College of Engineering, Shenyang Agricultural University, Shenyang, 110866, China.
Key Laboratory of Development and Application of Rural Renewable Energy, Biogas Institute of Ministry of Agriculture and Rural Affairs, 610041, Chengdu, China.
Anal Methods. 2023 Aug 10;15(31):3902-3914. doi: 10.1039/d3ay00436h.
Effective treatment of sewage requires accurate measurement of important water quality parameters, such as chemical oxygen demand (COD), pH value, total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (NH-N). Traditional detection techniques can result in secondary contamination and are time- and labor-intensive. Near infrared spectroscopy was used in this study to create a model of these parameters of pig manure anaerobic fermentation sewage. The models' viability for quickly estimating the aforementioned water quality characteristics was reviewed, and the models' performance in predicting the results of several samples (biogas slurry, supernatant, and biogas residue) was contrasted. By analyzing the near infrared spectrograms with a spectral range of 4000 cm and 12 500 cm and using second derivative (SD), Savitzky-Golay smoothing (SG) and standard normal variable (SNV) to preprocess the spectra, partial least squares (PLS) was selected to establish the prediction model. The results showed that the effect of the NIR model constructed from the supernatant was better than that of biogas slurry and biogas residue. The determination coefficients for COD, pH value, NH-N and TN were 0.69, 0.87, 0.81, and 0.94, respectively. This study could provide reference for on-line monitoring of wastewater in the future.
有效处理污水需要准确测量重要的水质参数,如化学需氧量(COD)、pH 值、总氮(TN)、总磷(TP)和氨氮(NH-N)。传统的检测技术可能会导致二次污染,并且耗时耗力。本研究采用近红外光谱法建立了猪粪厌氧发酵污水中这些参数的模型。评价了这些模型快速估算上述水质特征的可行性,并对比了模型在预测几个样品(沼气浆、上清液和沼气渣)结果方面的性能。通过对光谱范围为 4000 cm 和 12500 cm 的近红外光谱进行分析,并采用二阶导数(SD)、Savitzky-Golay 平滑(SG)和标准正态变量(SNV)对光谱进行预处理,选择偏最小二乘法(PLS)建立预测模型。结果表明,上清液近红外模型的构建效果优于沼气浆和沼气渣。COD、pH 值、NH-N 和 TN 的决定系数分别为 0.69、0.87、0.81 和 0.94。本研究可为未来废水的在线监测提供参考。