In order to quickly assess the transfer of radioactive cesium after a nuclear incident, it is useful to know the main biospheric parameters influencing this transfer. A suitably simplified heuristic formula for the Cs transfer is helpful for further application in a Geographic Information System (GIS). In order to determine the most relevant parameters given their huge variability in nature, samples of 150 aquatic plants and the corresponding sediments of 26 diverse aquatic locations such as lakes, ponds, and disconnected parts of rivers were measured for 137Cs, 134Cs, and 40K radioactivity one year after the nuclear disaster of Chernobyl. Sediments were characterized by determination of weight loss after heating, extractable Cs and K, pH(KCl), particle size distribution, content of clay minerals, and similar biospheric, chemical, and physical parameters. As a general concept, the procedure of uptake of radioactive cesium was subdivided into the two following steps: “resorption of cesium fallout by soil” and “uptake of soil cesium by plants”. Results for the resorption by soil show strong dependence on the percentage of dry matter and on the content of muscovite (mica) in the sediment. The uptake in plants, however, depends mostly on the content of 137Cs in the sediment itself, on the content of montmorillonite (weathered mica) and on the transfer factor of 40K which indicates the potassium affinity of the 30 different collected plant species. These findings can serve to quickly and practically assess the transfer factor across larger geographic regions in an evidence-based manner. Suitable IT tools for such space-related estimations are Geographic Information Systems or Virtual Globes such as Google Earth.

A newly isolated white-rot fungus, Armillaria sp. strain F022, was isolated from the decayed wood in a tropical rain forest. Strain F022 was capable of decolorizing a variety of synthetic dyes, including azo, triphenylmethane, and anthraquinone dyes, with an optimal efficiency of decolorization obtained when dyes added after 96 h of culture, with the exception of Brilliant Green. All of the tested dyes were decolorized by the purified laccase in the absence of any redox mediators, but only a few were completely removed, while others were not completely removed even when decolorization time was increased. The laccase, with possible contributions from unknown enzymes, played a role in the decolorization process carried out by Armillaria sp. F022 cultures, and this biosorption contributed a negligible part to the decolorization by cultures. The effect of dye to fungal growth was also investigated. When dyes were added at 0 h of culture, the maximum dry mycelium weight (DMW) values in the medium containing Brilliant Green were 1/6 of that achieved by the control group. For other dyes, the DMW was similar with control. The toxic tolerance of dye for the cell beads was excellent at least up to a concentration of 500 mg/l. The optimum conditions for decolorization of three synthetic dyes are at pH 4 and 40°C.

Nanocomposite of CeO₂–SnO₂ containing different CeO₂ contents was prepared by coprecipitation process. The material obtained was characterized by X-ray diffraction and N₂ adsorption–desorption isotherms. Its photocatalytic activity was tested in the degradation of azo dye of leather, Direct Black 38, in aqueous solution under sunlight. The photocatalytic activity of the coupled CeO₂–SnO₂ oxide ranged depending on the CeO₂ contents. The optimum amount of CeO₂ for the synthesis of CeO₂–SnO₂ was 7 wt.% since the nanoparticles showed high photocatalytic activity in the degradation of the dye, similar to that of the TiO₂–P25 photocatalyst. The kinetics of photocatalytic degradation and total organic carbon removal under sunlight were found to follow a first-order rate law. The results indicated that CeO₂–SnO₂ can be used for the removal of dyes from wastewater.

Faecal contamination of drinking water extracted from alluvial aquifers can lead to severe problems. River water infiltration can be a hazard for extraction wells located nearby, especially during high discharge events. The high dimensionality of river–groundwater interaction and the many factors affecting bacterial survival and transport in groundwater make a simple assessment of actual water quality difficult. The identification of proxy indicators for river water infiltration and bacterial contamination is an important step in managing groundwater resources and hazard assessment. The time resolution of microbial monitoring studies is often too low to establish this relationship. A proxy-based approach in such highly dynamic systems requires in-depth knowledge of the relationship between the variable of interest, e.g. river water infiltration, and its proxy indicator. In this study, continuously recorded physico-chemical parameters (temperature, electrical conductivity, turbidity, spectral absorption coefficient, particle density) were compared to the counts for faecal indicator bacteria, Escherichia coli and Enterococcus sp. obtained from intermittent sampling. Sampling for faecal indicator bacteria was conducted on two temporal scales: (a) routine bi-weekly monitoring over a month and (b) intense (bi-hourly) event-based sampling over 3 days triggered by a high discharge event. Both sampling set-ups showed that the highest bacterial concentrations occurred in the river. E. coli and Enterococcus sp. concentrations decreased with time and length of flow path in the aquifer. The event-based sampling was able to demonstrate differences in bacterial removal between clusters of observation wells linked to aquifer composition. Although no individual proxy indicator for bacterial contamination could be established, it was shown that a combined approach based on time-series of physico-chemical parameters could be used to assess river water infiltration as a hazard for drinking water quality management.

Animal wastes are commonly used in a sustainable manner to fertilize crops. However, manures contain numerous pathogenic bacteria that can impact animal and human health. Treatment of animal waste by anaerobic digestion has the potential to reduce pathogen loading to land. This study was conducted to determine the fate of bacteria applied in raw and anaerobically digested dairy slurries that were broadcast and subsurface applied in a field of forage grasses. Digested slurry had significantly fewer indicator bacteria, Escherichia coli and fecal coliform at time of application. Anaerobic digestion did not increase the survivability of indicator bacteria. Waste treatment and application method did not affect the rate of bacteria die-off. There were fewer E. coli and fecal coliform at the end of each trial in the soils that received digested slurry. Anaerobic digestion of dairy waste has the potential to reduce pathogenic bacteria loading to cropland.

The occurrence of fluoride in groundwater has been reported in many countries, mainly because the excess fluoride in drinking water can lead to dental or skeletal fluorosis. Fluoride removal by coagulation with Moringa oleifera seeds, followed by separation with membranes, was investigated in this work. Artificially fluoridated water, at a starting fluoride concentration of 10 mg L⁻¹, was submitted to a coagulation process with aqueous extracts of M. oleifera seeds. The coagulation process was followed by ultrafiltration with membranes at different pressures. The coagulation process with 2.5 g L⁻¹ of M. oleifera promoted a reduction of 90.90 % in the fluoride content of the treated water, making it possible for poor communities to consume this water. It is noteworthy that the combined coagulation/filtration process using raw coagulant showed the highest values of colour and turbidity, which, however, were still below the limits set for drinking water by Brazilian legislation. The advantage of proposing a sequential process using membrane separation is that it removes colour and turbidity, caused by the use of M. oleifera as a coagulant, resulting in water that meets potability standards.

In remotely located watersheds or large waterbodies, monitoring water quality parameters is often not feasible because of high costs and site inaccessibility. A cost-effective remote sensing-based methodology was developed to predict water quality parameters over a large and logistically difficult area. Landsat spectral data were used as a proxy, and a neural network model was developed to quantify water quality parameters, namely chlorophyll-a, turbidity, and phosphorus before and after ecosystem restoration and during the wet and dry seasons. The results demonstrate that the developed neural network model provided an excellent relationship between the observed and simulated water quality parameters. These correlated for a specific region in the greater Florida Everglades at R ² > 0.95 in 1998–1999 and in 2009–2010 (dry and wet seasons). Moreover, the root mean square error values for phosphorus, turbidity, and chlorophyll-a were below 0.03 mg L⁻¹, 0.5 NTU, and 0.17 mg m⁻³, respectively, at the neural network training and validation phases. Using the developed methodology, the trends for temporal and spatial dynamics of the selected water quality parameters were investigated. In addition, the amounts of phosphorus and chlorophyll-a stored in the water column were calculated demonstrating the usefulness of this methodology to predict water quality parameters in complex ecosystems.

Microbiologically contaminated water severely impacts public health in low-income countries, where treated water supplies are often inaccessible to much of the population. Groundwater represents a water source that commonly has better microbiological quality than surface water. A 2-month intensive flow and quality monitoring programme of a spring in a densely settled, unsewered parish of Kampala, Uganda, revealed the persistent presence of high chloride and nitrate concentrations that reflect intense loading of sewage in the spring’s catchment. Conversely, thermotolerant coliform bacteria counts in spring water samples remained very low outside of periods of intense rainfall. Laboratory investigations of mechanisms responsible for this behavior, achieved by injecting a pulse of H40/1 bacteriophage tracer into a column packed with locally derived granular laterite, resulted in near-total tracer adsorption. X-ray diffraction (XRD) analysis showed the laterite to consist predominantly of quartz and kaolinite, with minor amounts (<5%) of haematite. Batch studies comparing laterite adsorption capacity with a soil having comparable mineralogy, but with amorphous iron oxide rather than haematite, showed the laterite to have a significantly greater capacity to adsorb bacteriophage. Batch study results using pure haematite confirmed that its occurrence in laterite contributes substantially to micro-organism attenuation observed and serves to protect underlying groundwater.

In situ remediation with waste material is an inexpensive method to reduce contaminant availability in polluted soil. The experiments were done to investigate the effects of possible in situ application of two different amendments: inorganic material (marble sludge) and organic material (horticultural waste compost) on chemical and biological properties of abandoned metalliferous mine wastes. The results show that the application of inorganic material raises the pH above neutrality and the combination of inorganic and organic material would produce the highest ratio of biological activity. The reductions of available Zn, Pb and As in lime, organic and lime/organic amendments were favoured by incubation time. However, available Cd content increased after 275 days of incubation, except the treatment with inorganic amendment. This work denoted that the application of lime with organic amendments has a better effect than the lime alone because the addition of both amendments improves both soil chemical and biological properties.

A set of indices was developed in order to classify the vulnerability of agricultural land to water and nitrogen losses (LOS), setting a basis for the integrated water resources management in agricultural systems. To calibrate the indices using multiple regression analysis, the simulation results of Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model for combinations of different soil properties, topography, and climatic conditions of a reference field crop were used as “observed values.” GLEAMS quantified (1) the annual losses of the percolated water beneath the root zone, (2) the annual losses of the surface runoff, (3) the annual losses of the nitrogen leaching beneath the root zone, and (4) the annual losses of nitrogen through the surface runoff, which were used to calibrate the following indices LOSW-P, LOSW-R, LOSN-PN, and LOSN-RN, respectively. All the simulations to gain the LOS indices were carried out for the same reference field crop, the same nitrogen fertilization, and the same irrigation practice, in order to obtain the intrinsic vulnerability of agricultural land to water and nitrogen losses. The LOS indices were also combined to derive nitrogen concentrations in the percolated and in the runoff water. Finally, the connection of LOS indices with the groundwater was performed using an additional equation, which determines the minimum transit time of the percolated water to reach the groundwater table.