Several biomarker enzymes such as catalase (CAT) and glutathione S-transferase (GST) can be used to measure oxidative stress in animals caused by exposure to xenobiotics. The objective of the present study was to characterize different points of the Capivari (CP1 and CP2), Paraguaçu (PG1 and PG2) and Subaé (SB1 and SB2) Rivers, state of Bahia, in relation to the presence of xenobiotics, using CAT and GST as bioindicators in M. jelskii. The water-sampling sites were considered urban or rural and in all of them signs of environmental degradation were observed. Therefore, acute exposure tests (96h) were performed with water samples collected during the dry and rainy seasons. Results showed that the activity of CAT and GST in prawns exposed to water from CP1 and CP2 were very similar, while those exposed to water from PG1, PG2, SB1 and SB2 formed distinct groups of data. Significant increase in the activity of at least one of the analyzed enzymes in each sampling site was observed, when compared to animals in the control group. This demonstrated a possible oxidative stress in M. jelskii caused by the presence of xenobiotics in the water (e.g., domestic sewage, pesticides, oil, and heavy metals). Enzymatic activities were higher in animals from experiments carried out in the rainy season, except for the CAT activity of animals exposed to water from Subaé River. This study demonstrated the potential of M. jelskii as bioindicator and contributed to the knowledge of aspects of the antioxidant defense system of this species.
Combined sewer systems are often unable to respond adequately to rising water volumes draining from urban areas during rainfall events, resulting in frequent direct discharges into receiving waters and floods, with severe environmental and economic impacts. Despite stricter legislation on pollution control and flood risk assessment, there are still some challenges regarding the development of early warning systems based on water quality issues and fully integrated models. An innovative, real-time urban warning system for flooding and pollution events was built for the Alcântara basin (the largest in Lisbon), to provide timely information to wastewater management entities and to civil protection services. The platform provides real-time access to monitoring data and, based on 48-hour precipitation forecasts, predicts the performance of the system through the integrated use of mathematical models for both drainage network and estuary. Predictions are automatically compared and validated with on-line data. This paper presents the overall design of the system and main results obtained thus far. The analysis of the system shows the ability of the integrated models to represent the main spatial and temporal patterns observed, effectively predicting the system response to precipitation events and estimating volumes discharged into the water bodies and their average pollution loads. Furthermore, the overall results strongly indicate UV-Vis spectra to be reliable for TSS and COD estimation in sewer systems.
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