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On-line Analysis of Nitrogen Containing Compounds in Complex Hydrocarbon Matrixes
Published on: August 5, 2016
Development of continuous on-line purge and trap analysis
Chutarat Saridara1, Roman Brukh, Somenath Mitra
1International Postgraduate Programs in Environmental Management, Chulalongkorn University, Bangkok, Thailand.
Journal of Separation Science
|March 21, 2006
Summary
This study introduces an automated system for continuous monitoring of Volatile Organic Compounds (VOCs) in water. The novel on-line purge and trap method offers high sensitivity and precision for environmental analysis.
Area of Science:
- Environmental Chemistry
- Analytical Chemistry
- Instrumental Analysis
Background:
- Continuous monitoring of Volatile Organic Compounds (VOCs) is crucial for environmental and industrial applications.
- Traditional methods often involve time-consuming sample preparation and analysis.
- There is a need for automated, high-frequency analytical systems for real-time VOC detection.
Purpose of the Study:
- To develop and present an on-line purge and trap system for the continuous monitoring of VOCs in water.
- To evaluate the system's performance in terms of sensitivity, precision, and stability.
- To investigate factors influencing system performance and develop a predictive model.
Main Methods:
- Design of a continuous extraction purge chamber using nitrogen.
- Preconcentration of analytes on a microtrap.
- Analysis using Gas Chromatography (GC) with Flame Ionization Detection (FID).
- Implementation of fixed-interval injections for high-frequency analysis.
Main Results:
- The system demonstrated high sensitivity and precision for VOC detection.
- Achieved detection limits at the parts per billion (ppb) level.
- Exhibited stable performance over extended periods of continuous operation.
- Identified key factors affecting system performance.
Conclusions:
- The developed on-line purge and trap system is effective for continuous VOC monitoring.
- The system offers a sensitive, precise, and stable solution for real-time water quality analysis.
- A predictive model based on gas-liquid partitioning aids in understanding and optimizing system performance.
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