Atmospheric Carbon Monoxide Research Articles

Biogenic Amine Content and Shelf-Life of Salmon Fillets Packaged in Modified Atmospheres of Low-Level Carbon Monoxide and Different Carbon Dioxide Concentrations

Biogenic Amine Content and Shelf-Life of Salmon Fillets Packaged in Modified Atmospheres of Low-Level Carbon Monoxide and Different Carbon Dioxide Concentrations

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model

Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and contributes to the formation of secondary atmospheric pollutants, such as ozone (O3). This study aims to elucidate global CO pollution in relation to health risks and the influence of natural events like wildfires. Utilizing artificial intelligence (AI) big data techniques, we developed a high-performance Convolutional Neural Network (CNN)-based Residual Network (ResNet) model to estimate daily global CO concentrations at a high spatial resolution of 0.07° from June 2018 to May 2021. Our model integrated the global TROPOMI Total Column of atmospheric CO (TCCO) product and reanalysis datasets, achieving desirable estimation accuracies with R-values (correlation coefficients) of 0.90 and 0.96 for daily and monthly predictions, respectively. The analysis reveals that the CO concentrations were relatively high in northern and central China, as well as northern India, particularly during winter months. Given the significant role of wildfires in increasing surface CO levels, we examined their impact in the Indochina Peninsula, the Amazon Rain Forest, and Central Africa. Our results show increases of 60.0%, 28.7%, and 40.8% in CO concentrations for these regions during wildfire seasons, respectively. Additionally, we estimated short-term mortality cases related to CO exposure in 17 countries for 2019, with China having the highest mortality cases of 23,400 (95% confidence interval: 0–99,500). Our findings highlight the critical need for ongoing monitoring of CO levels and their health implications. The daily surface CO concentration dataset is publicly available and can support future relevant sustainable studies, which is accessible at https://doi.org/10.5281/zenodo.11806178.

Radiocarbon as a tracer of the fossil fraction of regional carbon monoxide emissions

Abstract Carbon monoxide (CO) is an atmospheric pollutant with a positive net warming effect on the climate. The magnitude of CO sources and the fraction of fossil vs biogenic sources are still uncertain and vary across emissions inventories. Measurements of radiocarbon (14C) in CO could potentially be used to investigate the sources of CO on a regional scale because fossil sources lack 14C and reduce the 14C/C ratio (Δ14C) of atmospheric CO more than biogenic sources. We use regional Lagrangian model simulations to investigate the utility of Δ14CO measurements for estimating the fossil fraction of CO emissions and evaluating bottom-up emissions estimates (United Kingdom Greenhouse Gas, UKGHG, and TNO Copernicus Atmosphere Monitoring Service, TNO) in London, UK. Due to the high Δ14CO in atmospheric CO from cosmogenic production, both fossil and biogenic CO emissions cause large reductions in Δ14CO regionally, with larger reductions for fossil than biogenic CO per ppb added. There is a strong seasonal variation in Δ14CO in background air and in the sensitivity of Δ14CO to fossil and biogenic emissions of CO. In the UK, the CO emissions estimate from TNO has a higher fraction from fossil fuels than UKGHG (72\% vs 67\%). This results in larger simulated decreases in Δ14C per ppb CO for TNO emissions. The simulated differences between UKGHG and TNO are likely to be easily detectable by current measurement precision, suggesting that Δ14CO measurements could be an effective tool to understand regional CO sources and assess bottom-up emissions estimates.

Statistical modeling of the effects of wind speed, air temperature and relative humidity on the concentration of carbon monoxide in the urban atmosphere

The high carbon monoxide content in the urban atmosphere is one of the most important indicators of poor air quality in megacities such as Moscow. This study is to evaluate the importance of wind speed, air temperature, and relative air humidity for predicting the concentrations of carbon monoxide for the day ahead using a simplified one-dimensional quasistationary statistical model. It is shown that the concentration of carbon monoxide in the Moscow atmosphere is determined by a combination of internal (previous days CO concentration) and external (meteorological conditions) factors. The variation of carbon monoxide concentration at one station differs from the variation at another station due to the differences in local conditions. Taking into account wind speed and air temperature increases the predictive value of the onedimensional quasi-stationary statistical model for most of the stations. In contrast to wind, relative air humidity decreases the predictive value of the model for most of the stations. This means that meteorological factors considered in this study could have different effects on predicting carbon monoxide concentration in the case of Moscow. The data from the Balchug weather station, located in the city center, offers a more accurate CO concentration forecast for most Moscow stations compared to the VDNKh weather station. For a more complete description of the influence of meteorological conditions on the predicted low concentration of gases, it is useful to take into account the model wind direction, surface air pressure, and the intensity of mixing in the urban boundary layer.

Planetary Waves Drive Horizontal Variations in Trace Species in the Venus Deep Atmosphere

Abstract The deep atmosphere of Venus remains mysterious because of the planet’s high, optically thick cloud decks. While phenomena such as the observed decadal fluctuations in sulfur dioxide abundance above the clouds could shed light on conditions below, poor understanding of vertical and horizontal transport limits such an approach. Nightside spectral windows permit observation of trace gas species in the lower atmosphere, but incomplete understanding of the circulation makes the distribution of these species challenging to interpret. We performed two simulations with the Venus Planetary Climate Model including an age of air calculation to investigate tracer transport (a) between the surface and the stagnant lower haze layer and (b) between the cloud deck and the observable upper atmosphere. We find a timescale on the order of many decades for surface-to-lower haze layer transport and ∼1.4 yr from the lowest cloud deck to 101 km. The extreme slowness of transport from the surface to the clouds makes it unlikely that compositional variability at the surface could affect the upper atmosphere sulfur dioxide abundance on observed timescales. Planetary-scale Rossby waves with a zonal wavenumber of 1 in both hemispheres are found to circumnavigate the planet in the deep atmosphere in 36 Earth days. These waves are associated with gyres that collect tracers and areas of upwelling that transport them to higher altitudes, leading to significantly younger air at polar latitudes in the altitude range of 25–45 km. The existence of chemically enhanced traveling Rossby gyres could explain the observed deep atmosphere carbon monoxide variability.

TROPOMI unravels transboundary transport pathways of atmospheric carbon monoxide in Tibetan Plateau

Numerous studies have reported in situ monitoring and source analysis in the Tibetan Plateau (TP), a region crucial for climate systems. However, a gap remains in understanding the comprehensive distribution of atmospheric pollutants in the TP and their transboundary pollution transport. Here, we analyzed the high-resolution satellite TROPOMI observations from 2018 to 2023 in Tibet and its surrounding areas. Our result reveals that, contrary to the results from in situ surface CO monitoring, Tibet exhibits a distinct seasonality in atmospheric carbon monoxide total column average mixing ratio (XCO), with higher levels in summer and lower levels in winter. This distinctive seasonal pattern may be related to the TP's ‘air pump’ effect and the Asia summer monsoon. Before 2022, the annual growth rate of XCO in Tibet was 1.63 %·year−1; however, it declined by 6.88 % in 2022. Source analysis and satellite observations suggest that CO from South Asia may enter Tibet either by crossing the Himalayas or through the Yarlung Zangbo Grand Canyon. We discovered that spring outbreaks of open biomass burning (OBB) in South and Southeast Asia led to an 11.57–27.98 % increase in XCO over Tibet. Favorable wind pattern and unique topography of the canyon promote the high concentrations CO transport to Tibet. Our greater concern is whether the TP will experience more severe transboundary pollution in the future.

Small Fires, Big Impact: Evaluating Fire Emission Estimates in Southern Africa Using New Satellite Imagery of Burned Area and Carbon Monoxide

AbstractVarious fire emission estimates for southern Africa during 2019, derived with multiple burned area data sets with resolutions ranging from 500 to 20 m, are evaluated using satellite carbon monoxide (CO) observations. Southern African emissions derived from burned area generated by 20 m Sentinel‐2 satellite imagery are up to 120% higher than other estimates because small fires are better detected with a higher‐resolution satellite instrument. A comprehensive comparison between simulated and observed atmospheric CO indicates that the Sentinel‐2 burned area data significantly improves emission estimates, with up to 15% reduction in CO concentration biases in comparison to emissions based on coarser resolution burned area data. We also found that the temporal lag between emissions and atmospheric CO concentrations during the peak fire month was related to atmospheric transport. These findings emphasize the importance of utilizing higher‐resolution satellite instruments in accurately estimating emissions and understanding the impact of small fires on global climate.

Recent decline in carbon monoxide levels observed at an urban site in Ahmedabad, India.

Carbon monoxide (CO) is a prominent air pollutant in cities, with far-reaching implications for both local air quality and global atmospheric chemistry. The long-term change in atmospheric CO levels at a specific location is influenced by a complex interplay of local emissions, atmospheric transport, and photochemical processes, making it a subject of considerable interest. This study presents an 8-year analysis (2014-2021) of in situ CO observations using a cutting-edge laser-based analyzer at an urban site in Ahmedabad, western India. The long-term observations reveal a subtle trend in CO levels, masked by contrasting year-to-year variations, particular after 2018, across distinct diurnal time windows. Mid-afternoon (12:00-16:00h) CO levels, reflecting background and regional conditions, remained relatively stable over the study period. In contrast, evening (18:00-21:00h) CO levels, influenced by local emissions, exhibited substantial inter-annual variability without discernible trends from 2014 to 2018. However, post-2018, evening CO levels showed a consistent decline, predating COVID-19 lockdown measures. This decline coincided with the nationwide adoption of Bharat stage IV emission standards and other measures aimed at reducing vehicular emissions. The COVID-19 lockdown in 2020 further resulted in a noteworthy 29% reduction in evening CO levels compared to the pre-lockdown (2014-2019) period, highlighting the potential for substantial CO reduction through stringent vehicular emission controls. The observed long-term changes in CO levels do not align with the decreasing emission estimated by various inventories from 2014 to 2018, suggesting a need for improved emission statistics in Indian urban regions. This study underscores the importance of ongoing continuous CO measurements in urban areas to inform policy efforts aimed at controlling atmospheric pollutants.

Distributions, sea-to-air fluxes, and biological consumption of carbon monoxide in the Bohai and Yellow Seas during winter

Carbon monoxide (CO) concentrations in the atmosphere and ocean are mainly influenced by anthropogenic inputs, abiotic photoproduction, biogenic sources, and bacterial consumption. This study, for the first time, investigated the distributions, sea-to-air fluxes, and microbial consumption rates of CO in the Bohai Sea (BS) and the Yellow Sea (YS) in winter to identify the main factors controlling CO distributions in both the atmosphere and seawater in colder temperature. Atmospheric CO mixing ratios ([CO]atm) and the concentrations of CO in surface seawater ([CO]surf) ranged from 176.8 to 1245.8 ppbv (mean value: 551.4 ± 214 ppbv) and from 0.49 to 3.1 nmol L−1 (mean value: 0.98 ± 0.55 nmol L−1), respectively. In addition, the spatial distribution of [CO]atm and [CO]surf showed that anthropogenic sources dominated the distribution of [CO]atm, but abiotic photoproduction processes were the main influencers of the distribution of [CO]surf. The surface water at most sampling stations was supersaturated with CO, with a mean saturation factor of 1.9, and the sea-to-air fluxes of CO were estimated to range from −13.88 to 123.88 nmol m−2 h−1 (12.59 ± 21.32 nmol m−2 h−1), suggesting that the BS and the YS were the source of atmospheric CO, and were estimated to contribute 0.009% to 1.4% to the global ocean emission. Microbial consumption experiments indicated that the microbial CO consumption rate constants (Kbio) ranged from 0.15 to 2.14 h−1, and showed that CO concentrations decreased exponentially with incubation time, suggesting that anaerobic CO consumption would limit CO accumulation in winter, thereby affecting the flux of [CO]surf to [CO]atm.

Physiological basis for atmospheric methane oxidation and methanotrophic growth on air

Atmospheric methane oxidizing bacteria (atmMOB) constitute the sole biological sink for atmospheric methane. Still, the physiological basis allowing atmMOB to grow on air is not well understood. Here we assess the ability and strategies of seven methanotrophic species to grow with air as sole energy, carbon, and nitrogen source. Four species, including three outside the canonical atmMOB group USCα, enduringly oxidized atmospheric methane, carbon monoxide, and hydrogen during 12 months of growth on air. These four species exhibited distinct substrate preferences implying the existence of multiple metabolic strategies to grow on air. The estimated energy yields of the atmMOB were substantially lower than previously assumed necessary for cellular maintenance in atmMOB and other aerobic microorganisms. Moreover, the atmMOB also covered their nitrogen requirements from air. During growth on air, the atmMOB decreased investments in biosynthesis while increasing investments in trace gas oxidation. Furthermore, we confirm that a high apparent specific affinity for methane is a key characteristic of atmMOB. Our work shows that atmMOB grow on the trace concentrations of methane, carbon monoxide, and hydrogen present in air and outlines the metabolic strategies that enable atmMOB to mitigate greenhouse gases.

Trace gas oxidation sustains energy needs of a thermophilic archaeon at suboptimal temperatures

Diverse aerobic bacteria use atmospheric hydrogen (H2) and carbon monoxide (CO) as energy sources to support growth and survival. Such trace gas oxidation is recognised as a globally significant process that serves as the main sink in the biogeochemical H2 cycle and sustains microbial biodiversity in oligotrophic ecosystems. However, it is unclear whether archaea can also use atmospheric H2. Here we show that a thermoacidophilic archaeon, Acidianus brierleyi (Thermoproteota), constitutively consumes H2 and CO to sub-atmospheric levels. Oxidation occurs across a wide range of temperatures (10 to 70 °C) and enhances ATP production during starvation-induced persistence under temperate conditions. The genome of A. brierleyi encodes a canonical CO dehydrogenase and four distinct [NiFe]-hydrogenases, which are differentially produced in response to electron donor and acceptor availability. Another archaeon, Metallosphaera sedula, can also oxidize atmospheric H2. Our results suggest that trace gas oxidation is a common trait of Sulfolobales archaea and may play a role in their survival and niche expansion, including during dispersal through temperate environments.

Influence of reduction parameters on, weight loss, crack propagation, iron whisker growth, and morphological characteristics of directly reduced iron produced by non-contact direct reduction process

Non-contact direct reduction (NDR) is an alternative technique in iron and steelmaking. Direct reduced iron production (DRI) uses it. To further harness the metallurgical and operational capabilities of the process for its suitability as an alternative feed in the blast furnace process, there is a need to study the effect of the reduction parameters on the weight loss, crack propagation level, gas porosity, iron whisker growth, and morphological characteristics of the DRI. Thus, this paper attempts to utilize the NDR process using commercially acquired goethite-hematite ore in a carbon-monoxide atmosphere from wood charcoal under specified isothermal conditions, with a reduction temperature range from 570, 800, and 1000 °C. The effect of reduction parameters on weight loss, crack propagation, iron whisker growth, and morphological properties of the DRI was investigated using standardized reduction reaction practices under a nitrogen gas atmosphere with a flow rate of 120 mL. Mineralogical and morphological analyses of the direct reduced iron (DRI) and charcoal were performed using XRF and SEM/ED analysis. Proximate and ultimate analyses of the reductant were performed to ascertain their physical and chemical properties. The results show that reduction parameters tremendously influence the weight loss, crack propagation, gas porosity level, and metallurgical quality of the DRI. The reduction degree and swelling extent of the DRI also increase with crack propagation and iron whisker growth. Thus, the overall reduction mechanism still follows the usual stepwise chronological reduction order (Fe2O3 → Fe3O4 → FeO → Fe) regardless of temperature, with ash layer control being the reaction rate control. The NDR technique shows no carbon deposition in the DRI metal matrix. It indicates that this approach can serve as a viable alternative for DRI production in the ironmaking process.

Retrieval of Ar, N2, O, and CO in the Martian Thermosphere Using Dayglow Limb Observations by EMM EMUS

AbstractThe Emirates Ultraviolet Spectrometer (EMUS) onboard the Emirates Mars Mission (EMM) Hope probe images Mars at wavelengths extending from approximately 100 to 170 nm. EMUS observations began in February 2021 and cover over a full Mars year. We report the first limb scan observations at Mars of ultraviolet emissions Ar I 106.6 nm, N I 120 nm, and carbon monoxide (CO) Fourth Positive Group (A − X) band system excited by electron impact on CO. We use EMUS limb scan observations to retrieve number density profiles of argon, molecular nitrogen, atomic oxygen, and CO in the upper atmosphere of Mars from 130 to 160 km. CO is a sensitive tracer of the thermal profile and winds in Mars' middle atmosphere and the chemistry that balances CO2 in the atmosphere of Mars. EMUS insertion orbit special observations demonstrate that far ultraviolet limb measurements of the Martian thermosphere can be spectroscopically analyzed with a robust retrieval algorithm to further quantify variations of CO composition in the Martian upper atmosphere.

Efficient Data-Driven Gap Filling of Satellite Image Time Series Using Deep Neural Networks with Partial Convolutions

Abstract The abundance of gaps in satellite image time series often complicates the application of deep learning models such as convolutional neural networks for spatiotemporal modeling. Based on previous work in computer vision on image inpainting, this paper shows how three-dimensional spatiotemporal partial convolutions can be used as layers in neural networks to fill gaps in satellite image time series. To evaluate the approach, we apply a U-Net-like model on incomplete image time series of quasi-global carbon monoxide observations from the Sentinel-5 Precursor (Sentinel-5P) satellite. Prediction errors were comparable to two considered statistical approaches while computation times for predictions were up to three orders of magnitude faster, making the approach applicable to process large amounts of satellite data. Partial convolutions can be added as layers to other types of neural networks, making it relatively easy to integrate with existing deep learning models. However, the approach does not provide prediction uncertainties and further research is needed to understand and improve model transferability. The implementation of spatiotemporal partial convolutions and the U-Net-like model is available as open-source software. Significance Statement Gaps in satellite-based measurements of atmospheric variables can make the application of complex analysis methods such as deep learning approaches difficult. The purpose of this study is to present and evaluate a purely data-driven method to fill incomplete satellite image time series. The application on atmospheric carbon monoxide data suggests that the method can achieve prediction errors comparable to other approaches with much lower computation times. Results highlight that the method is promising for larger datasets but also that care must be taken to avoid extrapolation. Future studies may integrate the approach into more complex deep learning models for understanding spatiotemporal dynamics from incomplete data.

Comparison of Gas Treatments of High Oxygen, Carbon Monoxide, and Nitric Oxide on Ground Beef Color in Modified Atmosphere Packaging.

The objective of this study was to evaluate the viability and performance of nitric oxide modified-atmosphere packaging (MAP) as a novel alternative to high oxygen and carbon monoxide MAP for ground beef. Packages of ground beef under high oxygen (HI-OX), carbon monoxide (CO), and nitric oxide (NO) atmospheres were evaluated for descriptive and instrumental color every 12 h during a 120 h display period. Surface myoglobin percentages, internal cooked color, thiobarbituric acid reactive substances (TBARS), and residual nitrite and nitrate were also evaluated. There were gas × time interactions for descriptive color, discoloration, a* values, b* values, deoxymyoglobin percentages, and metmyoglobin percentages (p < 0.05). There were also gas-type main effects for cooked color and TBARS (p < 0.05). Carbon monoxide maintained the most redness and least discoloration throughout the display period, while HI-OX started with a bright red color but rapidly browned (p < 0.05). Nitric oxide started as dark red to tannish-red but transitioned to a dull red (p < 0.05). However, NO had increased redness and a* values for internal cooked color (p < 0.05). Although CO outperformed NO packages, NO exhibited a unique color cycle warranting further research to optimize its use.

Spatiotemporal distribution of carbon monoxide dynamics and probabilistic health risk assessment: A comprehensive sensitivity analysis across India's state capitals

Carbon monoxide (CO) is a harmful trace gas produced from the incomplete combustion of fossil fuels. Carbon monoxide (CO) poses a substantial threat to human health. The objectives of this study were to investigate carbon monoxide (CO) annual and seasonal variations with meteorological factors, study the marginal effects of weather factors on CO, analyze the impact of independent variables (meteorological factors) importance on CO distribution, time series trend analysis (Mann-Kendall and Sen's slope, additive decomposition model, and linear trend model), study the spatial distribution of CO in the capital cities and non-carcinogenic health risk in India from 2019 to 2022. The study showed that CO concentrations varied, notably across different years (from 2019 to 2022), months, and seasons. The maximum annual CO (0.91 ± 0.17 mg/m3) concentration was recorded in 2019, while the lowest was (0.67 ± 0.12 mg/m3) in 2022. Seasonally, the winter season had the highest load of CO (ranging from 0.17 to 2.17 mg/m3) in the ambient atmosphere compared to the monsoon (0.08 to 1.38 mg/m3) and summer (0.10 to 1.50 mg/m3) seasons. The analysis of the importance of the independent variables (meteorological factors) on CO indicated that temperature had the most substantial impact on CO variation, followed by wind direction, relative humidity, and wind speed. The trend analysis using different models showed a declining trend in CO concentrations over the study period. The non-carcinogenic health risk HQ values were less than 1, suggesting no notable risk. The Monte Carlo simulation revealed that the 5th and 95th percentile range of HQ risk was 0.02 to 0.07 and the sensitivity analysis of non-carcinogenic risk at the state capital level was conducted, and revealed that Delhi was at a higher risk than Chandigarh, Patna, Gandhinagar, Bengaluru, Mumbai, and others, respectively. The results of this study on CO emissions will be beneficial in creating focused plans and policies to reduce CO pollution in seasonal influences and its effects on ambient air quality and public health in the capital cities of Indian states.

Prevalence of trace gas-oxidizing soil bacteria increases with radial distance from Polloquere hot spring within a high-elevation Andean cold desert.

High-elevation arid regions harbor microbial communities reliant on metabolic niches and flexibility to survive under biologically stressful conditions, including nutrient limitation that necessitates the utilization of atmospheric trace gases as electron donors. Geothermal springs present "oases" of microbial activity, diversity, and abundance by delivering water and substrates, including reduced gases. However, it is unknown whether these springs exhibit a gradient of effects, increasing their impact on trace gas-oxidizers in the surrounding soils. We assessed whether proximity to Polloquere, a high-altitude geothermal spring in an Andean salt flat, alters the diversity and metabolic structure of nearby soil bacterial populations compared to the surrounding cold desert. Recovered DNA and metagenomic analyses indicate that the spring represents an oasis for microbes in this challenging environment, supporting greater biomass with more diverse metabolic functions in proximal soils that declines sharply with radial distance from the spring. Despite the sharp decrease in biomass, potential rates of atmospheric hydrogen (H2) and carbon monoxide (CO) uptake increase away from the spring. Kinetic estimates suggest this activity is due to high-affinity trace gas consumption, likely as a survival strategy for energy/carbon acquisition. These results demonstrate that Polloquere regulates a gradient of diverse microbial communities and metabolisms, culminating in increased activity of trace gas-oxidizers as the influence of the spring yields to that of the regional salt flat environment. This suggests the spring holds local importance within the context of the broader salt flat and potentially represents a model ecosystem for other geothermal systems in high-altitude desert environments.

МЕТОДИКА ВИМІРЮВАНЬ ЯСКРАВІСНОЇ ТЕМПЕРАТУРИ АТМОСФЕРИ НА ЧАСТОТАХ БЛИЗЬКО 100 ГГЦ

Subject and Purpose. The improvement of the atmosphere brightness temperature measuring method at frequencies of about 100 GHz is considered. The possibilities of the atmospheric carbon monoxide (CO) remote sensing instrument, developed at Institute of Radio Astronomy of the National Academy of Sciences of Ukraine were analyzed. They show that the functional of this instrument can be significantly expanded. It can provide more operational information about the troposphere, useful for aeronomy and radio astronomy. The purpose of this work is to improve the atmosphere brightness temperature measuring method in relation to the existing instrument. We determine the possibility of the spectroradiometer broadband channel to measure the sky brightness temperature. Methods and Methodology. A detailed analysis of the existing installation for monitoring atmospheric CO was carried out and the measurement method was improved. It is shown that the broadband channel of this instrument, created as a service, can be used to measure atmosphere brightness temperature. Such measurement will allow creating a database of the zenith brightness temperature of the sky at frequencies of about 100 GHz. Results. It is possible to create the base data of the brightness temperature of the sky at frequencies about 100 GHz. In order to do this, it is necessary to make only some modifications of the instrument. The main thing is to make changes to the data capture file of the broadband channel and create a program to convert the data obtained from the instrument into brightness temperature values according to the specified formulas. All necessary formulas for presenting observational results in the form of brightness temperatures are given. Conclusions. It has been proven that there is a possibility to create the base date of the troposphere brightness temperature over Kharkiv (Ukraine) at the frequencies of the short-wave part of the mm range. The high stability of the radiometric part of the installation allows determining the brightness temperature of the sky with an accuracy that is sufficient for aeronomical, radioastronomical and radiophysical studies. On the basis of analytical calculations and experimental data, the necessary modifications for creating such a base data are defined.

Sub-50 nm patterning of alloy thin films via nanophase separation for hydrogen gas sensing

A novel patterning method achieves two-dimensional nano-patterning of metal nanofibers by depositing a platinum–cerium alloy film on a silicon wafer and inducing phase separation in an oxygen–carbon monoxide atmosphere.

Saltire: a model to measure dynamical masses for high-contrast binaries and exoplanets with high-resolution spectroscopy

ABSTRACT High-resolution cross-correlation methods are widely used to discover and to characterise atomic and molecular species in exoplanet atmospheres. The characteristic cross-correlation signal is typically represented as a function of the velocity of the system, and the semi-amplitude of the planet’s orbit. We present Saltire, a fast and simple model that accurately reproduces the shape of such cross-correlation signals, allowing a direct fit to the data by using a minimum set of parameters. We show how to use this model on the detection of atmospheric carbon monoxide in archival data of the hot Jupiter $\rm \tau$ Boötis b, and how Saltire can be used to estimate the semi-amplitude and rest velocity of high brightness ratio binaries. By including the shape of the signal, we demonstrate that our model allows to robustly derive the signal position up to 10 times more accurate, compared to conventional methods. Furthermore, we discuss the impact of correlated noise and demonstrate that Saltire is a robust tool for estimating systematic uncertainties on the signal position. Saltire opens a new door to analyse high signal-to-noise data to accurately study atmospheric dynamics and to measure precise dynamical masses for exoplanets and faint stellar companions. We show that the phase-resolved shape of the atmospheric cross-correlation signal can accurately be reproduced, allowing studies of phase-dependent signal changes and to disentangle them from noise and data aliases.