The costs,benefits, and limitations of organizational level stress interventions

Models of organizational stress posit that a number of undesirable employee states and behaviors, such as lower levels of well‐being and performance, and higher levels of absence and turnover are caused by organizational stress. It is often suggested that organizational level interventions which aim to reduce stress, such as job redesign, will therefore reduce or eliminate these states and behaviors. This suggestion is, however, based on two unsupportable assertions. The first is that these states and behaviors are caused by organizational stress. While there is some limited evidence for the role of stress, the quality of this evidence is severely compromised by numerous methodological and conceptual problems. The second assertion is that organizational level interventions aimed at changing some of these states and behaviors will actually have an effect, and that these effects will be uniformly positive. However, the available evidence suggests that these interventions often have little or no effect, and where they do have effects, these may be both positive and negative., The implications of this analysis for future work on organizational level stress interventions are discussed. Copyright © 1999 John Wiley & Sons, Ltd.     

Assessment of the detection abilities of monitoring networks for passive tracers at local and regional scales

We propose a method to evaluate the detection abilities of networks used for protection purposes. Such networks are designed for the detection of nuclear, biological or gaseous emissions, without constraint on the source location. Their assigned goal is to have the best chance to detect a threatening emission located anywhere in the vicinity of a domain to protect. Two sensors siting applications are addressed: sensors placed in the surroundings of a facility to protect, or sensors carried by people scattered within a small area. A network protection ability is related both to its detection scope, and to its response time. To assess the performance of such networks, two statistical indicators are therefore designed: the detection probability, computed on a large number of possible source locations, and the saturation time, which is the time when the maximum detection probability has been reached.Simulations are then carried out with the Polyphemus air quality modeling system for many emission scenarios, including 961 possible source locations, various emitted species, and a few representative meteorological situations. This allows to assess the performance of single sensors as well as full networks, and their sensitivity to parameters like meteorological conditions and source characteristics. The emitted quantity and meteorological dispersion are found to be important parameters, whereas the species type does not significantly influence the results. Two network design methods are considered: (1) networks composed of a given number of the “best” sensors according to an indicator, and (2) sensors placed in circles around the protected domain. The networks built with respect to the detection probability show good results with a limited number of sensors, while the saturation time is not reliable enough to build networks. The networks based on circles also show a good performance in the studied cases, provided there is a sufficient number of sensors.     

First Europe-wide correlation analysis identifying factors best explaining the total nitrogen concentration in mosses

In this study, the indicative value of mosses as biomonitors of atmospheric nitrogen (N) depositions and air concentrations on the one hand and site-specific and regional factors which explain best the total N concentration in mosses on the other hand were investigated for the first time at a European scale using correlation analyses. The analyses included data from mosses collected from 2781 sites across Europe within the framework of the European moss survey 2005/6, which was coordinated by the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation). Modelled atmospheric N deposition and air concentration data were calculated using the Unified EMEP Model of the European Monitoring and Evaluation Programme (EMEP) of the Convention on Long-range Transboundary Air Pollution (CLRTAP). The modelled deposition and concentration data encompass various N compounds. In order to assess the correlations between moss tissue total N concentrations and the chosen predictors, Spearman rank correlation analysis and Classification and Regression Trees (CART) were applied. The Spearman rank correlation analysis showed that the total N concentration in mosses and modelled N depositions and air concentrations are significantly correlated (0.53 ≤ r_s ≤ 0.68, p < 0.001). Correlations with other predictors were lower than 0.55. The CART analysis indicated that the variation in the total N concentration in mosses was best explained by the variation in NH₄⁺ concentrations in air, followed by NO₂ concentrations in air, sampled moss species and total dry N deposition. The total N concentrations in mosses mirror land use-related atmospheric concentrations and depositions of N across Europe. In addition to already proven associations to measured N deposition on a local scale the study at hand gives a scientific prove on the association of N concentration in mosses and modelled deposition at the European scale.     

Comparison of the performances of land use regression modelling and dispersion modelling in estimating small-scale variations in long-term air pollution concentrations in a Dutch urban area

The performance of a Land Use Regression (LUR) model and a dispersion model (URBIS – URBis Information System) was compared in a Dutch urban area. For the Rijnmond area, i.e. Rotterdam and surroundings, nitrogen dioxide (NO₂) concentrations for 2001 were estimated for nearly 70 000 centroids of a regular grid of 100 × 100 m.A LUR model based upon measurements carried out on 44 sites from the Dutch national monitoring network and upon Geographic Information System (GIS) predictor variables including traffic intensity, industry, population and residential land use was developed. Interpolation of regional background concentration measurements was used to obtain the regional background. The URBIS system was used to estimate NO₂ concentrations using dispersion modelling. URBIS includes the CAR model (Calculation of Air pollution from Road traffic) to calculate concentrations of air pollutants near urban roads and Gaussian plume models to calculate air pollution levels near motorways and industrial sources. Background concentrations were accounted for using 1 × 1 km maps derived from monitoring and model calculations.Moderate agreement was found between the URBIS and LUR in calculating NO₂ concentrations (R = 0.55). The predictions agreed well for the central part of the concentration distribution but differed substantially for the highest and lowest concentrations. The URBIS dispersion model performed better than the LUR model (R = 0.77 versus R = 0.47 respectively) in the comparison between measured and calculated concentrations on 18 validation sites. Differences can be understood because of the use of different regional background concentrations, inclusion of rather coarse land use category industry as a predictor variable in the LUR model and different treatment of conversion of NO to NO₂.Moderate agreement was found between a dispersion model and a land use regression model in calculating annual average NO₂ concentrations in an area with multiple sources. The dispersion model explained concentrations at validation sites better.     

Multiparametric approach for assessing environmental quality variations in West African aquatic ecosystems using the black-chinned tilapia (Sarotherodon melanotheron) as a sentinel species

The study highlights the potential of the black-chinned tilapia to be used as a sentinel to assess environmental contaminants based on the use of a set of biomarkers. The usefulness of fish species as sentinels for assessing aquatic environment contamination was tested using a set of biomarkers in Senegalese environments characterized by multi-pollution sources. The black-chinned tilapia (Sarotherodon melanotheron) was selected as a sentinel because of its abundance, wide distribution in all coastal aquatic ecosystems and physiological properties. The potential influence of confounding factors such as salinity on biomarker in the tilapia has been examined. Individuals were sampled during two seasons (dry and wet) in eight sites characterized by various degrees of anthropogenic contamination and different salinities (from 0 to 102?psu). Biomarkers??including growth rate (GR), condition factor (CF), biotransformation enzymes such as 7-ethoxyresorufin-O-deethylase (EROD) and glutathione-S-transferase (GST), lipid peroxidation (TBARS) and acetylcholinesterase (AChE)??were measured. Chemical contaminant [polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs)] levels showed different sources of contamination with relatively high concentrations of PAHs in the Hann Bay and Foundiougne locations. The most sensitive biomarker present in different sites according to the principal component analysis is EROD. Few variations of the AChE activity and TBARS levels were found. No clear relationship was found between biomarker responses and salinity, but GR and CF were lower in hypersaline conditions. Tilapia is responsive to environmental contaminants such as PAHs, OCPs and PCBs. The S. melanotheron multiparametric approach showed a better discrimination of sites.     

Influence of organic matter on arsenic removal by continuous flow electrocoagulation treatment of weakly mineralized waters

The aim of this study is to evaluate and understand the electrocoagulation/flocculation (ECF) process to remove arsenic from both model and natural waters with low mineral content and to compare its performances to the coagulation/flocculation (CF) process already optimized. Experiments were thus conducted with iron electrodes in the same specific treatment conditions (4≤current density (mAcm(-2))≤33) to study the influence of organic matter on arsenic removal in conditions avoiding the oxidation step usually required to improve As(III) removal. The process performance was evaluated by combining quantification of arsenic residual concentrations and speciation and dissolved organic carbon residual concentrations with zeta potential and turbidity measurements. When compared to CF, ECF presented several disadvantages: (i) lower As(V) removal yield because of the ferrous iron dissolved from the anode and the subsequent negative zeta potential of the colloidal suspension, (ii) higher residual DOC concentrations because of the fractionation of high molecular weight compounds during the treatment leading to compounds less prone to coagulate and (iii) higher residual turbidities because of the charge neutralization mechanisms involved. However, during this process, As(III) was oxidized to As(V) improving considerably its removal whatever the matrix conditions. ECF thus allowed to improve As(III) removal without applying an oxidation step that could potentially lead to the formation of toxic oxidation by-products.     

Influence of the initial state of carbon nanotubes on their colloidal stability under natural conditions

The colloidal stability of dry and suspended carbon nanotubes (CNTs) in the presence of amphiphilic compounds (i.e. natural organic matter or surfactants) at environmentally realistic concentrations was investigated over several days. The suspensions were analyzed for CNT concentration (UV-vis spectroscopy), particle size (nanoparticle tracking analysis), and CNT length and dispersion quality (TEM). When added in dry form, around 1% of the added CNTs remained suspended. Pre-dispersion in organic solvent or anionic detergent stabilized up to 65% of the added CNTs after 20 days of mild shaking and 5 days of settling. The initial state of the CNTs (dry vs. suspended) and the medium composition hence are critical determinants for the partitioning of CNTs between sediment and the water column. TEM analysis revealed that single suspended CNTs were present in all suspensions and that shaking and settling resulted in a fractionation of the CNTs with shorter CNTs remaining predominantly in suspension.     

Atmospheric phenanthrene pollution modulates carbon allocation in red clover (Trifolium pratense L.)

The influence of atmospheric phenanthrene (PHE) exposure (160 μg m⁻³) during one month on carbon allocation in clover was investigated by integrative (plant growth analysis) and instantaneous ¹³CO₂ pulse-labelling approaches. PHE exposure diminished plant growth parameters (relative growth rate and net assimilation rate) and disturbed photosynthesis (carbon assimilation rate and chlorophyll content), leading to a 25% decrease in clover biomass. The root-shoot ratio was significantly enhanced (from 0.32 to 0.44). Photosynthates were identically allocated to leaves while less allocated to stems and roots. PHE exposure had a significant overall effect on the ¹³C partitioning among clover organs as more carbon was retained in leaves at the expense of roots and stems. The findings indicate that PHE decreases root exudation or transfer to symbionts and in leaves, retains carbon in a non-structural form diverting photosynthates away from growth and respiration (emergence of an additional C loss process).     

Bioavailability of particulate metal to zebra mussels: biodynamic modelling shows that assimilation efficiencies are site-specific

This study investigates the ability of the biodynamic model to predict the trophic bioaccumulation of cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni) and zinc (Zn) in a freshwater bivalve. Zebra mussels were transplanted to three sites along the Seine River (France) and collected monthly for 11 months. Measurements of the metal body burdens in mussels were compared with the predictions from the biodynamic model. The exchangeable fraction of metal particles did not account for the bioavailability of particulate metals, since it did not capture the differences between sites. The assimilation efficiency (AE) parameter is necessary to take into account biotic factors influencing particulate metal bioavailability. The biodynamic model, applied with AEs from the literature, overestimated the measured concentrations in zebra mussels, the extent of overestimation being site-specific. Therefore, an original methodology was proposed for in situ AE measurements for each site and metal.     

Landscape multifunctionality: a powerful concept to identify effects of environmental change

The interdisciplinary concept of landscape multifunctionality provides a suitable platform to combine or disentangle effects of multiple environmental stressors acting on the landscape. The concept allows mapping of trade-offs, synergies, and priority conflicts between individual landscape functions, thus providing easily accessible, hands-on means to communicate findings of environmental research to decision makers and society. This rapid communication provides an overview of current developments and potential future research avenues in landscape multifunctionality.