Towards a better understanding of the variables that influence renewable energy sources in eastern Poland.

Both the authorities and the public in Poland have turned their attention towards alternative energy production based on renewable energy sources (RES). However, according to the Polish Energy Policy 2030, the public energy sector is facing numerous challenges. The goal of this paper is, therefore, to identify the relationships between 15 spatial-economic variables and the number of RES, and to determine the strength of the correlation between each variable and the number of RES using the Spearman's rank correlation coefficient test. The study involved five voivodeships that make up the macro-region of Eastern Poland and form the eastern border of the European Union and the Schengen Area. The analysis involved two sample groups that included rural districts (n = 87), and urban districts (n = 14), respectively. In urban districts, there is a positive correlation for economic variables; whereas in rural districts, the positive correlation was found mostly for spatial variables. The surface area of agricultural land influences three types of RES, while the surface area of land under flowing water, the surface area of wasteland, and the total budget revenue demonstrate an influence on two types of RES in rural districts. All these variables also influence the total number of RES. The impact on RES is less meaningful in urban districts. Only two types of RES in urban districts and as many as four types of RES in rural districts are responsive to spatial-economic variables. Among them, the number of biogas power plants and the number of photovoltaic power stations are most strongly influenced in rural and urban districts, respectively. The results are important from the point of view of local and regional authorities and the European Renewable Energy Directive. • Spatial-economic variables can impact the number of renewable energy sources (RES). • Poorly developed European Union regions in eastern Poland were investigated. • Economic variables and RES are positively correlated in urban districts. • Spatial variables and RES are positively correlated in rural districts. [ABSTRACT FROM AUTHOR]