Occurrence and behavior of butyltins in intertidal and shallow subtidal surface sediments of an estuarine beach under different sampling conditions

Contamination by butyltin compounds (BTs) has been reported in estuarine environments worldwide, with serious impacts on the biota of these areas. Considering that BTs can be degraded by varying environmental conditions such as incident light and salinity, the short-term variations in such factors may lead to inaccurate estimates of BTs concentrations in nature. Therefore, the present study aimed to evaluate the possibility that measurements of BTs in estuarine sediments are influenced by different sampling conditions, including period of the day (day or night), tidal zone (intertidal or subtidal), and tides (high or low). The study area is located on the Brazilian southeastern coast, Sao Vicente Estuary, at Pescadores Beach, where BT contamination was previously detected. Three replicate samples of surface sediment were collected randomly in each combination of period of the day, tidal zone, and tide condition, from three subareas along the beach, totaling 72 samples. BTs were analyzed by GC-PFPD using a tin filter and a VF-5 column, by means of a validated method. The concentrations of tributyltin (TBT), dibutyltin (DBT), and monobutyltin (MBT) ranged from undetectable to 161 ng Sn g(-1) (d.w.). In most samples (71%), only MBT was quantifiable, whereas TBTs were measured in only 14, suggesting either an old contamination or rapid degradation processes. DBT was found in 27 samples, but could be quantified in only one. MBT concentrations did not differ significantly with time of day, zones, or tide conditions. DBT and TBT could not be compared under all these environmental conditions, because only a few samples were above the quantification limit. Pooled samples of TBT did not reveal any difference between day and night. These results indicated that, in assessing contamination by butyltin compounds, surface-sediment samples can be collected in any environmental conditions. However, the wide variation of BTs concentrations in the study area, i.e., over a very small geographic scale, illustrates the need for representative hierarchical and composite sampling designs that are compatible with the multiscalar temporal and spatial variability common to most marine systems. The use of such sampling designs will be necessary for future attempts to quantitatively evaluate and monitor the occurrence and impact of these compounds in nature

Carbon monoxide and related trace gases and aerosols over the Amazon Basin during the wet and dry seasons

We present the results of airborne measurements of carbon monoxide (CO) and aerosol particle number concentration (CN) made during the Balan double dagger o Atmosf,rico Regional de Carbono na Amazonia (BARCA) program. The primary goal of BARCA is to address the question of basin-scale sources and sinks of CO2 and other atmospheric carbon species, a central issue of the Large-scale Biosphere-Atmosphere (LBA) program. The experiment consisted of two aircraft campaigns during November-December 2008 (BARCA-A) and May-June 2009 (BARCA-B), which covered the altitude range from the surface up to about 4500 m, and spanned most of the Amazon Basin. Based on meteorological analysis and measurements of the tracer, SF6, we found that airmasses over the Amazon Basin during the late dry season (BARCA-A, November 2008) originated predominantly from the Southern Hemisphere, while during the late wet season (BARCA-B, May 2009) low-level airmasses were dominated by northern-hemispheric inflow and mid-tropospheric airmasses were of mixed origin. In BARCA-A we found strong influence of biomass burning emissions on the composition of the atmosphere over much of the Amazon Basin, with CO enhancements up to 300 ppb and CN concentrations approaching 10 000 cm(-3); the highest values were in the southern part of the Basin at altitudes of 1-3 km. The Delta CN/Delta CO ratios were diagnostic for biomass burning emissions, and were lower in aged than in fresh smoke. Fresh emissions indicated CO/CO2 and CN/CO emission ratios in good agreement with previous work, but our results also highlight the need to consider the residual smoldering combustion that takes place after the active flaming phase of deforestation fires. During the late wet season, in contrast, there was little evidence for a significant presence of biomass smoke. Low CN concentrations (300-500 cm(-3)) prevailed basinwide, and CO mixing ratios were enhanced by only similar to 10 ppb above the mixing line between Northern and Southern Hemisphere air. There was no detectable trend in CO with distance from the coast, but there was a small enhancement of CO in the boundary layer suggesting diffuse biogenic sources from photochemical degradation of biogenic volatile organic compounds or direct biological emission. Simulations of CO distributions during BARCA-A using a range of models yielded general agreement in spatial distribution and confirm the important contribution from biomass burning emissions, but the models evidence some systematic quantitative differences compared to observed CO concentrations. These mismatches appear to be related to problems with the accuracy of the global background fields, the role of vertical transport and biomass smoke injection height, the choice of model resolution, and reliability and temporal resolution of the emissions data base.

Investigating Smart Sampling as a population initialization method for Differential Evolution in continuous problems

Recently, researches have shown that the performance of metaheuristics can be affected by population initialization. Opposition-based Differential Evolution (ODE), Quasi-Oppositional Differential Evolution (QODE), and Uniform-Quasi-Opposition Differential Evolution (UQODE) are three state-of-the-art methods that improve the performance of the Differential Evolution algorithm based on population initialization and different search strategies. In a different approach to achieve similar results, this paper presents a technique to discover promising regions in a continuous search-space of an optimization problem. Using machine-learning techniques, the algorithm named Smart Sampling (SS) finds regions with high possibility of containing a global optimum. Next, a metaheuristic can be initialized inside each region to find that optimum. SS and DE were combined (originating the SSDE algorithm) to evaluate our approach, and experiments were conducted in the same set of benchmark functions used by ODE, QODE and UQODE authors. Results have shown that the total number of function evaluations required by DE to reach the global optimum can be significantly reduced and that the success rate improves if SS is employed first. Such results are also in consonance with results from the literature, stating the importance of an adequate starting population. Moreover, SS presents better efficacy to find initial populations of superior quality when compared to the other three algorithms that employ oppositional learning. Finally and most important, the SS performance in finding promising regions is independent of the employed metaheuristic with which SS is combined, making SS suitable to improve the performance of a large variety of optimization techniques. (C) 2012 Elsevier Inc. All rights reserved.

Decisions on Temporal Sampling Protocol Influence the Detection of Ecological Patterns

Within-site variability in species detectability is a problem common to many biodiversity assessments and can strongly bias the results. Such variability can be caused by many factors, including simple counting inaccuracies, which can be solved by increasing sample size, or by temporal changes in species behavior, meaning that the way the temporal sampling protocol is designed is also very important. Here we use the example of mist-netted tropical birds to determine how design decisions in the temporal sampling protocol can alter the data collected and how these changes might affect the detection of ecological patterns, such as the species-area relationship (SAR). Using data from almost 3400 birds captured from 21,000 net-hours at 31 sites in the Brazilian Atlantic Forest, we found that the magnitude of ecological trends remained fairly stable, but the probability of detecting statistically significant ecological patterns varied depending on sampling effort, time of day and season in which sampling was conducted. For example, more species were detected in the wet season, but the SAR was strongest in the dry season. We found that the temporal distribution of sampling effort was more important than its total amount, discovering that similar ecological results could have been obtained with one-third of the total effort, as long as each site had been equally sampled over 2 yr. We discuss that projects with the same sampling effort and spatial design, but with different temporal sampling protocol are likely to report different ecological patterns, which may ultimately lead to inappropriate conservation strategies.

Gases and volatile compounds associated with micro-organisms in blown pack spoilage of Brazilian vacuum-packed beef

This study correlated the composition of the spoilage bacterial flora with the main gaseous and volatile organic compounds (VOCs) found in the package headspace of spoiled, chilled, vacuum-packed meat. Fifteen chilled, vacuum-packed beef samples, suffering from blown pack spoilage, were studied using 16S rRNA clone sequencing. More than 50% of the bacteria were identified as lactic acid bacteria (LAB), followed by clostridia and enterobacteria. Fifty-one volatile compounds were detected in the spoiled samples. Although the major spoilage compounds were identified as alcohols and aldehydes, CO2 was identified as the major gas in the spoiled samples by headspace technique. Different species of bacteria contribute to different volatile compounds during meat spoilage. LAB played an important role in blown pack deterioration of the Brazilian beef studied.

Use of passive diffusion sampling method for defining NO2 concentrations gradient in São Paulo, Brazil

Abstract Background Air pollution in São Paulo is constantly being measured by the State of Sao Paulo Environmental Agency, however there is no information on the variation between places with different traffic densities. This study was intended to identify a gradient of exposure to traffic-related air pollution within different areas in São Paulo to provide information for future epidemiological studies. Methods We measured NO2 using Palmes' diffusion tubes in 36 sites on streets chosen to be representative of different road types and traffic densities in São Paulo in two one-week periods (July and August 2000). In each study period, two tubes were installed in each site, and two additional tubes were installed in 10 control sites. Results Average NO2 concentrations were related to traffic density, observed on the spot, to number of vehicles counted, and to traffic density strata defined by the city Traffic Engineering Company (CET). Average NO2concentrations were 63μg/m3 and 49μg/m3 in the first and second periods, respectively. Dividing the sites by the observed traffic density, we found: heavy traffic (n = 17): 64μg/m3 (95% CI: 59μg/m3 – 68μg/m3); local traffic (n = 16): 48μg/m3 (95% CI: 44μg/m3 – 52μg/m3) (p < 0.001). Conclusion The differences in NO2 levels between heavy and local traffic sites are large enough to suggest the use of a more refined classification of exposure in epidemiological studies in the city. Number of vehicles counted, traffic density observed on the spot and traffic density strata defined by the CET might be used as a proxy for traffic exposure in São Paulo when more accurate measurements are not available.

Emissão de gases de efeito estufa (GEE) pela pecuária: situação e perspectivas para criação de um mercado de crédito de carbono

O mercado mundial de carbono desenvolveu-se rapidamente com a ratificação do Protocolo de Quioto, sendo considerado como base para a implantação deste mercado. O objetivo do presente estudo foi analisar a situação e perspectivas da emissão de gases de efeito estufa (GEE) pela pecuária, e a possível criação de um mercado de crédito de carbono. Pelos dados levantados, pode-se afirmar que o Brasil tem um grande potencial para a criação deste mercado, por possuir o maior rebanho bovino comercial do mundo e importante participação na emissão de GEE, principalmente o metano. Com um horizonte de crescimento para o setor, a melhora da eficiência técnica e a utilização dos preceitos de sustentabilidade são fatores importantes para quem almeja um desenvolvimento sólido e sustentável.