Distribution and availability of potentially toxic metals in soil in central area of Belgrade,Serbia

Belgrade, capital city of Serbia, has over 1,600,000 inhabitants and over 400,000 vehicles trafficking every day on its streets. The investigation of soil pollution was performed by sequential extraction analysis to investigate the availability of potentially toxic metals (Zn, Cd, Pb, Co, Ni, Cu, Cr and Mn) under different oxidation and pH conditions. All investigated metals were mainly extracted from soils with neutral or acidic extractants. Serious pollution was observed along roads and streets with high traffic frequency, but Pb and Ni pollution was the highest since their concentrations exceed both soil Serbian standard and Canadian guidance values and is characteristic for all investigated sites. Cd, Cu, Cr and Zn concentrations are moderately high since they are between Canadian guideline and Serbian standard.     

Screening of phthalic acid esters in raw materials,premixes and feed additives

Phthalates are animal carcinogens and may cause death or tissue deformities. Samples of feedstuffs collected in 2005 and 2006 from industrial feed manufacturers in the Czech Republic were analysed for contamination with phthalic acid esters (PAEs), specifically di-2-ethylhexyl phthalate (DEHP) and di-n-butyl phthalate (DBP). Samples of feed additives, premixes and raw materials were collected (year 2005, n = 26). For soybean oil, the total volume of phthalates measured (DBP + DEHP) reached a level of 131.42 mg kg⁻¹; for rapeseed oil, fish meal and animal fats, the levels measured were 15.00, 7.96 and 58.87 mg kg⁻¹, respectively. The lowest level of DBP + DEHP was found in corn (2.03 mg kg⁻¹). Since phthalates were detected, samples of feed additives (n = 28) and raw materials (n = 28) were collected again in 2006. The highest levels of DBP + DEHP were found in raw materials containing fat. Phthalate levels in rapeseed oil samples ranged from 1.38 to 32.40 mg kg⁻¹ DBP + DEHP. For feed additives, contamination levels in vitamins and amino acids ranged from 0.06 to 3.15 and 1.76 to 4.52 mg kg⁻¹ DBP + DEHP, respectively. Here, we show that the levels of PAEs found in cereals such as wheat, barley and corn may be regarded as being alarmingly high, because cereals make up the largest proportion of compound feed of farm animals.     

Relationship of safety climate perceptions and job satisfaction among employees in the construction industry: the moderating role of age

This study examines the degree to which construction sector employees perceive that safety is important in their organizations/sites and how job satisfaction affects these perceptions when age is introduced as a moderator variable. Two-way analysis of variance demonstrated that job satisfaction has a strong effect on perceived management commitment to work safety and that this relationship was moderated by respondents’ age. Job satisfaction was associated with perceived accident rate and safety inspection frequency, but the proposed role of age in this linkage was not confirmed. Consequently, the findings indicated that by increasing the level of job satisfaction, perceptions of these safety climate aspects proved to be more positive. The conclusion is that these relationships could further lead to a lower percentage of accidents and injuries in the workplace and better health among employees. A significant relationship between job satisfaction, age and perceived co-workers’ commitment to work safety was not found.     

Exposure of microplastics to organic matter in waters enhances microplastic encapsulation into calcium carbonate

Environmental Chemistry Letters - Plastic pollution in water ecosystems is threatening the survival of wildlife. In particular, microplastics may be encapsulated into calcium carbonate, a crucial...     

Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition

An important consideration in conservation and biodiversity planning is an appreciation of the condition or integrity of ecosystems. In this study, we have applied various machine learning methods to the problem of predicting the condition or quality of the remnant indigenous vegetation across an extensive area of south-eastern Australia—the state of Victoria. The field data were obtained using the ‘habitat hectares’ approach. This rapid assessment technique produces multiple scores that describe the condition of various attributes of the vegetation at a given site. Multiple sites were assessed and subsequently circumscribed with GIS and remote-sensed data.     

Atmospheric aerosol growth rates at different background station types

Environmental Science and Pollution Research - Highly time-resolved particle number size distributions (PNSDs) were evaluated during 5 years (2013–2017) at four background stations in the...     

Kinetic sodium analyses in the crab Carcinus mediterraneus

Kinetic analyses were made of the stable sodium and radioactive sodium (²²Na) in some tissues of the crab Carcinus mediterraneus CSRN. Fast ²²Na outflux constant is increased in gills, hepatopancreas, hemolymph, digestive tract and muscles. In the reproductive organs the values of the sodium outflux constant are lower. The values of the fast outflux rates (t=20°C) of sodium amount, in the whole animal, to 22.5 M Na/g/h, in the hemolymph, to 69.3 M Na/g/h; the slow outflux rates have much lower values (0.02 to 0.13 M Na/g/h). Moulting crabs show a rate of sodium outflux 6 times greater than that of intermoulting individuals.     

Using multi-objective classification to model communities of soil microarthropods

In agricultural soil, a suite of anthropogenic events shape the ecosystem processes and populations. However, the impact from anthropogenic sources on the soil environment is almost exclusively assessed for chemicals, although other factors like crop and tillage practices have an important impact as well. Thus, the farming system as a whole should be evaluated and ranked according to its environmental benefits and impacts. Our starting point is a data set describing agricultural events and soil biological parameters. Using machine learning methods for inducing regression and model trees, we produce empirical models able to predict the soil quality from agricultural measures in terms of quantities describing the soil microarthropod community. We are also interested in discovering additional higher level knowledge. In particular, we have identified the most important factors influencing the population densities of springtails and mites and their biodiversity. We also identify to which agricultural actions different microarthropods react distinctly. To obtain this higher level knowledge, we employ multi-objective regression trees.