Uptake of Cd,Pb, U,and Zn by plants in floodplain pollution hotspots contributes to secondary contamination

Environmental Science and Pollution Research - Willows, woody plants of genus Salix common in floodplains of temperate regions, act as plant pumps and translocate the Cd and Zn in the soil profiles...     

Cycling Skill Inventory: Assessment of motor–tactical skills and safety motives

Abstract

Objective: It is well established within the traffic psychology literature that a distinction can be made between driving skill and driving style. The majority of self-report questionnaires have been developed for car drivers, whereas only limited knowledge exists on the riding skill and style of cyclists. Individual differences in cycling skills need to be understood in order to apply targeted interventions.

Methods: This study reports on a psychometric analysis of the Cycling Skill Inventory (CSI), a self-report questionnaire that asks cyclists to rate themselves from definitely weak to definitely strong on 17 items. Herein, we administered the CSI using an online crowdsourcing method, complemented with respondents who answered the questionnaire using paper and pencil (n?=?1,138 in total). Our analysis focuses on understanding the major sources of variance of the CSI and its correlates with gender, age, exposure, and self-reported accident involvement as a cyclist.

Results: The results showed that 2 components underlie the item data: Motor–tactical skills and safety motives. Correlational analyses indicated that participants with a higher safety motives score were involved in fewer self-reported cycling accidents in the past 3 years. The analysis also confirmed well-established gender differences, with male cyclists having lower safety motives but higher motor–tactical skills than female cyclists.

Conclusions: The nomological network of the CSI for cyclists is similar to that of the Driving Skill Inventory for car drivers. Safety motives are a predictor of self-reported accident involvement among cyclists.     

Ferulic acid supplementation for 40 days in hair ewe lambs experiencing seasonal heat stress: short-term effects on physiological responses,growth, metabolism,and hematological profile

Environmental Science and Pollution Research - Free ferulic acid (FA) is a natural compound with antioxidant properties which mitigates the negative effects of cold stress in sheep; however, its...     

A vegetation management experiment: Goats grazing shrublands in Doñana Natural Park

We have studied the effect of goat grazing on the shrub understory of a pine forest situated in a protected area (Doñana Natural Park). Along three years we have studied the changes in phytovolume, flammability, species richness and diversity in a grazed shrubland and in a control area not grazed by the goats. We studied also food preferences of the goats and the ability of the goats to disperse the seeds of the plants they eat. Goat grazing significantly reduced shrub biomass and flammability, decreasing the risk of forest fire. Goats selected the species they eat, changing the pattern of selection throughout the year. Grazing reduced shrub diversity, but did not affected species richness. The goats can also potentially disperse the seeds of some of the species they eat, since the seeds were able to pass through the goat’s gut and germinated afterwards. Goat grazing on scrub vegetation can be used as an effective tool for the control of shrubs in protected forest areas, without losing biodiversity.     

Low cost organic and inorganic sorbents to fight soil and water pollution

Environmental Science and Pollution Research -     

Induction of glutathione reductase enzyme activity by β‐aminobutyric acid in plant leaves

Abstract

Treatment of pea and tobacco leaf discs with the resistance inducer DL‐β‐amino‐n‐butyric acid (BABA) led to a substantial induction of glutathione reductase (GR, E.C. 1.6.4.2.) enzyme activity. After exposure to 1 mM BABA for 96 hrs, the GR activities were 3.2‐fold and 2.9‐fold higher in pea and tobacco leaf discs, respectively, than GR activities in untreated controls. Elevated GR levels may contribute to the antioxidative protection of plants during pathogen attack.     

An hourly PM10 diagnosis model for the Bilbao metropolitan area using a linear regression methodology

There is extensive evidence of the negative impacts on health linked to the rise of the regional background of particulate matter (PM) 10 levels. These levels are often increased over urban areas becoming one of the main air pollution concerns. This is the case on the Bilbao metropolitan area, Spain. This study describes a data-driven model to diagnose PM10 levels in Bilbao at hourly intervals. The model is built with a training period of 7-year historical data covering different urban environments (inland, city centre and coastal sites). The explanatory variables are quantitative—log [NO₂], temperature, short-wave incoming radiation, wind speed and direction, specific humidity, hour and vehicle intensity—and qualitative—working days/weekends, season (winter/summer), the hour (from 00 to 23 UTC) and precipitation/no precipitation. Three different linear regression models are compared: simple linear regression; linear regression with interaction terms (INT); and linear regression with interaction terms following the Sawa’s Bayesian Information Criteria (INT-BIC). Each type of model is calculated selecting two different periods: the training (it consists of 6 years) and the testing dataset (it consists of 1 year). The results of each type of model show that the INT-BIC-based model (R ²?=?0.42) is the best. Results were R of 0.65, 0.63 and 0.60 for the city centre, inland and coastal sites, respectively, a level of confidence similar to the state-of-the art methodology. The related error calculated for longer time intervals (monthly or seasonal means) diminished significantly (R of 0.75–0.80 for monthly means and R of 0.80 to 0.98 at seasonally means) with respect to shorter periods.     

Suitability of selected bioindicators of atmospheric pollution in the industrialised region of Ostrava,Upper Silesia,Czech Republic

This study is a continuation of our preceding research identifying suitable environmental samples for the tracing of atmospheric pollution in industrial areas. Three additional types of environmental samples were used to characterise contamination sources in the industrial area of Ostrava city, Czech Republic. The region is known for its extensive metallurgical and mining activities. Fingerprinting of stable Pb isotopes was applied to distinguish individual sources of anthropogenic Pb. A wide range of ²⁰⁶Pb/²⁰⁷Pb ratios was observed in the investigated samples: ²⁰⁶Pb/²⁰⁷Pb = 1.168–1.198 in mosses; ²⁰⁶Pb/²⁰⁷Pb = 1.167–1.215 in soils and ²⁰⁶Pb/²⁰⁷Pb = 1.158–1.184 in tree cores. Black and brown coal combustion, as well as metallurgical activities, is the two main sources of pollution in the area. Fossil fuel burning in industry and households seems to be a stronger source of Pb emissions than from the metallurgical industry. Concentration analyses of tree rings showed that a significant increase in As concentrations occurred between 1999 and 2016 (from 0.38 mg kg^?1 to 13.8 mg kg^?1). This shift corresponds to the use of brown coal from Bílina, Czech Republic, with an increased As concentration. The burning of low-quality fuels in households remains a problem in the area, as small ground sources have a greater influence on the air quality than do industrial sources.     

No relationship found between mercury and lead concentrations in muscle and scales of chub Squalius cephalus L.

We examined the relationship between muscle and scale mercury (Hg) and lead (Pb) concentrations in chub Squalius cephalus L. from six riverine sites in the Czech Republic in order to determine whether scale analysis alone could provide a nonlethal and convenient method for prediction of heavy metal concentration in muscle tissue. Our results confirm tissue-specific heavy metal accumulation in chub, with Hg tending to accumulate primarily in muscle tissue and Pb in scales. We found no significant relationship, however, for concentrations of either Pb or Hg between muscle tissue and scales of chub. Our results indicate that scales cannot be used for predicting heavy metal contamination in muscle of chub and we recommend, therefore, that muscle biopsy methods continue as the preferred method of analysis.