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Improved mean field estimates from the Geostationary Environment Monitoring Spectrometer (GEMS) Level-3 aerosol optical depth (L3 AOD) product: using spatiotemporal variability 地球静止环境监测分光仪(GEMS)第三级气溶胶光学深度(L3 AOD)产品的改进型平均实地估算:利用时空变异性
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-06 DOI: 10.5194/amt-17-5221-2024
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
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.
摘要本研究介绍了卫星遥感数据处理方面的进展,主要侧重于地球静止环境监测分光仪(GEMS)的气溶胶光学深度(AOD)检索。将包括大气状态检索在内的二级(L2)数据转换为更高质量的三级(L3)数据在遥感中至关重要。我们的贡献在于对处理算法进行了两项新的改进。首先,我们将质量标志信息纳入权重计算,从而改进了反距离加权算法。通过分配与不可靠网格数量成反比的权重,该方法可以提供更精确的 L3 产品。我们通过模拟研究验证了这一方法,并将其应用于不同区域和波长的 GEMS AOD 数据。在算法中使用质量标志可以提供更准确的遥感分析。其次,我们采用了一种时空合并方法来处理 AOD 数据的空间和时间变异性,这有别于以往只关注空间变异性的方法。我们的方法考虑了跨越以往时间间隔的时间变化。此外,计算出的平均场显示出与以往研究相似的时空模式,证实了其捕捉真实世界现象的能力。最后,利用这一程序,我们计算出了 GEMS AOD 数据的平均场估计值,从而可以更深入地了解气溶胶对气候变化和公共健康的影响。
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引用次数: 0
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument 利用机器学习加强与 TROPOMI 卫星仪器一致性的偏差校正 GEMS 地球静止卫星二氧化氮产品
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-05 DOI: 10.5194/amt-17-5147-2024
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
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.
摘要。2020 年 2 月发射的地球静止环境监测分光计(GEMS)目前正在亚洲东部(南纬 5°-45°,东经 75-145°)上空以 3.5 × 7.7 平方公里的像素分辨率对二氧化氮(NO2)柱进行白天每小时连续观测。这些数据提供了独特的信息,有助于更好地了解氮氧化物(NOx)的来源、化学和传输,对大气化学和空气质量有影响,但直接验证的机会非常有限。在这里,我们用机器学习(ML)模型修正了来自全球环境监测系统(GEMS)的运行 2 级(L2)氮氧化物垂直柱密度(VCDs),使其与低地球轨道 TROPOspheric Monitoring Instrument(TROPOMI)更稀少但更成熟的观测数据相匹配,既保留了 GEMS 的数据密度,又使其与 TROPOMI 保持一致。我们首先对 GEMS 和 TROPOMI 运行的 L2 产品进行重新处理,使用来自 GEOS-Chem 化学传输模型的共同先验垂直 NO2 剖面(形状因子)。这消除了两个卫星产品之间的主要不一致性,并大大提高了它们与地面 Pandora NO2 VCD 数据在源区的一致性。然后,我们将 GEMS NO2 VCD 和检索参数作为预测变量,应用 ML 模型修正剩余差异 Δ(GEMS-TROPOMI)。我们利用 GEMS 和 TROPOMI NO2 VCDs 共址来训练 ML 模型,利用 TROPOMI 离轨观测来覆盖 GEMS 观测到的广泛有效天顶角 (EZAs)。Δ(GEMS-TROPOMI)的两个最重要的预测变量是 GEMS NO2 VCD 和 EZA。与 TROPOMI 相比,校正后的 GEMS 产品没有偏差,与运行产品相比,它在源区显示出与 Pandora 更一致的昼夜变化。
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引用次数: 0
Spatial analysis of PM2.5 using a concentration similarity index applied to air quality sensor networks 利用应用于空气质量传感器网络的浓度相似性指数对 PM2.5 进行空间分析
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-05 DOI: 10.5194/amt-17-5129-2024
Rósín Byrne, John C. Wenger, Stig Hellebust
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
摘要空气质量传感器(AQS)网络可用于绘制城市环境中 PM2.5(直径为 2.5 µm 或更小的颗粒)的分布图,但目前对观测到的空间和时间变化的定量评估还不完善。本研究引入了一个新指标--浓度相似性指数(CSI)--以方便对空气质量传感器网络中每个传感器测量到的 PM2.5 浓度-时间曲线进行定量和时间平均比较。CSI 功能是在一个数据集上开发的,该数据集具有最小的无法解释的变化和稳健的测试,CSI 功能用于对监测网络覆盖区域内的空气质量变化进行无偏公平的描述。测量数据用于推导网络中每对传感器组合的 CSI 值,从而获得 PM2.5 空间变化的宝贵信息。这种新方法分别应用于爱尔兰邓加文和科克市的两个空气质量监测网络。Dungarvan 的 CSI 平均值较低(x‾CSI, Dungarvan=0.61,x‾CSI, Cork=0.71),表明网络中不同地点之间的总体相似性较低。在这两个网络中,每个传感器的平均昼夜图都显示出由于居民固体燃料燃烧排放造成的傍晚 PM2.5 浓度峰值;但是,该峰值的大小存在很大差异。应用于 CSI 矩阵的聚类技术在每个网络中识别出两种不同的位置类型:位于中心或居民区的位置受到固体燃料燃烧的污染较多,而位于城市边缘的位置空气较清新。这两种地点类型的 PM2.5 平均值在 Dungarvan 相差 6 微克/立方米,在科克相差 2 微克/立方米。此外,对冬季和夏季月份(1 月和 5 月)的研究表明,在居民固体燃料燃烧增加的时期,PM2.5 水平较高,是造成两个网络中不同地点之间差异较大(相似性指数较低)的主要原因,季节性 CSI 平均值的差异超过了 0.25,季节性 PM2.5 平均值的差异超过了 7 µg m-3。这些发现强调了将冬季可吸入颗粒物数据纳入分析的重要性,因为在固体燃料燃烧活动高峰期,不同地点之间的差异会加大。此外,CSI 方法还有助于评估在空气质量监管监测点测量到的 PM2.5 在人口暴露方面的代表性,这表明在相似性和空间代表性评估方面,地点类型比物理距离更重要。以这种方式应用 CSI 可以优化监测基础设施的布置。结果表明,Dungarvan的PM2.5人口暴露在当前监管监测点的代表性一般(x‾CSI=0.63),而科克的监管监测点很好地代表了全市的PM2.5水平(x‾CSI=0.76)。
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引用次数: 0
Optimizing the iodide-adduct chemical ionization mass spectrometry (CIMS) quantitative method for toluene oxidation intermediates: experimental insights into functional-group differences 优化针对甲苯氧化中间产物的碘化加成化学电离质谱(CIMS)定量方法:对官能团差异的实验见解
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-05 DOI: 10.5194/amt-17-5113-2024
Mengdi Song, Shuyu He, Xin Li, Ying Liu, Shengrong Lou, Sihua Lu, Limin Zeng, Yuanhang Zhang
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.
摘要碘化物加成飞行时间化学电离质谱(I-CIMS)是检测挥发性有机化合物氧化产物的有力工具。然而,如何准确定量没有通用标准的物种仍然是 I-CIMS 应用的一大挑战。为了准确定量芳香烃氧化中间产物,针对中间产物建立了 I-CIMS 定量和半定量方法。直接定量实验结果表明,对碘化物加成的敏感性与物种中存在的极性官能团(酮基、羟基和酸基)数量之间存在相关性。利用 I-CIMS 对具有不同官能团的物种的选择性,本研究建立了四个不同类别的半定量方程:单酚、单酸、多酚或二酸物种以及具有多个官能团的物种。建议的分类方法为提高半定量方法的准确性提供了途径,使 R2 值从 0.52 提高到 0.88 以上。总之,在低氮和高氮条件下,利用分类半定量方法对甲苯氧化过程中形成的中间产物进行了定量分析,揭示了氧化产物随氮氧化物浓度变化而产生的不同变化。
{"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}
引用次数: 0
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties 空间成像仪的亮度温度差对探测云相的帮助有多大?关于云相和相关云特性的敏感性分析
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-05 DOI: 10.5194/amt-17-5161-2024
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, Christiane Voigt
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.
摘要本研究调查了旋转增强可见光和红外成像仪(SEVIRI)红外窗口中两个亮度温差(BTD)对各种云参数的敏感性,以了解其信息含量,重点是云的热力学相位。为此,本研究进行了辐射传递计算,概述了所有辐射相关云参数的相对重要性,包括热力学相位、云顶温度 (CTT)、光学厚度 (τ)、有效半径 (Reff) 和冰晶习性。通过分解云吸收和散射的作用,我们能够通过云光学特性的光谱差异来解释 BTD 与云参数的关系。此外,从辐射量到亮度温度的非线性转换所产生的效应也有助于形成 BTDs 的具体特征及其对 τ 和 CTT 的依赖性。我们发现,BTD 对相位的依赖比有时假设的要复杂得多。虽然两个 BTD 都对相位直接敏感,但与其他云参数相比,这种敏感性相对较小。相反,相位与 BTD 之间的主要联系在于它们对 CTT(或更广义的地表-云层温度对比)的敏感性,而 CTT 与相位相关。结果之一是,区分高冰云和低液云很简单,但区分中层冰云和中层液云却很困难。这些发现有助于更好地理解和改进相位检索算法的工作原理。
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引用次数: 0
Assessment and application of melting layer simulations for spaceborne radars within the RTTOV-SCATT v13.1 model 评估和应用 RTTOV-SCATT v13.1 模型中的空间雷达融化层模拟
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-04 DOI: 10.5194/amt-2024-131
Rohit Mangla, Mary Borderies, Philippe Chambon, Alan Geer, James Hocking
Abstract. 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.
摘要。由于对水文介质的高灵敏度和高垂直分辨率,星载雷达观测正在成为数值天气预报(NWP)应用中不可否认的资产。EUMETSAT(欧洲气象卫星应用组织)NWP SAF(卫星应用设施)在 RTTOV(TOVS 辐射传输)软件第 13 版中发布了一个有源传感器模块,目的是在一个框架内使用相同的辐射传输假设模拟有源和无源微波仪器。本研究深入介绍了该软件中的雷达模拟器。此外,本研究还对 RTTOV-SCATT v13.1 模型中现有的 Bauer(2001 年)熔化层参数化方案提出了一个修订版本,以便更好地拟合冰冻层以下的观测数据。利用在法国气象局运行的 ARPEGE(Action de Recherche Petite Echelle Grande Echelle)全球 NWP 模式,在两个不同的单月期间(2020 年 6 月和 2021 年 1 月),对 GPM 机载双降水雷达(DPR)仪器进行了有融化层方案和无融化层方案的模拟。大西洋上空的案例研究结果表明,与默认方案相比,修订后的融化方案在 Ku(13.5 千兆赫)和 Ka(35.5 千兆赫)频率下产生的模拟结果更加逼真,而且这些模拟结果更接近观测结果。使用更多样本进行的统计评估显示,与现有熔化方案相比,修订方案的第一猜测偏离统计有了显著改善。本研究进一步展示了利用双频比算法(DFR)将熔融层模拟用于降水分类(层状、对流和过渡)。分类结果还显示,所有半球的降雨反射率都被严重高估,这可能是由于 ARPEGE 模式倾向于产生过多的对流降水,也可能是由于前向算子错误地反映了对流降水部分。
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引用次数: 0
A novel aerosol filter sampler for measuring the vertical distribution of ice-nucleating particles via fixed-wing uncrewed aerial vehicles 通过固定翼无人驾驶飞行器测量冰核颗粒垂直分布的新型气溶胶过滤采样器
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-04 DOI: 10.5194/amt-2024-120
Alexander Julian Böhmländer, Larissa Lacher, David Brus, Konstantinos-Matthaios Doulgeris, Zoé Brasseur, Matthew Boyer, Joel Kuula, Thomas Leisner, Ottmar Möhler
Abstract. 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.
摘要。开发了一种移动采样器,用于在无人驾驶飞行器(UAV)上收集气溶胶粒子,并在连续三次帕拉斯云实验活动期间部署在萨马尔顿图里全球大气观测站附近(北纬 67°58',东经 24°7',海拔 565 米)。采样器的设计目的是将气溶胶颗粒收集到 Nuclepore 过滤器上,然后用卡尔斯鲁厄理工学院(INSEKT)的冰核分光仪分析采样气溶胶中冰核颗粒随温度变化的数量浓度。这种设置是将 INP 浓度测量与云微观物理联系起来的一种简便灵活的方法。采样器与固定翼无人机一起在离地面 1000 米的不同高度飞行。根据环境条件的不同,总飞行时间从 1 小时到 1.5 小时以上不等。还测量了压力、温度和相对湿度,以提供有关气象飞行条件的信息。过滤器的流量由微型隔膜泵维持,在相当于海平面以上 500 米的压力下,小型过滤器(直径 25 毫米)的流量约为每分钟 10 标准升,大型过滤器(直径 47 毫米)的流量约为每分钟 11 标准升。典型的飞行时间为 1.5 小时,因此每次飞行的采样空气量约为 930 至 1000 标准升,INP 检测限分别为每标准升约 1.1 × 10-3 和 1.0 × 10-3 INP。为了与飞行结果进行比较,还在地面部署了一个类似的装置。比较结果显示,两种装置都能明显区分水和处理空白背景,证明了装置在技术上的可行性。此外,在某些飞行中,可以看到两个 INP 群体之间存在偏移,这表明地面 INP 测量结果与无人机上采集的样本存在偏差。
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引用次数: 0
A new aerial approach for quantifying and attributing methane emissions: implementation and validation 量化和归因甲烷排放的新空中方法:实施与验证
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-04 DOI: 10.5194/amt-17-5091-2024
Jonathan F. Dooley, Kenneth Minschwaner, Manvendra K. Dubey, Sahar H. El Abbadi, Evan D. Sherwin, Aaron G. Meyer, Emily Follansbee, James E. Lee
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.
摘要甲烷(CH4)是一种强大的温室气体,由多种自然和人为排放源产生。生物源甲烷一般涉及厌氧腐烂过程,如发生在湿地、永久冻土融化或反刍动物内脏中有机物的消化过程。热生甲烷来源于地壳内高温高压下有机物的分解,这一过程也会产生乙烷(C2H6)等更复杂的痕量碳氢化合物。在此,我们介绍了无人驾驶航空系统(UAS)的开发和部署情况,该系统采用了快速(1 Hz)、灵敏(1-0.5 ppb s-1)的 CH4 和 C2H6 传感器以及超声波风速计。无人机系统平台是一架垂直起飞的六旋翼无人机(DJI Matrice 600 Pro,M600P),能够在 120 米的高度进行垂直剖面测量,并在 1 公里的范围内进行羽流采样。通过对 CH4 和 C2H6 浓度、矢量风和位置数据的同时测量,可以对来源进行分类(生物源与热源)、区分和排放率,而无需对风、垂直混合或其他环境条件进行建模或先验假设。该系统已被用于直接量化甲烷点源(如无主井)和分布式排放源(如垃圾填埋场和废水处理设施)。该无人机系统的可探测源速率低至 0.04,最高可达 1500 千克/小时-1,提供了一种直接、可重复的方法,可在一定范围内对排放羽流进行水平和垂直剖面分析,是区域航空调查和局部地面监测的补充。
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引用次数: 0
Classification accuracy and compatibility across devices of a new Rapid-E+ flow cytometer 新型 Rapid-E+ 流式细胞仪的分类准确性和设备兼容性
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-03 DOI: 10.5194/amt-17-5051-2024
Branko Sikoparija, Predrag Matavulj, Isidora Simovic, Predrag Radisic, Sanja Brdar, Vladan Minic, Danijela Tesendic, Evgeny Kadantsev, Julia Palamarchuk, Mikhail Sofiev
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.
摘要该研究评估了 Plair SA 气流细胞计数器的新型号 Rapid-E+,并评估了其是否适用于业务网络中的空气花粉监测。新模型的主要特征与之前的 Rapid-E 进行了比较。针对 (i) 实验室条件下的参考花粉类型分类和 (ii) 实际现场活动中的监测,构建并评估了一种机器学习算法。研究的第二个目标是评估设备在即将建立的监测网络中的可用性,这需要不同设备之间测量信号的相似性和可重复性。我们使用了三种设备,并分析了它们在实验室条件下测量结果的(不)相似性。实验室评估结果表明,Rapid-E+ 的识别性能与 Rapid-E 相似,但在空气中同时存在多种花粉类型的情况下进行的实地测量结果表明,Rapid-E+ 与人工赫斯特式观测结果的一致性明显低于旧型号。总花粉测量结果是个例外。对 Rapid-E+ 设备进行比较后发现,三种测试设备的荧光测量结果存在明显差异。因此,将根据一种设备的数据训练的识别算法应用到另一种设备上会导致很大的误差。这项研究证实了荧光测量在区分不同花粉类别方面的潜力,但每台仪器都需要经过单独训练才能达到可接受的技能。需要解决荧光测量的巨大不确定性和不同设备之间的可变性问题,以提高设备的可用性。
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引用次数: 0
Simultaneous measurement of greenhouse gases (CH4, CO2 and N2O) at atmospheric levels using a gas chromatography system 利用气相色谱系统同时测量大气中的温室气体(CH4、CO2 和 N2O
IF 3.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-09-03 DOI: 10.5194/egusphere-2024-2125
Michal Bucha, Dominika Lewicka-Szczebak, Piotr Wójtowicz
Abstract. 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.
摘要本文介绍了一种利用色谱系统测定环境大气中温室气体(CH4、CO2、N2O)含量的简单方法。该方法的新颖之处在于采用 Carboxen 1010 PLOT 毛细管色谱柱分离空气样品中的痕量气体(CH4、CO2 和 N2O),并使用阻挡放电离子化检测器 (BID) 进行检测。与此同时,与热导检测器(TCD)相连的平行分子筛色谱柱可测定 0.1 % 至 100 % 的 CH4、N2 和 O2 浓度。该系统配备了一个自动进样器,通过真空泵-惰性气体冲洗选项传输样品,不会造成空气污染。使用商用气体标准进行了方法验证,并与参考方法进行了对比测量:采用光学方法,使用 Picarro 同位素和浓度仪器以及空腔降环光谱法测量 CO2、CH4 和 N2O。对环境空气中最低温室气体浓度进行了为期三天的连续测量,并对温室气体浓度增加时的典型小瓶样品测量进行了测试。该方法的优点是系统设置简单,使用一个气相色谱柱和一个检测器就能同时检测和分析环境中主要温室气体的浓度,从而省去了用于分析一氧化二氮的含有辐射成分的电子捕获检测器(ECD)和用于分析低浓度二氧化碳样品的带有甲烷化器的火焰离子化检测器(FID)。系统的简化降低了分析成本,方便了仪器维护,提高了测量的稳定性。
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引用次数: 0
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Atmospheric Measurement Techniques
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