Estimation of plant pollution removal capacity based on intensive air quality measurements.

This study investigated the role of present vegetation in improving air quality in Bucharest (Romania) by analyzing six years of air quality data (PM10 and NO2) from multiple monitoring stations. The target value for human health protection is regularly exceeded for PM10 and not for NO2 over time. Road traffic has substantially contributed (over 70%) to ambient PM10 and NO2 levels. The results showed high seasonal variations in pollutant concentrations, with a pronounced effect of vegetation in reducing PM10 and NO2 levels. Indeed, air quality improvements of 7% for PM10 and 25% for NO2 during the growing season were reported. By using Principal Component Analysis and pollution data subtraction methodology, we have disentangled the impact of vegetation on air pollution and observed distinct annual patterns, particularly higher differences in PM10 and NO2 concentrations during the warm season. Despite limitations such as a lack of full tree inventory for Bucharest and a limited number of monitoring stations, the study highlighted the efficiency of urban vegetation to mitigate air pollution.

Easy method for six-fragment Golden Gate Assembly of modular vectors.

Efficient cloning techniques are a requirement for synthetic biology. This study provides a simplified cloning method based on Golden Gate Assembly that can be used for rapid vector construction. The building of multiple expression vectors with customizable modules is achieved in a timely manner with minimal hands-on time by removing unnecessary steps in the workflow. The authors constructed a total of 21 mammalian episomal expression vectors and conducted a fluorescence expression comparison for different regulatory region combinations post-transfection in HEK293T and HEPG2 cells. Screening revealed that using the EF-1α promoter in combination with the bovine growth hormone polyadenylation sequence seemed to perform best in the types of cells tested compared with other variants.

GIS-Based Multi-Criteria Analysis Method for Assessment of Lake Ecosystems Degradation-Case Study in Romania.

In general, the elaboration of the synthesis of water quality in Romania is based on the processing of a large volume of information coming from primary analytical data collected with a constant frequency by the organisms with a specific role in water quality monitoring. This study proposes a novel methodology for multi-criteria analysis aiming to evaluate the degradation state of lake ecosystems. The cornerstone of the newly presented methodology is a geographic information system (GIS) automated tool, involving the assessment of potential degradation sources affecting the watershed that supply the lakes with water. The methodology was tested by performing an analysis on 30 lakes in Romania. The lakes belong to different geographical areas, owing various natural specific conditions and were selected to fit to various types and specific local conditions. The calculation of the WRASTIC-HI (Wastewater-Recreation-Agriculture-Size-Transportation-Industry-Cover-Hazard Index) revealed that, out of 30 lake ecosystems selected as the case study, two lakes were fully degraded, 24 lakes were semi-degraded, and four were in a natural state. The four lakes characterised by a natural state are located in mountainous regions or in the Danube Delta. The results obtained on the selected lakes proved that the proposed index calculation corresponded in all case studies to the real field situation, highlighting thus the accuracy of the assessing process and increased advantages of the assessment's automation.

Evaluation of the quality of lentic ecosystems in Romania by a GIS based WRASTIC model.

Globally, ecosystems are constantly degrading as a result of pressures derived from human activities and climate change. For working towards the restoration of the natural balance, it is necessary to evaluate the deviations induced in the ecosystems, to identify where the changes took place, to know what is their amplitude and to decide where it is possible to get involved. Many aquatic ecosystems are depreciated and their restoration is often difficult. Development of appropriate assessment methodologies will improve the decision-making process in public policies for environmental protection and conservation of biodiversity. This study presents an assessment of the degradation level of lentic ecosystems in Romania, performed through a multi-criteria analysis. An extension of the WRASTIC index (Wastewater-Recreational-Agricultural-Size-Transportations-Indutrial-Cover) was generated, namely WRASTIC-HI. The new index was obtained by including values derived from the Potential Pollutant Load index. The analysis showed that 13% of the evaluated lakes are natural, 56.5% are semi-degraded and 30.5% are degraded. The proposed methodology allows to determine the spatial distribution of the degradation sources and to calculate the corresponding indicators. The results obtained provide a useful tool for diagnostic step that can be used as a cornerstone to further identification of environmental conflicts and proposals for improvement of the ecological status of the lentic ecosystems.

Synthetic aperture radar sensitivity to forest changes: A simulations-based study for the Romanian forests.

Natural and anthropogenic disturbances pose a significant threat to forest condition. Continuous, reliable and accurate forest monitoring systems are needed to provide early warning of potential declines in forest condition. To address that need, state-of-the-art simulations models were used to evaluate the utility of C-, L- and P-band synthetic aperture radar (SAR) sensors within an integrated Earth-Observation monitoring system for beech, oak and coniferous forests in Romania. The electromagnetic simulations showed differentiated sensitivity to vegetation water content, leaf area index, and forest disturbance depending on SAR wavelength and forest structure. C-band data was largely influenced by foliage volume and therefore may be useful for monitoring defoliation. Changes in water content modulated the C-band signal by <1 dB which may be insufficient for a meaningful retrieval of drought effects on forest. C-band sensitivity to significant clear-cuts was rather low (1.5 dB). More subtle effects such as selective logging or thinning may not be easily detected using C- or L-band data with the longer P-band needed for retrieving small intensity forest disturbances. Overall, the simulations emphasize that additional effort is needed to overcome current limitations arising from the use of a single frequency, acquisition time and geometry by tapping the advantages of dense time series, and by combining acquisitions from active and passive sensors. The simulation results may be applicable to forests outside of Romania since the forests types used in the study have similar morphological characteristics to forests elsewhere in Europe.