Forecasting of energy and emissions for the cement sector: a comprehensive review and scenario-based assessment

The cement industry is a primary driver of the environmental footprint of the built environment, representing the most carbon-intensive component of construction material supply chains. Their energy and emissions trajectories directly shape the sustainability of buildings and urban infrastructure. However, forecasting these trajectories remains challenging due to limited data, technological transitions, and policy uncertainties. This study develops an integrated framework that combines a systematic review of forecasting methods with a comparative evaluation of the Grey Model (GM(1,1)) and the Markov-Chain Grey Model (MCGM). Using the cement sector of a rapidly developing economy as a case study, we embed forecasts within alternative scenarios, business-as-usual, efficiency improvement, and decline to assess future pathways of energy use and CO2 emissions. Results show that MCGM significantly improves forecasting accuracy relative to GM in this data-constrained and volatile industrial context and enables robust scenario analysis. Scenario outcomes highlight the risk of rising energy demand and emissions that could undermine sustainability targets in the construction sector, while efficiency pathways demonstrate alignment with international climate and development benchmarks. Beyond this case, the framework underscores the value of Grey–Markov forecasting as a transferable decision-support tool for evaluating the long-term environmental impacts of construction-related industries, supporting policymakers and sector stakeholders in achieving low-carbon development.