A data-driven modeling approach for the sustainable remediation of persistent arsenic (As) groundwater contamination in a fractured rock aquifer through a groundwater recirculation well (IEG-GCW®).

Ciampi P, Esposito C, Bartsch E, Alesi EJ, Rehner G, Morettin P, Pellegrini M, Olivieri S, Ranaldo M, Liali G, Papini MP

Open source

DOI
10.1016/j.envres.2022.114827
Published
2023 Jan 15
Container
Environmental research
Publisher
Not recorded
Open access
unknown

Credibility signals

limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1016/j.envres.2022.114827,
  title = {A data-driven modeling approach for the sustainable remediation of persistent arsenic (As) groundwater contamination in a fractured rock aquifer through a groundwater recirculation well (IEG-GCW®).},
  author = {Ciampi P and Esposito C and Bartsch E and Alesi EJ and Rehner G and Morettin P and Pellegrini M and Olivieri S and Ranaldo M and Liali G and Papini MP},
  year = {2023},
  journal = {Environmental research},
  doi = {10.1016/j.envres.2022.114827},
  url = {https://doi.org/10.1016/j.envres.2022.114827}
}

RIS

TY  - JOUR
TI  - A data-driven modeling approach for the sustainable remediation of persistent arsenic (As) groundwater contamination in a fractured rock aquifer through a groundwater recirculation well (IEG-GCW®).
AU  - Ciampi P
AU  - Esposito C
AU  - Bartsch E
AU  - Alesi EJ
AU  - Rehner G
AU  - Morettin P
AU  - Pellegrini M
AU  - Olivieri S
AU  - Ranaldo M
AU  - Liali G
AU  - Papini MP
PY  - 2023
JO  - Environmental research
DO  - 10.1016/j.envres.2022.114827
UR  - https://doi.org/10.1016/j.envres.2022.114827
ER  - 

APA

P, C., C, E., E, B., EJ, A., G, R., P, M., M, P., S, O., M, R., G, L., & MP, P. (2023). A data-driven modeling approach for the sustainable remediation of persistent arsenic (As) groundwater contamination in a fractured rock aquifer through a groundwater recirculation well (IEG-GCW®).. Environmental research. https://doi.org/10.1016/j.envres.2022.114827

Source records