This thesis examines the integration of carbon-reducing technologies and distribution decisions within the cement industry's supply chain, with a focus on the impact of these decisions on emerging carbon pricing mechanisms, particularly the European Union's Carbon Border Adjustment Mechanism (CBAM). As the cement industry is a major contributor to global carbon emissions, there is significant pressure to reduce its environmental footprint. Despite the potential of carbon capture technology, its adoption within the cement industry has been slow and remains limited. Moreover, decision‐support tools to guide these decarbonisation decisions remain scarce. This thesis develops and validates an integrated framework that combines long-term demand forecasting, strategic investment in carbon capture technologies, and distribution planning under evolving carbon-pricing regimes.


First, an extensive data collection process assembles detailed information on global cement production facilities, bilateral trade flows, and regional emission factors, providing a robust empirical foundation for the analysis. A country-level consumption series for 1995--2023 is then reconstructed by combining historical trade flows with production capacity data, applying outlier detection and interpolation techniques to ensure trend consistency. Building on this foundation, a systematic forecasting exercise produces reliable country-level demand -- which is thereafter distributed over the three biggest populated cities in the country -- projections for 2025--2050, which are spatially disaggregated to define demand nodes for the optimisation model.


The core of the methodology is a Mixed-Integer Linear Programming (MILP) model that simultaneously optimises binary investment decisions in carbon capture retrofits and continuous cement flows across a 25-year planning horizon. The model’s objective function maximises profit by balancing expected revenues against production, transportation, emissions-related costs, storage and transportation costs for captured carbon, and capital expenditures for retrofit investments.


To evaluate model robustness and the influence of future policy environments, the study conducts comprehensive parameter sensitivity and scenario analyses. Sensitivity analysis systematically perturbs key input parameters -- such as production and transportation costs -- to identify which uncertainties most affect optimal investment and distribution strategies. Scenario analysis contrasts three carbon pricing pathways (STEPS, APS, and NZE), each evaluated with and without the CBAM, to investigate how different policy trajectories shape investment decisions and trade flows.


Results show that the CBAM consistently accelerates retrofitting investments and reshapes international cement trade flows across the STEPS and NZE carbon pricing pathways. Under more aggressive carbon pricing scenarios (APS and NZE), domestic European retrofit projects become viable even without the CBAM, although the mechanism continues to redirect marginal investments toward lower-cost regions. Sensitivity tests reveal that assumptions about regional production costs exert the strongest influence on investment outcomes, while variations in transport-related costs have comparatively limited effects.


This thesis makes three key contributions. Methodologically, it provides a validated, end-to-end decision-support framework that integrates comprehensive data preparation, long-term demand forecasting, mathematical optimisation, and detailed post-analysis. Empirically, it offers novel insights into how the CBAM implementation and alternative carbon pricing trajectories jointly determine the geography of carbon capture investments and global cement flows. Practically, it delivers a strategic tool enabling industry stakeholders and policymakers to plan effective long-term decarbonisation strategies under uncertainty, highlighting the importance of targeted support measures in higher-cost regions and the need to align regulatory designs with the economic realities of global supply chains.