Biosurfactants during in situ bioremediation: factors that influence the production and challenges in evalution

Research on the influence of biosurfactants on the efficiency of in situ bioremediation of contaminated soil is continuously growing. Despite the constant progress in understanding the mechanisms involved in the effects of biosurfactants, there are still many factors that are not sufficiently elucidated. There is a lack of research on autochthonous or exogenous microbial metabolism when biostimulation or bioaugmentation is carried out to produce biosurfactants at contaminated sites. In addition, studies on the application of techniques that measure the biosurfactants produced in situ are needed. This is important because, although the positive influence of biosurfactants is often reported, there are also studies where no effect or negative effects have been observed. This review aimed to examine some studies on factors that can improve the production of biosurfactants in soils during in situ bioremediation. Moreover, this work reviews the methodologies that can be used for measuring the production of these biocomposts. We reviewed studies on the potential of biosurfactants to improve the bioremediation of hydrocarbons, as well as the limitations of methods for the production of these biomolecules by microorganisms in soil.     

Distribution of genetic elements associated with antibiotic resistance in treated and untreated animal husbandry waste and wastewater

Environmental Science and Pollution Research - Animal breeding for meat production based on swine, cattle, poultry, and aquaculture is an activity that generates several impacts on the environment,...     

Phosphorus and sulfur in a tropical soil and their effects on growth and selenium accumulation in Leucaena leucocephala (Lam.) de Wit

Selenium (Se) is an essential metalloid element for mammals. Nonetheless, both deficiency and excess of Se in the environment are associated with several diseases in animals and humans. Here, we investigated the interaction of Se, supplied as selenate (Se⁺⁶) and selenite (Se⁺⁴), with phosphorus (P) and sulfur (S) in a weathered tropical soil and their effects on growth and Se accumulation in Leucaena leucocephala (Lam.) de Wit. The P-Se interaction effects on L. leucocephala growth differed between the Se forms (selenate and selenite) supplied in the soil. Selenate was prejudicial to plants grown in the soil with low P dose, while selenite was harmful to plants grown in soil with high P dose. The decreasing soil S dose increased the toxic effect of Se in L. leucocephala plants. Se tissue concentration and total Se accumulation in L. leucocephala shoot were higher with selenate supply in the soil when compared with selenite. Therefore, selenite proved to be less phytoavailable in the weathered tropical soil and, at the same time, more toxic to L. leucocephala plants than selenate. Thus, it is expected that L. leucocephala plants are more efficient to phytoextract and accumulate Se as selenate than Se as selenite from weathered tropical soils, for either strategy of phytoremediation (decontamination of Se-polluted soils) or purposes of biofortification for animal feed (fertilization of Se-poor soils).

     

Microsatellite data reveal fine genetic structure in male Guiana dolphins (<Emphasis Type="Italic">Sotalia guianesis)</Emphasis> in two geographically close embayments at south-eastern coast of Brazil

A large macrogeographic differentiation has been observed among Sotalia guianensis populations along the South American coast. However, no genetic structure has been detected so far in closely distributed populations of this species, even though it has been observed in other cetaceans. Here, we examined the fine scale population structure for the largest populations of S. guianensis inhabiting Sepetiba and Paraty embayments at the south-eastern coast of Rio de Janeiro, Brazil. Analysis of mitochondrial DNA (mtDNA) control region sequences failed to detect variability among sequences. Conversely, evidence of significant male population structure was found on the basis of ten nuclear microsatellite loci. Surprisingly, the microsatellite markers were able to distinguish between individuals from the two embayments located 60 km apart. The results suggest that differences in habitat type and behavioral specializations are likely to explain the patterns of genetic structure. These findings should provide baselines for the management of communities exposed to increasing human-driven habitat loss.     

A conceptual framework for analyzing deltas as coupled social–ecological systems: an example from the Amazon River Delta

At the nexus of watersheds, land, coastal areas, oceans, and human settlements, river delta regions pose specific challenges to environmental governance and sustainability. Using the Amazon Estuary-Delta region (AD) as our focus, we reflect on the challenges created by the high degree of functional interdependencies shaping social–ecological dynamics of delta regions. The article introduces the initial design of a conceptual framework to analyze delta regions as coupled social–ecological systems (SES). The first part of the framework is used to define a delta SES according to a problem and/or collective action dilemma. Five components can be used to define a delta SES: social–economic systems, governance systems, ecosystems-resource systems, topographic-hydrological systems, and oceanic-climate systems. These components are used in association with six types of telecoupling conditions: socio-demographic, economic, governance, ecological, material, and climatic-hydrological. The second part of the framework presents a strategy for the analysis of collective action problems in delta regions, from sub-delta/local to delta to basin levels. This framework is intended to support both case studies and comparative analysis. The article provides illustrative applications of the framework to the AD. First, we apply the framework to define and characterize the AD as coupled SES. We then utilize the framework to diagnose an example of collective action problem related to the impacts of urban growth, and urban and industrial pollution on small-scale fishing resources. We argue that the functional interdependencies characteristic of delta regions require new approaches to understand, diagnose, and evaluate the current and future impacts of social–ecological changes and potential solutions to the sustainability dilemmas of delta regions.     

Composites Produced from Natural Rubber and Chrome-Tanned Leather Wastes: Evaluation of their In Vitro Toxicological Effects for Application in Footwear and Textile Industries

A new composite has been developed from natural rubber and chrome-tanned leather waste for use in footwear and textile industries. The contribution of this material to environmental quality and sustained development should be highligh because chrome tanned leather wastes, a major environmental problem, can be recycled. However, the safety of this new material for human use is questionable, as it is already well reported in the literature that chromium, particularly in its hexavalent oxidation state, can be genotoxic and carcinogenic to living beings. Thus, the aim of this study was to evaluate in vitro biocompatibility of this composite material for possible use in the footwear and textile industries, through cytotoxicity, cell adhesion, and genotoxicity tests. Inductively coupled plasma optical emission spectrometry (ICP-OES) was used to measure both concentrations of total and hexavalent chromium. Based on the findings, it was concluded that the composite exhibits low levels of cytotoxicity and genotoxicity, and possesses favorable properties for initial cell adhesion. Furthermore, it was verified that the composites released low concentrations of chromium and that the predominant species released would be trivalent chromium. The results of the present study open the possibility of the incorporation of solid residues of tanned leather into chromium without necessarily the chromium contained in these residues influences the toxicity and genotoxicity of this new material.     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.