Evidence of reproductive disturbance in Astyanax lacustris (Teleostei: Characiformes) from the Doce River after the collapse of the Fundão Dam in Mariana,Brazil

Environmental Science and Pollution Research - The Fundão Dam collapsed, on November 5th, 2015, dumping more than 50 million/m3 of iron ore tailings, enriched with metals, into the Doce River...     

Review: recent advances in biogas purifying technologies

Biomethane production through biogas upgrading is a promising renewable energy for some industries which could be part of the equilibrium needed with fossil fuels consumption to achieve a sustainable society. This paper presents a comprehensive list of biogas upgrading technologies focused on carbon dioxide removal as well as recent advances reported by researcher with wide expertise in this topic. Additionally, an extensive costs–performance comparison among the technologies studied is discussed. Among the different alternatives, chemical scrubbing stood out to achieve high biomethane purities while cryogenic technologies proved to be effective against methane losses. Regarding the different costs, water scrubbing and membrane separation seem to be the most affordable techniques.     

Some observations of the structure of the choroid plexus and its cysts

The structure of the choroid plexus was studied in five normal human embryos, three normal fetuses and three fetuses with choroid plexus cysts. These were detected by ultrasound and the fetuses were karyotypically normal. The choroid plexus appears in the lateral cerebral ventricles at the seventh developmental week. The early structure is lobulated with vessels running in the mesenchymal stroma and forming capillary nets under the single-layered ependymal epithelium. This embryonal structure is converted into the fetal type during the ninth developmental week as the embryonal capillary net is replaced by elongated loops of wavy capillaries that lie under regular longitudinal epithelial folds. The choroid plexus cysts exhibited accumulation of fluid within distended mesenchymal stroma and did not show the wavy folds on this surface, which was smooth. Within this connective tissue of the cyst wall were distended angiomatous interconnecting thin-walled capillaries. Therefore, filled cavities were not lined by any epithelium. We suggest that fetal choroid plexuses cysts (at least in many cases) are in fact pseudocysts exhibiting angiomatous patterns of capillaries in their walls. Copyright © 2002 John Wiley & Sons, Ltd.     

Assessment of environmental changes in the Orinoco River delta

Major anthropogenic driven changes in the hydrologic and sedimentation patterns of the Orinoco River have had an impact on environmental conditions in the delta. The abrupt water flow reduction from 3,600 to 200 m³ s^–1 in one of its major distributaries resulting from dam construction forced its transformation from a fresh-water body into a tidal channel with an increase in salinity level (as far as 100 km upstream) and with well-mixed water at the mouth and estuarine connection to the Paria Gulf. Three different sectors along this distributary can be identified (indicated by the Na/Cl ratio in the water). As a result, noticeable changes have occurred in the mangrove community which moved about 60 km further upstream. The changes have also promoted the formation of new islands of sediment progradation at the mouth of this distributary, where successional colonization and species replacement by different species of grasses and mangroves take place. Electronic Publication     

Ecosystem engineering by leaf-rolling mites enhances arthropod diversity

Bombardier beetles (Coleoptera, Carabidae, Brachininae) possess a remarkable defense mechanism where a hot chemical spray is released from the tip of their abdomen, with an audible explosive sound. To date, the repellent properties of these chemicals have been tested against a limited number of taxa, such as amphibians and insects. To investigate the impact of bombardier beetle defenses on avian predators, feeding trials were conducted using the bombardier beetle (Pheropsophus jessoensis) and the Japanese quail (Coturnix japonica), a sympatric and generalist predator. All naïve, hand-reared quail attacked live beetles, indicating the absence of an innate aversion to them. However, most of the quail rejected consuming the beetles whether or not the beetles sprayed them with chemicals. Naïve quail also rejected dead P. jessoensis individuals. These results support the recent hypothesis that it is not essential for P. jessoensis to spray noxious chemicals to deter predators. We also found that some of the quail exposed to live P. jessoensis remembered to avoid them for up to 5 weeks. Our results provide the first evidence of the repelling effects of bombardier beetle defense mechanisms on avian predators.

     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Arsenic speciation in human hair: a new perspective for epidemiological assessment in chronic arsenicism

The analysis for arsenic in hair is commonly used in epidemiological studies to assess exposure to this toxic element. However, poor correlation between total arsenic concentration in hair and water sources have been found in previous studies. Exclusive determination of endogenous arsenic in the hair, excluding external contamination has become an analytical challenge. Arsenic speciation in hair appears as a new possibility for analytical assessing in As-exposure studies. This study applied a relative simple method for arsenic speciation in human hair based on water extraction and HPLC-HG-ICP-MS. The concentration of arsenic species in human hair was assessed in chronically As(V)-exposed populations from two villages (Esqui?a and Illapata) of the Atacama Desert, Chile. The arsenic concentrations in drinking water are 0.075 and 1.25 mg L(-1), respectively, where As(V) represented between 92 and 99.5% of the total arsenic of the consumed waters. On average, the total arsenic concentrations in hair from individuals of Esqui?a and Illapata were 0.7 and 6.1 microg g(-1), respectively. Four arsenic species, As(III), DMA(V), MMA(V) and As(V), were detected and quantified in the hair extracts. Assuming the found species in extracts represent the species in hair, more than 98% of the total arsenic in hair corresponded to inorganic As. On average, As(III) concentrations in hair were 0.25 and 3.75 microg g(-1) in Esqui?a and Illapata, respectively; while, the As(V) average concentrations were 0.15 and 0.45 microg g(-1) in Esqui?a and Illapata, respectively. Methylated species represent less than 2% of the extracted As (DMA(V)+ MMA(V)) in both populations. As(III) in hair shows the best correlation with chronic exposure to As(V) in comparison to other species and total arsenic. In fact, concentrations of As(total), As(III) and As(V) in hair samples are correlated with the age of the exposed individuals from Illapata (R= 0.65, 0.69, 0.57, respectively) and with the time of residence in this village (R= 0.54, 0.71 and 0.58, respectively).     

Reduction of SO2 emissions by ammonia gas during unstaged combustion

The reduction of SO₂ by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH₃:SO₂ molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO₂ emissions was found at 40% excess air, at an NH₃:SO₂ molar ratio of 5.4. The onset of SO₂ reduction occurred at an NH₃:SO₂ ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO₂ reduction.It is difficult to determine how the SO₂ reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.