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

Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: recent advances - a review

Over the past two decades soil spectroscopy, particularly, in the infrared range, is becoming a powerful technique to simplify analysis relative to the traditional chemical methods. It is known as a rapid, cost-effective, quantitative and eco-friendly technique, which can provide hyperspectral data with narrow and numerous wavebands, both in the laboratory and in the field. In this context, the present article reviews the recent developments in mid and near infrared techniques coupled with chemometrics and machine learning tools in addition to the preprocessing transformations and variable selection strategies to diagnose soil physical and chemical properties. Both spectral techniques demonstrated a good ability to provide accurate predictions of specific properties. Moreover, the MIR spectroscopy outperformed NIR for the estimation of most indicators used for fertilizers recommendation. Herein, a detailed overview on the opportunities and challenges that soil spectroscopy offers as efficient diagnostic tool in soil science was provided

Chemical characterization of clastic cave sediments and insights into particle transport and storage in karst aquifers

Abstract Chemical characterization of clastic cave sediments and insights into particle transport and storage in karst aquifers Jill L. Riddell Cave sediments can be divided into two groups: precipitates and clastics. Precipitates are speleothems, or lithologic or mineral features that are chemically precipitated in the cave environment. Clastic cave sediments are frequently described by depositional facies, sorting, and particle size (Bosch and White, 2004). Robust analytical chemical analyses of these sediments to quantify their physical and chemical components is rarely performed although some chemical characterization of mineralogy and paleomagnetism has become prevalent in recent years (Chess et al., 2010; Sasowsky et al., 2007). The organic carbon content of cave sediments can be representative of organic carbon concentrations in the larger karst system and concentrations of organic carbon in cave sediments can be used to estimate the potential retardation of organic contaminants through the entire karst system. The ability of karst sediments to be a sorbent for metals and organic contaminants, and store and transport contaminants is positively correlated with the amount of organic carbon in the sediment; yet these concentrations are rarely reported in karst sediments. This dissertation seeks to fill the gap in the mineralogy and chemical components of cave sediments; quantify the organic carbon content of cave sediments relative to depositional facies; and measure the adsorption of an organic microsphere onto a cave sediment to explore sediment-contaminant interactions. A case study from Dropping Lick Cave in Monroe County, WV, is presented where a variety of analytical techniques were used to determine the active fraction ( \u3c 2mm) mineralogy and chemical components of the sediment The sediments were silt and sand-sized particles consisting of quartz, some clay or silicate minerals, dolomite, and amorphous materials. The particle size and total carbon was within the same range reported for the \u3c 2mm fraction in other clastic cave sediments in this region, in the central United States, and in Puerto Rico. The preliminary mineralogy of the sediments is congruent with the mineralogy of surrounding siliciclastic rocks indicating that the source of the sediment is erosional products from nearby Peters Mountain and its slopes. Particle size, TOC, and total nitrogen were measured in sediments representing different facies in Butler Cave, Virginia, USA. TOC concentrations ranged from 0.08 – 0.87 weight percent and C:N molar ratio ranged from 3 – 15, indicating a possible terrestrial source of organic carbon in these sediments. TOC concentrations measured in Butler Cave were within the same range as those observed in above water, eogenetic clastic cave sediments from two caves in Puerto Rico. Estimated retardation factors calculated based on the TOC concentrations in the Butler Cave sediments indicate the range of TOC in this cave could be responsible for 39 – 987% increase in retardation of selected contaminants. This study highlights the importance of measuring the ranges of TOC in clastic cave sediments across different facies and their role in contaminant fate and transport. In this study, The adherence of carboxylated and nonfunctionalized polystyrene microspheres onto a clastic cave sediment was quantified for microsphere dilutions in three water types – deionized water, a 25 mg/L CaCO3 solution, and a karst spring water. Regardless of water type, both types of microspheres adhered to the sediment. Infrared absorbance data of different microsphere-solution-sediment mixtures indicated the potential presence of sediment minerals and microspheres in the solution. Analysis of solution pH and infrared spectra suggested pH and mineral constituents of the sediment are the most important factors in microsphere adherence. Using the adherence data, estimated KOC values for both types of microspheres were calculated and were in the same ranges as phthalates, a known contaminant in karst aquifers that is also considered a plastic, like polystyrene. The chemical and physical commonalities between microspheres and organic and microplastic (MP) contaminants warrant further investigation of microspheres as a proxy for contaminants in sediment-contaminant experiments. The results of these experiments suggest that consideration of MPs adhered to sediments should be considered when quantifying MP contamination in karst systems