Job level risk assessment using task level ACGIH hand activity level TLV scores: a pilot study.

Existing upper extremity musculoskeletal disorder analytical tools are primarily intended for single or mono-task jobs. However, many jobs contain more than 1 task and some include job rotation. This case/control study investigates methods of modifying an existing tool, the American Conference of Governmental Industrial Hygienists (ACGIH) Hand Activity Level (HAL) Threshold Limit Value (TLV), to assess the upper extremity risk of multi-task jobs. Various methods of combining the task differences and ratios into a job level assessment were explored. Two methods returned significant odds ratios, (p < .05) of 18.0 (95% CI 1.8-172) and 12.0 (95% CI 1.2-120). These results indicate that a modified ACGIH HAL TLV may provide insight into the work-related risk of multi-task jobs. Further research is needed to optimize this process.     

Application of a Multi-Objective Optimization Method to Provide Least Cost Alternatives for NPS Pollution Control

Nonpoint source (NPS) pollutants such as phosphorus, nitrogen, sediment, and pesticides are the foremost sources of water contamination in many of the water bodies in the Midwestern agricultural watersheds. This problem is expected to increase in the future with the increasing demand to provide corn as grain or stover for biofuel production. Best management practices (BMPs) have been proven to effectively reduce the NPS pollutant loads from agricultural areas. However, in a watershed with multiple farms and multiple BMPs feasible for implementation, it becomes a daunting task to choose a right combination of BMPs that provide maximum pollution reduction for least implementation costs. Multi-objective algorithms capable of searching from a large number of solutions are required to meet the given watershed management objectives. Genetic algorithms have been the most popular optimization algorithms for the BMP selection and placement. However, previous BMP optimization models did not study pesticide which is very commonly used in corn areas. Also, with corn stover being projected as a viable alternative for biofuel production there might be unintended consequences of the reduced residue in the corn fields on water quality. Therefore, there is a need to study the impact of different levels of residue management in combination with other BMPs at a watershed scale. In this research the following BMPs were selected for placement in the watershed: (a) residue management, (b) filter strips, (c) parallel terraces, (d) contour farming, and (e) tillage. We present a novel method of combing different NPS pollutants into a single objective function, which, along with the net costs, were used as the two objective functions during optimization. In this study we used BMP tool, a database that contains the pollution reduction and cost information of different BMPs under consideration which provides pollutant loads during optimization. The BMP optimization was performed using a NSGA-II based search method. The model was tested for the selection and placement of BMPs in Wildcat Creek Watershed, a corn dominated watershed located in northcentral Indiana, to reduce nitrogen, phosphorus, sediment, and pesticide losses from the watershed. The Pareto optimal fronts (plotted as spider plots) generated between the optimized objective functions can be used to make management decisions to achieve desired water quality goals with minimum BMP implementation and maintenance cost for the watershed. Also these solutions were geographically mapped to show the locations where various BMPs should be implemented. The solutions with larger pollution reduction consisted of buffer filter strips that lead to larger pollution reduction with greater costs compared to other alternatives.     

Sampling approaches to predict urban street noise levels using fixed and temporary microphones

Requirements for static (prediction of L(den) and diurnal averaged noise pattern) and dynamic (prediction of 15 min and 60 min evolution of L(Aeq) and statistical levels L(A90,)L(A50) and L(A10)) noise level monitoring are investigated in this paper. Noise levels are measured for 72 consecutive days at 5 neighboring streets in an inner-city noise measurement network in Gent, Flanders, Belgium. We present a method to make predictions based on a fixed monitoring station, combined with short-term sampling at temporary stations. It is shown that relying on a fixed station improves the estimation of L(den) at other locations, and allows for the reduction of the number of samples needed and their duration; L(den) is estimated with an error that does not exceed 1.5 dB(A) to 3.4 dB(A) according to the location, for 90% of the 3 × 15 min samples. Also the diurnal averaged noise pattern can be estimated with a good accuracy in this way. It was shown that there is an optimal location for the fixed station which can be found by short-term measurements only. Short-term level predictions were shown to be more difficult; 7 day samples were needed to build models able to estimate the evolution of L(Aeq,60min) with a RMSE ranging between 1.4 dB(A) and 3.7 dB(A). These higher values can be explained by the very pronounced short-term variations appearing in typical streets, which are not correlated between locations. On the other hand, moderately accurate predictions can be achieved, even based on short-term sampling (a 3 × 15 minute sampling duration seems to be sufficient for many of the accuracy goals set related to static and dynamic monitoring). Finally, the method proposed also allows for the prediction of the evolution of statistical indicators.     

Characterization of spatial and temporal patterns in surface water quality: a case study of four major Lebanese rivers

In this work, four major Lebanese rivers were investigated, the Damour, Ibrahim, Kadisha, and Orontes, which are located in South, Central, and North Lebanon and Bekaa Valley, respectively. Five sampling sites were considered from upstream to downstream, and 12 sampling campaigns over four seasons were conducted during 2010–2011. Thirty-seven physicochemical parameters and five microbial tests were evaluated. A principal component analysis (PCA) was used for data evaluation. The first PCA, applied to the matrix-containing data that was acquired on all four rivers, showed that each river was distinct in terms of trophic state and pollution sources. The Ibrahim River was more likely to be polluted with industrial and human discharges, while the Kadisha River was severely polluted with anthropogenic human wastes. The Orontes and Damour rivers seemed to have the lowest rates of water pollution, especially the Orontes, which had the best water quality. PCA was also performed on individual data matrices for each river. In all cases, the results showed that the springs of each river have good water quality and are free from severe contamination. The other monitoring sites on each river were likely exposed to human activities and showed important spatial evolution. Through this work, a spatiotemporal fingerprint was obtained for each studied river, defining a “water mass reference” for each one. This model could be used as a monitoring tool for subsequent water quality surveys to highlight any temporal evolution of water quality.

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Evaluating multispecies landscape connectivity in a threatened tropical mammal community

Habitat corridors are important tools for maintaining connectivity in increasingly fragmented landscapes, but generally they have been considered in single‐species approaches. Corridors intended to facilitate the movement of multiple species could increase persistence of entire communities, but at the likely cost of being less efficient for any given species than a corridor intended specifically for that species. There have been few tests of the trade‐offs between single‐ and multispecies corridor approaches. We assessed single‐species and multispecies habitat corridors for 5 threatened mammal species in tropical forests of Borneo. We generated maps of the cost of movement across the landscape for each species based on the species’ local abundance as estimated through hierarchical modeling of camera‐trap data with biophysical and anthropogenic covariates. Elevation influenced local abundance of banded civets (Hemigalus derbyanus) and sun bears (Helarctos malayanus). Increased road density was associated with lower local abundance of Sunda clouded leopards (Neofelis diardi) and higher local abundance of sambar deer (Rusa unicolor). Pig‐tailed macaque (Macaca nemestrina) local abundance was lower in recently logged areas. An all‐species‐combined connectivity scenario with least‐cost paths and 1 km buffers generated total movement costs that were 27% and 23% higher for banded civets and clouded leopards, respectively, than the connectivity scenarios for those species individually. A carnivore multispecies connectivity scenario, however, increased movement cost by 2% for banded civets and clouded leopards. Likewise, an herbivore multispecies scenario provided more effective connectivity than the all‐species‐combined scenario for sambar and macaques. We suggest that multispecies habitat connectivity plans be tailored to groups of ecologically similar, disturbance‐sensitive species to maximize their effectiveness. Evaluación de la Conectividad de Terrenos Multiespecie en una Comunidad Tropical de Mamíferos