in large current. In this study, a disorder-in-ordered nanostructure carbon front-face coated with hard carbon which forms a heterogeneous carbon is prepared by coulomb adsorption of methylene blue and alkalized kapok fiber. A study on heterogeneous hard carbon material formation is proposed by incorporating heteroatoms at different carbonization temperatures. When the current density increases to 10 A g-1, the obtained carbon material shows stable cycling for 5000 cycles with only a decay rate of 0.056 ‰, which is significantly better than conventional biomass-based hard carbon materials. This work provides insights of synergistic effect into the achievement of superior rate capability, that is the internal heteroatoms facilitates the activation of deep sodium energy storage, while the external well-ordered interface enhances the transport of sodium ions. The evolution of heterogeneous structure is analyzed, offering a novel perspective on the utilization of alkalized kapok for wastewater recovery and energy storage applications.

CO2 selectivity and adsorption performance of K2CO3-modified zeolite: a temperature-dependent study.

High-performing zeolite materials for carbon dioxide capture are promising for applications such as flue gas CO2 capture. Potassium carbonate-loaded zeolites can offer a plethora of benefits. In this work, for the first time, zeolite-Y impregnated with K2CO3 was studied as a gas adsorbent (CO2, CH4, and N2) and characterized using TGA (thermogravimetric analyzer), XRD, BET, FTIR, FETEM (Field-Emission Transmission Electron Microscope), and XPS. The effect of carbonate loading, temperature, and pressure was particularly targeted and assessed. Accordingly, for a variation in K2CO3 loading from 5 to 15 wt.%, the CO2 adsorption capacity reduced from 3.61 to 1.73mmolg-1 in the synthesized adsorbents. Among all the cases, KYZC10 exhibited very good cyclic adsorption-desorption performance and thermal stability. Further equilibrium modeling studies indicate that the stable and optimally K2CO3-loaded adsorbent (KYZC10) demonstrates effective adsorption isotherm behavior, making it suitable for different temperature variation processes in commercial carbon dioxide capture applications. The KYZC10 adsorbent's stable performance at varying temperatures contributes to its enhanced economic feasibility. This study also used the ideal adsorbed solution theory (IAST) to predict CO2 selectivity over other gases (CH4 and N2).

Effect of organic/inorganic separation on the adsorption performance of sludge-based activated carbon

Large amounts of organic matter of sewage sludge are enriched into the organic sludge (OS) by sludge organic/inorganic separation technology of acidification combined with multistage elution, which gives the OS the potential for preparing activated carbon. Hereinto, OS-based activated carbon (OAC) and raw sludge (RS)-based activated carbon (RAC) were prepared from OS and RS as raw materials at different carbonization temperatures and holding times. The results showed that compared with RS, the organic matter in OS increases by above 30 % including volatiles and fixed carbon. The optimal preparation conditions for RAC and OAC are to maintain a carbonization temperature of 800 ℃ for 1.5 h and 2 h, respectively. Under this condition, the specific surface area of OAC (296.8 m2/g) is higher than that of RAC (246.6 m2/g), and OAC has a richer mesoporous structure and a new functional group of N-H appears on the surface. Moreover, the batch experiments results show that compared with RAC, the adsorption capacity of Pb2+ by OAC increased from 3.12 to 4.92 mg/g and that of Cd2+ from 2.79 to 2.98 mg/g. Besides, the adsorption mechanism of OAC and RAC is the same, which is consistent with the Langmuir model and the pseudo-first-order kinetic type.

Carbon dioxide exchange and temperature sensitivity of soil respiration along an elevation gradient in an arctic tundra ecosystem

Generally, with increasing elevation, there is a corresponding decrease in annual mean air and soil temperatures, resulting in an overall decrease in ecosystem carbon dioxide (CO2) exchange. However, there is a lack of knowledge on the variations in CO2 exchange along elevation gradients in tundra ecosystems. Aiming to quantify CO2 exchange along elevation gradients in tundra ecosystems, we measured ecosystem CO2 exchange in the peak growing season along an elevation gradient (9–387 m above sea level, m.a.s.l) in an arctic heath tundra, West Greenland. We also performed an ex-situ incubation experiment based on soil samples collected along the elevation gradient, to assess the sensitivity of soil respiration to changes in temperature and soil moisture. There was no apparent temperature gradient along the elevation gradient, with the lowest air and soil temperatures at the second lowest elevation site (83 m). The lowest elevation site exhibited the highest net ecosystem exchange (NEE), ecosystem respiration (ER) and gross ecosystem production (GEP) rates, while the other three sites generally showed intercomparable CO2 exchange rates. Topography aspect-induced soil microclimate differences rather than the elevation were the primary drivers for the soil nutrient status and ecosystem CO2 exchange. The temperature sensitivity of soil respiration above 0 °C increased with elevation, while elevation did not regulate the temperature sensitivity below 0 °C or the moisture sensitivity. Soil total nitrogen, carbon, and ammonium contents were the controls of temperature sensitivity below 0 °C. Overall, our results emphasize the significance of considering elevation and microclimate when predicting the response of CO2 balance to climate change or upscaling to regional scales, particularly during the growing season. However, outside the growing season, other factors such as soil nutrient dynamics, play a more influential role in driving ecosystem CO2 fluxes. To accurately upscale or predict annual CO2 fluxes in arctic tundra regions, it is crucial to incorporate elevation-specific microclimate conditions into ecosystem models.

Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.

Prediction Model for the Chloride Ion Permeability Resistance of Recycled Aggregate Concrete Based on Machine Learning

The chloride ion permeability resistance of recycled aggregate concrete (RAC) is influenced by multiple factors, and the prediction model for this resistance based on machine learning is still limited. In the paper, six impact factors (IFs), including the carbonation of recycled coarse aggregates (YN), the replacement ratio of recycled coarse aggregates (r), the bending load level (L), the carbonation time (t) and temperature (T) of RAC, and the replacement ratio of carbonated recycled fine aggregates (f), were considered to conduct a chloride penetration test on RAC. Based on the experimental data, four algorithms, including artificial neural network (ANN), support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost), were adopted to establish the machine learning prediction models and study the relationships between the electric flux of RAC and the IFs. The results showed that the predicted values of all four models were in good agreement with the experimental values, and the XGBoost model had the best prediction performance on the testing set. Based on the XGBoost model, the LIME method was adopted to solve the interpretability problem in the prediction process. The importance ranking of IFs on the electric flux was r > t > f > T > L > YN. A graphical user interface (GUI) was developed based on Python 3.8 software to facilitate the use of machine learning models for the chloride ion permeability resistance of RAC. The research results can provide an accurate prediction of the electric flux of RAC.

An assessment of live hard coral cover distribution and its physicochemical factors in the Strait of Malacca from 1995 to 2016

The Strait of Malacca is well-known as an important trade route with high marine biodiversity. Among the organisms residing in the strait are the reef-building hard corals. Studies have shown that climate change and other anthropogenic stressors have induced severe degradation of coral reefs through the disruption of coral productivity and metabolisms. Moreover, in-depth investigations of causal inference of coral degradation and its correlations with potential coral-affecting physicochemical factors within the strait are limited. Hence, this study presents the analyses of the latest bi-decadal time-series trend from 1995 to 2016 of the live hard coral coverage (or live coral cover) and six coral-affecting physicochemical factors (significant wave height, sea surface salinity, particulate inorganic carbon, particulate organic carbon, turbidity, and sea surface temperature) using remote sensing and reanalysis datasets. Their potential correlations were interpreted by implementing meta- and statistical analyses of past coral surveys and remote sensing data. This study revealed the overall persistent bi-decadal decline in live hard coral coverage within the Strait of Malacca and the complex correlations among the factors that correspond to the spatial stratification of the marine environment. Among the six physicochemical factors, sea surface temperature, turbidity, and sea surface salinity were determined to be the most influential parameters on live coral cover distribution within the strait.

Optimization of the Carbonization Process for the Preparation of High-Grade Needle Coke Based on the Response Surface Method and Microstructure Analysis.

Refined coal tar pitch (RCTP) with a quinoline insoluble (QI) content less than 0.01% was obtained from Wuhai coal tar pitch (CTP), which was used as a raw material to prepare needle coke by carbonization and calcination experiments. In this work, the effects of carbonization time, carbonization temperature, and carbonization pressure on the optical structure of green coke and the microstructure of needle coke were investigated. Meanwhile, the microstructure changes of products were characterized by polarizing microscopy, XRD analysis, Raman analysis, and SEM. The reliable transfer functions between the green coke mesophase content and the investigated factors, as well as the graphitization degree of needle coke, were established based on the response surface analysis method. Furthermore, we provide an operable window for carbonization temperature, time, and pressure, guaranteeing that the content of the green coke mesophase is greater than 90% and the graphitization degree of needle coke is greater than 80%. It can be found that the carbonization temperature has the most significant effect on the mesophase content and graphitization degree of coke. Prolongation of carbonization time is helpful for mesophase molecules to fully grow up, and the directional arrangement, which results in the structure of the coke, is regular. The appropriate carbonization pressure not only ensures that the carbonization reaction system has a certain viscosity but also provides hydrogen free radicals, which is conducive to the formation of drainage optical structure.

An automated AI-powered IoT algorithm with data processing and noise elimination for plant monitoring and actuating

This article aims to develop a novel Artificial Intelligence-powered Internet of Things (AI-powered IoT) system that can automatically monitor the conditions of the plant (crop) and apply the necessary action without human interaction. The system can remotely send a report on the plant conditions to the farmers through IoT, enabling them for tracking the healthiness of plants. Chili plant has been selected to test the proposed AI-powered IoT monitoring and actuating system as it is so sensitive to the soil moisture, weather changes and can be attacked by several types of diseases. The structure of the proposed system is passed through five main stages, namely, AI-powered IoT system design, prototype fabrication, signal and image processing, noise elimination and proposed system testing. The prototype for monitoring is equipped with multiple sensors, namely, soil moisture, carbon dioxide (CO2) detector, temperature, and camera sensors, which are utilized to continuously monitor the conditions of the plant. Several signal and image processing operations have been applied on the acquired sensors data to prepare them for further post-processing stage. In the post processing step, a new AI based noise elimination algorithm has been introduced to eliminate the noise in the images and take the right actions which are performed using actuators such as pumps, fans to make the necessary actions. The experimental results show that the prototype is functioning well with the proposed AI-powered IoT algorithm, where the water pump, exhausted fan and pesticide pump are actuated when the sensors detect a low moisture level, high CO2 concentration level, and video processing-based pests’ detection, respectively. The results also show that the algorithm is capable to detect the pests on the leaves with 75% successful rate.

Phytolith-Mediated Biocarbon Sequestration

The sequestration of biocarbon primarily arises from natural mechanisms and is acknowledged as a critical measure in mitigating climate change. An inactive form of carbon, known as phytolith occluded carbon, is sequestered within plants and persists in soil for thousands of years following the breakdown of vegetation. Formation, distribution and storage of phytolith occluded carbon are the major factors affecting phytolith-mediated biocarbon sequestration. Crop area, crop duration, aboveground net primary productivity, crop, plant species, plant parts, age of plant, age of plant parts, cell components, phytolith morphotypes, and mean annual precipitation are some of the factors affecting the formation of phytolith occluded carbon. The stability and dissolution of phytolith occluded carbon in the soil are determined by carbon dioxide, temperature, climate zone, topography, soil, and phytolith properties characteristics. The phytolith distribution in the soil is affected by soil type and depth, tillage, bioturbulence, percolation, and phytolith morphotypes. By adopting proper soil and crop management practices phytolith mediated biocarbon sequestration can be enhanced.

Soft sensor model for endpoint carbon content and temperature in BOF steelmaking based on just-in-time learning with multilayer structure preservation and sparse information enhancement

Ensuring precise prediction of the endpoint carbon content and temperature is paramount in controlling the endpoint of the basic oxygen furnace (BOF) steelmaking process. However, due to the frequent fluctuations in real-time blowing conditions, the conventional just-in-time learning soft sensor approach encounters challenges in effectively anticipating the blowing endpoint. To address these aforementioned issues, this research introduces a novel approach known as the pattern-oriented multilayer structure preservation and sparse information enhancement model (POMLSP-SIE). This approach involves dynamically generating a dataset with the same distribution based on the characteristics of the query sample pattern. It is combined with a multi-pathway dimension reduction model to preserve multi-view spatial geometry information while reducing data dimension. The low-dimensional embedding serves as dictionaries containing various hierarchical structural characteristics. Significant information within these dictionaries is sparsely represented to amplify its influence during the regression prediction process while diminishing the impact of less relevant information. This refinement aims to rectify the problem of static regression models being weak to adapt to changing working conditions, ultimately enhancing prediction performance. The effectiveness of the proposed method is substantiated through an experimental study utilising real converter steelmaking process data, thereby confirming its practical applicability.

Optimization of Magnetic Biochar Preparation Process, Based on Methylene Blue Adsorption.

The search for low-cost and effective adsorbents for the removal of organic dyes from contaminated water is urgently needed. The substantial amount of waste mushroom cultivation substrates generated in practical production can serve as an ideal material for the preparation of adsorbents. In this study, we investigated the main control parameters affecting the performance of magnetic mushroom substrate biochar and optimized the process of preparing biochar by using the Plackett-Burman and central composite design methods. Various analytical techniques including SEM, EDX, BET, and VSM were used to characterize the biochar. The results indicate that the carbonization temperature had the most significant impact on the yield and adsorption performance of biochar. Under the conditions of a carbonization temperature of 600 °C, a carbonization retention time of 1 h, and an impregnation ratio of 0.1, the yield and methylene blue adsorption value of magnetic biochar were 42.54% and 2297.04 μg/g, respectively, with a specific surface area of 37.17 m2/g. This biochar effectively removed methylene blue from the solution, demonstrating a high economic efficiency for wastewater treatment and pollution control. Furthermore, the adsorption-desorption cycle studies revealed its excellent stability and reusability. Additionally, based on the response surface methodology, a three-dimensional surface model of the adsorption performance of magnetic biochar under different carbonization conditions was established, providing a theoretical basis for the preparation of magnetic biochar from agricultural wastes.

Biofilm Formation in Clinical Isolates of Fusarium.

Many microbial pathogens form biofilms, assemblages of polymeric compounds that play a crucial role in establishing infections. The biofilms of Fusarium species also contribute to high antifungal resistance. Using our collection of 29 clinical Fusarium isolates, we focused on characterizing differences in thermotolerance, anaerobic growth, and biofilm formation across four Fusarium species complexes commonly found in clinical settings. We investigated the role of carbon sources, temperature, and fungal morphology on biofilm development. Using fluorescence microscopy, we followed the stages of biofilm formation. Biofilms were screened for sensitivity/resistance to the antifungals voriconazole (VOR), amphotericin B (AmB), and 5-fluorocytosine (5-FC). Our findings revealed generally poor thermotolerance and growth under anaerobic conditions across all Fusarium species. VOR was more effective than AmB in controlling biofilm formation, but the combination of VOR, AmB, and 5-FC significantly reduced biofilm formation across all species. Additionally, Fusarium biofilm formation varied under non-glucose carbon sources, highlighting the species' adaptability to different nutrient environments. Notably, early stage biofilms were primarily composed of lipids, while polysaccharides became dominant in late-stage biofilms, suggesting a dynamic shift in biofilm composition over time.

Effects of Cow-Dung Vermicomposting on Soil Carbon Mineralization and Temperature Sensitivity in Camellia oleifera Forest

Soil carbon mineralization plays an important role in the carbon cycle of terrestrial ecosystems. When it comes to the soil carbon cycle, however, research on how carbon mineralization characteristics of fertilized Camellia oleifera forest soil respond to temperature changes remains limited. This study used an indoor constant temperature incubation method to examine the effects of the vermicomposting of cow dung by applying it at three different quantities (A: 0.8 kg earthworm + 62.5 kg cow dung/Camellia oleifera; B: 1.6 kg earthworm + 125 kg cow dung/Camellia oleifera; C: 2.4 kg earthworm + 187.5 kg cow dung/Camellia oleifera) and set a control group with Camellia oleifera forest not being fertilized (CK). This research was conducted with incubators set at 5 °C, 15 °C, 25 °C, and 35 °C, and with continuous monitoring of soil carbon mineralization characteristics and temperature sensitivity of organic carbon mineralization. The results showed significant increases in soil MBC, MBN, DOC, DON, NO3−-N, and NH4+-N in groups with applications of cow-dung vermicomposting compared to CK. Except at 35 °C, soil respiration in the Camellia oleifera of Group A was consistently the strongest. The maximum soil carbon emission (C0) was determined through a simulation of potential carbon emissions, with all correlation coefficients exceeding 0.95. The contents of TC and TN were positively correlated with MBC and MBN (p <0.001), while the C: Nmicro was negatively correlated with TN, AN, MBN, and inorganic nitrogen. Based on temperature sensitivity (Q10), the influence of temperature on soil mineralization rate was observed. The vermicomposting of cow dung had a noticeable effect, as Group B showed significantly stronger enzyme activity compared to other groups. These results indicate that changes in MBC can impact the stability of soil carbon mineralization. The roles of soil moisture and microorganisms should be considered when predicting dynamic changes in the soil carbon pool of Camellia oleifera when applying fertilizers and improving its soil carbon sequestration capacity.