Near-infrared reflectance spectroscopy for rapid prediction of biochemical methane potential of wastewater wasted sludge

The information of biochemical methane potential (BMP) of wasted sludge is essential to ensure the stable operation of sludge management processes. However, conventional anaerobic digestion (AD) approach for BMP test is time-consuming and labour-intensive. Currently, the technique of Near Infrared S...

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Veröffentlicht in:The Science of the total environment 2024-02, Vol.912, p.169640-169640, Article 169640
Hauptverfasser: Lu, Dan, Yan, Wangwang, Le, Chencheng, Low, Siok Ling, Tao, Guihe, Zhou, Yan
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Yan, Wangwang
Le, Chencheng
Low, Siok Ling
Tao, Guihe
Zhou, Yan
description The information of biochemical methane potential (BMP) of wasted sludge is essential to ensure the stable operation of sludge management processes. However, conventional anaerobic digestion (AD) approach for BMP test is time-consuming and labour-intensive. Currently, the technique of Near Infrared Spectroscopy (NIRS) is gaining prominence in the biogas production within AD process. Previous studies mostly focused on predicting BMP values for fibrous plant biomass and solid waste, with only a limited number of studies attempting to apply NIRS to obtain BMP values across a wide array of wasted sludge types. To obtain BMP values for this diverse range of wasted sludge efficiently and accurately, it is imperative to develop precise models for assessing BMP values using NIRS. In this study, the possibility of using NIRS to predict the BMP values of wasted sludge was evaluated. A total of 70 sludge samples from different sources were investigated to develop a BMP-prediction model by correlating the measured BMP values with the obtained NIR spectra. As a result, a reliable and successful BMP-prediction model was established with the determination coefficient of 0.90, residual prediction deviation of 3.50 and low root mean square error of prediction of 36.8 mL CH4/g VS. This BMP-prediction model is satisfactory for predicting BMP values of various types of sludge. It could provide support for plant operators to make decisions rapidly, thereby improving the process efficiency and optimizing sludge management procedures. [Display omitted] •A rapid and reliable BMP-prediction model using NIRS was developed.•A wide range of types of wasted sludge was included in the prediction model.•Rt2 and RMSEP values of sludge BMP predicting model were 0.90 and 36.8 mL CH4/g VS.•The NIRS-assisted BMP prediction achieved satisfactory and successful results.
doi_str_mv 10.1016/j.scitotenv.2023.169640
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However, conventional anaerobic digestion (AD) approach for BMP test is time-consuming and labour-intensive. Currently, the technique of Near Infrared Spectroscopy (NIRS) is gaining prominence in the biogas production within AD process. Previous studies mostly focused on predicting BMP values for fibrous plant biomass and solid waste, with only a limited number of studies attempting to apply NIRS to obtain BMP values across a wide array of wasted sludge types. To obtain BMP values for this diverse range of wasted sludge efficiently and accurately, it is imperative to develop precise models for assessing BMP values using NIRS. In this study, the possibility of using NIRS to predict the BMP values of wasted sludge was evaluated. A total of 70 sludge samples from different sources were investigated to develop a BMP-prediction model by correlating the measured BMP values with the obtained NIR spectra. As a result, a reliable and successful BMP-prediction model was established with the determination coefficient of 0.90, residual prediction deviation of 3.50 and low root mean square error of prediction of 36.8 mL CH4/g VS. This BMP-prediction model is satisfactory for predicting BMP values of various types of sludge. It could provide support for plant operators to make decisions rapidly, thereby improving the process efficiency and optimizing sludge management procedures. [Display omitted] •A rapid and reliable BMP-prediction model using NIRS was developed.•A wide range of types of wasted sludge was included in the prediction model.•Rt2 and RMSEP values of sludge BMP predicting model were 0.90 and 36.8 mL CH4/g VS.•The NIRS-assisted BMP prediction achieved satisfactory and successful results.</description><identifier>ISSN: 0048-9697</identifier><identifier>EISSN: 1879-1026</identifier><identifier>DOI: 10.1016/j.scitotenv.2023.169640</identifier><identifier>PMID: 38151129</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Anaerobic digestion ; Biochemical methane potential (BMP) ; environment ; gas production (biological) ; methane ; Near-infrared reflectance spectroscopy (NIRS) ; near-infrared spectroscopy ; phytomass ; prediction ; Prediction model ; sludge ; solid wastes ; Waste sludge ; wastewater</subject><ispartof>The Science of the total environment, 2024-02, Vol.912, p.169640-169640, Article 169640</ispartof><rights>2023 Elsevier B.V.</rights><rights>Copyright © 2023 Elsevier B.V. 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However, conventional anaerobic digestion (AD) approach for BMP test is time-consuming and labour-intensive. Currently, the technique of Near Infrared Spectroscopy (NIRS) is gaining prominence in the biogas production within AD process. Previous studies mostly focused on predicting BMP values for fibrous plant biomass and solid waste, with only a limited number of studies attempting to apply NIRS to obtain BMP values across a wide array of wasted sludge types. To obtain BMP values for this diverse range of wasted sludge efficiently and accurately, it is imperative to develop precise models for assessing BMP values using NIRS. In this study, the possibility of using NIRS to predict the BMP values of wasted sludge was evaluated. A total of 70 sludge samples from different sources were investigated to develop a BMP-prediction model by correlating the measured BMP values with the obtained NIR spectra. As a result, a reliable and successful BMP-prediction model was established with the determination coefficient of 0.90, residual prediction deviation of 3.50 and low root mean square error of prediction of 36.8 mL CH4/g VS. This BMP-prediction model is satisfactory for predicting BMP values of various types of sludge. It could provide support for plant operators to make decisions rapidly, thereby improving the process efficiency and optimizing sludge management procedures. 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subjects Anaerobic digestion
Biochemical methane potential (BMP)
environment
gas production (biological)
methane
Near-infrared reflectance spectroscopy (NIRS)
near-infrared spectroscopy
phytomass
prediction
Prediction model
sludge
solid wastes
Waste sludge
wastewater
title Near-infrared reflectance spectroscopy for rapid prediction of biochemical methane potential of wastewater wasted sludge
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