Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process

Franca, Rita Dias Guardão; Carvalho, V.C.F.; Fradinho, Joana; Reis, Maria A.M.; Lourenço, Nídia D.

doi:10.3390/app11146600

Cited by 3 publications

(1 citation statement)

References 45 publications

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“…The biomass concentration was measured by dual excitation fluorometer developed in-house which was based on spectrophometer readings. In the method described, Franca et al [ 27 ] had great success in inferring the CO

, NO

, and total P concentrations. By using spectrophotometric measurements as input for the inferences, it was possible to manipulate the feed rate of CO

and control nitrogen and phosphorus concentrations.…”

Section: Introductionmentioning

confidence: 99%

Online Control of Lemna minor L. Phytoremediation: Using pH to Minimize the Nitrogen Outlet Concentration

Sigcau

Rooyen

Hoek

et al. 2022

Plants

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Phytoremediation technologies are employed worldwide to remove nutrient pollutants from agricultural and industrial wastewater. Unlike in algae-based nutrient removal, control methodologies for plant-based remediation have not been standardized. Control systems that guarantee consistently low outlet concentrations of nitrogen and phosphorous often use expensive analytical instruments and are therefore rarely viable. In this study, pH measurement was used as the sole input to control the nitrate outlet concentration in a continuously operated Lemna minor (lesser duckweed) phytoremediation tank. When grown in 20 L batches of modified Hoagland’s solution, it was found that a constant ratio exists between the amount of nitrate removed and the amount of acid dosed (required for pH control), which was equal to 1.25 mol N·(mol H+)−1. The nitrate uptake rates were determined by standard spetrophotometric method. At critically low nitrate concentrations, this ratio reduced slightly to 1.08 mol N·(mol H+)−1. Assuming a constant nitrogen content, the biomass growth rate could be predicted based on the acid dosing rate. A proportional-integral controller was used to maintain pH on 6.5 in a semi-continuously operated tank covered by L. minor. A nitrogen control strategy was developed which exploited this relationship between nitrate uptake and dosing and successfully removed upwards of 80% of the fed nitrogen from synthetic wastewater while a constant biomass layer was maintained. This study presents a clear illustration of how advanced chemical engineering control principles can be applied in phytoremediation processes.

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, NO

, and total P concentrations. By using spectrophotometric measurements as input for the inferences, it was possible to manipulate the feed rate of CO

and control nitrogen and phosphorus concentrations.…”

Section: Introductionmentioning

confidence: 99%

Online Control of Lemna minor L. Phytoremediation: Using pH to Minimize the Nitrogen Outlet Concentration

Sigcau

Rooyen

Hoek

et al. 2022

Plants

View full text Add to dashboard Cite

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Fast detection of volatile fatty acids in biogas slurry using NIR spectroscopy combined with feature wavelength selection

Sun²,

Chen³

et al. 2023

Science of The Total Environment

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Identification of the interference spectra of edible oil samples based on neighborhood rough set attribute reduction

XU¹,

Wu²,

GONG³

et al. 2023

Appl. Opt.

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Due to numerous edible oil safety problems in China, an automatic oil quality detection technique is urgently needed. In this study, rough set theory and Fourier transform spectrum are combined for proposing a digital identification method for edible oil. First, the Fourier transform spectra of three different types of edible oil samples, including colza oil, waste oil, and peanut oil, are measured. After the input spectra are differentially and smoothly processed, the characteristic wavelength bands are selected with neighborhood rough set attribution reduction (NRSAR). Moreover, the classification models are established based on random forest (RF) and extreme learning machine (ELM) algorithms. Finally, confusion matrix, classification accuracy, sensitivity, specificity, and the distribution of judgment are calculated for evaluating the classification performances of different models and determining the optimal oil identification model. The results show that by using the third-order difference pre-processing method, 193 wavelength bands in the visible range can be reduced to 10 characteristic wavelengths, with a compression ratio of over 88.61%. Using the established NRS-RF and NRS-ELM models, the total identification accuracies are 91.67% and 93.33%, respectively. In particular, the identification accuracy of peanut oil using the NRS-ELM model reaches up to 100%, whereas the identification accuracies obtained using the principal component analysis (PCA)-based models that are commonly used in information processing (PCA-RF and PCA-ELM) are 81.67% and 90.00%, respectively. As compared with feature extraction methods, the proposed NRSAR shows directive advantages in terms of precision, sensitivity, specificity, and the distribution of judgment. In addition, the execution time is also reduced by approximately 1/3. Conclusively, the NRSAR method and NRS-ELM the model in the spectral identification of edible oil show favorable performance. They are expected to bring forth insightful oil identification techniques.

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Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process

Cited by 3 publications

References 45 publications

Online Control of Lemna minor L. Phytoremediation: Using pH to Minimize the Nitrogen Outlet Concentration

Online Control of Lemna minor L. Phytoremediation: Using pH to Minimize the Nitrogen Outlet Concentration

Fast detection of volatile fatty acids in biogas slurry using NIR spectroscopy combined with feature wavelength selection

Identification of the interference spectra of edible oil samples based on neighborhood rough set attribute reduction

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