Browsing by Author "Nawar, S."
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Item Open Access Almost 25 years of chromatographic and spectroscopic analytical method development for petroleum hydrocarbons analysis in soil and sediment: State-of-the-art, progress and trends(Taylor & Francis, 2017-10-11) Douglas, Reward; Nawar, S.; Alamar, M. Carmen; Coulon, Frederic; Mouazen, Abdul M.This review provides a critical insight into the selection of chromatographic and spectroscopic techniques for semi-quantitative and quantitative detection of petroleum hydrocarbons in soil and sediment matrices. Advantages and limitations of both field screening and laboratory-based techniques are discussed and recent advances in chemometrics to extract maximum information from a sample by using the optimal pre-processing and data mining techniques are presented. An integrated analytical framework based on spectroscopic techniques integration and data fusion for the rapid measurement and detection of on-site petroleum hydrocarbons is proposed. Furthermore, factors influencing petroleum hydrocarbons analysis in contaminated samples are discussed and recommendations on how to reduce their influence provided.Item Open Access The applicability of spectroscopy methods for estimating potentially toxic elements in soils: state-of-the art and future trends(Taylor and Francis, 2019-05-08) Nawar, S.; Cipullo, Sabrina; Douglas, Reward; Coulon, Frederic; Mouazen, A. M.Potentially toxic elements (PTEs) in soils pose severe threats to the environment and human health. It is therefore imperative to have access to simple, rapid, portable, and accurate methods for their detection in soils. In this regard, the review introduces recent progresses made in the development and applications of spectroscopic methods for in situ semi-quantitative and quantitative detection of PTEs in soil and critically compares them to standard analytical methods. The advantages and limitations of these methods are discussed together with recent advances in chemometrics and data mining techniques allowing to extract useful information based on spectral data. Furthermore, the factors influencing soil spectra and data analysis are discussed and recommendations on how to reduce or eliminate their influences are provided. Future research and development needs for spectroscopy techniques are emphasized, and an analytical framework based on technology integration and data fusion is proposed to improve the measurement accuracy of PTEs in soil.Item Open Access The application of a handheld mid-infrared spectrometry for rapid measurement of oil contamination in agricultural sites(Elsevier, 2019-02-07) Douglas, R. K.; Nawar, S.; Alamar, M. Carmen; Coulon, Frederic; Mouazen, A. M.Rapid analysis of oil-contaminated soils is important to facilitate risk assessment and remediation decision-making process. This study reports on the potential of a handheld mid-infrared (MIR) spectrometer for the prediction of total petroleum hydrocarbons (TPH), including aliphatic (alkanes) and polycyclic aromatic hydrocarbons (PAH) in limited number of fresh soil samples. Partial least squares regression (PLSR) and random forest (RF) modelling techniques were compared for the prediction of alkanes, PAH, and TPH concentrations in soil samples (n = 85) collected from three contaminated sites located in the Niger Delta, Southern Nigeria. Results revealed that prediction of RF models outperformed the PLSR with coefficient of determination (R2) values of 0.80, 0.79 and 0.72, residual prediction deviation (RPD) values of 2.35, 1.96, and 2.72, and root mean square error of prediction (RMSEP) values of 63.80, 83.0 and 65.88 mg kg−1 for TPH, alkanes, and PAH, respectively. Considering the limited dataset used in the independent validation (18 samples), accurate predictions were achieved with RF for PAH and TPH, while the prediction for alkanes was less accurate. Therefore, results suggest that RF calibration models can be used successfully to predict TPH and PAH using handheld MIR spectrophotometer under field measurement conditions.Item Open Access Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression(Nature Publishing Group, 2019-03-14) Cipullo, S.; Nawar, S.; Mouazen, A. M.; Campo Moreno, Pablo; Coulon, FredericA 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.Item Open Access Rapid detection of alkanes and polycyclic aromatic hydrocarbons in oil-contaminated soil with visible near-infrared spectroscopy(Wiley, 2018-05-16) Douglas, Reward K.; Nawar, S.; Alamar, M. Carmen; Coulon, Frederic; Mouazen, A. M.Recent developments and applications of rapid measurement tools (RMTs) such as visible near‐infrared (vis–NIR) spectroscopy confirmed that these technologies can provide ‘fit for purpose’ and cost‐effective data for risk assessment and management of oil‐contaminated sites. Although vis–NIR spectroscopy has been used frequently to predict total petroleum hydrocarbons (TPHs), it has had limited use for polycyclic aromatic hydrocarbons (PAHs) and there has been none for alkanes. In the present study, the potential of vis–NIR spectroscopy (350–2500 nm) to measure PAHs and alkanes in 85 fresh (wet, unprocessed) oil‐contaminated soil samples collected from three sites in the Niger Delta, Nigeria, was evaluated. The vis–NIR signal and alkanes and PAHs measured in the laboratory by sequential ultrasonic solvent extraction followed by gas chromatography‐mass spectrometry (GC‐MS) were then used to develop calibration models using partial least squares regression (PLSR) and random forest (RF) modelling tools. Prior to model development, the pre‐processed spectra were divided into calibration (75%) and prediction (25%) sets. Results showed that the prediction performance of RF calibration models for both alkanes (a coefficient of determination (R2) of 0.58, a root mean square error of prediction (RMSEP) of 53.95 mg kg−1 and a residual prediction deviation (RPD) of 1.59) and PAHs (R2 = 0.71, RMSEP = 0.99 mg kg−1 and RPD = 1.99) outperformed PLSR (R2 = 0.36, RMSEP = 66.66 mg kg−1 and RPD = 1.29, and R2 = 0.56, RMSEP = 1.21 mg kg−1 and RPD = 1.55, respectively). The RF modelling approach accounted for nonlinearity of the soil spectral responses and therefore resulted in considerably greater prediction accuracy than the linear PLSR. Adoption of vis–NIR spectroscopy coupled with RF is recommended for rapid and cost‐effective assessment of PAHs and alkanes in contaminated soil.