Nitrate Analysis of Water Using a Fiber Optics Dip Probe
Applications | 2021 | Agilent TechnologiesInstrumentation
Reliable and rapid determination of nitrate concentrations in water is essential for environmental monitoring, public health assessment, and regulatory compliance. Traditional cuvette-based UV-Vis methods can be time-consuming and limited to laboratory settings. The use of a fiber optics dip probe enables on-site and high-throughput analysis, improving operational efficiency and minimizing sample handling errors.
This application note evaluates the performance of a quartz fiber optics dip probe coupled to a Cary 50 UV-Vis spectrophotometer (and its successor, the Cary 60) for quantifying nitrate levels in aqueous samples. Key goals include establishing a calibration model, assessing reproducibility, and comparing analysis time against conventional cuvette methods.
The protocol follows Standard Methods for the Examination of Water and Wastewater and Agilent’s recommended procedure:
This study employed the following equipment and software:
A quadratic calibration curve (Abs = –0.00017·conc² + 0.23364·conc + 0.01705) achieved an R² of 0.99931 across six standards. Relative standard deviations for replicates were below 1.3%, indicating excellent precision. Two tap water samples yielded consistent nitrate values with RSDs below 2%. Total analysis time for six standards and two samples (each in triplicate) was approximately five minutes, including probe rinsing and drying—significantly faster than cuvette-based assays.
Key advantages of the fiber optics dip probe method include:
Emerging developments may further expand the utility of fiber optic probes in water analysis:
The quartz fiber optic dip probe combined with Cary UV-Vis instrumentation offers a precise, efficient, and versatile approach for nitrate analysis in water. Its speed and portability make it an attractive alternative to traditional cuvette methods, supporting both laboratory and field applications.
1. Eaton, D., Clesceri, L. S. & Greenberg, A. E. Standard Methods for the Examination of Water and Wastewater, 19th Edition, American Public Health Association, 1995, p. 4-85.
2. Liberatore, P. A. Automated Nitrate Analysis of Water, Agilent publication UV59.
UV–VIS spectrophotometry
IndustriesEnvironmental
ManufacturerAgilent Technologies
Summary
Significance of the Topic
Reliable and rapid determination of nitrate concentrations in water is essential for environmental monitoring, public health assessment, and regulatory compliance. Traditional cuvette-based UV-Vis methods can be time-consuming and limited to laboratory settings. The use of a fiber optics dip probe enables on-site and high-throughput analysis, improving operational efficiency and minimizing sample handling errors.
Objectives and Study Overview
This application note evaluates the performance of a quartz fiber optics dip probe coupled to a Cary 50 UV-Vis spectrophotometer (and its successor, the Cary 60) for quantifying nitrate levels in aqueous samples. Key goals include establishing a calibration model, assessing reproducibility, and comparing analysis time against conventional cuvette methods.
Methodology
The protocol follows Standard Methods for the Examination of Water and Wastewater and Agilent’s recommended procedure:
- Prepare nitrate standards in the range 0–7 mg NO3–N/L using potassium nitrate.
- Adjust sample pH with 37% hydrochloric acid and perform an optional chloroform extraction step to remove interferences.
- Measure absorbance at 220 nm and 275 nm; calculate corrected absorbance as Abs(220) – 2×Abs(275) to compensate for dissolved organic matter.
- Collect triplicate readings for each standard and sample, rinsing the probe with deionized water between measurements.
- Use Cary WinUV Concentration software to fit a quadratic regression and compute sample concentrations dynamically.
Instrumentation
This study employed the following equipment and software:
- Cary 50 UV-Vis spectrophotometer (superseded by Cary 60 UV-Vis).
- Dip probe fiber optics coupler and quartz fiber optic dip probe.
- Cary WinUV software with dynamic concentration evaluation.
Results and Discussion
A quadratic calibration curve (Abs = –0.00017·conc² + 0.23364·conc + 0.01705) achieved an R² of 0.99931 across six standards. Relative standard deviations for replicates were below 1.3%, indicating excellent precision. Two tap water samples yielded consistent nitrate values with RSDs below 2%. Total analysis time for six standards and two samples (each in triplicate) was approximately five minutes, including probe rinsing and drying—significantly faster than cuvette-based assays.
Benefits and Practical Applications
Key advantages of the fiber optics dip probe method include:
- High throughput and rapid analysis suitable for routine laboratory screening.
- Portability for field measurements without the need for cuvettes.
- Low sample carryover and minimal preparation time.
- Robust correction for organic interferences using dual-wavelength measurement.
Future Trends and Potential Applications
Emerging developments may further expand the utility of fiber optic probes in water analysis:
- Integration with handheld or online UV-Vis instruments for real-time monitoring.
- Advanced fiber coatings to resist fouling and broaden chemical compatibility.
- Multiplexed detection for simultaneous measurement of nitrates, phosphates, and other ions.
- Machine learning algorithms for automated baseline correction and concentration prediction.
Conclusion
The quartz fiber optic dip probe combined with Cary UV-Vis instrumentation offers a precise, efficient, and versatile approach for nitrate analysis in water. Its speed and portability make it an attractive alternative to traditional cuvette methods, supporting both laboratory and field applications.
Reference
1. Eaton, D., Clesceri, L. S. & Greenberg, A. E. Standard Methods for the Examination of Water and Wastewater, 19th Edition, American Public Health Association, 1995, p. 4-85.
2. Liberatore, P. A. Automated Nitrate Analysis of Water, Agilent publication UV59.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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