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Kwon DY, Kim J, Park S, Hong S. Advancements of remote data acquisition and processing in unmanned vehicle technologies for water quality monitoring: An extensive review. CHEMOSPHERE 2023; 343:140198. [PMID: 37717916 DOI: 10.1016/j.chemosphere.2023.140198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 08/28/2023] [Accepted: 09/14/2023] [Indexed: 09/19/2023]
Abstract
Regular water quality monitoring is becoming desirable due to the increase in water pollution caused by both climate change and the generation of industrial chemicals. Unmanned vehicles have emerged as key technologies for remote data acquisition, providing fast and accurate methods for water quality monitoring. However, current research on unmanned vehicles has not systematically examined their features and limitations, which are crucial for identifying future research directions and applications of unmanned vehicle technologies. Therefore, this study extensively reviews the advancements in remote data acquisition and processing using unmanned vehicle technologies for water quality monitoring to provide valuable insights for future research. First, the types of unmanned vehicles and their application ranges for water quality monitoring are summarized. Among the unmanned vehicle technologies, unmanned aerial vehicles are considered primary platforms for water quality monitoring due to their wide data acquisition range and their ability to accommodate diverse sensors and samplers. Also, the types of samplers and sensors mounted on the unmanned vehicles are analyzed based on their characteristics. It is concluded that spectral sensors offer the most cost-effective approach for acquiring real-time water quality data. Furthermore, algorithms that convert image data into water quality data are examined, focusing on data preprocessing, analysis, and validation. The findings reveal a close relationship between the analysis of spectral characteristics of each water quality parameter and the wavelength ranges of red and red-edge. Lastly, future research directions for unmanned vehicle technologies are further suggested based on the summarized technological limitations.
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Affiliation(s)
- Da Yun Kwon
- School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Jungbin Kim
- School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea; Department of Environmental Science, College of Science, Mathematics and Technology, Wenzhou-Kean University, 88 Daxue Road, Ouhai, Wenzhou, 325060, Zhejiang Province, China
| | - Seongyeol Park
- School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Seungkwan Hong
- School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.
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A Rapid UV/Vis Spectrophotometric Method for the Water Quality Monitoring at On-Farm Root Vegetable Pack Houses. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10249072] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Our research aim was to apply UV/Vis spectrophotometric techniques for the rapid monitoring of the quality of water sourced from on-farm root vegetable washing processes. To achieve this goal, the quality assessment of the washing water and wastewater at different stages of the technological processes was performed using physicochemical, biological, and UV/Vis absorbance measurements as well as statistical methods, such as principal component analysis (PCA) and partial least squares (PLS) regression. Limit values of UV/Vis absorbance at specific wavelengths were predicted in order to adapt them for routine testing and water quality monitoring at the farm packhouses. Results of the lab analyses showed, that the main problems of the water quality were caused by suspended solids (470–3400 mg L−1), organic substances (BOD5 215–2718 mg L−1; COD 540–3229 mg L−1), nitrogen (3–52 mg L−1), phosphorus (1–6 mg L−1), and pathogenic microorganisms (TVC > 300 cfu mL−1, E. coli 5.5 × 103–1.0 × 104 cfu mL−1, intestinal enterococci 2.8 × 102–1.5 × 104 cfu mL−1, coliform bacteria 1.6 × 103–2.0 × 104 cfu mL−1). Suspended solids exceeded the limit values by 10–50 times, organic matter by 10–25 times, dissolved organic carbon by 3–5 times, nitrogen by 3–7 times, total phosphorus by 3–12 times, and microorganisms by 3–10 times. UV/Vis limit values calculated were as follows: A210 nm—3.997–4.009 cm−1, A 240 nm—5.193–5.235 cm−1, A254 nm—4.042–4.047 cm−1, A320 nm—7.387–7.406 cm−1, and A 660 nm—3.937–3.946 cm−1. UV/Vis measurements at A320 nm are proposed for the routine water quality monitoring.
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Bayo J, López-Castellanos J. Principal factor and hierarchical cluster analyses for the performance assessment of an urban wastewater treatment plant in the Southeast of Spain. CHEMOSPHERE 2016; 155:152-162. [PMID: 27108373 DOI: 10.1016/j.chemosphere.2016.04.038] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Revised: 03/07/2016] [Accepted: 04/10/2016] [Indexed: 06/05/2023]
Abstract
Process performance and operation of wastewater treatment plants (WWTP) are carried out to ensure their compliance with legislative requirements imposed by European Union. Because a high amount of variables are daily measured, a coherent and structured approach of such a system is required to understand its inherent behavior and performance efficiency. In this sense, both principal factor analysis (PFA) and hierarchical cluster analysis (HCA) are multivariate techniques that have been widely applied to extract and structure information for different purposes. In this paper, both statistical tools are applied in an urban WWTP situated in the Southeast of Spain, a zone with special characteristics related to the geochemical background composition of water and an important use of fertilizers. Four main factors were extracted in association with nutrients, the ionic component, the organic load to the WWTP, and the efficiency of the whole process. HCA allowed distinguish between influent and effluent parameters, although a deeper examination resulted in a dendrogram with groupings similar to those previously reported for PFA.
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Affiliation(s)
- Javier Bayo
- Depart. of Chemical and Environmental Engineering, Technical University of Cartagena, Paseo Alfonso XIII, 44 E-30203 Cartagena, Spain.
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Mesquita DP, Amaral AL, Ferreira EC. Activated sludge characterization through microscopy: A review on quantitative image analysis and chemometric techniques. Anal Chim Acta 2013; 802:14-28. [DOI: 10.1016/j.aca.2013.09.016] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 09/05/2013] [Accepted: 09/07/2013] [Indexed: 02/07/2023]
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Farmaki EG, Thomaidis NS, Simeonov V, Efstathiou CE. A comparative chemometric study for water quality expertise of the Athenian water reservoirs. ENVIRONMENTAL MONITORING AND ASSESSMENT 2012; 184:7635-7652. [PMID: 22270597 DOI: 10.1007/s10661-012-2524-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2011] [Accepted: 01/04/2012] [Indexed: 05/31/2023]
Abstract
The aim of the present study is to compare the application of unsupervised and supervised pattern recognition techniques for the quality assessment and classification of the reservoirs used as the source for the domestic and industrial water supply of the city of Athens, Greece. A new optimization strategy for sampling, monitoring, and water management is proposed. During the period of October 2006 to April 2007, 89 samples were collected from the three water reservoirs (Iliki, Mornos, and Marathon), and 13 parameters (metals and metalloids) were analytically determined. Generally, all the elements were found to fluctuate at very low levels, especially for Mornos that comprises the main water reservoir of Athens. Iliki and Marathon showed relatively elevated values, compared to Mornos, but below the legislative limits. Multivariate unsupervised statistical techniques, such as factor analysis/principal components analysis, and cluster analysis and supervised ones, like discriminant analysis and classification trees, were applied to the data set, and their classification abilities were compared. All the chemometric techniques successfully revealed the critical variables and described the similarities and dissimilarities among the sampling points, emphasizing the individual characteristics in every sample and revealing the sources of elements in the region. New data from posterior samplings (November and December 2007) were used for the validation of the supervised techniques. Finally, water management strategies were proposed concerning the sampling points and representative parameters.
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Affiliation(s)
- Eleni G Farmaki
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimioupolis Zografou, 15771 Athens, Greece
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Bioreactor monitoring with spectroscopy and chemometrics: a review. Anal Bioanal Chem 2012; 404:1211-37. [DOI: 10.1007/s00216-012-6073-9] [Citation(s) in RCA: 185] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 04/21/2012] [Indexed: 11/26/2022]
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Qin X, Gao F, Chen G. Wastewater quality monitoring system using sensor fusion and machine learning techniques. WATER RESEARCH 2012; 46:1133-44. [PMID: 22200261 DOI: 10.1016/j.watres.2011.12.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2011] [Revised: 10/04/2011] [Accepted: 12/05/2011] [Indexed: 05/12/2023]
Abstract
A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality.
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Affiliation(s)
- Xusong Qin
- Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
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Valotto G, Quaranta A, Melgani F, Gonella F, Rampazzo G. Multivariate analysis as a tool for Ion Beam Induced Luminescence (IBIL) spectra interpretation. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2011; 81:353-358. [PMID: 21767982 DOI: 10.1016/j.saa.2011.06.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2011] [Revised: 06/07/2011] [Accepted: 06/14/2011] [Indexed: 05/31/2023]
Abstract
Multivariate analysis is used to identify the number and wavelength position of components evolving during irradiation with different rates in Ion Beam Induced Luminescence (IBIL) spectra. The method, based on the study of the eigenvectors of the matrix whose elements are the luminescence intensity values for different wavelengths and fluences, is tested on two different simulated cases and on experimental IBIL spectra collected from a polysiloxane scintillators.
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Affiliation(s)
- G Valotto
- Department of Environmental Science, Informatics and Statistics, Università Ca' Foscari Venezia, Dorsoduro 2137, I-30123 Venezia, Italy.
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Characterization of activated sludge abnormalities by image analysis and chemometric techniques. Anal Chim Acta 2011; 705:235-42. [DOI: 10.1016/j.aca.2011.05.050] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2010] [Revised: 04/29/2011] [Accepted: 05/31/2011] [Indexed: 11/15/2022]
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Lourenço ND, Paixão F, Pinheiro HM, Sousa A. Use of spectra in the visible and near-mid-ultraviolet range with principal component analysis and partial least squares processing for monitoring of suspended solids in municipal wastewater treatment plants. APPLIED SPECTROSCOPY 2010; 64:1061-1067. [PMID: 20828444 DOI: 10.1366/000370210792434332] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
The present work assesses the possibility of using spectrophotometry in the near-mid-ultraviolet and visible wavelength ranges (282-790 nm) for the direct monitoring of treatment performance in municipal wastewater treatment plants (WWTPs). Principal component analysis (PCA) was used to analyze spectral data from samples collected along three WWTP process lines with different primary and secondary treatment units. The clustering observed in PCA score plots was mainly attributed to the suspended solids fraction present in the wastewater and highlighted differences in solids quality between plants and along the treatment lines. Thus, satisfactory partial least squares (PLS) calibration models to estimate total suspended solids (TSS) values from the acquired spectra could only be established per plant. The PLS models were established using 1-2 factors, with root mean error of cross-validation and coefficient of determination values in the 50-86 mg TSS L(-1) and 82-95% ranges, respectively.
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Affiliation(s)
- Nídia D Lourenço
- Institute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, Technical University of Lisbon, Av. Rovisco Pais 1049-001 Lisbon, Portugal.
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Razmkhah H, Abrishamchi A, Torkian A. Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehran, Iran). JOURNAL OF ENVIRONMENTAL MANAGEMENT 2010; 91:852-60. [PMID: 20056527 DOI: 10.1016/j.jenvman.2009.11.001] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2008] [Revised: 10/29/2009] [Accepted: 11/08/2009] [Indexed: 05/24/2023]
Abstract
In this paper, principal component analysis (PCA) and hierarchical cluster analysis (CA) methods have been used to investigate the water quality of Jajrood River (Iran) and to assess and discriminate the relative magnitude of anthropogenic and "natural" influences on the quality of river water. T, EC, pH, TDS, NH(4), NO(3), NO(2), Turb., T.Hard., Ca, Mg, Na, K, Cl, SO(4), SiO(2) as physicochemical and TC, FC as biochemical variables have been analyzed in the water samples collected every month over a three-year period from 18 sampling stations along a 50 km section of Jajrood River that is under the influence of anthropogenic and natural changes. Exploratory analysis of experimental data has been carried out by means of PCA and CA in an attempt to discriminate sources of variation in water quality. PCA has allowed identification of a reduced number of mean 5 varifactors, pointing out 85% of both temporal and spatial changes. CA classified similar water quality stations and indicated Out-Meygoon as the most polluted one. Ahar, Baghgol, Rooteh, Befor Zaygan, Fasham, Roodak and Lashgarak were identified as affected by organic pollution. A Scree plot of stations in the first and second extracted components on PCA also gave us a classification of stations due to the similarity of pollution sources. CA and PCA led to similar results, though Out-Meygoon was identified as the most polluted station in both methods. Box-plots showed that PCA could approximately demonstrate temporal and spatial variations. CA gave us an overview of the problem and helped us to classify and better explain the PCA results.
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Lourenço ND, Menezes JC, Pinheiro HM, Diniz D. Development of PLS calibration models from UV-Vis spectra for TOC estimation at the outlet of a fuel park wastewater treatment plant. ENVIRONMENTAL TECHNOLOGY 2008; 29:891-898. [PMID: 18724644 DOI: 10.1080/09593330802015581] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
In the present work ultraviolet (UV)-visible spectra of water samples collected at the outlet of a fuel park wastewater treatment plant, including biological treatment, were acquired and used for the development of partial least squares (PLS) calibration models for the fast and simple estimation of total organic carbon (TOC). Three different PLS models were developed and compared on the basis of a common spectral range. The first model was obtained using spectra of raw samples, the second using spectra of diluted samples, to assess signal saturation in the UV region, and the third using spectra of both diluted and raw samples, in order to expand the narrow interval of TOC concentration values present in the original dataset. The root mean squared error of cross-validation values for the developed PLS models were 2.3, 1.0 and 4.4 mg Cl(-1), respectively, and the validation results where highly satisfactory (root mean squared error of prediction values of 1.8, 0.8 and 4.5 mg Cl(-1), respectively).
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Affiliation(s)
- N D Lourenço
- IBB - Institute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, Instituto Superior Técnico, Technical University of Lisbon, Lisboa, Portugal
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