The petrogenesis of volcanics from Mt. Bulusan and Mt. Mayon in the Bicol arc,the Philippines

Pliocene to recent volcanic rocks from the Bulusan volcanic complex in the southern part of the Bicol arc (Philippines) exhibit a wide compositional range (medium- to high-K basaltic-andesites, andesites and a dacite/rhyolite suite), but are characterised by large ion lithophile element enrichments and HFS element depletions typical of subduction-related rocks. Field, petrographic and geochemical data indicate that the more silicic syn- and post-caldera magmas have been influenced by intracrustal processes such as magma mixing and fractional crystallisation. However, the available data indicate that the Bicol rocks as a group exhibit relatively lower and less variable ⁸⁷Sr/⁸⁶Sr ratios (0.7036–0.7039) compared with many of the other subduction-related volcanics from the Philippine archipelago. The Pb isotope ratios of the Bicol volcanics appear to be unlike those of other Philippine arc segments. They typically plot within and below the data field for the Philippine Sea Basin on ²⁰⁷Pb/²⁰⁴Pb versus ²⁰⁶Pb/²⁰⁴Pb and ²⁰⁸Pb/²⁰⁴Pb versus ²⁰⁶Pb/²⁰⁴Pb diagrams, implying a pre-subduction mantle wedge similar to that sampled by the Palau Kyushu Ridge, east of the Philippine Trench. ¹⁴³Nd/¹⁴⁴Nd ratios are moderately variable (0.51285–0.51300). Low silica (<55 wt%) samples that have lower ¹⁴³Nd/¹⁴⁴Nd tend to have high Th/Nd, high Th/Nb, and moderately low Ce/Ce* ratios. Unlike some other arc segments in the Philippines (e.g. the Babuyan-Taiwan segment), there is little evidence for the involvement of subducted terrigenous sediment. Instead, the moderately low ¹⁴³Nd/¹⁴⁴Nd ratios in some of the Bicol volcanics may result from subduction of pelagic sediment (low Ce/Ce*, high Th/Nd, and high Th/Nb) and its incorporation into the mantle wedge via a slab-derived partial melt.     

An intelligent neural network model for evaluating performance of immobilized cell biofilter treating hydrogen sulphide vapors

Biofiltration has shown to be a promising technique for handling malodours arising from process industries. The present investigation pertains to the removal of hydrogen sulphide in a lab scale biofilter packed with biomedia, encapsulated by sodium alginate and poly vinyl alcohol. The experimental data obtained under both steady state and shock loaded conditions were modelled using the basic principles of artificial neural networks. Artificial neural networks are powerful data driven modelling tools which has the potential to approximate and interpret complex input/output relationships based on the given sets of data matrix. A predictive computerised approach has been proposed to predict the performance parameters namely, removal efficiency and elimination capacity using inlet concentration, loading rate, flow rate and pressure drop as the input parameters to the artificial neural network model. Earlier, experiments from continuous operation in the biofilter showed removal efficiencies from 50 to 100 % at inlet loading rates varying up to 13 g H₂S/m³h. The internal network parameter of the artificial neural network model during simulation was selected using the 2^k factorial design and the best network topology for the model was thus estimated. The results showed that a multilayer network (4-4-2) with a back propagation algorithm was able to predict biofilter performance effectively with R² values of 0.9157 and 0.9965 for removal efficiency and elimination capacity in the test data. The proposed artificial neural network model for biofilter operation could be used as a potential alternative for knowledge based models through proper training and testing of the state variables.     

Recent changes in the precipitation-driving processes over the southern tropical Andes/western Amazon

Climate Dynamics - Analyzing December–February (DJF) precipitation in the southern tropical Andes—STA ($$12^{\circ }\,\hbox {S}$$–$$20^{\circ }\,\hbox {S}$$; &gt; 3000...     

Removal of Two Pharmaceutically Active Compounds from Aqueous Phase Using an Engineered Floodplain Filtration System

This study investigated the removal of two model pharmaceutically active compounds (PhAcs), viz., ibuprofen and triclosan, in lab‐scale engineered floodplain filtration (EFF) system. Biodegradation experiments were performed to acquire knowledge about the degradation of the targeted PhAcs, at an initial concentration of 350 µg/L. Biodegradation results showed that the two compounds were bio‐transformed to >70% after 15 days of incubation. Column tests were performed in a statistically significant manner to determine the adsorptive potential of the suggested filler layer in the EFF (C/C₀), by varying the flow rate and initial concentration of the compound. It was observed based on the F and p‐values that the main effects (F = 3163, p < 0.005) were more significant than the interactive effects (F = 9561, p < 0.05) for both ibuprofen and triclosan removal. Besides, by performing the Student's “t” test, it was concluded that the flow rate plays a major role in determining the rapidness of achieving complete breakthrough than the initial concentration of both the compounds. The data obtained from column studies under biotic conditions indicated that the removal mechanism for PhAcs is mainly biotransformation based, and that an EFF system may be effectively used to remove these emerging compounds during ground water recharge for water recycling.     

A local scale-sensitive indicator of spatial autocorrelation for assessing high- and low-value clusters in multiscale datasets

Georeferenced user-generated datasets like those extracted from Twitter are increasingly gaining the interest of spatial analysts. Such datasets oftentimes reflect a wide array of real-world phenomena. However, each of these phenomena takes place at a certain spatial scale. Therefore, user-generated datasets are of multiscale nature. Such datasets cannot be properly dealt with using the most common analysis methods, because these are typically designed for single-scale datasets where all observations are expected to reflect one single phenomenon (e.g., crime incidents). In this paper, we focus on the popular local G statistics. We propose a modified scale-sensitive version of a local G statistic. Furthermore, our approach comprises an alternative neighbourhood definition that enables to extract certain scales of interest. We compared our method with the original one on a real-world Twitter dataset. Our experiments show that our approach is able to better detect spatial autocorrelation at specific scales, as opposed to the original method. Based on the findings of our research, we identified a number of scale-related issues that our approach is able to overcome. Thus, we demonstrate the multiscale suitability of the proposed solution.     

Geochemical Assessment of a Subtropical Reservoir: A Case Study in Curitiba,Southern Brazil

Suspended particles and dissolved substances in water provide reactive surfaces, influence metabolic activity and contribute to the net sediment deposition. It therefore plays an important part in the ecology and quality of the water mass. The water quality in reservoirs is crucial and it is naturally maintained by flushing and sedimentation, which continuously remove phosphorus from the water. In some reservoirs, however, these removal processes are countered by recycling of ions which could play a key role to start and/or maintain the eutrophic state. The combination of macro‐, trace‐ and microanalysis techniques can be useful to trace pollution sources through a chemical fingerprint, whether be during an acute environmental disaster or a long‐term release of pollutants. The water quality and total metal content of reservoir sediments were assessed in a reservoir, situated in the capital of the Paraná State, in the South‐Eastern part of Brazil. The goal of this paper was to determine the metal presence in the sediment and metal and ionic speciation in the Green River reservoir water. Water and bed sediment samples, collected from various sites during 2008 and 2009, were investigated using XRF, ICP‐OES, ICP‐MS, XRD and zeta potential measurements. Based on the results, the heavy metal concentration and chemical composition of the suspended matter in the water samples, as well as the sediment's chemical composition will be discussed.     

Petrogenesis of group A eclogites and websterites: evidence from the Obnazhennaya kimberlite,Yakutia

Mantle xenoliths from the Obnazhennaya kimberlite pipe, Yakutia, possess a large range of mineralogical and chemical compositions, from both group A and B eclogites. Major-element contents of the group A eclogites exhibit transitional features between the group B eclogites and peridotite. The Mg# of clinopyroxenes is 0.86–0.94, with 0.60–0.84 for garnets. Differences in concentration of LREEs exist between the Obnazhennaya group A and the well-studied group B eclogites from the Udachnaya kimberlite pipe. In general, garnets in the group A eclogites contain lower LREEs than those from the group B eclogites; however, the trend for clinopyroxene is reversed. High d ¹⁸O (5.46–7.81) values, and the positive Eu anomalies in the garnets and clinopyroxenes (Eu/Eu* 1.2–1.4) demonstrate the involvement of an oceanic crustal component in the formation of the group A eclogites. The group A eclogites formed between 21.0 and 37.6 kbar, and 711 and 923 °C, in a time interval of 1,071–1,237 Ma. An innovative model is proposed to explain the formation of the group A eclogites and websterites. It involves the reaction of a depleted mantle peridotite with TTG and carbonatite melts closely related to the subduction of oceanic crust.     

Performance of upflow anoxic bioreactor for wastewater treatment

Laboratory scale studies were conducted in an up-flow anoxic bioreactor using synthetic fertilizer wastewater for ascertaining the denitrification efficiency. The performance of the reactor was compared using ethanol and topioca starch as the carbon source. The initial No₃-N concentrations (50–250 mg/L) and hydraulic retention time (FTRT, 12–24 h) were varied to evaluate the COD and No₃-N removal. The results from this study shows that ethanol gave very good denitrification efficiency (78–98%) compared to topioca starch (68–96%).