Cadmium accumulation and its effect on the in vitro growth of woody fleabane and mycorrhized white birch

The effect of Cd on woody fleabane (Dittrichia viscosa (L.) Greuter) and white birch (Betula celtiberica Rothm. & Vasc.) was examined. Woody fleabane and white birch were grown in vitro in Murashige, T., Skoog, F., [1962. A revised medium for rapid growth and bioassays with tobacco tissue cultures. Physiol. Plant. 15, 473-479] (MS) plus Cd (10 mg Cd kg(-1)) and except for root length in white birch, plant development was inhibited when Cd was added. Cd accumulation in above-ground tissues showed differences among clones, reaching 1300 and 463 mg Cd kg(-1) dry wt. in selected clones of woody fleabane and white birch, respectively. Tolerance of Paxillus filamentosus (Scop) Fr. to Cd was also examined before mycorrhization. Plants of mycorrhized white birch grown in the presence of Cd had a better development and accumulated more Cd in their shoots than the non-mycorrhized ones. The use of selected clones of woody fleabane and the mycorrhization of white birch enhance extraction efficiency from contaminated soils in phytoremediation programs.     

Effect of copper on soil functional stability measured by relative soil stability index (RSSI) based on two enzyme activities

Copper can affect essential processes in soils, often for long periods. Enzyme activity is considered a sensitive indicator to evaluate soil health and the potential toxic impact of a soil contaminant. Nevertheless, there is heterogeneity in the responses from enzyme activity assays because of the influence of pH and other physicochemical parameters on both enzyme activity and metal speciation. This leads to complications when comparing soils and limits the validity of the results. To overcome these problems, this paper evaluates resistance and recovery, quantified by using a relative soil stability index (RSSI), of the beta-glucosidase and protease activities towards an additional heat disturbance (17 h at 60 degrees C) in soils where soil organic matter, pH and Cu content were modified in a factorial setup. Chemical analyses (dissolved Cu, pCu(2+), dissolved organic carbon, pH) were performed both before the heat-perturbation and after the enzyme activity monitoring period. Results show that soil pH did not interfere with the RSSI scores of both enzymes. beta-glucosidase RSSI scores were scarcely affected by copper, making it inappropriate for evaluating copper-induced stress to soils. Protease activity shows stimulations of up to 2.5 times the activity of the unperturbed control in uncontaminated samples only. Thus, the protease RSSI score seems a good indicator for soil health relative to copper contamination given that all samples were affected by the presence of copper and high correlations were observed between RSSI scores and the different copper forms.     

Impact of metal stress on the production of secondary metabolites in <Emphasis Type="Italic">Pteris vittata</Emphasis> L. and associated rhizosphere bacterial communities

Plants adapt to metal stress by modifying their metabolism including the production of secondary metabolites in plant tissues. Such changes may impact the diversity and functions of plant associated microbial communities. Our study aimed to evaluate the influence of metals on the secondary metabolism of plants and the indirect impact on rhizosphere bacterial communities. We then compared the secondary metabolites of the hyperaccumulator Pteris vittata L. collected from a contaminated mining site to a non-contaminated site in Vietnam and identified the discriminant metabolites. Our data showed a significant increase in chlorogenic acid derivatives and A-type procyanidin in plant roots at the contaminated site. We hypothesized that the intensive production of these compounds could be part of the antioxidant defense mechanism in response to metals. In parallel, the structure and diversity of bulk soil and rhizosphere communities was studied using high-throughput sequencing. The results showed strong differences in bacterial composition, characterized by the dominance of Proteobacteria and Nitrospira in the contaminated bulk soil, and the enrichment of some potential human pathogens, i.e., Acinetobacter, Mycobacterium, and Cupriavidus in P. vittata’s rhizosphere at the mining site. Overall, metal pollution modified the production of P. vittata secondary metabolites and altered the diversity and structure of bacterial communities. Further investigations are needed to understand whether the plant recruits specific bacteria to adapt to metal stress.     

Carbon and nitrogen stocks and nitrogen mineralization in organically managed soils amended with composted manures

The use of composted manures and of legumes in crop rotations may control the quality and quantity of soil organic matter and may affect nutrient retention and recycling. We studied soil organic C and N stocks and N mineralization in organically and conventionally managed dryland arable soils. We selected 13 extensive organic fields managed organically for 10 yr or more as well as adjacent fields managed conventionally. Organic farmers applied composted manures ranging from 0 to 1380 kg C ha yr and incorporated legumes in crop rotations. In contrast, conventional farmers applied fresh manures combined with slurries and/or mineral fertilizers ranging from 200 to 1900 kg C ha yr and practiced a cereal monoculture. Despite the fact that the application of organic C was similar in both farming systems, organically managed soils showed higher C and similar N content and lower bulk density than conventionally managed soils. Moreover, organic C stocks responded to the inputs of organic C in manures and to the presence of legumes only in organically managed soils. In contrast, stocks of organic N increased with the inputs of N or C in both farming systems. In organically managed soils, organic N stocks were less mineralizable than in conventional soils. However, N mineralization in organic soils was sensitive to the N fixation rates of legumes and to application rate and C/N ratio of the organic fertilizers.     

Spatial Prediction of Ground Subsidence Susceptibility Using an Artificial Neural Network

Ground subsidence in abandoned underground coal mine areas can result in loss of life and property. We analyzed ground subsidence susceptibility (GSS) around abandoned coal mines in Jeong-am, Gangwon-do, South Korea, using artificial neural network (ANN) and geographic information system approaches. Spatial data of subsidence area, topography, and geology, as well as various ground-engineering data, were collected and used to create a raster database of relevant factors for a GSS map. Eight major factors causing ground subsidence were extracted from the existing ground subsidence area: slope, depth of coal mine, distance from pit, groundwater depth, rock-mass rating, distance from fault, geology, and land use. Areas of ground subsidence were randomly divided into a training set to analyze GSS using the ANN and a test set to validate the predicted GSS map. Weights of each factor’s relative importance were determined by the back-propagation training algorithms and applied to the input factor. The GSS was then calculated using the weights, and GSS maps were created. The process was repeated ten times to check the stability of analysis model using a different training data set. The map was validated using area-under-the-curve analysis with the ground subsidence areas that had not been used to train the model. The validation showed prediction accuracies between 94.84 and 95.98%, representing overall satisfactory agreement. Among the input factors, “distance from fault” had the highest average weight (i.e., 1.5477), indicating that this factor was most important. The generated maps can be used to estimate hazards to people, property, and existing infrastructure, such as the transportation network, and as part of land-use and infrastructure planning.     

Analysing the influence of different street vegetation on traffic-induced particle dispersion using microscale simulations

Urban vegetation can be viewed as compensation to the environmental drawbacks of urbanisation. However, its ecosystem function is not well-known and, for urban planning, vegetation is mainly considered as an element of urban design. This article argues that planning practice needs to re-examine the impact of vegetation cover in the urban fabric given our evaluation of vegetation's effects on air quality, including the dispersion of traffic-induced particles at street level. Using the three-dimensional microclimate model ENVI-met?, we evaluate these effects regarding the height-to-width ratio of streets flanked by buildings and the vertical and horizontal density of street vegetation. Our results reveal vegetation's effect on particle dispersion through its influence on street ventilation. In general, vegetation was found to reduce wind speed, causing inhibition of canyon ventilation and, consequently, an increase in particle concentrations. Vegetation was also found to reduce wind speed at crown-height and to disrupt the flow field in close vicinity to the canopy. With increasing height-to-width ratio of street canyons, wind speed reduction increases and the disturbance of the flow impacts across a canyon's entire width. We also found that the effect is more pronounced in configurations with poor ventilation, such as the low wind speed, perpendicular inflow direction, and in deep canyons cases.     

Removal of Hydrocarbons from Wastewater Using Treated Bark

ABSTRACT

This paper explores the possibility of removing hydrocarbons (HCs) and trace elements from synthetic and industrial effluents using treated bark as biosorbent. Coniferous bark was treated either chemically (Tc) or biologically (Tb) to eliminate soluble organic compounds of bark. The removal efficiency (RE) of the HCs from a synthetic oil-water mixture containing spent diesel motor oil exceeds 95% using 2 g/L of treated bark mixed with a synthetic oil-water mixture containing 2 g/L of spent oil. Under these conditions, the retention capacity (RC) was ~1 g HC/g dry substrate. The sorption reaction seems to be quasi-instantaneous, and the retention capacity of spent oil on treated bark increases as the temperature augments. This implies that the retention mechanism is related to the capillary action.

Results of Fourier transform infrared (FTIR) spectros-copy indicate that spent oil is mainly composed of al-kanes. They also suggest that no chemical bonds between

Tc and spent oil were established. Measurement of the surface tension of spent oil and the wetting index of the bark suggests that only spent oil will be retained by the substrate. Treatment of an industrial effluent containing 14.4 g/L of total HCs was performed using Tc. It was possible to remove 97% of HCs and retain some trace elements such as Al, Ca, Fe, Mg, S, and so on.     

Removal of PCDD/F from Incinerator Flue Gases by Entrained-Phase Adsorption

Abstract

The emission abatement of polychlorinated dioxins and furans (PCDD/F) issued from municipal solid waste incineration is growing in importance because of more stringent emission standards and general concern about their toxic characteristics. These substances cannot be separated by conventional gas cleanup processes but are successfully removed through adsorption onto carbonaceous materials. The simplest technique is the entrained-phase injection of pulverized adsorbents in the flue gas, followed by fabric filter separation. The various related techniques are briefly reviewed here. Operating conditions and results obtained from Flemish MSWIs are given. The results illustrate the excellent overall removal efficiency. Furans are adsorbed to a slightly higher extent than dioxins.

PCDD/F removal by carbonaceous adsorbents is thereafter modeled from first principles for the contribution of both entrained-phase (η₁) and cake filtration (η₂) to the overall efficiency (η_T). Application of the model equations and comparison of measured and predicted overall efficiencies for the Flemish municipal solid waste incinerators (MSWIs) demonstrate that the approach is meaningful and that the dominant parameters are the operating temperature, the dosage and activity of adsorbent, and the fraction of adsorbent in the filter cake. The model equations enable the MSWI operators to predict the adsorption efficiencies for any combination of operating parameters and to assess the sensitivity of the process to varying operating conditions.     

Utilization of long duration high-volume sampling coupled to SPME-GC-MS/MS for the assessment of airborne pesticides variability in an urban area (Strasbourg,France) during agricultural application

Atmospheric samples have been collected between 14 March and 12 September 2012 on a 2-week basis (15 days of sampling and exchange of traps each 7 days) in Strasbourg (east of France) for the analysis of 43 pesticides. Samples (particle and gas phases) were separately extracted using Accelerated Solvent Extraction (ASE) and pre-concentrated by Solid Phase Micro-Extraction (SPME) before analysis by gas chromatography coupled to tandem mass spectrometry (GC-MS/MS). Four SPME consecutive injections at distinct temperatures were made in order to increase the sensitivity of detection for the all monitored pesticides. Currently used detected pesticides can be grouped in four classes; those used in maize crops (acetochlor, benoxacor, dicamba, s-metolachlor, pendimethalin, and bromoxynil), in cereal crops (benoxacor, chlorothalonil, fenpropimorph, and propiconazole), in vineyards (tebuconazole), and as herbicides for orchards, meadows of green spaces (2,4-MCPA, trichlopyr). This is in accordance with the diversity of crops found in the Alsace region and trends observed are in accordance with the period of application of these pesticides. Variations observed permit also to demonstrate that the long time sampling duration used in this study is efficient to visualize temporal variations of airborne pesticides concentrations. Then, long time high-volume sampling could be a simple method permitting atmospheric survey of atmospheric contamination without any long analysis time and consequently low cost.     

Range contraction and loss of genetic variation of the Pyrenean endemic newt <Emphasis Type="Italic">Calotriton asper</Emphasis> due to climate change

Many studies have identified climate warming to be among the most important threats to biodiversity. Climate change is expected to have stronger effects on species with low genetic diversity, ectothermic physiology, small ranges, low effective populations sizes, specific habitat requirements and limited dispersal capabilities. Despite an ever-increasing number of studies reporting climate change-induced range shifts, few of these have incorporated species’ specific dispersal constraints into their models. Moreover, the impacts of climate change on genetic variation within populations and species have rarely been assessed, while this is a promising direction for future research. Here we explore the effects of climate change on the potential distribution and genetic variation of the endemic Pyrenean newt Calotriton asper over the period 2020–2080. We use species distribution modelling in combination with high-resolution gridded climate data while subsequently applying four different dispersal scenarios. We furthermore use published data on genetic variation of both mtDNA and AFLP loci to test whether populations with high genetic diversity (nucleotide diversity and expected heterozygosity) or evolutionary history (unique haplotypes and K clusters) have an increased extinction risk from climate change. The present study indicates that climate change drastically reduces the potential distribution range of C. asper and reveals dispersal possibilities to be minimal under the most realistic dispersal scenarios. Despite the major loss in suitable climate, the models highlight relatively large stable areas throughout the species core distribution area indicating persistence of populations over time. The results, however, show a major loss of genetic diversity and evolutionary history. This highlights the importance of accounting for intraspecific genetic variation in climate change impact studies. Likewise, the integration of species’ specific dispersal constraints into projections of species distribution models is an important step to fully explore the effects of climate change on species potential distributions.