Perspective Chapter: Rapid Measurement of Potentially Toxic Elements (PTEs) in Petroleum Hydrocarbons Polluted Soils by X-Ray Fluorescence (XRF) Spectroscopy

Potentially toxic elements (PTEs) contamination in soils threats human wellbeing and ecological health because of their toxicity and bioaccumulation. This research presents a portable Olympus Delta Premium 6000 Series XRF Analyser (Olympus, USA) as a rapid measurement tool (RMT) for PTEs: Cr, Cu, Fe, Pb, Mn, and Zn in contaminated soils in the Niger Delta, Nigeria. A total of 45 crude oil-contaminated soils were collected from three genuinely oil spill sites. The range of measured PTEs concentrations (mg/kg) in the study sites are as follows: Site 1: chromium (Cr) 54–75, copper (Cu) 5.4–16.6, iron (Fe) 14,841–23,404, lead (Pb) 13.5–21.4, manganese (Mn) 158–555, and zinc (Zn) 32.6–47.2; Site 2: (35–66), (5–16.1), (10166–20,967), (12–17.8), (209–440), (17.6–33.6); and Site 3: (32–115), (6.5–20.8), (7538–22,800), (12–135), (98–338), (19.9–177). The trend of PTEs across the three sites follows the same order: Fe > Mn > Cr > Zn > Pb > Cu. The average concentration values of PTEs in all the 3 sites were higher than background concentration values. Thus, crude oil spill spiked the PTEs concentrations. XRF spectroscopy is recommended as a cost-effective and RMT for PTEs in soils

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

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

Rapid prediction of total petroleum hydrocarbons concentration in contaminated soil using vis-NIR spectroscopy and regression techniques

Petroleum hydrocarbons contamination in soil is a worldwide significant environmental issue which has raised serious concerns for the environment and human health (Brevik and Burgess, 2013). Petroleum hydrocarbons encompass a mixture of short and long-chain hydrocarbon compounds. However the difference between the term petroleum hydrocarbons (PHC) as such and the term total petroleum hydrocarbons (TPH) should be noted. PHC typically refer to the hydrogen and carbon containing compounds that originate from crude oil, while TPH refer to the measurable amount of petroleum-based hydrocarbons in an environmental matrix and thus to the actual results obtained by sampling and chemical analysis (Coulon and Wu, 2017). TPH is thus a method-defined term. Among a range of techniques, gas chromatography is preferred for the measurement of hydrocarbon contamination in environmental samples, since it allows to detect a broad range of hydrocarbons and can provide both sensitivity and selectivity depending on the detector and hyphenated configuration used (Brassington et al., 2010; Drozdova et al., 2013). However, GC-based techniques can be time consuming and expensive and do not allowed rapid and broad scale analysis of petroleum contamination on-site (Okparanma and Mouazen, 2013; Okparanma et al., 2014)

Rapid detection of alkanes and polycyclic aromatic hydrocarbons in oil-contaminated soil with visible near-infrared spectroscopy

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

Evaluation of vis-NIR reflectance spectroscopy sensitivity to weathering for enhanced assessment of oil contaminated soils

This study investigated the sensitivity of visible near-infrared spectroscopy (vis-NIR) to discriminate between fresh and weathered oil contaminated soils. The performance of random forest (RF) and partial least squares regression (PLSR) for the estimation of total petroleum hydrocarbon (TPH) throughout the time was also explored. Soil samples (n = 13) with 5 different textures of sandy loam, sandy clay loam, clay loam, sandy clay and clay were collected from 10 different locations across the Cranfield University's Research Farm (UK). A series of soil mesocosms was then set up where each soil sample was spiked with 10 ml of Alaskan crude oil (equivalent to 8450 mg/kg), allowed to equilibrate for 48 h (T2 d) and further kept at room temperature (21 °C). Soils scanning was carried out before spiking (control TC) and then after 2 days (T2 d) and months 4 (T4 m), 8 (T8 m), 12 (T12 m), 16 (T16 m), 20 (T20 m), 24 (T24 m), whereas gas chromatography mass spectroscopy (GC–MS) analysis was performed on T2 d, T4 m, T12 m, T16 m, T20 m, and T24 m. Soil scanning was done simultaneously using an AgroSpec spectrometer (305 to 2200 nm) (tec5 Technology for Spectroscopy, Germany) and Analytical Spectral Device (ASD) spectrometer (350 to 2500 nm) (ASDI, USA) to assess and compare their sensitivity and response against GC–MS data. Principle component analysis (PCA) showed that ASD performed better than tec5 for discriminating weathered versus fresh oil contaminated soil samples. The prediction results proved that RF models outperformed PLSR and resulted in coefficient of determination (R2) of 0.92, ratio of prediction deviation (RPD) of 3.79, and root mean square error of prediction (RMSEP) of 108.56 mg/kg. Overall, the results demonstrate that vis–NIR is a promising tool for rapid site investigation of weathered oil contamination in soils and for TPH monitoring without the need of collecting soil samples and lengthy hydrocarbon extraction for further quantification analysis

The applicability of spectroscopy methods for estimating potentially toxic elements in soils: state-of-the art and future trends

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

Evaluation of the potential of agricultural wastes-cattle manure and poultry manure for bioremediation of crude oil-contaminated soil

The Niger Delta region of Nigeria suffers from petroleum pollution, which affects ecosystem functioning and human health, which necessitates finding sustainable remediation options that utilize local resources. In this work, cattle manure (CM) and poultry manure (PM), which are primarily utilized as biofertilizer for agricultural purposes, were utilized to bioremediate crude oil-contaminated soil on a laboratory scale. In addition to being readily accessible, CM and PM are also sustainable bioresources that are host to a wide variety of microflora that can be used for bioaugmentation. At the end of the 1.5 month study, the impact of the amendments on speciated total petroleum hydrocarbons (STPH) in the range of nC10-nC40 was evaluated. A significantly higher STPH degradation of 36% in PM-amended soil was observed compared to CM-amended soil (23%); and only 1% degradation in enhanced by natural attenuation soil (RENA). The pre-dominant aliphatic fractions in the samples analyzed were nC16-nC35. In comparison to the CM amendment option, PM amendments achieved better bioremediation of these fractions. Moreover, the effect of biowaste ratio amendment to the contaminated soil showed that the ratio 1:1 (w/w) for both bioadmendments performed better than the ratio 1:2 (w/w), suggesting that the higher the amount of amendment to contaminated soil, the more effective the bioremediation. The results of this study demonstrate the potential of PM as a sustainable, affordable, and local bioremediation technique for recovering soil contaminated by crude oil in the Niger Delta

Rapid detection of alkanes and polycyclic aromatic hydrocarbons

<i>Vis-NIR data spectra analysis and chemometric modelling</i