Quantifying and predicting ecological and human health risks for binary heavy metal pollution accidents at the watershed scale using Bayesian Networks.

Sakari Kuikka

Quantifying and predicting ecological and human health risks for binary heavy metal pollution accidents at the watershed scale using Bayesian Networks.

Forskningsoutput: Tidskriftsbidrag › Artikel › Vetenskaplig › Peer review

Originalspråk	finska
Tidskrift	Environmental Pollution
ISSN	0269-7491
Status	!!Accepted/In press - 2021
MoE-publikationstyp	A1 Tidskriftsartikel-refererad

Åtkomst av dokument

https://www.sciencedirect.com/science/article/pii/S0269749120368147?via%3Dihub

Citera det här

@article{9798b2662bb94cd38e87f740af2315a0,

title = "Quantifying and predicting ecological and human health risks for binary heavy metal pollution accidents at the watershed scale using Bayesian Networks.",

author = "Sakari Kuikka",

year = "2021",

language = "suomi",

journal = "Environmental Pollution",

issn = "0269-7491",

publisher = "ELSEVIER SCI IRELAND LTD",

}

TY - JOUR

T1 - Quantifying and predicting ecological and human health risks for binary heavy metal pollution accidents at the watershed scale using Bayesian Networks.

AU - Kuikka, Sakari

PY - 2021

Y1 - 2021

UR - https://www.sciencedirect.com/science/article/pii/S0269749120368147?via%3Dihub

M3 - Artikkeli

JO - Environmental Pollution

JF - Environmental Pollution

SN - 0269-7491

ER -