Mole Fraction Measurements Research Articles

Mathematical consideration of massive estimation of dissociation rate constant for genotype–phenotype linking molecules bound to targets through washing/selection and next-generation sequencing

As one of methods for in vitro selection, a flow reactor type washing/selection system seems to be effective, where a ligand library is composed of “genotype–phenotype linking molecules”. In this system, high affinity ligands are selected by their respective “residual ratio” given by exp(−koff×t), where koff is the dissociation rate constant and t is the washing time. In this paper, we mathematically considered the following possibility. When the washing/selection dynamics obeys the residual ratio exp(−koff×t) deterministically and mole fraction measurement for sampled sequences by next-generation sequencing (NGS) is performed ideally, the “relative value” of koff for each of high-ranking sequences can be estimated simultaneously. In addition to these, when the residual ratio for the whole ligand population is measured correctly, the “absolute value” for each sequence can be estimated. We deduced formulas to present the relative and absolute estimates, and mathematically analyzed the effect of fluctuations in the number of NGS reads on the estimates in details. These were confirmed by numerical simulations.

Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission

Abstract. Reducing methane (CH4) emissions from the oil and gas (O&G) sector is crucial for mitigating climate change in the near term. MethaneSAT is an upcoming satellite mission designed to monitor basin-wide O&G emissions globally, providing estimates of emission rates and helping identify the underlying processes leading to methane release in the atmosphere. MethaneSAT data will support advocacy and policy efforts by helping to track methane reduction commitments and targets set by countries and industries. Here, we introduce a CH4 retrieval algorithm for MethaneSAT based on the CO2 proxy method. We apply the algorithm to observations from the maiden campaign of MethaneAIR, an airborne precursor to the satellite that has similar instrument specifications. The campaign was conducted during winter 2019 and summer 2021 over three major US oil and gas basins. Analysis of MethaneAIR data shows that measurement precision is typically better than 2 % at a 20×20 m2 pixel resolution, exhibiting no strong dependence on geophysical variables, e.g., surface reflectance. We show that detector focus drifts over the course of each flight, likely due to thermal gradients that develop across the optical bench. The impacts of this drift on retrieved CH4 can mostly be mitigated by including a parameter that squeezes the laboratory-derived, tabulated instrument spectral response function (ISRF) in the spectral fit. Validation against coincident EM27/SUN retrievals shows that MethaneAIR values are generally within 1 % of the retrievals. MethaneAIR retrievals were also intercompared with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). We estimate that the mean bias between the instruments is 2.5 ppb, and the latitudinal gradients for the two data sets are in good agreement. We evaluate the accuracy of MethaneAIR estimates of point-source emissions using observations recorded over the Permian Basin, an O&G basin, based on the integrated-mass-enhancement approach coupled with a plume-masking algorithm that uses total variational denoising. We estimate that the median point-source detection threshold is 100–150 kg h−1 at the aircraft's nominal above-surface observation altitude of 12 km. This estimate is based on an ensemble of Weather Research and Forecasting (WRF) large-eddy simulations used to mimic the campaign's conditions, with the threshold for quantification set at approximately twice the detection threshold. Retrievals from repeated basin surveys indicate the presence of both persistent and intermittent sources, and we highlight an example from each case. For the persistent source, we infer emissions from a large O&G processing facility and estimate a leak rate between 1.6 % and 2.1 %, higher than any previously reported emission levels from a facility of its size. We also identify a ruptured pipeline that could increase total basin emissions by 2 % if left unrepaired; this pipeline was discovered 2 weeks before it was found by its operator, highlighting the importance of regular monitoring by future satellite missions. The results showcase MethaneAIR's capability to make highly accurate, precise measurements of methane dry-air mole fractions in the atmosphere, with a fine spatial resolution (∼ 20×20 m2) mapped over large swaths (∼ 100×100 km2) in a single flight. The results provide confidence that MethaneSAT can make such measurements at unprecedentedly fine scales from space (∼ 130×400 m2 pixel size over a target area measuring ∼ 200×200 km2), thereby delivering quantitative data on basin-wide methane emissions.

Estimation of Urban Greenhouse Gas Fluxes from Mole Fraction Measurements Using Monin–Obukhov Similarity Theory

Abstract The purpose of this study is to determine whether urban greenhouse gas (GHG) fluxes can be quantified from tower-based mole fraction measurements using Monin–Obukhov similarity theory (MOST). Tower-based GHG mole fraction networks are used in many cities to quantify whole-city GHG emissions. Local-scale, micrometeorological flux estimates would complement whole-city estimates from atmospheric inversions. CO2 mole fraction and eddy-covariance flux data at an urban site in Indianapolis, Indiana, from October 2020 through January 2022 are analyzed. Using MOST flux–variance and flux–gradient relationships, CO2 fluxes were calculated using these mole fraction data and compared to the eddy-covariance fluxes. MOST-based fluxes were calculated using varying measurement heights and methods of estimating stability. The MOST flux–variance relationship method showed good temporal correlation with eddy-covariance fluxes at this site but overestimated flux magnitudes. Fluxes calculated using flux–gradient relationships showed lower temporal correlation with eddy-covariance fluxes but closer magnitudes to eddy-covariance fluxes. Measurement heights closer to ground level produce more precise flux estimates for both MOST-based methods. For flux–gradient methods, flux estimates are more accurate and precise when low-altitude measurements are combined with a large vertical separation between measurement heights. When stability estimates based on eddy-covariance flux measurements are replaced with stability estimates based on the weather station or net radiation data, the MOST-based fluxes still capture the temporal patterns measured via eddy covariance. Based on these results, MOST can be used to estimate the temporal patterns in local GHG fluxes at mole fraction tower sites, complementing the small number of eddy-covariance flux measurements available in urban settings.

Probing the Reaction of Propargyl Radical with Molecular Oxygen by Synchrotron VUV Photoionization Mass Spectrometry.

Self-reaction of propargyl (C3H3) radical is the main pathway to benzene, the formation of which is the rate-controlling step toward the formation of polycyclic aromatic hydrocarbons (PAHs) and soot. Oxidation of C3H3 is a promising strategy to inhibit the formation of hazardous PAHs and soot. In the present study, we studied the C3H3 + O2 reaction from 650 to 1100 K in a laminar flow reactor and identified the intermediates and products by synchrotron VUV photoionization mass spectrometry. 2-Propynal, ethenone, formaldehyde, CO, CO2, C2H2, C2H4, and C3O2 were identified. Among them, 2-propynal, ethenone, and formaldehyde provided direct evidence for the branching reaction of C3H3 + O2 → HCCCHO + OH, C3H3 + O2 → H2CCO + CHO, and C3H3 + O2 → H2CO + CHCO, respectively. Potential energy surface calculation and mechanistic analysis of the C3O2 formations implied that C3H3 + O2 → CCCHO + H2O and C3H3 + O2 → HCCCO + H2O could occur, despite lacking direct observations of CCCHO and HCCCO radicals. The formation of ethenone and CO suggested the occurrence of the two CO elimination channels. We incorporated these validated reactions and the corresponding rate coefficients in the kinetic model of NUIGMech1.3, and the simulation showed obvious improvements toward the measured mole fractions of C3H3 and H2CCO, suggesting that the new C3H3 + O2 reaction channels were crucial in the overall combustion modeling of the important intermediate propyne (C3H4).

New insights into the effect of molecular structure on stable intermediate formation during the pyrolysis of normal and branched alkanes – I: Multi-species time history measurements

Decarbonization of energy systems that drive the transportation industry is imperative for effectively mitigating global greenhouse gas emissions. In this pursuit, the transition towards scalable and sustainable fuels will play a key role. These fuels are predominantly composed of a diverse array of hydrocarbons spanning various molecular classes. To better understand the complex chemistry of such fuels, we studied the impact of molecular structure on the distribution of pyrolysis products of C6-C12 hydrocarbons, encompassing both normal and branched alkanes, in a shock tube at combustion-relevant temperatures. An extensive suite of laser absorption spectroscopy-based diagnostics was used to simultaneously measure the time histories of key intermediates (methane, ethylene, and larger alkenes) and fuel during the pyrolysis of ten neat hydrocarbons: n-hexane, n-heptane, n-octane, n-decane, n-dodecane, 2-methylhexane, 2-methylheptane, 2-methylnonane, triptane (or 2,2,3-trimethylbutane), and iso-octane (or 2,2,4-trimethylpentane). These experiments were conducted behind reflected shock waves using 2% Fuel/Argon test mixtures at a nominal pressure of 2 atm over the temperature range of 1100–1500 K. Conducting these experiments under similar test conditions facilitated the observation of clear trends in the distribution of intermediates formed during the pyrolysis of these fuels. The current paper delineates the experimental strategy and presents the measured mole fraction time histories of the stable intermediates. A companion paper [1] delves into the observed trends and effects of molecular structure, in particular, the impact of increasing carbon number and the impact of varying degree of branching on the yields of these pyrolysis products. We also investigate the impact of fuel blending and provide insights into the role of inter-coupling on the distribution of stable intermediates. The authors anticipate that the trends and findings presented in these two papers will guide the design of sustainable fuels and play a pivotal role in modeling the combustion chemistry of the next generation of fuels. To the best of our knowledge, this work presents the first systematic, detailed pyrolysis study of several transportation-relevant hydrocarbon fuels, involving simultaneous measurements of multiple species in a shock tube using laser absorption spectroscopy.

Underestimation of Thermogenic Methane Emissions in New York City.

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state, and national levels. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop appropriately focused emission reduction strategies. Top-down emission estimates based on atmospheric greenhouse gas measurements can help to improve inventories and inform policy decisions. This study presents a new high-resolution (0.02 × 0.02°) methane emission inventory for New York City and its surrounding area, constructed using the latest activity data, emission factors, and spatial proxies. The new high-resolution inventory estimates of methane emissions for the New York-Newark urban area are 1.3 times larger than those for the gridded Environmental Protection Agency inventory. We used aircraft mole fraction measurements from nine research flights to optimize the high-resolution inventory emissions within a Bayesian inversion. These sectorally optimized emissions show that the high-resolution inventory still significantly underestimates methane emissions within the New York-Newark urban area, primarily because it underestimates emissions from thermogenic sources (by a factor of 2.3). This suggests that there remains a gap in our process-based understanding of urban methane emissions.

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.

Detection and long-term quantification of methane emissions from an active landfill

Abstract. Landfills are a significant source of fugitive methane (CH4) emissions, which should be precisely and regularly monitored to reduce and mitigate net greenhouse gas emissions. In this study, we present long-term, in situ, near-surface, mobile atmospheric CH4 mole fraction measurements (complemented by meteorological measurements from a fixed station) from 21 campaigns that cover approximately 4 years from September 2016 to December 2020. These campaigns were utilized to regularly quantify the total CH4 emissions from an active landfill in France. We use a simple atmospheric inversion approach based on a Gaussian plume dispersion model to derive CH4 emissions. Together with the measurements near the soil surface, mainly dedicated to the identification of sources within the landfill, measurements of CH4 made on the landfill perimeter (near-field) helped us to identify the main emission areas and to provide some qualitative insights about the rank of their contributions to total emissions from the landfill. The two main area sources correspond, respectively, to a covered waste sector with infrastructure with sporadic leakages (such as wells, tanks, pipes, etc.) and to the last active sector receiving waste during most of the measurement campaigns. However, we hardly managed to extract a signal representative of the overall landfill emissions from the near-field measurements, which limited our ability to derive robust estimates of the emissions when assimilating them in the atmospheric inversions. The analysis shows that the inversions based on the measurements from a remote road further away from the landfill (far-field) yielded reliable estimates of the total emissions but provided less information on the spatial variability of emissions within the landfill. This demonstrates the complementarity between the near- and far-field measurements. According to these inversions, the total CH4 emissions have a large temporal variability and range from ∼ 0.4 to ∼ 7 t CH4 d−1, with an average value of ∼ 2.1 t CH4 d−1. We find a weak negative correlation between these estimates of the CH4 emissions and atmospheric pressure for the active landfill. However, this weak emission–pressure relationship is based on a relatively small sample of reliable emission estimates with large sampling gaps. More frequent robust estimations are required to better understand this relationship for an active landfill.

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.

A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10

Abstract. Measurements of column-averaged dry air mole fraction of CO2 (termed XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) contain systematic errors and regional-scale biases, often induced by forward model error or nonlinearity in the retrieval. Operationally, these biases are corrected for by a multiple linear regression model fit to co-retrieved variables that are highly correlated with XCO2 error. The operational bias correction is fit in tandem with a hand-tuned quality filter which limits error variance and reduces the regime of interaction between state variables and error to one that is largely linear. While the operational correction and filter are successful in reducing biases in retrievals, they do not allow for throughput or correction of data in which biases become nonlinear in predictors or features. In this paper, we demonstrate a clear improvement in the reduction in error variance over the operational correction by using a set of nonlinear machine learning models, one for land and one for ocean soundings. We further illustrate how the operational quality filter can be relaxed when used in conjunction with a nonlinear bias correction, which allows for an increase in sounding throughput by 14 % while maintaining the residual error in the operational correction. The method can readily be applied to future Atmospheric CO2 Observations from Space (ACOS) algorithm updates, to OCO-2's companion instrument OCO-3, and to other retrieved atmospheric state variables of interest.

Transient analysis of solar pyrolysis and hydrogen yield via interband cascade laser absorption spectroscopy of methane, acetylene, ethylene, and ethane

A mid-infrared laser absorption sensing method has been developed to measure species concentrations of four hydrocarbons and gas temperature over a range of temperatures in mixture compositions relevant to the pyrolytic decomposition of natural gas. The four measured species (methane, acetylene, ethylene, and ethane) are the most abundant hydrocarbons during the pyrolysis of natural gas, and provide a means to monitor decomposition progress and hydrogen yield through molar balance. In this work, time-division multiplexed signals of three distributed-feedback interband cascade lasers are used to make simultaneous measurements of select C-H stretch rovibrational transitions of the target hydrocarbons in the 3.00–3.34 μm range. The sensor was validated over a range of temperatures and pressures (300–1000 K, 0.03–1 atm) at relevant mixture compositions, with correction methods developed to mitigate cross-species interference. The sensor was demonstrated on a solar-thermal pyrolysis reactor, where time-resolved measurements of species mole fractions were performed across a range of insolation conditions to capture the transient response of the reactor.

Intercomparison of detection and quantification methods for methane emissions from the natural gas distribution network in Hamburg, Germany

Abstract. In August and September 2020, three different measurement methods for quantifying methane (CH4) emissions from leaks in urban gas distribution networks were applied and compared in Hamburg, Germany: the “mobile”, “tracer release”, and “suction” methods. The mobile and tracer release methods determine emission rates to the atmosphere from measurements of CH4 mole fractions in the ambient air, and the tracer release method also includes measurement of a gaseous tracer. The suction method determines emission rates by pumping air out of the ground using soil probes that are placed above the suspected leak location. The quantitative intercomparison of the emission rates from the three methods at a small number of locations is challenging because of limitations of the different methods at different types of leak locations. The mobile method was designed to rapidly quantify the average or total emission rate of many gas leaks in a city, but it yields a large emission rate uncertainty for individual leak locations. Emission rates determined for individual leak locations with the tracer release technique are more precise because the simultaneous measurement of the tracer released at a known rate at the emission source eliminates many of the uncertainties encountered with the mobile method. Nevertheless, care must be taken to properly collocate the tracer release and the leak emission points to avoid biases in emission rate estimates. The suction method could not be completed or applied at locations with widespread subsurface CH4 accumulation or due to safety measures. While the number of gas leak locations in this study is small, we observe a correlation between leak emission rate and subsurface accumulation. Wide accumulation places leaks into a safety category that requires immediate repair so that the suction method cannot be applied to these larger leaks in routine operation. This introduces a sampling bias for the suction method in this study towards the low-emission leaks, which do not require immediate repair measures. Given that this study is based on random sampling, such a sampling bias may also exist for the suction method outside of this study. While an investigation of the causal relationship between safety category and leak size is beyond the scope of this study, on average higher emission rates were observed from all three measurement-based quantification methods for leaks with higher safety priority compared to the leaks with lower safety concern. The leak locations where the suction method could not be applied were the biggest emitters, as confirmed by the emission rate quantifications using mobile and tracer methods and an engineering method based on the leak's diameter, pipeline overpressure, and depth at which the pipeline is buried. The corresponding sampling bias for the suction technique led to a low bias in derived emission rates in this study. It is important that future studies using the suction method account for any leaks not quantifiable with this method in order to avoid biases, especially when used to inform emission inventories.

Study of demixing in C–F plasma produced in a capillary discharge

The spatial distribution of chemical elements in plasma produced by a pulsed discharge in a capillary made of polytetrafluoroethylene has been studied by methods and means of optical spectroscopy. It has been found that the ratio of the molar fractions of fluorine and carbon differs significantly from that in the polymer wall and varies nonmonotonically along the radius of the plasma jet emerging from the capillary. The performed qualitative analysis of the intensity and direction of a number of competing diffusion fluxes involving C, C+, F, and F+ indicates both the possibility of the slowdown in the fluorine and carbon demixing, which start from the peripheral zone, and a change in the direction of some of these fluxes in the central zone of the discharge, which is reflected in the measured mole fraction profiles of these elements.

A retrieval of xCO2 from ground-based mid-infrared NDACC solar absorption spectra and comparison to TCCON

Abstract. Two global networks of ground-based Fourier transform spectrometers are measuring abundances of atmospheric trace gases that absorb in the near infrared and mid-infrared: the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON). The first lacks a CO2 product; therefore, this study focuses on developing an xCO2 retrieval method for NDACC from a spectral window in the 4800 cm−1 region. This retrieval will allow extending ground-based measurements back in time, which we will demonstrate with historical data available from Ny-Ålesund, Svalbard. At this site, both TCCON and NDACC measurements are routinely performed, which is an advantage for collocated comparisons. The results are compared with collocated TCCON measurements of column-averaged dry-air mole fractions of CO2 (denoted by xCO2) in Ny-Ålesund, Svalbard, and only TCCON in Burgos, Philippines. We found that it is possible to retrieve xCO2 from NDACC spectra with a precision of 0.2 %. The comparison between the new retrieval and TCCON showed that the sensitivity of the new retrieval is high in the troposphere and lower in the upper stratosphere, similar to TCCON, as seen in the averaging kernels, and that the seasonality is well captured as seen in the retrieved time series. Additionally, we have included a retrieval strategy suggestion to improve the quality of the xCO2 product.

A Mid-Infrared Laser Absorption Sensor for Gas Temperature and Carbon Monoxide Mole Fraction Measurements at 15 kHz in Engine-Out Gasoline Vehicle Exhaust

<div>Quantifying exhaust gas composition and temperature in vehicles with internal combustion engines (ICEs) is crucial to understanding and reducing emissions during transient engine operation. This is particularly important before the catalytic converter system lights off (i.e., during cold start). Most commercially available gas analyzers and temperature sensors are far too slow to measure these quantities on the timescale of individual cylinder-firing events, thus faster sensors are needed. A two-color mid-infrared (MIR) laser absorption spectroscopy (LAS) sensor for gas temperature and carbon monoxide (CO) mole fraction was developed and applied to address this technology gap. Two quantum cascade lasers (QCLs) were fiber coupled into one single-mode fiber to facilitate optical access in the test vehicle exhaust. The QCLs were time-multiplexed in order to scan across two CO absorption transitions near 2013 and 2060 cm<sup>–1</sup> at 15 kHz. This enabled in situ measurements of temperature and CO mole fraction to be acquired at 15 kHz in the engine-out exhaust of a research vehicle (modified production vehicle) with an 8-cylinder gasoline ICE. Three different vehicle tests were characterized with the LAS sensor as follows: (1) cold start with engine idle, (2) warm start with a drive cycle on a chassis dynamometer, and (3) hot start with a drive cycle on a chassis dynamometer. The measurements obtained from the LAS sensor had a time resolution that was three orders of magnitude faster than that of thermocouple and gas analyzer data acquired at the Ford vehicle emissions research laboratory (VERL) in Dearborn, Michigan. This enabled the LAS sensor to resolve high-speed engine dynamics and exhaust gas transients, which the conventional instrumentation could not, thereby providing valuable insight into the evolution of ICE emissions during transient engine operation.</div>

Cavity ring-down spectroscopy with a laser frequency stabilized and locked to a reference target gas absorption for drift-free accurate gas sensing measurements

A new gas sensor system with fast response and ultra-high sensitivity has been developed based on a combination of frequency modulation spectroscopy (FMS) and cavity ring-down spectroscopy (CRDS). The system consisted of two distributed feedback laser diodes (DFB-LDs) emitting at frequencies 6251.761 cm-1 (Laser-1) and 6257.762 cm-1 (Laser-2), respectively. A portion of Laser-1’s output was used by a frequency modulation spectroscopy technique to lock its frequency precisely at a CO2 absorption peak, while the rest of its output was coupled to an optical ring-down cavity, together with the Laser-2 output. The Laser-2 operated at a non-absorbing frequency for real-time correction of any baseline ring-down time drift caused by environmental changes (e.g., temperature, pressure). Laser frequency stabilization achieved a 5-fold improvement in CRDS detection sensitivity. This new system was able to make measurements at a data rate of 9 Hz. Based on Allan deviation analysis, the absorbance detection limit of the system was 4.4 × 10−11 cm-1 at an optimum averaging time of ∼5 s, whereas the time-normalized sensitivity at 1 s was 7.3 × 10−11 cm-1/Hz1/2. Measurements of atmospheric CO2 mole fraction were conducted and demonstrated its good performance and reliability. This sensor will be particularly suitable for making drift-free measurements over long periods, in the fields of environmental and industrial gas sensing.

Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season

Over the last decade we have witnessed a rapid, so far unexplained, increase in the emission of methane to the atmosphere and this increase could lead to an acceleration of the ongoing climate changes. The increase is likely to originate from agriculture, but oil and gas production as well as wetlands are also under suspicion. The best way to quantify the emission of methane and other greenhouse gasses to our atmosphere is by using space based remote sensing. Here, we analyse 3 years of measurements of the column-averaged dry-air mole fraction of methane from the Tropospheric Monitoring Instrument on Sentinel-5P obtained with two different retrieval methods in order to evaluate the dependency on geographic, land cover type and season. The land cover types were obtained from the Moderate Resolution Imaging Spectroradiometer aboard the Terra and Aqua satellites and from the World Cover data product using observations from the Copernicus Sentinel-1 and Sentinel-2 missions. The analysis reveals that while the highest methane concentrations are generally found over croplands, the lowest are generally found over shrublands, which is in agreement with expectations. It is more surprising that the analysis also reveals lower than average methane concentrations over wetlands as wetlands are generally thought to be a major source of methane emission. Until this discrepancy is resolved the methane concentration over wetlands from the Tropospheric Monitoring Instrument on Sentinel-5P should be handled with caution. It is also found that the annual methane cycle, as seen in the measured methane concentrations, for croplands, shrublands and savannas is delayed in Africa compared to Asia.

Trend and Multi‐Frequency Analysis Through Empirical Mode Decomposition: An Application to a 20‐Year Record of Atmospheric Carbonyl Sulfide Measurements

AbstractThe Empirical Mode Decomposition (EMD) is a fully non‐parametric analysis of frequency modes and trends in a given series that is based on the data alone. We have devised an improved strategy based on a series of best practices to use EMD successfully in the analysis of the monthly time series of carbonyl sulfide (OCS) atmospheric mole fractions measured at NOAA network stations (2000–2020). Long‐term trends and intra‐ and inter‐annual variability has been assessed. After a phase of generally increasing mole fractions up to 2015, with a temporary decline around 2009, we found that the OCS atmospheric mole fraction subsequently decreased at all stations, reflecting a recent imbalance in its total sources and losses. Our analysis has revealed a characteristic time scale for variation of 8–10 years. The variance associated with this long‐term behavior ranges from 15% to 40% of the total strength of the signal, depending on location. Apart from this complex long‐term behavior, the OCS time series show a strong annual cycle, which primarily results from the well‐known OCS uptake by vegetation. In addition, we have also found one more frequency of minor variance intensity in the measured mole fraction time‐history, which corresponds to periods in the range of 2–3 years. This inter‐annual variability of OCS may be linked to the Quasi‐Biennial Oscillation.

Cellular structures of laminar lean premixed H2/CH4/air polyhedral flames

Fundamental studies on the effects of differential diffusion of hydrogen (H2) on flame structure are motivated as the high diffusivity of H2 presents challenges for the modeling and optimization of combustion systems. Polyhedral Bunsen flames are examples of cellular flames mainly induced by the thermal-diffusive and hydrodynamic instabilities, which are characterized by periodic positively curved troughs and negatively curved cusps. Stationary laminar premixed fuel-lean H2/CH4/air polyhedral flames, with 50%, 68% and 79% H2 (by volume) and Lewis number (Le) less than unity, are investigated in this study. The internal scalar structures of cellular troughs and cusps in target flames are measured with a high-spatial-resolution 1D Raman/Rayleigh scattering system, combined with planar laser-induced fluorescence of hydroxyl radicals (OH-PLIF) and chemiluminescence imaging measurements to quantify the cell number and local flame curvature. The performance of the 1D Raman/Rayleigh imaging system is first assessed by comparing measurements of temperature and major species in a laminar premixed counterflow H2/CH4/air twin flame with a corresponding simulation. The results reveal significant combined effects of differential diffusion and curvature on flame structures with differences between trough and cusp regions in the measured mole fractions, equivalence ratio, temperature, and C/H-atom ratio. The positively curved troughs have significantly higher H2 mole fraction compared to the negatively curved cusps, due to the respective focusing/defocusing effect of curvature on highly diffusive H2. Consequently, the local equivalence ratio and temperature in trough regions are higher than those of cusps. With the increase of H2 content in the reactant mixture, the scalar differences between trough and cusp regions are enlarged due to the enhanced effects of curvature and differential diffusion. Near-vertical initial trajectories in H2 mole fraction, equivalence ratio, and C/H-atom ratio plotted against temperature showed that differential diffusion of H2 alters the species mole fractions in the cold reactants (≤ 350 K).

Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space?

Abstract. In this paper, we compare Orbiting Carbon Observatory 2 (OCO-2) measurements of column-averaged dry-air mole fractions (DMF) of CO2 (XCO2) and its urban–rural differences against ground-based remote sensing data measured by the Munich Urban Carbon Column network (MUCCnet). Since April 2020, OCO-2 has regularly conducted target observations in Munich, Germany. Its target-mode data provide high-resolution XCO2 within a 15 km × 20 km target field of view that is greatly suited for carbon emission studies from space in cities and agglomerated areas. OCO-2 detects urban XCO2 with a root mean square different (RMSD) of less than 1 ppm when compared to the MUCCnet reference site. OCO-2 target XCO2 is biased high against the ground-based measurements. The close proximity of MUCCnet's five fully automated remote sensing sites enables us to compare spaceborne and ground-based XCO2 in three urban areas of Munich separately (center, north, and west) by dividing the target field into three smaller comparison domains. Due to this more constrained collocation, we observe improved agreement between spaceborne and ground-based XCO2 in all three comparison domains. For the first time, XCO2 gradients within one OCO-2 target field of view are evaluated against ground-based measurements. We compare XCO2 gradients in the OCO-2 target observations to gradients captured by collocated MUCCnet sites. Generally, OCO-2 detects elevated XCO2 in the same regions as the ground-based monitoring network. More than 90 % of the observed spaceborne gradients have the same orientation as the XCO2 gradients measured by MUCCnet. During our study, urban–rural enhancements are found to be in the range of 0.1 to 1 ppm. The low urban–rural gradients of typically well below 1 ppm in Munich during our study allow us to test OCO-2's lower detection limits for intra-urban XCO2 gradients. Urban XCO2 gradients recorded by the OCO-2 instruments and MUCCnet are strongly correlated (R2=0.68) with each other and have an RMSD of 0.32 ppm. A case study, which includes a comparison of one OCO-2 target overpass to WRF-GHG modeled XCO2, reveals a similar distribution of enhanced CO2 column abundances in Munich. In this study, we address OCO-2's capability to detect small-scale spatial XCO2 differences within one target observation. Our results suggest OCO-2's potential to assess anthropogenic emissions from space.