Calcium Looping (CaL) is a technology that makes use of CaO to capture CO₂ from industrial flue gas sources in a carbonator, after which the CO₂ is released in a concentrated form in an oxyfired calciner. The CO₂ carrying capacity of the particles circulating between the carbonator and calciner is a key variable, as it is intimately linked to CO₂ capture efficiency in the carbonator reactor. Therefore, the ability to predict dynamic changes in the CO₂ carrying capacity of the sorbent is required to understand the dynamic performance of CaL systems. This work investigates the dynamic evolution of the average CO₂ carrying capacity of the sorbent (X_ave) during transient scenarios in a large CaL pilot plant. Several experimental campaigns with extensive solids sampling and analyses were carried out to analyse the evolution of X_ave with time when the make-up flow fed into the calciner is modified (between 0–2.7 kmol CaCO₃/h). Variations in X_ave were tracked and the observed trends were interpreted using two residence time distribution models of different complexity. The main characteristics and limitations of each model are discussed in this study. The choice between the two modelling approaches developed in this work depends on the input information available and the degree of accuracy required for each specific application.

钙循环（CaL）技术是一种利用CaO在碳酸化器中从工业烟道气中捕获CO ₂的技术，然后将CO ₂以浓缩的形式释放到氧燃烧煅烧炉中。在碳酸化炉和煅烧炉之间循环的颗粒的CO ₂承载能力是一个关键变量，因为它与碳酸化炉反应器中的CO ₂捕集效率密切相关。因此，需要具有预测吸附剂的CO ₂承载能力动态变化的能力，以了解CaL系统的动态性能。这项工作研究了吸附剂（X _ave）的平均CO ₂承载能力的动态演变。）在大型CaL中试工厂的瞬态情况下。进行了几次具有大量固体采样和分析的实验，分析了当改变煅烧炉的补充流量（0-2.7 kmol CaCO ₃ / h之间）时X _ave随时间的变化。跟踪X _ave的变化，并使用两个不同复杂度的停留时间分布模型解释观察到的趋势。本研究讨论了每种模型的主要特征和局限性。在这项工作中开发的两种建模方法之间的选择取决于可用的输入信息以及每种特定应用所需的准确性程度。