Production-Process Simulation and Life-Cycle Assessment of Metakaolin as Supplementary Cementitious Material

Abstract

An environmental assessment of metakaolin as a supplementary cementitious material (SCM) through an integrated production-process-simulation and Life-Cycle-Assessment (LCA) approach is presented in this work. Initially, process simulation models were developed to reproduce the basic stages of the metakaolin production process. The effect of various operational parameters and scenarios, such as calcination temperature, moisture of raw material and associated drying, exhaust gas recirculation and the use of alternative-fuel combustion to provide kiln heat requirements, was evaluated. The resulting process heat-demand and CO2-emission computations were used as inputs in the LCA along with upstream literature data using a cradle-to-gate approach. LCA results focused on the most relevant environmental impact category of cement production, the Global Warming Potential (GWP (100)). The major findings showed a strong influence of process temperature and kaolin humidity on the lifecycle GWP, since both parameters affected not only the core-process heat demand but also the upstream impact related to fossil-fuel extraction, processing, transportation and distribution. Recirculating the exhaust provided a GWP reduction potential of up to 19%. In all examined production scenarios, metakaolin depicted a lower Global Warming Potential compared to clinker due to the avoidance of emissions related to limestone calcination. As regards the impact contribution of fuels, coal was responsible for higher onsite emissions and natural gas indicated higher upstream emissions. The GWP (100) could be further reduced when alternative waste fuels such as plastic waste, MSW (municipal solid waste) and tires were used. The LCA results have been cross-checked with previous literature reports, and the corresponding deviations are accordingly explained. In any case, the LCA results of different studies are rarely directly comparable due to the numerous assumptions required, which cannot be identically replicated.