Surface water is frequently contaminated by the trace metals, in particular lead and zinc, produced by mining activities. The infiltration of this water is likely to pollute surface soils and ground water. The study of the transfer of trace elements, especially lead, under real conditions is difficult to carry out due to the physicochemical and hydrodynamic complexity of real soil (preferential flows, conditions of unsaturation...), of the presence of colloids and of many candidate elements. The objective of the present study was to gain a better understanding of the parameters influencing the migration processes of trace elements in simplified systems; it was based on the study of Pb transfer in laboratory columns filled with soil. The results showed that retention of lead in soil is strongly dependent on feed flow rate, particulate bed tortuosity, bed height, water-soil surface contact and volume of water. Increase in bed height, water-soil surface contact and particulate bed tortuosity leads to higher contact time thus higher lead retention by soil, whereas increase in feed flow rate and volume of water leads to lower contact time thus lower lead retention by soil.

Heavy metal pollution in sediments derived from the Deûle canal and sampled at different sites not far from a smelting plant has been examined in the present work in order to identify the sources of these metals and to assess the sediment environmental quality. The total concentrations of lead, zinc, cadmium, thallium, indium and tin in the samples were determined using inductively coupled plasma-atomic emission spectroscopy (ICP-AES). Our investigations have revealed that metal pollution is readily apparent in the studied sediments, with metals contents largely exceeding those measured in the background soils: maximum values are obtained for sediments collected near the industrial zone. The chemical forms of Pb, Zn, Cd, Tl, In and Sn in these sediments have also been studied using a sequential extraction method in order to evaluate their possible mobility, bioavailability and toxicity in this aquatic environment. Overall, the averaged fractionation of Pb and Zn is dominated, in a decreasing order, by the easily reducible, oxidizable and carbonate fractions. The importance of oxidizable phase (which is assumed to be composed mainly of organic matter and sulphides) in the Pb and Zn fractionations has been confirmed by the detection of X-ray diffraction peaks ascribed to galena (PbS) and wurtzite (ZnS) in contaminated sediment samples. Anthropogenic Tl, In, and Cd are mainly retained in Fe–Mn oxides/hydroxides, whereas anthropogenic Sn predominates in aluminosilicates/clays. We suspect that elevated percentage levels of Pb, Zn, Cd and In in the reducible fraction constitute a particular potential risk to this aquatic environment in case early diagenetic phenomena (that are observed in the sedimentary material) and physical disturbances (that occur in the water column) both take place strongly in the medium.

Suspended particulate matter is significantly related to the degradation of air quality in urban agglomerations, generating adverse health effects. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important in order to improve public awareness and air quality management. This study aims at developing models using multiple regression and neural network (NN) methods that might produce accurate 24-h predictions of daily average (DA) value of PM10 concentration and at comparatively assessing the above mentioned techniques. Pollution and meteorological data were collected in the urban area of Volos, a medium-sized coastal city in central Greece, whose population and industrialization is continuously increasing. Both models utilize five variables as inputs, which incorporate meteorology (difference between daily maximum and minimum hourly value of ground temperature and DA value of wind speed), persistency in PM10 levels and weekly and annual variation of PM10 concentration. The validation of the models revealed that NN model showed slightly better skills in forecasting PM10 concentrations, as the regression and the NN model can forecast 55 and 61% of the variance of the data, respectively. In addition, several statistical indexes were calculated in order to verify the quality and reliability of the developed models. The results showed that their skill scores are satisfying, presenting minor differences. It was also found that both are capable of predicting the exceedances of the limit value of 50 μg/m³ at a satisfactory level.

This study conducted a two-stage experiment. The first stage attempted to establish biostable filter beds. Two parameters, total bacterial count (TBC) and non-purgeable dissolved carbon (NPDOC), measured by passing through a 0.2 μm membrane filter, were selected to compare the difference of biostability of a filtration system with recirculation with different O₃-to-NPDOC ratios of filtered water. The excitation emission fluorescence matrix (EEFM) was used as an effective tool for understanding information regarding organic characteristics by comparing source filtered water before and after ozonation and the effluent during biostablizing filter. During the second stage, a biostable filter was used to compare differences in biodegradability of ozonated products sodium oxalate and sodium acetate. Experimental results demonstrate that both parameters, NPDOC removal and TBC, can be utilized to evaluate the biostabilty of a filter bed. With each parameter, a plateau was reached in roughly 20 days. The source water from Chen Ching Lake (CCL) contained a protein-like substance determined by the EEFM. This protein-like substance was also destroyed by O₃/NPDOC = 1.1. Soluble microbial products (SMPs) released from the biostablizing filter into the effluent have two peaks in the EEFM, identified as protein-like and humic-like acid. The NPDOC removal for the biostabilizing filter using O₃/NPDOC = 1.7 was less than that using O₃/NPDOC = 1.1. Bacterial counts in the effluent from the biostabilizing filter using O₃/NPDOC = 1.1 was better than that of O₃/NPDOC = 1.7. This difference can be explained by the high ratio of O₃/NPDOC producing by-products of ozonation that were easily utilized by microorganisms; however, filter bed also released relatively more SMPs owing to increased proliferation of microorganisms attached to glass pellets in the filter. Regarding the differences in decomposition of the by-products of ozonation by the biostable filter, such as sodium oxalate, the NPDOC removal at O₃/NPDOC = 1.1 was better than that at O₃/DOC = 1.7. This phenomenon can be explained as previously mentioned.

Field study at the Cervenohorske sedlo (1,013 m a.s.l.) (Hruby Jesenik Mountains, the Czech Republic, Central Europe) during 1999-2002 has been conducted in order to analyse the chemistry of rain/snow water using bulk and throughfall collector and fog/cloud water using modified passive Grunow collector. Fog water input to coniferous forest (Picea abies) was quantified using canopy balance method. For all samples pH, and the concentrations of [graphic removed] , Ca²⁺, K⁺, Mg²⁺, Na⁺, Cl-, [graphic removed] , and [graphic removed] were measured. The volume-weighted mean pH value varied from 4.92 to 5.43 in open bulk precipitation, from 4.30 to 4.71 in throughfall and from 4.66 to 5.23 in fog water. The fog droplets generally contain higher ion concentrations than rainwater. The related enrichment factors lie between 1.1 and 10.7 for the relevant species. The fog samples exhibit higher concentrations of [graphic removed] and [graphic removed] as compared to the bulk samples during 2000-2002. [graphic removed] are 5.7-10.7 times more concentrated in fog water and [graphic removed] are 3.4-7.2 times more concentrated in fog water. These differences may result from the height and characteristics of formation of the droplets. Based on canopy balance method, the annual fog water inputs were estimated to be 22 and 19% of rain and snow annual amounts in 1999 and 2000, respectively. For [graphic removed] , [graphic removed] , and [graphic removed] , the contribution of fog deposition in total (bulk + fog) deposition is estimated as 54, 47, and 42%, respectively.

Intermittent wastewater loading, a characteristic of aquaculture operations, undermines the usefulness of treatment wetlands designed using the steady state assumption. Being biological systems, the treatment variability of such wetlands must also be addressed during the design phase. A simulation-optimization model suitable for modeling intermittent pollutant releases and identifying optimal area and wastewater loading patterns for aquaculture operations is integrated with a decision-analytic framework to determine wetland area and release pattern under uncertainty and risk. Wetland area and release patterns corresponding to different decision making priorities were obtained by applying the minimax, maximax, Hurwicz and minimax regret criteria. The developed methodology provides a convenient framework for aquaculture operators and wetland design engineers to consider trade-off between the wetland size (an indicator of construction and opportunity costs) and wastewater loadings (an indicator of operation costs) during the design process. The results can also be used to characterize the risk-attitudes of the aquaculture operators and identify the worth of additional studies (i.e., pilot tests) given their risk-preferences.

This study qualifies and quantifies the effects of pH, hardness, alkalinity, salinity and bone calcination temperature related with the adsorption of As(V) onto biogenic hydroxyapatite (HAPb) obtained from cow-charred bones. Arsenic contamination of surface and subsurface waters is widely extended in Argentina. It is a problem of major concern, particularly in rural and suburban areas where there are not water treatment plants for supplying of drinking water. HAPb is a natural material, whose absorbent properties can be used for the design of low-cost technologies for As(V) abatement in water. In this work HAPb has been characterized by physical and chemical analysis (XRD, SEM, EDAX, BET, and electrophoretic mobility). A Plackett–Burman screening experimental design allowed us to determine the main variables affecting the efficiency of As(V) sorption onto HAPb. Based on these variables and with a design of higher order we developed a model of the system to study its behaviour. Data collection was planned through a Doehlert experimental design and a back propagation artificial neural network was used to work it out. Results showed that salinity is the major variable affecting the efficiency of the As(V) immobilization process but pH and hardness should be taken into account because of associations among them.

In this study critical load functions and target load functions of nitrogen and sulphur deposition with respect to acidity and minimum base cation to aluminium ratio were calculated with the SAFE model using three different averaging strategies: (1) averaging based on current forest generation, (2) averaging based on next generation and (3) averaging based on the entire simulation period. From the results it is evident that although target load calculation and indeed critical load calculation is straight forward, there is a problem in translating a predicted recovery according to the target load calculation back to a site-specific condition. We conclude that a policy strategy for emission reductions that ensures recovery, according to calculated target load functions, is likely to be beneficial from an ecosystem point of view. However, such a strategy may not be sufficient to achieve actual non-violation of the chemical criteria throughout the seasonal or rotational variations. To address this issue we propose a method for calculating dynamic critical loads which ensures that the chosen criteria is not violated.