Two Brazilian archaeological sites investigated by GPR: Serrano and Morro Grande

The application of the ground penetrating radar (GPR) at two archaeological sites, Serrano and Morro Grande, situated in Araruama County, Rio de Janeiro, Brazil, aids the study of a prehistoric indigenous culture, associated with the “Tupinambá” that inhabited the region during prehistoric times.The archaeological remains of the study area are mainly characterized by pottery artifacts for several uses, including funerary urns, which were buried within layers of sand and clay. Several profiles were acquired using a RAMAC system, with a 200 and 400 MHz frequency antennae. At the Serrano site, the profiles were acquired around some partially exposed pottery shards, due to sand exploitation. The resultant profiles provided a response model to guide the interpretation of new profiles acquired at other sites in the area, which present similar characteristics.The results showed the great importance of the dielectric permittivity contrast which exists between the targets and the host media, in order for possibly significant features to be identified in radar data.     

Study of the Interaction Mechanism in the Biosorption of Copper(II) Ions onto Posidonia oceanica and Peat

A systematic approach was used to characterize the biosorption of copper(II) onto two biosorbents, Posidonia oceanica and peat, focusing on the interaction mechanisms, the copper(II) sorption–desorption process and the thermal behavior of the biosorbents. Sorption isotherms at pH 4–6 were obtained and the experimental data were fitted to the Langmuir model with a maximum uptake (q_max) at pH 6 of 85.78 and 49.69 mg g^?1, for P. oceanica and peat, respectively. A sequential desorption (SD) with water, Ca(NO₃)₂, and EDTA was applied to copper‐saturated biosorbents. Around 65–70% copper(II) were desorbed with EDTA, indicating that this heavy metal was strongly bound. The reversibility of copper(II) sorption was obtained by desorption with HCl and SD. Fourier transform IR spectroscopy (FTIR) analysis detected the presence of peaks associated with OH groups in aromatic and aliphatic structures, CH, CH₂, and CH₃ in aliphatic structures, COO^? and COOH groups and unsaturated aromatic structures on the surface of both biosorbents, as well as peaks corresponding to Si? O groups on the surface of peat. The results of SEM‐EDX and FTIR analysis of copper‐saturated samples demonstrated that ion exchange was one of the mechanisms involved in copper(II) retention. Thermal analysis of biosorbent samples showed that copper(II) sorption–desorption processes affected the thermal stability of the biosorbents.     

On the accuracy of atmospheric forcing for extra-tropical storm surge prediction

The ability of the SMARA storm surge numerical prediction system to reproduce local effects in estuarine and coastal winds was recently improved by considering one-way coupling of the air–sea momentum exchange through the wave stress, and best forecasting practices for downscaling. The inclusion of long period atmospheric pressure forcing in tide and tide/surge calculations corrected a systematic error in the surge, produced by the South Atlantic Ocean quasi-stationary pressure patterns. The maximum forecast range for the storm surge at Buenos Aires provided by the real-time use of water level observations is approximately 12 h. The best available water level prediction is the 6-h forecast (nowcast) based on the closest water level observations. The 24-h forecast from the numerical models slightly improves this nowcast. Although the numerical forecast accuracy degrades after the first 48 h, the improvement to the full range observation-based prediction is maintained at the inner Río de la Plata area and extends to the first 3 days at the intermediate navigation channels.     

Amazon forest biomass density maps: tackling the uncertainty in carbon emission estimates

As land use change (LUC), including deforestation, is a patchy process, estimating the impact of LUC on carbon emissions requires spatially accurate underlying data on biomass distribution and change. The methods currently adopted to estimate the spatial variation of above- and below-ground biomass in tropical forests, in particular the Brazilian Amazon, are usually based on remote sensing analyses coupled with field datasets, which tend to be relatively scarce and often limited in their spatial distribution. There are notable differences among the resulting biomass maps found in the literature. These differences subsequently result in relatively high uncertainties in the carbon emissions calculated from land use change, and have a larger impact when biomass maps are coded into biomass classes referring to specific ranges of biomass values. In this paper we analyze the differences among recently-published biomass maps of the Amazon region, including the official information used by the Brazilian government for its communication to the United Nation Framework on Climate Change Convention of the United Nations. The estimated average pre-deforestation biomass in the four maps, for the areas of the Amazon region that had been deforested during the 1990–2009 period, varied from 205?±?32 Mg ha^?1 during 1990–1999, to 216?±?31 Mg ha^?1 during 2000–2009. The biomass values of the deforested areas in 2011 were between 7 and 24 % higher than for the average deforested areas during 1990–1999, suggesting that although there was variation in the mean value, deforestation was tending to occur in increasingly carbon-dense areas, with consequences for carbon emissions. To summarize, our key findings were: (i) the current maps of Amazonian biomass show substantial variation in both total biomass and its spatial distribution; (ii) carbon emissions estimates from deforestation are highly dependent on the spatial distribution of biomass as determined by any single biomass map, and on the deforestation process itself; (iii) future deforestation in the Brazilian Amazon is likely to affect forests with higher biomass than those deforested in the past, resulting in smaller reductions in carbon dioxide emissions than expected purely from the recent reductions in deforestation rates; and (iv) the current official estimate of carbon emissions from Amazonian deforestation is probably overestimated, because the recent loss of higher-biomass forests has not been taken into account.     

The 23 April 1909 Benavente earthquake (Portugal): macroseismic field revision

The 23 April 1909 earthquake, with epicentre near Benavente (Portugal), was the largest crustal earthquake in the Iberian Peninsula during the twentieth century (M _w = 6.0). Due to its importance, several studies were developed soon after its occurrence, in Portugal and in Spain. A perusal of the different studies on the macroseismic field of this earthquake showed some discrepancies, in particular on the abnormal patterns of the isoseismal curves in Spain. Besides, a complete list of intensity data points for the event is unavailable at present. Seismic moment, focal mechanism and other earthquake parameters obtained from the instrumental records have been recently reviewed and recalculated. Revision of the macroseismic field of this earthquake poses a unique opportunity to study macroseismic propagation and local effects in central Iberian Peninsula. For this reasons, a search to collect new macroseismic data for this earthquake has been carried out, and a re-evaluation of the whole set has been performed and it is presented here. Special attention is paid to the observed low attenuation of the macroseismic effects, heterogeneous propagation and the distortion introduced by local amplifications. Results of this study indicate, in general, an overestimation of the intensity degrees previously assigned to this earthquake in Spain; also it illustrates how difficult it is to assign an intensity degree to a large town, where local effects play an important role, and confirms the low attenuation of seismic propagation inside the Iberian Peninsula from west and southwest to east and northeast.     

The role of biogenic structures on the biogeochemical functioning of mangrove constructed wetlands sediments - A mesocosm approach

Benthic metabolism (measured as CO₂ production) and carbon oxidation pathways were evaluated in 4 mangrove mesocosms subjected daily to seawater or 60% sewage in the absence or presence of mangrove trees and biogenic structures (pneumatophores and crab burrows). Total CO₂ emission from darkened sediments devoid of biogenic structures at pristine conditions was comparable during inundation (immersion) and air exposure (emersion), although increased 2-7 times in sewage contaminated mesocosms. Biogenic structures increased low tide carbon gas emissions at contaminated (30%) and particularly pristine conditions (60%). When sewage was loaded into the mesocosms under unvegetated and planted conditions, iron reduction was substituted by sulfate reduction and contribution of aerobic respiration to total metabolism remained above 50%. Our results clearly show impacts of sewage on the partitioning of electron acceptors in mangrove sediment and confirm the importance of biogenic structures for biogeochemical functioning but also on greenhouse gases emission.     

An investigation of ensemble-based assimilation of satellite altimetry and tide gauge data in storm surge prediction

Cyclogenesis and long-fetched winds along the southeastern coast of South America may lead to floods in populated areas, as the Buenos Aires Province, with important economic and social impacts. A numerical model (SMARA) has already been implemented in the region to forecast storm surges. The propagation time of the surge in such extensive and shallow area allows the detection of anomalies based on observations from several hours up to the order of a day prior to the event. Here, we investigate the impact and potential benefit of storm surge level data assimilation into the SMARA model, with the objective of improving the forecast. In the experiments, the surface wind stress from an ensemble prediction system drives a storm surge model ensemble, based on the operational 2-D depth-averaged SMARA model. A 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) initializes the ensemble in a 6-h cycle, assimilating the very few tide gauge observations available along the northern coast and satellite altimeter data. The sparse coverage of the altimeters is a challenge to data assimilation; however, the 4D-LETKF evolving covariance of the ensemble perturbations provides realistic cross-track analysis increments. Improvements on the forecast ensemble mean show the potential of an effective use of the sparse satellite altimeter and tidal gauges observations in the data assimilation prototype. Furthermore, the effects of the localization scale and of the observational errors of coastal altimetry and tidal gauges in the data assimilation approach are assessed.     

Response of suspended sediment particle size distributions to changes in water chemistry at an Andean mountain stream confluence receiving arsenic rich acid drainage

Acid drainage is an important water quality issue in Andean watersheds, affecting the sustainability of urban, agricultural, and industrial activities. Mixing zones receiving acid drainage are critical sites where changes in pH and chemical environment promote the formation and dissolution of iron and aluminum oxy/hydroxides. These particles can significantly change the speciation of toxic metals and metalloids throughout drainage networks via sorption, desorption, and settling processes. However, little is known about the behavior of particle size distributions (PSDs) in streams affected by acid drainage and their relationship to metal speciation. This work studied: (a) the PSDs for a wide range of mixing ratios found at a fluvial confluence affected by acid drainage, and (b) the response of PSDs and arsenic speciation to environmental changes found when the particles approach complete mixing conditions. The confluence between the Azufre River (pH ~ 2, high concentration of dissolved metals) and Caracarani River (pH = 8.6, low concentration of dissolved metals) was used as a representative model for study. Field measurements show a bimodal PSD with modal diameters of ~50 and 300 μm. At shorter distances from the junction, the smaller modes with smaller particle volumes were dominant across the stream cross‐sections. A systematic shift towards larger particle sizes and larger particle volumes occurred downstream. The analysis of laboratory PSDs for Azufre/Caracarani mixing ratios between 0.01 and 0.5 (pH from 6.2 to 2.3) showed a bimodal trend with ~15 and 50 μm characteristic diameters; larger particles formed at pH>4. When particle suspensions were transferred in laboratory experiments from very low pH to full mixing conditions (pH ~ 2.8 and mixing ratio ~ 0.25) particle sizes varied, and the dissolved arsenic concentration decreased. The observed reaction kinetics were slow compared to the time scale of advective transport, creating opportunities for engineered controls for arsenic. This work contributes to a better understanding of the chemical‐hydrodynamic interactions in watersheds affected by mining, and identifying opportunities to improve water quality at points of use.