The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

Preferential sorption of some natural organic matter fractions to titanium dioxide nanoparticles: influence of pH and ionic strength

Natural organic matter (NOM) sorption to nanoparticles (NPs) can influence their transport and bioavailability in the aquatic environment. The sorption affinity of NOM to surfaces including NPs is size dependent, and depending on environmental conditions, NOM may enhance or mitigate NPs toxicity. The aim of this study was to investigate the preferential sorption of different-sized fractions of NOM to titanium dioxide (TiO₂) NPs. We specifically investigated the influence of pH, ionic strength, and NOM concentration on the extent of this preferential sorption using a constant sorbent concentration (400 mg/L TiO₂ NPs). Additionally, sorption of NOM to TiO₂ NPs at varying pH was investigated. The nonsorbed NOM was separated from the sorbed, by 50 nm polycarbonate membrane filters and ultracentrifugation. High-performance size exclusion chromatography (HPSEC) was used to determine the average molecular weights of NOM (MWw). Corroborative evidence of preferential sorption of different-sized molecular weight fractions of NOM was obtained from optical techniques such as absorbance and fluorescence spectrophotometry. The total organic carbon was measured by the Total Organic Carbon Analyzer—Shimadzu (TOC-VCPH). The results indicated that there is preferential sorption of larger sized fractions of NOM to TiO₂ NPs irrespective of NOM concentration. It was observed that the sorption of larger sized fractions of NOM was much enhanced at lower pH and at higher ionic strength. Both absorbance and fluorescence spectrophotometric techniques gave credible corroborative evidence on the extent of preferential sorption of lager sized fractions of NOM with respect to pH and ionic strength. The sorption results demonstrated higher sorption at lower pH than at higher pH. Overall, the results of this study suggest that the environmental conditions are key factors that can contribute to NOM’s fractional preferential sorption to NPs in the aquatic environment.     

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research and Forecasting (simulated). The SWAT model was applied to two 10-digit hydrologic unit code watersheds in the Coastal Plain and Piedmont zones of North Carolina. Nitrogen cycling and loading response to these meteorological data were investigated by exploring 19 SWAT nitrogen outputs relating to landscape delivery, biogeochemical assimilation, and atmospheric deposition. The largest difference in model output using both meteorology data sets was for large loads/fluxes. Landscape delivery outputs (e.g., NO^? ₃ watershed discharge, groundwater NO^? ₃ flux, soil NO^? ₃ percolation) showed the largest difference across all values. Use of the two weather data sources resulted in a nearly twofold difference in NO^? ₃ watershed discharge and groundwater NO^? ₃ flux. Differences for many nitrogen outputs were greater than those for sub-basin flow. Nitrogen outputs showed the greatest difference for agricultural land covers and there was no flow-related pattern in output differences across sub-basins or over time (years). In general, nitrogen parameter models that had a greater number of nitrate concentration, flow, and temperature terms (equation variables) in each transport model showed the greatest difference between both meteorology applications.     

Potential Impact of Clean Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin: a Modeling Investigation Using CMAQ and SWAT

There has been extensive analysis of Clean Air Act Amendment (CAAA) regulation impacts to changes in atmospheric nitrogen deposition; however, few studies have focused on watershed nitrogen transfer particularly regarding long-term predictions. In this study, we investigated impacts of CAAA NOx emissions on the fate and transport of nitrogen for two watersheds in the Neuse River Basin. We applied the Soil and Water Assessment Tool (SWAT) using simulated deposition rates from the Community Multiscale Air Quality (CMAQ) model. Two scenarios were investigated: one that considered CAAA emission controls in CMAQ simulation (with) and a second that did not (without). By 2020, results showed a 70 % drop in nitrogen discharge for the Little River watershed and a 50 % drop for the Nahunta watershed from 1990 levels under the with-CAAA scenario. Denitrification and plant nitrogen uptake played important roles in nitrogen discharge from each watershed. Nitrogen watershed response time to a change in atmospheric nitrogen deposition was 4 years for Nahunta and 2 years for Little River. We attribute these differences in nitrogen response time to contrasts in agricultural land use and diversity of crop types. Soybean, hay, and corn land covers had comparatively longer response times to changes in atmospheric deposition. The studied watersheds demonstrate relatively large nitrogen retention: ≥80 % of all delivered nitrogen.     

Biomonitoring of polychlorinated biphenyls (PCBs) in heavily polluted aquatic environment in different fish species

The distribution and concentrations of polychlorinated biphenyls (PCBs) were determined in fish species (European perch Perca fluviatilis, northern pike Esox lucius, pike perch Sander lucioperca, wels catfish Silirus glanus, common carp Cyprinus carpio, European eel Anguilla anguilla, freshwater bream Abramis brama, goldfish Carassius auratus, and roach Rutilus rutilus) in a heavily polluted water reservoir Zemplínska ?írava (Slovakia). The study performed at two different time points 5?years apart (2004 and 2009) revealed serious PCB contamination of fish muscle tissue and significant interspecies as well as tissue-specific differences in PCB uptake by fish. Total PCBs broadly correlated with the trophic position of individual fish species within a food chain (P??0.05). The study has shown that the kind of fish, its feeding habit, and specific conditions of the habitat are mutually interrelated factors that are responsible for significant variations in fish body burdens. A tendency to PCB biomagnification was also proved in some fish species of this water reservoir.     

Multivariate analysis of mixed contaminants (PAHs and heavy metals) at manufactured gas plant site soils

Principal component analysis (PCA) was used to provide an overview of the distribution pattern of polycyclic aromatic hydrocarbons (PAHs) and heavy metals in former manufactured gas plant (MGP) site soils. PCA is the powerful multivariate method to identify the patterns in data and expressing their similarities and differences. Ten PAHs (naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]pyrene) and four toxic heavy metals — lead (Pb), cadmium (Cd), chromium (Cr) and zinc (Zn) — were detected in the site soils. PAH contamination was contributed equally by both low and high molecular weight PAHs. PCA was performed using the varimax rotation method in SPSS, 17.0. Two principal components accounting for 91.7% of the total variance was retained using scree test. Principle component 1 (PC1) substantially explained the dominance of PAH contamination in the MGP site soils. All PAHs, except anthracene, were positively correlated in PC1. There was a common thread in high molecular weight PAHs loadings, where the loadings were inversely proportional to the hydrophobicity and molecular weight of individual PAHs. Anthracene, which was less correlated with other individual PAHs, deviated well from the origin which can be ascribed to its lower toxicity and different origin than its isomer phenanthrene. Among the four major heavy metals studied in MGP sites, Pb, Cd and Cr were negatively correlated in PC1 but showed strong positive correlation in principle component 2 (PC2). Although metals may not have originated directly from gaswork processes, the correlation between PAHs and metals suggests that the materials used in these sites may have contributed to high concentrations of Pb, Cd, Cr and Zn. Thus, multivariate analysis helped to identify the sources of PAHs, heavy metals and their association in MGP site, and thereby better characterise the site risk, which would not be possible if one uses chemical analysis alone.     

Heavy metal pattern and solute concentration in soils along the oldest highway of the world – the AVUS Autobahn

Highways and main roads are a potential source of contamination for the surrounding environment. High traffic rates result in elevated heavy metal concentrations in road runoff, soil and water seepage, which has attracted much attention in the recent past. Nonetheless, investigations of pollutants in roadside soils are still a subject of major interest due to the rapid development of traffic systems and increasing traffic all over the world. The accumulation of the heavy metals Pb, Cd, Cu and Zn in soils along the oldest federal highway of the world has been studied by sampling a roadside transect of 125 by 10?m. In addition, heavy metal concentrations of Pb, Cd, Zn, Cu, Ni and Cr in soil solutions from different distances (2.5, 5 and 10?m) from the hard shoulder of the highway and from three soil depths (10, 30, and 50?cm) were investigated. The results show that heavy metal concentrations are up to 20 times increased compared to the geochemical background levels and a reference site of 800-m distance from the roadside. Soil matrix concentrations in the topsoil (0-10?cm) mostly exceeded the precautionary values of the German Federal Soil Protection and Contamination Ordinance (BBodSchV). The concentrations of Cd, Pb and Zn in the soil matrix tended to decrease with distance from the roadside edge, whereas the concentrations in the soil solution increased at a distance of 10?m onwards due to a lower soil pH. Because of both high pH values and a high sorption capacity of the soils, soil solution concentrations seldom exceeded the trigger values of the German Federal Soil Protection and Contamination Ordinance (BBodSchV) for transferring soil solution to groundwater.     

Determination of heavy metals and metals levels in five fish species from I??kl? Dam Lake and Karaca?ren Dam Lake (Turkey)

The concentrations of heavy metals and metals (Zn, Pb, Bi, Cd, Ni, Co, Fe, Mn, Mg, Cu, Cr, Ca, Sr, Na, Li, K) were measured in muscle of five species Cyprinus carpio (from I??kl? dam), Scardinius erythrophthalmus (from I??kl? dam), Tinca tinca (from I??kl? dam), C. carpio (from Karaca?ren dam), Carassius carassius (from Karaca?ren dam) caught from I??kl? and Karaca?ren. The highest metal was Na (466.95 μg/g) in C. carassius, while the lowest levels were Fe (0.37 μg/g) and Cu (0.37 μg/g) in C. carpio from I??kl? dam. The mean concentrations μg/g d.w. some of heavy metals in muscle of C. carpio (from I??kl? dam), S. erythrophthalmus (from I??kl? dam), T. tinca (from I??kl? dam), C. carpio (from Karaca?ren dam), C. carassius (from Karaca?ren dam) were as follows: Cd 2.00-2.10-1.95-2.06-2.27, Zn 4.36-2.64-13.13-13.33-24.47, Pb 1.65-1.24-1.90-2.37-2.41, Co 2.46-2.37-2.48-2.58-2.80, Mg 138.51-154.35-218.59-204.58-202.16, Fe 0.37-2.62-3.17-3.01-12.33, respectively.