Estimation of short-lived climate forced sulfur dioxide in Tehran, Iran, using machine learning analysis.
ARIMA forecasting
Air pollution
Machine learning
Meteorological parameters
Short-lived climate pollutants
Sulfur dioxide
Journal
Stochastic environmental research and risk assessment : research journal
ISSN: 1436-3240
Titre abrégé: Stoch Environ Res Risk Assess
Pays: Germany
ID NLM: 101473235
Informations de publication
Date de publication:
2022
2022
Historique:
accepted:
24
12
2021
pubmed:
18
1
2022
medline:
18
1
2022
entrez:
17
1
2022
Statut:
ppublish
Résumé
This paper presents a time-series analysis of SO
Identifiants
pubmed: 35035281
doi: 10.1007/s00477-021-02167-x
pii: 2167
pmc: PMC8741550
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2847-2860Informations de copyright
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.
Déclaration de conflit d'intérêts
Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.