Comparison of specific versus literature species sensitivity distributions for herbicides risk assessment

Species sensitivity distributions (SSDs) are an important predictive tool in risk assessment. Usually, literature data are used to build SSDs that are mostly based on planktonic species. But, to get adequate protective thresholds for environmental communities, one could argue that SSD should be built on ecotoxicological data obtained from species found in the ecosystem that should be protected. This is particularly true when benthic algae are of concern. Due to the lack of literature data, building SSD on benthic microalgae is difficult. This paper aims in comparing SSDs, and thus protective thresholds (hazardous concentration that affects 5 % of the species of a community, HC₅), built on ecotoxicological data obtained (1) from literature and (2) with specific bioassays on benthic diatoms from a lake. Thresholds were derived for protection against four herbicides separately and for a mixture of them. Sensitivity data obtained from literature were statistically lower than the specific data for all herbicides: Species tested in the literature were usually more sensitive (mainly chlorophytes), leading to more protective lower HC₅. The HC₅ thresholds (literature or specific) derived for protection against the mixture were also compared to the observed sensitivity of an assemblage of benthic diatom species exposed to an increasing range of herbicide mixture concentrations. We observed that one species within the assemblage (Fragilaria rumpens) was affected at a concentration below both the literature and the specific HC₅ thresholds.     

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.     

The use of biomass production and allometric models to estimate carbon sequestration of <Emphasis Type="Italic">Jatropha curcas</Emphasis> L. plantations in western Burkina Faso

The topic of carbon sequestration in plants has received much attention recently due to concerns about global climate change, which is being exacerbated by deforestation. In the early days of the global bioenergy boom, the private sector and non-government organizations enthusiastically promoted the planting of Jatropha curcas L. as a key candidate shrub species for the production of bioenergy in West Africa. This study investigates the aboveground biomass production and carbon sequestration potential of J. curcas, which is already widely cultivated for the production of oil seeds, biodiesel and biokerosene. The specific objective is to use a destructive method to develop allometric prediction equations of the aboveground biomass production of J. curcas plantations. 38 J. curcas shrubs were harvested and weighed in order to estimate biomass production. These data were used to develop allometric equations for the estimation of wood, leaf and total aboveground biomass production. The best-fit models found for estimating shrub component biomass and total aboveground biomass production were of the power form. All of the regression equations relating the prediction of leaf biomass, wood biomass and total aboveground biomass with J. curcas diameter at 20 cm above the ground (D) were statistically significant (p < 0.001) and also presented the highest goodness of fit (high R ²). The aboveground biomass carbon content was estimated using the ash method. Carbon content in leaves and wood was, respectively, 48 and 54 %. The current established allometric equations can be helpful to provide a rapid estimation of the aboveground biomass and C stock for J. curcas biofuel projects in semi-arid conditions.     

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.     

Modeling of methane oxidation in landfill cover soil using an artificial neural network

Knowing the fraction of methane (CH₄) oxidized in landfill cover soils is an important step in estimating the total CH₄ emissions from any landfill. Predicting CH₄ oxidation in landfill cover soils is a difficult task because it is controlled by a number of biological and environmental factors. This study proposes an artificial neural network (ANN) approach using feedforward backpropagation to predict CH₄ oxidation in landfill cover soil in relation to air temperature, soil moisture content, oxygen (O₂) concentration at a depth of 10 cm in cover soil, and CH₄ concentration at the bottom of cover soil. The optimum ANN model giving the lowest mean square error (MSE) was configured from three layers, with 12 and 9 neurons at the first and the second hidden layers, respectively, log-sigmoid (logsig) transfer function at the hidden and output layers, and the Levenberg-Marquardt training algorithm. This study revealed that the ANN oxidation model can predict CH₄ oxidation with a MSE of 0.0082, a coefficient of determination (R ²) between the measured and predicted outputs of up to 0.937, and a model efficiency (E) of 0.8978. To conclude, further developments of the proposed ANN model are required to generalize and apply the model to other landfills with different cover soil properties.

Implications:

To date, no attempts have been made to predict the percent of CH₄ oxidation within landfill cover soils using an ANN. This paper presents modeling of CH₄ oxidation in landfill cover soil using ANN based on field measurements data under tropical climate conditions in Malaysia. The proposed ANN oxidation model can be used to predict the percentage of CH₄ oxidation from other landfills with similar climate conditions, cover soil texture, and other properties. The predicted value of CH₄ oxidation can be used in conjunction with the Intergovernmental Panel on Climate Change (IPCC) First Order Decay (FOD) model by landfill operators to accurately estimate total CH₄ emission and how much it contributes to global warming.     

Variation patterns in individual fish responses to chemical stress among estuaries, seasons and genders: the case of the European flounder (Platichthys flesus) in the Bay of Biscay

The objective was to describe and model variation patterns in individual fish responses to contaminants among estuaries, season and gender. Two hundred twenty-seven adult European flounders were collected in two seasons (winter and summer) in four estuaries along the Bay of Biscay (South West France), focusing on a pristine system (the Ster), vs. three estuaries displaying contrasted levels of contaminants (the Vilaine, Loire and Gironde). Twenty-three variables were measured by fish, considering the load of contaminants (liver metals, liver and muscle persistent organic pollutants, muscle polycyclic aromatic hydrocarbons); the gene expression (Cyt C oxydase, ATPase, BHMT, Cyt P450 1A1, ferritin); the blood genotoxicity (Comet test); and liver histology (foci of cellular alteration–tumour, steatosis, inflammation, abnormal glycogen storage). Canonical redundancy analysis (RDA) was used to model these variables using gender, season and estuary of origin as explanatory variables. The results underlined the homogeneity of fish responses within the pristine site (Ster) and more important seasonal variability within the three contaminated systems. The complete model RDA was significant and explained 35 % of total variance. Estuary and season respectively explained 30 and 5 % of the total independent variation components, whilst gender was not a significant factor. The first axis of the RDA explains nearly 27 % of the total variance and mostly represents a gradient of contamination. The links between the load of contaminants, the expression of several genes and the biomarkers were analysed considering different levels of chemical stress and a possible multi-stress, particularly in the Vilaine estuary.     

Meta-analysis of environmental contamination by phthalates

Phthalate acid esters (PAE), commonly named phthalates, are toxics classified as endocrine-disrupting compounds; they are primarily used as additives to improve the flexibility in polyvinyl chloride. Many studies have reported the occurrence of phthalates in different environmental matrices; however, none of these studies has yet established a complete overview for those compounds in the water cycle within an urban environment. This review summarizes PAE concentrations for all environmental media throughout the water cycle, from atmosphere to receiving waters. Once the occurrences of compounds have been evaluated for each environmental compartment (urban wastewater, wastewater treatment plants, atmosphere, and the natural environment), we reviewed data in order to identify the fate of PAE in the environment and establish whether geographical and historical trends exist. Indeed, geographical and historical trends appear between Europe and other countries such as USA/Canada and China, however they remain location dependent. This study aimed at identifying both the correlations existing between environmental compartments and the processes influencing the fate and transport of these contaminants into the environment. In Europe, the concentrations measured in waterways today represent the background level of contamination, which provides evidence of a past diffuse pollution. In contrast, an increasing trend has actually been observed for developing countries, especially for China.     

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.     

Rapid measurement of the yield stress of anaerobically-digested solid waste using slump tests

The anaerobic digestion of solid waste is usually performed using dry or semi-dry technology. Incoming waste and fermenting digestate are pasty media and thus, at the industrial scale, their suitability for pumping and mixing is a prerequisite at the industrial scale. However, their rheology has been poorly characterised in the literature because there is no suitable experimental system for analysing heterogeneous media composed of coarse particles. We have developed a practical rheometrical test, a “slump test”, for the analysis of actual digested solid waste. It makes it possible to estimate yield stress from the final slump height. From the slump behavior, we conclude that digestates behave as visco-elastic materials. The yield stress of different digested waste was measured between 200 and 800 Pa. We show that the media containing smaller particles or with higher moisture content are characterised by smaller yield stresses. This study thus demonstrates the impact of the origin of the digestate on the yield stress.