Herbicides in the upper Poxim River, Sergipe, and the risk of contamination of water resources

Increased agricultural activity in watershed areas has been causing concern over contamination by herbicides in agricultural areas. The problem becomes more important when contamination can affect water for human consumption, as happens with water from the Poxim river, which supplies the city of Aracaju, capital of the State of Sergipe. The aim of this study was to evaluate the risk of contamination by herbicides to both surface and groundwater in the upper sub-basin of the Poxim River, and to detect the presence of the active ingredients Diuron and Ametrine up-river from the sugar-cane plantations. Risk analysis was carried out using criteria from the Environmental Protection Agency (EPA), the GUS index, and the GOSS method. It was observed that several active ingredients are at risk of leaching, demonstrating the importance of monitoring the river to control both the quality of water and the frequency and volume of herbicides used in the region. Based on the results, monitoring was carried out bi-monthly from July 2009 to July 2010 at two sampling points. Water samples were analyzed in the laboratory, where the presence of Diuron and Ametrine was noted. Water quality in the Sub-basin of the Rio Poxim is being influenced by the use of herbicides in the region. There was an increase in herbicide concentration in the surface water during the rainy season, possibly caused by soil runoff.

Isotopic, trace element and nutrient characterization of coastal waters from Ubatuba inner shelf area, south-eastern Brazil

Stable isotopes, tritium, radium isotopes, radon, trace elements and nutrients data were collected during two sampling campaigns in the Ubatuba coastal area (south-eastern Brazil) with the aim of investigating submarine groundwater discharge (SGD) in the region. The isotopic composition (delta D, delta(18)O, (3)H) of submarine waters was characterised by significant variability and heavy isotope enrichment. The stable isotopes and tritium data showed good separation of groundwater and seawater groups. The contribution of groundwater in submarine waters varied from a few % to 17%. Spatial distribution of (222)Rn activity concentration in surface seawater revealed changes between 50 and 200 Bq m(-3) which were in opposite relationship with observed salinities. Time series measurements of (222)Rn activity concentration in Flamengo Bay (from 1 to 5 kBq m(-3)), obtained by in situ underwater gamma-spectrometry showed a negative correlation between the (222)Rn activity concentration and tide/salinity. This may be caused by sea level changes as tide effects induce variations of hydraulic gradients, which increase (222)Rn concentration during lower sea level, and opposite, during high tides where the (222)Rn activity concentration is smaller. The estimated SGD fluxes varied during 22-26 November between 8 and 40 cm d(-1), with an average value of 21 cm d(-1) (the unit is cm(3)/cm(2) per day). The radium isotopes and nutrient data showed scattered distributions with offshore distance and salinity. which implies that in a complex coast with many small bays and islands, the area has been influenced by local currents and groundwater-seawater mixing. SGD in the Ubatuba area is fed by coastal contaminated groundwater and re-circulated seawater (with small admixtures of groundwater). which claims for potential environmental concern with implications on the management of freshwater resources in the region. (C) 2007 Elsevier Ltd. All rights reserved.

Advancing the management of primary immunodeficiency diseases in Latin America: Latin American Society for Immunodeficiencies (LASID) Initiatives

Primary immunodeficiency diseases (PIDD) are associated with significant morbidity and mortality and result in a significant public health burden. This is in part due to the lack of appropriate diagnosis and treatment of these patients. It is critical that governments become aware of this problem and provide necessary resources to reduce this impact on health care systems. Leading physicians in their respective countries must be supported by their own governments in order to implement tools and provide education and thus improve the diagnosis and treatment of PIDD. The Latin American Society of Primary Immunodeficiencies (LASID) has initiated a large number of activities aimed at achieving these goals, including the establishment of a PIDD registry, development of educational programmes and guidelines, and the introduction of a PIDD fellowship programme. These initiatives are positively impacting the identification and appropriate treatment of patients with PIDD in Latin America. Nevertheless, much remains to be done to ensure that every person with PIDD receives proper therapy. (C) 2011 SEICAP. Published by Elsevier Espana, S.L. All rights reserved.

Evaluation of the capability of decentralized management of epidemiological surveillance in the state of Bahia

Evaluative research into the capability of decentralized management of epidemiological vigilance (EV) was conducted in the operational, organizational and sustainable dimensions in the state of Bahia, Brazil. The quantitative approach was used in the construction of a baseline, with primary data obtained through an online questionnaire answered by thirty-eight municipal EV managers. In the qualitative approach to analyze the context and assess the management capability of municipalities in two case studies, techniques adapted to the analysis of discursive practices were used. This was done through semi-structured interviews with managers of regional and municipal government, health workers and representatives of the municipal health council. The case studies showed that the municipality with enhanced management capability is that in which the manager has the greatest potential of using the resources of his position, in addition to his ability to control, negotiate and coordinate with other actors. Due to decentralization of EV, considering the shared nature of management between the three spheres of government, there is a marked variation in the management capability of municipalities, determined by social, economic, political inequalities and management mechanisms adopted.

Optimization of Large-Scale Hydrothermal System Operation

This paper presents the development of a mathematical model to optimize the management and operation of the Brazilian hydrothermal system. The system consists of a large set of individual hydropower plants and a set of aggregated thermal plants. The energy generated in the system is interconnected by a transmission network so it can be transmitted to centers of consumption throughout the country. The optimization model offered is capable of handling different types of constraints, such as interbasin water transfers, water supply for various purposes, and environmental requirements. Its overall objective is to produce energy to meet the country's demand at a minimum cost. Called HIDROTERM, the model integrates a database with basic hydrological and technical information to run the optimization model, and provides an interface to manage the input and output data. The optimization model uses the General Algebraic Modeling System (GAMS) package and can invoke different linear as well as nonlinear programming solvers. The optimization model was applied to the Brazilian hydrothermal system, one of the largest in the world. The system is divided into four subsystems with 127 active hydropower plants. Preliminary results under different scenarios of inflow, demand, and installed capacity demonstrate the efficiency and utility of the model. From this and other case studies in Brazil, the results indicate that the methodology developed is suitable to different applications, such as planning operation, capacity expansion, and operational rule studies, and trade-off analysis among multiple water users. DOI: 10.1061/(ASCE)WR.1943-5452.0000149. (C) 2012 American Society of Civil Engineers.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.