Development of a loading dock safety evaluation tool

INTRODUCTION: Companies that use forklifts to load and unload trucks at loading docks are well aware of the main danger associated with this type of activity (i.e., the possibility of the forklift falling or tipping over when the truck suddenly moves away from the dock). Even if various truck restraint measures can be implemented to reduce the possibility of this type of accident, a number of hazardous incidents that result in a forklift tipping over from a loading dock still do occur regularly in day-to-day activities. This situation has brought experts to examine and evaluate the effectiveness of different measures and systems depending on the context in which they are used. METHODS: The present study touched upon both the technical and the organizational aspects of the restraint measures that could have an impact on safety. Certain elements were examined very closely, especially the failure of mechanical devices and their relation to the environment in which they are used, as well as the systemic interaction between people and the various restraint measures in use in a given context. CONCLUSION: This article presents a safety evaluation tool regarding restraint measures or systems for trucks docked at loading platforms - a tool that, of course, would take into consideration both the specific contextual aspects related to the docking bay itself, and to the plant. IMPACT ON INDUSTRY: This tool is designed to help companies choose the optimal safety measures to implement, while remaining realistic in terms of the technical and economic aspects of any given situation.     

Phytotoxicity to and uptake of TNT by rice

The contamination of the environment by explosives is a worldwide problem resulting in part from 2,4,6-trinitrotoluene (TNT) production. In situ phytoremediation is an appropriate, alternative, cost-effective technology to detoxify extended contamination of surface soil. The ability of rice (Oriza sativa) to both tolerate and assimilate ¹⁴C-labeled TNT was investigated over a 40-day exposure period. The germination rate decreased at 500 mg/kg TNT whereas root and shoot length increased significantly at high TNT concentrations, from 150 to 500 mg/kg. Rice took up TNT residues from soil and accumulated most in roots. Less than 25% of radioactivity taken up was translocated to aerial parts. Above 200 mg/kg TNT, the concentration of TNT residues in roots reached a maximum of approximately 0.7 mg/g. No TNT was found in plant extracts, good evidence for rapid metabolism of TNT. More than 60% of ¹⁴C activity was found as unextractable residues in roots. It was concluded that TNT metabolized and subsequently sequestered by roots could not be translocated to aerial parts.     

Genetic identity determines risk of post-settlement mortality of a marine fish

Longitudinal sampling of four cohorts of Neopomacentrus filamentosus, a common tropical damselfish from Dampier Archipelago, Western Australia, revealed the evolution of size structure after settlement. Light traps collected premetamorphic individuals from the water column ("settlers") to establish a baseline for each cohort. Subsequently, divers collected benthic juveniles ("recruits") at 1-3-month intervals to determine the relative impacts of post-settlement mortality during the first three months. Growth trajectories for individual fish were back-calculated from otolith records and compared with nonlinear mixed-effects models. Size-selective mortality was detected in all cohorts with the loss of smaller, slower growing individuals. Three months after settlement, recruits showed significantly faster growth as juveniles, faster growth as larvae, and larger sizes as hatchlings. The timing and intensity of post-settlement selection differed among cohorts and was correlated with density at settlement. The cohort with the greatest initial abundance experienced the strongest selective mortality, with most of this mortality occurring between one and two months after settlement when juveniles began foraging at higher positions in the water column. Significant genetic structure was found between settlers and three-month-old recruits in this cohort as a result of natural selection that changed the frequency of mtDNA haplotypes measured at the control region. The extent of this genetic difference was enlarged or reduced by artificially manipulating the intensity of size-based selection, thus establishing a link between phenotype and haplotype. Sequence variation in the control region of the mitochondrial genome has been linked to mitochondrial efficiency and weight gain in other studies, which provides a plausible explanation for the patterns observed here.     

A necessary distinction between spatial representativeness of an air quality monitoring station and the delimitation of exceedance areas

The European legislation on ambient air quality introduces the concepts of spatial representativeness of a monitoring station and spatial extent of an exceedance zone. Spatial representativeness is an essential macro-scale siting criterion which should be evaluated before the setting-up and during the life of a monitoring point. As for the exceedance area, it has to be defined each time an environmental objective is exceeded in an assessment zone. No specific approach is prescribed to delimit such areas. A probabilistic methodology is presented, based on a preliminary kriging estimation of atmospheric concentrations at each point of the domain. It is applied to NO₂ pollution on the urban scale. In the proposed approach, a point belongs to the area of representativeness of a station if its concentration differs from the station measurement by less than a given threshold. To take the estimation uncertainty into account, the standard deviation of the kriging error is used in a probabilistic framework. The choice of the criteria used to deal with overlapping areas is first tested on NO₂ annual mean concentration maps of France, built by combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. At the local scale, data from passive sampling surveys and high -resolution auxiliary variables are used to provide a more precise estimation of the background pollution in different French cities. The traffic-related pollution can also be accounted for in the map by additional predictors such as distance to the road, and traffic-related NO_x emissions. Similarly, the proposed approach is implemented to identify the points, at a given statistical risk, where the NO₂ concentration is above the annual limit value.     

Impact of land-cover change in the Southern Amazonia climate: a case study for the region of Alta Floresta,Mato Grosso,Brazil

The transformation of forest into pastures in the Brazilian Amazon leads to significant consequences to climate at local scale. In the region of Alta Floresta (Mato Grosso, Brazil), deforestation has been intense with over half the forests being cut since 1970. This article first examines the evolution of precipitation observed in this region and shows a significant trend in the decrease in total precipitation especially at the end of the dry season and at the beginning of the rainy season. The study then compares the temperatures measured in cleared and forested sectors within a reserve in the area of Alta Floresta (Mato Grosso, Brazil) between 2006 and 2007. The cleared sector was always hotter and drier (from 5% to 10%) than the forested area. This difference was not only especially marked during the day when it reached on average 2°C but also seemed to increase during the night with the onset of the dry season (+0.5°C). The Urban Heat Island effect is also evident especially during the night and in the dry season.     

Optimising vegetation monitoring. A case study in A French lowland forest

Biodiversity monitoring surveys are rarely optimised statistically before being initiated. Here, we optimised the monitoring of plants in a temperate forest. The total inventory cost, the number and size of quadrats were optimised to detect a 10% change in species richness over 5 years with α = β = 0.05, using data from ongoing long-term floristic monitoring programs. The procedure showed that the inventory cost would be ca 15% lower using 100-, 200-m² quadrats instead of 300- or 400-m² quadrats. Despite the cost associated with the optimisation (e.g. gathering preliminary data) and the imprecise estimates (due to the typically small sample size of the pilot studies), optimisation would often be a better option than expert opinion when designing a monitoring survey.     

Ecotoxicological assessment of TiO2 byproducts on the earthworm Eisenia fetida

The increasing production of nanomaterials will in turn increase the release of nanosized byproducts to the environment. The aim of this study was to evaluate the behaviour, uptake and ecotoxicity of TiO₂ byproducts in the earthworm Eisenia fetida. Worms were exposed to suspensions containing 0.1, 1 and 10 mg/L of byproducts for 24 h. Size of TiO₂ byproducts showed aggregation of particles up to 700 μm with laser diffraction. Only worms exposed at 10 mg/L showed bioaccumulation of titanium (ICP-AES), increasing expression of metallothionein and superoxide dismutase mRNA (Real-time PCR) and induction of apoptotic activity (Apostain and TUNEL). TiO₂ byproducts did not induce cytotoxicity on cœlomocytes, but a significant decrease of phagocytosis was observed starting from 0.1 mg/L. In conclusion, bioaccumulation of byproducts and their production of reactive oxygen species could be responsible for the alteration of the antioxidant system in worms.     

Using a chemistry transport model to account for the spatial variability of exposure concentrations in epidemiologic air pollution studies

Environmental epidemiology and more specifically time-series analysis have traditionally used area-averaged pollutant concentrations measured at central monitors as exposure surrogates to associate health outcomes with air pollution. However, spatial aggregation has been shown to contribute to the overall bias in the estimation of the exposure-response functions. This paper presents the benefit of adding features of the spatial variability of exposure by using concentration fields modeled with a chemistry transport model instead of monitor data and accounting for human activity patterns. On the basis of county-level census data for the city of Paris, France, and a Monte Carlo simulation, a simple activity model was developed accounting for the temporal variability between working and evening hours as well as during transit. By combining activity data with modeled concentrations, the downtown, suburban, and rural spatial patterns in exposure to nitrogen dioxide, ozone, and PM2.5 (particulate matter [PM] < or = 10 microm in aerodynamic diameter) were captured and parametrized. Exposures predicted with this model were used in a time-series study of the short-term effect of air pollution on total nonaccidental mortality for the 4-yr period from 2001 to 2004. It was shown that the time series of the exposure surrogates developed here are less correlated across co-pollutants than in the case of the area-averaged monitor data. This led to less biased exposure-response functions when all three co-pollutants were inserted simultaneously in the same regression model. This finding yields insight into pollutant-specific health effects that are otherwise masked by the high correlation among co-pollutants.     

Transferring the heterogeneity of surface emissions to variability in pollutant concentrations over urban areas through a chemistry-transport model

Horizontal resolution of grid-based chemistry-transport models is limited to a few square kilometers which has been proved insufficient for assessing human exposure and health impact. We propose a general methodology, applicable on any kind of grid-based air-quality model, that combines subgrid scale information on emission and land-use data in order to disaggregate the grid-averaged emission flux into a set of source-specific components (subgrid-environments). Different subgrid concentrations are calculated inside each one of these environments providing a direct estimate of pollutant variability along with the ‘standard’ grid-averaged model output. The method was first validated over a controlled emissions case by comparing concentrations modeled in the subgrid-environments with concentrations modeled directly at higher model resolution and next over a real case-study, where subgrid concentrations were compared with monitor data from sites representing different types of urban environments (i.e. roads and residential blocks). It was shown that the method is capable to yield accurate estimates of small scale pollutant variability.