The satellite based monitoring initiative for regional air quality (SAMIRA) initiative was set up to demonstrate the exploitation of existing satellite data for monitoring regional and urban scale air quality. The project was carried out between May 2016 and December 2019 and focused on aerosol optical depth (AOD), particulate matter (PM), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂). SAMIRA was built around several research tasks: 1. The spinning enhanced visible and infrared imager (SEVIRI) AOD optimal estimation algorithm was improved and geographically extended from Poland to Romania, the Czech Republic and Southern Norway. A near real-time retrieval was implemented and is currently operational. Correlation coefficients of 0.61 and 0.62 were found between SEVIRI AOD and ground-based sun-photometer for Romania and Poland, respectively. 2. A retrieval for ground-level concentrations of PM_2.5 was implemented using the SEVIRI AOD in combination with WRF-Chem output. For representative sites a correlation of 0.56 and 0.49 between satellite-based PM_2.5 and in situ PM_2.5 was found for Poland and the Czech Republic, respectively. 3. An operational algorithm for data fusion was extended to make use of various satellite-based air quality products (NO₂, SO₂, AOD, PM_2.5 and PM₁₀). For the Czech Republic inclusion of satellite data improved mapping of NO₂ in rural areas and on an annual basis in urban background areas. It slightly improved mapping of rural and urban background SO₂. The use of satellites based AOD or PM_2.5 improved mapping results for PM_2.5 and PM₁₀. 4. A geostatistical downscaling algorithm for satellite-based air quality products was developed to bridge the gap towards urban-scale applications. Initial testing using synthetic data was followed by applying the algorithm to OMI NO₂ data with a direct comparison against high-resolution TROPOMI NO₂ as a reference, thus allowing for a quantitative assessment of the algorithm performance and demonstrating significant accuracy improvements after downscaling. We can conclude that SAMIRA demonstrated the added value of using satellite data for regional- and urban-scale air quality monitoring.

The cessation or downsizing of mining activities induced complex challenges for entire regions in Romania, leading to depopulation, poverty, and pollution. Resource-dependency locked these regions in a mono-industry setting where it was difficult for new development paths to emerge. This paper presents a historical overview of a well-known Romanian mining region and identifies promising recovery opportunities that could shift the trajectory of its mining communities towards new sustainable paths. The research was based on official statistical data for the period 1965/1966–2018, complemented by qualitative data extracted from 39 semi-structured interviews with residents from the study area. The results revealed that the concentration of employment in the mining sector, together with other concurring factors, made it difficult for the communities to find sustainable ways of development while, at the same time, highlighting some possible revitalization and recovery opportunities. The findings contribute to a better understanding of mining communities, which will support the creation of tailored policies and planning strategies aimed towards their sustainable redevelopment.

Aerosols play an important role in Earth’s climate system, and thus long-time ground- based measurements of aerosol optical properties are useful in understanding this role. Ten years of quality-assured measurements between 2010 and 2020 are used to investigate the aerosol climatology in the Cluj-Napoca area, in North-Western Romania. In this study, we analyze the aerosol optical depth (AOD), single scattering albedo (SSA) and angstrom exponent obtained by the CIMEL sun photometer, part of the aerosol robotic network (AERONET), to extract the seasonality of aerosols in the region and investigate the aerosol climatology of the area. Higher aerosol loads are found during July and August. The angstrom exponent has the lowest values in April and May, and the highest in August. The classification of aerosols using AERONET data is performed to separate dust, biomass burning, polluted urban, marine and continental-dominant aerosol mixtures. In addition, the study presents the validation efforts of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) dataset against AERONET AOD over a 10-year period.

Urban growth triggers massive changes in land use cover, exacerbating extreme natural and technological events. In order for land use planning to be efficient, it requires the integration of comprehensive risk and vulnerability assessment. This paper aims to create a bridge between the existing vulnerability theories and their implementation in land use planning policies and proposes an innovative approach to determine whether the changes in the territorial dynamics of cities draw considerable changes in communities’ social vulnerability. The methodology identifies and selects three case studies from the Urban Atlas inventory, representative of the dynamics of large Romanian cities, taking into consideration the following hazards: earthquakes, floods, and technological hazards. Vulnerability was then assessed by assigning each land use class a specific vulnerability level. The methodology involved assessing the level of vulnerability specific to the situation in 2018 compared to 2006. The results showed that major changes in land use are related to the transition of areas with a low level of vulnerability to areas with a higher level of vulnerability as a result of the urban areas expansion to the detriment of natural and agricultural areas. This is generally translated into a higher degree of vulnerability due to an increased density of artificial elements and of population in the residential areas. The findings of the study of territorial dynamics in the proximity of large industrial operators did not reveal a tendency that differed from the general trend. Although many territorial changes have been observed in the period 2006–2018, it is necessary to extend the analysis, with the issue of the new versions of the Urban Atlas, to confirm the identified trends and to express the up-to-date situation.

Mineral aerosols are considered to be the second largest source of natural aerosol, the Saharan desert being the main source of dust at global scale. Under certain meteorological conditions, Saharan dust can be transported over large parts of Europe, including Romania. The aim of this paper is to provide a complex analysis of a Saharan dust outbreak over the Transylvania region of Romania, based on the synergy of multiple ground-based and satellite sensors in order to detect the dust intrusion with a higher degree of certainty. The measurements were performed during the peak of the outbreak on April the 24th 2019, with instruments such as a Cimel sun-photometer and a multi-wavelength Raman depolarization lidar, together with an in-situ particle counter measuring at ground level. Remote sensing data from MODIS sensors on Terra and Aqua were also analyzed. Results show the presence of dust aerosol layers identified by the multi-wavelength Raman and depolarization lidar at altitudes of 2500–4000 m, and 7000 m, respectively. The measured optical and microphysical properties, together with the HYSPLIT back-trajectories, NMMB/BSC dust model, and synoptic analysis, confirm the presence of lofted Saharan dust layers over Cluj-Napoca, Romania. The NMMB/BSC dust model predicted dust load values between 1 and 1.5 g/m² over Cluj-Napoca at 12:00 UTC for April the 24th 2019. Collocated in-situ PM monitoring showed that dry deposition was low, with PM10 and PM2.5 concentrations similar to the seasonal averages for Cluj-Napoca.

This paper presents the validation results of Aerosol Optical Depth (AOD) retrieved from the Spinning Enhanced Visible Infrared Radiometer (SEVIRI) data using the near-real-time algorithm further developed in the frame of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project. The SEVIRI AOD was compared against multiple data sources: six stations of the Aerosol Robotic Network (AERONET) in Romania and Poland, three stations of the Aerosol Research Network in Poland (Poland–AOD) and Moderate Resolution Imaging Spectroradiometer (MODIS) data overlapping Romania, Czech Republic and Poland. The correlation values between a four-month dataset (June–September 2014) from SEVIRI and the closest temporally available data for both ground-based and satellite products were identified. The comparison of the SEVIRI AOD with the AERONET AOD observations generally shows a good correlation (r = 0.48–0.83). The mean bias is 0.10–0.14 and the root mean square error RMSE is between 0.11 and 0.15 for all six stations cases. For the comparison with Poland–AOD correlation values are 0.55 to 0.71. The mean bias is 0.04–0.13 and RMSE is between 0.10 and 0.14. As for the intercomparison to MODIS AOD, correlations values were generally lower (r = 0.33–0.39). Biases of −0.06 to 0.24 and RMSE of 0.04 to 0.28 were in good agreement with the ground–stations retrievals. The validation of SEVIRI AOD with AERONET results in the best correlations followed by the Poland–AOD network and MODIS retrievals. The average uncertainty estimates are evaluated resulting in most of the AOD values falling above the expected error range. A revised uncertainty estimate is proposed by including the observed bias form the AERONET validation efforts.