Three-step treatment of real complex, variable high-COD rolling wastewater by rational adjustment of acidification, adsorption, and photocatalysis using big data analysis
Three-step treatment of real complex, variable high-COD rolling wastewater by rational adjustment of acidification, adsorption, and photocatalysis using big data analysis
复制标题
用大数据分析合理调整酸化、吸附和光催化三步法处理实际复杂多变的高COD轧钢废水
DOI：
10.1016/j.seppur.2021.118865
复制
发表时间：
2021-09
影响因子：
8.6
通讯作者：
Qiurong Yang;Rongjie Xu;Pan Wu;Jian He;Changjun Liu;Wei Jiang
中科院分区：
文献类型：
--
作者：
Qiurong Yang;Rongjie Xu;Pan Wu;Jian He;Changjun Liu;Wei Jiang
针对金属加工行业真实的轧制废水（RRW），开发了酸化-吸附-沉淀三步法工艺，并利用大数据分析合理解决废水成分变化的问题。结果表明，初始值为50000 ~ 74000 mg/L的垃圾渗滤液，经过三级串联，其化学氧化需量（COD）降至70 mg/L以下：用H2SO 4酸化回收石蜡回用，用g-C3 N4吸附去除大部分长烃链有机物，在太阳光下用TiO 2光降解，使残留有机物完全光降解。人工神经网络和遗传算法相结合的模型RRW处理和精确预测的三步处理的可用操作参数。提供了一种完全处理高COD含油污水的有效技术（这种三步级联工艺）和一种智能解决废水可变性和复杂性的潜在策略（大数据分析），可作为废水处理的参考。
A three-step process of acidification, adsorption, and photocatalysis is developed to treat real rolling wastewater (RRW) from the metal-processing industry, and big data analysis is employed to rationally solve the problem of varying wastewater composition. The results show that the chemical oxidation demand (COD) of RRW with initial values between 50,000 and 74,000 mg/L decreases to below the standard value of 70 mg/L after three cascaded steps: acidification with H2SO4to recover paraffin for reuse, adsorption by g-C3N4to remove most organics with long hydrocarbon chains, and photodegradation by TiO2under sunlight to completely photodecompose residual organics. An artificial neural network and a genetic algorithm are combined to model RRW treatment and to precisely predict the usable operating parameters of the three-step treatment. An effective technique for completely treating high-COD oily water (this three-step cascade process) and a potential strategy for intelligently solving wastewater variability and complexity (big data analysis) are provided as a reference for wastewater treatment.