Richter, Andreas
Lade...
Preferred name
Richter, Andreas
Official Name
Richter, Andreas
2 Ergebnisse
Gerade angezeigt 1 - 2 von 2
- Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Evaluation and application of TROPOMI data: cloud retrieval algorithms and global shipping NO2 detection(2025-12-11); ; Satellite-based atmospheric measurements provide an important data basis for monitoring air pollution over long periods. Using the DOAS technique, tropospheric columns of nitrogen dioxide (NO2), a key air pollutant, can be retrieved from these observations. The TROPOspheric Monitoring Instrument (TROPOMI), launched on Sentinel-5P in October 2017, provides daily global measurements, significantly enhancing the ability to detect small-scale emissions like shipping plumes due to its high signal-to-noise ratio and spatial resolution. Clouds have a substantial impact on satellite measurements of tropospheric trace gases in the UV, VIS, and NIR spectral ranges. Therefore, NO2 retrievals rely on information on cloud fraction and cloud height from satellite cloud products. In the first part of this thesis, the cloud parameters from different cloud retrieval algorithms for TROPOMI are compared. Overall, the cloud products show qualitative consistency in processor version 1.x and reasonable agreement in processor version 2.x, except for the VIIRS cloud fraction. Differences between the cloud retrievals are found especially for low cloud heights and small cloud fractions, i.e., clouds that are particularly relevant for tropospheric trace gas retrievals. Cloud fractions primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters exhibit systematic issues related to across-track dependence, and the consistency among these parameters depends strongly on how the data is filtered. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data. Shipping is an important source of NOx emissions worldwide, negatively affecting marine environments and human health. The second part of the thesis uses the TROPOMI tropospheric NO2 slant columns (tSCDs) to qualitatively identify global shipping routes. Preprocessing techniques, including iterative high-pass and Fourier filtering, markedly improve the detection of shipping lanes, revealing many previously undetectable routes. The analysis examines the impact of high-pass filter box sizes, demonstrating that smaller sizes enhance the visibility of narrow shipping features, whereas larger box sizes increase overall NO2 signals. Additionally, various flagging criteria are investigated that affect NO2 signal distribution, highlighting the critical importance of careful selection for accurate emission monitoring. Filtered TROPOMI NO2 tSCDs over oceans show a strong correlation with shipping activities, as confirmed by comparison with the CAMS-GLOB-SHIP inventory, and reveal unknown shipping routes. TROPOMI also effectively captures NO2 emissions from oil and gas platforms. Finally, the filtered TROPOMI tropospheric NO2 vertical columns (tVCDs) are compared with those from the CAMS global model. While both datasets show NO2 enhancements over global shipping lanes, the CAMS NO2 values are significantly larger than the TROPOMI measurements in the North Atlantic and strongly depend on the masking threshold in the high-pass filtering method in the South Atlantic.Dissertation43 45 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Investigating the role of glyoxal using satellite and MAX-DOAS measurements(2016-06-21); ; ; Volatile Organic Compounds (VOC) are key species in tropospheric chemistry, air pollution and climate. The largest fraction of VOC is emitted from natural sources, but significant contributions are also attributed to anthropogenic emissions and vegetation fires. Despite many studies estimating VOC amounts in the atmosphere and identifying their sources, the uncertainties in estimation are large. Glyoxal (CHOCHO), the smallest and most abundant of the alpha-dicarbonyls in the atmosphere, is an intermediate product in the oxidation of most VOC and an indicator of secondary aerosol formation in the atmosphere. Glyoxal in combination with other VOC (e.g. formaldehyde: HCHO) can be used for source identification of VOC. Glyoxal has been measured from space since 2003 by the SCIAMACHY and GOME-2 (MetOp-A) instruments and provides a unique global long-term dataset. The focus of this thesis is to retrieve glyoxal from measurements by the OMI instrument, to improve the SCIAMACHY and GOME-2 (MetOp-A and-B) analysis, and to investigate the resulting long-term datasets. The first part of this thesis focuses on the development of an improved retrieval for glyoxal from OMI measurements. From sensitivity tests, optimized fit parameters are determined. Two different approaches to reduce the interference of liquid water absorption over oceanic regions are evaluated, achieving a significant reduction of the number of negative columns over clear water regions. The impact of using different absorption cross-sections for water vapour is evaluated and only small differences are found. Finally, a high temperature (boundary layer ambient 294 K) absorption cross-section of nitrogen dioxide (NO2) is introduced in the DOAS retrieval to account for potential interferences with NO2 over regions with large anthropogenic emissions, leading to improved fit quality over these areas. In a sensitivity test, a spectrum of backscattered solar radiation over the Pacific Ocean is used as a reference spectrum, in order to reduce the offsets ("stripes") that sometimes are observed between viewing directions in the OMI instrument. The new retrieval has also been applied to measurements from SCIAMACHY and GOME-2 (MetOp-A and-B) instruments. Using the new CHOCHO dataset, the combination of four instruments provides more than 12 years of glyoxal measurements, which are used for the investigation of the temporal variability of VOC on a global scale. The link between vegetation, fires, anthropogenic activity, and glyoxal columns is investigated both globally and locally. This provides a general picture of where glyoxal comes from and what its temporal behaviour is depending on the region. CHOCHO and HCHO are used synergistically for the identification of VOC emission sources by computing their ratio and correlating it with indicators of biogenic emissions, fires, and anthropogenic activities, giving important information for assigning the ratios of glyoxal to formaldehyde to emission sources of VOC. In a case study, mapped averages are computed for a fire event in Russia between mid-July and mid-August 2010. Enhanced CHOCHO levels are found in close spatial and temporal proximity to elevated levels of fire radiate power, demonstrating that pyrogenic emissions can be clearly identified in the new CHOCHO data product. Also, for the first time long-range transport of glyoxal in the atmosphere has been clearly identified, where elevated levels of glyoxal follow the trajectories of simulated air masses. Finally, CHOCHO, HCHO, and NO2 columns have been retrieved from ground based measurements for two MAX-DOAS stations, which are part of the BREDOM network. Diurnal and seasonal variations have been computed for the three species and also the glyoxal to formaldehyde and formaldehyde to nitrogen dioxide ratios. The results have been compared to results from the satellite observations and with other studies.Dissertation938 251