Phytoremediation potential and morphological changes of plants growing in the vicinity of lead smelter plant

With the increasing industrialization, heavy metals concentration in soils has greatly increased. Phytoremediation is a low-cost, non-intrusive and aesthetically harmonious technology that uses plants to remediate contaminated sites by heavy metals. The aim of the study was to determine Cd, Pb and Zn concentration in the biomass of plant species growing on a multi-metal-contaminated site of lead smelter processing, to assess the workability of using these plants for phytoremediation purposes and highlight possible damage in morphological leaf changes. Two plant species, i.e., Ipomoea asarifolia and Urochloa decumbens and the associated soil samples were collected and analyzed Cd, Pb and Zn concentrations and then calculating the bioconcentration factor and translocation factor parameters for each element. Leaves and roots samples were observed by light microscopy. Metal concentrations varied greatly and majorly depend on site sampled, plant species and tissue. Cd, Pb and Zn in tissue ranged from 0 to 102.48, 0 to 381.04 and 12.84 to 295.02 mg Kg^?1. However, none of the plant showed potential for hyperaccumulation. Both plants showed bioaccumulation factor more than one, where it was 7.66 and 6.82 for Pb and Zn in U. decumbens, respectively. Translocation factor was calculated below one for both plants and all metals. Morphological studies revealed development of adaptive features that strengthen the U. decumbens to grow in contaminated soil. Our study suggests that I. asarifolia and U. decumbens have potential for phytostabilization at multi-metal-contaminated site.     

Adsorption of methylene blue and crystal violet on low-cost adsorbent: waste fruits of <Emphasis Type="Italic">Rapanea ferruginea</Emphasis> (ethanol-treated and H<Subscript>2</Subscript>SO<Subscript>4</Subscript>-treated)

This study assesses the ability of two low-cost adsorbents made from waste of Rapanea ferruginea treated with ethanol (WRf) and its H₂SO₄-treated analog (WRf/H₂SO₄) for the removal of two cationic dyes methylene blue (MB) and crystal violet (CV) from aqueous solutions. The adsorbent was characterized by scanning electron microscopy, Fourier transform infrared spectrometry, thermogravimetric analysis, point of zero charge (pH_pzc), specific surface, and functional groups. The adsorption of dye onto the adsorbents was studied as a function of pH solution (2–12), contact time (up to 120 min) and initial concentration (20–120 mg/L), and temperature (25, 35, and 55 °C). The influence of these parameters on adsorption capacity was studied using the batch process. The response surface methodology (RSM) was used in the experimental design, modeling of the process, and optimizing of the variables and was optimized by the response involving Box–Behnken factorial design (15 runs). The results show that the data correlated well with the Sips isotherm. The maximum adsorption capacities of MB and CV onto WRf were found to be 69 and 106 mg/g, and onto WRf/H₂SO₄, the adsorption capacities were 33 and 125 mg/g, respectively. The kinetic data revealed that adsorption of cationic dyes onto the adsorbents closely follows the pseudo-second-order kinetic model. Regression analysis showed good fit of the experimental data to the second-order polynomial model, with coefficient of determination (R²) values for MB (R²?=?0.9685) and MB (R²?=?0.9832) for WRf and CV (R²?=?0.9685) and CV (R²?=?0.9832) for WRf/H₂SO₄ indicated that regression analysis is able to give a good prediction of response for the adsorption process in the range studied. The results revealed that waste from R. ferruginea is potentially an efficient and low-cost adsorbent for adsorption of MB and CV.     

What is wrong with post-fire soil erosion modelling? A meta-analysis on current approaches,research gaps,and future directions

In the near future, a higher occurrence of wildfires is expected due to climate change, carrying social, environmental, and economic implications. Such impacts are often associated with an increase of post-fire hydrological and erosive responses, which are difficult to predict. Soil erosion models have been proven to be a valuable tool in the decision-making process, from emergency response to long-term planning, however, they were not designed for post-fire conditions, so need to be adapted to include fire-induced changes. In recent years, there have been an increasing number of studies testing different models and adaptations for the prediction of post-fire soil erosion. However, many of these adaptations are being applied without field validation or model performance assessment. Therefore, this study aims to describe the scientific advances in the last 20 years in post-fire soil erosion modelling research and evaluate model adaptations to burned areas that aim to include: (i) fire-induced changes in soil and ground cover; (ii) fire-induced changes in infiltration; (iii) burn severity; and (iv) mitigation measures in their predictions. This study also discusses the strengths and weaknesses of these approaches, suggests potential improvements, and identifies directions for future research. Results show that studies are not homogeneously distributed worldwide, according to the model type used or by region most affected by wildfire. During calibration, 73% of cases involved model adaptation to burned conditions, and only 21% attempted to accommodate new processes. Burn severity was addressed in 75% of cases, whilst mitigation measures were simulated in 27%. Additionally, only a minor percentage of model predictions were validated with independent field data (17%) or assessed for uncertainties (13%). Therefore, further efforts are required in the adaptation of erosion models to burned conditions, to be widely used for post-fire management decisions. © 2020 John Wiley & Sons, Ltd.     

Geochemical evidence for melting of carbonated peridotite on Santa Maria Island, Azores

The islands of the Azores archipelago emerge from an oceanic plateau built on lithosphere increasing in age with distance from the Mid-Atlantic Ridge from 10 to 45 Ma. Here, we present the first comprehensive major and trace element and Sr–Nd–Pb isotope data from Santa Maria, the easternmost island of the archipelago, along with published data from the other Azores islands situated much closer to the Mid-Atlantic Ridge axis. We can show that the distinctively more variable and more enriched trace element ratios at Santa Maria combined with a relatively small range in Sr–Nd–Pb isotope ratios are the result of low degrees of partial melting of a common Azores mantle plume source underneath thicker lithosphere. This implies that melt extraction processes and melting dynamics may be able to better preserve the trace element mantle source variability underneath thicker lithosphere. These conclusions may apply widely for oceanic melts erupted on relatively thick lithosphere. In addition, lower Ti/Sm and K/La ratios and SiO₂ contents of Santa Maria lavas imply melting of a carbonated peridotite source. Mixing of variable portions of deep small-degree carbonated peridotite melts and shallow volatile-free garnet peridotite could explain the geochemical variability underneath Santa Maria in agreement with the volatile-rich nature of the Azores mantle source. However, Santa Maria is the Azores island where the CO₂-rich nature of the mantle source is more evident, reflecting a combination of a smaller extent of partial melting and the positioning at the edge of the tilted Azores mantle plume.     

Vulnerability of Bulgarian agriculture to drought and climate variability with focus on rainfed maize systems

Bulgarian agriculture is affected by droughts and, likely, by climate change. Thus, aiming at assessing its vulnerability, this study includes a general characterization of climate variability in eight selected locations, both in northern and southern Bulgaria. Trend tests were applied to monthly precipitation, maximum and minimum temperature and to the Standardized Precipitation Index with two-month time step (SPI-2) relative to the period of 1951–2004. Negative trends were identified for precipitation and SPI-2 at various locations, mainly in the Thrace Plain, indicating that dryness is likely to be increasing in Bulgaria. The vulnerability of rainfed maize systems to drought was studied using the previously calibrated WinISAREG model and the Stewart’s yield model to compute both the relative yield decrease (RYD) due to water stress and the corresponding net irrigation required to overcome those losses. Results identified a strong relation between SPI-2 for July–August (SPI-2_July–Aug) and RYD. Results also show that yield losses are higher when the soils have a smaller soil water holding capacity. For the various regions under study, thresholds for RYD were defined considering the related economic impacts and the influence of soil characteristics on the vulnerability of the rainfed maize systems. Finally, to support drought risk management, SPI-2_July–Aug thresholds were developed to be used as indicators of the economic risk of rainfed maize for various climate regions and soil groups in Bulgaria.     

The influence of geological factors on radon risk in groundwater and dwellings in the region of Amarante (Northern Portugal)

The region of Amarante (Northern Portugal) is composed of Hercynian tardi-tectonics granites and Paleozoic metasediments. Petrographic observations and SEM studies show that uranium is mainly contained within the rock in heavy accessory minerals such as apatite, zircon, monazite, uraninite, thorite and thorianite. The geological, geochemical and radiological data obtained suggest that the radon concentrations in dwellings of the studied area are mainly related with the uranium content of the rocks. Indeed, the highest contents were observed in granite AT2 of Padronelo (18.2 ppm) and the granite AT1 of Telões (10.3 ppm), with metasediments showing much lower uranium contents of 1.6 ppm; radon concentrations were evaluated in dwellings, using CR-39 passive detectors, and the results obtained in winter conditions suggest that the most productive geological units are the granites AT2 and AT1, with geometric means of 430 and 220 Bq/m³, respectively, while the metasediments show the lowest value of 85 Bq/m³. Some moderate radiometric anomalies, where uranium contents can double typical background values, were found in relation with specific fault systems of the region affecting granitic rocks, thus increasing radon risk; this is an indication of uranium mobility, likely resulting from the leaching of primary mineral supports as uraninite. Groundwater radionuclide contents show a wide range of results, with the highest activities related with granitic lithologies: 2,295 Bq/l for radon, 0.83 Bq/l for gross α and 0.71 Bq/l for gross β, presenting metasediments much lower values, in good agreement with other results obtained. Absorbed dose measured with gamma spectrometers in direct contact with the rocks is directly related with the uranium contents of the rocks, and thus works as a fast proxy for radon risk. It is concluded that radon risk is moderate to high in the granitic areas of the Amarante region and low in the metasediments of the same region.     

Amino acid analyses of type 3 chondrites Colony,Ornans, Chainpur,and Bishunpur

Abstract– The CO3s Colony and Ornans and LL3s Chainpur and Bishunpur were analyzed for the first time for amino acids using gas chromatography–mass spectrometry (GC‐MS). Type 3 chondrites have relatively unaltered metamorphic and petrological histories. Chainpur was the most amino acid rich of the four type 3 chondrites with a total amino acid abundance of 3330 parts per billion (ppb). The other type 3 chondrites had total amino acid abundances that ranged from 660 to 1110 ppb. A d /l ratio of <0.7 for all proteic amino acids suggests at least some amino acid terrestrial contamination. However, a small fraction of indigenous extraterrestrial amino acids cannot be excluded because of the presence of the nonprotein amino acid α‐aminoisobutyric acid (α‐AIB), and unusually high relative abundances (to glycine) of β‐alanine and γ‐ABA. The comparisons between the free and total amino acid contents of the samples also indicate a low free/total amino acid ratio (ranging from about 1:4 in CO chondrites to about 1:50 in Chainpur), which indicate that amino acids are present mainly in the bound form and were made detectable after acid hydrolysis.     

Multi-scale approach using remote sensing images to characterize the iron deposit N1 influence areas in Carajás Mineral Province (Brazilian Amazon)

Mining activities cause a wide range of changes to the environment, substantially affecting both the physical and biological environmental sectors. In the Carajás Mineral Province, located in the Amazon rainforest, environmental regulations tend to be more rigorous, due to the fragility of the environment in which large iron deposits are found. The characterization of the impact of mining on environment considers: the type and extent of the impact, the physical chemistry differences and similarities of the mineral deposits, the deposit size, the adopted mining process, and the environment (both natural and economic) in which the mining process was developed. Remote sensing technology is utilized in this study, in particular, the use of ortho-aerial photograph, and optical and radar images with distinct spatial resolution. These permit the elaboration in synoptic maps, multi-scale and dynamic, of the changes wrought upon the environment: deforestation, removal of vegetation cover, topographic surface and landscape alteration, and slope instabilities among others. In this aspect, determining the extent of influence of the mining activity is directly tied to the characterization of its impact on various natural systems at the observed scale, and not by simply defining a predetermined Euclidean distance. The results showed that remote sensing technology, optical and radar images, proved to be efficient in the study of environmental information and the areas of influence on the semi-regional and local scales in the Amazon forest.     

Estimation of the Rock Deformation Modulus and RMR Based on Data Mining Techniques

In this work Data Mining tools are used to develop new and innovative models for the estimation of the rock deformation modulus and the Rock Mass Rating (RMR). A database published by Chun et al. (Int J Rock Mech Min Sci 46:649–658, 2008) was used to develop these models. The parameters of the database were the depth, the weightings of the RMR system related to the uniaxial compressive strength, the rock quality designation, the joint spacing, the joint condition, the groundwater condition and the discontinuity orientation adjustment, the RMR and the deformation modulus. As a modelling tool the R program environment was used to apply these advanced techniques. Several algorithms were tested and analysed using different sets of input parameters. It was possible to develop new models to predict the rock deformation modulus and the RMR with improved accuracy and, additionally, allowed to have an insight of the importance of the different input parameters.