Abstract

The Chlorophyta Picocystis sp. isolated from a Tunisian household sewage pond appears promising for effective removal of Bisphenol A (BPA). Efficient and cost-effective technology for contaminants remediation relies on a tradeoff between several parameters such as removal efficiency, microorganism growth, and its tolerance to contaminant toxicity. This article demonstrates the optimum conditions achieving the highest removal rates and the minimal growth inhibition in batch cultures of Picocystis using response surface methodology. A central composite face-centered (CCF) design was used to determine the effects on removal and growth inhibition of four operating parameters: temperature, inoculum cell density, light intensity, and initial BPA concentration. Results showed that the maximal BPA removal was 91.36%, reached the optimal culture conditions of 30.7 °C, 25 × 10⁵ cells ml⁻¹ inoculum density, 80.6 µmol photons m⁻² s⁻¹ light intensity, and initial BPA concentration of 10 mg l⁻¹. Various substrate inhibition models were used to fit the experimental data, and robustness analysis highlighted the Tessier model as more efficient to account for the interaction between Picocystis and BPA and predict removal efficiency. These results revealed how Picocystis respond to BPA contamination and suggest that optimization of experimental conditions can be effectively used to maximize BPA removal in the treatment process.

• Highlights

• Surface response methodology was applied for optimization of BPA removal by the Chlorophyta Picocystis sp.

• Temperature, light intensity, inoculum cell density and initial BPA concentration were selected as factors that may affect BPA removal and microalgae growth.

• The optimal conditions for the maximum BPA removal and minimum growth inhibition were 30.7 °C; 80.6 µmol photons m⁻² s⁻¹; 25 × 10⁵ cells ml⁻¹ and 10 mg l⁻¹ BPA.

• Teissier model was selected to fit the kinetic of BPA removal by Picocystis with R² = 0.92.

摘要

Chlorophyta Picocystis sp。从突尼斯家庭污水池中分离出的分离物似乎有望有效去除双酚 A (BPA)。用于污染物修复的高效且具有成本效益的技术依赖于几个参数之间的权衡，例如去除效率、微生物生长及其对污染物毒性的耐受性。本文展示了在Picocystis分批培养中实现最高去除率和最小生长抑制的最佳条件使用响应面方法。中心复合面心 (CCF) 设计用于确定四个操作参数对去除和生长抑制的影响：温度、接种细胞密度、光强度和初始 BPA 浓度。结果表明，BPA最大去除率为91.36%，达到最佳培养条件30.7℃、25×10 ^{5 个}细胞ml ^-1接种密度、80.6 μmol光子m ^-2 s ^-1光强、初始BPA浓度10毫克 l ^-1。使用各种底物抑制模型来拟合实验数据，稳健性分析强调 Tessier 模型更有效地解释了皮囊藻之间的相互作用和 BPA 并预测去除效率。这些结果揭示了Picocystis如何对 BPA 污染做出反应，并表明可以有效地利用实验条件的优化来最大限度地去除处理过程中的 BPA。

• 强调

• 表面响应方法用于优化 Chlorophyta Picocystis sp.对 BPA 的去除。

• 选择温度、光照强度、接种细胞密度和初始 BPA 浓度作为可能影响 BPA 去除和微藻生长的因素。

• 最大BPA去除和最小生长抑制的最佳条件为30.7℃；80.6 µmol 光子 m ^-2 s ^-1；25 × 10 ^{5 个}细胞 ml ^-1和 10 mg l ^-1 BPA。

• Teissier模型被选择通过适合移除BPA的动能Picocystis与[R ² = 0.92。