Drivers of global microplastic concentrations in rivers. A comparison of the multiple linear regression and random forest regression approach.
dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Vliet, Michelle van | |
dc.contributor.author | Smits, Simon | |
dc.date.accessioned | 2022-09-09T04:01:42Z | |
dc.date.available | 2022-09-09T04:01:42Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/42712 | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | Microplastic in rivers can have a negative effect on the overall water quality and a harming effect on biotic species living in aquatic ecosystems. The drivers of microplastic pollution are therefore important players in determining and counteracting microplastics concentrations in rivers. In this study, multiple linear regression and random forest regression is applied to analyse the influence of socio-economic-, hydrologic- and land use drivers on microplastic concentrations in rivers. | |
dc.title | Drivers of global microplastic concentrations in rivers. A comparison of the multiple linear regression and random forest regression approach. | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.courseuu | Earth Surface and Water | |
dc.thesis.id | 10398 |