Trace elements in muscle of three fish species from Todos os Santos Bay,Bahia State,Brazil

In this study, an analysis was performed on the concentrations of the trace elements Al, As, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn in muscle of two carnivorous and one planktivorous fish species collected at Todos os Santos Bay (BTS). The accumulation order of the trace elements in Lutjanus analis was Al >Zn >Fe >Cr >Ba >Ni. In Cetengraulis edentulus, the order was Al >Fe >Zn >Cr >Ni >Mn >As. In the species Diapterus rhombeus, the order was Al >Fe >Zn >Cr >Ni >Mn >Cd. To determine the risk related to the consumption of fish, toxicity guidelines were used as standard references. It was observed that the species C. edentulus contained concentrations of As exceeding WHO limits, but these concentrations were acceptable according to the Agência Nacional de Vigilância Sanitária (ANVISA) guidelines. Cd levels were found only in D. rhombeus and in low concentrations according to the determinations of WHO and ANVISA. Pb levels were not detected in any of the three fish species. The analyzed elements did not differ statistically according to the species and feeding habits. The results point to possible risks of human contamination by As related to the consumption of the fish species C. edentulus from the BTS.     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

A Novel Formulation for Designing a Monitoring Strategy: Application to the Design of a River Quality Monitoring System

In this work, we propose a technique to automatically optimize the monitoring of any distributed indicator (concentration of a substance along a river, blood pressure of a patient over time, etc.) for which a reliable estimate is previously available. From a mathematical point of view, the problem is based on obtaining a reliable estimate of the chosen indicator (e.g., by numerical simulation), and then solving a multi-objective optimization problem (with mixed real and integer variables) whose solution must provide an efficient and satisfactory monitoring strategy. As an illustrative case, we show the steps to follow in order to implement that strategy when designing a system for monitoring water quality in a river. Finally, we present and analyze the results when applying the proposed technique to study a real case in the Neuse River (North Carolina, USA).