Recovery simulations of grossly polluted sediments in the Bilbao Estuary

The Bilbao Estuary is one of the most contaminated estuaries on the north coast of Spain, and vast efforts have been made to abate pollution there. In fact, the local water authority has forecast a biological recovery of the native fauna after a substantial increase in dissolved oxygen to normoxic levels. In order to assess this prediction by evaluating the extent of natural regeneration of these polluted sediments, two long-term bioassays (t=90 d) were performed. In both of them, lethal (differences in survival) and sublethal (differences in length and weight growth) effects were measured by using juvenile individuals of the autochthonous clam, Scrobicularia plana (Da Costa, 1778). The sediments tested differed in pollution levels, as measured by a set of indicators including PAHs, PCBs, heavy metals, volatile organic matter and coprostanol. All sediments were finally exposed to normoxic conditions in situ in the Bilbao Estuary (DO approximately 6.3 mg l(-1)). In the first experiment, concerning moderately polluted sediments from the Bilbao Estuary and reference sediments from the "pristine" Plentzia Estuary, no significant differences (P>0.05) were found regarding animal survival (approximately 94.5%) or growth in length or weight between the sediments tested. In the second experiment, also involving grossly polluted sediments (GPS) from the Bilbao Estuary, survival (24.5%) was statistically lower (P<0.05) than in the other sediments (approximately 93%). No significant differences were found in growth (length, weight) between animals exposed to moderately polluted or reference sediments. We interpret this dramatic difference in survival as the lethal effect on the animals tested of the GPS of the Bilbao Estuary, indicating a situation where biological recovery is not possible due to the adverse consequences of contaminants sorbed into sediments. The extensive use of this inexpensive bioassay could help to distinguish sediments in which homeostatic recovery is possible from grossly polluted "hot spots", which need costly remedial actions.     

龙马溪—五峰组富有机质页岩三维岩石物理模板分析及"甜点"预测

为识别四川盆地丁山区龙马溪—五峰组目的层富含页岩气的"甜点区",本文对页岩的有机碳含量、脆性、孔隙度及微裂隙等核心指标进行分析研究.对页岩展开岩石物性特征和岩石物理分析,结果显示"甜点区"具有TOC含量高、高孔隙度、低密度、脆性高(石英含量高)的特点,此外储层的拉梅常数和密度的乘积λρ分布范围是18～30 GPa·g·cm-3,泊松比v范围是0.18～0.22,剪切模量μ范围是13～18 GPa.根据储层的岩石物理特征,同时考虑孔隙度、裂隙纵横比和矿物组分对优质页岩敏感弹性参数的影响,采用等效嵌入体应力平均(EIAS)理论模型构建适合页岩气储层的三维岩石物理模板,进而预测储层的孔隙度、裂隙纵横比和石英矿物含量.基于测井数据,对构建的三维岩石物理模板进行校正,将校正后的模板应用到研究工区,选取过三口井的二维测线和三维区块,进行孔隙度、裂隙纵横比和石英矿物含量的定量预测.对比实际资料分析得出的优质页岩储层孔隙度预测范围与测井结果吻合较好,过三口井的目的层产气情况与预测结果一致性良好,目的层页岩具有高孔隙度、低裂隙纵横比和高石英含量的特征,可有效地指示优质页岩储层分布.     

Validation of a method to estimate direct normal irradiance of UVA and PAR bands from global horizontal measurements for cloudless sky conditions in Valencia, Spain, by a measurement campaign

A method is proposed to provide measurement of direct normal solar irradiance of bands with wavelength ranges (315?C400?nm, 400?C700?nm) from measurements of global horizontal band irradiance for cloudless sky conditions in Valencia. Global and normal direct irradiance data for every air mass were obtained by applying the SMART2 model to the atmosphere of Valencia. The direct normal to global irradiance ratio was parameterized versus the relative optical air mass. A measurement campaign of global horizontal and diffuse irradiance of UVA and PAR bands was carried out in Valencia, after which, the inferred direct normal irradiance was compared with those provided by the method. The result of the comparison shows that the method is acceptably accurate. The proposed model tends to underestimate the direct normal irradiance of the UVA band by 6%, although for values below 25?W/m² the model overestimates the direct irradiance by 6%, while for values above 25?W/m² the model underestimates it by 10%. The other two error estimators used ranging from 11% to 15% are similar in the defined interval measurements in relation to the whole UVA band. Regarding the PAR band, the model overestimates the direct normal irradiance of the PAR band by only 2.2%. With this, the results of the PAR band are more conclusive, as it has been found that for direct normal irradiance values higher than 280?W/m² the MBE error is almost zero and the other two estimator errors are small, about 5%.     

Listening to the Deep: live monitoring of ocean noise and cetacean acoustic signals

The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO (Listening to the Deep Ocean Environment) is an international project that is allowing the real-time long-term monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises.     

Classifying wave forecasts with model-based Geostatistics and the Aitchison distribution

This paper proposes a non-parametric method of classification of maps (i.e., variable fields such as wave energy maps for the Western Mediterranean Sea) into a set of D typical regimes (calm, E-, SW- or N/NW-wind dominated storms, the 4 synoptic situations more often occurring in this region). Each map in the training set is described by its values at P measurement points and one of these regime classes. A map is thus identified as a labelled point in a P-dimensional feature space, and the problem is to find a discrimination rule that may be used for attaching a classification probability to future unlabelled maps. The discriminant model proposed assumes that some log-contrasts of these classification probabilities form a Gaussian random field on the feature space. Then, available data (labelled maps of the training set) are linked to these latent probabilities through a multinomial model. This model is quite common in model-based Geostatistics and the Gaussian process classification literature. Inference is here approximated numerically using likelihood based techniques. The multinomial likelihood of labelled features is combined in a Bayesian updating with the Gaussian random field, playing the role of prior distribution. The posterior corresponds to an Aitchison distribution. Its maximum posterior estimates are obtained in two steps, exploiting several properties of this family. The first step is to obtain the mode of this distribution for labelled features, by solving a mildly non-linear system of equations. The second step is to propagate these estimates to unlabelled features, with simple kriging of log-contrasts. These inference steps can be extended via Markov-chain Monte Carlo (MCMC) sampling to a hierarchical Bayesian problem. This MCMC sampling can be improved by further exploiting the Aitchison distribution properties, though this is only outlined here. Results for the application case study suggest that E- and N/NW-dominated storms can be successfully discriminated from calm situations, but not so easily distinguished from each other.     

Synchrotron-based X-ray study of iron oxide transformations in terraces from the Tinto-Odiel river system: Influence on arsenic mobility

Simultaneous analysis of micro-X-ray diffraction (μ-XRD) and micro-X-ray fluorescence (μ-XRF) based on synchrotron light sources, and electron microprobe (EMP) analyses, were performed on iron terrace samples taken from Tinto-Odiel river system from the Iberian Pyrite Belt (IBP, SW Iberian Peninsula). Iron terraces are formed during the oxidation and precipitation of dissolved iron along the riverbeds impacted by acid mine drainage (AMD). This paper includes the study of actively-forming current terraces and fossil terraces isolated from the stream courses due to the river migration over time. The results of the study of current terrace samples from AMD-affected streams of two IPB abandoned mines (Tinto Santa Rosa and Cueva de la Mora) showed that fresh precipitates at the surface are composed primarily of metastable schwertmannite, which is gradually transformed at depth over short-time scales into goethite. Sediments of ancient terraces are composed mainly of goethite, which most likely originated from the re-crystallization of a precursor schwertmannite. However, at century-time scale, goethite partially re-crystallizes to hematite due to diagenetic processes. The transformation rate of goethite into hematite is negatively correlated with grain size and the crystallinity of goethite. Moreover, this transformation is accompanied by an increase in grain size and a decrease in surface area of hematite, and a concomitant decrease in arsenic trapped in the solid. This increase in the arsenic mobility during the diagenetic maturation should be considered in the development of conceptual and analytical models describing long-term fate, transport and bioavailability of arsenic in environmental systems.     

An Analytical Model for Hydraulic Fracturing in Shallow Bedrock Formations

A theoretical method is proposed to estimate post‐fracturing fracture size and transmissivity, and as a test of the methodology, data collected from two wells were used for verification. This method can be employed before hydrofracturing in order to obtain estimates of the potential hydraulic benefits of hydraulic fracturing. Five different pumping test analysis methods were used to evaluate the well hydraulic data. The most effective methods were the Papadopulos‐Cooper model (1967), which includes wellbore storage effects, and the Gringarten‐Ramey model (1974), known as the single horizontal fracture model. The hydraulic parameters resulting from fitting these models to the field data revealed that as a result of hydraulic fracturing, the transmissivity increased more than 46 times in one well and increased 285 times in the other well. The model developed by dos Santos (2008) , which considers horizontal radial fracture propagation from the hydraulically fractured well, was used to estimate potential fracture geometry after hydrofracturing. For the two studied wells, their fractures could have propagated to distances of almost 175 m or more and developed maximum apertures of about 2.20 mm and hydraulic apertures close to 0.30 mm. Fracturing at this site appears to have expanded and propagated existing fractures and not created new fractures. Hydraulic apertures calculated from pumping test analyses closely matched the results obtained from the hydraulic fracturing model. As a result of this model, post‐fracturing geometry and resulting post‐fracturing well yield can be estimated before the actual hydrofracturing.