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.     

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.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Benthic foraminiferal assemblages as pollution proxies in the northern coast of Gabes Gulf,Tunisia

A study of chemical and sedimentological parameters integrated with benthic foraminifera investigation was conducted along the northern coast of Gabes Gulf. Thirty-two samples were studied and a total of 68 benthic foraminiferal species were identified. Heavy metals enrichment factors and total hydrocarbon concentrations showed both metal and petrogenic pollution related mainly to phosphogypsum, sewage, and fishing activities. Statistical analysis (bivariate correlation and hierarchical cluster analysis) show a possible control of these pollutants on density, diversity, as well as the taxonomic composition of the benthic foraminiferal assemblages. The extent to which the population was found less dense and less diversified corresponded to the degree to which the sediment was contaminated. In these contaminated sites, an increase in relative abundance of opportunistic species such Ammonia tepida and Haynesina germanica was found. Far from pollution, foraminiferal assemblages are dominated by species characteristic of Mediterranean shallow water (Ammonia beccarii, Ammonia parkinsoniana, Elphidium crispum, Elphidium williamsoni, Elphidium advenum, Peneroplis planatus, Peneroplis pertesus).     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.