IAP-25-089

Advancing ultra-high resolution palaeoenvironmental records from lake sediment cores through integrated laser-induced breakdown spectroscopy and hyperspectral imaging

Reconstructing past environmental and climatic variability is central to understanding Earth system processes and the trajectories of future change. Sedimentary archives from lakes and oceans provide continuous, dateable records of palaeoenviromental conditions, preserving the geochemical and physical imprints of climate, ecosystem dynamics, and human activity. Over the past two decades, palaeoclimatology and palaeoenvironmental science have been revolutionized by the emergence of high-resolution, non-destructive scanning technologies, such as scanning X-ray fluorescence (XRF) and X-ray radiography or computed tomography (CT). These tools have enabled rapid detection of elemental composition, sediment structure, and density at sub-cm resolution, providing new insights into past climate variability, sedimentary processes, biogeochemical cycling and the timing of environmental change.

Despite these advances, current technologies face key limitations. Traditional XRF core scanning, while powerful, is constrained by its inability to detect light elements and to discriminate mineralogical and organic phases with similar elemental signatures. Radiographic and CT methods provide important structural data but little geochemical detail. Consequently, researchers are often forced to combine multiple independent techniques to achieve a complete understanding of past environmental signals, leading to gaps in resolution and integration. To address these challenges, next-generation analytical tools capable of simultaneously resolving the elemental and mineralogical characteristics at ultra-high-resolution are essential.

Through a CASE award with Geotek, this PhD project will develop and advance an innovative core scanning technology platform that, for the first time, couples laser-induced breakdown spectroscopy (LIBS) with visible to short-wave infrared hyperspectral imaging (HIS). Funded through a recent NERC Capital Call and working with the manufacturers Geotek, this LIBS-HSI system offers the potential to provide fully integrated, ultra-high-resolution elemental and mineralogical datasets from sediment cores. The overarching aim is to establish the machine-learning based analytical capability of this new LIBS-HSI platform, and to apply it to palaeoenvironmental research questions, allowing us to bridge the gap between elemental and mineralogical analyses in Earth system science. The specific archives to be used and the research questions addressed will be developed in the first year according to the successful candidates’ interests.

Specific objectives are to:
1. Develop and optimise the LIBS-HSI data acquisition protocols for sediment cores, including calibration, quantification and data integration.
2. Quantitatively evaluate analytical performance in comparison to established scanning technologies (e.g., XRF core scanning, CT imaging), and assess precision, spatial resolution and detection limits.
3. Integrate LIBS elemental maps with hyperspectral mineralogical and organic data to generate comprehensive multi-dimensional datasets describing sediment composition and structure at sub-mm resolution.
4. Apply the LIBS-HSI approach to selected lake archives, targeting case studies that capture abrupt environmental transitions, e.g., glacial-interglacial transitions, Holocene climate events, human-induced eutrophication, wildfire impacts on lake biogeochemistry etc.
5. Develop open-access machine learning based analytical and visualisation tools for the integration of LIBS-HSI outputs with existing palaeo-records and multi-proxy datasets.

The PhD student will initially design and set up an experimental framework to test the analytical capabilities of the Geotek LIBS-HSI platform. This will be done through a range of known sediment samples, synthetic mineral mixtures and reference materials that cover light and heavy elements. As laser-induced breakdown spectroscopy (LIBS) uses a focused laser pulse to ablate microscopic areas of a sample, producing a plasma whose emission spectrum reveals the samples elemental composition, assessments of chemical and physical matrix effects will be required. Visible near infrared and shortwave infrared (VNIR-SWIR) hyperspectral imaging (HSI), by contrast measures reflectance over hundreds of contiguous spectral bands, providing detailed mineralogical and organic composition information, and these data will be calibrated using X-ray diffraction and HPLC to detect minerals and pigments in a range of sediment matrices, and is essential to quantify reflectance data. Data fusion will use multivariate regression and machine-learning approaches (including GAN and Transfer Learning) to translate combined LIBS-HSI signatures into quantitative elemental and mineralogical maps. Reproducibility will be quantified through replicates and pre/post-scan imagery.

The data produced by the LIBS-HSI platform will then be compared to scanning XRF, XRF mapping and micro-CT on identical core sections (available at BOSCORF) to assess precision, detection limits and effective spatial resolution. Field applications will target a range of lake sediment settings, but could include varved lacustrine sediments for seasonal resolution, carbonate-rich systems to test for abrupt climate events, organic-rich lake sediments to test for organic proxies and light element detection, glaciolacustrine settings to test for event stratigraphy of glacial melt, as well as shallow lake environments that record the impacts of human-driven nutrient inputs. For example, the supervisory team work across a breadth of potential case studies, and you will have access to lake sediments that have been taken to investigate anthropogenic impacts on tropical Asian lakes, understanding Holocene climate change in the Arctic, the evolution of the Asian monsoon from the Tibetan Plateau, climate change in the southern hemisphere and human-environment interactions in UK lakes.

The application of LIBS-HSI to lake sediment records, however, may require the retrieval of new core material and therefore, a field component to the studentship will recover new Holocene lake sediment cores from sites in the Lake District, UK. Where existing datasets and core material exist, the student will visit these core repositories and use what is available. Potential case studies will be identified in the first year of the studentship and a healthy network of international collaborators have already indicated their interest in the outputs of this new scanning platform. There is great flexibility in the types of palaeo-records that the student would want to use, and this will be discussed with the supervisory team and Geotek.

As this is a CASE studentship, the expectation is the student will work closely with the LIBS-HSI manufacturer Geotek. The expectation for the successful candidate is they spend a minimum of 3 months at Geotek HQ learning about the LIBS-HSI systems and developing expertise in how the systems function to aid the development of protocols and data extraction.

Year 1

• Conduct comprehensive literature review on LIBS, HSI, and existing core-scanning methods.
• Design an experimental geochemical framework to start to test LIBS-HSI integration.
• Begin calibration using established key reference materials and sediment analogues.
• Explore data management and processing environment for spectral analysis.
• Optimise LIBS-HSI and test for data outputs, begin to develop data workflows.
• Spend 3 months at Geotek training and learning the core scanning across a range of core scanning technologies.
• Present initial progress to internal seminars and prepare short methods review exploring data calibration and quantification.
• Consider the palaeoenvironmental questions that the student would be interested in addressing.
• Undertake advanced data science training (e.g., R, Python, hyperspectral analytics, machine learning) through MSc level modules offered in School of Computing at Newcastle (e.g., CSC8628: Image Processing and CSC8645: Advanced AI).
• Attend appropriate NERC training courses and participate in Newcastle’s graduate training programme, alongside IAPETUS training events.

Year 2

• Validate and quantify data outputs, and evaluate analytical uncertainties, detection limits and matrix effects.
• Develop new domain-informed machine-learning models for data analytics.
• Conduct systematic analysis of a range of lake sediment records and compare to existing technologies, and existing geochemical datasets.
• Spend 3 months at Geotek training and learning the core scanning across a range of core scanning technologies
• Prepare first peer-reviewed publication describing analytical development targeted at a geochemical audience.
• Present initial results at either an internation geoscience or analytical conference (e.g., EGU, Goldschmidt).
• Identify key palaeoenvironmental archives in collaboration with partners, connected to ideas and research interests of the student.

Year 3

• Undertake full-scale LIBS-HSI scanning on selected cores and integrate this with existing stratigraphic, chronological and proxy datasets.
• Compare outcomes with proxy records to to reconstruct high-resolution palaeoenvironmental changes.
• Draft publications exploring the integration of LIBS-HSI data, as well as exploring palaeoenvironmental change from lake sediments.
• Begin writing thesis chapters, focused on literature review and methods.
• Present key findings at a UK/International conference and participate in IAPETUS student conference.

Year 3.5

• Final data synthesis and inter-palaeoenvironmental record comparison, identifying how ultra-high-resolution scanning contributes to our understanding of change.
• Summarise methodological advances and the palaeoenvironmental insights.
• Complete PhD chapters on results and discussion.
• Thesis submission.

The PhD student will gain comprehensive, interdisciplinary training spanning environmental science, analytical chemistry and data science. Core research skills will include advanced operation and optimisation of the LIBS-HSI system, working closely with CASE partner – Geotek. As part of the PhD the student will also develop quantitative calibration techniques, gaining laboratory skills in ICP-OES and HPLC, as well as expertise in running instruments, data acquisition and integration of multi-sensor datasets. In addition, the student will spend time at BOSCORF to undertake wider complimentary non-destructive analytical technique training.

Specialist analytical and computational training will encompass spectral processing, machine learning for data fusion, as well as statistical analysis using R, Python and/or MATLAB. The project will also provide experience in lake sediment coring, water quality, proxy analysis, geochronology and innovative scanning methods.

Complementary professional development will be delivered through IAPETUS and institutional programmes, including courses in project management, science communication and research impact. The student will present findings at national and international conferences, publish in peer-reviewed journals and engage with a range of scientific collaborators. By completion, the student will possess highly transferable skills in environmental geochemistry, big data analytics, and interdisciplinary collaboration, which all fully align with NERC’s training outcomes.