Anaerobic Biodegradation of Blends Based on Polyvinyl Alcohol

The presented work deals with blends composed of polyvinyl alcohol (PVA) and biopolymers (protein hydrolysate, starch, lignin). PVA does not belong to biologically inert plastics but its degradation rate (particularly under anaerobic conditions) is low. A potential solution to the issue problem lies in preparation of blends with readily degradable substrates. We studied degradation of blow-molded films made of commercial PVA and mentioned biopolymers in an aqueous anaerobic environment employing inoculation with digested activated sludge from the municipal wastewater treatment plant. Films prepared in the first experimental series were to be used for comparing biodegradation of blends modified with native or plasticized starch; in this case effect of plasticization was not proved. The degree of PVA degradation after modification with native or plasticized starch increases in a striking and practically same manner already at a starch level as low as approximately 5 wt.%. Films of the second experimental series were prepared as additionally modified with protein hydrolysate and lignin. Only lignin-modified samples exhibited a somewhat lower degree of biodegradation but regarding the measure of lignin present in blend this circumstance is not essential. Level of biodegradation with all discussed films differed only slightly—within range of experimental error.     

Analysis of emergency situations at municipal solid waste landfills

Journal of Material Cycles and Waste Management - This work focuses on the issue of emergency prevention in the operation of municipal solid waste landfills. In this work, an emergency is...     

Cybernetic formulation of control in ecosystems

Hierarchical control formulations are given for a simple predator-prey model: self-optimization of one subsystem, natural multi-goal optimization, man's multiparameter control of an ecosystem and man's control of a self-optimizing ecosystem. Natural multigoal optimization suggests how several levels of an ecosystem can be optimized simultaneously. The idea of management of a self-optimizing ecosystem takes into account the reactions of the ecosystem to man's activity.     

Natural control mechanisms in models of aquatic ecosystems

Based on cybernetic categories of natural control mechanisms, four generations of ecosystem models are distinguished: feed-forward, feedback, self-adaptation and self-organization models. The analysis of the natural control mechanisms in aquatic ecosystems suggests that different processes are controlled in different ways, and, although the four mechanisms were identified in historical sequence, they all operate simultaneously. The concept of self-organization of an ecosystem is introduced and specified for a model of an aquatic pelagic ecosystem. The concept of the ecosystem as a multilayer, multigoal and multiechelon hierarchical system with hierarchy of the levels of biological organization is also introduced.     

Modelling future soil chemistry at a highly polluted forest site at Istebna in Southern Poland using the "SAFE" model

The multi-layer dynamic model SAFE was applied to the forested catchment Istebna (Southern Poland), to study recovery from acidification. Environmental pollution in the area has been historically high. The model uses data from an intensive monitoring plot established in 1999 in a spruce stand, which was planted in 1880. Observations showed that the soil was depleted of base cations. The measured base saturation in 1999 was between 5 and 8% in the different soil layers. Model predictions assuming full implementation of the UNECE 1999 Gothenburg Protocol and present day base cation deposition show that the base saturation will slowly increase to 20% by 2100. Despite large emission reductions, Istebna still suffers from the very high loads of acidifying input during the past decades. Soil recovery depends on future emissions especially on base cation deposition. The recovery will be even slower if the base cation deposition decreases further.     

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.