Conference proceedings

Displaying 1 - 4 of 4 in soil (remove filter), remediation (remove filter)

CEST Proceedings are published under the ISSN 2944-9820.

Per-and polyfluoroalkyl substances (PFAS): an emerging contaminant

(Corresponding) Toskos T., Panagiotakis I., Dermatas D.
Topic: 
Soil and groundwater contamination and remediation
PFAS compounds are ubiquitous in the environment and in consumer products. Unlike other emergent contaminants this is a family of compounds with, literally, thousands of compounds. Our knowledge of toxicological and environmental fate and transport properties is an evolving field. On the other hand...Read more
Keywords: 
PFAS, soil, groundwater, contamination, remediation
Conference: 
CEST2019
Paper ID: 
cest2019_00463

IN-SITU REMOVAL OF ANTIBIOTICS IN SOIL BY COLD PLASMA

(Corresponding) Aggelopoulos C., Hatzisymeon M., Tataraki D., Rassias G.
Topic: 
Soil and groundwater contamination and remediation
Antibiotics are extensively used in clinical settings to treat or prevent human diseases, in veterinary science for farm and domestic animal health and in agriculture for crop protection. Due to their incomplete biological degradation, human and animal antibiotics are released through discharges...Read more
Keywords: 
in-situ soil remediation, antibiotics, cold plasma, degradation pathway, advanced oxidation
Conference: 
CEST2019
Paper ID: 
cest2019_00603

Trifluralin-polluted soil treatment using nanosecond pulsed DBD plasma

Hatzisymeon M., Tataraki D., Rassias G., (Corresponding) Aggelopoulos C.
Topic: 
Soil and groundwater contamination and remediation
Cold atmospheric plasma (CAP) was examined as an advanced oxidation process (AOP) for the remediation of trifluralin in soil. Trifluralin is a commonly used herbicide, which is toxic and persistent in soil. CAP experiments were conducted using a cylinder-to-cylindrical-grid reactor layout, driven...Read more
Keywords: 
Soil remediation, DBD plasma, Trifluralin, Herbicides
Conference: 
CEST2021
Paper ID: 
cest2021_00047

A Deep Learning Model, interpreted with an XAI technique, to simulate and optimize the remediation of oil-drilling cuttings in bubble flow reactors

Kalari K., Christodoulis K., Bali N., Theodoropoulou M., (Corresponding) Tsakiroglou C.
Topic: 
Environmental data analysis and modelling
A multitask deep neural network (DNN) is developed to simulate the ozonation of oil-drilling cuttings (ODC) and is interpreted through a technique of explainable artificial intelligence (XAI) to provide knowledge about the experimental conditions that will maximize the decontamination of ODC. On a...Read more
Keywords: 
Ozonation, Soil Remediation, Bubble Column Reactor, Deep Neural Networks, Multitask Learning, Explainable Artificial Intelligence.
Conference: 
CEST2023
Paper ID: 
cest2023_00166