About this Research Topic

Background

Intensive technological development has led to tremendous pressure on the quality of the environment, which is reflected in its pollution by toxic trace pollutants. Heavy metal(loid)s, polycyclic hydrocarbons (PAH), ambient air particulate matter (PM), ground-level ozone (O3), volatile organic compounds (VOC), polychlorinated biphenyls (PCB), dioxins (TCDD), pesticides, pharmaceuticals, viruses, bacteria, and radionuclides are pollutants that cause the most concern. A modern approach to study risks coming from these pollutants inevitably includes the use of chemometrics. Principal component analysis (PCA), hierarchical cluster analysis (HCA), positive matrix factorization (PMF), PARAFAC, geostatistical analysis (GIS), Monte Carlo simulation, factorial design (DOE), machine learning prediction, and artificial intelligence modeling are frequently used chemometric methods. It is common to use several methods together in a particular study. Among the above methods, there is great competitivity or complementarity. Therefore, a comprehensive approach is needed in this area where different research can be incorporated, covering a range of chemometric methods and their combinations, for various pollutants in the environment.

Nowadays, the dramatic increase in the amount of data generated by modern analytical instruments in studies on trace pollutants present in the environment requires chemometricians to extract meaningful information from these data. It is a quite complex task that requires an integration of analytical chemistry, environmental science, mathematics, statistics, and toxicology. This Research Topic is aimed to address recent advances in the development and application of chemometrics in studies on the occurrence, distribution, and fate of trace pollutants in different media (soil, air, water, plants, and food). It will focus not only on pattern recognition, classification, and pollution source identification but also on ecological and health risk assessment using deterministic and probabilistic approaches. A part of this Research Topic will cover chemometric optimization of methods for analysis or removal of trace pollutants. Besides the above-mentioned pollutants, other emerging pollutants can be considered.

This Research Topic will cover the following areas:

• Implementation of chemometric methods in case studies of the occurrence and fate of environmental trace pollutants from specific regions
• Addressing environmental pollution using different chemometric tools
• Chemometric analysis of trace pollutants in different media (soil, air, water, plants, and food) and estimating the associated environmental risks
• Integration of geostatistics, multivariate analysis, and risk assessment of trace pollutants
• New developments in chemometrics of trace pollutants
• Chemometric optimization of analytical methods for, and methods for removal of trace pollutants

We are primarily interested in collecting high-quality original research articles. We highly welcome review papers from distinguished researchers. A full list of available article types is available via the specialty section homepages.

Suggested Editors based on chemometric applications for different environmental compartments:

Associate Professor Antonije Onjia – food, plant, soil, air, and water pollution fields
Associate Professor Xin Huang – air pollution field
Dr Juan Manuel Trujillo-Gonzalez – soil and sediment pollution field
Dr Johnbosco Egbueri – water pollution field

Keywords: chemometrics, source apportionment, soil, air, water, plants, food, pollution, quality index, multivariate assessment, geostatistics, neural network, positive matrix factorization, Monte Carlo simulation, heavy metals, metalloids, polycyclic hydrocarbons, volatile organics, viruses, bacteria, radionuclides

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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