Tape-stripping as a method for measuring dermal exposure to resin acids during wood pellet production

The purpose of this study was to develop a sensitive and specific method for quantifying dermal exposure to the resin acids 7-oxodehydroabietic acid (7-OXO), dehydroabietic acid (DHAA), abietic acid (AA), and pimaric acid (PA). In addition the method was evaluated in occupational settings during production of wood pellets. Tape-strips were spiked with the substances to evaluate the recovery of the acids from the tape. The removal efficiency of the tape was assessed by tape-stripping a specified area on a glass plate spiked with resin acids. The recovery of the acids from human skin in vivo was evaluated by applying acids in methanol onto the skin of volunteers. Occupational dermal exposure to the resin acids was assessed by tape-stripping the skin of workers involved in the production of wood pellets. The resin acids were analyzed by liquid chromatography mass spectrometry (LC-MS). The limit of detection was 15 pg (7-OXO), 150 pg (DHAA), 285 pg (AA) and 471 pg (PA) per injection. The recovery from spiked tapes was in general 100%. The removal efficiency of the tape was 48-101%. Recovery tests from human skin in vivo showed a mean recovery of 27%. Quantifiable amounts of resin acids were observed on four different skin areas with an increase in exposure during a work shift. This study shows that occupational dermal exposure to resin acids can be assessed by tape-stripping and quantified by LC-MS.     

Dynamical Allocation Method of Emission Rights of Pollutants by Viability Constraints Under Tychastic Uncertainty

This study proposes a method of dynamic decentralization by constraints and its associated software. It can be used to allocate pollutant emissions rights among the different polluters such that they achieve both given global and local emission thresholds not to be transgressed. Knowing the maximum growth rates of polluting emissions of each polluter in the worst case, this method provides the rule of a dynamic allocation of pollutant emissions rights as well as the required initial emissions of each polluters assuring that, whatever the growth rates of the emissions below the maximum growth rates, the resulting emissions will be, both globally and locally, under their thresholds. These guaranteed initial emissions supply each polluter with a measure of risk insurance. This problem, formulated as a “tychastic” regulated system with viability constraints, is solved with mathematical and algorithmic tools of viability theory and numerical results obtained by a dedicated software are presented.     

Documentation of bioaerosol concentrations in an indoor composting facility in France

Bioaerosol concentrations were investigated in a totally indoor composting facility processing fermentable household and green wastes to assess their variability. Stationary samples were collected by filtration close to specific composting operations and then were analysed for cultivable mesophilic bacteria, thermophilic bacteria, mesophilic fungi, thermophilic fungi, endotoxins and total airborne bacteria (DAPI-staining). Indoor concentrations exceeded the background levels, between 500 and 5400 EU m(-3) for endotoxins, 10(4) and 10(6) CFU m(-3) for cultivable bacteria and generally below 10(5) CFU m(-3) for airborne cultivable fungi. No significant (p > 0.05) differences were observed between the indoor composting operations. Successive 30 minute bioaerosol samples were collected to investigate the variation of cultivable mesophilic microorganisms over the work shift. Concentrations of mesophilic bacteria and fungi varied up to 1 log unit depending on the time at which they were collected in the day. Total airborne particles, counted using an optical particle counter, were present at up to 10(8) particles m(-3) and several concentration peaks were noted. Values for total airborne bacteria were roughly 70-fold higher than cultivable bacteria. These results raise the question of the sampling strategy (duration of sampling; number of samples to be collected) used in similar studies. They provide new bioaerosol concentration data in a composting facility and suggest that the filtration sampling method might be a useful tool for exposure measurements in that occupational environment.     

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.     

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.     

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.     

Combined effects of deltamethrin, temperature and salinity on oxidative stress biomarkers and acetylcholinesterase activity in the black tiger shrimp (Penaeus monodon)

This study aimed to investigate the interactions of two abiotic factors (temperature and salinity) and deltamethrin (pyrethroid pesticide) exposure on some oxidative stress biomarkers as well as on acetylcholinesterase activity (AChE) in hepatopancreas, gills and muscle of black tiger shrimp (Penaeus monodon). A combination of three temperatures (24, 29 and 34 °C), two salinities (15 and 25 ppt), and the absence or presence of 0.1 μg L⁻¹ deltamethrin was applied on shrimp during 4 d under laboratory conditions. Lipid peroxidation level (LPO) and glutathione S-transferase activity (GST) were not affected by combined effect of temperature, salinity and deltamethrin in any of the studied tissues. Deltamethrin impaired other tested oxidative stress biomarkers, i.e. total glutathione (tGSH), catalase (CAT), glutathione peroxidase (GPx). tGSH level significantly increased in hepatopancreas due to deltamethrin exposure mainly at 34 °C, while pesticide effects on tGSH and CAT activity in gills were influenced by both temperature and salinity. In addition, GPx activity in hepatopancreas decreased after deltamethrin treatment mainly at 24 °C. Finally, AChE in muscle was strongly inhibited by deltamethrin at all tested temperatures and salinities. These novel findings demonstrate that interactions between abiotic factors and a commonly used pesticide exposure should be taken into account when analyzing some widespread biomarkers in black tiger shrimp.     

Fecal coliforms, caffeine and carbamazepine in stormwater collection systems in a large urban area

Water samples from streams, brooks and storm sewer outfall pipes that collect storm waters across the Island of Montréal were analyzed for caffeine, carbamazepine and fecal coliforms. All samples contained various concentrations of these tracers, indicating a widespread sanitary contamination in urban environments. Fecal coliforms and caffeine levels ranged over several orders of magnitude with a modest correlation between caffeine and fecal coliforms (R² value of 0.558). An arbitrary threshold of 400 ng caffeine L⁻¹ allows us to identify samples with an elevated fecal contamination, as defined by more than 200 colony-forming units per 100 mL (cfu 100 mL⁻¹) of fecal coliforms. Low caffeine levels were sporadically related to high fecal coliform counts. Lower levels of caffeine and fecal coliforms were observed in the brooks while the larger streams and storm water discharge points contained over ten times more. The carbamazepine data showed little or no apparent correlation to caffeine. These data suggest that this storm water collection system, located in a highly urbanized urban environment, is widely contaminated by domestic sewers as indicated by the ubiquitous presence of fecal contaminants as well as caffeine and carbamazepine. Caffeine concentrations were relatively well correlated to fecal coliforms, and could potentially be used as a chemical indicator of the level of contamination by sanitary sources. The carbamazepine data was not significantly correlated to fecal coliforms and of little use in this dataset.