Carbon capture and storage (CCS) is an attractive area of research in such fields as CO 2 mineral carbonation, global warming and sustainable energy systems. In this study, carbonation efficiency for aqueous mineral carbonation (MC) was achieved through two steps, which include leaching of calcium from cement kiln dust (CKD) followed by the reaction of pure CO 2 with the calcium hydroxide precipitates formed by the hydroxylation using NaOH. Response surface methodology (RSM) with a Box-Behnken design (BBD) was applied to optimize the calcium leaching yield, while the carbonation efficiency from CKD was assessed using RSM with central composite design (CCD). Optimization of calcium leaching is highly important, as it is a rate-limiting reaction step in MC and also influences and enhances carbonation efficiency. Different parameters including acid concentration (HNO 3 ), leaching temperature, leaching time, and dose of CKD sample were considered in order to optimize the maximum yield of Ca leaching from the CKD sample. In addition, different CO 2 flow rates and temperatures were used as parameters for optimizing carbonation efficiency. Two quadratic regression models were developed for each process, i.e. calcium leaching and carbonation. For calcium leaching, a maximum of 98.55% calcium was extracted under the optimal set of acid concentration 4.13 M, 90 °C, 28 min leaching time, and 13.8 g of CKD sample. For carbonation, the maximum carbonation efficiency of 89.2% was achieved for a CO 2 flow rate of 1163 cm 3 /min at 90 °C. Calcium leaching results indicate that the leaching yield was significantly affected by all the input parameters except leaching time. For carbonation, both factors affected the carbonation efficiency, with the effect temperature shown to be greater than that of the CO 2 flow rate. Additionally, the predicted results agreed well with the experimental values for both calcium leaching and carbonation processes, with errors of less than 1% and 5%, respectively.

中文翻译：

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使用响应面方法结合 Box-Behnken 和中心复合设计方法对水泥窑粉尘的含水矿物碳化进行建模和优化

碳捕获和储存 (CCS) 是 CO 2 矿物碳化、全球变暖和可持续能源系统等领域的一个有吸引力的研究领域。在本研究中，水性矿物碳酸化 (MC) 的碳酸化效率通过两个步骤实现，包括从水泥窑粉尘 (CKD) 中浸出钙，然后纯 CO 2 与使用 NaOH 羟基化形成的氢氧化钙沉淀反应. 使用 Box-Behnken 设计 (BBD) 的响应面方法 (RSM) 来优化钙浸出率，而使用具有中心复合设计 (CCD) 的 RSM 评估 CKD 的碳酸化效率。钙浸出的优化非常重要，因为它是 MC 中的限速反应步骤，也会影响和提高碳酸化效率。考虑酸浓度（HNO 3 ）、浸出温度、浸出时间和CKD样品剂量等不同参数以优化从CKD样品中浸出Ca的最大产率。此外，不同的CO 2 流速和温度被用作优化碳酸化效率的参数。为每个过程开发了两个二次回归模型，即钙浸出和碳酸化。对于钙浸出，在酸浓度 4.13 M、90 °C、28 分钟浸出时间和 13.8 g CKD 样品的最佳设置下，最多可提取 98.55% 的钙。对于碳酸化，在 90°C 下，CO 2 流速为 1163 cm 3 /min 时，最高碳酸化效率达到 89.2%。钙浸出结果表明，除浸出时间外，所有输入参数都显着影响浸出率。对于碳酸化，这两个因素都会影响碳酸化效率，其影响温度显示大于 CO 2 流速的影响温度。此外，预测结果与钙浸出和碳酸化过程的实验值吻合良好，误差分别小于 1% 和 5%。