Photochemical Smog Modelling Using the Air Pollution Chemical Transport Model (TAPM-CTM) in Ho Chi Minh City,Vietnam

Environmental Modeling & Assessment - This paper describes the application of the air pollution model (TAPM-CTM) for photochemical airshed modelling in the Ho Chi Minh region. The model was...     

The assessment and prediction of temporal variations in surface water quality—a case study

In order to optimize the processes of sampling, monitoring, and management, the initial aim of this paper was to develop a model for the definition and prediction of temporal changes of water quality. In the case of the Morava River Basin (Serbia), the patterns of temporal changes have been recognized by applying different multivariate statistical techniques. The results of the conducted cluster analysis are the indicators of the existence of the three monitoring periods: the low-water, transitional, and high-water periods, which is in accordance with changes in the water flow in the analyzed river basin. A possibility of reducing the initial data set and recognizing the main pollution sources was examined by carrying out the principal component/factor analysis. The results indicate that the natural factor has a dominant influence in temporal groups. In order to recognize the discriminatory water quality parameters, a discriminant analysis (DA) was carried out. Conducting the DA enabled a significant reduction in the data set by the extraction of two parameters (the water temperature and electrical conductivity). Furthermore, the artificial neural network technique was used for testing the possibility of predicting changes in the values of the discriminant factors in the monitoring periods. The reliability of this method for the prediction of temporal variations of both extracted parameters within all temporal clusters has been proven.     

Photocatalytic reduction of carbon dioxide over Cu/TiO<Subscript>2</Subscript> photocatalysts

The photocatalytic reduction of CO₂ with H₂O was investigated using Cu/TiO₂ photocatalysts in aqueous solution. For this purpose, Cu/TiO₂ photocatalysts (with 0.2, 0.9, 2, 4, and 6 wt.% of Cu) have been synthesized via sol-gel method. The photocatalysts were extensively characterized by means of inductively coupled plasma optical emission spectrometry (ICP-OES), N₂ physisorption (BET), XRD, UV-vis DRS, FT-IR, Raman spectroscopy, TEM-EDX, and photoelectrochemical measurements. The as-prepared photocatalysts contain anatase as a major crystalline phase with a crystallite size around 13 nm. By increasing the amount of Cu, specific surface area and band gap energy decreased in addition to the formation of large agglomeration of CuO. Results revealed that the photocatalytic reduction of CO₂ decreased in the presence of Cu/TiO₂ in comparison to pure TiO₂, which might be associated to the formation of CuO phase acting as a recombination center of generated electron-hole pair. Decreasing of photoactivity can also be connected with a very low position of conduction band of photocatalysts with high Cu content, which makes H₂ production necessary for CO₂ reduction more difficult.     

Determination of microbiological contamination,antibacterial and antioxidant activities of natural plant hazelnut (Corylus avellana L.) pollen

The aim of our study is to determine microbial contamination, antibacterial and antioxidant activities of 14 pollen samples of Corylus avellana collected from different locations in Slovakia. Microbiological analysis was carried out in two steps: microbiological assays and studies of antibacterial activity of pollen extracts. The antimicrobial properties of pollen extracts were carried out with the disc-diffusion method. Methanol (70%), ethanol (70%) and distilled water were used for pollen extracts. Five strains of bacteria such as gram-negative (Salmonella enterica subsp. enterica CCM 3807, Escherichia coli CCM 2024, and Yersinia enterocolitica CCM 5671) and gram-positive (Staphylococcus aureus CCM 2461 and Bacillus thuringiensis CCM 19T) were tested. Antioxidant activity of pollen extracts was determined by the DPPH method. Bacterial analysis includes the determination of the total bacterial count ranged from 4.08 to 4.61 log CFU g^?1, mesophilic aerobic bacteria ranged from 3.40 to 4.89 log CFU g^?1, mesophilic anaerobic bacteria ranged from 3.20 to 4.52 log CFU g^?1, coliform bacteria ranged from 3.30 to 4.55 log CFU g^?1, yeasts and filamentous fungi ranged from 3.00 to 3.56 log CFU g^?1. Microscopic filamentous fungi Aspergillus spp., Alternaria spp., Penicillium spp., Cladosporium spp., Rhizopus spp., and Paecylomyces spp. were isolated from hazelnut pollen. Yersinia enterocolitica was the most sensitive strain among ethanolic and methanolic pollen hazelnut extracts. Staphylococcus aureus was the most sensitive strain against aqueous hazelnut pollen extracts. We determined the following sensitivity against ethanol pollen extracts respectively: Yersinia enterocolitica?>?Salmonella enterica?>?Staphylococcus aureus?>?Bacillus thuringiensis?>?Escherichia coli. Methanol pollen extracts had shown following sensitivity: Yersinia enterocolitica?>?Salmonella enterica?>?Escherichia coli?>?Staphylococcus aureus?>?Bacillus thuringiensis. Aqueous extracts had shown the following sensitivity: Staphylococcus aureus?>?Salmonella enterica?>?Escherichia coli?>?Bacillus thuringiensis?>?Yersinia enterocolitica. Hazelnut pollen extracts have over 82% antioxidant capacity in samples from non-urban zones. An elevated level of antioxidant potential in the pollen is determined by its biological properties conditioned by biologically active substances. DPPH method allowed characterizing pollen as a source of antioxidants.     

Socio-demographic determinants of municipal waste generation: case study of the Czech Republic

Journal of Material Cycles and Waste Management - Increasing pressure of the European Union on diverting municipal waste from landfills requires an active role of households and commands a radical...     

Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

When apologizing hurts: Felt transgression and restoration efforts

Apologizing is important for conflict resolution and relationship reconciliation, yet apologies often fail to restore the damaged relationship. While much research has been devoted to investigating the victims' reactions upon receiving an apology, in this paper, we adopt an apologizer-centric approach and explore the phenomenon of apologizing with no felt transgression (vis-à-vis when there is felt transgression) along with its affective and reconciliation outcomes for the apologizer. Based on Appraisal Tendency Framework, we predict that apologizing with no felt transgression will lead to reduced guilt and increased anger in the apologizer, which will result in a decreased level of their restoration efforts towards the victim. In addition, we further hypothesize about the role of organizational conflict cultures in influencing the relationship between apologizing and restoration efforts via guilt and anger. Study 1 uses a micro-narrative procedure and an inductive data analysis approach to demonstrate the varied situations and motivations of employees apologizing with (no) felt transgression, Study 2 utilizes an experimental design to examine the mediation effect, and Study 3 employs the critical incident technique to test our whole research model. Our hypotheses were largely supported across our studies. Theoretical and practical implications are discussed.