550 Geowissenschaften
Refine
Year of publication
Document Type
- Article (888)
- Doctoral Thesis (194)
- Contribution to a Periodical (32)
- Book (26)
- Working Paper (22)
- Part of Periodical (20)
- Conference Proceeding (18)
- Part of a Book (9)
- Diploma Thesis (8)
- diplomthesis (7)
Language
Keywords
- climate change (11)
- Climate change (7)
- Klima (7)
- Klimaänderung (7)
- Modellierung (7)
- COSMO-CLM (6)
- Klimawandel (6)
- precipitation (6)
- Atmospheric chemistry (5)
- Deutschland (5)
Institute
- Geowissenschaften (775)
- Geowissenschaften / Geographie (135)
- Biodiversität und Klima Forschungszentrum (BiK-F) (61)
- Geographie (61)
- Senckenbergische Naturforschende Gesellschaft (54)
- Präsidium (44)
- Extern (28)
- Biowissenschaften (22)
- Institut für Ökologie, Evolution und Diversität (8)
- Physik (8)
Living on the edge: environmental variability of a shallow late Holocene cold-water coral mound
(2022)
Similar to their tropical counterparts, cold-water corals (CWCs) are able to build large three-dimensional reef structures. These unique ecosystems are at risk due to ongoing climate change. In particular, ocean warming, ocean acidification and changes in the hydrological cycle may jeopardize the existence of CWCs. In order to predict how CWCs and their reefs or mounds will develop in the near future one important strategy is to study past fossil CWC mounds and especially shallow CWC ecosystems as they experience a greater environmental variability compared to other deep-water CWC ecosystems. We present results from a CWC mound off southern Norway. A sediment core drilled from this relatively shallow (~ 100 m) CWC mound exposes in full detail hydrographical changes during the late Holocene, which were crucial for mound build-up. We applied computed tomography, 230Th/U dating, and foraminiferal geochemical proxy reconstructions of bottom-water-temperature (Mg/Ca-based BWT), δ18O for seawater density, and the combination of both to infer salinity changes. Our results demonstrate that the CWC mound formed in the late Holocene between 4 kiloannum (ka) and 1.5 ka with an average aggradation rate of 104 cm/kiloyears (kyr), which is significantly lower than other Holocene Norwegian mounds. The reconstructed BWTMg/Ca and seawater density exhibit large variations throughout the entire period of mound formation, but are strikingly similar to modern in situ observations in the nearby Tisler Reef. We argue that BWT does not exert a primary control on CWC mound formation. Instead, strong salinity and seawater density variation throughout the entire mound sequence appears to be controlled by the interplay between the Atlantic Water (AW) inflow and the overlying, outflowing Baltic-Sea water. CWC growth and mound formation in the NE Skagerrak was supported by strong current flow, oxygen replenishment, the presence of a strong boundary layer and larval dispersal through the AW, but possibly inhibited by the influence of fresh Baltic Water during the late Holocene. Our study therefore highlights that modern shallow Norwegian CWC reefs may be particularly endangered due to changes in water-column stratification associated with increasing net precipitation caused by climate change.
Oceanic islands only comprise a small amount of the Earth’s land area but harbour a disproportionate amount of global biodiversity. This vast diversity is not only reflected in the taxonomic uniqueness of island biota but also in the remarkable evolution of functional traits. Functional traits, i.e. measurable characteristics that strongly influence the fitness of species, determine how a species responds to its environment and can help to gain more insights into the biogeographical, ecological and evolutionary processes that have shaped island biodiversity. However, research in island biogeography has primarily focused on species richness, and knowledge of functional trait patterns on oceanic islands is scarce. Hence, in this dissertation, I have explored how trait-based approaches can increase our understanding of how biodiversity on oceanic islands assembles and how it is driven by the environment. The Canary Islands (Spain) are a particularly suitable model system to investigate patterns and drivers of biodiversity. The archipelago is characterised by a high variation in environmental heterogeneity and inhabits a unique and well-described native flora. Therefore, I have investigated five principal research questions using the flora (Spermatophytes) of the Canary Islands as a study object. First, I have analysed how climate and biogeography shape the assembly of the Canary Islands flora using a novel trait-based approach. Second, the question of whether rare climates link to functional trait distinctiveness in the native Canary Islands flora was addressed. Third, I have examined how intraspecific trait variation is represented in the native flora of oceanic islands focusing on the succulent scrub of La Palma (Canary Islands). Fourth, this dissertation investigated whether scientific floras can be reliable sources for trait data of plants native to oceanic islands. Finally, I have explored how climate change may impact the native Canary Islands flora by analysing possible climate change-induced shifts in plant species distribution and plant traits.
The results of my dissertation expand the understanding of the importance of biogeography and the environment in determining the functional composition of island floras. I have assessed that traits of endemic plant species did not expand the functional trait space of the Canary Islands but were packed with the ones of non-endemic species. This result hints at a trait convergence in endemic species, possibly driven by non-adaptive speciation processes. Moreover, I have evidenced that humidity is a critical driver of functional diversity in native plant assemblages and particularly leads to a high trait convergence in arid environments via environmental filtering. In contrast, alien species have expanded the Canary Islands flora’s functional trait space. I further have shown that in contrast to native species assemblages, alien species assemblages are characterised by an increasing functional diversity with increasing aridity. This contrasting pattern of functional diversity could pose a potential risk to the native flora of the Canary Islands as a low functional diversity is expected to reduce the resilience of species assemblages to the establishment of more functionally diverse alien plant species. However, in this dissertation, I also have revealed that endemic plant species on the Canary Islands show a high intraspecific variation in arid environments, possibly as an adaptation to environmental stress. Intraspecific variation could help endemic plant species have a competitive advantage over alien species and be more resilient to environmental changes. Furthermore, in this dissertation, I have shown that scientific floras and taxonomic monographs could be used to gain information on quantitative functional traits of plants native to oceanic islands. This finding is particularly relevant for advances in trait-based research, as coverage of trait data for oceanic island floras is extremely poor in global trait databases. Hence, for some of the studies included in this dissertation, trait data were retrieved from scientific floras and taxonomic monographs and used to answer novel scientific research questions. Thus, I have used trait data from the literature to analyse the effect of climate change on the range size of plants native to the Canary Islands. Identifying plant species of particular conservation concern is critical on oceanic islands as many island species have limited distributions and small population sizes, and their niche tracking is impeded by insularity. I have revealed that single-island endemic plants gain less and lose more climatically suitable areas than archipelago endemic and non-endemic native plants due to a climate change-induced decrease in precipitation until 2100...
Diamant hat besondere physikalische und optische Eigenschaften sowie eine starke Resistenz gegenüber Strahlenschädigung. Diese Eigenschaften ermöglichen eine vielfältige Anwendung von Diamant in Wissenschaft und Technik, wie zum Beispiel als Sensormaterial in Strahlungsdetektoren.
Kubisches Zirconiumdioxid (ZrO2) wird aufgrund seiner mechanisch und optisch ähnlichen Eigenschaften unter anderem an Stelle von Diamant eingesetzt. Es ist ebenfalls ein geeignetes Material für viele technische Anwendungen und wird durch seine Strahlenresistenz in Strahlungsumgebungen verwendet. Da beide Materialien in diesem Anwendungsbereich hoher energetischer Strahlung ausgesetzt sind, sind Reaktionen auf die Bestrahlung wie etwa strukturelle Veränderungen oder die Änderungen von Materialeigenschaften von großem Interesse.
In der vorliegenden Arbeit wurde die Morphologie, Struktur und physikalischen Eigenschaften von Diamant und Yttriumoxid-stabilisiertem kubischem ZrO2 nach der Bestrahlung mit 14 MeV Au-Ionen und 1.6 GeV Au-Ionen untersucht. Die durch die Bestrahlung verursachten Veränderungen der Oberflächen und der bestrahlten Volumina wurden mit diversen komplementären analytischen Methoden charakterisiert, bewertet und für die verschiedenen Materialien und Ionenenergien verglichen.
Mittels Röntgenfluoreszenzmessungen wurde die Verteilung und Menge an implantiertem Au semi-quantitativ ermittelt. Die Oberflächen der Proben wurden mit optischer Mikroskopie, Rasterkraftmikroskopie, Rasterelektronenmikroskopie, Röntgenreflektometrie und Elektronenrückstreubeugung untersucht. Strukturelle Veränderungen wurden mit Raman-Spektroskopie analysiert. Der elektrische Widerstand, die Dichte, die Härte sowie das Ätzverhalten der bestrahlten Proben wurden ermittelt und geben Auskunft über die Änderung physikalischer Eigenschaften der Materialien.
Diamant und kubisches ZrO2 reagieren sehr unterschiedlich auf die Bestrahlung mit Au-Ionen gleicher Energien und Fluenzen. Die Diamantproben zeigen nach der Bestrahlung mit 14 MeV Au-Ionen deutliche Veränderungen und Schädigungen der Oberfläche sowie des bestrahlten Volumens. Es wird eine Änderung der Struktur, der Dichte, der Härte, des elektrischen Widerstands sowie des Ätzverhaltens der Proben beobachtet, was auf die Amorphisierung von Diamant zurückgeführt wird. Kubisches ZrO2 ist deutlich strahlungsresistenter gegenüber der Bestrahlung mit 14 MeV Au-Ionen. Es werden keine signifikanten strukturellen Änderungen im getesteten Fluenzbereich beobachtet.
Die mit 1.6 GeV Au-Ionen bestrahlten Diamanten zeigen nur geringe Schädigungen und keine deutliche Änderung der Struktur oder der physikalischen Eigenschaften. Die kubischen ZrO2 Proben sind als Folge der Bestrahlung mit 1.6 GeV Au-Ionen zerbrochen, was auf hohe interne Spannung durch Defektbildung zurückgeführt wird.
Extreme convective precipitation events are among the most severe hazards in central Europe and are expected to intensify under global warming. However, the degree of intensification and the underlying processes are still uncertain. In this thesis, recent advances in continuous, radar-based precipitation monitoring and convection-permitting climate modeling are used to investigate Lagrangian properties of convective rain cells such as precipitation intensity, cell area, and precipitation sum and their relationship to large-scale, environmental conditions.
Firstly, convective precipitation objects are tracked in a gauge-adjusted radar-data set and the properties of these cells are related to large-scale environmental variables to investigate the observed super-Clausius-Clapeyron (CC) scaling of convective extreme precipitation. The Lagrangian precipitation sum of convective cells increases with dew point temperature at rates well above the CC-rate with increasing rates for higher dew point temperatures. These varying, high rates are caused by a covarying increase of CAPE with dew point temperature as well as the effect of high vertical wind shear causing an increase in cell area and thus precipitation sum. At the same time, cells move faster at high vertical wind shear so that Eulerian scaling rates are lower than Lagrangian but still above the CC-rate. The results show that wind shear and static instability need to be taken into account when transferring precipitation scaling under current climate conditions to future conditions. Secondly, the representation of convective cell properties in the convection-permitting climate model COSMO-CLM is evaluated. The model can simulate the observed frequency distributions of cell properties such as lifetime, area, mean and maximum intensity, and precipitation sum. The increase of area and intensity with lifetime is also well captured despite an underestimation of the intensity of the most severe cells. Furthermore, the model can represent the temperature scaling of intensity, area, and precipitation sum but fails to simulate the observed increase of lifetime. Thus, the model is suitable to study climatologies of convective storms in Germany. Thirdly, two COSMO-CLM projections at the end of the century under emission scenario RCP8.5 were investigated. While the number of convective cells and their lifetime remain approximately constant compared to present conditions, intensity and area increase strongly. The relative increase of intensity and area is largest for the highest percentiles meaning that extreme events intensify the most. The characteristic afternoon maximum of convective precipitation is damped, and shifted to later times of day which leads to an increase of nighttime precipitation in the future. Scaling rates of cell properties with dew point temperature are nearly identical in present and future in the simulation driven by the EC-Earth model which means that the upper limit of cell properties like intensity, area, and precipitation sum could be predicted from near-surface dew point temperature. However, this result could not be reproduced by the simulation driven by MIROC5 and needs further investigation.
Auf der Suche nach Erfahrungen in den Tropen setzte der Geografiestudent Jürgen Runge das erste Mal in Togo seinen Fuß auf den afrikanischen Kontinent. Aus einem etwas holprigen Start wurde eine große Zuneigung zu Zentral- und Westafrika. Heute ist Runge Direktor des Zentrums für Interdisziplinäre Afrikaforschung an der Goethe-Universität und forscht gemeinsam mit Partnern der Region vor allem zu Landschaftsentwicklung, Flusssedimenten und Klimawandel.
Cratonic eclogite is the product of oceanic crust subduction into the subcontinental lithospheric mantle, and it also is a fertile diamond source rock. In contrast to matrix minerals in magma-borne xenoliths, inclusions in diamond are shielded from external fluids, retaining more pristine information on the state of the eclogite source at the time of encapsulation. Vanadium is a multi-valent element and a widely used elemental redox proxy. Here, we show that that xenolithic garnet has lower average V abundances than garnet inclusions. This partly reflects crystal-chemical controls, whereby higher average temperatures recorded by inclusions, accompanied by enhanced Na2O and TiO2 partitioning into garnet, facilitate V incorporation at the expense of clinopyroxene. Unexpectedly, although diamond formation is strongly linked to metasomatism and xenoliths remained open systems, V concentrations are similar for bulk eclogites reconstructed from inclusions and from xenoliths. This suggests an oxygen-conserving mechanism for eclogitic diamond formation, and implies that eclogite is an efficient system to buffer fO2 over aeons of lithospheric mantle modification by subduction-derived and other fluids.
The Altenberg–Teplice Volcanic Complex (ATVC) is a large ~ NNW–SSE trending volcano-plutonic system in the southern part of the Eastern Erzgebirge (northern Bohemian Massif, south-eastern Germany and northern Czech Republic). This study presents high precision U–Pb CA-ID-TIMS zircon ages for the pre-caldera volcano-sedimentary Schönfeld–Altenberg Complex and various rocks of the caldera stage: the Teplice rhyolite, the microgranite ring dyke, and the Sayda-Berggießhübel dyke swarm. These data revealed a prolonged time gap of ca. 7–8 Myr between the pre-caldera stage (Schönfeld–Altenberg Complex) and the climactic caldera stage. The volcanic rocks of the Schönfeld–Altenberg Complex represent the earliest volcanic activity in the Erzgebirge and central Europe at ca. 322 Ma. The subsequent Teplice rhyolite was formed during a relatively short time interval of only 1–2 Myr (314–313 Ma). During the same time interval (314–313 Ma), the microgranite ring dyke intruded at the rim of the caldera structure. In addition, one dyke of the Sayda-Berggiesshübel dyke swarm was dated at ca. 314 Ma, while another yielded a younger age (ca. 311 Ma). These data confirm the close genetic and temporal relationship of the Teplice rhyolite, the microgranite ring dyke, and (at least part of) the Sayda-Berggießhübel dyke swarm. Remarkably, the caldera formation in the south of the Eastern Erzgebirge (caldera stage of ATVC: 314–313 Ma) and that in the north (Tharandt Forest caldera: 314–312 Ma) occurred during the same time. These data document a large ~ 60 km NNW–SSE trending magmatic system in the whole Eastern Erzgebirge. For the first time, Hf-O-isotope zircon data was acquired on the ring dyke from the ATVC rocks to better characterize its possible sources. The homogeneous Hf-O-isotope zircon data from the microgranite ring dyke require preceding homogenization of basement rocks. Some small-scale melts that were produced during Variscan amphibolite-facies metamorphism show similar Hf-O-isotope characteristics and can therefore be considered as the most probable source for the microgranite ring dyke melt. In addition, a second source with low oxygen isotope ratios (e.g. basic rocks) probably contributed to the melt and possibly triggered the climactic eruption of the Teplice rhyolite as well as the crystal-rich intrusion of the ring dyke.
The climate system is one of the classical examples of a complex dynamical system consisting of interacting sub-systems through mass, momentum, and energy exchange across various spatial and temporal scales. This thesis aims to detect and quantify sub-component interactions from an information exchange (IE) perspective. For this purpose, IE estimators derived from information theory are explored and applied to the available climate data obtained from observations, reanalysis, global and regional climate models. Specifically, this thesis investigates the usefulness of information theory methods for process-oriented climate model evaluation.
Firstly, methods derived from the concepts of information theory such as transfer entropy and information flow along with their linear and non-linear estimation techniques are initially tested and applied to idealized two-dimensional dynamical systems. The results revealed an expected direction and magnitude of IE providing insights into underlying dynamics. However, as expected the linear estimators are robust for linear systems but fail for non-linear systems. Though the non-linear estimators (kernel and kraskov) showed expected results for all the idealized systems, their free tuning parameters are to be tested for consistent results. Moreover, these methods are sensitive to the available time series length.
A real world example case study involving the dynamics between the Indian and Pacific oceans revealed a physically consistent bi-directional IE. However, unexpected IE was detected in the example of North Atlantic and European air temperatures indicating hidden drivers. Though IE provides insights into system dynamics, the availability of time series length and the system at hand must be carefully taken into account before inferring any possible interpretations of the results.
Quantifying the IE from El-Ni\~{n}o southern oscillation (ENSO) and Indian Ocean Dipole (IOD) to the Indian Summer Monsoon Rainfall (ISMR) with the observational and reanalysis data sets revealed that both ENSO and IOD are synergistic predictors for the inter-annual variability of the ISMR over central India i.e., the monsoon core region. Though the investigated three Global Climate Models (GCM) could not reveal the underlying IE dynamics of ENSO, IOD, and ISMR, a Regional Climate Model (RCM) simulation downscaling one of the GCMs with realistic large scale signals across the lateral boundaries showed good agreement with the observations.
Evaluating a coupled regional climate modeling system driven by two different global data sets with IE estimators revealed significant differences between the process chains linking the north-west Mediterranean sea surface temperatures, evaporation, wind speed, and the Vb-cyclone induced precipitation over Danube, Odra, and Elbe catchments in the historical period (1951-2005). Detailed investigation revealed that the north-west Mediterranean Sea in the coupled regional simulation driven by ERA-20C reanalysis corresponded to the Vb-cyclone precipitation over the three catchments while no such correspondence is noted in the EC-EARTH driven simulation. This discrepancy is attributed to the inheritance of the simulation biases from GCM into the RCM. In the future period (1965-2099), no significant changes in the processes are noted from the simulation.
Overall, this thesis used IE estimators in investigating the underlying dynamics of climate system and climate models. The estimators proved useful in providing insights into climate system dynamics assisting in a process based climate model evaluation.
Carbon is an element that controls planetary habitability, and is fundamental for life on Earth. Its behaviour has important consequences for the global climate system, the origin and evolution of life on Earth. While the biosphere and atmosphere’s carbon cycle only accounts for less than 1% of the global carbon budget, hidden reservoirs of deep carbon in the Earth’s interior comprise the predominant storage of carbon on the planet. At the Earth’s surface, 60-70 % of carbon is hosted by carbonate minerals, which are then transported to the Earth’s interior, mainly in the form of sediments, by subduction of the oceanic lithosphere. Subducting plates are subjected to decarbonation, dehydration, and melting with CO2 release via supra-subduction volcanism. Nevertheless, part of the subducted carbonates’ may survive and be further transported to the deep mantle. Direct evidence of the existence of carbonates in the Earth’s interior, possibly reaching down to the lower mantle, comes from the finding of syngenetic inclusions of carbonates in diamonds and mantle xenoliths. The presence of carbonates in the deep Earth has a critical effect on the physical properties of the mantle. Melting and chemical speciation of the mantle are strongly affected by the form of C and carbonate stability. Therefore, the study of the stability and physical properties of carbonates at high pressures and temperatures is fundamental, because understanding the processes involved in the deep carbon cycle helps to improve our picture of the whole mantle.
The systematic characterization of the elastic properties of carbonates as a function of their structure and chemical composition is of great importance because it may allow to identify their presence and distribution by seismology. Inverting seismic observations to successfully constrain the chemical composition and mineralogy of the Earth’s interior requires knowledge of the physical properties of all possible Earth’s materials at pressures and temperatures applicable to the Earth’s interior. Up to now, a multitude of studies has focused on the construction of phase diagrams and structural transitions by means of X-ray diffraction and vibrational spectroscopy experiments.
Few studies are available on the complete elastic tensor of carbonates, however most of the datasets are not accompanied by an accurate characterization of the samples, which are often solid solutions and the exact chemical composition, density or the details about the experimental methods used are not presented. The aim of this thesis is to study the effect of chemical composition on the elastic properties of carbonates, providing a reliable dataset on the elasticity of the main carbonates. In particular, the elastic properties of crystalline aragonite, CaCO3, and Fe-dolomite, (Ca, Mg, Fe)(CO3)2, with different compositions were studied by Brillouin spectroscopy at ambient conditions. Brillouin spectroscopy was also used to investigate the elastic behaviour of amorphous calcium carbonate samples with different water contents (up to 18 wt%) at high pressures, up to 20 GPa.
Furthermore, the importance of cationic substitution on the structure and high pressure behaviour of carbonates was investigated by studying a synthetic CaCO3-SrCO3 solid solution at ambient conditions and at high pressures, up to 10 GPa, by single crystal X-ray diffraction. Finally, the study of the effect of composition on the elastic properties of families of isostructural solids was also extended to a different class of materials, the metal guanidinium formates. The elasticity of a family of perovskite metal organic frameworks, metal guanidinium formates C(NH2)3MII(HCOO)3, with MII =Mn, Zn, Cu, Co, Cd and Ca was investigated by combining Brillouin spectroscopy, resonant ultrasound spectroscopy, density functional theory and thermal diffuse scattering analysis.
Reise ohne Wiederkehr
(2022)
Seasonal forecasting systems still have difficulties predicting temperature over continental regions, while their performance is better over some maritime regions. On the other hand, the land surface is a substantial source of (sub-)seasonal predictability. A crucial land surface component in focus here is the snow cover, which stores water and modulates the surface radiation balance. This paper’s goal is to attribute snow cover seasonal forecasting biases and lack of skill to either initialization or parameterization errors. For this purpose, we compare the snow representation in five seasonal forecasting systems (from DWD, ECMWF, Météo-France, CMCC, and ECCC) and their performances in predicting snow and 2-m temperature over a Siberian region against ERA5 reanalysis and station data. Although all systems use similar atmospheric and land initialization approaches and data, their snow and temperature biases differ in sign and amplitude. Too-large initial snow biases persist over the forecast period, delaying and prolonging the melting phase. The simplest snow scheme (used in DWD’s system) shows too-early and fast melting in spring. However, systems including multi-layer snow schemes (Météo-France and CMCC) do not necessarily perform better. Both initialization and parameterization are causes of snow biases, but, depending on the system, one can be more dominant.
Although global- and catchment-scale hydrological models are often shown to accurately simulate long-term runoff time-series, far less is known about their suitability for capturing hydrological extremes, such as droughts. Here we evaluated simulations of hydrological droughts from nine catchment scale hydrological models (CHMs) and eight global scale hydrological models (GHMs) for eight large catchments: Upper Amazon, Lena, Upper Mississippi, Upper Niger, Rhine, Tagus, Upper Yangtze and Upper Yellow. The simulations were conducted within the framework of phase 2a of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). We evaluated the ability of the CHMs, GHMs and their respective ensemble means (Ens-CHM and Ens-GHM) to simulate observed hydrological droughts of at least one month duration, over 31 years (1971–2001). Hydrological drought events were identified from runoff-deficits and the Standardised Runoff Index (SRI). In all catchments, the CHMs performed relatively better than the GHMs, for simulating monthly runoff-deficits. The number of drought events identified under different drought categories (i.e. SRI values of -1 to -1.49, -1.5 to -1.99, and ≤-2) varied significantly between models. All the models, as well as the two ensemble means, have limited abilities to accurately simulate drought events in all eight catchments, in terms of their occurrence and magnitude. Overall, there are opportunities to improve both CHMs and GHMs for better characterisation of hydrological droughts.
PolarCAP – A deep learning approach for first motion polarity classification of earthquake waveforms
(2022)
Highlights
• We present PolarCAP, a deep learning model that can classify the polarity of a waveform with a 98% accuracy.
• The first-motion polarity of seismograms is a useful parameter, but its manual determination can be laborious and imprecise.
• We demonstrate that in several cases the model can assign trace polar-ity more accurately than a human analyst.
Abstract
The polarity of first P-wave arrivals plays a significant role in the effective determination of focal mechanisms specially for smaller earthquakes. Manual estimation of polarities is not only time-consuming but also prone to human errors. This warrants a need for an automated algorithm for first motion polarity determination. We present a deep learning model - PolarCAP that uses an autoencoder architecture to identify first-motion polarities of earth-quake waveforms. PolarCAP is trained in a supervised fashion using more than 130,000 labelled traces from the Italian seismic dataset (INSTANCE) and is cross-validated on 22,000 traces to choose the most optimal set of hyperparameters. We obtain an accuracy of 0.98 on a completely unseen test dataset of almost 33,000 traces. Furthermore, we check the model generalizability by testing it on the datasets provided by previous works and show that our model achieves a higher recall on both positive and negative polarities.
Atmospheric particles play an important role in the radiative balance of the Earth, as well as they affect human health and air quality. Hence, the chemical characterization constitutes a crucial task to determinate their properties, sources and fate. Particularly, the analysis of nanoparticles (d<100 nm) represents an analytical challenge, since these particles are abundant in number but have very little mass.
This accumulative thesis focuses on the chemical characterization of nanoparticles, performed in both laboratory and field studies. Here, I present four manuscripts, two of which are my main project as a lead author.
The first manuscript (Caudillo et al., 2021) focuses on the gas and the particle phase originated from biogenic precursor gases (α-pinene and isoprene). The experiments were performed in the CLOUD chamber at CERN to simulate pure biogenic new particle formation. Both gas and particle phases are measured with a nitrate CI-APi-TOF mass spectrometer, while the TD-DMA is coupled to it for particle-phase measurements, this setup allows a direct comparison as both measurements use the identical chemical ionization and detector. This study demonstrates the suitability of the TD-DMA for measuring newly formed nanoparticles and it confirms that isoprene suppresses new particle formation but contributes to the growth of newly formed particles.
The second manuscript (Caudillo et al., 2022) presents an intercomparison of four different techniques (including the TD-DMA) for measuring the chemical composition of SOA nanoparticles. The measurements were conducted in the CLOUD chamber. The intercomparison was done by contrasting the observed chemical composition, the calculated volatility, and the thermal desorption behavior (for the thermal desorption techniques). The methods generally agreed on the most important compounds that are found in the nanoparticles. However, they did see different parts of the organic spectrum. Potential explanations for these differences are suggested.
The third manuscript (Ungeheuer al., 2022) presents both laboratory and ambient measurements to investigate the ability of lubricant oil to form new particles. These new particles are an important source of ultrafine particles in the areas nearby large airports. The ambient measurements were performed downwind of Frankfurt International Airport, and it was found that the fraction of lubricant oil is largest in the smallest particles. In the laboratory, the main finding was that evaporated lubricant oil nucleates and forms new particles rapidly. The results suggest that nucleation of lubricant oil and subsequent particle growth can occur in the cooling exhaust plumes of aircraft-turbofans.
The fourth manuscript (Wang et al., 2022) is a new particle formation study in the CLOUD chamber at CERN. This study shows that nitric acid, sulfuric acid, and ammonia interact synergistically and rapidly form particles under upper free tropospheric conditions. These particles can grow by condensation (driven by the availability of ammonia) up to CCN sizes and INP particles. The ability of these particles to act as a CCN and INP was also investigated and it was found to be as efficient as for desert dust. This mechanism constitutes an important finding and it can account for previous observations of high concentrations of ammonia and ammonium nitrate over the Asia monsoon region.
Nontarget screening exhibits a seasonal cycle of PM2.5 organic aerosol composition in Beijing
(2022)
The molecular composition of atmospheric particulate matter (PM) in the urban environment is complex, and it remains a challenge to identify its sources and formation pathways. Here, we report the seasonal variation of the molecular composition of organic aerosols (OA), based on 172 PM2.5 filter samples collected in Beijing, China, from February 2018 to March 2019. We applied a hierarchical cluster analysis (HCA) on a large nontarget-screening data set and found a strong seasonal difference in the OA chemical composition. Molecular fingerprints of the major compound clusters exhibit a unique molecular pattern in the Van Krevelen-space. We found that summer OA in Beijing features a higher degree of oxidation and a higher proportion of organosulfates (OSs) in comparison to OA during wintertime, which exhibits a high contribution from (nitro-)aromatic compounds. OSs appeared with a high intensity in summer-haze conditions, indicating the importance of anthropogenic enhancement of secondary OA in summer Beijing. Furthermore, we quantified the contribution of the four main compound clusters to total OA using surrogate standards. With this approach, we are able to explain a small fraction of the OA (∼11–14%) monitored by the Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM). However, we observe a strong correlation between the sum of the quantified clusters and OA measured by the ToF-ACSM, indicating that the identified clusters represent the major variability of OA seasonal cycles. This study highlights the potential of using nontarget screening in combination with HCA for gaining a better understanding of the molecular composition and the origin of OA in the urban environment.