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.     

Permeability of hair to cadmium,copper and lead in five species of terrestrial mammals and implications in biomonitoring

The capacity of mammal hair to absorb toxic metals and its utility in biomonitoring has been broadly studied. Though these metal-binding properties has generally been attributed to the sulphur contained in cysteine, an amino acid that forms part of keratin, there are not many experimental studies that analyze the role of sulphur in the external deposition of potentially toxic metallic elements in order to better understand the potential of hair in biomonitoring and generate better tools for differentiating between internal and external deposition of contaminants. In this study, an experimental analysis is carried out using a scanning electron microscope on hairs of five terrestrial mammal species (Peromyscus furvus, P. maniculatus, Glossophaga soricina, Artibeus jamaicensis and Marmosa mexicana) treated with cadmium, copper and lead salts. We quantified absorbed metals as well as natural elements of the hair by energy dispersive X-ray spectroscopy (EDS) to analyze using simple statistics the role of sulphur in the absorption Cd, Cu and Pb. Given the lack of studies comparing the mechanisms of deposition of metal elements among different orders of Class Mammalia, external morphology was considered to be an important factor in the deposition of metallic particles of Cd, Cu and Pb. Bat species (Glossophaga soricina, Artibeus jamaicensis) showed a high concentration of particles in their scales, however, no between-species differences in metal absorption were observed, and during the exogenous deposition metal particles do not permeate the medulla. These results suggest that the sulphur in hair itself cannot bind metals to hair cuticle and that hair absorption capacity depends on a variety of factors such as aspects of hair morphology.     

Assessing post-industrial land cover change at the Pine Point Mine,NWT, Canada using multi-temporal Landsat analysis and landscape metrics

This study investigates land cover change near the abandoned Pine Point Mine in Canada’s Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine’s closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.     

A Novel Formulation for Designing a Monitoring Strategy: Application to the Design of a River Quality Monitoring System

In this work, we propose a technique to automatically optimize the monitoring of any distributed indicator (concentration of a substance along a river, blood pressure of a patient over time, etc.) for which a reliable estimate is previously available. From a mathematical point of view, the problem is based on obtaining a reliable estimate of the chosen indicator (e.g., by numerical simulation), and then solving a multi-objective optimization problem (with mixed real and integer variables) whose solution must provide an efficient and satisfactory monitoring strategy. As an illustrative case, we show the steps to follow in order to implement that strategy when designing a system for monitoring water quality in a river. Finally, we present and analyze the results when applying the proposed technique to study a real case in the Neuse River (North Carolina, USA).     

Adaptation Scenarios of Agriculture in Poland to Future Climate Changes

This paper demonstrates the ability of Polish agriculture to adapt to predicted climate change according to GISS and GFDL scenarios. Both climate-change scenarios will significantly affect farming conditions in Poland through water deficit, shifts in planting and harvesting seasons, changes in crop yields and crop structure. Neither scenario seems to endanger the self-sufficiency of Poland as long as preventative measures are taken. Moreover, the realization of GISS creates the possibility of a surplus in production. It must be emphasized that regardless of the scenario, the adaptation of agriculture to an expected climate change cannot be handled by the farming community itself.     

Speciation of Cr and its leachability in coal by-products from spanish coal combustion plants

This study evaluates the behaviour of total Cr and Cr (VI) during coal combustion in two Spanish power stations. The content and distribution of Cr in the feed coal and combustion wastes was determined and the Cr contents were normalized using enrichment factor indexes. The speciation of Cr in the fly ash fractions from the different hoppers of the electrostatic precipitators was established and the possibility that the Cr (VI) might lixiviate when ashes are disposed of at landfill sites was assessed. Differences in the distribution and behavior of Cr in the two power stations were observed. According to European directive 1999/31/CEE, soluble Cr(VI) in the fly ashes studied would be unlikely to pose an environmental or health risk when the ash is disposed of.     

Assessing benthic community condition in Chesapeake Bay: does the use of different benthic indices matter?

Federal and state environmental agencies conduct several programs to characterize the environmental condition of Chesapeake Bay. These programs use different benthic indices and survey designs, and have produced assessments that differ in the estimate of the extent of benthic community degradation in Chesapeake Bay. Provided that the survey designs are unbiased, differences may exist in the ability of these indices to identify environmental degradation. In this study we compared the results of three indices calculated on the same data, and the assessments of two programs: the Chesapeake Bay Program and the Mid-Atlantic Integrated Assessment (MAIA). We examined the level of agreement of index results using site-based measures of agreement, evaluated sampling designs and statistical estimation methods, and tested for significant differences in assessments. Comparison of ratings of individual sites was done within separate categories of water and sediment quality to identify which indices summarize best pollution problems in Chesapeake Bay. The use of different benthic indices by these programs produced assessments that differed significantly in the estimate of degradation. A larger fraction of poor sites was classified as good by the Environmental Monitoring and Assessment Program’s Virginian Province and MAIA benthic indices compared to the Chesapeake Bay benthic index of biotic integrity, although overall classification efficiencies were similar for all indices. Differences in survey design also contributed to differences in assessments. The relative difference between the indices remained the same when they were applied to an independent dataset, suggesting that the indices can be calibrated to produce consistent results.