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.

Renewable energy (RE) policies can play an effective role in the development of renewable resources. The main goal of this paper was to conduct a content analysis on RE development policies in Iran’s five-year National Development Plan (NDP) by investigating upstream national documents. To achieve the goal, 29 upstream documents related to RE were identified and analyzed through a systematic literature review. Then, a qualitative content analysis was applied to analyze the documents. The results showed that Iran’s current RE policies need to be reviewed, reformed, and strengthened. For example, lack of sufficient attention to renewable heat and fuel was one of the deficiencies of RE policies in Iran’s five-year NDP. The decentralization of policymaking in the unified organization was also one of the weaknesses in the policymaking process of the RE. Iran can develop sustainable and clean RE policies by using sources such as solar, wind, geothermal, hydropower, wave, and tidal power. The paper concludes that, although RE policies have the potential for development in Iran due to environmental, social, and economic advantages, they could face some infrastructural, managerial, socio-cultural, and economic challenges. Accordingly, effective and innovative policymaking is required to meet such challenges.

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.

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.

Between 14 March and 21 April 2022, an extensive investigation of an extraordinary Saharan dust intrusion over Europe was performed based on lidar measurements obtained by the European Aerosol Research Lidar Network (EARLINET). The dust episode was divided into two distinct periods, one in March and one in April, characterized by different dust transport paths. The dust aerosol layers were studied over 18 EARLINET stations, examining aerosol characteristics during March and April in four different regions (M-I, M-II, M-III, and M-IV and A-I, A-II, A-III, and A-IV, respectively), focusing on parameters such as aerosol layer thickness, center of mass (CoM), lidar ratio (LR), particle linear depolarization ratio (PLDR), and Ångström exponents (ÅE). In March, regions exhibited varying dust geometrical and optical properties, with mean CoM values ranging from approximately 3.5 to 4.8 km, and mean LR values typically between 36 and 54 sr. PLDR values indicated the presence of both pure and mixed dust aerosols, with values ranging from 0.20 to 0.32 at 355 nm and 0.24 to 0.31 at 532 nm. ÅE values suggested a range of particle sizes, with some regions showing a predominance of coarse particles. Aerosol Optical Depth (AOD) simulations from the NAAPS model indicated significant dust activity across Europe, with AOD values reaching up to 1.60. In April, dust aerosol layers were observed between 3.2 to 5.2 km. Mean LR values typically ranged from 35 to 51 sr at both 355 nm and 532 nm, while PLDR values confirmed the presence of dust aerosols, with mean values between 0.22 and 0.31 at 355 nm and 0.25 to 0.31 at 532 nm. The ÅE values suggested a mixture of particle sizes. The AOD values in April were generally lower, not exceeding 0.8, indicating a less intense dust presence compared to March. The findings highlight spatial and temporal variations in aerosol characteristics across the regions, during the distinctive periods. From 15 to 16 March 2022, Saharan dust significantly reduced UV-B radiation by approximately 14% over the ATZ station (Athens, GR). Backward air mass trajectories showed that the dust originated from the Western and Central Sahara when, during this specific case, the air mass trajectories passed over GRA (Granada, ES) and PAY (Payerne, CH) before reaching ATZ, maintaining high relative humidity and almost stable aerosol properties throughout its transport. Lidar data revealed elevated aerosol backscatter (b_aer) and PLDR values, combined with low LR and ÅE values, indicative of pure dust aerosols.

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.