Atmospheric Measurement Techniques最新文献

{"title":"Improved mean field estimates from the Geostationary Environment Monitoring Spectrometer (GEMS) Level-3 aerosol optical depth (L3 AOD) product: using spatiotemporal variability","authors":"Sooyon Kim, Yeseul Cho, Hanjeong Ki, Seyoung Park, Dagun Oh, Seungjun Lee, Yeonghye Cho, Jhoon Kim, Wonjin Lee, Jaewoo Park, Ick Hoon Jin, Sangwook Kang","doi":"10.5194/amt-17-5221-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5221-2024","url":null,"abstract":"Abstract. This study presents advancements in the processing of satellite remote sensing data, focusing mainly on aerosol optical depth (AOD) retrievals from the Geostationary Environment Monitoring Spectrometer (GEMS). The transformation of Level-2 (L2) data, which includes atmospheric-state retrievals, into higher-quality Level-3 (L3) data is crucial in remote sensing. Our contributions lie in two novel improvements to the processing algorithm. First, we improve the inverse-distance-weighting algorithm by incorporating quality flag information into the weight calculation. By assigning weights that are inversely proportional to the number of unreliable grids, the method can provide more accurate L3 products. We validate this approach through simulation studies and apply it to GEMS AOD data across various regions and wavelengths. The use of quality flags in the algorithm can provide a more accurate analysis of remote sensing. Second, we employ a spatiotemporal merging method to address both spatial and temporal variability in AOD data, a departure from previous approaches that solely focused on spatial variability. Our method considers temporal variations spanning previous time intervals. Furthermore, the computed mean fields show similar spatiotemporal patterns to previous studies, confirming their ability to capture real-world phenomena. Lastly, utilizing this procedure, we compute the mean field estimates for GEMS AOD data, which can provide a deeper understanding of the impact of aerosols on climate change and public health.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"77 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument","authors":"Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, Jhoon Kim","doi":"10.5194/amt-17-5147-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5147-2024","url":null,"abstract":"Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 is now providing continuous daytime hourly observations of nitrogen dioxide (NO2) columns over eastern Asia (5° S–45° N, 75–145° E) with 3.5 × 7.7 km2 pixel resolution. These data provide unique information to improve understanding of the sources, chemistry, and transport of nitrogen oxides (NOx) with implications for atmospheric chemistry and air quality, but opportunities for direct validation are very limited. Here we correct the operational level-2 (L2) NO2 vertical column densities (VCDs) from GEMS with a machine learning (ML) model to match the much sparser but more mature observations from the low Earth orbit TROPOspheric Monitoring Instrument (TROPOMI), preserving the data density of GEMS but making them consistent with TROPOMI. We first reprocess the GEMS and TROPOMI operational L2 products to use common prior vertical NO2 profiles (shape factors) from the GEOS-Chem chemical transport model. This removes a major inconsistency between the two satellite products and greatly improves their agreement with ground-based Pandora NO2 VCD data in source regions. We then apply the ML model to correct the remaining differences, Δ(GEMS–TROPOMI), using the GEMS NO2 VCDs and retrieval parameters as predictor variables. We train the ML model with colocated GEMS and TROPOMI NO2 VCDs, taking advantage of TROPOMI off-track viewing to cover the wide range of effective zenith angles (EZAs) observed by GEMS. The two most important predictor variables for Δ(GEMS–TROPOMI) are GEMS NO2 VCD and EZA. The corrected GEMS product is unbiased relative to TROPOMI and shows a diurnal variation over source regions more consistent with Pandora than the operational product.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"27 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial analysis of PM2.5 using a concentration similarity index applied to air quality sensor networks","authors":"Rósín Byrne, John C. Wenger, Stig Hellebust","doi":"10.5194/amt-17-5129-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5129-2024","url":null,"abstract":"Abstract. Air quality sensor (AQS) networks are useful for mapping PM2.5 (particles with a diameter of 2.5 µm or smaller) in urban environments, but quantitative assessment of the observed spatial and temporal variation is currently underdeveloped. This study introduces a new metric – the concentration similarity index (CSI) – to facilitate a quantitative and time-averaged comparison of the concentration–time profiles of PM2.5 measured by each sensor within an air quality sensor network. Following development on a dataset with minimal unexplained variation and robust tests, the CSI function is used to represent an unbiased and fair depiction of the air quality variation within an area covered by a monitoring network. The measurement data is used to derive a CSI value for every combination of sensor pairs in the network, yielding valuable information on spatial variation in PM2.5. This new method is applied to two separate AQS networks, in Dungarvan and in the city of Cork, Ireland. In Dungarvan there was a lower mean CSI value (x‾CSI, Dungarvan=0.61, x‾CSI, Cork=0.71), indicating lower overall similarity between locations in the network. In both networks, the average diurnal plots for each sensor exhibit an evening peak in PM2.5 concentration due to emissions from residential solid-fuel burning; however, there is considerable variation in the size of this peak. Clustering techniques applied to the CSI matrices identify two different location types in each network; locations in central or residential areas that experience more pollution from solid-fuel burning and locations on the edge of the urban areas that experience cleaner air. The difference in mean PM2.5 between these two location types was 6 µg m−3 in Dungarvan and 2 µg m−3 in Cork. Furthermore, the examination of winter and summer months (January and May) indicates that higher PM2.5 levels during periods of increased residential solid-fuel burning act as a major driver for greater differences (lower similarity indices) between locations in both networks, with differences in mean seasonal CSI values exceeding 0.25 and differences in mean seasonal PM2.5 exceeding 7 µg m−3. These findings underscore the importance of including wintertime PM data in analyses, as the differences between locations is enhanced during periods when solid-fuel burning activities are at a peak. Additionally, the CSI method facilitates the assessment of the representativeness of the PM2.5 measured at regulatory air quality monitoring locations with respect to population exposure, showing here that location type is more important than physical proximity in terms of similarity and spatial representativeness assessments. Applying the CSI in this manner can allow for the placement of monitoring infrastructure to be optimised. The results indicate that the population exposure to PM2.5 in Dungarvan is moderately represented (x‾CSI=0.63) by the current regulatory monitoring location, and the regulatory monitoring location a","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"69 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing the iodide-adduct chemical ionization mass spectrometry (CIMS) quantitative method for toluene oxidation intermediates: experimental insights into functional-group differences","authors":"Mengdi Song, Shuyu He, Xin Li, Ying Liu, Shengrong Lou, Sihua Lu, Limin Zeng, Yuanhang Zhang","doi":"10.5194/amt-17-5113-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5113-2024","url":null,"abstract":"Abstract. Iodide-adduct time-of-flight chemical ionization mass spectrometry (I-CIMS) has been developed as a powerful tool for detecting the oxidation products of volatile organic compounds. However, the accurate quantification of species that do not have generic standards remains a challenge for I-CIMS application. To accurately quantify aromatic hydrocarbon oxidation intermediates, both quantitative and semi-quantitative methods for I-CIMS were established for intermediate species. The direct quantitative experimental results reveal a correlation between sensitivity to iodide addition and the number of polar functional groups (keto groups, hydroxyl groups, and acid groups) present in the species. Leveraging the selectivity of I-CIMS for species with diverse functional groups, this study established semi-quantitative equations for four distinct categories: monophenols, monoacids, polyphenol or diacid species, and species with multiple functional groups. The proposed classification method offers a pathway to enhancing the accuracy of the semi-quantitative approach, achieving an improvement in R2 values from 0.52 to beyond 0.88. Overall, the categorized semi-quantitative method was utilized to quantify intermediates formed during the oxidation of toluene under both low-NO and high-NO conditions, revealing the differential variations in oxidation products with varying levels of NOx concentration.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties","authors":"Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, Christiane Voigt","doi":"10.5194/amt-17-5161-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5161-2024","url":null,"abstract":"Abstract. This study investigates the sensitivity of two brightness temperature differences (BTDs) in the infrared (IR) window of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to various cloud parameters in order to understand their information content, with a focus on cloud thermodynamic phase. To this end, this study presents radiative transfer calculations, providing an overview of the relative importance of all radiatively relevant cloud parameters, including thermodynamic phase, cloud-top temperature (CTT), optical thickness (τ), effective radius (Reff), and ice crystal habit. By disentangling the roles of cloud absorption and scattering, we are able to explain the relationships of the BTDs to the cloud parameters through spectral differences in the cloud optical properties. In addition, an effect due to the nonlinear transformation from radiances to brightness temperatures contributes to the specific characteristics of the BTDs and their dependence on τ and CTT. We find that the dependence of the BTDs on phase is more complex than sometimes assumed. Although both BTDs are directly sensitive to phase, this sensitivity is comparatively small in contrast to other cloud parameters. Instead, the primary link between phase and the BTDs lies in their sensitivity to CTT (or more generally the surface–cloud temperature contrast), which is associated with phase. One consequence is that distinguishing high ice clouds from low liquid clouds is straightforward, but distinguishing mid-level ice clouds from mid-level liquid clouds is challenging. These findings help to better understand and improve the working principles of phase retrieval algorithms.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"27 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment and application of melting layer simulations for spaceborne radars within the RTTOV-SCATT v13.1 model","authors":"Rohit Mangla, Mary Borderies, Philippe Chambon, Alan Geer, James Hocking","doi":"10.5194/amt-2024-131","DOIUrl":"https://doi.org/10.5194/amt-2024-131","url":null,"abstract":"<strong>Abstract.</strong> Because of their high sensitivity to hydrometeors and their high vertical resolutions, space-borne radar observations are emerging as an undeniable asset for Numerical Weather Prediction (NWP) applications. The EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) NWP SAF (Satellite Application Facility) released an active sensor module within version 13 of the RTTOV (Radiative Transfer for TOVS) software with the goal of simulating both active and passive microwave instruments within a single framework using the same radiative transfer assumptions. This study provides an in-depth description of the radar simulator available within this software. In addition, this study proposes a revised version of the existing melting layer parametrization scheme of Bauer (2001) within the RTTOV-SCATT v13.1 model to provide a better fit to observations below the freezing level. Simulations are performed with and without melting layer schemes for the Dual precipitation radar (DPR) instrument onboard GPM using the ARPEGE (Action de Recherche Petite Echelle Grande Echelle) global NWP model running operationally at Météo-France for two different one-month periods (June, 2020 and January, 2021). Results for a case study over the Atlantic ocean show that the revised melting scheme produces more realistic simulations as compared to the default scheme both at Ku (13.5 GHz) and Ka (35.5 GHz) frequencies and these simulations are much closer to observations. A statistical assessment using more samples show significant improvement of the first-guess departure statistics with the revised scheme compared to the existing melting scheme. As a step further, this study showcases the use of melting layer simulations for the classification of precipitation (stratiform, convective and transition) using the Dual Frequency Ratio algorithm (DFR). The classification results also reveal a significant overestimation of the rain reflectivities in all hemispheres, which can either be due to a tendency of the ARPEGE model to produce a too large amount of convective precipitation, or to a mis-representation of the convective precipitation fraction within the forward operator.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"2 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel aerosol filter sampler for measuring the vertical distribution of ice-nucleating particles via fixed-wing uncrewed aerial vehicles","authors":"Alexander Julian Böhmländer, Larissa Lacher, David Brus, Konstantinos-Matthaios Doulgeris, Zoé Brasseur, Matthew Boyer, Joel Kuula, Thomas Leisner, Ottmar Möhler","doi":"10.5194/amt-2024-120","DOIUrl":"https://doi.org/10.5194/amt-2024-120","url":null,"abstract":"<strong>Abstract.</strong> A mobile sampler for the collection of aerosol particles on an uncrewed aerial vehicle (UAV) was developed and deployed during three consecutive Pallas Cloud Experiment campaigns in the vicinity of the Sammaltunturi Global Atmosphere Watch site (67°58’ N, 24°7’ E, 565 m above sea level). The sampler is designed to collect aerosol particles onto Nuclepore filters, which are subsequently analysed for the temperature-dependent number concentration of ice-nucleating particles of the sampled aerosol with the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT). This setup is an easy and flexible way to connect INP concentration measurements with cloud microphysics. The sampler was flown with a fixed-wing UAV in different altitudes up to 1000 m above ground level. The total flight time ranges from 1 hour to more than 1.5 hours, depending on environmental conditions. Pressure, temperature and relative humidity are also measured to provide information about the meteorological flight conditions. The flow over the filter was maintained by a micro-diaphragm pump, providing around 10 standard litres per minute over a small filter (diameter of 25 mm) and around 11 standard litres per minute over a larger filter (diameter of 47 mm) at a pressure corresponding to 500 m above sea level. For a typical flight time of 1.5 hours, this results in a sampled air volume of about 930 to 1000 standard litres per flight, giving an INP detection limit of approximately 1.1 × 10⁻³ and 1.0 × 10⁻³ INPs per standard litre, respectively. For comparison to the flight results, a similar setup was deployed at ground level. The comparison shows a clear distinction from the water and handling blank background for both setups, proving the technical feasibility of the setups. Furthermore, for some flights, a shift between the two INP populations can be seen, indicating that ground-based INP measurements deviate from the samples collected on-board the UAV.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"101 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new aerial approach for quantifying and attributing methane emissions: implementation and validation","authors":"Jonathan F. Dooley, Kenneth Minschwaner, Manvendra K. Dubey, Sahar H. El Abbadi, Evan D. Sherwin, Aaron G. Meyer, Emily Follansbee, James E. Lee","doi":"10.5194/amt-17-5091-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5091-2024","url":null,"abstract":"Abstract. Methane (CH4) is a powerful greenhouse gas that is produced by a diverse set of natural and anthropogenic emission sources. Biogenic methane sources generally involve anaerobic decay processes such as those occurring in wetlands, melting permafrost, or the digestion of organic matter in the guts of ruminant animals. Thermogenic CH4 sources originate from the breakdown of organic material at high temperatures and pressure within the Earth's crust, a process which also produces more complex trace hydrocarbons such as ethane (C2H6). Here, we present the development and deployment of an uncrewed aerial system (UAS) that employs a fast (1 Hz) and sensitive (1–0.5 ppb s−1) CH4 and C2H6 sensor and ultrasonic anemometer. The UAS platform is a vertical-takeoff, hexarotor drone (DJI Matrice 600 Pro, M600P) capable of vertical profiling to 120 m altitude and plume sampling across scales up to 1 km. Simultaneous measurements of CH4 and C2H6 concentrations, vector winds, and positional data allow for source classification (biogenic versus thermogenic), differentiation, and emission rates without the need for modeling or a priori assumptions about winds, vertical mixing, or other environmental conditions. The system has been used for direct quantification of methane point sources, such as orphan wells, and distributed emitters, such as landfills and wastewater treatment facilities. With detectable source rates as low as 0.04 and up to ∼ 1500 kg h−1, this UAS offers a direct and repeatable method of horizontal and vertical profiling of emission plumes at scales that are complementary to regional aerial surveys and localized ground-based monitoring.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"32 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification accuracy and compatibility across devices of a new Rapid-E+ flow cytometer","authors":"Branko Sikoparija, Predrag Matavulj, Isidora Simovic, Predrag Radisic, Sanja Brdar, Vladan Minic, Danijela Tesendic, Evgeny Kadantsev, Julia Palamarchuk, Mikhail Sofiev","doi":"10.5194/amt-17-5051-2024","DOIUrl":"https://doi.org/10.5194/amt-17-5051-2024","url":null,"abstract":"Abstract. The study evaluated a new model of a Plair SA airflow cytometer, Rapid-E+, and assessed its suitability for airborne pollen monitoring within operational networks. Key features of the new model are compared with the previous one, Rapid-E. A machine learning algorithm is constructed and evaluated for (i) classification of reference pollen types in laboratory conditions and (ii) monitoring in real-life field campaigns. The second goal of the study was to evaluate the device usability in forthcoming monitoring networks, which would require similarity and reproducibility of the measurement signal across devices. We employed three devices and analysed (dis-)similarities of their measurements in laboratory conditions. The lab evaluation showed similar recognition performance to that of Rapid-E, but field measurements in conditions when several pollen types were present in the air simultaneously showed notably lower agreement of Rapid-E+ with manual Hirst-type observations than those of the older model. An exception was the total-pollen measurements. Comparison across the Rapid-E+ devices revealed noticeable differences in fluorescence measurements between the three devices tested. As a result, application of the recognition algorithm trained on the data from one device to another led to large errors. The study confirmed the potential of the fluorescence measurements for discrimination between different pollen classes, but each instrument needed to be trained individually to achieve acceptable skills. The large uncertainty of fluorescence measurements and their variability between different devices need to be addressed to improve the device usability.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"217 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous measurement of greenhouse gases (CH4, CO2 and N2O) at atmospheric levels using a gas chromatography system","authors":"Michal Bucha, Dominika Lewicka-Szczebak, Piotr Wójtowicz","doi":"10.5194/egusphere-2024-2125","DOIUrl":"https://doi.org/10.5194/egusphere-2024-2125","url":null,"abstract":"<strong>Abstract.</strong> This article presents a simple method for determining greenhouse gases (CH₄, CO₂, N₂O) at ambient atmospheric levels using a chromatographic system. The novelty of the presented method is the application of a Carboxen 1010 PLOT capillary column for separation of trace gases – CH₄, CO₂ and N₂O – from air samples and their detection using a barrier discharge ionisation detector (BID). Simultaneously, a parallel molecular sieve column connected to a thermal conductivity detector (TCD) allowed the determination of CH₄, N₂ and O₂ concentrations from 0.1 to 100 %. The system was equipped with an autosampler transferring the samples without air contamination thanks to a vacuum pump-inert gas flushing option. Method validation was performed using commercial gas standards and undertaking a comparison measurement with a reference method: optical methods applying Picarro isotope and concentration instruments with cavity ring-down spectroscopy for CO₂, CH₄ and N₂O. A three-day continuous measurement series of the lowest GHG concentrations in ambient air and tests of typical vial sample measurements with increased GHG concentrations were performed. The advantage of this method is that the system is easy to set up and allows for simultaneous detection and analysis of the main GHGs in their ambient concentrations using one GC column and one detector, thereby omitting the need for an electron capture detector (ECD) containing radiogenic components for N₂O analysis and a flame ionisation detector (FID) with a methaniser for low-concentration CO₂ samples. The simplification of the system reduces analytical costs, facilitates instrument maintenance and improves measurement robustness.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"31 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}