Metal contents of marine turtle eggs (Chelonia mydas; Lepidochelys olivacea) from the tropical eastern pacific and the implications for human health

Concentrations of eight elements were measured in Chelonia mydas and Lepidochelys olivacea eggs collected along the Pacific coast of Panama. Manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and mercury (Hg) concentrations were similar to previous reports of these species from around the world, while lead (Pb) was lower than previous reports. Cd posed the highest health risk to people who regularly eat the eggs, with average consumption rates leading to target hazard quotients (THQ) of up to 0.35 ± 0.15. Our conclusions indicate that current turtle egg consumption in isolated, coastal Pacific communities may pose a health concern for young children, and that youth and young adults should limit their consumption of turtle eggs to reduce their total intake of nonessential metals.     

Anoxic-aerobic treatment of the liquid fraction of cattle manure

Cattle manure from a dairy farm was treated in order to reduce its pollution potential. The manure came from a farm with 120 cows kept in stables in a free stall barn. As pretreatment, the manure is usually filtered on the farm using a screw press separator with a 0.5 mm mesh. Approximately 70% of the total filtered volume passes through the screen, thus constituting the liquid fraction. This fraction, with a composition of around 64,500 mg COD/l, 5770 mg total-N/l and 800 mg total-P/l, was subjected to centrifugation followed by a two-step biological treatment (anoxic-aerobic) to reduce organic matter (COD), nitrogen and phosphorus compounds. Centrifugation led to the following removal efficiencies: 35% total solids, 60% COD, 75% total phosphorus and 20% total nitrogen (mainly organic nitrogen). With the subsequent anoxic-aerobic treatment, average removal efficiencies of 85% for COD, 90% for total phosphorus and 75% for total nitrogen were achieved.     

Diel cycles of arsenic speciation due to photooxidation in acid mine drainage from the Iberian Pyrite Belt (Sw Spain)

Twenty four hours diel cycles of arsenic speciation in Acid Mine Drainage (AMD) due to photooxidation have been reported for the first time. AMD samples were taken during 48 h (31st March and 1st April, 2005) at 6 h intervals from the effluent of a massive abandoned polymetallic sulphide mine of the Iberian Pyrite Belt (Sw Spain). Samples were preserved in situ using cationic exchange prior to analysis by coupled high performance liquid chromatography, hydride generation and atomic fluorescence spectrometry (HPLC-HG-AFS) for arsenic speciation. The results indicated the presence of inorganic arsenic species with daily means of 262mugl(-1) for As(V) and 107 microg l(-1) for As(III). No marked diel trend was observed for As(V). However, a marked diel trend was observed for As(III) in the two studied days, with maximum concentrations during nighttime (141-143 microg l(-1)) and minimum concentrations at daytime (72-77 microg l(-1)). This difference in concentration during daytime and nighttime is ca. 100%. A similar diel cycle was observed for iron. An explanation for the arsenic diel cycles observed is the light induced photooxidation of As(III) and the elimination of As(V) due to its adsorption onto Fe precipitates during the daytime. Furthermore, the diel changes in arsenic speciation emphasize the importance of designing suitable sampling strategies in AMD systems.     

Photocatalytic reduction of carbon dioxide over Cu/TiO<Subscript>2</Subscript> photocatalysts

The photocatalytic reduction of CO₂ with H₂O was investigated using Cu/TiO₂ photocatalysts in aqueous solution. For this purpose, Cu/TiO₂ photocatalysts (with 0.2, 0.9, 2, 4, and 6 wt.% of Cu) have been synthesized via sol-gel method. The photocatalysts were extensively characterized by means of inductively coupled plasma optical emission spectrometry (ICP-OES), N₂ physisorption (BET), XRD, UV-vis DRS, FT-IR, Raman spectroscopy, TEM-EDX, and photoelectrochemical measurements. The as-prepared photocatalysts contain anatase as a major crystalline phase with a crystallite size around 13 nm. By increasing the amount of Cu, specific surface area and band gap energy decreased in addition to the formation of large agglomeration of CuO. Results revealed that the photocatalytic reduction of CO₂ decreased in the presence of Cu/TiO₂ in comparison to pure TiO₂, which might be associated to the formation of CuO phase acting as a recombination center of generated electron-hole pair. Decreasing of photoactivity can also be connected with a very low position of conduction band of photocatalysts with high Cu content, which makes H₂ production necessary for CO₂ reduction more difficult.     

Elemental and isotopic determination of lead (Pb) in particulate matter in the Brazilian city of Goiânia (GO) using ICP-MS technique

Environmental Science and Pollution Research - The toxic metal lead (Pb) can be harmful to human health in various manners, but is also considered as a distinguished tracer of environmental...     

Effect of ferrate on green algae removal

Green algae Cladophora aegagropila, present in cooling water of thermal power plants, causes many problems and complications, especially during summer. However, algae and its metabolites are rarely eliminated by common removal methods. In this work, the elimination efficiency of electrochemically prepared potassium ferrate(VI) on algae from cooling water was investigated. The influence of experimental parameters, such as Fe(VI) dosage, application time, pH of the system, temperature and hydrodynamics of the solution on removal efficiency, was optimized. This study demonstrates that algae C. aegagropila can be effectively removed from cooling water by ferrate. Application of ferrate(VI) at the optimized dosage and under the suitable conditions (temperature, pH) leads to 100% removal of green algae Cladophora from the system. Environmentally friendly reduction products (Fe(III)) and coagulation properties favour the application of ferrate for the treatment of water contaminated with studied microorganisms compared to other methods such as chlorination and use of permanganate, where harmful products are produced.

     

Composition and quantification of the anthropogenic and natural fractions of wastes collected from the stormwater drainage system for discussions about the waste management and people behavior

A study was made of the composition of wastes collected from the pipes of the stormwater drainage system of Sorocaba, SP, Brazil (600 thousand inhabitants). A total of 10 samples weighing at least 100 kg each were sorted into 19 items to determine the fraction that can be considered natural (earth/sand, stones, organic matter, and water, the latter determined after oven-drying the samples) and the anthropogenic fraction (the remaining 15 items, especially construction and demolition wastes and packaging). Soil/sand was found to be the main item collected (52.5 % dry weight), followed by the water soaked into the waste (24.3 %), which meant that all the other wastes were saturated in mud, whose contents varied from 6.4 % (glass) to 87.2 % (metalized plastics packaging). In general, 83 % of the collected wastes can be classified as “natural,” but the remaining 17 % represent 2,000 kg of the most varied types of wastes discarded improperly every day on the streets of the city. This is an alarming amount of wastes that may clog parts of the drainage systems, causing troubles for all the population (like flooding) and must be strongly considered in municipal solid wastes management and in environmental education programs.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.