Aims: Computational modelling may help us to detect the more important factors governing
this process in order to optimize it.
Background: The generation of hazardous organic waste in teaching and research laboratories poses a
big problem that universities have to manage.
Methods: In this work, we report on the experimental measurement of waste generation on the chemical
education laboratories within our department. We measured the waste generated in the teaching laboratories
of the Organic Chemistry Department II (UPV/EHU), in the second semester of the 2017/2018
academic year. Likewise, to know the anthropogenic and social factors related to the generation of
waste, a questionnaire has been utilized. We focused on all students of Experimentation in Organic
Chemistry (EOC) and Organic Chemistry II (OC2) subjects. It helped us to know their prior knowledge
about waste, awareness of the problem of separate organic waste and the correct use of the containers.
These results, together with the volumetric data, have been analyzed with statistical analysis software.
We obtained two Perturbation-Theory Machine Learning (PTML) models including chemical, operational,
and academic factors. The dataset analyzed included 6050 cases of laboratory practices vs. practices
Results: These models predict the values of acetone waste with R2 = 0.88 and non-halogenated waste
with R2 = 0.91.
Conclusion: This work opens a new gate to the implementation of more sustainable techniques and a
circular economy with the aim of improving the quality of university education processes.