摘要
序批式活性污泥反应器(SBR)是目前应用较广的活性污泥处理装置。通过SBR反应器处理人工模拟高氨氮废水研究短程硝化反应系统启动过程中硝酸盐氮和亚硝酸盐氮含量的变化,利用紫外光谱采集所得数据为基础建立模型,以期快速预测SBR反应器出水中硝酸盐氮、亚硝酸盐氮含量。采用实验室配置的不同浓度硝酸盐氮和亚硝酸盐氮混合溶液,以三种不同波段选择的区间偏最小二乘法(iPLS)构建标准混合液的校正模型。研究结果显示,所建模型对混合液中硝酸盐氮和亚硝酸盐氮实测值与预测值相关性均较好。测定反应器出水指标,同样以三种不同波段选择的偏最小二乘法算法构建紫外光谱与硝酸盐氮和亚硝酸盐氮含量的模型。利用校正集相关系数、交叉验证均方根误差(RMSECV)、预测集的相关系数以及预测均方根误差(RMSEP)评价指标来评价模型结果。在iPLS、siPLS、biPLS三种模型中利用联合区间偏最小二乘法(siPLS)将全光谱分别等分为24、19个区间时,分别联合子区间[24]、[38]建立的模型预测拟合结果最优,其校正模型r=0.9393、RMSECV=1.6504,r=0.9507、RMSECV=0.4421,预测模型r=0.9992、RMSEP=1.3418,r=0.9119、RMSEP=2.6770。该模型对硝酸盐氮和亚硝酸盐氮的预测效果总体较好,表明利用紫外光谱建立区间偏最小二乘法模型可以实现对短程硝化反应器出水硝氮和亚硝氮含量的快速预测。
Sequential Batch Reactor(SBR)is one of the most widely used active sludge treatment devices.In this experiment,the nitrate and nitrite nitrogen content changes during the startup process of the short-term nitrification reaction system were studied using an SBR reactor to treat artificially simulated high ammonia wastewater.A model was established based on the data collected usingultraviolet spectroscopy,aiming to rapidly predict the nitrate nitrogen and nitrite nitrogen content in the effluent of the SBR reactor.Using laboratory-prepared solutions with different concentrations of nitrate and nitrite nitrogen,a calibration model for standard mixtures was constructedusing the interval partial least squares(iPLS)for three different band selection methods.The research results show that the models built exhibit good correlations between the measured and predicted values for nitrate nitrogen and nitrite nitrogen in the mixed solution.To determine the reactor effluent parameters,models for ultraviolet spectroscopy and the nitrate and nitrite nitrogen content were constructed using partial least squares algorithms for three different band selections.The model results were evaluated using the calibration set correlation coefficient,the root mean square error of cross-validation(RMSECV),the correlation coefficient of the prediction set,and the root mean square error of prediction(RMSEP)evaluation metrics.Among the three models,the model built using the synergy interval partial least squares(siPLS)method,which divided the full spectrum into 24 and 19 intervals and established models for the combined sub-intervals[24]and[38],exhibited the best prediction and fitting results.Its calibration model hadr=0.9393 and RMSECV=1.6504,and the prediction model hadr=0.9507 and RMSEP=0.4421.This model showed an overall good prediction performance for nitrate nitrogen and nitrite nitrogen,indicating that establishing interval partial least squares models using ultraviolet spectroscopy can rapidly predict nitrate nitrogen and nitrite nitro
作者
宋彧
李卫华
薛同站
余丽
申慧彦
SONG Yu;LI Wei-hua;XUE Tong-zhan;YU Li;SHEN Hui-yan(School of Environment and Energy Engineering,Anhui Jianzhu University,Hefei 230601,China;Anhui Provincial Key Laboratory of Environmental Pollution Control and Resource Reuse,Anhui Jianzhu University,Hefei 230601,China)
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2024年第8期2224-2232,共9页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(51978003)
安徽高校自然科学研究项目(2022AH050258)
环境污染控制与废弃物资源化利用教育厅创新研究团队(2022AH010019)资助。
