Superposition of tectonic structures leading elongated intramontane basin: the Alhabia basin (Internal Zones,Betic Cordillera)

International Journal of Earth Sciences - The relief of the Betic Cordillera was formed since the late Serravallian inducing the development of intramontane basins. The Alhabia basin, situated in...     

Episodic Biogeochemical Variability in a Low-Flow Mediterranean Estuary

To investigate to what extent episodic physical processes regulate nutrient availability and phytoplankton assemblages of the Mahon estuary (Minorca Island), we carried out an intensive field study during 2010–2011. During the study period, environmental conditions spanned from intense stratification to a continuous mixing and from lack of riverine inflow to intense runoff. Our data reveals a sequence of biogeochemical states of the estuary that result from the interplay between runoff, other non-periodic forcings (winds, sea level oscillations), and variations in water renewal. Seasonal runoff was revealed as a major driver of winter circulation and of the influx of inorganic nutrients, in particular nitrate. However, because of the combination between runoff and flushing time, the effects of floodwater events on phytoplankton are short-lived (days). Conversely, during summer, when freshwater influx declines, water renewal relies on pulsed atmospheric forcing that may be of local or remote origin. As depicted from the low nitrate concentrations (<1 μM) and enhanced ammonium (>1 μM), this change in circulation and external loads carries nutrient assimilation within the estuary head and forces the use of remnant nutrients through regenerating pathways to sustain an enhanced phytoplankton biomass at the lower estuary. Episodic variability represented between 52 and 65% of the annual chlorophyll variance. Despite the fact that episodic pulses represented intense departures from base biogeochemical state of the estuary, at time scale larger than weeks, the phytoplankton community composition and dynamics was largely regulated by the integrated effect of these episodes and other environmental drivers associated with seasonality rather than by individual storm events only. Our results suggest that even though the system presents good recovery capacity to individual storm episodes, it may be more vulnerable to increased nutrient fluxes during summer, as well as to changes in episode timing and frequency.     

Moving bed biofilm reactor to treat wastewater

This review carries out a comparative study of advanced technologies to design, upgrade and rehabilitate wastewater treatment plants. The study analyzed the relevant researches in the last years about the moving bed biofilm reactor process with only attached biomass and with hybrid biomass, which combined attached and suspended growth; both could be coupled with a secondary settling tank or microfiltration/ultrafiltration membrane as a separation system. The physical process of membrane separation improved the organic matter and NH₄ ⁺-N removal efficiencies compared with the settling tank. In particular, the pure moving bed biofilm reactor–membrane bioreactor showed average chemical oxygen demand, biochemical oxygen demand on the fifth day and total nitrogen removal efficiencies of 88.32, 90.84 and 60.17%, respectively, and the hybrid moving bed biofilm reactor–membrane bioreactor had mean chemical oxygen demand, biochemical oxygen demand on the fifth day and total nitrogen reduction percentages of 91.18, 97.34 and 68.71%, respectively. Moreover, the hybrid moving bed biofilm reactor–membrane bioreactor showed the best efficiency regarding organic matter removal for low hydraulic retention times, so this system would enable the rehabilitation of activated sludge plants and membrane bioreactors that did not comply with legislation regarding organic matter removal. As the pure moving bed biofilm reactor–membrane bioreactor performed better than the hybrid moving bed biofilm reactor–membrane bioreactor concerning the total nitrogen removal under low hydraulic retention times, this system could be used to adapt wastewater treatment plants whose effluent was flowed into sensitive zones where total nitrogen concentration was restricted. This technology has been reliably used to upgrade overloaded existing conventional activated sludge plants, to treat wastewater coming from textile, petrochemical, pharmaceutical, paper mill or hospital effluents, to treat wastewater containing recalcitrant compounds efficiently, and to treat wastewater with high salinity and/or low and high temperatures.     

Real‐time distributed hybrid testing: coupling geographically distributed scientific equipment across the Internet to extend seismic testing capabilities

Large‐scale testing and qualification of structural systems and their components is crucial for the development of earthquake engineering knowledge and practice. However, laboratory capacity is often limited when attempting larger experiments due to the sheer size of the structures involved. To overcome traditional laboratory capacity limitations, we present a new earthquake engineering testing method: real‐time distributed hybrid testing. Extending current approaches, the technique enables geographically distributed scientific equipment including controllers, dynamic actuators and sensors to be coupled across the Internet in real‐time. As a result, hybrid structural emulations consisting of physical and numerical substructures need no longer be limited to a single laboratory. Larger experiments may distribute substructures across laboratories located in different cities whilst maintaining correct dynamic coupling, required to accurately capture physical rate effects. The various aspects of the distributed testing environment have been considered. In particular, to ensure accurate control across an environment not designed for real‐time testing, new higher level control protocols are introduced acting over an optimised communication system. New large time‐step prediction algorithms are used, capable of overcoming both local actuation and distributed system delays. An overview of the architecture and algorithms developed is presented together with results demonstrating a number of current capabilities. Copyright © 2013 John Wiley & Sons, Ltd.     

Applying Fractal Dimensions and Energy-Budget Analysis to Characterize Fracturing Processes During Magma Migration and Eruption: 2011–2012 El Hierro (Canary Islands) Submarine Eruption

The impossibility of observing magma migration inside the crust obliges us to rely on geophysical data and mathematical modelling to interpret precursors and to forecast volcanic eruptions. Of the geophysical signals that may be recorded before and during an eruption, deformation and seismicity are two of the most relevant as they are directly related to its dynamic. The final phase of the unrest episode that preceded the 2011–2012 eruption on El Hierro (Canary Islands) was characterized by local and accelerated deformation and seismic energy release indicating an increasing fracturing and a migration of the magma. Application of time varying fractal analysis to the seismic data and the characterization of the seismicity pattern and the strain and the stress rates allow us to identify different stages in the source mechanism and to infer the geometry of the path used by the magma and associated fluids to reach the Earth’s surface. The results obtained illustrate the relevance of such studies to understanding volcanic unrest and the causes that govern the initiation of volcanic eruptions.     

Prediction of PM10 and SO2 exceedances to control air pollution in the Bay of Algeciras,Spain

In this paper, the authors apply different classification techniques in order to provide 24 h advance forecasts of the daily peaks of SO₂ and PM10 concentrations in the Bay of Algeciras. K-nearest-neighbours, multilayer neural network with backpropagation and support vector machines (SVMs) are the classification methods used. The aim of this research is to obtain a suitable prediction model that would enable us to predict the peaks of pollutant concentrations in critical meteorological situations caused by the widespread existing industry and population in the area. A resampling strategy with twofold crossvalidation has been applied, using different quality indexes to evaluate the performance of the prediction models. SVM models achieved better true positive rate and accuracy (ACC) quality indexes. Results of ACC index value of 0.795 for PM10 and 0.755 for SO₂ showed the ability of the model to predict peaks and non-peaks correctly.