Exposure to inhalable dust and endotoxin among Danish livestock farmers: results from the SUS cohort study

Studies on personal dust and endotoxin concentrations among animal farmers have been either small or limited to a few sectors in their investigations. The present study aimed to provide comparable information on the levels and variability of exposure to personal dust and endotoxin in different types of animal farmers. 507 personal inhalable dust samples were collected from 327 farmers employed in 54 pig, 26 dairy, 3 poultry, and 3 mink farms in Denmark. Measurements in pig and dairy farmers were full-shift and performed during summer and winter, while poultry and mink farmers were monitored during 4 well-defined production stages. The collected samples were measured for dust gravimetrically and analyzed for endotoxin by the Limulus amebocyte lysate assay. Simple statistics and random-effect analysis were used to describe the levels and the variability in measured dust and endotoxin exposure concentrations. Measured inhalable dust levels had an overall geometric mean of 2.5 mg m(-3) (range 相似文献   

Evolution of building façade road traffic noise levels in Flanders

The evolution of daytime fa?ade noise levels by road traffic at 250 dwellings in Flanders is assessed. Three identical man-operated measurement campaigns have been conducted in the years 1996, 2001 and 2009, during fall. A practical methodology has been developed, based on short time noise measurements and context observations at these locations. The uncertainty introduced by short-term sampling has been quantified as a function of the noise level. Furthermore, a correction is proposed for measuring at a random moment during daytime. Analysis of the data showed that road traffic noise levels hardly changed globally over this period of 13 years. The distribution of changes in noise level at corresponding measurement locations is nevertheless rather wide-all improvements are equally compensated by increases in noise levels at other locations. The percentage of the dwelling fa?ades exposed to daytime noise levels above 65 dBA has increased slightly between 1996 and 2001, but seems to stagnate in 2009. In spite of the increased interest and actions of policy makers during the past decades, noise exposure caused by road traffic at dwelling fa?ades is a persistent problem.     

Are network indices robust indicators of food web functioning? A Monte Carlo approach

Indices based on network theory are often used to describe food web functioning. These indices take as input food web flows that are estimated based on merging of (scarce) data with linear inverse methods (LIMs). Due to under sampling, most food webs are highly uncertain and can only be quantified within a specific uncertainty range. The linear inverse method (LIM) can estimate food web flows using a variety of techniques, e.g. the parsimonious or minimum norm (MN) solution, which selects one food web, based on a quadratic minimization technique or the Monte Carlo solution where a finitely many random solutions are generated which are then averaged. We use the Monte Carlo approach (MCA) to estimate the values of several indices from four published food webs, the Gulf of Riga for the autumn, summer and spring seasons, and the Takapoto atoll system. We first show that network indices are much better constrained than the uncertain food webs from which they are calculated. Therefore, even in the face of food web uncertainty, they are robust estimators of food web functioning. We then use the MCA-derived network indices to generate cumulative density functions for each index. These serve to compute the probabilities of the MN indices estimates being an extreme solution as compared to the median values. Our findings show that 82% of the MN solutions are smaller than the MCA solutions, and 63% of the network indices are significantly under-estimated.     

Removing Chinese Privet (Ligustrum sinense Lour.) and Establishing Native Plants in a Flooded Riparian Corridor in North‐Central Texas,USA

The objectives of this study were to evaluate the allelopathic effects of Chinese privet (Ligustrum sinense Lour.) extract on native seeds and cuttings and to assess the survivability of native plants in a flooded riparian corridor. Field sites occupied the Trinity River floodplain in southeast Dallas County, Texas. Eight native species were evaluated. They were soapberry, red mulberry, persimmon, elderberry, beautyberry, coralberry, mustang grape, and heartleaf peppervine. From this study, we concluded that:

• Truncating privet at ground level and applying equal parts of glyphosate and water to the stump effectively kills the plant;
• Once removed, privet does not curtail establishment of native plants;
• A 60‐day (d) flood killed most plants, with red mulberry being the most resilient;
• A 1% leaf and berry extract from privet significantly reduced soapberry seed germination; and
• A 1% extract from various parts of privet did not significantly affect root growth from cuttings.

     

Effect of clays, metal oxides, and organic matter on rhamnolipid biosurfactant sorption by soil

Rhamnolipids produced by Pseudomonas aeruginosa have been proposed as soil washing agents for enhanced removal of metal and organic contaminants from soil. A potential limitation for the application of rhamnolipids is sorption by soil matrix components. The objective of this study is to empirically determine the contribution of representative soil constituents (clays, metal oxides, and organic matter) to sorption of the rhamnolipid form most efficient at metal complexation (monorhamnolipid). Sorption studies show that monorhamnolipid (R1) sorption is concentration dependent. At low R1 concentrations that are relevant for enhancing organic contaminant biodegradation, R1 sorption followed the order: hematite (Fe(2)O(3))>kaolinite>MnO(2) approximately illite approximately Ca-montmorillonite>gibbsite (Al(OH)(3))>humic acid-coated silica. At high R1 concentrations, relevant for use in complexation/removal of metals or organics, R1 sorption followed the order: illite>humic acid-coated silica>Ca-montmorillonite>hematite>MnO(2)>gibbsite approximately kaolinite. These results allowed prediction of R1 sorption by a series of six soils. Finally, a comparison of R1 and R2 (dirhamnolipid) shows that the R1 form sorbs more strongly alone than when in a mixture of both the R1 and R2 forms. The information presented can be used to estimate, on an individual soil basis, the extent of rhamnolipid sorption. This is important for determining: (1) whether rhamnolipid addition is a feasible remediation option and (2) the amount of rhamnolipid required to efficiently remove the contaminant.     

Assessment of stream biological responses under multiple-stress conditions

Background, aim and scope  

Due to the numerous anthropogenic stress factors that affect aquatic ecosystems, a better understanding of the adverse consequences on the biological community of combined pressures is needed to attain the objectives of the European Water Framework Directive. In this study we propose an innovative approach to assess the biological impact of toxicants under field conditions on a large spatial scale.     

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed,Ethiopia

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km² in 1973 to 95.2 km² in 2011, while that of Lake Cheleleka whose area was 11.3 km² in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The “change and no change” analysis revealed that more than one third (548.0 km²) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.     

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.     

On the ability of consumer electronics microphones for environmental noise monitoring

The massive production of microphones for consumer electronics, and the shift from dedicated processing hardware to PC-based systems, opens the way to build affordable, extensive noise measurement networks. Applications include e.g. noise limit and urban soundscape monitoring, and validation of calculated noise maps. Microphones are the critical components of such a network. Therefore, in a first step, some basic characteristics of 8 microphones, distributed over a wide range of price classes, were measured in a standardized way in an anechoic chamber. In a next step, a thorough evaluation was made of the ability of these microphones to be used for environmental noise monitoring. This was done during a continuous, half-year lasting outdoor experiment, characterized by a wide variety of meteorological conditions. While some microphones failed during the course of this test, it was shown that it is possible to identify cheap microphones that highly correlate to the reference microphone during the full test period. When the deviations are expressed in total A-weighted (road traffic) noise levels, values of less than 1 dBA are obtained, in excess to the deviation amongst reference microphones themselves.