Department of Chemical Engineering, Indian Institute of Technology, Kharagpur, 721302, India.
Department of Chemical Engineering, Indian Institute of Technology, Kharagpur, 721302, India; Biological Systems Engineering, Plaksha University, Mohali, 140306, India.
Environ Res. 2022 Nov;214(Pt 3):113952. doi: 10.1016/j.envres.2022.113952. Epub 2022 Aug 5.
This multiscale model quantifies transport and reaction processes in mixotrophic microalgal growth at three characteristic length scales, namely, macro (photobioreactor), meso (algal cell), micro (organelles). The macro and the meso scale equations capture the temporal dynamics of the transport of CO, O, H, organic carbon and nitrogen sources in the photobioreactor and the cell, respectively, while the micro scale quantifies the reaction rates of CO fixation and photorespiration in the chloroplast, and mitochondrial respiration. Our model is validated using our experiments (R = 0.96-0.99) on urea, CO (0.04-5%), and acetic acid-mediated mixotrophic cultivation of Chlorella sorokiniana for 138 h using municipal wastewater (with and without media) at 11,000 lx light in 25-liter pilot-scale bubble-column photobioreactors, which produces 0.47-2.74 g/L biomass with 22.8-29.6% lipids, while reducing the COD, ammonium, phosphate, nickel, and H concentrations by 65-89%. The alga assimilates the ammonium and the phosphates present in wastewater into amino acids and ATP, respectively. Our simulations quantify the autotrophic and heterotrophic components of mixotrophic biomass yield to find the optimal inlet CO concentration (of 3%) that synergizes autotrophic CO sequestration with heterotrophic assimilation of organic carbon, thereby maximizing both autotrophic and heterotrophic growths. Super-optimal levels of inlet CO acidify the stroma of the chloroplast, inhibit RuBisCo's enzymatic activity for CO fixation in the Calvin Cycle, decelerate carrier-mediated uptake of acetate, and reduce biomass yields. Our harvesting process drastically reduces the algal harvesting time to less than 29 min. This multiscale reaction-transport model provides a useful tool for further scaling up this pilot-scale technology that synergistically integrates CO sequestration and wastewater treatment with rapid microalgal cultivation (using municipal wastewater without autoclaving) and cost-effective harvesting.
该多尺度模型量化了混合营养微藻生长在三个特征长度尺度下的传输和反应过程，即宏观（光生物反应器）、中观（藻细胞）和微观（细胞器）。宏观和中观尺度的方程分别捕获了 CO、O、H、有机碳和氮源在光生物反应器和细胞中的时间动态，而微观尺度则量化了叶绿体和线粒体呼吸中 CO 固定和光呼吸的反应速率。我们的模型使用我们的实验进行了验证（R=0.96-0.99），实验中使用城市废水（有无培养基）在 11000 lx 光下，通过添加尿素、CO（0.04-5%）和乙酸，在 25 升规模的鼓泡式光生物反应器中培养集胞藻 138 小时，在 25 升规模的鼓泡式光生物反应器中产生 0.47-2.74 g/L 的生物质，生物量中含有 22.8-29.6%的脂质，同时将 COD、铵、磷、镍和 H 的浓度降低 65-89%。藻类将废水中的铵和磷酸盐分别同化到氨基酸和 ATP 中。我们的模拟量化了混合营养生物量产生的自养和异养成分，以找到最佳的入口 CO 浓度（3%），该浓度协同自养 CO 固定和异养同化有机碳，从而最大限度地促进自养和异养生长。入口 CO 的超最佳水平酸化了叶绿体的基质，抑制 RuBisCo 酶在卡尔文循环中固定 CO 的活性，减缓载体介导的乙酸摄取，并降低生物质产量。我们的收获过程将藻类的收获时间缩短到不到 29 分钟。这种多尺度反应-传输模型为进一步扩大该试点规模技术提供了有用的工具，该技术协同集成了 CO 固定和废水处理与快速微藻培养（使用未经高压灭菌的城市废水）和具有成本效益的收获。
