TY - JOUR
T1 - Volatile organic compounds (VOCs) in wastewater
T2 - Recent advances in detection and quantification
AU - Lim, Yun Mun
AU - Swamy, Varghese
AU - Ramakrishnan, Narayanan
AU - Chan, Eng Seng
AU - Kesuma, Howgen Pratama
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023/12
Y1 - 2023/12
N2 - Purpose: 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. Approach: 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. Findings: 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. Value: 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.
AB - Purpose: 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. Approach: 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. Findings: 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. Value: 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.
KW - Artifical intelligence
KW - E-nose
KW - Gas chromatography
KW - Methodologies
KW - Monitoring
KW - Volatile organic compounds
KW - Wastewater
UR - http://www.scopus.com/inward/record.url?scp=85174735993&partnerID=8YFLogxK
U2 - 10.1016/j.microc.2023.109537
DO - 10.1016/j.microc.2023.109537
M3 - Review Article
AN - SCOPUS:85174735993
SN - 0026-265X
VL - 195
JO - Microchemical Journal
JF - Microchemical Journal
M1 - 109537
ER -