Fraction Of Carbon Dioxide Research Articles

COCCON Measurements of XCO2, XCH4 and XCO over Coal Mine Aggregation Areas in Shanxi, China, and Comparison to TROPOMI and CAMS Datasets

This study presents the first column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4) and carbon monoxide (XCO) in the coal mine aggregation area in Shanxi, China, using two portable Fourier transform infrared spectrometers (EM27/SUNs), in the framework of the Collaborative Carbon Column Observing Network (COCCON). The measurements, collected over two months, were analyzed. Significant daily variations were observed, particularly in XCH4, which highlight the impact of coal mining emissions as a major CH4 source in the region. This study also compares COCCON XCO with measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5P satellite, revealing good agreement, with a mean bias of 7.15 ± 9.49 ppb. Additionally, comparisons were made between COCCON XCO2 and XCH4 data and analytical data from the Copernicus Atmosphere Monitoring Service (CAMS). The mean biases between COCCON and CAMS were −6.43 ± 1.75 ppm for XCO2 and 15.40 ± 31.60 ppb for XCH4. The findings affirm the stability and accuracy of the COCCON instruments for validating satellite observations and detecting local greenhouse gas sources. Operating COCCON spectrometers in coal mining areas offers valuable insights into emissions from these high-impact sources.

CH4 and CO emission estimates for megacities: deriving enhancement ratios of CO2, CH4, and CO from GOSAT-2 observations

Abstract Enhancement ratios among trace gases co-emitted by combustion of fossil fuels vary with emission sources and their combustion efficiency. We used column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4), and carbon monoxide (XCO) from the Greenhouse gases Observing SATellite-2 (GOSAT-2), a unique satellite that observes them simultaneously with the same field of view, to derive the enhancement ratios (ΔXCO/ΔXCO2, ΔXCO/ΔXCH4, and ΔXCH4/ΔXCO2) for the 40 most populous cities in the world. These enhancement ratios were used to evaluate the Emissions Database for Global Atmospheric Research (EDGAR). For cities where the difference in the 2015 EDGAR CO emissions between the latest versions (v6.1 and v5.0) was 30% or less, the GOSAT-2 ΔXCO/ΔXCO2 ratios and EDGAR (v6.1/v7.0) CO/CO2 emission ratios were in good agreement (correlation coefficient of 0.65). For ~70% of the cities where the difference of CO emissions exceeded 30%, the EDGAR CO/CO2 emission ratios using v6.1 CO emissions were in better agreement with the GOSAT-2 ΔXCO/ΔXCO2 ratios than those using v5.0 CO emissions, indicating that v6.1 CO emissions were improved over v5.0 emissions. However, for the remaining cities, the version upgrade may have reduced the CO emissions too much. The CH4 and CO emissions for each city were then estimated from the ΔXCH4/ΔXCO2 and ΔXCO/ΔXCO2 ratios, respectively, by reference to the CO2 emissions from the Open-data Inventory for Anthropogenic CO2 (ODIAC) or EDGAR. Compared to our estimates using the ODIAC (EDGAR) CO2 emissions, the EDGAR v7.0 CH4 and v6.1 CO emissions were underestimated for 74% (57%) and 76% (53%), respectively, of all cities where results were available. For several cities where emissions were estimated using in situ observations and ground-based remote sensing observations, our results were in reasonable agreement with these results. The implication is that satellite-derived enhancement ratios can provide informative constraints on anthropogenic emissions in megacities.

Fundamental representation of the amount of substance fraction of carbon dioxide in nitrogen according to the dynamic volumetric principle

Abstract The new Austrian primary standard for the amount of substance fraction of carbon dioxide in nitrogen is presented. The primary standard is working according to the dynamic volumetric principle and is a fundamental representation of the measurement quantity. The direct traceability to the basic SI units is thereby thermodynamically realized without an artefact. A complete measurement uncertainty budget is calculated and verified with a bilateral inter-laboratory comparison.

TECHNOLOGICAL SOLUTION FOR COMBATING HYDROGEN SULFIDE AT THE FIELD

One of the urgent problems in the production of hydrogen sulfide-containing oils is the problem of increasing the efficiency of hydrogen sulfide removal. Optimization of costs associated with the production, transportation and preparation of oil is very important at the present time. In order to reduce the costs of oil preparation, the use of a differentiated approach to solving the problem of its purification from hydrogen sulfide at the Kashagan field depends on the volumes of oil preparation, the mass fraction of hydrogen sulfide in the oil, the presence of gas near the high-sulfur oil preparation unit (UPVSN) that does not contain hydrogen sulfide, the presence of a gas collection system and the possibility of transporting increased volumes of hydrogen sulfide-containing gas to the sulfur purification unit. Taking these factors into account, it is necessary to identify the maximum values ​​​​of the volume fractions of methane, ethane, nitrogen and carbon dioxide in the composition of the stripping gas, at which the mass of oil will be preserved, as well as the conditions under which it will be purified from hydrogen sulfide in the conditions of the Kashagan field. Studies have shown that with an increase in the oil heating temperature and a decrease in the pressure in the desorption column, the maximum total volume fraction of methane and nitrogen in the mixture in the composition of the stripping gas decreases. A decrease in the mass fraction of hydrogen sulfide in oil below 100 ppm and maintaining the mass yield of oil depending on the proportion of these components in the composition of the stripping gas is possible if the oil temperature and pressure in the column are optimized. An increase in the total volume fraction of methane and nitrogen in the composition of the stripping gas leads to a decrease in its required consumption to achieve a certain efficiency of oil purification from hydrogen sulfide at specified operating parameters of the column.

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

Abstract. This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH4) and carbon dioxide (CO2), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s−1 when the wind magnitude is less than 3.5 m s−1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH4 and CO2 occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH4 emissions in near real time.

Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements

Abstract. The increase in greenhouse gas concentrations, particularly CO2, has significant implications for global climate patterns and various aspects of human life. Spaceborne remote sensing satellites play a crucial role in high-resolution monitoring of atmospheric CO2. However, the next generation of greenhouse gas monitoring satellites is expected to face challenges, particularly in terms of computational efficiency in atmospheric CO2 retrieval and analysis. To address these challenges, this study focuses on improving the speed of retrieving the column-averaged dry-air mole fraction of carbon dioxide (XCO2) using spectral data from the Orbiting Carbon Observatory-2 (OCO-2) satellite while still maintaining retrieval accuracy. A novel approach based on neural network (NN) models is proposed to tackle the nonlinear inversion problems associated with XCO2 retrievals. The study employs a data-driven supervised learning method and explores two distinct training strategies. Firstly, training is conducted using experimental data obtained from the inversion of the operational optimization model, which is released as the OCO-2 satellite products. Secondly, training is performed using a simulated dataset generated by an accurate forward calculation model. The inversion performance and prediction performance of the machine learning model for XCO2 are compared, analyzed, and discussed for the observed region over east Asia. The results demonstrate that the model trained on simulated data accurately predicts XCO2 in the target area. Furthermore, when compared to OCO-2 satellite product data, the developed XCO2 retrieval model not only achieves rapid predictions (<1 ms) with good accuracy (1.8 ppm or approximately 0.45 %) but also effectively captures sudden increases in XCO2 plumes near industrial emission sources. The accuracy of the machine learning model retrieval results is validated against reliable data from Total Carbon Column Observing Network (TCCON) sites, demonstrating its ability to effectively capture CO2 seasonal variations and annual growth trends.

Enhancing Skin Flap Survival with Preoperative Carbon Dioxide Fractional Laser Treatment: A Novel Approach in Reconstructive Surgery

Background: Skin flap necrosis remains a significant challenge in reconstructive surgery, predominantly due to insufficient blood supply. Traditional methods like the surgical delay procedure, while effective, are invasive and associated with considerable patient discomfort and health care costs. This study explores the efficacy of Carbon Dioxide Fractional Laser (CDFL) treatment as a novel, less invasive alternative to enhance skin flap survival. Methods: Twenty-nine adult male Sprague-Dawley rats were divided into 2 groups: a CDFL treatment group (n=14) and a control group (n=15). The CDFL group received laser pretreatment 1 week before flap surgery, whereas the control group underwent flap surgery without pretreatment. Flap survival was assessed 7 days postsurgery using indocyanine green fluorescence angiography. In addition, histological analysis was conducted to evaluate tissue integrity, capillary density, and VEGF expression. Results: The CDFL-treated flaps showed significantly increased survival areas compared with controls (P<0.01). Histological evaluation revealed enhanced capillary dilation and increased VEGF expression in the CDFL group (P<0.05). Although capillary density was higher in the CDFL group, it did not reach statistical significance (P=0.052). Conclusion: CDFL pretreatment significantly improves skin flap survival in rats, suggesting potential as a minimally invasive alternative to traditional surgical delay techniques. This approach could offer substantial benefits in reconstructive surgery, reducing patient morbidity and associated costs. Further studies are warranted to confirm these findings in clinical settings.

Multiparameter Detection of Summer Open Fire Emissions: The Case Study of GAW Regional Observatory of Lamezia Terme (Southern Italy)

In Southern Mediterranean regions, the issue of summer fires related to agriculture practices is a periodic recurrence. It implies a significant increase in carbon dioxide (CO2) emissions and other combustion-related gaseous and particles compounds emitted into the atmosphere with potential impacts on air quality and global climate. In this work, we performed an analysis of summer fire events that occurred on August 2021. Measurements were carried out at the permanent World Meteorological Organization (WMO)/Global Atmosphere Watch (GAW) station of Lamezia Terme (Code: LMT) in Calabria, Southern Italy. The observatory is equipped with greenhouse gases and black carbon analyzers, an atmospheric particulate impactor system, and a meteo-station for atmospheric parameters to characterize atmospheric mechanisms and transport for land and sea breezes occurrences. High mole fractions of carbon monoxide (CO) and carbon dioxide (CO2) coming from quadrants of inland areas were correlated with fire counts detected via the MODIS satellite (GFED-Global Fire Emissions Database) at 1 km of spatial resolution. In comparison with the typical summer values, higher CO and CO2 were observed in August 2021. Furthermore, the growth in CO concentration values in the tropospheric column was also highlighted by the analyses of the L2 products of the Copernicus SP5 satellite. Wind fields were reconstructed via a Weather Research and Forecasting (WRF) output, the latter suggesting a possible contribution from open fire events observed at the inland region near the observatory. So far, there have been no documented estimates of the effect of prescribed burning on carbon emissions in this region. This study suggested that data collected at the LMT station can be useful in recognizing and consequently quantifying emission sources related to open fires.

Quantitative analysis of spatiotemporal coverage and uncertainty decomposition in OCO-2/3 XCO2 across China

The Orbiting Carbon Observatory 2/3 (OCO-2/3) employs a full-physics inversion algorithm and estimates the column-averaged dry air mole fraction of carbon dioxide (XCO2). This research focuses on the spatiotemporal coverage and associated uncertainties of OCO-2/3's XCO2 measurements within the Chinese region. We undertook an extensive statistical examination of the daily, weekly, 16-day, and monthly spatiotemporal coverage of XCO2 across China, employing data from both OCO-2 and OCO-3 and their amalgamated datasets. Additionally, we used a posterior error analysis method to rigorously evaluate the uncertainties induced by various input parameters in the XCO2 inversion model across different regions in China. Our findings reveal that OCO-2's spatial coverage spans 2.3–53.8% in China at a spatial resolution of 1° × 1°, and OCO-3's spatial coverage spans 3.3 and 47.4% across these time scales in China. Notably, the combined coverage rates of both satellites are significantly higher, ranging from 5.4 to 72.6%. Our analysis also reveals a gradual decrease in XCO2 coverage and inversion rates from north to south and west to east across China. A significant portion of the uncertainties in OCO-2/3 XCO2 measurements, over 90%, were attributed to primary error sources such as instrument, aerosol, and CO2 prior profile. Aerosol-induced errors show regional variations, with higher levels observed in Southeast China. Compared to TCCON data, the accuracy of XCO2 measurements in the two Chinese sites was lower than the global average. Our research identifies the spatiotemporal distribution and uncertainty decomposition of carbon satellites at a regional scale in China, providing an essential reference for future research.

Characterization of Aerosol and CO2 Co-Emissions around Power Plants through Satellite-Based Synergistic Observations

The tracking of carbon and aerosol co-emissions is essential for environmental management. Satellite-based atmospheric synoptic observation networks provide large-scale and multifaceted data to help resolve emission behaviors. This study employs a comprehensive analysis of atmospheric dynamics, combustion byproducts, and aerosol characteristics around power plants. Strong correlations between Aerosol Optical Depth (AOD) at 500 nm and the column-averaged dry-air mole fraction of carbon dioxide (XCO2) were observed, revealing synchronous peaks in their emission patterns. The investigation into combustion completeness utilized metrics such as the ratio of carbon monoxide (CO)/XCO2 and Black Carbon Extinction (BCEXT)/Total Aerosol Extinction (TOTEXT). Discrepancies in these ratios across cases suggest variations in combustion efficiency and aerosol characteristics. Nitrogen dioxide (NO2) distributions closely mirrored XCO2, indicating consistent emission patterns, while variations in sulfur dioxide (SO2) distributions implied differences in sulfide content in the coal used. The influence of coal composition on AOD/XCO2 ratios was evident, with sulfide content contributing to variations besides combustion efficiency. This multifactorial analysis underscores the complex interplay of combustion completeness, aerosol composition, and coal components in shaping the air quality around power stations. The findings highlight the need for a nuanced understanding of these factors for effective air quality management.

Forest-floor respiration, N2O fluxes, and CH4 fluxes in a subalpine spruce forest: drivers and annual budgets

Abstract. Forest ecosystems play an important role in the global carbon (C) budget by sequestering a large fraction of anthropogenic carbon dioxide (CO2) emissions and by acting as important methane (CH4) sinks. The forest-floor greenhouse gas (GHG; CO2, CH4, and nitrous oxide (N2O)) flux, i.e., from soil and understory vegetation, is one of the major components to consider when determining the C or GHG budget of forests. Although winter fluxes are essential to determine the annual C budget, only very few studies have examined long-term, year-round forest-floor GHG fluxes. Thus, we aimed to (i) quantify seasonal and annual variations of forest-floor GHG fluxes; (ii) evaluate their drivers, including the effects of snow cover, timing, and amount of snowmelt; and (iii) calculate annual budgets of forest-floor GHG fluxes for a subalpine spruce forest in Switzerland. We measured GHG fluxes year-round during 4 years with four automatic large chambers at the ICOS Class 1 Ecosystem station Davos (CH-Dav). We applied random forest models to investigate environmental drivers and to gap-fill the flux time series. The forest floor emitted 2336 g CO2 m−2 yr−1 (average over 4 years). Annual and seasonal forest-floor respiration responded most strongly to soil temperature and snow depth. No response of forest-floor respiration to leaf area index or photosynthetic photon flux density was observed, suggesting a strong direct control of soil environmental factors and a weak, or even lacking, indirect control of canopy biology. Furthermore, the forest floor was a consistent CH4 sink (−0.71 g CH4 m−2 yr−1), with annual fluxes driven mainly by snow depth. Winter CO2 fluxes were less important for the CO2 budget (6.0 %–7.3 %), while winter CH4 fluxes contributed substantially to the annual CH4 budget (14.4 %–18.4 %). N2O fluxes were very low (0.007 g N2O m−2 yr−1), negligible for the forest-floor GHG budget at our site. In 2022, the warmest year on record with below-average precipitation at the Davos site, we observed a substantial increase in forest-floor respiration compared with other years. The mean forest-floor GHG budget indicated emissions of 2319 ± 200 g CO2 eq. m−2 yr−1 (mean ± standard deviation (SD) over all years), with respiration fluxes dominating and CH4 offsetting a very small proportion (0.8 %) of the CO2 emissions. Due to the relevance of snow cover, we recommend year-round measurements of GHG fluxes with high temporal resolution. In a future with increasing temperatures and less snow cover due to climate change, we expect increased forest-floor respiration at this subalpine site modulating the carbon sink of the forest ecosystem.

Spatio-temporal modeling of satellite-observed CO2 columns in China using deep learning

Satellite measurements of the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) play a crucial role in monitoring CO2 emissions and sinks. However, the current limitations of satellite observations, including sparse sampling, narrow swath coverage, and data gaps caused by factors like clouds, significantly hinder their ability to accurately capture local-scale CO2 sources and sinks. This study introduces an innovative data-driven approach based on deep learning, which takes into consideration both spatial and temporal variations, to map XCO2 using observations from multiple satellites. By leveraging advanced deep learning techniques like conventional neural network (CNN), long short-term memory network (LSTM), channel-spatial attention, and artificial neural network (ANN) in the model training, this approach not only incorporates spatiotemporal variations of XCO2 but also integrates information from related terrestrial, anthropogenic, and meteorological variables. The results demonstrate a notable improvement in the predictive capability of the approach. An important advancement over previous studies is that this approach breaks away from the conventional practice of using model-generated XCO2 simulations for both training and validation. Monthly deep-learning XCO2 (DL-XCO2) of China from 2014 to 2022 was generated with a spatial resolution of 0.25° based on satellite retrievals from GOSAT and OCO-2/3. Cross-validation results show an average prediction bias of −0.16 ppm. Additionally, DL-XCO2 exhibits high precision when compared to two TCCON stations, with errors of 0.93 and 1.29 ppm in Hefei and Xianghe, respectively. Ultimately, the DL-XCO2 data effectively capture urban CO2 variations, showcasing the potential in accurately characterizing fine-scale CO2 sources and sinks.

Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates

Abstract. The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).

The present and future contribution of ships to the underwater soundscape

Since the industrial revolution the ocean has become noisier. The global increase in shipping is one of the main contributors to this. In some regions, shipping contributed to an increase in ambient noise of several decibels, especially at low frequencies (10 to 100 Hz). Such an increase can have a substantial negative impact on fish, invertebrates, marine mammals and birds interfering with key life functions (e.g. foraging, mating, resting, etc.). Consequently, engineers are investigating ways to reduce the noise emitted by vessels when designing new ships. At the same time, since the industrial revolution (starting around 1760) greenhouse gas emissions have increased the atmospheric carbon dioxide fraction x(CO2) by more than 100 μmol mol-1. The ocean uptake of approximately one third of the emitted CO2 decreased the average global surface ocean pH from 8.21 to 8.10. This decrease is modifying sound propagation, especially sound absorption at the frequencies affected by shipping noise lower than 10 kHz, making the future ocean potentially noisier. There are also other climate change effects that may influence sound propagation. Sea surface warming might alter the depth of the deep sound speed channel, ice melting could locally decrease salinity and more frequent storms and higher wind speed alter the depth of the thermocline. In particular, modification of the sound speed profile can lead to the appearance of new ducts making specific depths noisier. In addition, ice melting and the increase in seawater temperature will open new shipping routes at the poles increasing anthropogenic noise in these regions. This review aims to discuss parameters that might change in the coming decades, focusing on the contribution of shipping, climate change and economic and technical developments to the future underwater soundscape in the ocean. Examples are given, contrasting the open ocean and the shallow seas. Apart from the changes in sound propagation, this review will also discuss the effects of water quality on ship-radiated noise with a focus on propeller cavitation noise.

Explosion characteristics of hydrogen-nitrous oxide mixtures with carbon dioxide addition

In this work, the explosion of hydrogen/nitrous oxide/carbon dioxide mixtures with various equivalence ratios (0.6–1.0), initial pressures (40–100 kPa), and carbon dioxide fractions (20%–40 %) at ambient temperature (298 K) was conducted inside a normative 15.625-L cubic container. The maximum explosion pressure and pressure rise speed were obtained and analyzed. The results show that carbon dioxide plays a crucial role in weakening H2/N2O explosion intensity, flame instabilities, as well as the tendency of deflagration to detonation. In addition, the addition of carbon dioxide has affected the two competitive effects between adiabatic temperature and molecular number. The variations of maximum explosion pressure and pressure rise speed with equivalence ratios depend on the carbon dioxide fraction. Only a linear dependence was found between maximum pressure rise speed and original pressure. These results would be useful in developing explosion-proof devices in the event of potential fire and explosion hazards.

Exploring CO2 anomalies in Brazilian biomes combining OCO-2 & 3 data: Linkages to wildfires patterns

Climate change is a challenge to the global community and one of the causes is the increase of greenhouse gases (GHG) in the atmosphere, especially carbon dioxide (CO2). The major emission source of this gas into the atmosphere comes from the burning of fossil fuels and biomass burning, on the other hand, the main sink comes from biochemical processes such as photosynthesis. Thus, the observation of CO2 is a key point to understanding sources and sinks. In this context, The Orbiting Carbon Observatory 2 (OCO-2) and 3 (OCO-3), are a NASA dedicated mission to monitor the column-averaged dry-air mole fraction of carbon dioxide (XCO2) on a global scale. We combined the OCO-2 and OCO-3 observations to study the spatial distribution of XCO2 anomalies and how some of these anomalies are related to fire occurrence in the Brazilian Biomes during 2020 and 2021 considering two different seasons, Dry and Wet. The fire occurrence was obtained from Fire Information for Resource Management System (FIRMS) that provides the data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) product of active fires and thermal anomalies at Near-Real Time (MCD14DL, collection 6). The OCO-2/3 observations are affected by cloud formations in wet seasons, we observe that the dry period has more observations. The XCO2 anomaly values range from ∼ 7.0 ppm to −7.0 ppm and mostly positive anomalies occur in Amazon Biome, and this ecosystem has higher average values for all periods (∼0.9 ppm), compared to the other biomes. The fire occurrence was higher in dry periods, especially in 2020 when unprecedented fire outbreaks were registered in Brazil. The most affected biomes were Pantanal, Cerrado, and Amazon. XCO2 positive anomalies spatially agree with fire foci over some areas, and the correlation values between them ranged from 0.2 to 0.5 depending on the biome and season, and when considering observations with clouds the correlation is slightly higher. We point out for the first time the possibility of using OCO-2 and 3 combined, also, how positive XCO2 anomalies are related to fire occurrence in different ecosystems and periods, and the role of cloud detection in this relationship.

Effect of Combined Oxygen Therapy and Use of a Surgical Mask or N95 Mask on Inspired Oxygen Fraction and Expired Carbon Dioxide Fraction.

Combined use of a surgical mask and oxygen mask might decrease the inspired oxygen concentration and increase the risk of hypercapnia. We investigated the fraction of inspired oxygen (FiO2) and end-tidal carbon dioxide (ETCO2) under different combinations of masks and oxygen flows. Five healthy volunteers were administered oxygen using the following methods: oxygen mask alone (O group), oxygen mask over a surgical mask (S group), and oxygen mask over an N95 mask (N group). FiO2 and ETCO2 were measured at oxygen flow rates of 0, 5, and 8L/min under each mask condition. At oxygen flow rates of 5 and 8L/min, FiO2 was lower in the order of N group (0.32 at 5L/min, 0.36 at 8L/min), S group (0.45 at 5L/min, 0.52 at 8L/min), and O group (0.61 at 5L/min, 0.73 at 8L/min). ETCO2 was higher in the order of N, S, and O groups. In conclusion, wearing the oxygen mask over the surgical mask or N95 mask reduces FiO2 and increases ETCO2 in healthy volunteers. Since patients who have emerged from general anaesthesia are more likely to have worse respiratory conditions, they need close observation to avoid hypoxemia and hypercapnia.

Assessment of the Emission Characteristics of Major States in the United States using Satellite Observations of CO2, CO, and NO2

By using space-based measurements of the column-averaged dry air mole fraction of carbon dioxide (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) and CO and NO2 from the Tropospheric Monitoring Instrument (TROPOMI), this study investigates the seasonal variation in the characteristics of CO2, CO, and NO2 across major states in the United States. Beyond correlating these trends with natural factors, significant emphasis is placed on human activities, including heating demands, energy usage, and the impacts of the COVID-19 pandemic. Concentration enhancements in observations influenced by anthropogenic emissions from urban regions relative to background values are calculated to estimate gas emissions. Our investigation reveals a strong correlation between NO2 and CO2 emissions, as evidenced by a correlation coefficient (r) of 0.75. Furthermore, we observe a correlation of 0.48 between CO2 and CO emissions and a weaker correlation of 0.37 between CO and NO2 emissions. Notably, we identify the NO2 concentration as a reliable indicator of CO2 emission levels, in which a 1% increase in NO2 concentration corresponds to a 0.8194% (±0.0942%) rise in annual mean CO2 emissions. Enhancement ratios among NO2, CO, and XCO2 are also calculated, uncovering that high ΔNO2: ΔXCO2 ratios often signify outdated industrial structures and production technologies, while low ΔCO: ΔXCO2 ratios are linked to states that utilize clean energy sources. This approach offers a deeper understanding of the effect of human activities on atmospheric gas concentrations, paving the way for more effective environmental monitoring and policy-making.

Decoding spatiotemporal dynamics in atmospheric CO2 in Chinese cities: Insights from satellite remote sensing and geographically and temporally weighted regression analysis

Understanding the primary factors influencing atmospheric carbon dioxide (CO2) dynamics is essential for addressing global climate change. However, these factors' spatial and temporal impact is seldom considered in the extant literature. This study employs a geographically and temporally weighted regression (GTWR) to examine the magnitude and direction of the effects that human activities, ecological conditions, and meteorological parameters exert on atmospheric CO2 variations. This examination encompasses 356 Chinese cities, utilizing satellite-derived column-averaged dry air mole fraction of carbon dioxide (XCO2) data from 2010 to 2019. Our findings reveal that cities in eastern China predominantly exhibit higher atmospheric CO2 concentrations, with most average values exceeding 399.34 ppm. Conversely, western regions generally maintain levels below 398.98 ppm. Trend analyses show a consistent increase over the decade, with a rate of 2.25–2.54 ppm/yr, coupled with pronounced seasonal variations. Anthropogenic emissions are found to amplify atmospheric CO2 concentrations during springs (overall-averaged GTWR coefficient of 0.72 ppm), autumns (0.51 ppm), and winters (0.87 ppm), especially in western cities. Vegetative activities can effectively reduce atmospheric CO2 during summers nationwide (temporally-averaged GTWR coefficients of −5.67 ~ −0.41 ppm) and autumn in southern cities (−1.32–0.00 ppm). From a meteorological perspective, increased summer relative humidity (overall-averaged coefficient of 2.41 ppm) and precipitation (1.57 ppm) can intensify atmospheric CO2 in most Chinese Cities. At the same time, warmer winter temperatures (−0.63 ppm) can mitigate it. Wind speed generally reduces atmospheric CO2 levels during spring (−1.02 ppm), autumn (−1.55 ppm), and winter (−1.76 ppm). Yet, it can heighten atmospheric CO2 concentrations during summers, particularly in eastern cities (0.07 ppm). The relationships between atmospheric CO2 concentrations and their influencing factors present significant spatial and seasonal variations. These findings offer comprehensive guidance for regions in developing targeted carbon emission control policies and enable a more practical approach to sustainable development.

Clinical Efficacy and Safety Analysis of 308nm Excimer Ultraviolet Light Combined with Carbon Dioxide Fractional Laser in the Treatment of Refractory Vitiligo

This paper aims to explore the clinical effect and safety of combined application of 308 nm excimer ultravioletlight and carbon dioxide fractional laser in the treatment of refractory vitiligo. The study was carried out from January 2020 to December 2022. 60 patients with refractory vitiligo were selected and divided into the study group (n = 30) and the control group (n = 30) through the lottery method of medical record envelopes. The patients in the control group were treated with 308 nm excimer ultraviolet light, and the patients in the study group were treated with 308 nm excimer ultraviolet light combined with carbon dioxide fractional laser treatment. The clinical effective rate, leukoplakia area, IgG level, and incidence of adverse reactions were compared between the two groups. The clinical effective rate of the study group was higher than that of the control group (P < 0.05). After treatment, the leukoplakia area of the study group was lower than that of the control group (P < 0.05), and the IgG level of the study group was lower than that of the control group (P < 0.05). The incidence of adverse reactions in the study group was lower than that in the control group (P < 0.05). The combined application of 308 nm excimer ultraviolet light and carbon dioxide fractional laser therapy for patients with refractory vitiligo has a significant effect, can reduce the area of leukoplakia and IgG levels, and has high treatment safety, which can be widely applied in clinical practice.