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作 者:Ziming Zhao Wenjun Sun Madhumita BRay Ajay K Ray Tianyin Huang Jiabin Chen
机构地区:[1]School of Environment,Tsinghua University,Beijing 100084,China [2]Department of Chemical and Biochemical Engineering,Western University,London Ontario N6A 5B9,Canada [3]Research Institute for Environmental Innovation(Suzhou),Tsinghua University,Suzhou 215163,China [4]School of Environmental Science and Engineering,Suzhou University of Science and Technology,Suzhou 215009,China
出 处:《Frontiers of Environmental Science & Engineering》2019年第5期115-127,共13页环境科学与工程前沿(英文)
摘 要:Seasonal algal blooms of Lake Yangcheng highlight the necessity to develop an effective and optimal water treatment process to enhance the removal of algae and dissolved organic matter (DOM). In the present study, the coagulation performance for the removal of algae, turbidity, dissolved organic carbon (DOC) and ultraviolet absorbance at 254 nm (UV254) was investigated systematically by central composite design (CCD) using response surface methodology (RSM). The regression models were developed to illustrate the relationships between coagulation performance and experimental variables. Analysis of variance (ANOVA) was performed to test the significance of the response surface models. It can be concluded that the major mechanisms of coagulation to remove algae and DOM were charge neutralization and sweep flocculation at a pH range of 4.66–6.34. The optimal coagulation conditions with coagulant dosage of 7.57 mg Al/L, pH of 5.42 and initial algal cell density of 3.83 × 106 cell/mL led to removal of 96.76%, 97.64%, 40.23% and 30.12% in term of cell density, turbidity, DOC and UV254 absorbance, respectively, which were in good agreement with the validation experimental results. A comparison between the modeling results derived through both ANOVA and artificial neural networks (ANN) based on experimental data showed a high correlation coefficient, which indicated that the models were significant and fitted well with experimental results. The results proposed a valuable reference for the treatment of algae-laden surface water in practical application by the optimal coagulation-flocculation process.
关 键 词:ALGAE COAGULATION-FLOCCULATION Response surface methodology Artificial NEURAL networks
分 类 号:X70[环境科学与工程—环境工程]
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