RESUMO

Submarine outfalls have been employed to convey urban effluents to their fate in the open ocean due to their dilution capacity and organic matter decay. This work analysed Escherichia coli concentrations in the Barra da Tijuca (Rio de Janeiro, Brazil) submarine outfall plume, considering an hourly variable bacterial die-off due to environmental parameters associated with dynamic changes, vertical plume position, and thickness in response to hydrodynamic conditions. The adopted modelling procedure included coupling a near-field mixing zone model, NRFIELD, with the far-field Lagrangian transport and water quality model of the SisBaHiA® ( http://www.sisbahia.coppe.ufrj.br ). The coupling methodology simulated E. coli concentrations considering simultaneous variations in temperature, salinity, solar radiation, and hydrodynamic conditions. The results showed substantial variability in E. coli concentrations in the marine environment due to variable environmental conditions, regulating solar radiation levels over the submerged plume.

Assuntos

RESUMO

Air quality is one of the main factors that must be guaranteed in animal production. However, the measurement of pollutants is still a problem in several countries because the available methods are costly and do not always apply to the reality of the constructive typology adopted, as in countries with a hot climate, which adopt predominantly open facilities. Thus, the objective of the present study was to develop predictive models for the potential generation and emission of ammonia in the production of broiler chickens with different types of litter, different reuse cycles and under different climatic conditions. Samples of poultry litter from thirty commercial aviaries submitted to different air temperatures were analyzed. The experiment was conducted and analyzed in a completely randomized design, following a factorial scheme. Models were developed to predict the potential for generation and emission of ammonia, which can be applied in facilities with ambient conditions of air temperature between 25 and 40 °C and with wood shaving bed with up to four reuse cycles and coffee husks bed with up to six reuse cycles. The developed and validated models showed high accuracy indicating that they can be used to estimate the potential for ammonia generation and emission.

RESUMO

Classification of beaches into morphodynamic states is a common approach in sandy beach studies, due to the influence of natural variables in ecological patterns and processes. The use of remote sensing for identifying beach type and monitoring changes has been commonly applied through multiple methods, which often involve expensive equipment and software processing of images. A previous study on the South African Coast developed a method to classify beaches using conditional tree inferences, based on beach morphological features estimated from public available satellite images, without the need for remote sensing processing, which allowed for a large-scale characterization. However, since the validation of this method has not been tested in other regions, its potential uses as a trans-scalar tool or dependence from local calibrations has not been evaluated. Here, we tested the validity of this method using a 200-km stretch of the Brazilian coast, encompassing a wide gradient of morphodynamic conditions. We also compared this locally derived model with the results that would be generated using the cut-off values established in the previous study. To this end, 87 beach sites were remotely assessed using an accessible software (i.e., Google Earth) and sampled for an in-situ environmental characterization and beach type classification. These sites were used to derive the predictive model of beach morphodynamics from the remotely assessed metrics, using conditional inference trees. An additional 77 beach sites, with a previously known morphodynamic type, were also remotely evaluated to test the model accuracy. Intertidal width and exposure degree were the only variables selected in the model to classify beach type, with an accuracy higher than 90% through different metrics of model validation. The only limitation was the inability in separating beach types in the reflective end of the morphodynamic continuum. Our results corroborated the usefulness of this method, highlighting the importance of a locally developed model, which substantially increased the accuracy. Although the use of more sophisticated remote sensing approaches should be preferred to assess coastal dynamics or detailed morphodynamic features (e.g., nearshore bars), the method used here provides an accessible and accurate approach to classify beach into major states at large spatial scales. As beach type can be used as a surrogate for biodiversity, environmental sensitivity and touristic preferences, the method may aid management in the identification of priority areas for conservation.

Assuntos

RESUMO

Mercury pollution of water bodies exerts significant human and ecosystem health impacts due to high toxicity. Relatively high levels of mercury have been detected in the Amazon River and its tributaries and associated lakes. The study employed a Bayesian Network approach to investigate the contribution from geogenic sources to mercury pollution of lakes in the Madeira River basin, which is the largest tributary of the Amazon River. It was found that the source indicators of naturally occurring mercury have both, positive and negative relationships with mercury in lake sediments. Although the positive relationships indicated the influence of geological and soil formations, the negative relationships implied that the use of mercury amalgam for gold extraction in artisanal and small-scale mining (ASM), which is the primary anthropogenic source of mercury, also contribute to mercury in Amazon tributaries. This was further evident as mercury concentrations in lake sediments were found to be significantly higher than those in the surrounding rocks. However, potential anthropogenic mercury was attributed to historical inputs from gold mining due to the recent decline of ASM mining practice in the region.

Assuntos

RESUMO

Índices topográficos (IT) obtidos computacionalmente a partir do modelo numérico de elevação do terreno (MNE) têm sido incorporados em algoritmos computacionais aplicados na simulação de processos hidrológicos, erosivos e de transporte de poluentes. Por meio desses índices, zonas de acúmulo de umidade em uma bacia hidrográfica, por exemplo, podem ser previstas espacialmente através de IT, que levam em consideração efeitos de orientação de drenagem e declividade do terreno. Este trabalho tem como propósito o de apresentar uma revisão bibliográfica sobre esse tema e de demonstrar a aplicabilidade desses índices por meio de alguns exemplos, aplicada à modelagem agrícola e ambiental.

Topographic indices obtained computationally from the numerical model of elevation have been incorporated into computer algorithms and used in hydrological simulating processes, erosion and pollutant transport. Through these indices, zones of water accumulation in a catchment, for example, can be predicted using topographic index that take into account the slope orientation and land slope. This study aims to present a review of the literature on this topic by means of some examples applied in agricultural and environmental modelling.