Bioaccumulation of heavy metals in <Emphasis Type="Italic">Limnobium laevigatum</Emphasis> and <Emphasis Type="Italic">Ludwigia peploides</Emphasis>: their phytoremediation potential in water contaminated with heavy metals

Contamination with heavy metals in surface and groundwater is a threat to human health and ecosystems. Due to this, the need arises to remediate water polluted through ecological and profitable technologies, such as phytoremediation. The objective of the work was to evaluate the concentration of lead (Pb) and zinc (Zn) in the floating macrophytes Limnobium laevigatum and Ludwigia peploides, after being exposed to contaminated water experimentally. In this way to be able to determine if these plants have mechanisms that allow them to accumulate the metals in the roots and to perform the translocation of these to different vegetative organs, L. laevigatum and L. peploides were placed in solutions contaminated with Pb ([Pb]?=?5 mg/l) and Zn ([Zn]?=?20 mg/l). The concentrations of metals in water, root and leaf samples were evaluated as a function of time (0, 1, 2 and 4 days). The determination of the metals was performed by the atomic absorption spectrophotometry technique. After 4 days of exposure to Pb and Zn, the plants showed high metal removal efficiencies of water, more to 70% in all cases. Pb was accumulated fundamentally by roots, while Zn was accumulated more in the leaves. In addition, the bioconcentration and translocation factors for each metal were calculated.     

Science-based approach for credible accounting of mitigation in managed forests

Background

The credibility and effectiveness of country climate targets under the Paris Agreement requires that, in all greenhouse gas (GHG) sectors, the accounted mitigation outcomes reflect genuine deviations from the type and magnitude of activities generating emissions in the base year or baseline. This is challenging for the forestry sector, as the future net emissions can change irrespective of actual management activities, because of age-related stand dynamics resulting from past management and natural disturbances. The solution implemented under the Kyoto Protocol (2013–2020) was accounting mitigation as deviation from a projected (forward-looking) “forest reference level”, which considered the age-related dynamics but also allowed including the assumed future implementation of approved policies. This caused controversies, as unverifiable counterfactual scenarios with inflated future harvest could lead to credits where no change in management has actually occurred, or conversely, failing to reflect in the accounts a policy-driven increase in net emissions. Instead, here we describe an approach to set reference levels based on the projected continuation of documented historical forest management practice, i.e. reflecting age-related dynamics but not the future impact of policies. We illustrate a possible method to implement this approach at the level of the European Union (EU) using the Carbon Budget Model.

Results

Using EU country data, we show that forest sinks between 2013 and 2016 were greater than that assumed in the 2013–2020 EU reference level under the Kyoto Protocol, which would lead to credits of 110–120 Mt CO₂/year (capped at 70–80 Mt CO₂/year, equivalent to 1.3% of 1990 EU total emissions). By modelling the continuation of management practice documented historically (2000–2009), we show that these credits are mostly due to the inclusion in the reference levels of policy-assumed harvest increases that never materialized. With our proposed approach, harvest is expected to increase (12% in 2030 at EU-level, relative to 2000–2009), but more slowly than in current forest reference levels, and only because of age-related dynamics, i.e. increased growing stocks in maturing forests.

Conclusions

Our science-based approach, compatible with the EU post-2020 climate legislation, helps to ensure that only genuine deviations from the continuation of historically documented forest management practices are accounted toward climate targets, therefore enhancing the consistency and comparability across GHG sectors. It provides flexibility for countries to increase harvest in future reference levels when justified by age-related dynamics. It offers a policy-neutral solution to the polarized debate on forest accounting (especially on bioenergy) and supports the credibility of forest sector mitigation under the Paris Agreement.

     

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.     

The Effect of Key Parameters on the Strength of a Dispersive Soil Stabilized with Sustainable Binders

Geotechnical and Geological Engineering - Dispersive soils are susceptible to phenomena of internal and external erosion when in contact with relatively pure water due to its particle’s...     

Modelling size effect on rock aggregates strength using a DEM bonded-cell model

Empirical evidence has shown that particle breakage affects the mechanical behaviour of granular materials. The source of this mechanism takes place at the particle scale, and the main consequence on the macromechanical behaviour is increasing compressibility. Due to the inverse correlation between particle size and particle crushing strength, coarse rockfill materials are particularly vulnerable to mechanical degradation due to particle breakage. However, such coarse materials do not fit in standard laboratory devices, and the alternative of large sample testing is usually unavailable or too expensive. Alternatively, recent works have proposed multi-scale approaches using the discrete element method (DEM) to carry out numerical testing of coarse crushable materials, although few studies have focused on size effects. This article presents the application of a DEM bonded-cell model to study particle size-strength correlation on angular rock aggregates. Each particle is modelled by a cluster of perfectly rigid polyhedral cells with Mohr–Coulomb contact law. Constant cell density within particles implies that the presence of potential fragmentation planes increases with size. Therefore, particle strength decreases with size. A comprehensive sensitivity analysis was carried out through 1477 particle crushing simulations in a given particle size. Based on published experimental data on calcareous rock aggregates, part of the simulations were used for calibration, and 97 additional simulations of a coarser size fraction were performed for validation. The results show a good agreement with the empirical data in terms of size effect and data scatter through Weibull statistics.

     

EXERCISE IN DOWNSCALING ON SEA SURFACE TEMPERATURE ALONG CHINESE COAST

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Exercise in downscaling on sea surface temperature along Chinese coast

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Towards new applications of underwater photogrammetry for investigating coral reef morphology and habitat complexity in the Myeik Archipelago,Myanmar

Photogrammetry represents a non-destructive, cost-effective tool for coral reef monitoring, able to integrate traditional remote sensing techniques and support researchers’ work. However, its application to submerged habitats is still in early stage. We present new ways to employ Structure from Motion techniques to infer properties of reef habitats. In particular, we propose the use of Digital Surface Models and Digital Terrain Models for assessing coral colonies extension and height and discriminating between seabed and coral cover. Such information can be coupled with digital rugosity estimates to improve habitat characterization. DTM, DSM and orthophotos were derived and used to compute a series of metrics like coral morphologies, reef topography, coral cover and structural complexity. We show the potentialities offered by underwater photogrammetry and derived products to provide useful basic information for marine habitat mapping, opening the possibility to extend these methods for large-scale assessment and monitoring of coral reefs.     

X-ray activity from different types of stars

X-ray emission is an important indicator of stellar activity. In this paper, we study stellar Xray activity using the XMM-Newton and LAMOST data for different types of stars. We provide a sample including 1259 X-ray-emitting stars, of which 1090 have accurate stellar parameter estimations. Our sample size is much larger than those used in previous works. We find a bimodal distribution of the X-ray to optical flux ratio(log(fX/fV)) for G and K stars. We interpret that this bimodality is due to two subpopulations with different coronal heating rates. Furthermore, using the full widths at half maxima calculated from Hα and Hβ lines, we show that these stars in the inactive peaks have smaller rotational velocities. This is consistent with the magnetic dynamo theory that presumes stars with low rotational velocities have low levels of stellar activity. We also examine the correlation between log(fX/fV) and luminosity of the excess emission in the Hα line, and find a tight relation between the coronal and chromospheric activity indicators.     

Area usage estimation and spatiotemporal variability in distribution patterns of southern right whales,Eubalaena australis,of southern Brazil

Southern right whales—Eubalaena australis (Desmoulins, 1822)—migrate seasonally from high‐latitude feeding grounds to coastal breeding and calving grounds at lower latitudes such as the southern coast of Brazil. Understanding how these whales are distributed along the coast is important for monitoring their postwhaling recovery and defining management strategies. In this study, we applied Kernel density estimators to aerial survey data to determine main occurrence and concentration areas of right whales in southern Brazil and investigate inter‐ and intra‐annual distribution patterns between 2003 and 2012. Our results show considerable variation in area usage within and among years, and changes in the general distribution pattern of right whales in the last years of the study. Intra‐annually, higher concentration area tended to expand from July to September and decrease in November. Some areas stood out as high‐density areas for right whales: Ribanceira/Ibiraquera, Itapirubá Sul/Sol, and from Arroio to Gaivota. Some evidences also suggest preferential areas for mother–calf pairs. The higher concentration area of right whales in southern Brazil was estimated at 52,541 km² and the occurrence area was 682.69 km², which is the whole study area. As right whale distribution in the region is likely expanding due to this population's current recovery, our study provides essential information for management plan of the Right Whale Environmental Protection Area.