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Article

On-Site Detection of Ca and Mg in Surface Water Using Portable Laser-Induced Breakdown Spectroscopy

1
School of Photoelectric Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2
Research Center of Intelligent Equipment, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
3
Key Laboratory of Agricultural Sensors, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
*
Author to whom correspondence should be addressed.
Chemosensors 2025, 13(1), 16; https://doi.org/10.3390/chemosensors13010016
Submission received: 29 November 2024 / Revised: 23 December 2024 / Accepted: 9 January 2025 / Published: 14 January 2025
(This article belongs to the Special Issue Application of Laser-Induced Breakdown Spectroscopy, 2nd Edition)

Abstract

:
Ca and Mg are key constituents in surface water that are essential nutrients and vital indicators of water hardness. Rapid on-site measurement of Ca and Mg concentrations in surface water is important. However, traditional laboratory detection methods are complex and time-consuming, and on-site detection is difficult. In this study, a portable surface water detection method was developed using laser-induced breakdown spectroscopy with a miniaturized spectrometer LIBS and a liquid jet device for sample introduction. The device enables the rapid online in situ measurement of elemental concentrations in the water. The limits of detection for the rapid on-site detection of Ca and Mg in surface water were 11.58 and 2.57 mg/L, respectively. We applied this method to assess the concentrations of Ca and Mg in authentic water samples collected from rivers and ponds. The recovery rates for Ca and Mg were 90.83–101.74% and 93.43–108.74%, respectively. This method is suitable for rapid, on-site, and highly sensitive monitoring of Ca and Mg concentrations in the environment.

1. Introduction

Public health, agricultural irrigation, and ecosystems are all directly affected by the quality of surface water [1]. The determination of Ca and Mg concentrations is important for monitoring the quality of surface water [2]. The concentrations of these ions can be used to assess the hardness of surface water and evaluate the water quality [3,4]. This is important for the protection of water resources, safeguarding human health, and maintenance of ecological balance. For human health, the concentrations of Ca and Mg ions serve as a crucial indicator of water hardness [5]. These ions influence water characteristics such as color, pH, and dissolved oxygen, and are closely correlated with cardiovascular disease and cancer [6,7]. In aquaculture, Ca and Mg are vital components of the skeletons, scales, and shells of shrimp and crabs, and play an important role in their growth [8]. Furthermore, the concentrations of Ca and Mg in surface water affect the growth of aquatic plants [9,10]. Consequently, the prompt detection of Ca and Mg concentrations in surface water is of practical significance.
Traditional water quality testing methods include atomic absorption spectrometry (AAS) [11], atomic emission spectrometry (AES) [12], inductively coupled plasma-mass spectrometry (ICP-MS) [13], and fluorescence spectrometry (FS) [14]. These methods are precise and stable. However, some of these techniques require intricate sample preprocessing procedures, while others can only detect a single element type at a time, which makes them unsuitable for rapid water quality assessments. Currently, the primary on-site detection methods are electrochemical methods, biosensors, and spectroscopic techniques. Electrochemical methods feature high sensitivity and good selectivity in detection but are plagued by issues such as high electrode maintenance costs and limitations to a single detection parameter [15]. Biosensors offer high precision and multiple selective options but suffer from difficulties with storage and are prone to environmental interference, which leads to insufficient reliability [16,17]. Consequently, the development of a technique for rapid on-site detection of Ca and Mg concentrations in surface water is important.
Laser-induced breakdown spectroscopy (LIBS) [18,19] is an atomic spectroscopic technique that involves exciting samples into a plasma state using a high-energy, focused pulsed laser beam. This excitation leads to the emission of spectra corresponding to the constituent elements of the sample [20]. The intensity of the spectrum is measured to determine the types and concentrations of the elements. LIBS technology is rapid, sensitive, and suitable for multi-element analysis [21]. This method has been used extensively in geology [22], industry [23], food science [24], deep-sea exploration [25], and biomedicine [26]. Among them, it is used in the field of agri-environment for the measurement of soil and water. Especially for water detection, LIBS has an advantage. However, when directly detecting water, the interaction between the laser and the liquid surface can lead to liquid splashing and laser quenching. These problems seriously affect the analytical sensitivity and signal stability of LIBS signals. To enhance the sensitivity and stability of LIBS detection in aquatic samples, various sample preprocessing methods have been proposed, such as liquid-solid conversion, incorporating advanced materials, and converting water into jet flow. Typical liquid–solid conversion, such as using filter papers [27], graphite [28], electrochemical deposition [29], ion exchange membranes [30], and chelating resins [31], all effectively improve the sensitivity and stability of LIBS detection. However, the experimental setup is complex and difficult to implement for routine applications. The combination of LIBS with advanced materials such as nanoparticles (NPs) [32] and metal–organic frameworks (MOFs) [33] enhances the detection capability of trace metals in water and improves the selectivity toward specific elements. Nevertheless, this approach results in secondary contamination and prolongs detection times. As a direct method for measuring water, jets have good application potential in the direct measurement of water. Yueh et al. evaluated the ability of the jet mode to detect Mg, Cr, Mn, and Re and demonstrated that the jet mode has a better detection limit than the bulk mode [34]. Bhatt et al. found that the jet mode can effectively measure As, Hg, S, and Se in the water. These studies have shown that elemental concentrations in the water can be well assessed using the jet mode [35]. However, these studies rely on sophisticated equipment in laboratories and are difficult to use for on-site testing. To address this problem, we propose a portable in situ device for measuring Ca and Mg in water.
This paper introduces a portable method for in situ detection of Ca and Mg elements in surface water using LIBS combined with a liquid jet. This method employs a miniaturized LIBS system and a liquid jet device with a liquid jet sampling technique to achieve highly sensitive and stable in situ detection of surface water. Factors that significantly affected the LIBS spectrum were optimized. Under the optimum conditions, the qualitative and quantitative capabilities of the system for Ca and Mg were analyzed. Finally, the detection capabilities of the LIBS system were validated using actual surface water samples.

2. Experimental

2.1. The LIBS System

The LIBS setup (Figure 1) consisted of a Q-switched Nd:YAG laser (16.2 × 6.0 × 6.6 cm3), a laser controller (15.2 × 5.6 × 5.6 cm3), a spectrometer (17.2 × 12.7 × 4.5 cm3), a peristaltic pump (5 × 2.9 × 3.6 cm3), a power supply (16 × 8.2 × 4.7 cm3), a control board (11.4 × 6.6 × 2.9 cm3), optical fibers, and focusing lenses. Regarding the laser part, a Q-switched Nd:YAG laser (pulse duration: 10 ns; Beijing Leimeng Optoelectronic Technology Co., Ltd., Beijing, China), operating at 1064 nm and 10 Hz, was used as an ablation source. The laser pulse energy was set to 42 mJ. The laser beam passed through a mirror with a focal length of 50 mm, and then focused onto the sample surface to generate plasma. The spectral collector was positioned at a 45° angle to the laser-induced plasma and coupled via optical fibers to the spectrometer (grating of 3600 lines per mm; AvaSpec-ULS, Avantes, Apeldoorn, Netherlands) to collect the plasma emission spectrum. The spectrometer had a wavelength range of 180–800 nm and a spectral resolution of 0.05 nm. To minimize the influence of the continuous background, spectra were collected with an optimized delay time of 2 μs and an integration time of 30 μs. The jet device consisted of a miniature peristaltic pump, a sample reservoir, and a miniature needle tube (inner diameter: 0.64 mm). To mitigate the impact of irregularities on the liquid column’s surface on spectral stability, the distance between the laser ablation point and the nozzle was optimized to 5 mm. The liquid jet speed was 60 mL/min.

2.2. Sample Preparation

Two separate solutions of CaCl2 and MgCl2 were prepared in deionized water. All chemicals were sourced from Aladdin (Shanghai, China) and were >99% pure. The reagents in this experiment were prepared in strict accordance with the national standard of the People’s Republic of China GB/T 601-2016 [36]. Standard solutions containing 1000 mg/L Ca and Mg were prepared by dissolving 2.769 g of CaCl2 and 8.366 g of MgCl2·6H2O in 1 L of deionized water, respectively. Ten other standard solutions of Ca and Mg ranging from 20 mg/L to 750 mg/L were prepared by diluting the standard solutions by the stepwise dilution method. The concentration range for each solution was 20 to 1000 mg/L (Table 1). These solutions were used to build a quantitative model.

3. Results and Discussion

3.1. Typical LIBS Emission Spectra

The collected LIBS spectra are shown in Figure 2. The main characteristic peaks of Ca and Mg appeared between 275 and 425 nm. Within the spectral region of 275–290 nm, atomic emission lines of Mg were clearly visible at 279.55, 280.27, and 285.21 nm. The characteristic peak at 279.55 nm was much more intense than the other two peaks, and had no notable interference from other peaks. Consequently, 279.55 nm was selected as an ideal characteristic peak for the quantitative analysis of Mg to ensure the accuracy and reliability of the analytical results. For Ca, atomic emission lines were observed in the spectral ranges of 310–320 nm and 390–425 nm. The peak at 393.36 nm was selected as the characteristic peak for quantitative analysis of Ca because of its strong spectral intensity and absence of interference.

3.2. Optimization of the Spectral Acquisition Conditions

To optimize the analytical performance of the LIBS detection, we optimized the diameter of the jet liquid column and the laser ablation position (relative distance between the laser irradiation point on the jet and the jet orifice) as key parameters. The experimental data indicated that the direct influence of variation in the jet column diameter on the spectral intensity was relatively limited (Figure 3a). This observation aligns with our expectations in the experiment. This phenomenon can be attributed to the fact that laser energy is primarily focused on the surface of the liquid column for ablation, which means that slight adjustments to the liquid column diameter do not greatly alter the intensity of the spectral signal. However, further analysis revealed that as the liquid column diameter decreased, the laser ablation process exhibited greater stability. This may be caused by a reduction in the amount of water being ablated by the laser, which would reduce its susceptibility to signal quenching (Figure 3b). When the liquid column diameter was reduced to 0.64 mm, the spectral signal quenching phenomenon nearly disappeared completely. This change indicated that the interaction between the laser and the liquid column at this diameter was stable and controllable.
Subsequently, we concentrated on the mechanisms by which the relative distance between the jet orifice and the point of laser interaction affected LIBS when the laser was irradiated on the jet. The results revealed that the peak intensity was less affected by the laser ablation position (Figure 3c). However, substantial fluctuations in the spectral signals were observed when the relative distance was relatively far, with significant changes in the RSD (Figure 3d). This was attributed to the fluid dynamic characteristics of the jet. Upon ejection from the jet orifice, the liquid assumes a regular cylindrical shape. However, once it is freed from the confinement of solid boundaries, the liquid undergoes diffusive motion within the surrounding gas. As the relative distance between the jet column and the orifice increases, the regularity of the cylindrical water surface gradually deteriorates, which affects the laser ablation. This manifests as a large increase in the irregularity of the liquid column’s surface, which affects the stability of the spectral signals. The RSD did not differ much when the relative distance was 5 mm or 3 mm. Therefore, we concluded that the position of 5 mm from the jet orifice was optimal for laser ablation. At this position distance, the surface of the jet column maintained a regular shape, which facilitated spectral acquisition by the spectrometer. This position minimized spectral fluctuations that arose from the irregularity of the liquid column’s surface, which ensured smooth spectral acquisition. Consequently, this guaranteed the accuracy and reliability of LIBS detection.

3.3. Quantitative Analysis

To evaluate the effectiveness of liquid-jet LIBS for elemental analysis in a liquid, the concentrations of Ca and Mg were measured in the solution. The results were compared with those obtained using bulk liquid mode. Figure 4 shows the calibration curves of Ca and Mg for the concentrations and peak intensities in the two modes. In the bulk liquid mode, a fitting curve with a very poor correlation was obtained (Figure 4a,c). This was attributed to interactions between the laser beam and the liquid surface leading to issues such as liquid splashing, laser quenching, and self-absorption effects. Consequently, this method was not suitable to quantitatively analyze liquid samples. Jet mode significantly mitigated the adverse effects of the complex physical properties of bulk water. When water was converted into a jet, the linearity and stability of the LIBS spectra greatly improved (Figure 4b,d). This was attributed to effective control of liquid sample fluctuations and the laser-ablated liquid volume achieved with the jet, which reduced the complexity and uncertainty associated with direct laser–liquid interactions. Specifically, after adopting jet mode, the coefficient of determination of the calibration curve for Ca increased from 0.836 to 0.974 and the relative standard deviation (RSD) decreased from 27.38% to 21.26%. Similarly, the coefficient of determination of the calibration curve for Mg increased from 0.834 to 0.999 and the RSD decreased from 18.01% to 16.36%. However, the RSD remained at a high level after the use of the jet flow. This is due to the fact that slight fluctuations could be induced on the surface of the jet column by the impact force of the laser beam. And this slight fluctuation may cause the laser energy to be absorbed differently by the water. Meanwhile, during the formation process of the plasma, tiny bubbles generated in the liquid can alter the propagation path of the laser, resulting in a different effective energy for each laser-liquid interaction. The difference in the effective energy of the laser can alter the key plasma parameters of the spectrum, such as the formation time and temperature.
Although jet mode greatly improved the spectral signals obtained by LIBS, the signal stability was challenging for quantitative analysis. To address this issue, a method of accumulating and averaging multiple spectra was used to enhance the signal stability. This may be attributed to the averaging of multiple spectra, where random noise or minor fluctuations in each individual spectrum tend to cancel each other out during the averaging process. Consequently, as the number of spectra increases, the mean value becomes more stable, effectively reducing the RSD. The impact of averaging different numbers of accumulated spectra on the RSD was analyzed using a solution containing 100 mg/L Mg and 100 mg/L Ca, respectively (Figure 5). As the number of accumulated spectra increased, the RSD of the LIBS spectra gradually decreased, which indicated that the signal stability was enhanced. Notably, when 20 spectra were accumulated on average, the RSD decreased to approximately 2%. This relatively low value showed there was significant improvement in the signal stability, and the modified method was suitable for quantitative analysis.
Large enhancements in the quantitative analytical performance of jet LIBS were achieved through optimization. Clear increases in the intensities of the characteristic peaks for Ca and Mg were observed with increases in their concentrations in solution (Figure 6a,b). This served as the preliminary validation of the effectiveness and accuracy of the detection system. To assess the detection performance of the system with greater precision, linear fitting was conducted on the spectral intensities of Ca and Mg solutions at various concentrations. The resulting calibration curves are shown in Figure 6c,d. The calibration curves were nonlinear, with inflection points at 200 mg/L for Ca and 100 mg/L for Mg. The entire concentration range was divided into two segments, within which the signal intensities showed linear variations with the concentration gradient. This was attributed to the occurrence of self-absorption phenomena in the spectra of Ca and Mg at high concentrations [37,38]. When the concentration of the target element in the water body is high, the spectra emitted by atoms or ions in the laser-induced plasma may be absorbed by similar atoms or ions in the plasma. This self-absorption phenomenon is more pronounced at higher concentrations because higher concentrations mean that there are more absorbing particles in the plasma. According to regulations set by the International Union of Pure and Applied Chemistry, the detection capability of LIBS technology can be quantified by calculating the limit of detection (LOD). The LOD is calculated as LOD = 3σ/k, where σ is the standard deviation of the background signal in LIBS spectra, and k is the slope of the calibration curve for each element. The LOD is the minimum detectable concentration of an element under the given detection conditions, and a lower LOD indicates stronger detection capability. The calculated LODs for Ca and Mg in this study were 11.58 and 2.57 mg/L, respectively. Additionally, the RSDs for Ca and Mg were 4.42% and 4.25%, respectively.

3.4. Verification with Real Samples

To assess the detection performance of the portable LIBS in real surface water samples, pond water, and river water, samples were collected from the Haidian District in Beijing, China. These samples were submitted to a professional water quality testing institution for inductively coupled plasma-mass spectrometry analysis to determine the initial concentrations of Ca and Mg. Although directly detecting these elements at trace concentrations using liquid-jet LIBS is feasible, to provide a clearer indication of the detection capabilities, the water samples were spiked with Ca at 40, 80, 120, and 160 mg/L, and Mg at 20, 40, 60, and 80 mg/L. The recovery rates for Mg were 93.43–108.74%, and those for Ca were 90.83–101.74% (Table 2). These results suggest that the LIBS system is an effective method for in situ detection of Ca and Mg concentrations in aquatic environments. In future research, the LIBS system can be further optimized to enhance its detection sensitivity and stability. For example, components such as a more stable laser source, a more compact optical system, and more sensitive sensors can be used. Through these methods, noise and interference can be reduced, the quality of the spectrum can be improved, and the portability of the system can be achieved. Meanwhile, new algorithms and data processing methods should be developed to analyze the spectrum more accurately and improve the detection capability of the LIBS system.

4. Conclusions

A portable LIBS detection method was developed using miniaturized LIBS components and a jet device for sample introduction. Using this method, on-site, rapid, and highly sensitive detection of Ca and Mg concentrations in surface water was achieved. The jet stream diameter and the positioning of the laser ablation point within the water column were optimized. The best spectral acquisition conditions for the stability of the LIBS signals were obtained with a jet stream diameter of 0.64 mm and a position of 5 mm from the jet outlet. To enhance the signal stability, each final spectrum was derived by averaging 20 individually acquired spectra. This successfully reduced the RSD from approximately 16% to 2%. Under the optimal conditions, the detection sensitivity of the portable jet LIBS system gave LODs for Ca and Mg of 11.58 and 2.57 mg/L, respectively. To validate the detection capability of the LIBS system, two real surface water samples were used for verification. High recovery rates for both Ca (90.83–101.74%) and Mg (93.43–108.74%) were achieved, which showed that portable LIBS was suitable for application to on-site water quality analysis. This method is effective for on-site detection of Ca and Mg concentrations in surface water.

Author Contributions

Conceptualization, Y.W. and D.D.; methodology, Y.W. and S.M.; validation, Y.W. and H.T.; formal analysis, Y.W.; investigation, Z.X., L.J. and P.Z.; resources, D.D., Z.X. and X.Z.; data curation, Y.W. and X.Z.; writing—original draft preparation, Y.W. and S.M.; writing—review and editing, Y.W., S.M. and H.T.; supervision, P.Z. and L.J.; project administration, S.M. and H.T.; funding acquisition, D.D., H.T. and Z.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by National Natural Science Foundation of China (32225035, 32271977, 32171627) and the Science and Technology Innovation Ability Construction Project of Beijing Academy of Agriculture and Forestry Science (No. KJCX20220405) and Beijing Agricultural Research System Innovation Consortium (BAIC08-2024-FQ04).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Acknowledgments

This work was supported by National Natural Science Foundation of China (32225035, 32271977, 32171627), the Science and Technology Innovation Ability Construction Project of Beijing Academy of Agriculture and Forestry Science (No. KJCX20220405) and Beijing Agricultural Research System Innovation Consortium (BAIC08-2024-FQ04).

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Farouk, M.I.H.Z.; Zadariana, J.; Mohd, F.A.L. Towards Online Surface Water Quality Monitoring Technology: A Review. Environ. Res. 2023, 238, 117147. [Google Scholar] [CrossRef] [PubMed]
  2. Bogart, S.J.; Azizishirazi, A.; Pyle, G.G. Challenges and Future Prospects for Developing Ca and Mg Water Quality Guidelines: A Meta-Analysis. Philos. Trans. R. Soc. B-Biol. Sci. 2019, 374, 20180364. [Google Scholar] [CrossRef] [PubMed]
  3. Koseki, M.; Fujiki, S.; Tanaka, Y.; Noguchi, H.; Nishikawa, T. Effect of Water Hardness on the Taste of Alkaline Electrolyzed Water. J. Food Sci. 2006, 70, S249–S253. [Google Scholar] [CrossRef]
  4. Markich, S.J. Water Hardness Reduces the Accumulation and Toxicity of Uranium in a Freshwater Macrophyte (Ceratophyllum Demersum). Sci. Total Environ. 2013, 443, 582–589. [Google Scholar] [CrossRef]
  5. Kozisek, F. Regulations for Calcium, Magnesium or Hardness in Drinking Water in the European Union Member States. Regul. Toxicol. Pharmacol. 2020, 112, 104589. [Google Scholar] [CrossRef]
  6. Rapant, S.; Cvečková, V.; Fajčíková, K.; Sedláková, D.; Stehlíková, B. Impact of Calcium and Magnesium in Groundwater and Drinking Water on the Health of Inhabitants of the Slovak Republic. Int. J. Environ. Res. Public Health 2017, 14, 278. [Google Scholar] [CrossRef]
  7. Escobedo-Monge, M.F.; Barrado, E.; Parodi-Román, J.; Escobedo-Monge, M.A.; Torres-Hinojal, M.C.; Marugán-Miguelsanz, J.M. Magnesium Status and Ca/Mg Ratios in a Series of Children and Adolescents with Chronic Diseases. Nutrients 2022, 14, 2941. [Google Scholar] [CrossRef]
  8. Al-Subiai, S.N.; Jang, I.K.; Bae, S.-H.; Yoon, H.; Hussain, S.; AlNuaimi, S.; Al-Foudari, M.; Al-Hasan, E. Enhancing the Performance of Litopenaeus Vannamei Nursery and Grow-out by Modifying Mg/Ca Ratios in Biofloc Systems Using Low-Salinity Groundwater of Kuwait Desert. Aquaculture 2025, 594, 741405. [Google Scholar] [CrossRef]
  9. Van Dam, R.A.; Hogan, A.C.; McCullough, C.D.; Houston, M.A.; Humphrey, C.L.; Harford, A.J. Aquatic Toxicity of Magnesium Sulfate, and the Influence of Calcium, in Very Low Ionic Concentration Water. Environ. Toxicol. Chem. 2010, 29, 410–421. [Google Scholar] [CrossRef]
  10. Langenfeld, N.J.; Pinto, D.F.; Faust, J.E.; Heins, R.; Bugbee, B. Principles of Nutrient and Water Management for Indoor Agriculture. Sustainability 2022, 14, 10204. [Google Scholar] [CrossRef]
  11. Jaworek, K.; Czaplicka, M. Organoarsenic Compounds in Water Samples—The Problem of Hydride Generation Atomic Absorption Spectroscopic Method. Desalination Water Treat. 2022, 261, 141–150. [Google Scholar] [CrossRef]
  12. Huang, Y.-H.; Hirose, D.; Minami, J.; Wang, M.-J.; Takamura, Y. Fabrication and Characterizations of Axial View Liquid Electrode Plasma Atomic Emission Spectrometry for the Sensitive Determination of Trace Zinc, Cadmium, and Lead. Anal. Chem. 2022, 94, 8209–8216. [Google Scholar] [CrossRef] [PubMed]
  13. Chen, J.H.; Luo, Y.T.; Su, Y.A.; Ke, Y.R.; Deng, M.-J.; Chen, W.Y.; Wang, C.Y.; Tsai, J.L.; Lin, C.H.; Shih, T.T. Fabrication of a Microfluidic-Based Device Coated with Polyelectrolyte-Capped Titanium Dioxide to Couple High-Performance Liquid Chromatography with Inductively Coupled Plasma Mass Spectrometry for Mercury Speciation. Polymers 2024, 16, 2366. [Google Scholar] [CrossRef] [PubMed]
  14. Hart, E.J.A.; Siebecker, M.G. Portable X-ray Fluorescence Spectrometry Accurately Measures Metal Concentrations in Aqueous Mehlich III Soil Extraction Solutions. Soil Sci. Soc. Am. 2024, 88, 2336–2342. [Google Scholar] [CrossRef]
  15. Kanoun, O.; Lazarević-Pašti, T.; Pašti, I.; Nasraoui, S.; Talbi, M.; Brahem, A.; Adiraju, A.; Sheremet, E.; Rodriguez, R.D.; Ali, M.B.; et al. A Review of Nanocomposite-Modified Electrochemical Sensors for Water Quality Monitoring. Sensors 2021, 21, 4131. [Google Scholar] [CrossRef]
  16. Herrera-Domínguez, M.; Morales-Luna, G.; Mahlknecht, J.; Cheng, Q.; Aguilar-Hernández, I.; Ornelas-Soto, N. Optical Biosensors and Their Applications for the Detection of Water Pollutants. Biosensors 2023, 13, 370. [Google Scholar] [CrossRef]
  17. Liu, L.; Lai, Y.; Cao, J.; Peng, Y.; Tian, T.; Fu, W. Exploring the Antibacterial and Biosensing Applications of Peroxidase-Mimetic Ni0.1Cu0.9S Nanoflower. Biosensors 2022, 12, 874. [Google Scholar] [CrossRef]
  18. Radziemski, L.; Cremers, D.A. Brief History of Laser-Induced Breakdown Spectroscopy: From the Concept of Atoms to LIBS 2012. Spectrochim. Acta Part B-At. Spectrosc. 2013, 87, 3–10. [Google Scholar] [CrossRef]
  19. Evans, E.H.; Pisonero, J.; Smith, C.M.M.; Taylor, R.N. Atomic Spectrometry Update: Review of Advances in Atomic Spectrometry and Related Techniques. J. Anal. At. Spectrom. 2022, 37, 942–965. [Google Scholar] [CrossRef]
  20. Guo, Y.M.; Guo, L.B.; Li, J.M.; Liu, H.D.; Zhu, Z.H.; Li, X.Y.; Lu, Y.F.; Zeng, X.Y. Research Progress in Asia on Methods of Processing Laser-Induced Breakdown Spectroscopy Data. Front. Phys. 2016, 11, 114212. [Google Scholar] [CrossRef]
  21. Kim, D.; Yang, J.H.; Choi, S.; Yoh, J.J. Analytical Methods to Distinguish the Positive and Negative Spectra of Mineral and Environmental Elements Using Deep Ablation Laser-Induced Breakdown Spectroscopy (LIBS). Appl. Spectrosc. 2018, 72, 896–907. [Google Scholar] [CrossRef] [PubMed]
  22. Harmon, R.S. Laser-Induced Breakdown Spectroscopy in Mineral Exploration and Ore Processing. Minerals 2024, 14, 731. [Google Scholar] [CrossRef]
  23. Zeng, Q.D.; Chen, G.G.; Li, W.X.; Li, Z.T.; Tong, J.H.; Yuan, M.T.; Wang, B.Y.; Ma, H.H.; Liu, Y.; Guo, L.B.; et al. Classification of Steel Based on Laser-Induced Breakdown Spectroscopy Combined with Restricted Boltzmann Machine and Support Vector Machine. Plasma Sci. Technol. 2022, 24, 084009. [Google Scholar] [CrossRef]
  24. Stefas, D.; Gyftokostas, N.; Nanou, E.; Kourelias, P.; Couris, S. Laser-Induced Breakdown Spectroscopy: An Efficient Tool for Food Science and Technology (from the Analysis of Martian Rocks to the Analysis of Olive Oil, Honey, Milk, and Other Natural Earth Products). Molecules 2021, 26, 4981. [Google Scholar] [CrossRef]
  25. Yang, G.; Chen, G.Y.; Cai, Z.X.; Quan, X.Q.; Zhu, Y. Laser-Induced Breakdown Spectroscopy Instrument and Spectral Analysis for Deep-Ocean Fe-Mn Crusts. Front. Mar. Sci. 2023, 10, 1135058. [Google Scholar] [CrossRef]
  26. Khan, M.N.; Wang, Q.Q.; Idrees, B.S.; Teng, G.; Xiangli, W.; Cui, X.T.; Wei, K. Evaluation of Human Melanoma and Normal Formalin Paraffin-Fixed Samples Using Raman and LIBS Fused Data. Lasers Med. Sci. 2022, 37, 2489–2499. [Google Scholar] [CrossRef]
  27. Bukhari, M.; Awan, M.A.; Qazi, I.A.; Baig, M.A. Development of a Method for the Determination of Chromium and Cadmium in Tannery Wastewater Using Laser-Induced Breakdown Spectroscopy. J. Anal. Methods Chem. 2012, 2012, 823016. [Google Scholar] [CrossRef]
  28. Ewusi-Annan, E.; Surmick, D.M.; Melikechi, N.; Wiens, R.C. Simulated Laser-Induced Breakdown Spectra of Graphite and Synthetic Shergottite Glass under Martian Conditions. Spectrochim. Acta Part B At. Spectrosc. 2018, 148, 31–43. [Google Scholar] [CrossRef]
  29. Chen, S.H.; Li, Y.X.; Li, P.H.; Xiao, X.Y.; Jiang, M.; Li, S.S.; Zhou, W.Y.; Yang, M.; Huang, X.J.; Liu, W.-Q. Electrochemical Spectral Methods for Trace Detection of Heavy Metals: A Review. TrAC Trends Anal. Chem. 2018, 106, 139–150. [Google Scholar] [CrossRef]
  30. Zhu, Y.J.; Ma, S.X.; Yang, G.Y.; Tian, H.W.; Dong, D.M. Rapid Automatic Detection of Water Ca, Mg Elements Using Laser-Induced Breakdown Spectroscopy. Front. Phys. 2023, 11, 1179574. [Google Scholar] [CrossRef]
  31. Wang, J.M.; Li, G.; Zheng, P.C.; Shata, S.; Qazi, H.I.A.; Lu, J.S.; Liu, S.J.; Tian, H.W.; Dong, D.M. Highly Sensitive Detection of Heavy Metal Elements Using Laser-Induced Breakdown Spectroscopy Coupled with Chelating Resin Enrichment. Chemosensors 2023, 11, 228. [Google Scholar] [CrossRef]
  32. Ma, S.X.; Cao, F.J.; Wen, X.L.; Xu, F.H.; Tian, H.W.; Fu, X.L.; Dong, D.M. Detection of Heavy Metal Ions Using Laser-Induced Breakdown Spectroscopy Combined with Filter Paper Modified with PtAg Bimetallic Nanoparticles. J. Hazard. Mater. 2023, 443, 130188. [Google Scholar] [CrossRef] [PubMed]
  33. Papai, R.; Mariano, C.d.S.; Pereira, C.V.; Ferreira da Costa, P.V.; Leme, F.d.O.; Nomura, C.S.; Gaubeur, I. Matte Photographic Paper as a Low-Cost Material for Metal Ion Retention and Elemental Measurements with Laser-Induced Breakdown Spectroscopy. Talanta 2019, 205, 120167. [Google Scholar] [CrossRef] [PubMed]
  34. Yueh, F.-Y.; Sharma, R.C.; Singh, J.P.; Zhang, H.; Spencer, W.A. Evaluation of the Potential of Laser-Induced Breakdown Spectroscopy for Detection of Trace Element in Liquid. J. Air Waste Manag. Assoc. 2002, 52, 1307–1315. [Google Scholar] [CrossRef]
  35. Bhatt, C.R.; Hartzler, D.; Jain, J.; McIntyre, D.L. Determination of As, Hg, S, and Se in Liquid Jets by Laser-Based Optical Diagnostic Technique. Appl. Phys. B-Laser Opt. 2021, 127, 8. [Google Scholar] [CrossRef]
  36. GB/T 601-2016; Chemical Reagent Preparations of Reference Titration Solutions. National Standard of the People’s Republic of China: Beijing, China, 2016.
  37. Zhang, D.C.; Hu, Z.Q.; Su, Y.B.; Hai, B.; Zhu, X.L.; Zhu, J.F.; Ma, X. Simple Method for Liquid Analysis by Laser-Induced Breakdown Spectroscopy (LIBS). Opt. Express 2018, 26, 18794. [Google Scholar] [CrossRef]
  38. Zheng, Y.; Ban, D.; Li, N.; Song, J.; Zhang, J.; Luo, Y.; Guan, J.; Zhang, C.; Xue, C. Performance Improvement of Underwater LIBS Qualitative and Quantitative Analysis by Irradiating with Long Nanosecond Pulses. Analyst 2024, 149, 768–777. [Google Scholar] [CrossRef]
Figure 1. The overall schematic diagram of the experimental setup is shown on the left. And the main components: a spectrometer (17.2 × 12.7 × 4.5 cm3), an Nd:YAG laser (16.2 × 6.0 × 6.6 cm3), a laser controller (15.2 × 5.6 × 5.6 cm3), a control board (11.4 × 6.6 × 2.9 cm3), a peristaltic pump (5 × 2.9 × 3.6 cm3), and a power supply (16 × 8.2 × 4.7 cm3) are shown on the right.
Figure 1. The overall schematic diagram of the experimental setup is shown on the left. And the main components: a spectrometer (17.2 × 12.7 × 4.5 cm3), an Nd:YAG laser (16.2 × 6.0 × 6.6 cm3), a laser controller (15.2 × 5.6 × 5.6 cm3), a control board (11.4 × 6.6 × 2.9 cm3), a peristaltic pump (5 × 2.9 × 3.6 cm3), and a power supply (16 × 8.2 × 4.7 cm3) are shown on the right.
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Figure 2. Typical LIBS emission spectra.
Figure 2. Typical LIBS emission spectra.
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Figure 3. The optimization of laser ablation conditions involves the examination of two factors (the concentration of the solution is 1000 mg/L): (a) the effect of column diameter on peak value; (b) the effect of liquid column diameter on signal excitation; (c) the effect of laser ablation position (distance from jet nozzle) on peak intensity; (d) the effect of laser ablation position on RSD.
Figure 3. The optimization of laser ablation conditions involves the examination of two factors (the concentration of the solution is 1000 mg/L): (a) the effect of column diameter on peak value; (b) the effect of liquid column diameter on signal excitation; (c) the effect of laser ablation position (distance from jet nozzle) on peak intensity; (d) the effect of laser ablation position on RSD.
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Figure 4. Calibration curve. (a) Bulk liquid mode (natural water whose surface is at rest) of Ca; (b) liquid jet mode of Ca; (c) bulk liquid mode of Mg; (d) liquid jet mode of Mg.
Figure 4. Calibration curve. (a) Bulk liquid mode (natural water whose surface is at rest) of Ca; (b) liquid jet mode of Ca; (c) bulk liquid mode of Mg; (d) liquid jet mode of Mg.
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Figure 5. The RSD of the peak intensities of Ca (393.36 nm) and Mg (279.55 nm) were correlated with the cumulative spectra on average.
Figure 5. The RSD of the peak intensities of Ca (393.36 nm) and Mg (279.55 nm) were correlated with the cumulative spectra on average.
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Figure 6. Quantitative ability of Ca and Mg detection (a). And (b) averaged LIBS spectra for different concentration of Ca and Mg (20–1000 ppm); calibration curve of (c) Ca and (d) Mg by liquid jet mode.
Figure 6. Quantitative ability of Ca and Mg detection (a). And (b) averaged LIBS spectra for different concentration of Ca and Mg (20–1000 ppm); calibration curve of (c) Ca and (d) Mg by liquid jet mode.
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Table 1. Elemental concentrations of prepared CaCl2 and MgCl2.
Table 1. Elemental concentrations of prepared CaCl2 and MgCl2.
Sample NumberCa (mg/L)Mg (mg/L)Sample NumberCa (mg/L)Mg (mg/L)
No. 110001000No. 7100100
No. 2750750No. 88080
No. 3500500No. 96060
No. 4300300No. 104040
No. 5200200No. 112020
No. 6150150
Table 2. Analysis of Ca and Mg contents in real water samples.
Table 2. Analysis of Ca and Mg contents in real water samples.
TypeSample
No.
Element
(ICP-MS)
Add
(mg/L)
Predict
(mg/L)
Recovery Rate
Pond1Mg (16.814 mg/L)017.13101.87%
22035.8895.33%
34058.62104.52%
46076.6999.79%
58098.57102.20%
6Ca (14.097 mg/L)013.9598.95%
74053.5798.68%
88091.6196.89%
9120136.18101.74%
10160173.6099.69%
River11Mg (8.293 mg/L)08.56103.21%
122030.04108.74%
134048.85101.39%
146067.3898.47%
158083.0493.43%
16Ca (27.537 mg/L)026.8997.65%
174063.8790.83%
1880108.71101.47%
19120149.32101.49%
20160187.4799.96%
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Wan, Y.; Ma, S.; Zheng, P.; Zhao, X.; Xing, Z.; Jiao, L.; Tian, H.; Dong, D. On-Site Detection of Ca and Mg in Surface Water Using Portable Laser-Induced Breakdown Spectroscopy. Chemosensors 2025, 13, 16. https://doi.org/10.3390/chemosensors13010016

AMA Style

Wan Y, Ma S, Zheng P, Zhao X, Xing Z, Jiao L, Tian H, Dong D. On-Site Detection of Ca and Mg in Surface Water Using Portable Laser-Induced Breakdown Spectroscopy. Chemosensors. 2025; 13(1):16. https://doi.org/10.3390/chemosensors13010016

Chicago/Turabian Style

Wan, Yuanxin, Shixiang Ma, Peichao Zheng, Xiande Zhao, Zhen Xing, Leizi Jiao, Hongwu Tian, and Daming Dong. 2025. "On-Site Detection of Ca and Mg in Surface Water Using Portable Laser-Induced Breakdown Spectroscopy" Chemosensors 13, no. 1: 16. https://doi.org/10.3390/chemosensors13010016

APA Style

Wan, Y., Ma, S., Zheng, P., Zhao, X., Xing, Z., Jiao, L., Tian, H., & Dong, D. (2025). On-Site Detection of Ca and Mg in Surface Water Using Portable Laser-Induced Breakdown Spectroscopy. Chemosensors, 13(1), 16. https://doi.org/10.3390/chemosensors13010016

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