Impact of water quality on bacterioplankton assemblage along Cértima River Basin (central western Portugal) assessed by PCR–DGGE and multivariate analysis

The information on bacterial community composition (BCC) in Portuguese water bodies is very scarce. Cértima River (central western Portugal) is known to have high levels of pollution, namely organic. In the present work, the BCC from a set of 16 water samples collected from Cértima River Basin and its main tributaries was characterized using 16S rDNA–denaturing gradient gel electrophoresis, a culture-independent molecular approach. Molecular data were related to environmental parameters through multivariate analysis to investigate potential impact of water pollution along the river. Principal component analysis using environmental data showed a water quality gradient from more pristine waters (at the mountain tributaries) to waters with increasingly eutrophic potential (such as Fermentelos Lake). This gradient was mainly defined by factors such as organic and inorganic nutrient sources, electrical conductivity, hydrogen carbonate concentration, and pH. Molecular results showed variations in BCC along Cértima River Basin but in the main river section, a Bacteroidetes phylotype (Flavobacterium sp.) proved to be dominant throughout the river course. Multivariate analysis suggests that spatial variation of BCC along the Cértima River Basin depended mainly on parameters such as Chl a, total suspended solid (TSS), total organic carbon, electrical conductivity, and HCO _boxclose^-_{3}^{-} levels. Bacteroidetes phylotypes were all related to higher electrical conductivity and HCO₃^-_{3}^{-} levels although some of these were also correlated with high SO₄^2-_{4}^{2-} and others with high soluble reactive phosphorus, nitrate, TN, and Kjeld-N levels. The Gammaproteobacteria occurrence was correlated with high SO₄^2-_{4}^{2-} levels. One of the Betaproteobacteria phylotypes showed to correlate with low redox potential (E_h) and high temperature, pH, TSS, and Chl a levels while another one showed a negative correlation with Chl a values.     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

Rate of occurrence of failures based on a nonhomogeneous Poisson process: an ozone analyzer case study

Atmospheric pollutant monitoring constitutes a primordial activity in public policies concerning air quality. In São Paulo State, Brazil, the São Paulo State Environment Company (CETESB) maintains an automatic network which continuously monitors CO, SO₂, NO _x , O₃, and particulate matter concentrations in the air. The monitoring process accuracy is a fundamental condition for the actions to be taken by CETESB. As one of the support systems, a preventive maintenance program for the different analyzers used is part of the data quality strategy. Knowledge of the behavior of analyzer failure times could help optimize the program. To achieve this goal, the failure times of an ozone analyzer—considered a repairable system—were modeled by means of the nonhomogeneous Poisson process. The rate of occurrence of failures (ROCOF) was estimated for the intervals 0–70,800 h and 0–88,320 h, in which six and seven failures were observed, respectively. The results showed that the ROCOF estimate is influenced by the choice of the observation period, t ₀?=?70,800 h and t ₇?=?88,320 h in the cases analyzed. Identification of preventive maintenance actions, mainly when parts replacement occurs in the last interval of observation, is highlighted, justifying the alteration in the behavior of the inter-arrival times. The performance of a follow-up on each analyzer is recommended in order to record the impact of the performed preventive maintenance program on the enhancement of its useful life.     

Metals in water, sediments, and biota of an offshore oil exploration area in the Potiguar Basin, Northeastern Brazil

Metal concentrations were evaluated in water, bottom sediments, and biota in four field campaigns from 2002 to 2004 in the Potiguar Basin, northeastern Brazil, where offshore oil exploration occurs. Analyses were performed by inductively coupled plasma mass spectrometry and inductively coupled plasma optical emission spectrometry. Total metal concentrations in water (dissolved?+?particulate) and sediments were in the range expected for coastal and oceanic areas. Abnormally high concentrations in waters were only found for Ba (80 μg?l^?1) and Mn (12 μg?l^?1) at the releasing point of one of the outfalls, and for the other metals, concentrations in water were found in stations closer to shore, suggesting continental inputs. In bottom sediments, only Fe and Mn showed abnormal concentrations closer to the effluent releasing point. Metal spatial distribution in shelf sediments showed the influence of the silt–clay fraction distribution, with deeper stations at the edge of the continental shelf, which are much richer in silt–clay fraction showing higher concentrations than shallower sediments typically dominated by carbonates. Metal concentrations in estuarine (mollusks and crustaceans) and marine (fish) organisms showed highest concentrations in oysters (Crassostrea rhizophorae). Fish tissues metal concentrations were similar between the continental shelf influenced by the oil exploration area and a control site. The results were within the range of concentrations reported for pristine environments without metals contamination. The global results suggest small, if any, alteration in metal concentrations due to the oil exploration activity in the Potiguar Basin. For monitoring purposes, the continental inputs and the distribution of the clay–silt fraction need to be taken into consideration for interpreting environmental monitoring results.     

Genotoxic effects of the herbicide Roundup® in the fish Corydoras paleatus (Jenyns 1842) after short-term, environmentally low concentration exposure

The glyphosate-based herbicide, Roundup^®, is one of the most used pesticides worldwide. In concert with the advent of transgenic crops resistant to glyphosate, the use of this pesticide has led to an increase in agricultural yields. The objective of this study was to evaluate the genotoxic effect that the herbicide Roundup^® (at a concentration of 6.67 μg/L, corresponding to 3.20 μg/L glyphosate) can have on the fish Corydoras paleatus. Treatment groups were exposed for 3, 6, and 9 days, and effects were analyzed using the piscine micronucleus test (PMT) and comet assay. A group subjected to filtered water only was used as a negative control. The PMT did not show differences between the control and exposed groups for any of the treatment times. In contrast, the comet assay showed a high rate of DNA damage in group exposed to Roundup^® for all treatment times, both for blood and hepatic cells. We conclude that for the low concentration used in this research, the herbicide shows potential genotoxic effects. Future research will be important in evaluating the effects of this substance, whose presence in the environment is ever-increasing.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

Principal response curves technique for the analysis of multivariate biomonitoring time series

Although chemical and biological monitoring is often used to evaluate the quality of surface waters for regulatory purposes and/or to evaluate environmental status and trends, the resulting biological and chemical data sets are large and difficult to evaluate. Multivariate techniques have long been used to analyse complex data sets. This paper discusses the methods currently in use and introduces the principal response curves method, which overcomes the problem of cluttered graphical results representation that is a great drawback of most conventional methods. To illustrate this, two example data sets are analysed using two ordination techniques, principal component analysis and principal response curves. Whereas PCA results in a difficult-to-interpret diagram, principal response curves related methods are able to show changes in community composition in a diagram that is easy to read. The principal response curves method is used to show trends over time with an internal reference (overall mean or reference year) or external reference (e.g. preferred water quality or reference site). Advantages and disadvantages of both methods are discussed and illustrated.