Net Zero Polar Science DTP PhD in Mineral Weathering
This PhD is part of the Net Zero Polar Science DTP, which aims to make polar science possible in a net zero world. For further details visithttps://nzps-dtp.ac.uk/
Supervisory Team
* Co-Supervisor: Prof. Michael Lim, Northumbria University
* Co-Supervisor: Dr Yuvaraj Dhandapani, University of Leeds
* External Partner: Geological Survey of Canada, Bedford Institute of Oceanography
Project Summary
The Arctic is warming nearly 4x faster than the global average, causing widespread thawing of frozen ground (permafrost). While the impact of decomposing organic matter within the permafrost receives significant attention, a critical CO₂ source remains unaccounted for: mineral weathering. When permafrost thaws, sulphide minerals (pyrite, FeS₂) oxidise to produce sulphuric acid, which dissolves carbonates and releases CO₂ into the atmosphere. In Canada's Peel Plateau, this releases ~240,000 tonnes CO₂ annually – over 20% of Mackenzie Basin's total mineral weathering flux.
Sulphate concentration in Arctic rivers has increased 45% over the last 50 years, tracking with warming. Laboratory and field studies show CO₂ release can double with 10°C warming, yet climate models omit this feedback entirely. This project uses MASKE—a recently developed kinetic Monte Carlo (KMC) simulator proven for cement chemistry studies—to predict minerogenic CO₂ emissions from permafrost regions for the first time, filling a critical gap in Arctic carbon budgets.
This project addresses the Gt-scale gap in Arctic carbon budgets and investigates how computational methods can reduce the need for extensive field campaigns. Quantifying CO₂ emissions from mineral weathering across permafrost regions would require programmes extending across vast regions using regular, type-site, or random sampling, and relying on intensive logistics including helicopter transport, remote camps, and repeated sampling over decades—all of which are expensive and carbon intensive. Working with the Geological Survey of Canada (GSC), these carbon, financial, environmental, and time costs will be quantified and compared to those associated with new modelling and targeted validation using existing datasets (GSC data and aerial imagery) and new low‑cost, low‑power logging sensors and climate chamber testing on existing samples. The Green algorithms framework will be used to calculate computational carbon footprints, considering factors such as processing time, number of cores, and memory usage and provide an effective, quantifiable, and scalable analysis of the carbon savings achieved.
We will also assess the carbon‑savings achieved using low‑carbon satellite data (permafrost temperature, active layer thickness, watershed boundaries) from missions like ESA's Envisat and MODIS. While satellite remote sensing provides a panoptic view of permafrost extent and surface conditions, sub‑surface mineral weathering processes and chemically competing pathways will be assessed by a combination of computational modelling and field data, thus providing a comprehensive picture of Arctic permafrost weathering.
The research addresses a Gt-scale gap in Arctic carbon budgets. Climate models assume mineral weathering consumes CO₂, yet sulphuric acid‑driven weathering releases it and is highly temperature dependent. With accelerating permafrost thaw, this unaccounted source could dramatically alter regional carbon balances.
Outcomes
Outcomes provide: (1) mechanistic rate laws for climate models, (2) emission estimates for national inventories, (3) risk maps prioritising monitoring investments, and (4) tools applicable beyond permafrost—for example transferrable applications in mine drainage and carbon mineralisation.
Research Objectives
1. Objective 1: Collate and analyse field data (NWT, Canada) and integrate it with MASKE simulations to determine whether carbonate weathering in thawing permafrost leads to net releases or consumption of CO₂, based on sulphide‑carbonate ratios.
2. Objective 2: Quantify temperature dependant (-30°C to +30°C) weathering rates in Arctic thermokarst using a combination of field monitoring data and MASKE computational modelling, predicting how climate affects mineral driven CO₂ emissions.
3. Objective 3: Develop computational predictions of CO₂ fluxes from thawing permafrost weathering, validated against independent Canadian monitoring data, reducing carbon‑intensive additional fieldwork needs while improving Arctic carbon cycle understanding.
Placement Opportunity
Placement opportunity for 3 months with the Geological Survey of Canada at the Bedford Institute of Oceanography, Dartmouth, Nova Scotia. During the Canadian placement with GSC, the student will utilise existing archived data and samples to develop protocols to integrate the computational framework into new, low‑impact, targeted and predictive carbon modelling and impact assessment programmes.
Candidate Background
This project suits students with a degree in Civil/Environmental Engineering, Geosciences, Chemistry, Material Science, Computational Physics or Chemistry or any related fields. Strong computational and numerical skills—prior programming experience (MATLAB, Python or running MD simulations - LAMMPS) is highly valued. Background in geochemistry, thermodynamics or reaction kinetics is advantageous but not required. The project offers training in kinetic Monte Carlo simulation, geochemical analysis and Arctic field work. Enthusiasm for tackling complex environmental problems using computational approaches is key.
Eligibility
* A first or upper second (2:1) class honours undergraduate degree in a relevant subject, or an equivalent international qualification.
* A relevant master’s qualification or equivalent evidence of prior professional practice.
International applicants and candidates from non‑English speaking countries will need to meet the minimum language requirements for admission onto the programme of study for their Home institution.
How to Apply
Informal enquiries about the project and your application should be addressed to the project supervisor, Dr Aleena Alex - a.alex@northumbria.ac.uk
1. Complete the online NZPS Application Form by 09.00 GMT 12th January 2026 (EXTENDED DEADLINE).
2. Submit any additional application documents in the requested format to NZPS@northumbria.ac.uk by the closing date.
If you have any queries, contact nzps@northumbria.ac.uk
Funding Notes
Funding is available to Home/UK and international (including EU) students, subject to the successful completion of quality assurance checks and UK Visa and Immigration (UKVI) compliance requirements. This includes a full stipend at UKRI rates (for 2025/26 FT study this is £20,780 per year), full tuition fees and an annual Research Training and Support Grant (RTSG). Studentships are also available for Home applicants who wish to study part‑time in combination with work or personal responsibilities. Please note: additional costs may apply for international applicants.
References
1. Alex, A., Freeman, B., Jefferson, A. and Masoero, E., 2023. Carbonation and self‑healing in concrete: Kinetic Monte Carlo simulations of mineralisation. Cement and Concrete Composites, 144, p.105281.
2. Whalen, D., Forbes, D.L., Kostylev, V., Lim, M., Fraser, P., Nedimović, M.R., and Stuckey, S. 2022. Mechanisms, volumetric assessment, and prognosis for rapid coastal erosion of Tuktoyaktuk Island, an important natural barrier for the harbour and community. Canadian Journal of Earth Sciences. 59(11): 945-960.
3. Yue, Z., Dhandapani, Y., Provis, J.L. and Bernal, S.A., 2025. A reactive‑transport framework to model carbonation performance of a hardened cement: the case of alkali‑sulfate slag cement pastes. Cement and Concrete Research, 197, p.107961.
Seniority level
Internship
Employment type
Full-time
Industries
Higher Education
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