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This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM2.5 samples were collected during 2015–2016 and 2018–2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5 μg m−3. The PMF application identified eight sources of pollution that influenced PM2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018–2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons. [ABSTRACT FROM AUTHOR]

Wildfires are a significant source of organic aerosol during summer, with major impacts on air quality and climate. However, studies in Europe suggest a surprisingly low (less than 10%) contribution of biomass burning organic aerosol to average summertime fine particulate matter levels. In this study we combine field measurements and atmospheric chemical transport modeling, to demonstrate that the contribution of wildfires to fine particle levels in Europe during summer is seriously underestimated. Our work suggests that the corresponding contribution has been underestimated by a factor of 4–7 and that wildfires were responsible for approximately half of the total OA in Europe during July 2022. This discrepancy with previous work is due to the rapid physicochemical transformation of these emissions to secondary oxidized organic aerosol with an accompanying loss of its organic chemical fingerprints. These atmospheric reactions lead to a regionally distributed background organic aerosol that is responsible for a significant fraction of the health-related impacts caused by fine particles in Europe and probably in other continents. These adverse health effects can occur hundreds or even thousands of kilometers away from the fires. We estimate that wildfire emissions are responsible for 15–22% of the deaths in Europe due to exposure to fine particulate matter during summer. [ABSTRACT FROM AUTHOR]

An inversion method has been developed in order to quantify the emission fluxes of certain aerosol pollution sources across a wide region in the Northern Hemisphere, mainly in Europe and western Asia. The data employed are the aerosol contribution factors deducted by positive matrix factorization (PMF) on a PM 2.5 chemical composition dataset from 16 European and Asian cities for the period 2014 to 2016. The spatial resolution of the method corresponds to the geographic grid cell size of the Lagrangian particle dispersion model (Flexible Particle Dispersion Model, FLEXPART, 1 ∘ × 1 ∘) which was utilized for the air mass backward simulations. The area covered is also related to the location of the 16 cities under study. Species with an aerodynamic geometric mean diameter of 400 nm and 3.1 µ m and a geometric standard deviation of 1.6 and 2.25, respectively, were used to model the secondary sulfate and dust aerosol transport. Potential source contribution function (PSCF) analysis and generalized Tikhonov regularization were applied so as to acquire potential source areas and quantify their emission fluxes. A significant source area for secondary sulfate on the east of the Caspian Sea is indicated, when data from all stations are used. The maximum emission flux in that area is as high as 10 × 10 -12 kg m -2 s -1. When Vilnius, Dushanbe, and Kurchatov data were excluded, the areas with the highest emission fluxes were the western and central Balkans and southern Poland. The results display many similarities to the SO 2 emission maps provided by the OMI-HTAP (Ozone Monitoring Instrument-Hemispheric Transport Air Pollution) and ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) databases. For dust aerosol, measurements from Athens, Belgrade, Debrecen, Lisbon, Tirana, and Zagreb are utilized. The west Sahara region is indicated as the most important source area, and its contribution is quantified, with a maximum of 17.6 × 10 -12 kg m -2 s -1. When we apply the emission fluxes from every geographic grid cell (1 ∘ × 1 ∘) for secondary sulfate aerosol deducted with the new method to air masses originating from Vilnius, a useful approximation to the measured values is achieved. [ABSTRACT FROM AUTHOR]

Air quality in urban areas and megacities is dependent on emissions, physicochemical process and atmospheric conditions in a complex manner. The impact on air quality metrics of the COVID-19 lockdown measures was evaluated during two periods in Athens, Greece. The first period involved stoppage of educational and recreational activities and the second severe restrictions to all but necessary transport and workplace activities. Fresh traffic emissions and their aerosol products in terms of ultrafine nuclei particles and nitrates showed the most significant reduction especially during the 2nd period (40–50%). Carbonaceous aerosol both from fossil fuel emissions and biomass burning, as well as aging ultrafine and accumulation mode particles showed an increase of 10–20% of average before showing a decline (5 to 30%). It is found that removal of small nuclei and Aitken modes increased growth rates and migration of condensable species to larger particles maintaining aerosol volume. [ABSTRACT FROM AUTHOR]

3D printers are currently widely available and very popular among the general public. However, the use of these devices may pose health risks to users, attributable to air-quality issues arising from gaseous and particulate emissions in particular. We characterized emissions from a low-end 3D printer based on material extrusion, using the most common polymers: acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA). Measurements were carried out in an emission chamber and a conventional room. Particle emission rates were obtained by direct measurement and modeling, whereas the influence of extrusion temperature was also evaluated. ABS was the material with the highest aerosol emission rate. The nanoparticle emission ranged from 3.7·108 to 1.4·109 particles per second (# s−1) in chamber measurements and from 2.0·109 to 4.0·109 # s−1in room measurements, when the recommended extruder temperature was used. Printing with PLA emitted nanoparticles at the rate of 1.0·107 # s−1 inside the chamber and negligible emissions in room experiments. Emission rates were observed to depend strongly on extruder temperature. The particles' mean size ranged from 7.8 to 10.5 nanometers (nm). We also detected a significant emission rate of particles of 1 to 3 nm in size during all printing events. The amounts of volatile organic and other gaseous compounds were only traceable and are not expected to pose health risks. Our study suggests that measures preventing human exposure to high nanoparticle concentrations should be adopted when using low-end 3D printers. [ABSTRACT FROM AUTHOR]

The variability of common aerosol species in large Metropolitan urban areas is a major air quality issue with strong health impacts of large populations. PM 10 and PM 2.5 particulate matter samples were obtained at three sites characteristic of industrial, urban traffic and sub-urban residential areas in the Athens basin. Samples were analysed for anions (Cl − , NO 3 − , SO 4 2− ) and cations (K + , Na + , Ca 2+ , Mg 2+ , NH 4 + ) using ion chromatography. The spatial and temporal variability for the particulate matter (PM) concentration mass and water-soluble ionic species concentrations for the investigated sites were studied. Mean PM fine concentration levels were 20% higher at the industrial and the central urban areas compared to those in the suburban area (24.2 μg/m 3 ). The mean values for the coarse fraction at those two sites were two to three times higher compared to those at the suburban site (12.4 μg/m 3 ). Comparable concentration levels of most species were observed in all areas, while SO 4 2− and NO 3 − differ at a significant level. Furthermore, the average size distributions of the mass and individual ions at the suburban site (NCSR Demokritos) showed a bimodal size distribution. SO 4 2− and NH 4 + have their main peak in the fine fraction while NO 3 − showed equal distribution on the fine and coarse mode.. Good correlation was found for SO 4 2− and NO 3 − with Ca 2+ and Na + with Cl − for the coarse fraction in the industrial area. NH 4 + was closely correlated with SO 4 2− in the fine particles and in all areas. For the urban site the best correlations in coarse particulates were reported between Na + /Mg 2+ –Cl − , Ca 2+ /Mg 2+ –SO 4 2− , explained by neutralization of acidic aerosol by soil dust and sea salt in the coarse fraction. Moreover, time weighted concentrations roses at the industrial and urban sites, showed no significant directional dependence, indicating either uniform generation of mainly the coarse species within the metropolitan area or major influence of the regional background for the fine aerosol species. [ABSTRACT FROM AUTHOR]

Measurement of air exchange rate provides critical information in energy and indoor-air quality studies. Continuous measurement of ventilation rates is a rather costly exercise and requires specific instrumentation. In this work, an alternative methodology is proposed and tested, where the air exchange rate is calculated by utilizing indoor and outdoor routine measurements of a common pollutant such as SO 2, whereas the uncertainties induced in the calculations are analytically determined. The application of this methodology is demonstrated, for three residential microenvironments in Athens, Greece, and the results are also compared against ventilation rates calculated from differential pressure measurements. The calculated time resolved ventilation rates were applied to the mass balance equation to estimate the particle loss rate which was found to agree with literature values at an average of 0.50 h −1. The proposed method was further evaluated by applying a mass balance numerical model for the calculation of the indoor aerosol number concentrations, using the previously calculated ventilation rate, the outdoor measured number concentrations and the particle loss rates as input values. The model results for the indoors’ concentrations were found to be compared well with the experimentally measured values. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-021-93650-6, published online 14 July 2021 The original version of this Article contained an error in Affiliation 1, which was incorrectly given as 'Environmental Research Laboratory, INRASTES, NCSR Demokritos, 15310 Ag. Paraskevi, Athens, Greece'. The correct affiliation is listed below: Environmental Radioactivity Laboratory, INRASTES, NCSR Demokritos, 15310 Ag. Paraskevi, Athens, Greece The original Article has been corrected. [Extracted from the article]

Although many studies have discussed the impact of Europe's air quality, very limited research focused on the detailed phenomenology of ambient trace elements (TEs) in PM 10 in urban atmosphere. This study compiled long-term (2013–2022) measurements of speciation of ambient urban PM 10 from 55 sites of 7 countries (Switzerland, Spain, France, Greece, Italy, Portugal, UK), aiming to elucidate the phenomenology of 20 TEs in PM 10 in urban Europe. The monitoring sites comprised urban background (UB, n = 26), traffic (TR, n = 10), industrial (IN, n = 5), suburban background (SUB, n = 7), and rural background (RB, n = 7) types. The sampling campaigns were conducted using standardized protocols to ensure data comparability. In each country, PM 10 samples were collected over a fixed period using high-volume air samplers. The analysis encompassed the spatio-temporal distribution of TEs, and relationships between TEs at each site. Results indicated an annual average for the sum of 20 TEs of 90 ± 65 ng/m3, with TR and IN sites exhibiting the highest concentrations (130 ± 66 and 131 ± 80 ng/m3, respectively). Seasonal variability in TEs concentrations, influenced by emission sources and meteorology, revealed significant differences (p < 0.05) across all monitoring sites. Estimation of TE concentrations highlighted distinct ratios between non-carcinogenic and carcinogenic metals, with Zn (40 ± 49 ng/m3), Ti (21 ± 29 ng/m3), and Cu (23 ± 35 ng/m3) dominating non-carcinogenic TEs, while Cr (5 ± 7 ng/m3), and Ni (2 ± 6 ng/m3) were prominent among carcinogenic ones. Correlations between TEs across diverse locations and seasons varied, in agreement with differences in emission sources and meteorological conditions. This study provides valuable insights into TEs in pan-European urban atmosphere, contributing to a comprehensive dataset for future environmental protection policies. • Analysis of 20 trace elements (TEs) in PM 10 across various environments in Europe. • Decade-long, 55-site dataset enhances understanding of TEs dynamics. • TEs concentrations vary significantly between different monitoring sites. • Dominance of Zn, Ti, and Cu indicates diverse pollution sources. • Stricter emission controls and targeted health assessments for urban air quality. [ABSTRACT FROM AUTHOR]

Sampling campaigns using the same equipment and methodology were conducted to assess and compare the air quality at three South European subway systems (Barcelona, Athens and Oporto), focusing on concentrations and chemical composition of PM 2.5 on subway platforms, as well as PM 2.5 concentrations inside trains. Experimental results showed that the mean PM 2.5 concentrations widely varied among the European subway systems, and even among different platforms within the same underground system, which might be associated to distinct station and tunnel designs and ventilation systems. In all cases PM 2.5 concentrations on the platforms were higher than those in the urban ambient air, evidencing that there is generation of PM 2.5 associated with the subway systems operation. Subway PM 2.5 consisted of elemental iron, total carbon, crustal matter, secondary inorganic compounds, insoluble sulphate, halite and trace elements. Of all metals, Fe was the most abundant, accounting for 29–43% of the total PM 2.5 mass (41–61% if Fe 2 O 3 is considered), indicating the existence of an Fe source in the subway system, which could have its origin in mechanical friction and wear processes between rails, wheels and brakes. The trace elements with the highest enrichment in the subway PM 2.5 were Ba, Cu, Mn, Zn, Cr, Sb, Sr, Ni, Sn, Co, Zr and Mo. Similar PM 2.5 diurnal trends were observed on platforms from different subway systems, with higher concentrations during subway operating hours than during the transport service interruption, and lower levels on weekends than on weekdays. PM 2.5 concentrations depended largely on the operation and frequency of the trains and the ventilation system, and were lower inside the trains, when air conditioning system was operating properly, than on the platforms. However, the PM 2.5 concentrations increased considerably when the train windows were open. The PM 2.5 levels inside the trains decreased with the trains passage in aboveground sections. [ABSTRACT FROM AUTHOR]

[Display omitted] • Source apportionment of organic aerosol in 22 year-long datasets in Europe; • Harmonised source apportionment protocol; • Oxygenated organic aerosol dominates across Europe in all seasons; • Solid-fuel combustion is a significant source in most European sites, especially in winter; • Traffic source is present in both urban and non-urban sites with constant and non-negligible contributions. Organic aerosol (OA) is a key component of total submicron particulate matter (PM 1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM 1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models. [ABSTRACT FROM AUTHOR]