Modelling Phosphorus Retention in Lakes and Reservoirs

Steady-state models for the prediction of P retention coefficient (R) in lakes were evaluated using data from 93 natural lakes and 119 reservoirs situated in the temperate zone. Most of the already existing models predicted R relatively successfully in lakes while it was seriously under-estimated in reservoirs. A statistical analysis indicated the main causes of differences in R between lakes and reservoirs: (a) distinct relationships between P sedimentation coefficient, depth, and water residence time; (b) existence of significant inflow–outflow P concentration gradients in reservoirs. Two new models of different complexity were developed for estimating R in reservoirs: , where τ is water residence time (year), was derived from the Vollenweider/Larsen and Mercier model by adding a calibrated parameter accounting for spatial P non-homogeneity in the water body, and is applicable for reservoirs but not lakes, and , where [P_in] is volume-weighted P concentration in all inputs to the water body (μg l⁻¹), was obtained by re-calibrating the OECD general equation, and is generally applicable for both lakes and reservoirs. These optimised models yield unbiased estimates over a large range of reservoir types.     

Effect of Cadmium on Microbial Activity and a Ryegrass Crop in Two Semiarid Soils

Soil pollution with Cd is an environmental problem common in the world, and it is necessary to establish what Cd concentrations in soil could be dangerous to its fertility from toxicity effects and the risk of transference of this element to plants and other organisms of the food chain. In this study, we assessed Cd toxicity on soil microorganisms and plants in two semiarid soils (uncultivated and cultivated). Soil ATP content, dehydrogenase activity, and plant growth were measured in the two soils spiked with concentrations ranging from 3 to 8000 mg Cd/kg soil and incubated for 3 h, 20 days, and 60 days. The Cd concentrations that produced 5%; 10%;, and 50%; inhibition of each of the two soil microbiological parameter studied (ecological dose, ED, values) were calculated using two different mathematical models. Also, the effect of Cd concentration on plant growth of ryegrass (Lolium perenne, L.) was studied in the two soils. The Cd ED values calculated for soil dehydrogenase activity and ATP content were higher in the agricultural soils than in the bare soil. For ATP inhibition, higher ED values were calculated than for dehydrogenase activity inhibition. The average yields of ryegrass were reduced from 5.03 to 3.56 g in abandoned soil and from 4.21 to 1.15 g in agricultural soil with increasing concentrations of Cd in the soil. Plant growth was totally inhibited in abandoned and agricultural soils at Cd concentrations above 2000 and 5000 mg/kg soil, respectively. There was a positive correlation between the concentration of Cd in the plants and the total or DTPA-extractable concentrations of Cd in the soil.     

Spatiotemporal evolution of soil pH and zinc after the Aznalcollar mine spill

The residual pollution after the Aznalcóllar (southwestern Spain) pyrite mine spill is still a threat due to the continuing oxidation of sulfuric minerals. The objective of this paper was to analyze the combined effect of pyrite oxidation, sugar beet foam applications, and meteorological conditions on the spatiotemporal evolution of the pH and EDTA-extractable Zn concentration, using non co-located data from 11 sampling dates between June 1999 and March 2002. Median pH values ranged from 4.4 at the beginning of the monitoring period to 7.6 at the end, although values near 2.5 were observed throughout the entire period, despite of two sugar beet foam (SBF) applications. Zinc distributions were positively skewed and median concentrations ranged from 17 to 94 mg kg(-1). The inverse relationship between pH and Zn became weaker toward the end of the monitoring period as a consequence of the precipitation and posterior dissolution of newly formed minerals from the reaction products of the pyrite oxidation. Normal score maps showed that after the SBF applications only 0.5% of the monitored area was below the pH = 4 threshold, while on other dates up to one-third of the area remained below this value. The better performance of the second SBF application could be explained in terms of pyrite oxidation pathways and environmental conditions. From this analysis, with data obtained under uncontrolled field conditions, it is concluded that SBF should be applied before or during the wet and cold season to alleviate acidification, caused by the oxidation of pyrite or other sulfuric minerals.     

Larvicidal and pupicidal activities of eco-friendly phenolic lipid products from Anacardium occidentale nutshell against arbovirus vectors

Environmental Science and Pollution Research - Aedes aegypti and Culex quinquefasciatus are vectors of diseases that constitute public health problems. The discovery of products capable of...     

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.     

Binding of polycyclic aromatic hydrocarbons by humic acids formed during composting

Binding of two model polycyclic aromatic hydrocarbons (PAHs), phenanthrene and pyrene, by humic acids (HAs) isolated from an organic substrate at different stages of composting and a soil was investigated using a batch fluorescence quenching method and the modified Freundlich model. With respect to soil HA, the organic substrate HA fractions were characterized by larger binding affinities for both phenanthrene and pyrene. Further, isotherm deviation from linearity was larger for soil HA than for organic substrate HAs, indicating a larger heterogeneity of binding sites in the former. The composting process decreased the binding affinity and increased the heterogeneity of binding sites of HAs. The changes undergone by the HA fraction during composting may be expected to contribute to facilitate microbial accessibility to PAHs. The results obtained also suggest that bioremediation of PAH-contaminated soils with matured compost, rather than with fresh organic amendments, may result in faster and more effective cleanup.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

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.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).