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http://hdl.handle.net/10722/38565
2024-03-28T07:55:12ZDevelopments and applications of luminescence dating in earth sciences
http://hdl.handle.net/10722/336652
Title: Developments and applications of luminescence dating in earth sciences
Authors: Huang, Chang; 黄昶
Abstract: This thesis aims to address fundamental questions about developments and applications in luminescence dating in the past, present, and future, including the age range, accuracy, and thermochronological studies.
To estimate the equivalent dose (De) of calcite, a single-aliquot regenerative-dose (SAR) protocol with low-temperature measurements is employed. It uses the isothermal thermoluminescence (ITL) signals measured at ~225-240 °C, where a De vs. ITL temperature (De-T) plateau is observed. These ITL signals correspond to the TL signals of the 280 °C TL peak. Notably, ITL signals at 230-235 °C saturate at ~4000-5000 Gy, which has the potential to date geological and archaeological samples spanning the entire Quaternary period. The absence of detectable anomalous fading of ITL signals suggests that the signal is free of fading. Dose recovery tests further confirm the suitability of the SAR-ITL protocol for De estimation.
The SAR-ITL protocol was then employed to study the thermochronological applications of limestone rocks in the middle of the Nujiang River, southeastern Tibetan Plateau. The results show that apparent De values of ITL230 signals increase with increasing heights, while apparent ages increase before approximately 400 ka (the apparent age) and then reach dynamic equilibrium stages. From the isochron plot of apparent De values against dose rates, the effect lifetimes of ITL signals were obtained, which constrains the applicable ranges of ITL signals from calcite. It is proposed that calcite can be used in thermochronology within the applicable ranges from 530±25 ka to the present.
The accurate luminescence dating of volcanic-related materials remains challenging. This study focuses on quartz minerals extracted from lava-baked sediments in the Tengchong volcanic field, southeastern the Tibetan Plateau, using the optically stimulated luminescence (OSL) technique. The results show that samples with initial OSL signals dominated by the fast component yield reliable ages. Conversely, samples dominated by unstable medium and slow components broadly underestimate their OSL ages, requiring corrections. By using the plot of De against recuperation for each aliquot, the underestimated OSL ages can be corrected. The final single-aliquot quartz OSL ages are consistent with single-grain quartz OSL and 14C ages recording the same eruption event, thus validating the reliability of the dating ages.
The comprehensive research on photoluminescence (PL) emission spectra of various feldspar types remains poorly understood and the limited availability of instruments has hindered its research. This study investigated the PL properties of six feldspar types using a commercial Raman instrument. The results indicate that the number and medium positions of emission peaks depend on the specific feldspar types and samples analyzed. Additionally, the sensitivity of PL signals to irradiation dose varies across feldspar types and peak positions. Notably, PL emissions from ~865 and ~910 nm of K-feldspar are sensitive and show potential applicability for dating applications. The dose-response curves obtained using 860-870 nm PL signals of potassium feldspar conform to a relationship of a single saturating exponential function between the signal and irradiation dose. This study demonstrates that a commonly available Raman system can be utilized for PL measurements of single grains.2023-01-01T00:00:00ZHolocene hydroclimatic changes in mid-latitude Asia and implications for westerlies and monsoon behavior
http://hdl.handle.net/10722/336649
Title: Holocene hydroclimatic changes in mid-latitude Asia and implications for westerlies and monsoon behavior
Authors: Jiang, Jiawei; 姜佳玮
Abstract: Due to complex interactions of the westerlies and East Asian monsoon along with relatively dry conditions, mid-latitude Asia is susceptible to hydroclimatic changes. Contrasting moisture evolutions between westerlies-dominated Central Asia and monsoonal Asia since the mid-Holocene has been widely recognized. Yet, inconsistent hydrological and temperature records over the early Holocene from both regions have been reported, and moisture variations at the boundary between two circulations remain controversial. This thesis presents lacustrine records from mid-latitude Asia to investigate Holocene hydroclimatic changes and infer associated mechanisms.
Firstly, water depth control on n-alkane distribution and organic carbon isotope in mid-latitude Asian lakes was investigated using surface sediments from 55 lakes. Variations in relative proportion of mid-chain to long chain n-alkane homologues (Paq) and isotopic compositions of total organic carbon (δ13Corg) resemble arched patterns with water depth, with relatively high Paq and δ13Corg values corresponding to the depth of ~1–10 m. The results suggest that Paq and δ13Corg can be used to infer lake-level changes in mid-latitude Asia, and combined utilization of both indicators could improve the reliability of reconstructions. Further, updated n-fatty acid δD records from Lake Hurleg were presented to assess the relation between precipitation isotopes and moisture levels in arid Central Asia. The results indicate that isotopic differences between lake water and terrestrial water largely reflect isotopic enrichment due to lake water evaporation and thus aridity changes in arid Central Asia since the mid-Holocene, which also shed light on Holocene moisture variations in marginal monsoon regions.
Secondly, isotopic and biomarker records from Lake Sayram, Yanhaizi, and Qinghai were presented. The occurrence of particularly depleted isotopic values of lake water associated with lake freshening within the deglaciation and early Holocene, together with anomalously old 14C dates documented in many Asian lakes, strongly indicate substantial meltwater contribution to lake water budget, along with the climatic warming. Hence, the meltwater effect should be considered when inferring Asian summer monsoon and westerlies behavior over the early Holocene.
Thirdly, alkenone-based (U_37^K') Holocene temperature records from Lake Yihesariwusu, Kuchuk, and Maloye Yarovoye show contrasting trends. Temperature disparity over mid-high latitude Eurasia during the early to mid-Holocene and its reduction towards the late Holocene appear to be driven by wavy westerlies associated with remnant ice sheets and low solar irradiance during the early to mid-Holocene. Wavy westerlies presumably induce temperature disparity over other mid-high latitude northern continents.
Lastly, biomarker and elemental records from Lake Eastern Juyanze, Anguli-nuur, Badain-W, and Sumujilin-S show wet conditions during the Medieval Warm Period (MWP) and dry conditions during the Little Ice Age, following the temperature-moisture association in monsoonal region. The results indicate northwestward migration of the monsoonal limit during the MWP, possibly associated with strengthened monsoon. Moreover, decoupled temperature-moisture records from Lake Eastern Juyanze appear to be associated with abrupt meltwater input to the lake.
Findings in this thesis highlight that Holocene hydroclimatic conditions in mid-latitude Asia appear to be affected by meltwater and atmospheric circulation patterns, with important implications for our understanding of westerlies and monsoon behavior.2022-01-01T00:00:00ZStudy on the characteristics of geospace based on global simulation
http://hdl.handle.net/10722/336647
Title: Study on the characteristics of geospace based on global simulation
Authors: Yin, Qianfeng; 尹前鋒
Abstract: In recent decades, space weather forecasting has become increasingly important since the significant impact of the geospace environment on human activities. To enhance the precision of space weather forecasting, a comprehensive and thorough investigation of magnetosphere-ionosphere (M-I) coupling is necessary. Numerical simulations offer a valuable tool for studying the M-I coupling, which can be validated through observations and statistical models. However, physics-based long-run global simulations have been infrequent in previous studies. Therefore, an ideal and two long-run simulations using novel two-way coupled global models are conducted in four parts.
In the first part, I focus on geomagnetic substorms. Large-scale electromagnetic energy transport during a geomagnetic substorm is in the form of Alfvén waves, which is key to M-I coupling and has not been investigated quantitatively in physics-based models for space weather forecasting. Therefore, I use Grid Agnostic MHD for Research Applications (GAMERA)-Ring Current Model (RCM) (GR) to investigate the evolution of Alfvénic Poynting flux during an idealized substorm-steady magnetospheric convection (SMC). In the second part, I study the statistical features of M-I coupling including field-aligned current, polar cap potential, ionospheric Joule heating, and the downward Alfvénic Poynting flux, binned by the interplanetary magnetic field (IMF) clock angles and geomagnetic Kp indices using another novel two-way M-I model, GAMERA - Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) (GT) over an entire Carrington Rotation (March 20- April 16, 2008) event, which are compared with observations and empirical models. Unlike previous simulations that were only aimed at ideal conditions or short-term events, this is the first long-run global simulation of the new coupled model. In the third part, I conducted the same long-run simulation using GR and performed the same statistical and comparative analysis to test the coupling characteristics and applicability of the new model. These simulations establish an extensive database and significantly enhance the value of physics-based simulations in space weather forecasting research. Finally, I combine the ideal simulation and the entire Carrington Rotation using GR to study plasmaspheric plumes, which is an important aspect of the coupled response of the entire inner magnetosphere and ionosphere. These plumes impact ionospheric disturbances, magnetic variations, particle precipitation and other space weather processes.
Based on these new simulations and synoptic analyses, several key findings have been discovered. Firstly, during the substorm expansion phase, the Alfvénic Poynting flux is enhanced by approximately 200%, and the dawn-dusk asymmetry of the Alfvénic oval is diminished. Secondly, the simulated M-I coupling parameters by GT and GR are mostly consistent with empirical models and observations, with GT and GR showing more reasonable Joule heating than the Weimer model, suggesting the importance of the physics-based model in long-term space weather research and forecast. Moreover, with drift-kinetic ring current model coupled, geospace simulations reproduce plasmaspheric plumes during periods of southward IMF, which can persist as long as the Kp index remains elevated, and higher solar wind velocities can facilitate their development. Overall, these comprehensive analyses contribute to a much-advanced understanding of M-I coupling for future physics-based space weather forecasting and model development.2023-01-01T00:00:00ZMachine learning for natural hazard data analyses and data-driven geotechnical engineering applications
http://hdl.handle.net/10722/336622
Title: Machine learning for natural hazard data analyses and data-driven geotechnical engineering applications
Authors: Zhou, Yimeng; 周依盟
Abstract: Extensive exploration of novel machine learning (ML) technologies within the domain of geoscience has been actively pursued. This pursuit is driven by two primary factors: Firstly, there exists a wealth of concepts within geoscience that lend themselves to mathematical formulation, enabling more robust quantitative analyses. Secondly, the field of geoscience is inherently data-rich, offering fertile ground for the development of novel ML models tailored to geoscience. However, the integration of ML with geoscience is in its early stages and unevenly advancing.
This Ph.D. thesis aims to contribute to this interdisciplinary research field by taking a modest step forward. The thesis concentrates on two main research subjects: (1) natural hazard data analyses and (2) data-driven geotechnical engineering applications. These two subjects encompass a total of five specific research topics: (1) classic ML for classification, (2) classic ML for regression, (3) supervised learning by convolutional neural network (CNN), (4) unsupervised learning by CNN, and (5) deep learning (DL) with 3D input data. These five research topics cover a wide range of contents, including (1) boulder fall volume range prediction, (2) seismic source localization, (3) rock type classification, (4) low-light rock image enhancement, and (5) 3D point cloud filtering. They collectively contribute to the integration of ML in geoscience.
Based on the abovementioned research objectives, a series of experimental tests have been designed and carried out with the collection of massive geodata and the development of issue-specific ML models. The key findings and contributions regarding each research topic are as follows:
Regarding classic ML for classification, the volume ranges of potential boulder falls in Hong Kong have been predicted based on given ML features. The suitability of eight classic ML algorithms is adequately demonstrated.
Regarding classic ML for regression, the source locations of acoustic emission (AE) events are predicted using the support vector machine (SVM) and compared with those obtained by the conventional method. The negative impacts of anisotropy and water content on the accuracy of source localization are quantitatively investigated.
Regarding supervised learning by CNN, a large-scale rock image dataset is established, comprising common rock types found in Hong Kong. An advanced CNN, namely HKUDES_Net, is developed for rock type classification, demonstrating state-of-the-art performance.
Regarding unsupervised learning by CNN, a novel unsupervised DL model that caters to enhance low-light rock images is developed. The DL model utilizes the deep curve estimation (DCE) algorithm and a CNN architecture to perform automatic and pixel-wise enhancement.
Regarding DL with 3D input data, a novel DL model for 3D point cloud filtering is developed for geotechnical applications. The DL model has demonstrated superior performance in three key aspects: (1) effective noise filtering, (2) point-wise adjustments for noise points, and (3) preservation of edge features.
This thesis leverages domain knowledge of geoscience to enhance the development of ML models and utilizes advanced ML technologies to provide insights into traditional geoscience issues. The methodologies presented in this thesis extend beyond the illustrated applications and have broader applicability to various types of natural hazards and geotechnical engineering applications.2023-01-01T00:00:00Z