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Detection technology for phosphorus species in water

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Detection of phosphorus species in water: technology and strategies

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Phosphorus species are the sum of naturally evolved phosphorus elements with diverse forms of existence and unique properties. The detection and analysis of the optical properties of unknown phosphorus species via direct or indirect strategies offers unique advantages in understanding the growth processes and existence characteristics of various chemicals and microorganisms in water environments. This review highlights recent advances and future trends in methods of detection of total phosphorus in water, including photoelectric strategies, spectroscopy techniques, and modeling algorithms. These methods effectively explore the dynamic changes of total phosphorus content in complex water environments to reveal important signals in water, which is of great guiding significance for achieving accurate detection of water quality and promoting social development. We also discuss some extended strategies for its measurement and prediction via rational design and cross-combination, which may help inspire future design of more accurate and intelligent detection models or systems. The strategies based on these types of total phosphorus detection methods provide a versatile platform for novel sensors and thereby show great potential in the development of future water quality detection applications.

Graphical abstract: Detection of phosphorus species in water: technology and strategies


Fig. 1 Digital imaging colorimetry feature (a, b) and absorption spectra (c) of the interacting systems of potassium dihydrogen phosphate with molybdate solution and ascorbic acid Molybdate solution, 1.0 ml; Ascorbic acid, 3.57 g/L; Total phosphorus (mg/L): 1, 0.00; 2, 1.78; 3, 3.57; 4, 5.36; 5, 7.14; 6, 8.93. Reproduced from ref. 58 with permission from Elsevier B.V., copyright 2007.


Fig. 2 (a) Schematic diagram of the instrument; (b) The disassembled camera and parameter settings; (c) Constant light intensity circuit; (d) Color of the standard sequence and the corresponding concentration. Reproduced from ref. 64 with permission from the Royal Society of Chemistry, copyright 2018.


Fig. 3 (a) Diagrammatic description of the flow analysis system used for determination of total phosphorus. Sample or standard is pumped through a 100m mesh, followed by the addition of acidic peroxodisulfate oxidant (Ox). P1 and P2 are peristaltic pumps. The stream undergoes mineralisation in the UV reactor (UV-R) and a thermal reactor coil (TR), followed by filtration using a hollow fibre filter (HFF) and debubbling (DB), overflow from the debubbler goes to waste (W). Filtered digested sample is pumped into a reagent injection flow analyser, where reagents (R1 - acidic molybdate solution and R2 - acidic tin (II) chloride reductant) are delivered into the stream. Absorbance is measured using a multi-reflective cell coupled with a low-power 660nm light emitting diode source. Reproduced from ref. 69 with permission from Elsevier B.V., copyright 2010; (b) Flow Injection analyzer based on programmable flow, configured for automated analysis of phosphate. The confluence point is marked by the red circle. Reproduced from ref. 56 with permission from Elsevier B.V., copyright 2019.


Fig. 4 (a) Microfluidic chip layout with sample (S) and reagent (R) inlets, a serpentine reaction channel and viewing area (V), and waste outlet (W); (b) cross-sectional view of the microfluidic chip holder and detection components; (c) Diagram of the phosphate sensor and base station. Reproduced from ref. 48 with permission from Elsevier B.V., copyright 2007.


Fig. 5 (a) A schematic of the chip. The microstructures are designed in the microchannel. The width of the channel in the microreactor is 250 μm and the width of the channel in the F–P cavity is 300 μm; (b) The design of the microcavity, which is made from two parallel reflectors by coating gold films on the surface of optical fibers. Reproduced from ref. 76 with permission from the Royal Society of Chemistry, copyright 2017.


Fig. 6 (a) Absorption spectra of fosfate (0.05–1.5 μM) obtained by DSDME microvolume spectrophotometry. Reproduced from ref. 83 with permission from Elsevier B.V., copyright 2011; (b) Calibration curve obtained on the PhosphaSense system using prepared phosphate standards, where error bars show one standard deviation, with a slope of 0.003 AUL/μg and an R2 of 0.9958. The absorbance spectrum of the molybdenumblue product is shown in the top left insert. Reproduced from ref. 28 with permission from Elsevier B.V., copyright 2017; (c) Absorption spectra for 2.0 mg/L phosphate and their mixture; CWT spectra of species, in the presence of 0.02 mol/L ammonium molybdate and 3.0×10-2 -mol/L ascorbic acid. Reproduced from ref. 85 with permission from Springer Nature, copyright 2016.


Fig. 7 (a) The EDXRF spectrum of the sample containing 20 mg of phosphorus. Measurement was carried out under helium atmosphere; (b) Relationship between molybdenum radiation intensity and mass of extracted phosphorus. Error bars represent the standard deviation for N=6. Reproduced from ref. 90 with permission from the Royal Society of Chemistry, copyright 2012; (c) Relationship between molybdenum radiation intensity and concentration of the preconcentrated phosphorus. Error bars represent the standard deviation for N=3. Reproduced from ref. 91 with permission from the John Wiley and Sons, copyright 2015.


Fig. 8 (a) Fluorescence signals versus phosphate concentration for different flow velocities (7.1 (1), 6.1 (2), 4.3 (3) and 3.5 (4) mL/min) at constant injected volumes of 15 μL. Inset: original measurement data of the flow rate experiments for 4.3 and 6.1 mL min-1 are shown. Error bars ±3 standard deviation, n=15. Reproduced from ref. 92 with permission from Elsevier B.V., copyright 2014; (b) Quenching in fluorescence intensity of TGA capped CdTe QDs (400 μL,2 mg/ml) when titrated with 0.39 mM of Eu(NO3)3.Spectra with control and Spectra without control (elaborated to view the readings); (c) Restoration of fluorescence intensity of QD-Eu complex on addition of increasing concentrations of phosphate; (d) Change in peak fluorescence intensity of QD-Eu complex, with varying concentrations of phosphate. Reproduced from ref. 96 with permission from Elsevier B.V., copyright 2016.


Fig. 9 (a) Concentration-dependent Raman intensities of nitrate (1,056 cm−1) and nitrite (1,326 cm−1) in DI water determined by SERS coupled with gold nanosubstrates. The nitrate and nitrite concentrations (ranging from 1 to 1,000 mg/L) in each sample were the same. Reproduced from ref. 103 with permission from Springer Nature, copyright 2013; (b) SERS spectra of As(III) at different concentrations of 0, 10, 50,100, 500, and 1000 ppb, and (b) calibration curves for As. Reproduced from ref. 104 with permission from the Royal Society of Chemistry, copyright 2014; (c) SERS spectra of pyrocatechol on colloidal TiO2 NPs in the presence of phosphate anions with different concentrations. The concentrations from top to bottom are 0, 2, 6, 10, 20, 40, 60, 80, 100, 150, and 300 μM. The relative Raman intensity [(IR0–IR)/IR0] at 1481 cm−1 versus the phosphate anion concentration. Reproduced from ref. 105 with permission from the Royal Society of Chemistry, copyright 2015.


Fig. 10 (a) Conceptual model for estimating steady state phosphate concentrations in P-limited aquatic environments; (b)Total planktonic regeneration of dissolved phosphorus as a function of total P for all lakes. Reproduced from ref. 109 with permission from Springer Nature, copyright 2005; (c) Scatter plots summarizing how annual anomalies in measured total nitrogen and phosphorus concentrations were correlated to anomalies in modelled concentrations and water discharge for each of the investigated sites. Reproduced from ref. 110 with permission from Springer Nature, copyright 2014.


Fig. 11 (a) Flow chart for GAPLS model, the left diagram shows how GA processes spectral variables according to water quality parameters and the right diagram shows how PLS performs the regression according both spectral variables determined via GA and water quality parameters. (b) Scatter plot of measured vs. predicted TP for GA-PLS and error residual histogram for various datasets. Reproduced from ref. 125 with permission from Springer Nature, copyright 2012; (c) Variations of correlation coefficient between TP and band ratios Rrs (λ1)/Rrs (λ2) in the spectral range of 400 - 900 nm, obtained by using the total samples of three water types and the aggregated data; (d) Scatter plots between measured and predicted TP concentrations by using the developed SVR models. Reproduced from ref. 126 with permission from Springer Nature, copyright 2014; (e) Spatial pattern of total phosphorus concentration. Reproduced from ref. 127 with permission from Springer Nature, copyright 2015.

Conclusion and perspective

The construction of methodology integrated high selectivity, sensitivity, and low limit of detection has recently emerged as a promising field for water quality detection based on total phosphorus. In this review, three major types of strategies for accurate detection of total phosphorus in water, including photoelectronic detections, spectral analysis techniques, and modeling algorithms, have been described in detail. Some selective examples aimed to illustrate the importance of rational utilizing natural optical and chemical properties of phosphorus species as driving forces to achieve highly credible analysis and detection, which may provide guidance for the design and proposal of new strategies.

In comparison with other strategies, the photoelectric detection strategy can convert the optical characteristics into electrical signals, thus intuitively reflecting the measurement results by digital electronic technology. Obviously, the development of automation and intelligent analysis should be an inevitable trend in the field of current water quality detection. Furthermore, spectral technology is one of the most effective analytical tools developed on the basis of photoelectric technique for water quality detection. It not only improves the detection accuracy and lower the limit of detection, but also represents the direction where the total phosphorus detection moves forward. For example, the rapidly developing Raman spectroscopy and atomic emission spectroscopy technologies hold more potential to analyze the content of various forms of phosphate, organophosphorus and elemental phosphorus in phosphorus species. As an auxiliary tool, the modeling algorithm strategy can be effectively combined with other strategies to establish water quality models, which can not only analyze and predict the total phosphorus content in water, but also improve our understanding of the spatiotemporal dynamics of total phosphorus in water.

Although these achievements and progress are encouraging, there are still many challenges waiting to be overcomed. Firstly, the methods for detecting and analyzing total phosphorus are not abundant enough and are still evolving. Due to the lack of cross-applications between various disciplines, the combined available driving forces are just beginning to be explored. Secondly, the unknown water environment may contain more complex chemicals and microorganisms. Their existence characteristics and growing mechanism remain unclear, which may limit the precise control and analysis of total phosphorus. Lastly, the characteristics, properties, and intrinsic relevance of phosphorus species with diverse forms in water environment should be considered to develop more advanced photosensors, chemical sensors, and biosensors for directed measurement, effectively avoiding complex sample pretreatment processes. Future studies will be focused not only on measuring and analyzing total phosphorus content and complicated morphologies in water through a combination of effective strategies, but also on the accumulation of phosphorus in the soil, human body and other conditions that may trigger related diseases to broaden their applications.


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