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In this study, the trajectory mapping domain-filling technology, which can provide more reliable statistical estimates of long-lived gas concentrations in a broader geographical area based on limited station data, is used to map the CO2 concentration data of six ground observation stations to the entire Shanxi Province. The technology combines a dynamical model of the atmosphere with trace gas observations, combining forward and backward trajectories to greatly expand the information on long-lived CO2 gas concentrations over a trajectory path. The mapped results show good agreement with the observation results, which reveals the generalizability of the trajectory mapping domain-filling technology. The results show that the spatio-temporal distribution characteristics of CO2 concentration in the entire Shanxi region is significant: during the five years, the provincial average CO2 concentration exhibits an overall increasing trend. The CO2 concentration increases from the north to the south across the province. Influenced by the economic growth rate and COVID-19, there are differences in the annual variation characteristics of the CO2 concentration across the entire province, with the highest year-on-year growth in 2019 and a year-on-year decrease in 2020. The increasing rate of the CO2 concentration in the northern low-value areas is faster than that in the southern high-value areas. Overall, there is a decreasing trend in the CO2 concentration growth from the north to the south in the entire province. There are seasonal differences in the CO2 concentration distribution across the entire province. The CO2 concentration and amplitude are higher in autumn and winter than they are in spring and summer. This study can provide scientific support and methodological reference for the spatio-temporal distribution characteristics analysis of GHGs at the provincial–regional scale, as well as at the national and global scales. [ABSTRACT FROM AUTHOR]

In order to improve observations of the atmospheric boundary layer (ABL), the European Meteorological Network, EUMETNET, and the Aerosol, Clouds, and Trace Gases Research Infrastructure, ACTRIS, are currently working on building networks of microwave radiometers (MWRs). Elevation-scanning MWRs are well suited to obtain temperature profiles of the atmosphere, especially within the ABL. Understanding and assessing measurement uncertainties of state-of-the-art scanning MWRs is therefore crucial for accurate temperature profiling. In this paper, we discuss measurement uncertainties due to the instrument setup and originating from external sources, namely (1) horizontal inhomogeneities of the atmosphere, (2) pointing errors or a tilt of the instrument, (3) physical obstacles in the line of sight of the instrument, and (4) radio frequency interference (RFI). Horizontal inhomogeneities from observations at the Jülich Observatory for Cloud Evolution (JOYCE) are shown to have a small impact on retrieved temperature profiles (<|0.22K| in the 25th and 75th percentiles below 3000 m). Typical instrument tilts, that could be caused by uncertainties during the instrument setup, also have a very small impact on temperature profiles and are smaller than 0.1 K below 3000 m for up to 1 ∘ of tilt. Physical obstacles at ambient temperatures and in the line of sight and filling the complete beam of the MWR at the lowest elevation angle of 5.4 ∘ have to be at least 600 m away from the instrument in order to have an impact of less than 0.1 K on obtained temperature profiles. If the obstacle is 5 K warmer than its surroundings then the obstacle should be at least 2700 m away. Finally, we present an approach on how to detect RFI with an MWR with azimuth and elevation-scanning capabilities. In this study, we detect RFIs in a water vapor channel that does not influence temperature retrievals but would be relevant if the MWR were used to detect horizontal humidity inhomogeneities. [ABSTRACT FROM AUTHOR]

The Geostationary Environment Monitoring Spectrometer (GEMS) is the first geostationary earth orbit (GEO) environmental instrument, onboard the Geostationary Korea Multi-Purpose Satellite–2B (GEO-KOMPSAT-2B) launched on 19 February 2020, and is measuring reflected radiance from the earth's surface and atmosphere system in the range of 300–500 nm in the ultraviolet–visible (UV–Vis) region. The radiometric response of a satellite sensor that measures the UV–Vis wavelength region can depend on the polarization states of the incoming light. To reduce the sensitivity due to polarization, many current low earth orbit (LEO) satellites are equipped with a scrambler to depolarize the signals or a polarization measurement device (PMD) that simultaneously measures the polarization state of the atmosphere, then utilizes it for a polarization correction. However, a novel polarization correction algorithm is required since GEMS does not have a scrambler or a PMD. Therefore, this study aims to improve the radiometric accuracy of GEMS by developing a polarization correction algorithm optimized for GEMS that simultaneously considers the atmosphere's polarization state and the instrument's polarization sensitivity characteristics. The polarization factor and axis were derived by the preflight test on the ground as a function of wavelengths, showing a polarization sensitivity of more than 2 % at some specific wavelengths. The polarization states of the atmosphere are configured as a look-up table (LUT) using the Vector Linearized Discrete Ordinate Radiative-Transfer model (VLIDORT). Depending on the observation geometry and atmospheric conditions, the observed radiance spectrum can include a polarization error of 2 %. The performance of the proposed GEMS polarization algorithm was assessed using synthetic data, and the errors due to polarization were found to be larger in clear regions than in cloudy regions. After the polarization correction, polarization errors were reduced close to zero for almost all wavelengths, including the wavelength regions with high peaks and curvatures in the GEMS polarization factor, which sufficiently demonstrates the effectiveness of the proposed polarization correction algorithm. From the actual observation data after the launch of GEMS, the diurnal variation for the spatial distribution of polarization error was confirmed to be minimum at noon and maximum at sunrise/sunset. This can be used to improve the quality of GEMS measurements, the first geostationary environmental satellite, and then contribute to the retrieved accuracy of various Level-2 products, such as trace gases and aerosols in the atmosphere. [ABSTRACT FROM AUTHOR]

Dimethylsulfide (DMS) is a climatically active trace gas promoting cloud formation. The biochemical precursor of DMS, dimethylsulfoniopropionate (DMSP), is a phytoplankton metabolite and a source of reduced sulfur for many microbial species. Because of the complex interactions between their many producers and consumers, the dynamics of DMSP and DMS in the ocean are still poorly constrained. In this study we measure particulate DMSP, dissolved DMSP (DMSPd), and DMS concentrations in seven mesocosms where two consecutive phytoplankton blooms (first, pico‐ and nano‐algae; second, Emiliania huxleyi) were induced by nutrient addition, and we build a mechanistic numerical model to identify the sources and sinks that best account for the observations. The mesocosms were designed as replicates but differ from each other by their E. huxleyi virus abundance due to stochastic differences in initial conditions. The model shows that heterotrophic bacteria cannot be the only consumers of DMSPd. A fraction of dissolved DMSPd must be consumed by phytoplankton to avoid excessive DMSPd accumulation during the first bloom. The induced blooms increase DMS concentration by 220% on average, until an increase in the abundance of DMS‐consuming bacteria brings DMS concentration back to its pre‐bloom value, after 3 weeks of experiment. Therefore phytoplankton blooms can increase DMS emission to the atmosphere, but only during a transient regime of a few weeks. The model also shows that the DMS yield, production and emission are increased when the coccolithophore bloom is terminated by a viral infection, but decreased if the infection occurs several days before the bloom can reach its maximum. [ABSTRACT FROM AUTHOR]

Anthropogenic trace gases often exhibit interhemispheric gradients because of larger emissions in the Northern Hemisphere. Depending on a tracer's emission pattern and sink processes, trace gas observations can thus be used to investigate interhemispheric transport in the atmosphere. Vice versa, understanding interhemispheric transport is important for interpreting spatial tracer distributions and for inferring emissions. We combine several data sets from the upper troposphere (UT) to investigate the interhemispheric gradient of sulfur hexafluoride (SF6) covering latitudes from ∼ 80 ∘ N to ∼ 60 ∘ S: canister sampling based measurements from the IAGOS-CARIBIC infrastructure and data from the in-flight gas chromatography instruments GhOST (Gas chromatograph for Observational Studies using Tracers) and UCATS (Unmanned aircraft systems Chromatograph for Atmospheric Trace Species). The interhemispheric gradient of SF6 in the UT is found to be weaker than near the surface. Using the concept of a lag time removes the increasing trend from the time series. At the most southern latitudes, a lag time of over 1 year with respect to the northern mid-latitude surface is derived, and lag times decrease over the period 2006–2020 in the extra-tropics and the southern tropics. Observations are compared to results from the two-dimensional Advanced Global Atmospheric Gases Experiment (AGAGE) 12-box model. Based on Emissions Database for Global Atmospheric Research (EDGAR 7) emissions, fair agreement of lag times is obtained for the Northern Hemisphere, but southern hemispheric air appears too "old". This is consistent with earlier findings that transport from the northern extra-tropics into the tropics is too slow in many models. The influence of the emission scenario and the model transport scheme are evaluated in sensitivity runs. It is found that EDGAR 7 underestimates emissions of SF6 globally and in the Southern Hemisphere, whereas northern extra-tropical emissions seem overestimated. Faster southward transport from the northern extra-tropics would be needed in the model, but transport from the southern tropics into the southern extra-tropics appears too fast. [ABSTRACT FROM AUTHOR]

The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enables the calculation of daily globally averaged CH4 concentrations. To investigate changes in atmospheric methane, the background CH4 level (i.e. the CH4 concentration without seasonal and short-term variations) has to be determined. CH4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, and thus simple fitting methods do not produce reliable results. In this paper we present an approach based on fitting an ensemble of dynamic linear models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. This method is computationally fast and is not dependent on additional inputs, allowing for fast and continuous analysis of the most recent time series data. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data, which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres, we use zonal growth rates instead of AMIs, since they provide a higher temporal resolution. Clear differences can be observed between Northern Hemisphere and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from Copernicus Atmospheric Monitoring Service (CAMS) global-inversion-optimized (CAMS/INV) data, which use surface observations. In 2019 a reduction in growth rates can be observed for the Southern Hemisphere, while growth rates in the Northern Hemisphere stay stable or increase. During 2020 a strong increase in Southern Hemisphere growth rates can be observed, which is in accordance with recently reported increases in Southern Hemisphere wetland emissions. In 2022 the reduction in the global AMI can be attributed to decreased growth rates in the Northern Hemisphere, while growth rates in the Southern Hemisphere remain high. Investigations of fluxes from CAMS/INV data support these observations and suggest that the Northern Hemisphere decrease is mainly due to the decrease in anthropogenic fluxes, while in the Southern Hemisphere, wetland fluxes continued to rise. While the continued increase in Southern Hemisphere wetland fluxes agrees with existing studies about the causes of observed methane trends, the difference between Northern Hemisphere and Southern Hemisphere methane increases in 2022 has not been discussed before and calls for further research. [ABSTRACT FROM AUTHOR]

During the Asian monsoon season, greenhouse gases and pollution emitted near the ground are rapidly uplifted by convection up to an altitude of ∼ 13 km, with slower ascent and mixing with the stratospheric background above. Here, we address the robustness of the representation of these transport processes in different reanalysis data sets using ERA5, ERA-Interim and ERA5 1∘×1∘. This transport assessment includes the mean age of air from global three-dimensional simulations by the Lagrangian transport model CLaMS (Chemical Lagrangian Model of the Stratosphere), as well as different trajectory-based transport times and associated ascent rates compared with observation-based age of air and ascent rates of long-lived trace gases from airborne measurements during the Asian summer monsoon 2017 in Nepal. Our findings confirm that the ERA5 reanalysis yields a better representation of convection than ERA-Interim, resulting in different transport times and air mass origins at the Earth's surface. In the Asian monsoon region above 430 K, the mean age of air driven by ERA-Interim is too young, whereas the mean age of air from ERA5 1∘×1∘ is too old but somewhat closer to the observations. The mean effective ascent rates derived from ERA5 and ERA5 1∘×1∘ back trajectories are in good agreement with the observation-based mean ascent rates, unlike ERA-Interim, which is much faster above 430 K. Although a reliable CO2 reconstruction is a challenge for model simulations, we show that, up to 410 K, the CO2 reconstruction using ERA5 agrees best with high-resolution in situ aircraft CO2 measurements, indicating a better representation of Asian monsoon transport in the newest ECMWF reanalysis product, ERA5. [ABSTRACT FROM AUTHOR]

Trace gas measurement has a wide range of applications needed in industrial, medical, and environmental protection. With the evolution of time, the demand for real-time, sensitivity, and accuracy of gas detection has been increasingly heightened. Off-axis integrated cavity output spectroscopy (OA-ICOS) is an effective method for the high-sensitivity detection of trace gases. It uses an integrated cavity with two highly reflective mirrors to provide a long optical path, which guarantees its high sensitivity. However, as the reflectivity of the mirrors increases, the intensity of the output light decreases, and the signal-to-noise ratio decreases. This contradiction makes it difficult to achieve a long optical path and a high signal-to-noise ratio together. To combat this issue, this paper proposes a type of integrated cavity using a direct-injection method. This structure, under equivalent mirror conditions, can maintain an effective absorption optical path very close to the original off-axis integrated cavity while increasing the output light intensity hundreds of times. This enhancement increases the sensitivity of OA-ICOS. [ABSTRACT FROM AUTHOR]

Air pollution has emerged as a pressing concern in large urban areas, often stemming from sources like intensified traffic and industrial activities within city limits. Addressing this issue requires an understanding of air quality levels, leading to the adoption of low-cost, portable air quality monitoring systems. In our research, we conducted tests using a compact mobile air quality system, SNIFFER 4D (SN), comparing its performance against conventional air quality monitors utilizing standardized methods such as chemiluminescence and spectrometry. The equipment was stationed at the REXDAN research facility situated along one of Galati city's main roads. The primary objective of our study was to evaluate the reliability and suitability of the SN for detailed analysis of trace gases like NO2, O3, and PM10, by crossreferencing data with readings from standard instruments capable of measuring individual trace gases. Data collection spanned from August 17 to August 30, 2023. Our findings indicate that the SN system proved to be a stable and sophisticated tool for conducting high-resolution studies on local and regional air pollution, encompassing pollutants such as NO2, O3, and PM10. [ABSTRACT FROM AUTHOR]

In urban areas, there has been a recent rise in ground-level ozone. Given its toxicity to both humans and the environment, the investigation of ozone pollution demands attention and should not be overlooked. Therefore, we conducted a study on ozone concentration in three distinct locations within the city of Magurele, Romania. This investigation considered variations in both structure and location during the spring and summer seasons, specifically at a breathing level of 1.5 m above the ground. Our analysis aimed to explore the impact of different locations and meteorological variables on ozone levels. The three measurement points were strategically positioned in diverse settings: within the city, in a forest, and within an industrial area. For these measurements, we used a laser spectroscopy system to determine the system's sensitivity and selectivity and the influence of humidity in the detection of ozone in ambient air, which is a mixture of trace gases and water vapor. During the March–August campaign, the mean values in the three measuring points were 24.45 ± 16.44 ppb, 11.96 ± 3.80 ppb, and 95.01 ± 37.11 ppb. The peak concentrations of ozone were observed during the summer season. A diurnal analysis revealed that the atmospheric ozone levels were higher in the latter part of the day compared to the earlier part. These measurements suggest that the atmospheric temperature plays a significant role in tropospheric ozone production. Additionally, meteorological variables such as wind speed and direction were found to influence the ozone concentration. Remarkably, despite substantial traffic, the ozone levels remained consistently low throughout the entire period within the forested area. This observation may suggest the remarkable ability of trees to mitigate pollution levels. [ABSTRACT FROM AUTHOR]

Glyoxal (CHOCHO) is a trace gas in the atmosphere, often used as an indicator of biogenic emissions. It is frequently compared to formaldehyde concentrations, which serve as indicators of anthropogenic emissions, to gain insights into the characteristics of the environmental source. This study employed broadband cavity-enhanced absorption spectroscopy to detect gaseous CHOCHO, methylglyoxal, and NO2. Two different detection methods are compared. Spectrograph and CCD Detection: This approach involves coupling the system to a spectrograph with a charge-coupled device (CCD) detector. It achieved a 1 min 1-σ detection limit of 2.5 × 108 molecules/cm3, or 10 parts per trillion (ppt). Methylglyoxal and NO2 achieved 1 min 1-σ detection limits of 34 ppt and 22 ppt, respectively. Interferometer and PMT Detection: In this method, an interferometer is used in conjunction with a photomultiplier tube (PMT) detector. It resulted in a 2 min 1-σ detection limit of 1.5 × 1010 molecules/cm3, or 600 ppt. The NO2 2 min 1-σ detection limit was determined to be 900 ppt. Concentrations of methylglyoxal were difficult to determine using this method, as they appeared to be below the detection limit of the instrument. This study discusses the advantages and limitations of each of these detection methods. [ABSTRACT FROM AUTHOR]

NOMAD is a suite of spectrometers on the board of the ESA-Roscosmos Trace Gas Orbiter (TGO) spacecraft and is capable of investigating the Martian environment at very high spectral resolution in the ultraviolet–visible and infrared spectral ranges by means of three separate channels: UVIS (0.2–0.65 μm), LNO (2.2–3.8 μm), and SO (2.3–4.3 μm). Among all channels, LNO is the only one operating at infrared wavelengths in nadir-viewing geometry, providing information on the whole atmospheric column and on the surface. Unfortunately, the LNO data are characterized by an overall low level of signal-to-noise ratio (SNR), limiting their contribution to the scientific objectives of the TGO mission. In this study, we assess the possibility of enhancing LNO nadir data SNR by applying the Minimum Noise Fraction (MNF), a well-known algorithm based on the Principal Components technique that has the advantage of providing transform eigenvalues ordered with increasing noise. We set up a benchmark process on an ensemble of synthetic spectra in order to optimize the algorithm specifically for LNO datasets. We verify that this optimization is limited by the presence of spectral artifacts introduced by the MNF itself, and the maximum achievable SNR is dependent on the scientific purpose of the analysis. MNF application study cases are provided to LNO data subsets in the ranges 2.627–2.648 μm and 2.335–2.353 μm (spectral orders 168 and 189, respectively) covering absorption features of gaseous H2O and CO and CO2 ice, achieving a substantial enhancement in the quality of the observations, whose SNR increases up to a factor of 10. While such an enhancement is still not enough to enable the investigation of spectral features of faint trace gases (in any case featured in orders whose spectral calibration is not fully reliable, hence preventing the application of the MNF), interesting perspectives for improving retrieval of both atmospheric and surface features from LNO nadir data are implied. [ABSTRACT FROM AUTHOR]

In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm developed by SRON Netherlands Institute for Space Research is extended with a bi-directional reflection distribution function (BRDF) for snow surfaces. The capability of the extended algorithm is validated with both synthetic measurements and real satellite measurements from the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL), and a comparison has been made to retrievals with the baseline RemoTAP (without a snow kernel). For retrievals with real PARASOL observations, we use pixels over Aerosol Robotic Network (AERONET) stations for validation and we use the MODIS snow cover products to identify pixels over snow. We evaluate the retrieved aerosol optical thickness (AOT) at 550 nm (τ550) , single-scattering albedo (SSA) at 550 nm (ω550) and Ångström exponent (AE) for 440–870 nm (AE440-870). The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover >75 %. According to the real-data experiment, we find that the retrieval algorithm has difficulty in fitting the PARASOL 1020 nm band, where snow reflectance is significantly lower than that for the visible bands. When we perform a four-band retrieval (490, 565, 670, 865 nm) with the extended RemoTAP, we obtain a good retrieval result for τ550 , ω550 and AE440-870. Therefore, the four-band retrieval with the extended RemoTAP is recommended for aerosol retrieval over snow. [ABSTRACT FROM AUTHOR]

The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having collocated sun-photometric observations in the Aerosol Robotic Network (AERONET), a network exercise was held in order to derive profiles of the concentration and effective column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC (from Generalized Aerosol Retrieval from Radiometer and Lidar Combined data – GARRLiC – part of the Generalized Retrieval of Atmosphere and Surface Properties – GRASP) inversion algorithm. The objective of this network exercise was to explore the possibility of identifying the anthropogenic component and of monitoring its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases is far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to deriving a common methodology for applying GRASP/GARRLiC to a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low aerosol optical depth (AOD) like the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties. [ABSTRACT FROM AUTHOR]

We present an analysis of high-resolution far-UV archival spectra obtained with the Space Telescope Imaging Spectrograph on the Hubble Space Telescope of the star HD 75309, which probes high-velocity shocked gas in the Vela supernova remnant (SNR). We examine high-velocity features from intrinsically strong absorption lines of O i, Si ii, Si ii *, C ii, C ii *, and Si iii. We also detect high-velocity components in the N v doublet and compare these features to observations of high-velocity O vi absorption, available from archival Far Ultraviolet Spectroscopic Explorer data. Kinetic temperatures are derived from the observed fractional abundances of the various ions, while gas densities and thermal pressures are obtained from the relative populations in excited fine-structure levels of C ii and Si ii. Our results indicate that the highly ionized species at high velocity probe gas in a region immediately behind a shock driven into an interstellar cloud, while the lower-ionization species trace material further downstream in the cooling region of the postshock flow. Low-velocity N v and O vi absorption may trace gas in a conductive boundary layer between the unshocked portion of the cloud and the hot X-ray-emitting intercloud medium. Temporal variations in high-velocity Ca ii absorption features observed toward HD 75309 further confirm the highly inhomogeneous nature of the interstellar medium interacting with the Vela SNR. [ABSTRACT FROM AUTHOR]

Analysis of aircraft observations of atmospheric trace gases is key towards improving our understanding of fundamental chemical processes and quantifying anthropogenic emissions. A common approach for such analysis is use of chemical transport models to produce 4-D fields for comparison with these observations together with various inversion techniques to constrain the underlying fluxes and chemistry. Yet, time and monetary constraints of expensive computational jobs for chemical transport modelling can be a significant hindrance. Here, we show the advantages of using potential temperature as a dynamical coordinate to compare such simulations to aircraft observations of trace gases whose concentration fields are strongly influenced by synoptic-scale transport. We use global observations of ethane and propane from the Atmospheric Tomography (ATom) aircraft mission and simulate global mole fractions for these gases using GEOS-Chem High Performance v13.4.1. We show, using potential temperature as an analysis coordinate, that Bayesian estimates of the fluxes of these gases in the Northern Hemisphere are largely invariant (± 10 %) even as the simulation spatial resolution is increased 100-fold. Our approach can have broad applications for the modelling of trace gases in the extra-tropics, particularly those with lifetimes long compared to synoptic timescales. [ABSTRACT FROM AUTHOR]

Tropopause-overshooting convection in the midlatitudes provides a rapid transport pathway for air from the lower troposphere to reach the upper troposphere and lower stratosphere (UTLS), and can result in the formation of above-anvil cirrus plumes (AACPs) that significantly hydrate the stratosphere. Such UTLS composition changes alter the radiation budget and impact climate. Novel in situ observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign are used in this study to examine UTLS impacts from AACP-generating overshooting convection. Namely, a research flight on 31 May 2022 sampled active convection over the state of Oklahoma for more than three hours with the NASA ER-2 high-altitude research aircraft. An AACP was bisected during this flight, providing the first such extensive in situ sampling of this phenomenon. The convective observations reveal pronounced changes in air mass composition and stratospheric hydration up to altitudes of 2.3 km above the tropopause and concentrations more than double background levels. Unique dynamic and trace gas signatures were found within the AACP, including enhanced vertical mixing near the AACP edge and a positive correlation between water vapor and ozone. Moreover, the water vapor enhancement within the AACP was found to be limited to the saturation mixing ratio of the low temperature overshoot and AACP air. Comparison with all remaining DCOTSS flights demonstrates that the 31 May 2022 flight had some of the largest tropospheric tracer and water vapor perturbations in the stratosphere and within the AACP. [ABSTRACT FROM AUTHOR]

Dry reforming of methane (DRM) has attracted great interest for the production of syngas and/or hydrogen in a more environmentally friendly way. It is especially advantageous in this case to use biogas—as a mixture of methane, CO2, and traces of further gases—as a feedstock replacement for natural gas. Nevertheless, industrial implementation of DRM is currently limited because of its inherent process restrictions. The biggest challenge of dry reforming is the deposition of carbon on the catalyst, known as "coking." The focus of this theoretical study is to evaluate the feasibility of a biogas dry reforming process in a liquid metal (Sn) bubble column reactor. This technology has already been proven suitable for methane pyrolysis to obtain hydrogen, preventing issues related to reactor clogging or catalyst deactivation caused by carbon deposition. Results show that at high operating temperatures and atmospheric pressure, a product gas primarily composed of H2 and CO would be obtained. CO2 and water vapor may also be present in the final product depending on the operating conditions. The molten tin inside the reactor would, according to the presented theoretical considerations, not be affected by the formation of carbides and oxides. Additionally, the syngas composition (the H2 : CO ratio) could be adjusted by using different CH4 : CO2 feed ratios. [ABSTRACT FROM AUTHOR]

We present the most significant results of Russian scientists in the field of atmospheric ozone research for 2019–2022 and examine observations of tropospheric ozone, its distribution and variability on the territory of the Russian Federation, its relation with atmospheric parameters, modeling of formation processes, and its impact on public health. The state of stratospheric ozone over Russia, modeling of processes in the ozonosphere, and methods and instruments being developed are also analyzed. The review is a part of Russia's national report on meteorology and atmospheric sciences, which was prepared for the International Association of Meteorology and Atmospheric Sciences (IAMAS). It has been reviewed and approved at the 28th General Assembly of the International Union of Geodesy and Geophysics (IUGG). [ABSTRACT FROM AUTHOR]

A review of studies on the atmospheres of planets in the solar system performed by Russian scientists in 2019–2022 is presented. This review was prepared in the Commission on Planetary Atmospheres of the National Geophysical Committee for the National Report on Meteorology and Atmospheric Science at the 28th General Assembly of the International Union of Geodesy and Geophysics (IUGG 2023) in Berlin. [ABSTRACT FROM AUTHOR]

Black carbon-containing (BCc) particles are pervasive in ambient atmosphere. The unexpected outbreak of the COVID-19 pandemic in 2021 summer prompted a localized and prolonged lockdown in Yangzhou City, situated in the YRD, China, which provides a unique opportunity to gain insights into the relationship between emission sources and BCc. Satellite and ground-level measurements both demonstrated that strict emission controls effectively reduced local gaseous pollutants. Meanwhile, single particle aerosol mass spectrometer (SPA-MS) analysis showed that the number fraction of freshly emitted BCc particles decreased to 28 % during the lockdown (LD), with that from vehicle emissions experiencing the most substantial reduction. However, the uncontrolled reductions of nitrogen oxides (NO x) and volatile organic compounds (VOCs) likely contributed to increased ozone (O3) concentrations, increased the oxidizing capacity, which may in turn enhanced secondary PM2.5 formation and compensated the primary PM2.5 reduction. As a result, we did observe a slight increase of PM2.5 concentration (21.2 μg m-3) during the LD period compared to the period before the lockdown (BLD), and the increase of more aged BCc particles. Reactive trace gases (e.g., NO x , SO2, and VOCs) could form thick coatings on pre-existing particles likely via enhanced heterogeneous hydrolysis under high RH as well, resulting in significant BCc particle growth (~600 nm) during LD period. Furthermore, BCc source apportionment reveals that BCc particles were primarily of local origin (78 %) in Yangzhou during normal summertime. However, coal combustion (23 %) and vehicle emissions (21 %) were prominent non-local pollution sources, with the air mass originating from the southeast, along with biomass burning emissions (19 %) from the northeast, contributing significantly. Our research highlights that short-term, strict local emission controls may not effectively reduce PM pollution, due to the non-linear responses of PM2.5 to its precursors , further effective PM2.5 reduction requires a comprehensive and extensive approach with a regionally coordinated and balanced control strategy through joint regulation. [ABSTRACT FROM AUTHOR]

Context. Gas cooling processes in the interstellar medium (ISM) are key to understanding how star formation occurs in galaxies. Far-infrared (FIR) fine-structure emission lines can be used to infer gas conditions and trace different phases of the ISM. Aims. We model eight of the most important FIR emission lines and explore their variation with star formation rate (SFR) out to z = 6 using cosmological hydrodynamical simulations. In addition, we study how different physical parameters, such as the interstellar radiation field (ISRF) and metallicity, impact the FIR lines and line ratios. Methods. We implemented a physically motivated multi-phase model of the ISM by post-processing the EAGLE cosmological simulation and using CLOUDY look-up tables for line emissivities. In this model we included four phases of the ISM: dense molecular gas, neutral atomic gas, diffuse ionised gas (DIG), and H II regions. Results. Our model shows reasonable agreement (to ∼0.5 dex) with the observed line luminosity–SFR relations up to z = 6 in the FIR lines analysed. For ease of comparison, we also provide linear fits to our model results. Our predictions also agree reasonably well with observations in diagnostic diagrams involving various FIR line ratios. Conclusions. We find that [C II] is the best SFR tracer of the FIR lines even though it arises from multiple ISM phases, while [O III] and [N II] can be used to understand the DIG–H II balance in the ionised gas. In addition, line ratios such as [C II]/[O III] and [N II]/[O I] are useful for deriving parameters such as ISRF, metallicity, and specific SFR. These results can help interpret the observations of the FIR lines from the local Universe to high redshifts. [ABSTRACT FROM AUTHOR]

The data of 17 air quality monitoring stations of Greater Cairo are used to perform a statistical analysis aiming to detect any heterogeneous surface effects of mineral dust on the distribution of reactive trace gases (SO2 NO2, and ozone) in. After a thorough quality check, the methodology consisted of i) selecting representative stations by agglomerative hierarchical clustering, ii) identifying dust events based on PM10 measurements, remote sensing observations, and meteorology, and iii) applying the non-parametric Kruskal Wallis (KW) hypothesis test to compare (at the 95% confidence level) trace gas concentrations during dust and non-dust events. The representative stations display either a background-like or a bimodal variability with concentrations (even that of the secondary product NO2) peaking at traffic rush hours but during dust storms all stations capture the signal of mineral dust advection. Eight wintertime and springtime dust cases are retained for the study. After the role of the confounding factors (i.e., ventilation index, relative humidity, and photolysis) has been carefully discussed and taken into account, the KW test shows that there is no significant reduction of the SO2, NO2 and ozone concentrations attributable to dust during 7 of the 8 events. The drop of the concentrations coinciding with the advection of dry dust-laden Saharan air masses is rather an effect of the dilution resulting from the combination of large wind speed and mixing layer height than of the heterogeneous uptake of these gases on the mineral dust surface. [ABSTRACT FROM AUTHOR]

The ability of the relaxed eddy accumulation (REA) method to estimate the kinematic fluxes of temperature, water vapor and carbon dioxide was assessed for the dry season (3 months) at the ATTO (Amazon Tall Tower Observatory) site from turbulence measurements. The measurements were performed at 50 m above ground within the roughness sublayer. Non-conformity with inertial sublayer conditions was confirmed one more time by analyzing dimensionless scalar standard deviations. Over the scale of the whole dry season, REA and EC (eddy covariance) estimates are essentially equal. Recently found results that the REA method outperforms Monin–Obukhov-based approaches are confirmed. However, we also verify that such results fail to reveal significant variability and scatter of the REA estimates when the fluxes are of small magnitude. On the basis of previous studies, we conjecture that this is caused by a likely imbalance between scalar gradient production and molecular dissipation. Confirmation of our results to trace gases, therefore, requires further study. [ABSTRACT FROM AUTHOR]

Trace gases have demonstrated their strength for oceanographic studies, with applications ranging from the tracking of glacial meltwater plumes to estimates of the abyssal overturning duration. Yet measurements of such passive tracers in the ice-covered Arctic Ocean are sparse. We here present a unique data set of trace gases collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, during which R/V Polarstern drifted along with the Arctic sea ice from the Laptev Sea to Fram Strait, from October 2019 to September 2020. During the expedition, trace gases from anthropogenic origin (chlorofluorocarbon 12 (CFC-12), sulfur hexafluoride (SF 6), and tritium) along with noble gases (helium and neon) and their isotopes were collected at a weekly or higher temporal resolution throughout the entire water column (and occasionally in the snow) from the ship and from the ice. We describe the sampling procedures along with their challenges, the analysis methods, and the data sets, and we present case studies in the central Arctic Ocean and Fram Strait to illustrate possible usage for the data along with their robustness. Combined with simultaneous hydrographic measurements, these trace gas data sets can be used for process studies and water mass tracing throughout the Arctic in subsequent analyses. The two data sets can be downloaded via PANGAEA: 10.1594/PANGAEA.961729 (Huhn et al., 2023a) and 10.1594/PANGAEA.961738 (Huhn et al., 2023b). [ABSTRACT FROM AUTHOR]

The present manuscript aims to study the impact of the lockdown imposed during the COVID-19 pandemic on the air quality of Agra, India. Particulate matter (PM2.5), trace gases, and volatile organic compounds (VOCs) were evaluated to detect changes in air quality during pre-lockdown, lockdown, and post-lockdown periods. The average concentration of PM2.5 in pre-lockdown was 130 ± 79.3 µg/m3, which reduced to 48.3 ± 24.9 µg/m3 (62.8%) during the lockdown period, while during post-lockdown it again increased to 59.3 ± 26.6 µg/m3. Average concentrations of NO, NO2 and NOx, in pre-lockdown were 5.1 ± 0.5, 2.3 ± 0.3 and 6.2 ± 2.9 ppb, respectively, which decreased by 60.8, 56.5, and 67.7%, respectively, during lockdown as compared to pre-lockdown period. Average concentration of carbon monoxide (CO) was 710.7 ± 315.7 ppb in pre-lockdown, decreased to 381.8 ± 164.4 ppb (46.3%) during the lockdown and increased to 401.3 ± 280.5 ppb (5.2%) as post-lockdown occurred. Similar trend was observed for benzene and toluene. Average concentration of tropospheric ozone (O3) before the lockdown was 24.5 ± 9.5 ppb which rose to 40.4 ± 12.9 ppb (64.9%) during lockdown and reduced to 29.2 ± 5.8 ppb during post-lockdown period. CO may have reduced due to decreased vehicular intensity, while O3 showed high concentration due to the weakened chemical titration of O3 with NO. Interspecies ratio for benzene/toluene was 0.7, which suggests dominance of vehicular emissions and fresh air masses. The study may be beneficial in providing information for air pollution reduction and planning for future post-pandemic air quality management. [ABSTRACT FROM AUTHOR]

We have demonstrated a comparative study of NO2 gas sensing behavior of reactive sputtered growth WO3−x nanocrystalline thin films and its functionalization with Ag nanoparticles (Ag−WO3−x) on Si/SiO2 substrates. X-ray diffraction and transmission electron microscope characterizations demonstrate the formation of polycrystalline monoclinic phase of porous WO3-x thin film. X-ray photoelectron spectroscopy experiments reveal that W6+ charge state has higher concentration compared with that of W4+ and W5+. The Ag−WO3−x films exhibit a sensitivity of about 70% at 10 ppm, while WO3−x films show 12%, measured at 225 °C with same NO2 gas concentration. The response and recovery time are 2 and 3 min. for Ag−WO3−x films, while these for WO3−x films are 3 and 4 min., respectively. This work shows that nano-scale dendritic agglomeration growth of Ag nanoparticles on WO3−x surface can increase active sites for NO2 gas and play an important role in trace-level gas sensing performance. [ABSTRACT FROM AUTHOR]

Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean. The oxidation of DMS has long been recognised as being important for global climate through the role DMS plays in setting the sulfate aerosol background in the troposphere. However, the mechanisms in which DMS is oxidised are very complex and have proved elusive to accurately determine in spite of decades of research. As a result the representation of DMS oxidation in global chemistry–climate models is often greatly simplified. Recent field observations and laboratory and ab initio studies have prompted renewed efforts in understanding the DMS oxidation mechanism, with implications for constraining the uncertainty in the oxidation mechanism of DMS as incorporated in global chemistry–climate models. Here we build on recent evidence and develop a new DMS mechanism for inclusion in the UK Chemistry Aerosol (UKCA) chemistry–climate model. We compare our new mechanism (CS2-HPMTF) to a number of existing mechanisms used in UKCA (including the highly simplified three-reactions–two-species mechanism used in CMIP6 studies with the model) and to a range of recently developed mechanisms reported in the literature through a series of global and box model experiments. Global model runs with the new mechanism enable us to simulate the global distribution of hydroperoxylmethyl thioformate (HPMTF), which we calculate to have a burden of 2.6–26 Gg S (in good agreement with the literature range of 0.7–18 Gg S). We show that the sinks of HPMTF dominate uncertainty in the budget, not the rate of the isomerisation reaction forming it and that, based on the observed DMS / HPMTF ratio from the global surveys during the NASA Atmospheric Tomography mission (ATom), rapid cloud uptake of HPMTF worsens the model–observation comparison. Our box model experiments highlight that there is significant variance in simulated secondary oxidation products from DMS across mechanisms used in the literature, with significant divergence in the sensitivity of the rates of formation of these products to temperature exhibited; especially for methane sulfonic acid (MSA). Our global model studies show that our updated DMS scheme performs better than the current scheme used in UKCA when compared against a suite of surface and aircraft observations. However, sensitivity studies underscore the need for further laboratory and observational constraints. In particular our results suggest that as a priority long-term DMS observations be made to better constrain the highly uncertain inputs into the system and that laboratory studies be performed that address (1) the uptake of HPMTF onto aerosol surfaces and the products of this reaction and (2) the kinetics and products of the following reactions: CH 3 SO 3 decomposition, CH 3 S + O 2 , CH 3 SOO decomposition, and CH 3 SO + O 3. [ABSTRACT FROM AUTHOR]

Ionization cones and relativistic jets give us one of the most large-scale example of active galactic nuclei (AGN) influence on the surrounding gas environment in galaxies and beyond. The study of ionization cones makes it possible not only to test the predictions of the unified model of galactic activity, but also to probe galaxy gas environment and trace how the luminosity of the nucleus changes over time (a light echo). In the external galactic or even extragalactic gas ionization cones create Extended Emission-Line Regions (EELRs) which can span distances from several to hundreds kpc away a host galaxy. We review the recent results of studying the gas kinematics and its ionization properties in EELRs with a special attention to search of fading AGN radiation on the time scale few × (10 4 − 10 5) years.The role of modern narrow-band and integral-field surveys in these researches is also considered. [ABSTRACT FROM AUTHOR]

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This document is an editorial titled "Anthropogenic trace gases and their linkages to meteorology and climate change" that discusses the environmental problems of anthropogenic trace gases and climate change. It emphasizes the impact of urbanization and economic growth on trace gas emissions, air quality, and human and ecosystem health. The editorial also mentions the role of anthropogenic trace gases in the formation of surface ozone and particulate matter, which have negative effects on human health and the environment. The document concludes by mentioning several research articles published on the topic of air quality, climate change, and meteorology. Additionally, the given text discusses air pollution and air quality in India, highlighting the dominant sources of pollutants in specific regions and the factors that control ozone variability. It also addresses the challenges associated with monitoring and evaluating air quality using satellite data. This information can be valuable for researchers and policymakers in understanding and addressing air pollution issues in India. [Extracted from the article]

The air quality and climate of the Himalaya is found to be impacted profoundly by strong anthropogenic emissions and photochemical processes in the valley region. Considering rapid urbanization and population growth, we performed surface ozone (O3) measurements over Doon valley of the Indian Himalaya during April 2018–June 2023, in conjunction with the analysis of satellite observations and modeling. Noontime O3 levels are observed to be the highest during pre-monsoon (63.8 ± 15.3 ppbv in May) and lower (22.1–56.7 ppbv) during winter and monsoon seasons. Notably, the daily maximum 8-h average (MDA8) O3 exceeds the 50 ppbv threshold for ∼60% of the days during April–June, which suggests substantial health impacts in the region. Impact of O3 exposure on vegetation is also significant during this period of year, as reflected from high Accumulated Ozone above Threshold 40 ppbv (AOT40) and Mean of daytime 7 hours (M7) indices. The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis successfully reproduced the observed variability in the noontime O3 (r2 = 0.79–0.91). Analysis of a tracer in the CAMS model shows that the mean stratospheric contributions to surface O3 were typically smaller (up to 8%). This suggests that O3 pollution is governed primarily by the photochemical production favored by regional emissions and meteorological conditions. Analysis combining in-situ O3 measurements with satellite retrievals (HCHO and NO2) revealed that the photochemical O3 production is in the transition or VOC-limited regime, and therefore emission of both NOx and volatile organic compounds (VOCs) are to be reduced to mitigate O3 pollution. Finally, a statistical model considering the non-linearities was successfully applied to simulate observed O3 variability from available satellite observations and meteorological reanalysis data (r2 = 0.75, RMSE = 7 ppbv). Our study highlights the need to mitigate O3 pollution in the Doon valley of the Indian Himalaya and also provides invaluable inputs for designing science-informed policies.

Here, we report the development of a new Quantum cascade Laser infrared Absorption Spectroscopy (QLAS) instrument, the Airborne Tropospheric Tracer In-situ Laser Absorption spectrometer (ATTILA), for atmospheric trace gas measurements on board of the German High-Altitude Long-range Observatory (HALO) aircraft. Its small and light design makes it suitable for airborne measurements up to approximately 150 hPa of ambient pressure (13 - 14 km). The dual laser instrument can measure several trace gases simultaneously in two 36.4-m-path astigmatic Herriott cells with a data acquisition frequency of 1 Hz. We describe the measurement method and the data acquisition of ATTILA and its in-flight performance by focusing on potential sources of influences on the signal, which we investigated with a dedicated test flight during which the instrument sampled from a constant source. We show that linear critical influences associated with challenging movement patterns can be corrected afterwards, while non-linear limitations can be minimized by appropriate calibration frequencies and integrated time intervals. During the recent aircraft campaign CAFE-Brazil (Chemistry of the Atmosphere Field Experiment in Brazil) from December 2022 to January 2023, carbon monoxide (CO) measurements from ATTILA show a good agreement of a R² of 0.89 with simultaneous CO measurements from an established IR spectrometer for airborne measurements, the TRacer In-Situ Tdlas for Atmospheric Research (TRISTAR), on a 10 s time resolution. First dynamical characteristics and tracer distributions of CO and methane (CH4) over the Amazon rainforest can be identified with ATTILA measurements with a total measurement uncertainty of 10.1 % and 17.5 % and a data accuracy of 0.3 % and 5.5 % for a data acquisition frequency of 1 Hz for CO and CH4, respectively. [ABSTRACT FROM AUTHOR]

Isotopic measurements of trace gases such as N2O, CO2 and CH4 contain valuable information about production and consumption pathways. Quantification of the underlying pathways contributing to variability in isotopic timeseries can provide answers to key scientific questions, such as the contribution of nitrification and denitrification to N2O emissions under different environmental conditions, or the drivers of multiyear variability in atmospheric CH4 growth rate. However, there is currently no data analysis package available to solve isotopic production, mixing and consumption problems for timeseries data in a unified manner while accounting for uncertainty in measurements and model parameters. Bayesian hierarchical models combine the use of expert information with measured data and a mathematical mixing model while considering and updating the uncertainties involved, and are an ideal basis to approach this problem. Here we present the TimeFRAME data analysis package for 'Time-resolved Fractionation And Mixing Evaluation'. We use four different classes of Bayesian hierarchical model to solve production, mixing and consumption contributions using multi-isotope timeseries measurements: i) independent time step models, ii) Gaussian process priors on measurements, iii) Dirichlet-Gaussian process priors, and iv) generalized linear models with spline bases. All four models have been extensively tested in different variations and for a multitude of scenarios. Dirichlet-Gaussian process prior models have been found to be most reliable, allowing for simultaneous estimation of hyperparameters via Bayesian hierarchical modeling. Generalized linear models with spline bases seem promising as well, especially for fractionation estimation, although the robustness to real datasets is difficult to assess given their high flexibility. Experiments with simulated data for δ15Nbulk and δ15NSP of N2O showed that model performance across all classes could be greatly improved by reducing uncertainty in model input data – particularly isotopic endmembers and fractionation factors. The addition of the δ18O additional isotopic dimension yielded a comparatively small benefit for N2O production pathways but improved quantification of the fraction of N2O consumed. The TimeFRAME package can be used to evaluate both static and timeseries datasets, with flexible choice of the number and type of isotopic endmembers and the model set up allowing simple implementation for different trace gases. The package is available in R, and is implemented using Stan for parameter estimation, in addition to supplementary functions re-implementing some of the surveyed isotope analysis techniques. [ABSTRACT FROM AUTHOR]

Isotopic measurements of trace gases such as N2O, CO2 and CH4 contain valuable information about production and consumption pathways. Quantification of the underlying pathways contributing to variability in isotopic timeseries can provide answers to key scientific questions, such as the contribution of nitrification and denitrification to N2O emissions under different environmental conditions, or the drivers of multiyear variability in atmospheric CH4 growth rate. However, there is currently no data analysis package available to solve isotopic production, mixing and consumption problems for timeseries data in a unified manner while accounting for uncertainty in measurements and model parameters. Bayesian hierarchical models combine the use of expert information with measured data and a mathematical mixing model while considering and updating the uncertainties involved, and are an ideal basis to approach this problem. Here we present the TimeFRAME data analysis package for 'Time-resolved Fractionation And Mixing Evaluation'. We use four different classes of Bayesian hierarchical model to solve production, mixing and consumption contributions using multi-isotope timeseries measurements: i) independent time step models, ii) Gaussian process priors on measurements, iii) Dirichlet-Gaussian process priors, and iv) generalized linear models with spline bases. All four models have been extensively tested in different variations and for a multitude of scenarios. Dirichlet-Gaussian process prior models have been found to be most reliable, allowing for simultaneous estimation of hyperparameters via Bayesian hierarchical modeling. Generalized linear models with spline bases seem promising as well, especially for fractionation estimation, although the robustness to real datasets is difficult to assess given their high flexibility. Experiments with simulated data for δ15Nbulk and δ15NSP of N2O showed that model performance across all classes could be greatly improved by reducing uncertainty in model input data - particularly isotopic endmembers and fractionation factors. The addition of the δ18O additional isotopic dimension yielded a comparatively small benefit for N2O production pathways but improved quantification of the fraction of N2O consumed. The TimeFRAME package can be used to evaluate both static and timeseries datasets, with flexible choice of the number and type of isotopic endmembers and the model set up allowing simple implementation for different trace gases. The package available in R, and is implemented using Stan for parameter estimation, in addition to supplementary functions reimplementing some of the surveyed isotope analysis techniques. [ABSTRACT FROM AUTHOR]

Wildfires emit vast amounts of aerosols and trace gases into the atmosphere, exerting myriad effects on air quality, climate, and human health. Ensemble forecasting has been proposed to reduce the large uncertainties in the wildfire air pollution forecast. This study presents the development of a multi‐model ensemble (MME) wildfire air pollution forecast over North America. The ensemble members include regional models (GMU‐CMAQ, NACC‐CMAQ, and HYSPLIT), global models (GEFS‐Aerosols, GEOS5, and NAAPS), and global ensemble (ICAP‐MME). Performance of the ensemble forecast was evaluated with MAIAC and VIIRS‐SNPP retrieved aerosol optical depth (AOD) and AirNow surface PM2.5 measurements during the 2020 Western United States "Gigafire" events (August–September 2020). Compared to individual models, the ensemble mean significantly reduced the biases and produced more consistent and reliable forecasts during extreme fire events. For AOD forecasts, the ensemble mean was able to improve model performance, such as increasing the correlation to 0.62 from 0.33 to 0.57 by individual models compared to VIIRS AOD. The ensemble mean also yields the best overall RANK (a composite indicator of four statistical metrics) when compared to VIIRS and MAIAC AOD. For the surface PM2.5 forecast, the ensemble mean outperformed individual models with the strongest correlation (0.60 vs. 0.43–0.54 by individual models), lowest fractional bias (0.54 vs. 0.55–1.32), highest hit rate (87% vs. 40%–82%), and highest RANK (2.83 vs. 2.40–2.81). Finally, the ensemble shows the potential to provide a probability forecast of air quality exceedances. The exceedance probability forecast can be further applied to early warnings of extreme air pollution episodes during large wildfire events. Plain Language Summary: Wildfires are a major source of air pollution emitting large quantities of particles into the air that adversely affect human health. Predicting wildfire air pollution, however, is challenging. Ensemble forecasting has been proposed to improve the model predictability. We developed a new multi‐model ensemble forecast system of wildfire air pollution over North America, leveraging regional and global atmospheric models by federal agencies and academia. How well the ensemble forecast can predict wildfire pollution was evaluated with observations from satellites and ground monitors. We found that the ensemble mean can significantly reduce the forecast biases and produce more reliable forecasts during extreme wildfire fire events. The ensemble probability forecast of exceedance of the health‐based National Ambient Air Quality Standards for fine particles (PM2.5) can be further applied to early warnings of severe air pollution episodes during large wildfire events. These findings highlight the potential of the ensemble approach to improve the predictability of air pollution during large wildfires. Key Points: Ensemble mean of models provides reliable aerosol optical depth and PM2.5 forecasts with stronger correlation, lower bias, and the highest overall RANKsThe ensemble approach provides a well suited exceedance probability forecast during the 2020 Gigafire eventsThe multi‐model ensemble approach can reduce uncertainties in air quality forecasts and improve model predictability during wildfire events [ABSTRACT FROM AUTHOR]

Biomass burning releases large amounts of aerosols and chemical species into the atmosphere, which represents a major source of air pollutants. Emissions and by-products can be transported over long distances, presenting challenges in quantification. This is mainly done using satellites, which offer global coverage and data acquisition for places that are difficult to access. In this study, ground-based observations play an important role in assessing the abundance of trace gases and aerosols. On November 24, 2020, a significant increase in formaldehyde was observed, with a MAX-DOAS instrument located in Montevideo (Uruguay). Vertical column densities reached values of 2.4x1016 molec. cm-2, more than twice the values observed during the previous days. This was accompanied by an increase in the aerosol levels measured by an AERONET photometer located at the same site. For example, the AOD at 440 nm reached values close to 1, one order of magnitude larger than typical values in Montevideo. Our findings indicate that the cause of the increase was associated with the passage of a plume originating from distant biomass burning. This conclusion is supported using TROPOMI satellite observations as well as HYSPLIT trajectory simulations. The profiles of the gases and aerosols retrieved from the MAX-DOAS observations are consistent with the HYSPLIT analysis, showing the passage of a plume over Montevideo on November 24 located at a height of ∼1.5 km. This corroborates that biomass burning events that occur about 800 km north of Montevideo can affect the local atmosphere due to long-distance transport of emissions. This study underscores the potential of ground-based atmospheric monitoring as a tool for detection of such events. Furthermore, it demonstrates the greater sensitivity compared to satellite when it comes to detection of relatively small amounts of carbonyls like glyoxal and formaldehyde. [ABSTRACT FROM AUTHOR]

The total mass estimate of molecular clouds suffers from the uncertainty in the H2-CO conversion factor, the so-called X CO factor, which is used to convert the 12CO (1–0) integrated intensity to the H2 column density. We demonstrate the machine learning's ability to predict the H2 column density from the 12CO, 13CO, and C18O (1–0) data set of four star-forming molecular clouds: Orion A, Orion B, Aquila, and M17. When the training is performed on a subset of each cloud, the overall distribution of the predicted column density is consistent with that of the Herschel column density. The total column density predicted and observed is consistent within 10 per cent, suggesting that the machine learning prediction provides a reasonable total mass estimate of each cloud. However, the distribution of the column density for values >∼2 × 1022 cm−2, which corresponds to the dense gas, could not be predicted well. This indicates that molecular line observations tracing the dense gas are required for the training. We also found a significant difference between the predicted and observed column density when we created the model after training the data on different clouds. This highlights the presence of different X CO factors between the clouds, and further training in various clouds is required to correct for these variations. We also demonstrated that this method could predict the column density towards the area not observed by Herschel if the molecular line and column density maps are available for the small portion, and the molecular line data are available for the larger areas. [ABSTRACT FROM AUTHOR]

In the Multi-Axis Differential Absorption Spectroscopy (MAX-DOAS) trace gas and aerosol profile inversion algorithm, the vertical resolution and the observation information obtained through a series of continuous observations with multiple elevation angles (EAs) can affect the accuracy of an aerosol profile, thus further affecting the results of the gas profile. Therefore, this study examined the effect of the vertical resolution of an aerosol profile and EAs on the NO2 profile retrieval by combining simulations and measurements. Aerosol profiles were retrieved from MAX-DOAS observations and co-observed using light detection and ranging (Lidar). Three aerosol profile shapes (Boltzmann, Gaussian, and exponential) with vertical resolutions of 100 and 200 m were used in the atmospheric radiative transfer model. Firstly, the effect of the vertical resolution of the input aerosol profile on the retrieved aerosol profile with a resolution of 200 m was studied. The retrieved aerosol profiles from the two vertical resolution aerosol profiles as input were similar. The aerosol profile retrieved from a 100 m resolution profile as input was slightly overestimated compared to the input value, whereas that from a 200 m resolution input was slightly underestimated. The relative deviation of the aerosol profile retrieved from the 100 m resolution as input was higher than that of the 200 m. MAX-DOAS observations in Hefei city on 4 September 2020 were selected to verify the simulation results. The aerosol profiles retrieved from the oxygen collision complex (O4) differential slant column density derived from MAX-DOAS observations and Lidar simulation were compared with the input Lidar aerosol profiles. The correlation between the retrieved and input aerosol profiles was high, with a correlation coefficient R > 0.99. The aerosol profiles retrieved from the Lidar profile at 100 and 200 m resolutions as input closely matched the Lidar aerosol profiles, consistent with the simulation result. However, aerosol profiles retrieved from MAX-DOAS measurements differed from the Lidar profiles due to the influence of the averaging kernel matrix smoothing, the different location and viewing geometry, and uncertainties associated with the Lidar profiles. Next, NO2 profiles of different vertical resolutions were used as input profiles to retrieve the NO2 profiles under a single aerosol profile scenario. The effect of the vertical resolution on the retrieval of NO2 profiles was found to be less significant compared to aerosol retrievals. Using the Lidar aerosol profile as the a priori aerosol information had little effect on NO2 profile retrieval. Additionally, the retrieved aerosol profiles and aerosol optical depths varied under different EAs. Ten EAs (i.e., 1, 2, 3, 4, 5, 6, 8, 15, 30, and 90°) were found to obtain more information from observations. [ABSTRACT FROM AUTHOR]

We present dense-gas-tracing molecular observations of six resolved Giant Molecular Clouds (GMCs) in the Andromeda Galaxy (M31). Using the NOEMA interferometer, we observed the transitions of HCN(1–0), HCO+(1–0), and HNC(1–0), as well as 13CO(1–0) and 100 GHz continuum emission. This complements our earlier work with the Submillimetre Array, including resolved dust continuum detections of these clouds at 230 GHz. In this work, we first compare different continuum measurements to conclude that the average free–free contamination of the observed flux is 71 per cent at 3 mm but only 13 per cent at 1 mm, confirming that emission at 3 mm is less reliable than that at 1 mm for calculating dust masses of star-forming clouds. While the 13CO emission is more extended than both HCN and HCO+ emission, which in turn is more extended than HNC emission, we find that both HCN and HCO+ are spatially coincident with, and similarly extended as, the 230 GHz dust emission. This suggests that both the 230 GHz dust continuum and most importantly the HCN emission traces the dense gas component of these GMCs. From comparison of the molecular emission with dust masses derived from the 230 GHz continuum emission, we obtain the first direct measurements of the dust-mass-to-light ratios (⁠|$\alpha ^\prime _{\rm HCN}$| and |$\alpha ^\prime _{\rm HCO^+}$|⁠) in GMCs of an external galaxy. For HCN, the result is broadly similar to a measurement in the local Perseus cloud suggesting that these are indeed dense gas conversion factors. A larger cloud sample will be required to assess whether HCN is tracing comparable cloud-scale density regimes across the environments of M31. [ABSTRACT FROM AUTHOR]

Determination of trace gas emissions from sources is critical for understanding and regulating air quality and climate change. Here, we demonstrate a method for rapid quantification of the emission rate of multiple gases from simple and complex sources using a mass balance approach with a spatially scannable open-path sensor – in this case, an open-path dual-comb spectrometer. The open-path spectrometer measures the total column density of gases between the spectrometer and a retroreflector mounted on an uncrewed aerial vehicle (UAV). By measuring slant columns at multiple UAV altitudes downwind of a source (or sink), the total emission rate can be rapidly determined without the need for an atmospheric dispersion model. Here, we demonstrate this technique using controlled releases of CH 4 and C 2 H 2. We show an emission rate determination to within 56 % of the known flux with a single 10 min flight and within 15 % of the known flux after 12 flights. Furthermore, we estimate the detection limit for CH 4 emissions to be 0.03 g CH 4 s -1. This detection limit is approximately the same as the emissions from 25 head of beef cattle and is less than the average emissions from a small oil field pneumatic controller. Other gases including CO 2 , NH 3 , HDO, ethane, formaldehyde (HCHO), CO, and N 2 O can be measured by simply changing the dual-comb spectrometer. [ABSTRACT FROM AUTHOR]

To address ambitious goals of carbon neutrality set at national and city scales, a number of atmospheric networks have been deployed to monitor greenhouse gas (GHG) concentrations in and around cities. To convert these measurements into estimates of emissions from cities, atmospheric models are used to simulate the transport of various trace gases and help interpret these measurements. We set up a modelling framework using the Weather Research and Forecasting (WRF) model applied at a high spatial resolution (up to 400 m) to simulate the atmospheric transport of GHGs and attempt a preliminary interpretation of the observations provided by the Munich Urban Carbon Column Network (MUCCnet). Building on previous analyses using similar measurements performed within a campaign for the city of Berlin and its surroundings , our modelling framework has been improved regarding the initialization of tagged tracers, model settings, and input data. To assess the model performance, we validate the modelled output against two local weather stations and two radiosonde observations, as well as observed column GHG concentrations. The measurements were provided by the measurement campaign that was carried out from 1 to 30 August 2018. The modelled wind matches well with the measurements from the weather stations, with wind speeds slightly overestimated. In general, the model is able to reproduce the measured slant column concentrations of CH4 and their variability, while for CO2 , a difference in the slant column CO2 of around 3.7 ppm is found in the model. This can be attributed to the initial and lateral boundary conditions used for the background tracer. Additional mismatches in the diurnal cycle could be explained by an underestimation of nocturnal respiration in the modelled CO2 biogenic fluxes. The differential column method (DCM) has been applied to cancel out the influence from the background concentrations. We optimize its application by selecting suitable days on which the assumption of the DCM holds true: a relatively uniform air mass travels over the city, passing from an upwind site to a downwind site. In particular, the Stochastic Time-Inverted Lagrangian Transport (STILT) model is used here and driven by our WRF-modelled meteorological fields to obtain footprints (i.e. the potential areas of influence for signals observed at measurement stations), further used for interpreting measurement results. Combining these footprints with local knowledge of emission sources, we find evidence of CH4 sources near Munich that are missing or underestimated in the emission inventory used. This demonstrates the potential of this data–model framework to constrain local sources and improve emission inventories. [ABSTRACT FROM AUTHOR]

Lightning flashes are an important source of wildfires worldwide, contributing to the emission of trace gases to the atmosphere. Based on experiments and field observations, continuing currents in lightning have since a long time been proposed to play a significant role in the ignition of wildfires. However, simultaneous detections of optical and radio signals from fire‐igniting lightning confirming the role of continuing currents in igniting wildfires are rare. In this work, we first analyze the optical signal of the lightning‐ignited wildfires reported by the Geostationary Lightning Mapper over the Contiguous United States (CONUS) during the summer of 2018, and we then analyze the optical and the Extremely Low Frequency signal of a confirmed fire‐igniting lightning flash in the Swiss Alps. Despite data uncertainties, we found that the probability of ignition of a lightning flash with Continuing Current (CC) lasting more than 10 ms is higher than that of cloud‐to‐ground lightning in CONUS. Finally, we confirm the existence of a long CC (lasting about 400 ms) associated with a long‐lasting optical signal (lasting between 2 and 4 s) of a video‐recorded fire‐igniting lightning flash. Plain Language Summary: Lightning plays a significant role in causing natural fires. Previous studies have found that a specific type of lightning, known as continuing current lightning (CC), has a higher likelihood of igniting fires. CC lightning refers to a phenomenon where electrical charge continues to flow through the channel for extended periods of tens or hundreds of milliseconds, possibly leading to elevated vegetation temperatures. In our research, we used the optical lightning detections provided by the Geostationary Lightning Mapper to estimate the probability of wildfires associated with both normal lightning and CC lightning across the United States. To gain further insights, we employed a ground camera video and analyzed extremely low‐frequency radio signals to meticulously examine the duration of CC in a lightning strike that ignited a fire in the Alps. The findings of our study demonstrate that the probability of fire occurrence is higher when CC lightning is involved compared to typical lightning strikes. This highlights the importance of understanding the characteristics of lightning and its varying impacts on fire risk assessment. Key Points: The probability of wildfire ignition by cloud‐to‐ground lightning is larger for flashes with Continuing Current (CC)The variation of the lightning ignition efficiency of lightning with CC suggest a significant influence of other factorsThe analysis of one single lightning‐ignited fire in the Alps confirms the presence of a lightning with a long CC [ABSTRACT FROM AUTHOR]

Removal of trace CO impurities is an essential step in the utilization of Hydrogen as a clean energy source. While various solutions are currently employed to address this challenge, there is an urgent need to improve their efficiency. Here, we show that a bead-structured Mg, Cu, and Ce-based sorbent, Mg13CuCeOx, demonstrates superior removal capacity of trace CO from H2 with high stability. The incorporation of Mg boosts sorption performance by enhancing the porous structure and Cu+ surface area. Remarkably, compared to existing pelletized sorbents, Mg13CuCeOx exhibits 15.5 to 50 times greater equilibrium capacity under pressures below 10 Pa CO and 31 times longer breakthrough time in removing 50 ppm CO in H2. Energy-efficient oxidative regeneration using air at 120 °C allows its stable sorption performance over 20 cycles. Through in-situ DRIFTS analysis, we elucidate the reaction mechanism that Mg augments the surface OH groups, promoting the formation of bicarbonate and formate species. This study highlights the potential of MgCuCeOx sorbents in advancing the hydrogen economy by effectively removing trace CO from H2. The challenge of trace CO removal from H2 remains at the forefront of the hydrogen economy. Here, the authors demonstrated exceptional CO removal using a highly stable, hierarchically structured sorbent bead, Mg13CuCeOx. Mechanistic analysis showed the pivotal role of Mg in enhancing CO sorption. [ABSTRACT FROM AUTHOR]

Industrial emissions of trace gases and VOCs can be an important contributor to air quality in cities. Disentangling different point sources from each other and characterizing their emissions can be particularly challenging in dense industrial areas, such as Detroit, Dearborn and surrounding areas in Southeast Michigan (SEMI). Here, we leverage mobile measurements of trace gases and speciated volatile organic compounds (VOCs) to identify emitting sites. We characterize their complicated emissions fingerprints based on a core set of chemical ratios. We report chemical ratios for 7 source types including automakers, steel manufacturers, chemical refineries, industrial chemical use (cleaning; coatings; etc.), chemical waste sites, compressor stations, and more. The source dataset includes visits to over 85 distinct point sources. As expected, we find similarities between the different types of facilities, but observe variability between them and even at individual facilities day-to-day. Certain larger sites are better thought of as a collection of individual point sources. These results demonstrate the power of mobile laboratories over stationary sampling in dense industrial areas. [ABSTRACT FROM AUTHOR]

Laser spectroscopy has shown great potential as a cost‐effective method for trace gas detection with high sensitivity and specificity. However, it still falls short in applications such as the measurement of stable isotope ratios, which require high precision and stability. Here, ultrasensitive gas detection with remarkable precision and stability as well as better immunity to isobaric interference is demonstrated by use of low‐coherence photothermal interferometry. With a 10 cm long hollow‐core fiber, acetylene detection is achieved with a noise‐equivalent concentration of 0.7 part‐per‐billion and measurement precision of 0.025%. The instability of the detection over a period of 3 h is ±0.038%, 10 times better than the state‐of‐the‐art photothermal spectroscopy. The measurement of the 13C/12C isotope ratio of acetylene is demonstrated with measurement precision of ≈0.01%. This study highlights the potential of low‐coherence photothermal interferometry as an alternative to mass spectrometers, offering reliable gas detection in a compact form. [ABSTRACT FROM AUTHOR]

We implemented the Community Aerosol and Radiation Model for Atmospheres (CARMA) in both the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2). CARMA is a sectional microphysical model, which we use for aerosol in both the troposphere and stratosphere. CARMA is fully coupled to chemistry, clouds, radiation, and transport routines in CESM2. This development enables the comparison of simulations with a sectional (CARMA) and a modal (MAM4) aerosol microphysical model in the same modeling framework. The new implementation of CARMA has been adopted from previous work, with some additions that align with the current CESM2 Modal Aerosol Model (MAM4) implementation. The main updates include an interactive secondary organic aerosol description in CARMA, using the volatility basis set (VBS) approach, updated wet removal, and the use of transient emissions of aerosols and trace gases. In addition, we implemented an alternative aerosol nucleation scheme in CARMA, which is also used in MAM4. Detailed comparisons of stratospheric aerosol properties after the Mount Pinatubo eruption reveal the importance of prescribing sulfur injections in a larger region rather than in a single column to better represent the observed evolution of aerosols. Both CARMA and MAM4 in CESM2 are able to represent stratospheric and tropospheric aerosol properties reasonably well when compared to observations. Several differences in the performance of the two aerosol models show, in general, an improved representation of aerosols when using the sectional aerosol model in CESM2. These include a better representation of the aerosol size distribution after the Mount Pinatubo volcanic eruption in CARMA compared to MAM4. MAM4 produces on average smaller aerosols and less removal than CARMA, which results in a larger total mass. Both CARMA and MAM4 reproduce the stratospheric aerosol optical depth (AOD) within the error bar of the observations between 2001 and 2020, except for recent larger volcanic eruptions that are overestimated by both model configurations. The CARMA background surface area density and aerosol size distribution in the stratosphere and troposphere compare well to observations, with some underestimation of the Aitken-mode size range. MAM4 shows shortcomings in reproducing coarse-mode aerosol distributions in the stratosphere and troposphere. This work outlines additional development needs for CESM2 CARMA to improve the model compared to observations in both the troposphere and stratosphere. [ABSTRACT FROM AUTHOR]