Ana Gebejes
Ana Gebejes has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Arto Koistinen
Department of Technical Physics, University of Eastern Finland, PO Box 1627, Kuopio FI-70211, Finland
4 shared publications - Benjamin Osae Asamoah
University of Eastern Finland
3 shared publications - Blaž Hrovat
Department of Technical Physics, University of Eastern Finland, 70210 Kuopio, Finland
3 shared publications Kai-Erik Peiponen
3 shared publications- Antti Haapala
Department of Chemistry and Sustainable Technology, University of Eastern Finland, Joensuu, Finland
2 shared publications - Nikolaos Papamatthaiakis2 shared publications
Latest Publications
- Open Access
- 13 November 2026
- Published by Elsevier in Journal of Hazardous Materials: Plastics
Effects of thermal, chemical, mechanical, and UV aging on microplastics with environmentally relevant morphologies: A laboratory study
- 13 November 2026
- Published by Elsevier in Journal of Hazardous Materials: Plastics
Open AccessEffects of thermal, chemical, mechanical, and UV aging on microplastics with environmentally relevant morphologies: A laboratory study
- Open Access
- 30 October 2026
- Published by Elsevier in Total Environment Engineering
- Vol. 9
Ultra-high-definition imaging-based texture, morphology and motion parameters of transparent-translucent microplastics in flowing water: A feasibility study
- 30 October 2026
- Published by Elsevier in Total Environment Engineering
- Vol. 9
Open AccessUltra-high-definition imaging-based texture, morphology and motion parameters of transparent-translucent microplastics in flowing water: A feasibility study
- Open Access
- 20 February 2026
- Published by Elsevier in SSRN Electronic Journal
Morphology and motion parameters for detection and identification of microplastics in flowing water
Microplastics morphology, namely size, shape, and texture, play an important role in adhesion of different types of contaminants over a microplastic. In flowing water, this leads to formation of complex contaminant systems which are transported and become a potential hazard for virtually all Earth’s environmental compartments. Here, we provide methods to study morphology and motion of microplastics, and we derive parameters to aid in their early detection and identification in flowing water. On UPVC microplastic we demonstrate ultra-high-definition imaging paired with statistical parameters for light intensity distribution in analogy to surface roughness parameters and perceptual texture parameters derived from a Gray Level Co-occurrence matrix. Further, from LDPE and PS microplastics videos we derived distinct flow behavior parameters of each microplastic type. Finally, we analyse images of a complex water sample, a cellulose-rich influent of a paper mill wastewater treatment plant. The presented findings open a path towards new sensing solutions to detect and identify the type of MP contaminant, predict their location and fate during and after wastewater flow monitoring.
- 20 February 2026
- Published by Elsevier in SSRN Electronic Journal
Open AccessMorphology and motion parameters for detection and identification of microplastics in flowing water
Microplastics morphology, namely size, shape, and texture, play an important role in adhesion of different types of contaminants over a microplastic. In flowing water, this leads to formation of complex contaminant systems which are transported and become a potential hazard for virtually all Earth’s environmental compartments. Here, we provide methods to study morphology and motion of microplastics, and we derive parameters to aid in their early detection and identification in flowing water. On UPVC microplastic we demonstrate ultra-high-definition imaging paired with statistical parameters for light intensity distribution in analogy to surface roughness parameters and perceptual texture parameters derived from a Gray Level Co-occurrence matrix. Further, from LDPE and PS microplastics videos we derived distinct flow behavior parameters of each microplastic type. Finally, we analyse images of a complex water sample, a cellulose-rich influent of a paper mill wastewater treatment plant. The presented findings open a path towards new sensing solutions to detect and identify the type of MP contaminant, predict their location and fate during and after wastewater flow monitoring.
- Open Access
- 20 February 2026
- Published by Elsevier in SSRN Electronic Journal
Morphology and motion parameters for detection and identification of microplastics in flowing water
Microplastics morphology, namely size, shape, and texture, play an important role in adhesion of different types of contaminants over a microplastic. In flowing water, this leads to formation of complex contaminant systems which are transported and become a potential hazard for virtually all Earth’s environmental compartments. Here, we provide methods to study morphology and motion of microplastics, and we derive parameters to aid in their early detection and identification in flowing water. On UPVC microplastic we demonstrate ultra-high-definition imaging paired with statistical parameters for light intensity distribution in analogy to surface roughness parameters and perceptual texture parameters derived from a Gray Level Co-occurrence matrix. Further, from LDPE and PS microplastics videos we derived distinct flow behavior parameters of each microplastic type. Finally, we analyse images of a complex water sample, a cellulose-rich influent of a paper mill wastewater treatment plant. The presented findings open a path towards new sensing solutions to detect and identify the type of MP contaminant, predict their location and fate during and after wastewater flow monitoring.
- 20 February 2026
- Published by Elsevier in SSRN Electronic Journal
Open AccessMorphology and motion parameters for detection and identification of microplastics in flowing water
Microplastics morphology, namely size, shape, and texture, play an important role in adhesion of different types of contaminants over a microplastic. In flowing water, this leads to formation of complex contaminant systems which are transported and become a potential hazard for virtually all Earth’s environmental compartments. Here, we provide methods to study morphology and motion of microplastics, and we derive parameters to aid in their early detection and identification in flowing water. On UPVC microplastic we demonstrate ultra-high-definition imaging paired with statistical parameters for light intensity distribution in analogy to surface roughness parameters and perceptual texture parameters derived from a Gray Level Co-occurrence matrix. Further, from LDPE and PS microplastics videos we derived distinct flow behavior parameters of each microplastic type. Finally, we analyse images of a complex water sample, a cellulose-rich influent of a paper mill wastewater treatment plant. The presented findings open a path towards new sensing solutions to detect and identify the type of MP contaminant, predict their location and fate during and after wastewater flow monitoring.