Technical, financial and location criteria for the design of land application system treatment

Conventional water treatments when downsized to cover the demands of small and scattered populations are costly and ineffective. In fact, many small towns cannot afford the high average treatment costs nor provide the skill and complex management requirements. Even when these facilities are available, waste water might not be properly treated. Land application system treatments (LAST) have been shown to be preferable on the basis of their technical effectiveness and financial viability. The recently approved Spanish regulations (RDL 1620/2007, pp 50369–50661) represent an opportunity for the implementation of well-designed LASTs. This paper presents an assessment methodology for the design of LASTs by combining technical, financial and location criteria. The method is applied to the design of LASTs to cover the water disposal demand of twelve municipalities located within the protected natural landscape, and surrounding areas of ‘El Rebollar’, Salamanca, Spain.     

Building a 3D geomodel for water resources management: case study in the Regional Park of the lower courses of Manzanares and Jarama Rivers (Madrid, Spain)

Water resources management of protected sites requires a powerful tool to analyze the process and changes that are occurring in the environment. This paper describes a 3D geomodel design of the Jarama River Detrital Aquifer located in Madrid (Spain). That hydrogeological unit is included in the “Parque Regional de los Cursos Bajos de los Ríos Manzanares y Jarama” (Regional Park of the Lower Courses of Manzanares and Jarama Rivers). The goal of this work is to define a method by which a three-dimensional (3D) model can be created with hydrogeologic geometry real of main aquifer, to accomplish an adequate management of the groundwater resources. All data used in this study were integrated in a geographic database: geological and hydrogeological information, geological map (1:25,000), eleven cross-sections, piezometric maps and a digital elevation model. The constructed 3D model of the Jarama Aquifer shows geometric features and spatial distribution and variations of geologic units. Thus, the 3D model allows the assessment of volumes of each unit, the depth and thickness variations of the main aquifer, and the spatial and temporal variations of water tables. From the 3D model, the most suitable areas (in terms of groundwater protection) for managed recharge and mining works have been identified.     

Quick sulfide buffering in inner shelf sediments of the East China Sea impacted by eutrophication

In the eutrophic coastal ocean, quick formation of iron (Fe) sulfide is environmentally important to effectively prevent accumulation of dissolved sulfide and its detrimental effects on the benthic ecosystem. In this study, 0.5 N HCl-extractable labile Fe (LFe), acid volatile sulfide, and pyrite in the East China Sea inner shelf sediments were examined to investigate the mechanisms of quick sequestration of dissolved sulfide and potential impacts of frequent algal blooms on the capacity of quick sulfide-buffering in eutrophic coastal areas of the large-sized continental shelf subject to massive terrestrial input. The results indicate that sulfate reduction has been competitively suppressed by dissimilatory Fe reduction due to limited availability of labile organic matter. Dissolved sulfide can be quickly buffered by reaction with LFe and, therefore, is difficult to accumulate to a high level. The quick sulfide-buffering capacity has not become exhausted partly because of the formation of un-sulfidized LFe(II) via dissimilatory reduction of less reactive Fe oxides. It is expected that dissolved sulfide will not pose detrimental effects on the benthic ecosystem in the near future if the current biogeochemical/ecological state remains.     

Iron ore mining promotes iron enrichment in sediments of the Gualaxo do Norte River basin,Minas Gerais State,Brazil

The objective of the present study is to assess the influence of iron ore mining on Fe concentrations in fluvial sediments of the Gualaxo do Norte River basin (Minas Gerais State, Brazil). Initially background values were determined for Fe by means of the boxplot representation, the iterative 2σ technique and the calculated distribution function, using geochemical data obtained for alluvial terraces. Geochronologic analyses in carbonaceous materials attested for the proposed background values. After that, chemical analyses of active drainage sediments collected along the entire basin were carried out and a geochemical map of the study area was prepared. The mean background value for Fe is relatively high (8.2 wt %), when compared to the Fe concentration in the Earth’s crust (5.6 wt %). Such background value is strongly associated with the geological characteristics of the region. It was observed that most of the high Fe concentrations were detected in active sediments collected in the main river of the basin and not in its tributaries. This suggests that Fe enrichment is not only linked to the local geology but also to possible increase resulting from accidental leakage of iron ore mining tailings from containment dams and lakes upstream. It is suggested that measures that help stop or minimize such impact be adopted. The large capacity of Fe to adsorb and form complexes with toxic metals implicates in environmental hazards that may not be restricted only to the Gualaxo do Norte river basin, but may affect the other basins downstream.     

Magnetic susceptibility and electrical conductivity as a proxy for evaluating soil contaminated with arsenic,cadmium and lead in a metallurgical area in the San Luis Potosi State,Mexico

A total of 113 samples of waste and soil were collected from a site in the state of San Luis Potosi, Mexico, that was occupied for several years by the metallurgical industry. Specific magnetic susceptibility (MS), electrical conductivity (EC) and pH were determined, as well as the total and available concentrations of potentially toxic elements (PTEs) such as As, Cd, Cu, Fe, Pb and Zn, which may cause a health risk for humans, animals and ecosystems, and the concentrations of major ions in aqueous extracts of soils and wastes. The solid phases of the samples were also characterized. The results revealed that the soils and wastes exhibited elevated values of PTEs, MS and EC. For soils these values decreased with increasing distance from the waste storage sites. The MS values were elevated primarily due to the presence of Fe-oxyhydroxides, such as magnetite, hematite and goethite, which contain PTEs in their structure leading to a high correlation between the value of MS and the As, Cd, Fe and Pb contents (r = 0.57–0.91) as well as between the PTEs values (r = 0.68–0.92). The elevated EC values measured in the metallurgical wastes were the result of presence of the sulfate minerals of Ca, Mg and Fe. The pollution index, which indicates the levels of simultaneous toxicity from elements such as As, Cd and Pb, was determined, with extreme hazard zones corresponding to areas that exhibit high MS values (0.91 correlation). In conclusion, MS measurements can be used as an indirect indicator to evaluate the PTE contamination in metallurgical areas, and EC measurements can aid in the identification of pollution sources.     

Spatial evaluation of phosphorus retention in riparian zones using remote sensing data

Riparian zones act as important buffer zones for non-point source pollution, thus improving the health of aquatic ecosystems. Previous research has shown that riparian zones play an important role, and that land use has an important effect, on phosphorus (P) retention. A spatial basin-scale approach for analyzing P retention and land use effects could be important in preventing pollution in riparian zones. In this study, a riparian phosphorus cycle model based on EcoHAT was generated with algorithms from soil moisture and heat models, simplified soil and plant phosphorus models, plant growth models, and universal soil loss equations. Based on remote sensing data, model performance was enhanced for spatial and temporal prediction of P retention in the riparian zone. A modified soil and plant P model was used to simulate the soil P cycle of a riparian zone in a temperate continental monsoon climate in northern China. A laboratory experiment and a field experiment were conducted to validate the P cycle model. High coefficients of determination (R ²) between simulated and observed values indicate that the model provides reliable results. P uptake variations were the same as the net primary productivity (NPP) trends, which were affected by soil temperature and moisture in the temperate continental monsoon climate. Beginning in June, the monthly content increased, with the maximum appearing in August, when the most precipitation and the highest temperatures occur. The spatial distribution of P uptake rates from March to September showed that areas near water frequently had relatively high values from May to August, which is contrary to results obtained in March, April, and September. The P uptake amounts for different land uses changed according to expectation. The average monthly P uptake rates for farmlands and grasslands were more than those for orchards and lowlands, which had moderate P uptake rates, followed by shrubs and forests. The spatial distribution of soil erosion demonstrated that the soil erosion came primarily from high-intensity agricultural land in the western and central areas, while the northern and eastern study regions, which were less affected by human activity, experienced relatively slight soil erosion. From the point of view of P pollution prevention, the spatial structure of riparian zones and the spatial distribution of land use around the Guanting reservoir are thus not favorable.     

Salt and nitrate exports from the sprinkler-irrigated Malfarás creek watershed (Ebro river valley,Spain) during 2010

Irrigated agriculture is a clear source of non-point pollution by salts and nitrogen species. The impact of such pollution should be quantified according to specific cases. The case of the Malfarás creek basin, a sprinkler irrigation district located in the semiarid Ebro valley in northeast Spain, has been evaluated. The main crops in the district were corn, barley and alfalfa, occupying 93 % of the irrigated area. The fate of water, salts and nutrients was evaluated by a daily water balance developed at a field scale for the natural year 2010. The yearly data of the whole set of 101 irrigated fields plus the non-irrigated area compared to the measured drainage produced a basin water balance with a low degree of error. The basin consumed 90 % of the total water input of which 68 % was used for crop evapotranspiration and the rest was lost due to non-productive uses. 16 % of the incoming water left the irrigation area as drainage water. The irrigated area was responsible for 87 % of the drainage. The average volume of drained water was 152 mm year^?1 for the whole basin area. The irrigated area drained 183 mm year^?1. The basin exported 473 kg of salt per hectare during 2010. This value was the lowest of the sprinkler irrigation areas in the Ebro valley, mainly due to the lower soil salinity. All the crops except barley received a nitrogen surplus of 10–50 % above their needs. The extra nitrogen entered the water cycle increasing the nitrate concentration in the aquifer water (150 mg L^?1) and drainage water (98 mg L^?1). In 2010 the mass of nitrogen exported by drainage was 49 kg per irrigated hectare. This value is too high for this type of irrigation system and implies that 17 % of nitrogen applied as a fertilizer was lost to drainage water. The key to decreasing the nitrogen leaching and pollution that it causes could be appropriate time-controlled fertigation along with better irrigation scheduling.     

Sandstone alterations triggered by fire-related temperatures

The aim of the study was to identify and describe changes in two different sandstone types when undergoing different environmental and extreme temperature regimes to assess the possibility of finding insolation weathering and how these sandstones would behave during and after a fire. The first step was the simulation in the laboratory of temperature regimes up to 60 °C which would correspond to extreme events that could be found in insolation cycles even in Central Europe and the second one was the temperature above 200 °C simulating in laboratory conditions the thermal regime of a potential fire situation at temperatures up to 200, 400, 600 and 800 °C. Heating the samples above 400 °C led to gradual changes in mineral composition, colour, surface roughness and physical properties reaching, eventually, total rock breakdown through spalling and granular disaggregation. The different behaviour of sandstones exposed to high temperatures is mainly caused by their different mineral composition with various ratios of minerals that are more or less chemically stable at high temperatures as well as by the differences in the porosity.     

Hybrid Model for Urban Air Pollution Forecasting: A Stochastic Spatio-Temporal Approach

Air pollution is usually driven by a complex combination of factors in which meteorology, physical obstacles, and interactions between pollutants play significant roles. Considering the characteristics of urban atmospheric pollution and its consequent impacts on human health and quality of life, forecasting models have emerged as an effective tool to identify and forecast air pollution episodes. The overall objective of the present work is to produce forecasts of pollutant concentrations with high spatio-temporal resolution and to quantify the uncertainty in those forecasts. Therefore, a new approach was developed based on a two-step methodology. Firstly, neural network models were used to generate short-term temporal forecasts based on air pollution and meteorology data. The accuracy of those forecasts was then evaluated against an independent set of historical data. Secondly, local conditional distributions of the observed values with respect to the predicted values were used to perform spatial stochastic simulations for the entire geographic area of interest. With this approach the spatio-temporal dispersion of a pollutant can be predicted, while accounting for both the temporal uncertainty in the forecast (reflecting the neural networks efficiency at each monitoring station) and the spatial uncertainty as revealed by the spatial variograms. Based on an analysis of the results, our proposed method offers a highly promising alternative for the characterization of urban air quality.