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Volatile organic compounds (VOCs) in wastewater: Recent advances in detection and quantification

环境科学 废水 离子迁移光谱法 BTEX公司 室内空气质量 工艺工程 环境化学 化学 质谱法 环境工程 工程类 二甲苯 有机化学 色谱法
作者
Yun Mun Lim,Varghese Swamy,N. Ramakrishnan,Eng Seng Chan,Howgen Pratama Kesuma
出处
期刊:Microchemical Journal [Elsevier]
卷期号:195: 109537-109537 被引量:1
标识
DOI:10.1016/j.microc.2023.109537
摘要

Volatile organic compounds (VOCs) are a major source of air pollution, significantly affecting both human health and the environment. These VOCs from wastewater can enter the atmosphere through air–water exchange and pose a great threat to human health, as the quality of our environment has consequences for agriculture, drinking water, pollution, greenhouse effect, and so on. Gas chromatography (GC) is one of many techniques for detecting VOCs. Recent research has explored the integration of various detectors with GC, such as mass spectrometers, flame ionization detectors, ion mobility spectrometers, and thermal conductivity detectors. While GC remains a cornerstone in VOC detection, other techniques are also gaining significant attention. Notably, emerging technologies such as different types of E-nose and acoustic wave sensing devices offer promising results for VOC detection. Additionally, the evolution of data processing for VOCs through statistical and numerical methods, as well as the incorporation of artificial intelligence methodologies with smart sensing devices, further broadens the horizon of VOC detection and quantification. Apart from the well-established GC suite of experimental VOC detection and measurement tools, much progress has recently been made in the development of relatively inexpensive and portable semiconductor metal oxides-, conducting polymers-, and carbon nanomaterials-based E-nose and surface acoustic wave sensing devices for VOC sensing and quantification. Another significant development in wastewater VOC detection and characterization is the adoption of artificial intelligence tools such as machine learning and deep learning that have shown great promise towards automation and ability to deal with large and complex VOC analysis. This article provides valuable insights into the development of methodologies for monitoring VOCs in wastewater. The review outlines the advantages and limitations of different VOCs detection techniques as well as the challenges associated with VOCs monitoring in wastewater. Our aim is to provide guidance from a methodology perspective for researchers and practitioners working in the field of wastewater management and environmental monitoring, highlighting areas for future research and development. The insights presented will aid in the development of more accurate and efficient VOC monitoring methods for wastewater, thereby helping to protect human health and the environment.
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