Características hidroquímicas da água da sub-bacia hidrográfica do Rio Poxim–Sergipe / Hydrochemical characteristics of water in the Poxim – Sergipe river hydrographic sub-basin

Nesse estudo foram investigados, usando o digrama de Gibbs e as razões iônicas, os mecanismos que controlam a hidrogeoquímica da água da sub-bacia hidrográfica do rio Poxim, situada no estado de Sergipe, Nordeste do Brasil. Amostras de água de superfície foram coletadas no período seco de 2005 e chuvoso de 2006 em 15 estações distribuídas ao longo da sub-bacia, e nos períodos seco e chuvoso de 2013 e 2014, apenas nas estações 5, 8, 12 e 15. As amostras foram analisadas para determinação dos seguintes parâmetros: temperatura, pH, sólidos totais dissolvidos, sódio, potássio, cálcio, magnésio, cloreto, sulfato e bicarbonato. A abundância iônica ocorreu na seguinte ordem Na+ > Ca2+ > Mg2+ e HCO3- > Cl- > SO42-. O diagrama de Gibbs indicou a precipitação atmosférica e as interações água – rocha, como principais fatores que controlam a hidrogeoquímica dos constituintes dissolvidos na água. Através das razões iônicas foi possível inferir que o sódio e cloreto foram originários da dissolução da halita e do sal marinho carreado através da deposição atmosférica, enquanto o cálcio e magnésio foram resultantes da dissolução dos carbonatos (calcita, dolomita).

Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater : use of ultrafiltration and Kohonen neural network.

Humic substances (HS) are ubiquitous organic compounds able to affect mobility and availability of arsenic (As) in aquatic systems. Although it is known that associations between HS and As occur mainly via iron (Fe)-cationic bridges, the behaviour and distribution of this metalloid in HS- and Fe-rich environments is still not fully understood. In this paper, the quality of HS from different rivers in Brazil and Germany and its influence on the behaviour of As(V) under different Fe(III) concentrations were investigated. HS were extracted from four different rivers (Cascatinha, Holtemme, Selke and Warme Bode), characterised and fractionated into different molecular weight sizes (10, 5 and 1 kDa). Complexation tests were performed using an ultrafiltration system and 1 kDa membranes. All data was analysed using the Kohonen neural network (SOM e Self organising maps). All samples, except Selke, exhibited similar results of free As (<1 kDa). The results suggested that associations between HS, Fe and As were dependent on nitrogen (N)earomatic carbon (C), amount of sulphur (S) and the molecular size of the HS. Although all HS appeared to be similar after looking at most variables analysed, the SOM could discriminate them into three different groups. Characterisation of the HS indicated that they had terrestrial material (from C3 plants) as precursor material. Most of the As and Fe was distributed in the fractions of higher (>10 kDa) and lower (<1 kDa) size. HS quality is an important factor to take into account when studying the behaviour of As in HS-rich environments

Distribution and bioavailability of arsenic in natural waters of a mining area studied by ultrafiltration and diffusive gradients in thin films.

The distribution of metals and metalloids among particulate, dissolved, colloidal, free, and labile forms in natural waters is of great environmental concern since it determines their transportation behaviour and bioavailability. Organic matter can have an important role for this distribution process, since it is an important complexing agent and ubiquitous in the aquatic environment. We studied the distribution, mobility and bioavailability of Al, As and Fe in natural waters of a mining area (Quadril atero Ferr?fero, Brazil) and the influence of organic matter in these processes. Water samples were taken from 12 points during the dry and rainy seasons, filtrated at 0.45 mm and ultrafiltrated (<1 kDa) to separate the particulate, colloidal and free fractions. Diffusive gradients in thin films (DGT) were deployed at 5 sampling points to study the labile part of the elements. Total and dissolved organic carbon and the physicochemical parameters were measured along with the sampling. The results of ultrafiltration (UF) and DGT were compared. The relationship among the variables was studied through multivariate analysis (Kohonen neural network), which showed that the seasonality did not impact most of the samples. Fe and Al occurred mainly in the particulate fraction whereas As appeared more in the free fraction. Most of the dissolved Fe and Al were inert (colloidal form) while As was more labile and bioavailable. The results showed that sampling points with a higher quantity of complexed Fe (colloidal fraction) showed less labile As, which may indicate formation of ternary complexes among organic matter, As and Fe