We hypothesize that the dynamics of O2-mediated blood flow responses in skeletal muscle capillaries are altered under different tissue carbon dioxide concentrations ([CO2]) due to the interaction of overlapping mechanisms. Eight male Sprague Dawley rats (164-215 g) were anesthetized and instrumented for systemic monitoring. The extensor digitorum longus muscle was isolated and reflected over a microfluidic gas exchange chamber mounted in an inverted microscope stage. 4-min intravital video recordings of capillary blood flow during O2 challenges consisted of a 1-min baseline at 7% O2 concentration ([O2]), followed by 3 min at 2% [O2], under constant background [CO2] at 2%, 5%, and 8%. Recordings were analyzed offline using custom MATLAB software. Time transients (τ) of capillary hemodynamic responses were determined using a least squared regression fit to single- and double-exponential models. Fast component τ of the O2-mediated capillary red blood cell (RBC) velocity response was 2.1 s for 2% [CO2], 3.8 s for 5% [CO2], and 7.0 s for 8% [CO2]. Third minute low [O2] capillary RBC supply rate increases from baseline were greater for 8% [CO2] (5% [CO2]: 6.4 ± 8.7 cells/s vs. 8% [CO2]: 8.5 ± 10.7 cells/s, p = 0.0007). The fast component τ of O2-mediated capillary hemodynamic responses was found to be slower with increasing background tissue [CO2], suggesting that multiple interacting mechanisms are involved to appropriately regulate O2 delivery under different CO2 conditions in partial support of the hypothesis.

We aim to assess the reliability of cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) obtained simultaneously from a novel multi-band pseudo-continuous arterial spin labeling (M2-PCASL) sequence and hypercapnic gas challenge, to examine factors influencing CBF variability, and to evaluate the impact of carbon dioxide (CO2) concentration on CVR estimates. Nine participants underwent test-retest M2-PCASL scans at 3T with hypercapnia to quantify CBF and CVR. Reliability was assessed using the intraclass correlation coefficient (ICC) at whole brain, region of interest (ROI), and voxel levels. Linear mixed-effect models were used to investigate factors contributing to CBF variability. Independent samples t-tests were used to compare BOLD CVR and temporal contrast to noise ratio (tCNR) from different CO2 concentrations. With smoothing, the M2-PCASL sequence estimated baseline CBF and BOLD CVR with good to excellent reliability (ICC > 0.81) in the whole brain, gray matter (GM), and white matter (WM). Average ICCs across the Automated Anatomical Labeling atlas ROIs were between 0.50 ± 0.30 and 0.69 ± 0.19. CBF CVR achieved fair to moderate reliability in GM (ICCs between 0.42 and 0.55). Head motion was significantly associated with CBF temporal SNR (p ≤ 0.002). 5% and 8% CO2 yielded similar BOLD CVR estimates, but the BOLD tCNR using 5% CO2 was lower, although not statistically significant. The M2-PCASL sequence with hypercapnia reliably estimates baseline CBF and BOLD CVR at improved spatial and temporal resolutions relative to existing methods, enabling us to noninvasively and comprehensively assess cerebrovascular health.

Background Indoor air quality (IAQ) is a well demonstrated actionable determinant of health status. Low-cost sensors (LCS) could enable patient-centred assessments, but real-world clinical utility is uncertain. Objective Evaluate the feasibility, usability and clinical indications of home IAQ monitoring with LCS. Methods We conducted a cohort study involving household continuous IAQ monitoring with LCS of 205 adults with chronic obstructive pulmonary disease, bronchiectasis or asthma. Household IAQ was profiled prospectively over a 2-month period registering concentrations of carbon dioxide, particulate matter 2.5 µm (PM 2.5 ) and formaldehyde every 10 min. For each pollutant, dwellings were classified as good, moderate or unhealthy according to the Global Open Air Quality Standards thresholds. Pulmonary exacerbations requiring unplanned hospitalisations and all-cause emergency department (ED) visits over the preceding 12 months were registered and potential relationships with household IAQ results were explored. Results Of the 205 participants, 178 were included in the final analysis after excluding dropouts and cases with insufficient monitoring data. More than half of homes (51.7%) had at least one pollutant in an at-risk category. The burden was mostly generated by PM 2.5 : 40.1% of dwellings were classified as at risk (32.8% moderate; 7.3% unhealthy). Formaldehyde exceeded the low-risk threshold in 22 homes (12.4%). Tobacco smoking, either active or passive, was significantly associated with PM 2.5 levels (p<0.001). No relationships were found between IAQ categories and hospitalisations nor with all-cause ED visits. Conclusions LCS are useful tools for short-term, targeted household IAQ screening in chronic respiratory patients. Indoor pollution is highly prevalent and largely PM 2.5 driven. Further research is needed to assess the short-term health impacts of these exposures. Trial registration number NCT06421402 .

Forest ecosystems are the dominant terrestrial carbon sink and play a critical role in mitigating climate change. However, conventional approaches based on single methods often fail to accurately characterize background carbon dioxide (CO2) concentrations, limiting the reliability of regional carbon accounting. An integrated forest carbon sink monitoring framework was developed and applied in Kunyu Mountain, China, for reconstructing net ecosystem productivity (NEP). Within this framework, satellite observations, mobile ground-based measurements, the Gradient Boosting Regression Trees (GBRT) algorithm, and the Boreal Ecosystem Productivity Simulator model were combined. With the GBRT-derived prior CO2 field incorporated, the BEPS model's performance improved: the correlation between simulations and observations increased from 0.571 to 0.802. Results indicate that Kunyu Mountain's NEP exhibited a sustained increase, with a marked acceleration after 2016, coinciding with China's 13th Five-Year Plan, leading to a >40% rise in annual carbon sequestration by 2024 relative to 2001. Seasonal analyses likewise indicate that the carbon uptake period became both longer and more intense. Further attribution analysis reveals that ecological conservation policies generated an additional 5%-7% increase (approximately 30-50 gC·m-2). This framework provides a novel approach to more accurately account for regional carbon sinks and evaluate the effectiveness of ecological policies.

Underground bio-methanation entails the conversion of surplus renewable electricity into hydrogen ($\text{H}_2$), then storing the hydrogen and carbon dioxide ($\text{CO}_2$) in a geological formation, and the conversion of the mixture into methane ($\text{CH}_4$) using methanogenic bacteria. The method offers the dual benefit of storing renewable electricity and recycling carbon dioxide simultaneously. However, in-situ observations have revealed that the system's mixture is difficult to control due to the emergence of non-attenuating self-organizing patterns. These structures result in the formation of zones of high methane concentration and other of high carbon dioxide concentration, a typical behavior for non-linear reaction-diffusion systems. The spatial heterogeneity of the gas distribution implies incomplete methanation, which consequently affects the quality of the gas produced. To resolve this issue, it is necessary to determine the limits of the pattern zone with respect to the process parameters and to maintain the system outside of this zone. In this paper, we analyze the criteria that lead to the emergence of patterns. We demonstrate the appearance of different regimes including stationary patterns driven by Turing’s instability and uniform pattern in space but periodically oscillating in time associated with the phenomenon of Hopf-Andronov bifurcation. We introduce novel spatio-temporal patterns known as jumping waves. To our knowledge, this is the first time such a result is demonstrated in the context of underground hydrogen storage (UHS).

This experiment aimed to explore the effects of different doses of compound probiotics (a 1:1:1 mixture of Saccharomyces cerevisiae, Lactobacillus acidophilus, and Bacillus subtilis) added to the diet on pregnant sows and weaned piglets. The experiment was carried out in two stages. Experiment with pregnant sows: thirty-six second-parity Large White sows at 80 d of late gestation were randomly divided into a control group, experimental group I, and experimental group II. The control group was fed a basal diet, while experimental groups I and II were fed the basal diet supplemented with 2 g/kg and 3 g/kg of compound probiotics, respectively. The pre-experiment lasted 7 d, and the formal experiment continued until the end of lactation. The results showed that the numbers of live piglets per litter, healthy piglets per litter, litter birth weight and litter weaning weight in the experimental groups were significantly higher than those in the control group (p < 0.05). Colostrum IgG concentration in experimental group I was significantly higher than that in the control group and experimental group II (p < 0.05). Compound probiotics significantly increased colostrum immunoglobulin levels (p < 0.05). The concentrations of ammonia, carbon dioxide and PM2.5 in the barns of the experimental groups all showed a decreasing trend. Experiment with weaned piglets: a total of 160 Landrace × Yorkshire crossbred weaned piglets at 30 d of age with an initial body weight of (8.01 ± 0.13) kg were randomly assigned to four groups. The control group was fed a basal diet, while the treatment groups were supplemented with 2, 3, and 4 g/kg of compound probiotics, respectively. The results indicated that average daily gain and average daily feed intake in experimental group III were significantly higher than those in the control group, while the feed-to-gain ratio and diarrhea rate were significantly lower (p < 0.05). The apparent digestibility of crude fiber was significantly higher than that in the control group (p < 0.05), and serum IgA was significantly higher than in the other groups (p < 0.05). In conclusion, dietary supplementation with 2 g/kg compound probiotics for sows in late gestation showed the optimal effect, improving reproductive performance, colostrum immune indices and reducing harmful gases in the barn. For weaned piglets, supplementation with 4 g/kg compound probiotics improved growth performance, nutrient digestibility and serum immune indices.

Currently, the increasing concentration of carbon dioxide (CO2) pollutants in the Earth's atmosphere due to the expansion of factories and vehicles has caused destructive effects, including an increase in the greenhouse effect, long-term droughts, insufficient rainfall, melting polar ice, and climate change. The various methods are available for removing carbon. Photocatalytic processes have emerged as promising and sustainable approaches for CO2 conversion because they don't make harmful byproducts, affect most contaminants, do not have any detrimental effects on the environment, don't need expensive, complicated equipment, are readily recoverable, recover, and use again. Perovskite is a novel kind of photocatalyst that exhibits excellent photocatalytic performance. Photocatalysts with more than one structure are better at covering a bigger area. Perovskite photocatalysts can reduce pollutants more quickly and better than other mono-photocatalysts. When exposed to visible light, this investigation intends to make a modern perovskite photocatalyst that exhibits enhanced performance and can convert carbon dioxide into solar fuels. To achieve this, g-C3N4 (gCN), a non-metallic co-photocatalyst; Bi2ZnTiO6 (BZTO), a double perovskite; and zero valent nickel/copper (Ni/Cu) nanoparticles, a metallic co-photocatalyst, were synthesized. XRD, SEM, EDX/mapping, UV-vis, DRS, and PL experiments were employed to look at the phase, crystallographic, structural, and photocatalytic properties. The performance of the Ni/Cu-loaded Bi2ZnTiO6 perovskite/g-C3N4 0D/3D/2D QDs Schottky/Z-scheme ternary heterojunction nanocomposite was optimized and improved using Taguchi's experimental design. The temperature of the reaction, how rapidly it was agitated, how long it took, how much CO2 and photocatalyst were present, visible irradiation intensity, interval between photoreduction site and light source, and the pH of the reaction are all critical parameters. To achieve the best conditions according to the Taguchi method, the solution should have a reaction medium pH of 5.0, a temperature of 25°C, a mixing rate of 200rpm, a photoreduction time of 300min, a photocatalyst dosage of 1.0g/l, a CO2 concentration of 400mg L-1, a light intensity of 70 W, distance between light source and aqueous solution. The Ni/Cu-loaded Bi2ZnTiO6/g-C3N4 Schottky/Z-scheme ternary heterojunction nanocomposite transformed the CO2 with a proficiency rate of 1727μmol g-1h-1 (total CO2 conversion efficiency 95%) into the main solar fuels of methane (CH4) gas with a productivity ratio of 863.5μmol g-1h-1 (selectivity efficiency 50%) and methanol (CH3OH) with a productivity rate of 690.8μmol g-1h-1 (selectivity efficiency 40%). Additionally, the Ni/Cu-loaded Bi2ZnTiO6/g-C3N4 ternary nanocomposite maintained its structure and could be utilized over and over again, even after five cycles of continuous use.

Abstract Accurate simulation of regional carbon dioxide (CO 2 ) concentrations is critical for urban carbon monitoring, inverse modeling and mitigation. However, large uncertainties persist due to differences in anthropogenic emission inventories in China. Focusing on Jiangsu Province in the Yangtze River Delta, where the mean inter‐inventory spread in annual city‐level total emissions exceeds 60% and spatial discrepancies are substantial, we assessed how six widely used inventories affect modeled CO 2 fields. Using a 3‐km WRF‐Chem‐VPRM framework, we performed simulations for July and December 2022. To isolate the impact of inventory‐related uncertainties, we designed sensitivity experiments that separately perturbed inventory selection, emission magnitude, spatial distribution, and temporal and vertical allocation used in the inventory‐to‐model matching. All experiments were driven by identical meteorological conditions to ensure comparability. Model outputs showed good consistency with meteorological observations, CarbonTracker near‐surface CO 2 , and OCO‐2 XCO 2 ( R ≈ 0.83), while also capturing physically reasonable near‐surface diurnal behavior. Inventory selection led to a nighttime urban domain‐averaged standard deviation of 8.2 ppm. Sensitivity results indicated that spatial allocation differences contributed more to modeled CO 2 variability than total emission magnitude. Under stable boundary‐layer conditions, vertical allocation emerged as a key uncertainty source, producing 25–50 ppm differences in surface CO 2 . These results demonstrate that inventory‐to‐model matching, especially vertical allocation, can exceed the impact of inventory selection for high‐resolution urban CO 2 simulations under stable nighttime conditions. This study provides a quantitative basis for diagnosing inventory‐induced variability and supports the development of fine‐resolution, vertically resolved inventories for robust urban CO 2 modeling and future inversion efforts.

Microbial carbonate biomineralization in the deep subsurface biosphere: Decoding long-term carbon sequestration potential and methanogenesis risk.

A multimodal dataset for environmental occupancy detection

Aiming at the problems of poor real-time performance, weak local interaction and limited data processing capacity of traditional agricultural monitoring systems, this paper presents an intelligent farm monitoring and control system based on ESP32-P4 and a 7-inch IPS touch screen. Taking the dual-core RISC-V ESP32-P4 with a main frequency of 400 MHz as the main controller, the system drives the display screen via the MIPI-DSI interface and adopts the LVGL graphics library to realize a high-frame-rate local human-machine interaction interface. It integrates five types of sensors for temperature, humidity, soil moisture, light intensity and carbon dioxide concentration, and supports Wi-Fi cloud data transmission as well as closed-loop control functions including automatic irrigation and environmental regulation. The test results show that the interface refresh rate is no less than 28 FPS, and the control response time is less than 100 ms. The system can satisfy the requirements of real-time monitoring and precise control for small and medium-sized intelligent farms.

ABSTRACT As a key greenhouse gas, changes in carbon dioxide (CO2) concentrations critically in-fluence global ecosystems and sustainable human development. Current column-averaged dry-air mole fraction of CO2 (XCO2) monitoring methods exhibit significant data gaps due to limited range of observations and unfavourable atmospheric conditions such as aerosols and clouds. This limitation severely restricts high-resolution monitoring of the spatial distribution of carbon source-sink. To address these limitations, we develop a novel Semi-supervised Adaptive Multi-Pixel Transformer (SAMPT) that leverages spatial correlation among neighbouring pixels to achieve XCO2 mapping with high spatiotemporal resolution. Using this method, we generate daily 0.1° resolution continuous XCO2 dataset for China from 2016 to 2020. To evaluate the model’s reliability in generating full-coverage data, we conduct multidimensional validation using Orbiting Carbon Observatory-2 OCO-2 satellite products, ground-based station observations, and Global Moran’s I spatial autocorrelation analysis. Results show that high accuracy with 10-fold cross-validation (R 2 = 0.928 and RMSE = 1.05 ppm), ground-based station validation (R 2 = 0.982 and RMSE = 1.10 ppm), and with a high positive correlation (Global Moran’s I = 0.818). We find that China’s XCO2 distribution exhibited an east-west decreasing trend (Shanghai: 411.56 ppm; Tibet: 407.97 ppm). Anomalously, the southwest shows both low annual average but high variance, possibly indicating cross-border influences. Our study proposes an effective methodology for achieving complete regional XCO2 coverage estimation, which can provide enhanced data support for carbon source-sink research.

With carbon dioxide (CO2) concentrations onthe rise,direct air capture (DAC) technologies to remove carbon dioxide fromthe atmosphere are attracting increased attention. One popular approachis to use aminopolymer sorbents, such as polyethylenei mine (PEI),to absorb the CO2 and capture it through chemical reactionswith the amine groups. In practice, the CO2 capture efficiencyin aminopolymer sorbents strongly depends on the relative humidity,where the theoretical CO2 capture efficiency can changeby 2-fold in going from a dry to a humid environment through the formationof either an ammonium carbamate or carbamic acid capture product,respectively. In this study, we utilize monovalent chloride saltswith increasing cation size (LiCl, NaCl, KCl, or CsCl) to modulatewater uptake and thus product formation, quantified using both gravimetricand spectroscopic methods. We utilize tandem quartz crystal microbalancewith dissipation (QCM-D) and polarization modulation infrared reflectionabsorption spectroscopy (PM-IRRAS) to decouple the individual uptakeof CO2 and H2O from the total sorption mass.The added salts were found to alter the H2O sorption levelsof the PEI films, thereby impacting the CO2 uptake. Wecomplement QCM-D/PM-IRRAS measurements using a high-throughput attenuatedtotal reflectance Fourier transform infrared (ATR-FTIR) spectroscopycell that conditions PEI films under varying relative humidities ata constant CO2 concentration. The carbamate/carbamic acidformation and H2O absorption were quantified by measuringthe intensity of their characteristic vibrational signatures, informedby the QCM-D/PM-IRRAS experiments. Overall, we find that the additionof salt additives enables tuning of H2O and CO2 sorption at various humidity levels, with the identity of the saltcation directing the relative component uptake. These observationsprovide insight into the effectiveness of additives, especially salts,in modulating the CO2 uptake of aminopolymer sorbents beingdeployed in strategic carbon capture applications.

ABSTRACT To estimate litter and soil organic matter decomposition by using soil temperature at 5 cm in depth, litterbag and soil incubation experiments were conducted. Litterbags, filled with leaf litter obtained from oak and Japanese cedar forests in Rokkasho village, were placed on the soil surface of each forest, and each soil temperature were measured. In another experiment, soil from each forest was incubated at temperatures of 10°C, 20°C, or 30°C for approximately 700 days, and the atmospheric carbon dioxide concentrations in the incubation bottles were analyzed to estimate the amount of carbon dioxide released from the soil at each temperature. The remaining amount of SOM was calculated from the estimated cumulative carbon dioxide release. SOM decomposition rates and their temperature sensitivity were analyzed using a known model with two decomposable compartments with different decomposition rates (an active and an intermediate compartment) and one recalcitrant SOM compartment. The Arrhenius equation was applied with the field soil temperature or incubation temperature as the temperature parameter, and then Q10 and the activation energy of decomposition rate of leaf litter and two SOM compartments were calculated to examine the temperature sensitivity of each decomposition rates. The cedar leaf decomposition rate was estimated to be more sensitive to temperature than oak leaf. The estimated decomposition rate of the active compartment of SOM was more sensitive to temperature than that of the intermediate compartment. These experimental methods make it possible to use the same soil temperature within a forest to predict litter and SOM decomposition rates.

Oxygen content in wine significantly influences wine stability and shelf life. Wine producers commonly use nitrogen sparging to modify the final oxygen content in the wine, however, it is not always clear how long the wine producer should operate the sparging in order to achieve the desired oxygen content. Oxygen removal during sparging is controlled by the volumetric oxygen transfer coefficient (K L a). This study investigated the effect of wine type (red, rosé, and white), temperature (5°C, 10°C, and 20°C), and carbon dioxide concentration on K L a during nitrogen-induced oxygen removal. By systematising these variables, the work bridges knowledge gaps and offers actionable insights for more effective oxygen management in diverse wine matrices. Results indicate that K L a values are significantly influenced by both wine type and temperature, with higher values observed in red wine compared to white and rosé wines, potentially due to variations in ethanol and other dissolved compounds’ concentrations. Temperature elevation enhanced mass transfer rates across all wine types, highlighting the temperature dependence of K L a. Moreover, the presence of carbon dioxide reduced K L a, likely affecting bubble coalescence and stability. This is the first study which has investigated the variability of K L a as a function of composition, temperature, and carbon dioxide concentration – an important set of parameters since these are the variable conditions which wine makers must contend with.

• Saturation with carbon dioxide nanobubbles increases concentration and stability • Salt content influences carbon dioxide concentration and stability in dispersions • Nanobubble saturation of growth media results in higher concentration and stability The application of nanobubbles (NBs) in materials research, water treatment, and chemical reactions is well documented, primarily due to their high stability, longevity, and enhanced mass transfer rates. Recently, oxygen and air nanobubbles have been employed in enhancing algal and plant growth. However, data on carbon dioxide nanobubbles remain scarce, particularly regarding their effects on concentration and retention. In this work, carbon dioxide was dissolved into aqueous solutions with varying salt concentrations, and the flow was depressurized through a needle valve to generate NBs dispersions. Particle number and carbon dioxide concentration were analyzed over a 10-day period and compared with a control solution generated via bubbling. The dispersions exhibited significant NBs concentrations and, more importantly, higher carbon dioxide levels than the bubbling solution. The highest concentrations were observed in 1 mM NaCl and distilled water, corresponding to increases of 136% and 97%, respectively. All dispersions maintained superior concentrations compared to the control. Furthermore, the dispersions retained elevated carbon dioxide levels for an average of five additional days relative to the bubbling solution. Finally, the experimental data were used to fit exponential models describing the evolution of the dispersions. These models revealed both the influence of the saturation methodology and the trade-off between salinity, particle size, and carbon dioxide retention. Overall, the results demonstrate that this methodology provides advantages over conventional carbon dioxide delivery strategies and may contribute to process optimization in algal biomass production.

This study examined how external thermal exposure affected the self-sustained smouldering behaviour of chromated copper arsenate (CCA)-treated wood. A Fire Propagation Apparatus was used, varying incident heat flux and exposure duration to emulate passing wildfire scenarios. Wood density and CCA retention were kept within narrow ranges. Responses from ignition through smouldering propagation were evaluated using mass loss, thermocouple temperature, and exhaust-gas carbon monoxide (CO) and carbon dioxide (CO 2 ) concentrations over time. The time to peak CO or CO 2 aligned with the time to peak mass-loss rate, providing a practical and robust indicator of smouldering severity. Smouldering severity was governed mainly by total incident energy rather than heat-flux intensity or duration alone; tests with comparable incident energy produced similar severities. Increasing total incident energy deepened char, increased thermal penetration, and increased mass loss at the onset of self-sustained smouldering after flameout. However, smouldering severity does not increase linearly with incident energy. At bench scale, smouldering propagation was not perfectly one-dimensional despite the initial heating being almost one-dimensional. These findings identify total incident energy as a practical control parameter for reproducing wildfire-analogue exposures and provide an operational severity metric to support development of monitoring protocols, severity-based fire classifications, product screening and targeted intervention strategies. • Smouldering severity is governed mainly by total incident energy • CO and CO 2 concentration peaks provide practical proxies for smouldering severity • Smouldering severity does not increase linearly with incident energy • Smouldering propagation is not perfectly 1D even with predominantly 1D heating

Crops at high altitudes often face simultaneous ecological stress from cadmium (Cd) and freeze-thaw cycles during growth. In this study, rye (Secale cereale L.) was selected as the model organism to examine the physiological impacts of exogenous CA application (19 mg/L) on rye seedlings exposed to both individual and combined stresses of freeze-thaw and cadmium (30 mg/L). Molecular docking studies revealed interactions between Cd and the active sites of CAT, chlorophyll, and POD proteins. The results demonstrated that combined stress increased malondialdehyde (MDA) by 40.95%, hydrogen peroxide (H2O2) by 28.04%, and ascorbate peroxidase (APX) by 18.45%. The results confirmed that freeze-thaw condition (FTC) and Cd stresses reduced the net photosynthetic rate (Pn) by 64.87%, stomatal conductance (gs) by 27.45%, and Water use efficiency (Wue) by 30.84% while increasing intercellular carbon dioxide concentration (Ci) of rye seedlings. CA improved resistance to these stresses in rye seedlings by increasing the activity of APX and CAT enzymes. We believe that the findings of this study will be of particular interest to readers of environmental pollution and will be crucial for formulating strategies to enhance plant adaptability and flexibility in the face of rising levels of environmental pollutants and climatic fluctuations.

Accurate measurement of carbon dioxide (CO2) in water is essential for environmental monitoring, water quality assessment, and carbon flux estimation. Traditional methods, such as titration and conductivity-based methods, are often limited by high costs, operational complexity, or reliance on chemical reagents. This study proposes a new algorithm based on bubbling for determining free CO2 concentrations (CO2 (aq)) in water. By introducing air into water and fitting gas-phase CO2 dynamics with a nonlinear physical model, the initial CO2 (aq) concentration can be directly obtained. Experiments with tap water at different temperatures yielded CO2 (aq) concentrations of 121.38 ± 0.74 μmol/L, 184.50 ± 0.92 μmol/L, and 211.11 ± 0.78 μmol/L. Experiments with saltwater yielded CO2 (aq) concentrations of 128.46 ± 1.83 μmol/L, 165.15 ± 2.20 μmol/L, and 193.20 ± 1.46 μmol/L. Validation against an independent integration method yielded a minimum relative error of 0.67%, confirming the model's accuracy and stability. Furthermore, a significant negative correlation was observed between temperature and the equilibrium gas-liquid CO2 concentration ratio, suggesting that temperature effects require correction in practical applications. In conclusion, this method offers a simple and reliable approach for CO2 measurement in water, with promising applications in environmental science and engineering.

Lignocellulosic agricultural residues such as coconut husk are abundant but recalcitrant substrates that limit efficient biogas production during anaerobic digestion. We evaluated the effect of biological pretreatment of coconut husk on archaea, volatile fatty acid (VFA) profiles, and biogas production during anaerobic digestion. Coconut husk was pretreated for 50 days using a consortium of cellulolytic bacteria isolated from poultry feces and subsequently digested alongside untreated husk (control) in batch reactors. Cellulose-degrading bacteria were presumptively characterized based on morphological, cultural, and biochemical characteristics and included Bacillus megaterium, Bacillus licheniformis, Lactobacillus plantarum, Bacillus cereus, and Bacillus subtilis based on morphological, cultural, and biochemical characteristics. Ten archaeal genera were detected across treatments, including Methanobrevibacter, Methanomassiliicoccus, Methanobacterium, Methanoculleus, Methanosarcina, Methanomicrobium, Desulfurococcus, Thermosphaera, Methanogenium, and Methanoregula. The control digestate exhibited higher archaeal diversity with a low methane production. The pretreated reactor (Ch + Cdb) produced a cumulative biogas yield of 88,355 mL gVS⁻1, compared with 67,105 mL gVS⁻1 in the control, representing a significant 1.32-fold increase (p ≤ 0.05). Methane production commenced on day 3 in Ch + Cdb relative to day 15 in the control indicating a shortened lag phase and enhanced breakdown of substrate. Mean methane concentration increased from 44.52 ± 25.4% in the control (Ch) to 56.38 ± 16.54% in the Ch + Cdb treatment representing a 1.27-fold increase in methane content relative to the control. Carbon dioxide concentration also increased from 11.41 ± 6.24% in the control to 15.01 ± 5.54% in the treated sample, corresponding to a 1.32-fold increase. Total VFA concentration was higher in Ch + Cdb at 596.43 mg L⁻1 than in the control (562.24 mg L⁻1), with acetic acid as the dominant component. Increased concentrations of acetic acid, propionic acid, and butyric acid in the treated system did not inhibit methanogenesis, suggesting improved intermediate conversion and process stability. Biological pretreatment enhanced hydrolysis, accelerated methanogenesis, and improved biogas yield with a stable reactor performance, and highlight the whole-cell biocatalyst potential of cellulose-degrading bacteria for optimum anaerobic digestion of lignocellulosic biomass.