Microplastic removal in coagulation-flocculation: Optimization through chemometric and morphological insights
1
Issued Date
2026-02-01
Resource Type
eISSN
22998993
Scopus ID
2-s2.0-105028977051
Journal Title
Journal of Ecological Engineering
Volume
27
Issue
2
Start Page
277
End Page
292
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Ecological Engineering Vol.27 No.2 (2026) , 277-292
Suggested Citation
Yimrattanabovorn J., Kanjanapruthipong K., Wonglertarak W., Wichitsathian B., Khowattana M., Nawong S. Microplastic removal in coagulation-flocculation: Optimization through chemometric and morphological insights. Journal of Ecological Engineering Vol.27 No.2 (2026) , 277-292. 292. doi:10.12911/22998993/211594 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114826
Title
Microplastic removal in coagulation-flocculation: Optimization through chemometric and morphological insights
Corresponding Author(s)
Other Contributor(s)
Abstract
Microplastics in freshwater threaten human health, making their removal in water treatment processes essential. Conventional coagulation methods, however, often show limited and inconsistent efficiency due to the diverse sizes, shapes, and surface properties of microplastics, underscoring the need for improved approaches. This study examined the removal performance, surface morphology, and chemical characteristics of polypropylene (MP-PP), polyethylene (MP-PE), and polystyrene (MP-PS) using poly-aluminum chloride (PAC) and anionic polyacrylamide (PAM) in a coagulation-flocculation process, with a focus on identifying optimal operating conditions. Among the tested microplastics, MP-PS exhibited the highest removal efficiency, followed by MP-PE and MP-PP, while larger particle size and mass were found to further enhance removal performance. Differences in removal efficiency were consistent with zeta potential values and supported by morphological evidence from scanning electron microscopy (SEM). Fourier transform infrared (FTIR) spectra, combined with Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), further highlighted the influence of surface properties and aggregation behaviors on removal outcomes. Overall, the results demonstrate that optimizing parameters such as pH, coagulant dosage, polymer concentration, and consideration of microplastic characteristics can significantly enhance removal efficiency, providing practical guidance for advancing sustainable water treatment.