Shipboard bilge water treatment by electrocoagulation powered by microbial fuel cells

Reveals the synergy between microbial fuel cells and electrocoagulation. Demonstrates MFC-ECC shipboard wastewater treatment is advantageous. MFC-ECC integration enables energy neutral bilge water treatment. Ships generate large amounts of wastewater including oily bilge water, blackwater and greywater. Traditionally they are treated separately with high energy consumption. In this study we demonstrate the feasibility that these waste streams can be treated using an integrated electrocoagulation cell (ECC) and microbial fuel cell (MFC) process, which not only synergized the contaminants removal but also accomplished energy neutrality by directly powering EC with MFC electricity. Results showed that MFC stack powered ECC removed 93% of oily organics, which is comparable to the performance of an external DC voltage powered ECC. In the meantime, more than 80% of COD was removed from MFCs when fed with either acetate or municipal wastewater. Moreover, the ECC electrode area and distance showed notable effects on current generation and contaminants removal, and further studies should focus on operation optimization to enhance treatment efficiency.     

Use of the digestive gland of the oyster Crassostrea rhizophorae (Guilding, 1828) as a bioindicator of Zn,Cd and Cu contamination in estuarine sediments (south-east Brazil)

This study demonstrates the accumulation of Zn, Cd and Cu in the digestive gland of the oyster Crassostrea rhizophorae in response to the contamination of sediments and discusses the potential use of this specific organ in monitoring metal contamination in tropical areas. Sediment and oyster samples were collected from coastal Rio de Janeiro sites with different levels of human impact: Sepetiba Bay, Guanabara Bay and the Paraty coast. Metal concentrations were measured using inductively coupled plasma optical emission spectrometry (ICP OES). Significant statistical differences (p<0.001; p<0.05) were observed for Zn and Cd concentrations in the digestive gland; the highest Zn concentrations were found at Sepetiba, followed by Guanabara and Paraty. The highest digestive gland Cd concentrations were found at Paraty, followed by Sepetiba and Guanabara. These concentrations were proportional to those found in the sediments. There was no significant difference (p>0.05) in Cu among the sampling sites. The highest digestive-gland Cu concentration was also found at Sepetiba, followed by Guanabara. The biosediment accumulation factor indicated a gradient of sediment contamination for Zn and Cd. The digestive gland of C. rhizophorae can be a potential indicator of trace metal contamination in sediments from tropical estuarine environments.     

Woody plant richness and NDVI response to drought events in Catalonian (northeastern Spain) forests

The role of species diversity on ecosystem resistance in the face of strong environmental fluctuations has been addressed from both theoretical and experimental viewpoints to reveal a variety of positive and negative relationships. Here we explore empirically the relationship between the richness of forest woody species and canopy resistance to extreme drought episodes. We compare richness data from an extensive forest inventory to a temporal series of satellite imagery that estimated drought impact on forest canopy as NDVI (normalized difference vegetation index) anomalies of the dry summer in 2003 in relation to records of previous years. We considered five different types of forests that are representative of the main climatic and altitudinal gradients of the region, ranging from lowland Mediterranean to mountain boreal-temperate climates. The observed relationship differed among forest types and interacted with the climate, summarised by the Thorntwaite index. In Mediterranean Pinus halepensis forests, NDVI decreased during the drought. This decrease was stronger in forests with lower richness. In Mediterranean evergreen forests of Quercus ilex, drought did not result in an overall NDVI loss, but lower NDVI values were observed in drier localities with lower richness, and in more moist localities with higher number of species. In mountain Pinus sylvestris forests NDVI decreased, mostly due to the drought impact on drier localities, while no relation to species richness was observed. In moist Fagus sylvatica forests, NDVI only decreased in plots with high richness. No effect of drought was observed in the high mountain Pinus uncinata forests. Our results show that a shift on the diversity-stability relationship appears across the regional, climatic gradient. A positive relationship appears in drier localities, supporting a null model where the probability of finding a species able to cope with drier conditions increases with the number of species. However, in more moist localities we hypothesize that the proportion of drought-sensitive species would increase in richer localities, due to a higher likelihood of co-occurrence of species that share moist climatic requirements. The study points to the convenience of considering the causes of disturbance in relation to current environmental gradients and historical environmental constraints on the community.     

A global evaluation of metabolic theory as an explanation for terrestrial species richness gradients

We compiled 46 broadscale data sets of species richness for a wide range of terrestrial plant, invertebrate, and ectothermic vertebrate groups in all parts of the world to test the ability of metabolic theory to account for observed diversity gradients. The theory makes two related predictions: (1) In-transformed richness is linearly associated with a linear, inverse transformation of annual temperature, and (2) the slope of the relationship is near -0.65. Of the 46 data sets, 14 had no significant relationship; of the remaining 32, nine were linear, meeting prediction 1. Model I (ordinary least squares, OLS) and model II (reduced major axis, RMA) regressions then tested the linear slopes against prediction 2. In the 23 data sets having nonlinear relationships between richness and temperature, split-line regression divided the data into linear components, and regressions were done on each component to test prediction 2 for subsets of the data. Of the 46 data sets analyzed in their entirety using OLS regression, one was consistent with metabolic theory (meeting both predictions), and one was possibly consistent. Using RMA regression, no data sets were consistent. Of 67 analyses of prediction 2 using OLS regression on all linear data sets and subsets, two were consistent with the prediction, and four were possibly consistent. Using RMA regression, one was consistent (albeit weakly), and four were possibly consistent. We also found that the relationship between richness and temperature is both taxonomically and geographically conditional, and there is no evidence for a universal response of diversity to temperature. Meta-analyses confirmed significant heterogeneity in slopes among data sets, and the combined slopes across studies were significantly lower than the range of slopes predicted by metabolic theory based on both OLS and RMA regressions. We conclude that metabolic theory, as currently formulated, is a poor predictor of observed diversity gradients in most terrestrial systems.     

Algae turf scrubber and vertical constructed wetlands combined system for decentralized secondary wastewater treatment

Environmental Science and Pollution Research - Water shortage is a current problem faced by many regions. The deterioration of water bodies driven by the directly discard of untreated wastewater...     

Development of the Diatom Ecological Quality Index (DEQI) for peri-urban mountain streams in the Basin of Mexico

Environmental Science and Pollution Research - In the Basin of Mexico, one of the most important economic regions in the country with over 22 million inhabitants, peri-urban streams have been...     

Tradescantia pallida cv. purpurea boom in the characterization of air pollution by accumulation of trace elements

Tradescantia pallida cv. purpurea, a plant species widely employed for ornamentation in Brazil, has been successfully used for monitoring the genotoxicity of various agents by the micronucleus assay. To amplify knowledge about its suitability as a bioindicator species, its capacity for accumulating trace elements from urban air pollution was evaluated. T. pallida was rooted using standardized soil, and the vases were distributed in two highly polluted sites of the urban area of S?o Paulo, Brazil (Cerqueira Cesar and Congonhas districts), and in one unpolluted control site situated approximately 50 km from downtown S?o Paulo (in Caucaia do Alto). Approximately six months after exposure to pollutants, adult leaves of this plant were collected monthly for 12 months. The leaves were washed with deionized water, dried, and ground for analyses. Characterization of element levels was carried out by neutron activation analysis. Powdered samples and standards were irradiated at the IEA-R1 nuclear reactor for short and long periods, and concentrations of As, Ba, Br, Ca, Ce, Cl, Cr, Co, Fe, K, La, Mn, Na, Rb, Sb, Sc, Sr, Th, and Zn were determined. Analysis of variance applied to the results indicated that samples from polluted sites present the highest concentrations of Ba, Ce, Cr, Co, Fe, La, Sb, and Sc (p < 0.05). Discriminant analysis revealed that it was possible to distinguish the two polluted areas with a precision of 97.5%, based on the amount of pollutant elements measured in the plants at each site. The results indicated the potential use of T. pallida as an accumulator plant for air pollution biomonitoring.     

Assessing the effects of pseudo-absences on predictive distribution model performance

Modelling species distributions with presence data from atlases, museum collections and databases is challenging. In this paper, we compare seven procedures to generate pseudo-absence data, which in turn are used to generate GLM-logistic regressed models when reliable absence data are not available. We use pseudo-absences selected randomly or by means of presence-only methods (ENFA and MDE) to model the distribution of a threatened endemic Iberian moth species (Graellsia isabelae). The results show that the pseudo-absence selection method greatly influences the percentage of explained variability, the scores of the accuracy measures and, most importantly, the degree of constraint in the distribution estimated. As we extract pseudo-absences from environmental regions further from the optimum established by presence data, the models generated obtain better accuracy scores, and over-prediction increases. When variables other than environmental ones influence the distribution of the species (i.e., non-equilibrium state) and precise information on absences is non-existent, the random selection of pseudo-absences or their selection from environmental localities similar to those of species presence data generates the most constrained predictive distribution maps, because pseudo-absences can be located within environmentally suitable areas. This study shows that if we do not have reliable absence data, the method of pseudo-absence selection strongly conditions the obtained model, generating different model predictions in the gradient between potential and realized distributions.