Carbon Dioxide Research Articles

Enhancing water saturation predictions from conventional well logs in a carbonate gas reservoir with a hybrid CNN-LSTM model

Predicting water saturation in the South Pars gas field’s carbonate reservoirs has been challenging due to limitations in conventional methods like the Archie equation. This leads to unproduced gas volume and water coning phenomena, leaving a gap for an intelligent model to determine the water saturation profile more accurately. Four machine learning algorithms: XGBoost, long short-term memory (LSTM), 1-dimensional convolutional neural network (1D-CNN), and a hybrid CNN-LSTM were developed to predict experimental water saturation values from conventional well logs. A total of 10,674 data points were collected from four wells in the South Pars gas field, where well logging evaluations and core measurements were available. The methodology includes data pre-processing to de-noise and transform data into a proper format, feature engineering followed by feature selection based on domain knowledge, models’ training, testing, and optimizing. XGBoost hyperparameters were tuned using grid search, and each neural network model was optimized using a genetic algorithm. The network architectures were designed with specific layers and activation functions to enhance predictive capabilities. A robust validation process was conducted using a blind well dataset. Archie equation was also applied for better comparative analysis. Results showed that the CNN-LSTM model was the most effective, with an R-squared accuracy score of 0.859, while the Archie equation had the least R-squared accuracy of 0.322 in the validation dataset. Furthermore, utilizing an inclusive dataset, a new CNN-LSTM model was constructed with a 10-fold framework, achieving an average R-squared of 0.968. This model was utilized to develop an application that displays the reservoir’s water saturation profile and other features as a well log report within a dashboard. The findings support two points: first, 1D-CNN and LSTM work better together in a hybrid structure, and second, the Archie equation is ineffective in carbonate reservoirs of the South Pars gas field. The study intends to enrich the literature by employing a hybrid machine learning algorithm compared to earlier studies and surpassing traditional protocols by comparing algorithms in a blind well to offer a reliable validation mechanism.Graphical abstract

Detection of carbon monoxide and carbon dioxide gases using quartz crystal microbalance coated with a graphitic carbon nitride film

Detection of carbon monoxide and carbon dioxide gases using quartz crystal microbalance coated with a graphitic carbon nitride film

An Analytical Workflow to Quantify Biodegradable Polyesters in Soils and Its Application to Incubation Experiments.

Soil biodegradable polyesters are designed to undergo to microbial utilization in aerobic soils, forming carbon dioxide and microbial biomass. These polyesters are thus viable substitutes for conventional, persistent polymers (e.g., polyethylene) in specific applications for which the transfer of some of the polymers into the soil is inevitable. While polymer biodegradability is often assessed in laboratory incubations using respirometric analysis of formed CO2, approaches to accurately quantify biodegradable polyesters in soils and to track their mass loss in field incubations over time remain missing. This study first introduces an analytical workflow combining Soxhlet extraction with proton nuclear magnetic resonance spectroscopy for the accurate, high-throughput, and chemically selective quantification of eight commercially important biodegradable polyesters (i.e., poly(butylene adipate-co-terephthalate), polylactic acid, poly(3-hydroxybutyrate-co-3-hydroxyhexanoate), poly(3-hydroxybutyrate-co-3-hydroxyvalerate), polycaprolactone, polybutylene adipate, polybutylene azelate, and polybutylene succinate), and the nonbiodegradable polymer polystyrene, in six soils spanning a range of types and physicochemical properties. This work introduces an effective sample deployment-retrieval approach that, combined with the analytical method, allows the biodegradation of poly(butylene adipate-co-terephthalate) and polylactic acid from a biodegradable mulch film in three agricultural soils to be monitored. In combination, the two parts of this work lay the foundation to accurately quantify and monitor biodegradable polymers in soils.

Carbonates identified by the Curiosity rover indicate a carbon cycle operated on ancient Mars.

Ancient Mars had surface liquid water and a dense carbon dioxide (CO2)-rich atmosphere. Such an atmosphere would interact with crustal rocks, potentially leaving a mineralogical record of its presence. We analyzed the composition of an 89-meter stratigraphic section of Gale crater, Mars, using data collected by the Curiosity rover. An iron carbonate mineral, siderite, occurs in abundances of 4.8 to 10.5 weight %, colocated with highly water-soluble salts. We infer that the siderite formed in water-limited conditions, driven by water-rock reactions and evaporation. Comparison with orbital data indicates that similar strata (deposited globally) sequestered the equivalent of 2.6 to 36 millibar of atmospheric CO2. The presence of iron oxyhydroxides in these deposits indicates that a partially closed carbon cycle on ancient Mars returned some previously sequestered CO2 to the atmosphere.

Impact of climate change on aerobiology, rhinitis, and allergen immunotherapy: Work Group Report from the Aerobiology, Rhinitis, Rhinosinusitis & Ocular Allergy, and Immunotherapy, Allergen Standardization & Allergy Diagnostics Committees of the American Academy of Allergy, Asthma & Immunology.

Impact of climate change on aerobiology, rhinitis, and allergen immunotherapy: Work Group Report from the Aerobiology, Rhinitis, Rhinosinusitis & Ocular Allergy, and Immunotherapy, Allergen Standardization & Allergy Diagnostics Committees of the American Academy of Allergy, Asthma & Immunology.

Efficient Kinetic Separation of Carbon Dioxide from Acetylene Using Mordenites Featuring Modified 1D Channels with Excellent Selectivity and Diffusion.

The design of physical adsorbents for a precise recognition of gas molecules with similar kinetic sizes is of importance as adsorptive separation can serve as an alternative to energy-intensive distillation processes. However, it is challenging to balance the selectivity, capacity, and adsorption kinetics of the adsorbents. Herein, an efficient kinetic separation of acetylene and carbon dioxide is reported, which have nearly identical kinetic sizes, achieved through modification of the one-dimensional (1D) channels of a micrometer-sized mordenite. Under ambient conditions, the weak acid salt-modified mordenite denoted as NaAlO2@MOR(0.5), exhibits a remarkable kinetic separation selectivity of 534.3 while retaining an excellent diffusivity for CO2. Compared to other adsorbent materials, its dynamic column performance for carbon dioxide significantly exceeds those of molecular sieve materials. In terms of separation selectivity, it is superior to thermodynamic separation adsorbents. The high efficiency of NaAlO2@MOR(0.5) in CO2/C2H2 kinetic separation is validated by column breakthrough experiments. Furthermore, NaAlO2@MOR(0.5) has a low cost and high thermal stability. This study can guide the design of adsorbents that balance selectivity, capacity, and gas diffusivity, to provide a highly efficient kinetic separation of gas molecules with similar kinetic diameters.

Emissions of ammonia and greenhouse gases from broiler chickens can be reduced by growing younger birds.

Ammonia (NH3) and greenhouse gas (GHG) emissions from poultry production have become of increasing interest over the past decade. The objectives of this study were (1) to quantify the emissions of NH3, nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) from poultry houses and (2) to estimate the amount of each gas produced per kilogram of bird grown for flocks of various duration to determine if emissions per kg vary with flock length (i.e., bird marketing age). Two commercial broiler houses in Northwest Arkansas were used for this study. Gas concentrations and emissions were measured during 4-week flocks (n=12), 7-week flocks (n=3), and 8-week flocks (n=4). Average emissions per kg bird for the 4-week flocks were 2.9g NH3 kg-1, 0.3g N2O kg-1, 3.5g CH4 kg-1, and 658g CO2 kg-1. Ammonia emissions per kg bird increased by 179% and 293% for 7- and 8-week-old birds, respectively, compared to the 4-week-old birds.Nitrous oxide emissions per kg bird increased by 164% and 387% for 7- and 8-week birds, respectively.Methane emissions increased by 35% and 225% for 7- and 8-week-old birds, respectively. Carbon dioxide emissions increased by 185% and 351% for 7- and 8-week-old birds, respectively. Higher emissions from older birds were likely due to less efficient feed conversion as birds age.These results indicate that growing younger (i.e., smaller) chickens may be more sustainable, since it results in much lower emissions of NH3 and GHGs per kg of bird produced, while also utilizing much less feed and being more efficient.

Nannochloropsis oceanica IMET1 and its bacterial symbionts for carbon capture, utilization, and storage: biomass and calcium carbonate production under high pH and high alkalinity.

To combat the increasing levels of carbon dioxide (CO2) released from the combustion of fossil fuels, microalgae have emerged as a promising strategy for biological carbon capture, utilization, and storage. This study used a marine microalgal strain, Nannochloropsis oceanica IMET1, which thrives in high CO2 concentrations. A high-pH, high-alkalinity culture was designed for CO2 capture through algal biomass production as well as permanent sequestration through calcium carbonate (CaCO3) precipitation. This was accomplished by timed pH elevation and the addition of sodium bicarbonate to cultures of N. oceanica grown at lab scale (1 L) and pilot scale (500 L) with 10% and 5% CO2, respectively. Our data showed that 0.02 M NaHCO3 promoted algal growth and that sparging cultures with ambient air after 12 days raised pH and created favorable CaCO3 formation conditions. At the 1 L scale, we reached 1.52 g L-1 biomass after 12 days and an extra 9.3% CO2 was captured in the form of CaCO3 precipitates. At the 500 L pilot scale, an extra 60% CO2 was captured (Day 40) with a maximum CO2 capture rate of 63.2 g m-2 day-1 (Day 35). Bacterial communities associated with the microalgae were dominated by two novel Patescibacteria. Functional analysis revealed that genes for several plant growth-promotion traits (PGPTs) were enriched within this group. The microalgal-bacterial coculture system offers advantages for enhanced carbon mitigation through biomass production and simultaneous precipitation of recalcitrant CaCO3 for long-term CO2 storage.IMPORTANCECapturing carbon dioxide (CO2) released from fossil fuel combustion is of the utmost importance as the impacts of climate change continue to worsen. Microalgae can remove CO2 through their natural photosynthetic pathways and are additionally able to convert CO2 into a stable, recalcitrant form as calcium carbonate (CaCO3). We demonstrate that microalgae-based carbon capture systems can be greatly improved with high pH and high alkalinity by providing optimal conditions for carbonate precipitation. Our results with the microalga, Nannochloropsis oceanica strain IMET1, show an extra 9.3% CO2 captured as CaCO3 at the 1 L scale and an extra 60% CO2 captured at the 500 L (pilot) scale. Our optimized system provides a novel approach to capture CO2 through two mechanisms: (i) as organic carbon within microalgal biomass and (ii) as inorganic carbon stored permanently in the form of CaCO3.

Mechanistic Insights to Cation Effects in Electrolytes for Electrocatalysis.

Traditional understanding of electrocatalytic reactions has primarily focused on the covalent interactions between adsorbates and catalyst surfaces, often overlooking the significant influence of the electrolyte on the catalytic process. Recently, researchers have highlighted the pivotal role of cations in the electrolyte, demonstrating their capability to modulate the reaction pathways and thus the activity and selectivity. These findings underscore the need for a deeper, atomic-level understanding of the electrode-electrolyte interface. This perspective presents the mechanisms through which cations affect electrocatalysis, with a focus on the hydrogen-bond network, the adsorption behavior of reaction intermediates, the electric field within the electrochemical double layer, and the local electronic properties of catalysts. It provides a summary of the influences of cations on various electrocatalytic reactions, including hydrogen oxidation reaction (HOR), hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), nitrogen reduction reaction (NRR), nitrate reduction reaction (NO3-RR), and carbon dioxide reduction reaction (CO2RR). At the end, future research directions are provided to maximize the potential of leveraging the cation effects in the design of more efficient electrolyte systems.

Advancing Yeast Metabolism for a Sustainable Single Carbon Bioeconomy.

Single carbon (C1) molecules are considered as valuable substrates for biotechnology, as they serve as intermediates of carbon dioxide recycling, and enable bio-based production of a plethora of substances of our daily use without relying on agricultural plant production. Yeasts are valuable chassis organisms for biotech production, and they are able to use C1 substrates either natively or as synthetic engineered strains. This review highlights native yeast pathways for methanol and formate assimilation, their engineering, and the realization of heterologous C1 pathways including CO2, in different yeast species. Key features determining the choice among C1 substrates are discussed, including their chemical nature and specifics of their assimilation, their availability, purity and concentration as raw materials, as well as features of the products to be made from them.

Effect of mild hypercapnia during the recovery period on the emergence time from total intravenous anesthesia: a randomized controlled trial.

Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35-40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Measurement report: Greenhouse gas profiles and age of air from the 2021 HEMERA-TWIN balloon launch

Abstract. Within the HEMERA balloon infrastructure project, a stratospheric balloon carrying a multi-instrument payload to a maximum altitude of 31.2 km was launched on 12 August 2021. On board the openly constructed gondola, several types of instruments were used for simultaneous air sampling and in-flight measurements to characterize climate-relevant trace gases in the stratosphere and troposphere, as well as to compare and evaluate different instrumental approaches and sampling techniques. For observations of the main greenhouse gases carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and sulfur hexafluoride (SF6), flask with AirCore sampling and in-flight spectrometry were deployed. Overall, results from different methods agree well. While better precision was achieved for the post-flight measurements of AirCore devices and flask sampling, in situ spectrometry provided a higher degree of detail on the vertical structure of the CH4 profile. Age of air was derived from mixing ratios of CO2 and SF6. As seen in previous studies, higher values were obtained from SF6 than from CO2. Correcting for chemical losses, maximum values of 4.4–5.1 years were derived from SF6 mixing ratios at altitudes above 20 km compared to 4.2–5.0 years from CO2 mixing ratios. The resulting dataset should be well suited for multi-tracer approaches to derive age of air, particularly in combination with a large suite of halocarbons measured from flask and AirCore sampling and one more AirCore sample which was reported in a companion publication (Laube et al., 2025).

AI enhancing prefabricated aesthetics and low carbon coupled with 3D printing in chain hotel buildings from multidimensional neural networks

There are approximately 70,000 economy chain hotels worldwide, generating about 300 million tons of carbon dioxide annually. While reducing carbon emissions can lower energy consumption, these hotels must also continually attract guests to ensure revenue growth and achieve sustainable development. This study focuses on the application of Artificial Intelligence (AI) in the prefabricated renovation of hotels, investigating how AI plays a crucial role in coupling low-carbon construction and aesthetic design. Using multidimensional algorithms within machine learning (ML), neural networks (NN), and statistical modeling (SM), this paper analyzes the impact of AI-driven prefabricated room renovations on tourist satisfaction and carbon emissions. The results indicate that AI can not only optimize energy consumption and structural efficiency in the renovation process but also achieve low-carbon goals while maintaining high-quality aesthetic designs. This study offers new theoretical insights into the integration of low-carbon and aesthetic design, filling gaps in the current literature, providing a pathway for achieving sustainable development goals (SDG 7, 8, and 12), and offering valuable implications for robotic intelligent construction and 3D printing in prefabricated buildings industry.

Exploring the carbon sequestration of an asphalt base course mixture containing novel cold-bonded biochar-rich lightweight aggregates

An emerging strategy to compensate for the greenhouse gas emissions of products is to incorporate carbonaceous materials obtained from removed atmospheric carbon dioxide, mainly obtained through biomass conversion. This approach can turn asphalt pavements into a functional carbon sink. In particular, biochar has been used as a bitumen modifier. However, due to performance limitations, carbonaceous materials were only added in small quantities to asphalt mixtures. An alternative approach is to produce lightweight aggregates to substitute a part of the mineral aggregates of the asphalt mixture. To this end, biochar is pelletised with a hydraulic binder and water in a cold-bonding process, forming spherical pellets labelled as carbon-rich lightweight aggregates (C-LWA). Like other lightweight aggregates, C-LWA showed a reduced mechanical strength compared to conventional mineral aggregates, adversely affecting the asphalt mixture performance. Cracking and rutting resistance almost linearly decreased with C-LWA content. The direct addition of biochar had a similar adverse influence on the mixture performance. Despite a reduced performance, adding biochar and C-LWA reduces the greenhouse gas emissions of asphalt mixtures. Net-zero emissions were estimated for the produced asphalt mixture by adding 5.5 ± 0.4% C-LWA or 3.0 ± 0.2% biochar obtained from the pyrolysis of landscape management wood. A wider range of C-LWA addition (1% to 35.1%) was estimated considering the greenhouse gas emission estimation variability of both asphalt and biochar production.

Unlocking Methane Generation via Photo-Thermal-Coupled CO2 Hydrogenation by Integrating FeNiCrMnCo Multicomponent Alloy with GaN Nanowires.

The exploration of a noble-metal-free photo-thermal-coupled catalytic architecture plays a vital role in solar-driven conversion of carbon dioxide (CO2) into high-value fuels and chemicals. In this study, FeNiCrMnCo multicomponent alloy (MCA) is integrated with GaN nanowires (NW's) for photo-thermal-coupled catalytic CO2 methanation. The MCA/GaN NW's nanohybrid demonstrates a considerable methane production rate of 199 mmol∙g-1∙h-1 with an impressive selectivity of 93% under white light irradiation of 3 W∙cm-2 at 290°C by external heating. The turnover number approaches 20,160 mole CH4 per mole of MCA over a continuous operation period of 120 h, showcasing remarkable stability. Mechanistic investigations reveal that the unique MCA provides a flexible platform for tailoring the electronic and catalytic properties to optimize the adsorption and activation of CO₂ and H₂, thus leading to efficient and selective CO₂ methanation. This study presents an industry-friendly architecture for photo-thermal-coupled CO2 hydrogenation into high-value fuels and chemicals by coupling a noble-metal-free multicomponent alloy with GaN NWs, paving the way for advancements in sustainable energy conversion through CO2 utilization.

Validation of Designing a Photovoltaic Energy (PVE) System to Enhance Urban Life and Reduce Fossil Fuel Dependence in Tehran and Baghdad

Aim: This study aimed to design and validate a grid-connected photovoltaic (PV) system to assess its potential for reducing CO₂ emissions and enhancing urban sustainability in Tehran and Baghdad. Methods: The study employed a tilt angle of 30°/0° for both sites. A total of 3,654 photovoltaic modules were installed, covering an area of 9,990 m², with 57 inverters integrated into the system. The total system power capacity was 2,138 kW, incorporating components for storage and self-consumption. Results: The results demonstrated a significant reduction in CO₂ emissions over a 15-year system lifetime—amounting to 41,168.7 tons in Iraq and 25,814.1 tons in Iran. In terms of generated emissions, Iraq recorded 1,169.78 tons of CO₂, while the grid lifecycle emissions were 869 tons in Iraq and 575 tons in Iran. The annual system production was 1,833.9 MWh in Iraq and 1,663.5 MWh in Iran. These findings highlight the system's strong potential in mitigating carbon dioxide emissions and offering a sustainable energy solution for urban environments with high pollution levels. Conclusion: This work serves as a foundational contribution to the broader understanding of how oil and gas exporting countries can harness photovoltaic technologies to address escalating energy demands. This is particularly in densely populated urban areas while simultaneously avoiding environmental crises, such as those currently experienced in Tehran. Recommendations: There should be development and implementation of strategic approaches for integrating connected photovoltaic systems play a critical role in strengthening energy security. Addressing emerging challenges, and establishing effective pathways to reduce and prevent environmental degradation in the future.

Techno-economic analysis for the integration of ex situ CO2 mineralization and mineral mining

PurposeThe paper reports a techno-economic analysis (TEA) of ex situ carbon dioxide (CO2) mineralization integrated with a refining process for the recovery of valuable materials such as carbonates for construction and critical minerals for renewable energy systems.MethodsThe TEA compares the costs of two proposed processes for CO2 mineralization and material recovery. One process uses silicate rocks and the other considers deep-subsurface brines. The TEA model takes input on feed quality and process engineering parameters to produce economic outputs including capital and operating expenses as well as revenues from carbonates and metal sales. The results are combined with a harmonized life cycle assessment (LCA) to evaluate the net carbon balance, ultimately yielding a net cost for CO2 storage.ResultsThe results show that recovering high-purity products suitable for the market requires a series of refining units for both feedstocks. While rock-based processes can produce 4–5 times more critical elements annually compared to brine-based processes, the additional revenue does not offset the increased capital costs associated with the pre-processing of the ultramafic rocks.ConclusionIn conclusion, an integrated process of CO2 mineralization and material recovery utilizing deep-subsurface brine proves more cost-effective than one relying on ultramafic rocks, primarily due to the elimination of upstream grinding and extraction units. This approach also opens opportunities for integration with geothermal energy conversion, which is currently the primary operation producing deep-subsurface brines.

CO2 emission changes in two Italian regions: progress toward 2050 climate neutrality under the Covenant of Mayors

In 2008, the European Commission established the Covenant of Mayors (CoM), a voluntary initiative to involve and support local authorities in pursuing the European Union's climate change mitigation and adaptation goals. This study proposes a methodology to evaluate the effectiveness of Sustainable Energy Action Plans (SEAPs) and Sustainable Energy and Climate Action Plans (SECAPs) in terms of reducing carbon dioxide emissions in the regions of Apulia and Sicily. The CO2 emissions are analyzed at the provincial level, before and after the approval of the plans by the municipal council, using homogeneous consumption data from national sources, rather than from data declared by the CoM signatories themselves. The methodology adopted combines the analysis of variance and compound annual growth rate (CAGR) of emissions, both total and per capita, with an assessment of the level of involvement of municipalities and the population in CoM plans. Through Pearson's coefficient, the correlation between the spread of plans and emissions at the provincial level was also assessed. The main results show that Apulia and Sicily, with a share of approved plans of 45.5% and 87.7%, respectively, experienced a reduction in total emissions of 12.1% and 21.2%, and per capita of 9.3% and 18.7%, in the period after municipalities submitted their SEAPs or SECAPs. A greater effectiveness of the plans is denoted in Sicilian provinces than in Apulian ones. These findings underscore the importance of emissions monitoring by signatory local governments, particularly through a uniform methodology, as well as monitoring at the provincial and regional levels, implemented by the Covenant Territorial Coordinators (CTCs), to assess the implementation of the action plans and ensure that regional and national emission reduction targets are met.

Characterization of Multi-Pass Enhanced Raman Spectroscopy for Gaseous Measurement

With the rise in global temperatures, it is of great significance to achieve rapid and accurate detection of greenhouse gases, such as carbon dioxide and methane. Raman spectroscopy not only overcomes the weakness of absorption spectroscopy in simultaneously measuring homonuclear diatomic molecules but also enables the simultaneous detection of multiple gases using a single-wavelength laser. However, due to the small Raman scattering cross-section and weak intensity of molecules, its application in gas detection is limited. To enhance the intensity of Raman scattering, this paper designs and constructs a multi-pass enhanced Raman spectroscopy setup. This study focuses on the effects of Raman scattering collection geometry, laser multi-pass patterns, and laser polarization relative to the Raman collection direction on signal intensity. Investigations into Raman scattering collection angles of 30°, 60°, and 90° reveal that the Raman scattering signal intensity increases as the collection angle decreases. Different laser multi-pass patterns also impact the signal, with the near-concentric linear multi-pass pattern found to collect more signals. To minimize the influence of excitation light on the signal, a side collection system is employed. Experiments show that the Raman scattering signal is stronger when the laser polarization is perpendicular to the collection direction. This study achieves overall system performance enhancement through coordinated optimization of multiple physical mechanisms, including Raman scattering collection geometry, laser multi-pass patterns, and laser polarization characteristics. The optimized setup was employed to characterize the laser power dependence for nitrogen, oxygen, and carbon dioxide detection. The results showed that the Raman scattering intensity varied linearly with the laser power of the gases, with linear fitting goodness R2 values of 0.9902, 0.9848, and 0.9969, respectively. Finally, by configuring different concentrations of carbon dioxide gas using nitrogen, it was found that the Raman scattering intensity varied linearly with the concentration of carbon dioxide, with a linear fitting goodness R2 of 0.9812. The system achieves a CO2 detection limit of 500 ppm at 200 s integration time, meeting the requirements for greenhouse gas emission monitoring applications.

Quantification of SO2 and CO2 emission rates from coal-fired power plants in the Korean peninsula via airborne measurements.

Quantification of SO2 and CO2 emission rates from coal-fired power plants in the Korean peninsula via airborne measurements.