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Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression

S Cipullo, Said Nawar (UGent) , Abdul Mouazen (UGent) , P Campo-Moreno and F Coulon
(2019) SCIENTIFIC REPORTS. 9.
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Abstract
A number of studies have shown that visible and near infrared spectroscopy (VIS-NIRS) offers a rapid on-site measurement tool for the determination of total contaminant concentration of petroleum hydrocarbons compounds (PHC), heavy metals and metalloids (HM) in soil. However none of them have yet assessed the feasibility of using VIS-NIRS coupled to random forest (RF) regression for determining both the total and bioavailable concentrations of complex chemical mixtures. Results showed that the predictions of the total concentrations of polycyclic aromatic hydrocarbons (PAH), PHC, and alkanes (ALK) were very good, good and fair, and in contrast, the predictions of the bioavailable concentrations of the PAH and PHC were only fair, and poor for ALK. A large number of trace elements, mainly lead (Pb), aluminium (Al), nickel (Ni), chromium (Cr), cadmium (Cd), iron (Fe) and zinc (Zn) were predicted with very good or good accuracy. The prediction results of the total HMs were also better than those of the bioavailable concentrations. Overall, the results demonstrate that VIS-NIR DRS coupled to RF is a promising rapid measurement tool to inform both the distribution and bioavailability of complex chemical mixtures without the need of collecting soil samples and lengthy extraction for further analysis.
Keywords
DIFFUSE-REFLECTANCE SPECTROSCOPY, RAPID IDENTIFICATION, ENHANCED ASSESSMENT, NIR SPECTROSCOPY, HYDROCARBONS, REMEDIATION, EXTRACTION, METALS

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MLA
Cipullo, S., et al. “Predicting Bioavailability Change of Complex Chemical Mixtures in Contaminated Soils Using Visible and Near-Infrared Spectroscopy and Random Forest Regression.” SCIENTIFIC REPORTS, vol. 9, 2019, doi:10.1038/s41598-019-41161-w.
APA
Cipullo, S., Nawar, S., Mouazen, A., Campo-Moreno, P., & Coulon, F. (2019). Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression. SCIENTIFIC REPORTS, 9. https://doi.org/10.1038/s41598-019-41161-w
Chicago author-date
Cipullo, S, Said Nawar, Abdul Mouazen, P Campo-Moreno, and F Coulon. 2019. “Predicting Bioavailability Change of Complex Chemical Mixtures in Contaminated Soils Using Visible and Near-Infrared Spectroscopy and Random Forest Regression.” SCIENTIFIC REPORTS 9. https://doi.org/10.1038/s41598-019-41161-w.
Chicago author-date (all authors)
Cipullo, S, Said Nawar, Abdul Mouazen, P Campo-Moreno, and F Coulon. 2019. “Predicting Bioavailability Change of Complex Chemical Mixtures in Contaminated Soils Using Visible and Near-Infrared Spectroscopy and Random Forest Regression.” SCIENTIFIC REPORTS 9. doi:10.1038/s41598-019-41161-w.
Vancouver
1.
Cipullo S, Nawar S, Mouazen A, Campo-Moreno P, Coulon F. Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression. SCIENTIFIC REPORTS. 2019;9.
IEEE
[1]
S. Cipullo, S. Nawar, A. Mouazen, P. Campo-Moreno, and F. Coulon, “Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression,” SCIENTIFIC REPORTS, vol. 9, 2019.
@article{8610110,
  abstract     = {{A number of studies have shown that visible and near infrared spectroscopy (VIS-NIRS) offers a rapid on-site measurement tool for the determination of total contaminant concentration of petroleum hydrocarbons compounds (PHC), heavy metals and metalloids (HM) in soil. However none of them have yet assessed the feasibility of using VIS-NIRS coupled to random forest (RF) regression for determining both the total and bioavailable concentrations of complex chemical mixtures. Results showed that the predictions of the total concentrations of polycyclic aromatic hydrocarbons (PAH), PHC, and alkanes (ALK) were very good, good and fair, and in contrast, the predictions of the bioavailable concentrations of the PAH and PHC were only fair, and poor for ALK. A large number of trace elements, mainly lead (Pb), aluminium (Al), nickel (Ni), chromium (Cr), cadmium (Cd), iron (Fe) and zinc (Zn) were predicted with very good or good accuracy. The prediction results of the total HMs were also better than those of the bioavailable concentrations. Overall, the results demonstrate that VIS-NIR DRS coupled to RF is a promising rapid measurement tool to inform both the distribution and bioavailability of complex chemical mixtures without the need of collecting soil samples and lengthy extraction for further analysis.}},
  articleno    = {{4492}},
  author       = {{Cipullo, S and Nawar, Said and Mouazen, Abdul and Campo-Moreno, P and Coulon, F}},
  issn         = {{2045-2322}},
  journal      = {{SCIENTIFIC REPORTS}},
  keywords     = {{DIFFUSE-REFLECTANCE SPECTROSCOPY,RAPID IDENTIFICATION,ENHANCED ASSESSMENT,NIR SPECTROSCOPY,HYDROCARBONS,REMEDIATION,EXTRACTION,METALS}},
  language     = {{eng}},
  pages        = {{12}},
  title        = {{Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression}},
  url          = {{http://dx.doi.org/10.1038/s41598-019-41161-w}},
  volume       = {{9}},
  year         = {{2019}},
}
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