Under the European Union (EU) energy efficiency targets that Romania has assumed, increasing the share of solar energy has been one of the main points to be considered. The most important solar energy resources are found in the lowlands and low hills in southern and south-eastern parts of the country. The current paper is focused on the Romanian Plain, which has the best environmental conditions to support the development of photovoltaic (PV) farms. One hundred and ten PV farms have been identified and mapped which cover a total area of 1393 hectares. Although it provides a clean and sustainable energy source, the related environmental implications of PV farms could be either positive or negative. In this study, some of the main categories of impacts have been selected for identification and analysis of their environmental consequences. Several indicators have been computed: the share of PV farms from the main land use/cover categories and main soil types, and the distance of PV farms to forests, water bodies, or protected areas. The overall results of the study reveal the current and potential impacts of PV farms in order to understand the interactions between the environment and the use of renewable energy sources and further support science-based solutions for sustainable development.

The aboveground forest biomass plays a key role in the global carbon cycle and is considered a large and constant carbon reservoir. Hence, exploring the future potential changes in forest-cover pattern can help to estimate the trend of forest biomass and therefore, carbon stock in a certain area. As a result, the present paper attempts to model the potential changes in aboveground forest carbon stock based on the forest-cover pattern scenario simulated for 2050. Specifically, the resulting aboveground forest biomass, estimated for 2015 using the allometric equation based on diameter at breast height and the estimated forest density, was used as baseline data in the present approach. These spatial data were integrated into the forest-cover pattern scenario, predicted by using a spatially explicit model, i.e., the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), in order to estimate the potential variation of aboveground forest carbon stock. Our results suggest an overall increase by approximately 4% in the aboveground forest carbon stock until 2050 in Romania. However, important differences in the forest-cover pattern change were predicted on the regional scale, thus highlighting that the rates of carbon accumulation will change significantly in large areas. This study may increase the knowledge of aboveground forest biomass and the future trend of carbon stock in the European countries. Furthermore, due to their predictive character, the results may provide a background for further studies, in order to investigate the potential ecological, socio-economic and forest management responses to the changes in the aboveground forest carbon stock. However, in view of the uncertainties associated with the data accuracy and methodology used, it is presumed that the results include several spatial errors related to the estimation of aboveground forest biomass and simulation of future forest-cover pattern change and therefore, represent an uncertainty for the practical management of applications and decisions.

Based on the national level data on energy consumption by final consumption sectors (agricultural, industrial, construction, residential and transport), the present study is aimed at estimating the energy consumption at county level. The overall energy Romania has consumed throughout a year has been broken down into ‘demographic’ and ‘economic’ components. The changes in the two components were determined on an annual basis for the following reference years: 1995, 2000, 2005, 2010 and 2015. The variables used in the current investigation were assembled into two groups of indicators: demographic (urban population, population size, proportion of the population aged 65 years and over, the economically active population divided according to activities of national economy: agriculture, industry, transport), and economic (GDP per capita, energy consumption by the activities of the national economy: agriculture, residential, industry, transport). In some cases, where a significant share of the population worked in the industry sector (with the probability of a diversified industry), our calculations overestimated energy consumption. This may also be due to the cumulative effect of some demographic factors (i.e., the high degree of urbanization). The paper discusses the effect of the demographic variables (e.g., size, age and occupational structures) have on energy consumption. The paper shows that the economic growth Romania has been subject to since the year 2000 has led to a rise in energy consumption for two economic activities (agriculture, transportation) and it also turned out that improving the technologies used in industry has a positive effect on energy efficiency. Energy efficiency depends, in addition to the technologies used in each economic activity, on demographic factors. Some of the demographic factors have different trends in terms of energy consumption. The effect of the population size must be explained in the context of changes in the structure by age groups (aging of the population), changes in fertility and mortality rates. Moreover, the economic structure changes alongside the alterations undergone by the demographic structure. This, in turn, changes production and consumption, transport infrastructure, as well as social services. In order to draw firm conclusions about the relationship between energy consumption and population structure by age group, further detailed studies are needed, including making use of other indicators.

In the context of climate change, Romania is actively advancing its transition to renewable energy, contributing to the European Green Deal goals of zero greenhouse gas emissions by 2050 and 45 % renewable energy share by 2030. Romania's onshore wind potential is estimated at 14,000 MW, with an existing installed capacity of around 3000 MW, concentrated mainly in the Dobrogea region. The National Energy Strategy 2022-2030 forecasts an additional 2302 MW capacity increase. This study develops a spatial suitability model for wind farm siting using the Fuzzy Analytic Hierarchy Process (FAHP) combined with GIS-based analysis. Eight criteria were evaluated and weighted based on expert judgment. Factors considered include wind speed, slope, altitude, land use, distance to transmission lines, settlements, roads and protected areas. Using GIS Weighted Overlay analysis, land was classified into five suitability classes. Results show that 51.1 % of Romania's territory is suitable for wind energy projects, especially in the eastern and southeastern counties of Tulcea, Constanța, Brăila, Galați, Călăraşi, and Vaslui. Validation against existing wind farm locations showed a 69.9 % spatial match within areas classified a 'Very High' suitability, and over 80 % within the combined 'High' and 'Very High' classes. Discrepancies are mainly due to protected area zoning and spatial data resolution. The findings deliver quantitative evidence to optimize wind farm siting and support data-driven decisions for policymakers and investors in line with EU decarbonization objectives.

Living close to green infrastructure (GI) components might be the dream of many people who are often exposed to cities’ pollution, congestion, or lack of green amenities. Due to its multiple benefits, green infrastructure plays a significant role in driving people’s decisions to leave inner-city areas and move to suburban locations. However, how GI components are used once people move into the suburbs must be better understood. Thus, this study explores residents’ rationales for leaving the inner city and moving to the suburbs and how they use suburban GI components. A survey was undertaken in six suburbs from three European cities: Poznań (Poland), Salzburg (Austria), and Bucharest (Romania). We found that people self-reported that green amenities were the main reason for choosing a suburban residence. Furthermore, those residents who moved to the suburbs were more interested in using their private gardens than larger parks and prefer natural green areas with high potential for recreation to agricultural landscapes for leisure. This study advocates for investment in private green spaces in suburban developments due to their deep interweaving with residents’ leisure preferences.