Natural concentrations and reference values of heavy metals in sedimentary soils in the Brazilian Amazon

The soils of the Brazilian Amazon exhibit large geochemical diversity reflecting the different soil formation processes in an area covering 49% of the Brazilian territory. Soil contamination by heavy metals is one of the threats to the sustainability of this Biome but establishing quality reference values (QRVs) for the region is a challenging owing to the immense territorial area of the Amazon. This study aimed to determine the natural background of heavy metals in soils from the southwestern Brazilian Amazon in order to propose QRVs for Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sb, and Zn for alluvial sedimentary soils. One hundred and twenty-eight soil samples were collected at a depth of 0.0–0.2 m in sites with minimal anthropogenic interference. Soil sample digestion was based on the EPA 3051A method and metal concentrations were determined by ICP-OES. QRVs calculated for the southwestern Brazilian Amazon are among the lowest recorded in Brazil (mg kg^?1): Ba (16.5), Cd (0.1), Cr (6.9), Cu (2.8), Fe (15.4), Mn (13.4), Ni (1.7), Pb (4.4), Sb (0.9), and Zn (5.7). The low metal concentration is likely a result of the sedimentary origin of the soils. The results of this study can serve as a basis for defining public policies to investigate the environmental impacts resulting from changes in land use in areas of the Brazilian Amazon.     

Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin,Brazil

Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Dynamic Modeling of Biological Treatment of Leachates from Solid Wastes

Leachates from municipal solid wastes are liquids formed by organic and inorganic components suitable for biological treatment. In biological treatment plants, prediction of the output parameter value due to dynamic variation is essential. A dynamic model based on ASM1 has been applied for prediction of effluent COD value at real scale, using three different composition leachates. Tuning between dynamic variables and predicted parameter is tested for a correct proposal of the model. Dynamic model predicts correctly fluctuations in the output COD value and tempers dynamism caused by variation of temperature and biomass concentration in the case of high organic loaded leachates. Kinetic parameters Y _H and K _s are fixed to solve the model, and dynamic variables μ _H and X_BH are changing in time. μ_H,max is obtained in simulation (0.37–1.82 day^?1) for minimum error between predicted values and experimental data. μ_H,max value is much lower compared with the value for domestic wastewater treatment due to lower biodegradability of leachate.     

Implications of future bioclimatic shifts on Portuguese forests

As climate is an important driver of vegetation distribution, climate change represents an important challenge to forestry. We (1) identify prevailing bioclimatic conditions for 49 relevant forest species in Portugal and (2) assess future shifts under climate change scenarios. We compute two bioclimatic indices (aridity and thermicity) and a new composite index, at ~1 km spatial resolution, and overlap with the species’ current ranges. Locations are based on a digital inventory, while climate parameters for both recent-past (1950–2000) and future climates (2041–2060), under RCP4.5 and RCP8.5, are provided by a multi-model ensemble of climate simulations. Results for future scenarios highlight an overall warming and drying trend. Supramediterranean and mesomediterranean climates will be significantly reduced, while thermomediterranean climates will dramatically increase, from their almost absence in current conditions to an area coverage of ~54 % in 2041–2060 for RCP8.5. There is also a clear shift from hyper-humid and humid to sub-humid and from the latter to semi-arid climates (area coverage of ~13 % in 2041–2060 for RCP8.5). Lower thermomediterranean sub-humid to semi-arid zones will cover the southern half of Portugal. These projections identify the most vulnerable (e.g. Betula pubescens, Quercus pyrenaica and Castanea sativa) and the most adapted (e.g. Quercus suber, Q. rotundifolia, Ceratonia siliqua, Pinus pinea, Quercus coccifera) species in future climates. Current bioclimatic zones associated with Eucalyptus globulus and Pinus pinaster, economically relevant species, will be moderately reduced and relocated. Possible adaptation measures are discussed to improve forest resilience to climate change, while maintaining its economic and environmental benefits.     

Degradation of bisphenol A by the UV/H2O2 process: a kinetic study

A theoretical and experimental study of bisphenol A (BPA) degradation by the UV/H₂O₂ process in water is presented. The effects of the H₂O₂ concentration and the specific rate of photon emission (E_P,0) on BPA degradation were investigated. A kinetic model derived from a reaction sequence was employed to predict BPA and hydrogen peroxide concentrations over time using an annular photochemical reactor in batch recirculation mode. The local volumetric rate of photon absorption (LVRPA) inside the photoreactor was computed using a Line Source with Parallel Plane emission model (LSPP). From the proposed kinetic model and the experimental data, the second order rate constants of the reactions between hydroxyl radicals and the main reacting species (H₂O₂ and BPA) were estimated applying a nonlinear regression method. A good agreement between the kinetic model and experimental data, for a wide range of operating conditions, was obtained. For BPA, H₂O₂, and TOC concentrations, the calculated root means square errors (RMSE) were 2.3?×?10^??2, 9.8?×?10^??1, and 9.0?×?10^??2 mmol L^??1, respectively. The simplified kinetic model presented in this work can be directly applied to scaling-up and reactor design, since the estimated kinetic constants are independent of the reactor size, shape, and configuration. Further experiments were made by employing low BPA initial concentration (100 μg L^??1) in water and real wastewater. A lower degradation rate of BPA was observed in the real wastewater, although the UV/H₂O₂ process has also been able to completely degrade the target pollutant in less than 1 h.

     

Development of mixed conducting membranes for clean coal energy delivery

Mixed conducting membranes can be used for the separation of oxygen from air in both coal gasification and oxy-fuel power plants. In this review paper, the basic perovskite and non-perovskite structures, composition, properties and performance are addressed. Two typical perovskite materials, BSCF and LSCF, show promise in industrial applications as their oxygen fluxes are at least one order of magnitude higher than non-perovskite membranes. BSCF membranes are now delivering oxygen fluxes in excess of 5 ml min^?1 cm^?2. Latest developments in perovskite composition, effects of impurities in membrane performance and membrane geometry are discussed giving an insight into the potential utilisation in clean energy delivery processes. Strategies for improving membranes performance using unit operations with different geometries and possible future technologies are also addressed.     

Co-occurrence profiles of trace elements in potable water systems: a case study

Potable water samples (N?=?74) from 19 zip code locations in a region of Greece were profiled for 13 trace elements composition using inductively coupled plasma mass spectrometry. The primary objective was to monitor the drinking water quality, while the primary focus was to find novel associations in trace elements occurrence that may further shed light on common links in their occurrence and fate in the pipe scales and corrosion products observed in urban drinking water distribution systems. Except for arsenic at two locations and in six samples, rest of the analyzed elements was below maximum contaminant levels, for which regulatory values are available. Further, we attempted to hierarchically cluster trace elements based on their covariances resulting in two groups; one with arsenic, antimony, zinc, cadmium, and copper and the second with the rest of the elements. The grouping trends were partially explained by elements’ similar chemical activities in water, underscoring their potential for co-accumulation and co-mobilization phenomena from pipe scales into finished water. Profiling patterns of trace elements in finished water could be indicative of their load on pipe scales and corrosion products, with a corresponding risk of episodic contaminant release. Speculation was made on the role of disinfectants and disinfection byproducts in mobilizing chemically similar trace elements of human health interest from pipe scales to tap water. It is warranted that further studies may eventually prove useful to water regulators from incorporating the acquired knowledge in the drinking water safety plans.     

Seeds’ physicochemical traits and mucilage protection against aluminum effect during germination and root elongation as important factors in a biofuel seed crop (Ricinus communis)

We determined the length, volume, dry biomass, and density in seeds of five castor bean cultivars and verified notable physicochemical trait differences. Seeds were then subjected to different toxic aluminum (Al) concentrations to evaluate germination, relative root elongation, and the role of root apices’ rhizosphere mucilage layer. Seeds’ physicochemical traits were associated with Al toxicity responses, and the absence of Al in cotyledons near to the embryo was revealed by Al-hematoxylin staining, indicating that Al did not induce significant germination reduction rates between cultivars. However, in the more sensitive cultivar, Al was found around the embryo, contributing to subsequent growth inhibition. After this, to investigate the role of mucilage in Al tolerance, an assay was conducted using NH₄Cl to remove root mucilage before or after exposure to different Al concentrations. Sequentially, the roots were stained with hematoxylin and a quantitative analysis of staining intensity was obtained. These results revealed the significant contribution of the mucilage layer to Al toxicity responses in castor bean seedlings. Root growth elongation under Al toxicity confirmed the role of the mucilage layer, which jointly indicated the differential Al tolerance between cultivars and an efficient Al-exclusion mechanism in the tolerant cultivar.