Animal waste, including chicken manure, is a category of biomass considered for application in the energy industry. Poland is leading poultry producer in Europe, with a chicken population assessed at over 176 million animals. This paper aims to determine the theoretical and technical energy potential of chicken manure in Poland. The volume of chicken manure was assessed as 4.49 million tons per year considering three particular poultry rearing systems. The physicochemical properties of examined manure specimens indicate considerable conformity with the data reported in the literature. The results of proximate and ultimate analyses confirm a considerable effect of the rearing system on the energy parameters of the manure. The heating value of the chicken manure was calculated for the high moisture material in the condition as received from the farms. The value of annual theoretical energy potential in Poland was found to be equal to around 40.38 PJ. Annual technical potential of chicken biomass determined for four different energy conversion paths occurred significantly smaller then theoretical and has the value from 9.01 PJ to 27.3 PJ. The bigger energy degradation was found for heat and electricity production via anaerobic digestion path, while fluidized bed combustion occurred the most efficient scenario.

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The present paper discusses a novel methodology based on neural network to determine air pollutants' correlation with life expectancy in European countries. The models were developed using historical data from the period 1992-2016, for a set of 20 European countries. The subject of the analysis included the input variables of the following air pollutants: sulphur oxides, nitrogen oxides, carbon monoxide, particulate matters, polycyclic aromatic hydrocarbons and non-methane volatile organic compounds. Our main findings indicate that all the variables significantly affect life expectancy. Sensitivity of constructed neural networks to pollutants proved to be particularly important in the case of changes in the value of particulate matters, sulphur oxides and non-methane volatile organic compounds. The most frequent association was found for fine particle. Modelled courses of changes in the variable under study coincide with the actual data, which confirms that the proposed models generalize acquired knowledge well.

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Rapid weather phenomena, particularly sudden and intense rainfall, have become a problem in urban areas in recent years. During heavy rainfall, urban rainwater drainage systems are unable to discharge huge amounts of runoff into collecting reservoirs, which usually results in local flooding. This paper presents attempts to forecast a reduction in the load on the rainwater drainage system through the implementation of green roofs in a case study covering two selected districts of Opole (Poland)—the Old Town and the City Centre. Model tests of extensive and intensive roofs were carried out, in order to determine the reduction of rainwater runoff from the roof surface for the site under study. The potential of the roofs of the buildings to make a green roof was also determined using geographical information systems (GIS), for a case study of two central districts of Opole. It proposed a methodology to determine the rainwater drainage system load reduction by making green roofs. The analyses carried out lead to the conclusion that, in the districts selected for the study, the execution of green roofs on 25% of the of buildings with the potential to implement this type of roof solution could reduce the load on the rain water system by a degree that protects the city area from local flooding.