The purpose of this study, which contains historical data recorded over a period of 40 years, was to identify the main factors that influence and control the level of wood mass production. The main reason was to optimize the management of forest areas and was driven by the necessity to identify factors that can influence most of the volume produced by coniferous forests located in southeast Europe. The data was collected between1980 and 2005 at the National Institute for Research and Development in Forestry, for forests located in the Southern Carpathians, Romania. The studied data refer to the parameters that model forest structure for spruce, fir, pine, and larch. These are the main resinous species found in the Southern Carpathians. The total area covered by these forests is 143,431 ha. At the forest species level, the analysis consists of 16,162 records (corresponding to the elements of the trees), covering an area of 45,008 ha for fir, 4711 ha for larch, 81,995 ha for spruce, and 11,717 ha for pine. The aim of this research has been to investigate and to assess the impact and magnitude of abiotic factors such as altitude and field aspect on forest structures from the main resinous stands located in the Southern Carpathians. Taking into account the size of the database as well as the duration for collecting data, a complete statistical and systematic approach was considered optimum. This resulted from our wish to emphasize and evaluate the influence of each analysed factor on the wood mass production level. The relationship between abiotic factors and forest structure has been analysed by using a systematic statistical approach in order to provide a useful theoretical reference for the improvement of forest management practices in the context of multiple climatic, environmental, and socio-economic challenges. These common characteristics have been found by applying ANOVA and multivariate statistical methods such as PCA and FA methods. A series of parameters were considered in this investigation, namely altitude (ALT), forest site type (TS), forest type (TP), consistency (CONS) etc. In order to obtain a complete image, we have also applied multivariate analysis methods that emphasize the effect size for each database parameter. At such a level of recorded data, the statistical approach ensures a factor level of p <0.001 while the accuracy in evaluating effect size is increased. As such, they influence the spreading and structure of the studied resinous stands to a higher degree, regardless of species.

This study investigates changes in pollution associated with the lockdown period caused by the COVID-19 pandemic in Galati (45.43° N, 28.03° E), a Romanian city located in the southeast of Romania. The study is focused on nitrogen dioxide (NO₂), a trace gas which can be related to emissions from industrial activities, heating, and transportation. The investigation is based on in situ observations from local Air Quality Monitoring Stations (AQMS) and mobile remote sensing observations by Differential Optical Absorption Spectroscopy (DOAS) technique. We also show results of the NO₂ vertical column measured by TROPOMI (TROPOspheric Monitoring Instrument), a space instrument onboard of satellite mission Sentinel-5P, to complement local ground-based measurements. For in situ observations, the lockdown interval (23 March 2020–15 May 2020) was separated from normal periods. The decrease in local NO₂ concentration during lockdown, measured in situ, is rather small, of about 10–40% at the most, is observed only at some stations, and is better seen during workdays than during weekends. We conclude that the decrease in NO₂ content over Galati city during lockdown is relatively small and may be attributed to the reduction in local traffic, a consequence of special measures and restrictions imposed during the COVID-19 lockdown by the Romanian authorities.

This study aimed to improve the performance of a wastewater treatment plant (WWTP) simulated with Benchmark Model No. 2 (BSM2). To achieve this objective, three control strategies were implemented and tested. The first control strategy aimed to maintain the concentration of nitrate and nitrite nitrogen (S_NO) by controlling the external carbon flowrate (strategy A₁), and the second control strategy aimed to maintain the ammonia and ammonium nitrogen (S_NH) at a desired level with the use of a cascade controller (strategy A₂). The third strategy was applied to control the total suspended solids (TSS) (strategy A₃). Combinations of these strategies were considered (B₁, B₂, and B₃ strategies), as well as the use of all three together (strategy C₁). The control strategies presented in this paper were compared to the default control strategy of BSM2 to validate and identify the one that provided the best performance. The results revealed that the B₁ strategy was the most environmentally friendly, while C₁ obtained the highest overall performance. Several Monte Carlo simulations were performed for the validated control strategies, to identify the optimal setpoint values. For the C₁ strategy, a second method of optimization regarding polynomial interpolation was considered. The applied optimization methods provided the optimal reference values for the PI (proportional integral) controllers.

This study investigates the thermal behavior of three Lufft CHM15k ceilometers at ACTRIS observational platforms and evaluates statistical associations between housekeeping temperatures and attenuated backscatter. The instruments are deployed at RADO-Galati and RADO-Bucharest (Romania) and AGORA Granada (Spain). External, internal, optical-module, and detector temperatures from 14 July 2023 to 14 July 2025 were analyzed using Pearson and sliding-window correlations, while time–range correlations assessed associations with the SNR-screened and smoothed attenuated backscatter coefficient. Long-term analysis showed strong external–internal thermal coupling, with clearer seasonal modulation at the Romanian sites than at AGORA–Granada. Five warm- and five cold-season days from 2024 were analyzed per platform. Across the three sites, 51 contiguous regions with strong correlations (|PCC| ≥ 0.8) and at least 50 connected hour–range cells were identified; 47 occurred during warm-season cases and four during cold-season cases. Significant associations were concentrated mainly at lower measurement ranges and extended farther during warm-season cases. These correlations do not demonstrate direct temperature-induced modification of atmospheric backscatter because common diurnal atmospheric variability may contribute. Systematic housekeeping-parameter monitoring can support quality control, preventive maintenance, and resource-efficient operation of long-term atmospheric remote-sensing networks, strengthening sustainable environmental monitoring and resilient research infrastructure relevant to the Sustainable Development Goals (SDGs).