Inter-annual trends of ultrafine particles in urban Europe.

Ultrafine particles (UFP, those with diameters ≤ 100 nm), have been reported to potentially penetrate deeply into the respiratory system, translocate through the alveoli, and affect various organs, potentially correlating with increased mortality. The aim of this study is to assess long-term trends (5-11 years) in mostly urban UFP concentrations based on measurements of particle number size distributions (PNSD). Additionally, concentrations of other pollutants and meteorological variables were evaluated to support the interpretations. PNSD datasets from 12 urban background (UB), 5 traffic (TR), 3 suburban background (SUB) and 1 regional background (RB) sites in 15 European cities and 1 in the USA were evaluated. The non-parametric Theil-Sen's method was used to detect monotonic trends. Meta-analyses were carried out to assess the overall trends and those for different environments. The results showed significant decreases in NO, NO2, BC, CO, and particle concentrations in the Aitken (25-100 nm) and the Accumulation (100-800 nm) modes, suggesting a positive impact of the implementation of EURO 5/V and 6/VI vehicle standards on European air quality. The growing use of Diesel Particle Filters (DPFs) might also have clearly reduced exhaust emissions of BC, PM, and the Aitken and Accumulation mode particles. However, as reported by prior studies, there remains an issue of poor control of Nucleation mode particles (smaller than 25 nm), which are not fully reduced with current DPFs, without emission controls for semi-volatile organic compounds, and might have different origins than road traffic. Thus, contrasting trends for Nucleation mode particles were obtained across the cities studied. This mode also affected the UFP and total PNC trends because of the high proportion of Nucleation mode particles in both concentration ranges. It was also found that the urban temperature increasing trends might have also influenced those of PNC, Nucleation and Aitken modes.

Mandating indoor air quality for public buildings.

If some countries lead by example, standards may increasingly become normalized.

Variability of ambient air ammonia in urban Europe (Finland, France, Italy, Spain, and the UK).

This study addressed the scarcity of NH3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH3 concentration across sites reached 8.0 ± 8.9 µg/m3. Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 µg/m3), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 µg/m3, respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 µg/m3, with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH3 concentrations in urban Europe, contributing to future efforts in benchmarking NH3 pollution control in urban areas.

Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations.

A reliable determination of equivalent black carbon (eBC) mass concentrations derived from filter absorption photometers (FAPs) measurements depends on the appropriate quantification of the mass absorption cross-section (MAC) for converting the absorption coefficient (babs) to eBC. This study investigates the spatial-temporal variability of the MAC obtained from simultaneous elemental carbon (EC) and babs measurements performed at 22 sites. We compared different methodologies for retrieving eBC integrating different options for calculating MAC including: locally derived, median value calculated from 22 sites, and site-specific rolling MAC. The eBC concentrations that underwent correction using these methods were identified as LeBC (local MAC), MeBC (median MAC), and ReBC (Rolling MAC) respectively. Pronounced differences (up to more than 50 %) were observed between eBC as directly provided by FAPs (NeBC; Nominal instrumental MAC) and ReBC due to the differences observed between the experimental and nominal MAC values. The median MAC was 7.8 ± 3.4 m2 g-1 from 12 aethalometers at 880 nm, and 10.6 ± 4.7 m2 g-1 from 10 MAAPs at 637 nm. The experimental MAC showed significant site and seasonal dependencies, with heterogeneous patterns between summer and winter in different regions. In addition, long-term trend analysis revealed statistically significant (s.s.) decreasing trends in EC. Interestingly, we showed that the corresponding corrected eBC trends are not independent of the way eBC is calculated due to the variability of MAC. NeBC and EC decreasing trends were consistent at sites with no significant trend in experimental MAC. Conversely, where MAC showed s.s. trend, the NeBC and EC trends were not consistent while ReBC concentration followed the same pattern as EC. These results underscore the importance of accounting for MAC variations when deriving eBC measurements from FAPs and emphasize the necessity of incorporating EC observations to constrain the uncertainty associated with eBC.

Estimating the probability of occurrence of African dust outbreaks over regions of the western Mediterranean basin from thermodynamic atmospheric parameters.

Desert dust is currently recognized as a health risk factor. Therefore, the World Health Organization (WHO) is actively promoting the establishment of early warning systems for sand and dust storms. This study introduces a methodology to estimate the probability of African dust outbreaks occurring in eight different regions of the Iberian Peninsula and the Balearic Islands. In each region, a multilinear regression model was developed to calculate daily probabilities of dust events using three thermodynamic variables (geopotential thickness in the 1000-500 hPa layer, mean potential temperature between 925 and 700 hPa, and temperature anomalies at 850 hPa) as assessment parameters. All days with African dust transport over each study region were identified in the period 2001-2021 using a proven procedure. This information was then utilized to establish a functional relationship between the values of the thermodynamic parameters and the probability of African dust outbreaks occurring. The validation of this methodology involved comparing the daily probabilities of dust events generated by the models in 2001-2021 with the daily African dust contributions to PM10 regional background levels in each region. On average, daily dust contributions increased proportionally with the increase in daily probabilities, reaching zero for days with low probabilities. Furthermore, a well-defined seasonal evolution of probability values was observed in all regions, with the highest values in the summer months and the lowest in the winter period, ensuring the physical relevance of the models' results. Finally, upward trends were observed in all regions for the three thermodynamic parameters over 1940-2021. Thus, the probability of dust events development also increased in this period. It demonstrates that the aggravation of warm conditions in southern Europe in the last decades, have modified the frequency of North-African dust outbreaks over the western Mediterranean basin.

High-Precision Microscale Particulate Matter Prediction in Diverse Environments Using a Long Short-Term Memory Neural Network and Street View Imagery.

In this study, we propose a novel long short-term memory (LSTM) neural network model that leverages color features (HSV: hue, saturation, value) extracted from street images to estimate air quality with particulate matter (PM) in four typical European environments: urban, suburban, villages, and the harbor. To evaluate its performance, we utilize concentration data for eight parameters of ambient PM (PM1.0, PM2.5, and PM10, particle number concentration, lung-deposited surface area, equivalent mass concentrations of ultraviolet PM, black carbon, and brown carbon) collected from a mobile monitoring platform during the nonheating season in downtown Augsburg, Germany, along with synchronized street view images. Experimental comparisons were conducted between the LSTM model and other deep learning models (recurrent neural network and gated recurrent unit). The results clearly demonstrate a better performance of the LSTM model compared with other statistically based models. The LSTM-HSV model achieved impressive interpretability rates above 80%, for the eight PM metrics mentioned above, indicating the expected performance of the proposed model. Moreover, the successful application of the LSTM-HSV model in other seasons of Augsburg city and various environments (suburbs, villages, and harbor cities) demonstrates its satisfactory generalization capabilities in both temporal and spatial dimensions. The successful application of the LSTM-HSV model underscores its potential as a versatile tool for the estimation of air pollution after presampling of the studied area, with broad implications for urban planning and public health initiatives.

Constructing transferable and interpretable machine learning models for black carbon concentrations.

Black carbon (BC) has received increasing attention from researchers due to its adverse health effects. However, in-situ BC measurements are often not included as a regulated variable in air quality monitoring networks. Machine learning (ML) models have been studied extensively to serve as virtual sensors to complement the reference instruments. This study evaluates and compares three white-box (WB) and four black-box (BB) ML models to estimate BC concentrations, with the focus to show their transferability and interpretability. We train the models with the long-term air pollutant and weather measurements in Barcelona urban background site, and test them in other European urban and traffic sites. Despite the difference in geographical locations and measurement sites, BC correlates the strongest with particle number concentration of accumulation mode (PNacc, r = 0.73-0.85) and nitrogen dioxide (NO2, r = 0.68-0.85) and the weakest with meteorological parameters. Due to its similarity of correlation behaviour, the ML models trained in Barcelona performs prominently at the traffic site in Helsinki (R2 = 0.80-0.86; mean absolute error MAE = 3.90-4.73 %) and at the urban background site in Dresden (R2 = 0.79-0.84; MAE = 4.23-4.82 %). WB models appear to explain less variability of BC than BB models, long short-term memory (LSTM) model of which outperforms the rest of the models. In terms of interpretability, we adopt several methods for individual model to quantify and normalize the relative importance of each input feature. The overall static relative importance commonly used for WB models demonstrate varying results from the dynamic values utilized to show local contribution used for BB models. PNacc and NO2 on average have the strongest absolute static contribution; however, they simultaneously impact the estimation positively and negatively at different sites. This comprehensive analysis demonstrates that the possibility of these interpretable air pollutant ML models to be transfered across space and time.

Uncertainties in source allocation of carbonaceous aerosols in a Mediterranean region.

Understanding the atmospheric processes involving carbonaceous aerosols (CAs) is crucial for assessing air pollution impacts on human health and climate. The sources and formation mechanisms of CAs are not well understood, making it challenging to quantify impacts in models. Studies suggest residential wood combustion (RWC) and traffic significantly contribute to CAs in Europe's urban and rural areas. Here, we used an atmospheric chemistry model (MONARCH) and three different emission inventories (two versions of the European-scale emission inventory CAMS-REG_v4 and the HERMESv3 detailed national inventory for Spain) to assess the uncertainties in CAs simulation and source allocation (from traffic, RWC, shipping, fires and others) in Northeast Spain. For this, black carbon (BC) and organic aerosol (OA) measurements performed at three supersites representing different environments (urban, regional and remote) were used. Our findings show the importance of model resolution and detailed emission input data in accurately reproducing BC/OA observations. Even though emissions of total particulate matter are rather consistent between inventories in Spain, we found discrepancies between them mainly related to the spatiotemporal disaggregation (particularly relevant for traffic and RWC) and the treatment of the condensable fraction of CAs in RWC (changes in the speciation of elemental/organic carbon). The main source contribution to BC concentrations in the urban site is traffic, accounting for 71.1%/65.2% (January/July) in close agreement with the fossil contribution derived from observations (78.8%/84.2%), followed by RWC (12.8%/3%) and shipping emissions (5.4%/13.8%). An over-representation of RWC (winter) and shipping (summer) is obtained with CAMS-REG_v4. Noteworthy uncertainties arise in OA results due to condensables in emissions and a limited secondary aerosol production in the model. These findings offer insights into MONARCH's effectiveness in simulating CAs concentrations and source contribution in Northeast Spain. The study highlights the benefits of combining new datasets and modeling techniques to refine emission inventories and better understand and mitigate air pollution impacts.

Characterizing the sources of ambient PM10 organic aerosol in urban and rural Catalonia, Spain.

Organic aerosols (OA) have recently been shown to be the dominant contributor to the oxidative potential of airborne particulate matter in northeastern Spain. We collected PM10 filter samples every fourth day from January 2017 to March 2018 at two sampling stations located in Barcelona city and Montseny Natural Park, representing urban and rural areas, respectively. The chemical composition of PM10 was analyzed offline using a broad set of analytical instruments, including high-resolution time-of-flight mass spectrometry (HR-ToF-AMS), a total organic carbon analyzer (TCA), inductively coupled plasma atomic emission spectrometry (ICP-AES), inductively coupled plasma mass spectrometry (ICP-MS), ion chromatography (IC), and thermal-optical carbon analyzer. Source apportionment analysis of the water-soluble organic content of the samples measured via HR-ToF-AMS revealed two primary and two secondary sources of OA, which included biomass-burning OA (BBOA), sulfur-containing OA (SCOA), as well as summer- and winter­oxygenated OA (SOOA and WOOA). The presence of hydrocarbon-like water-insoluble OA was also identified based on concentration trends in black carbon and nitrogen oxides. The results from the source apportionment analysis of the inorganic composition were correlated with different OA factors to assess potential source contributors. Barcelona showed significantly higher average water-soluble OA concentrations (5.63 ± 0.56 µg m-3) than Montseny (3.27 ± 0.37 µg m-3) over the sampling period. WOOA accounted for nearly 27 % of the averaged OA in Barcelona compared to only 7 % in Montseny. In contrast, SOOA had a greater contribution to OA in Montseny (47 %) than in Barcelona (24 %). SCOA and BBOA were responsible for 15-28 % of the OA at both sites. There were also seasonal variations in the relative contributions of different OA sources. Our overall results showed that local anthropogenic sources were primarily responsible for up to 70 % of ambient soluble OA in Barcelona, and regulating local-scale emissions could significantly improve air quality in urban Spain.

Key factors for abating particulate matter in a highly industrialized area in N Spain: Fugitive emissions and secondary aerosol precursors.

In highly industrialized areas, abating particulate matter (PM) is complex owing to the variety of emission sources with different chemical profiles that may mix in the atmosphere. Gijón-an industrial city in northern Spain-was selected as a case study to better understand the key emission sources and improve air quality in highly industrialized areas. Accordingly, the trends of various air quality indicators (PM10, PM2.5, SO2, NO2, and O3) during the past decade (2010-2019) were analyzed. Additionally, the inorganic and organic PM10 compositions were analyzed for source apportionment studies and to assess the impact of COVID-19 restrictions on PM10 levels. The results revealed that over the past decade, PM10 concentrations decreased, whereas PM2.5 concentrations dominated by secondary inorganic aerosols (SIA) remained relatively constant. Notably, during the COVID-19 lockdown, the PM10 concentration increased by 9.1%, primarily owing to an increase in regional SIA (>65%) due to specific meteorological conditions that favor the formation of secondary PM from gaseous precursors. Overall, eight key PM10 sources were identified: "industrial fugitive PM resuspension" (FPM, 28% of mean PM10 concentration), "aged sea spray" (SSp, 16%), "secondary nitrate" (SN, 15%), "local diffuse source" (LPM, 12%), "solid fuel combustion" (SFC, 7.8%), "biomass burning" (BB, 7.4%), "secondary sulphate" (SSu, 6.0%), and "sinter" (SIN, 4.5%). The PM10 concentration in Gijón is significantly influenced by the integrated steel industry (FPM, SFC, and SIN; 41% of PM10) and fugitive primary PM emissions were the main source (FPM and LPM; 40%). To reduce PM10 and PM2.5 concentrations, industrial fugitive emissions, which are currently poorly regulated, and SIA precursors must be abated. This study provides a methodological approach that combines trend analysis, chemical speciation, and source apportionment for assessing pollution abatement strategies in industrialized areas with a complex mix of emission sources.

Assessing ozone abatement scenarios in the framework of the Spanish ozone mitigation plan.

Tropospheric ozone (O3) is a secondary air pollutant that affects human health, vegetation and climate, especially in Mediterranean countries such as Spain. In order to tackle this long-standing issue, the Spanish government recently started to design the Spanish O3 Mitigation Plan. To support this initiative and ultimately provide recommendations, we performed a first ambitious emission and air quality modeling exercise. This study presents the development of different emission scenarios - aligned with or beyond the measures planned for 2030 in Spain - and the modeling of their respective impact on the O3 pollution across Spain (in July 2019) with both MONARCH and WRF-CMAQ air quality models. The modeling experiments include a base case scenario, a so-called planned emission (PE) scenario integrating the expected emission changes related to 2030, and a set of specific emission scenarios in which additional emission changes are applied to specific sectors (on e.g., road transport, maritime traffic) on top of the PE scenario. The planned emission scenario considerably reduces daily 8-h maximum O3 concentrations (-4 µg/m3 on average), with strongest reductions in Madrid region, north of Catalonia, Valencia region, Galicia and Andalusia. The frequency of observed daily exceedances of the 120 µg/m3 daily 8-h maximum target value and 180 µg/m3 hourly information threshold could be reduced by -37 and -77 %, respectively. The results of the specific scenarios highlight road transport and maritime traffic as two key emission sectors contributing to O3 pollution, over the entire country and the Mediterranean coast, respectively, while solvent use and industry emissions have a more limited and localized impact on O3. In any case, even with the implementation of all the emission scenarios, daily exceedances of the aforementioned thresholds will still be recorded over the country.

The variability of mass concentrations and source apportionment analysis of equivalent black carbon across urban Europe.

This study analyzed the variability of equivalent black carbon (eBC) mass concentrations and their sources in urban Europe to provide insights into the use of eBC as an advanced air quality (AQ) parameter for AQ standards. This study compiled eBC mass concentration datasets covering the period between 2006 and 2022 from 50 measurement stations, including 23 urban background (UB), 18 traffic (TR), 7 suburban (SUB), and 2 regional background (RB) sites. The results highlighted the need for the harmonization of eBC measurements to allow for direct comparisons between eBC mass concentrations measured across urban Europe. The eBC mass concentrations exhibited a decreasing trend as follows: TR > UB > SUB > RB. Furthermore, a clear decreasing trend in eBC concentrations was observed in the UB sites moving from Southern to Northern Europe. The eBC mass concentrations exhibited significant spatiotemporal heterogeneity, including marked differences in eBC mass concentration and variable contributions of pollution sources to bulk eBC between different cities. Seasonal patterns in eBC concentrations were also evident, with higher winter concentrations observed in a large proportion of cities, especially at UB and SUB sites. The contribution of eBC from fossil fuel combustion, mostly traffic (eBCT) was higher than that of residential and commercial sources (eBCRC) in all European sites studied. Nevertheless, eBCRC still had a substantial contribution to total eBC mass concentrations at a majority of the sites. eBC trend analysis revealed decreasing trends for eBCT over the last decade, while eBCRC remained relatively constant or even increased slightly in some cities.

Source apportionment for indoor air pollution: Current challenges and future directions.

Source apportionment (SA) for indoor air pollution is challenging due to the multiplicity and high variability of indoor sources, the complex physical and chemical processes that act as primary sources, sinks and sources of precursors that lead to secondary formation, and the interconnection with the outdoor environment. While the major indoor sources have been recognized, there is still a need for understanding the contribution of indoor versus outdoor-generated pollutants penetrating indoors, and how SA is influenced by the complex processes that occur in indoor environments. This paper reviews our current understanding of SA, through reviewing information on the SA techniques used, the targeted pollutants that have been studied to date, and their source apportionment, along with limitations or knowledge gaps in this research field. The majority (78 %) of SA studies to date focused on PM chemical composition/size distribution, with fewer studies covering organic compounds such as ketones, carbonyls and aldehydes. Regarding the SA method used, the majority of studies have used Positive Matrix Factorization (31 %), Principal Component Analysis (26 %) and Chemical Mass Balance (7 %) receptor models. The indoor PM sources identified to date include building materials and furniture emissions, indoor combustion-related sources, cooking-related sources, resuspension, cleaning and consumer products emissions, secondary-generated pollutants indoors and other products and activity-related emissions. The outdoor environment contribution to the measured pollutant indoors varies considerably (<10 %- 90 %) among the studies. Future challenges for this research area include the need for optimization of indoor air quality monitoring and data selection as well as the incorporation of physical and chemical processes in indoor air into source apportionment methodology.

Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF.

Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.

Spatiotemporal variations of tropospheric ozone in Spain (2008-2019).

This study aims to support the development of Spain's Ozone Mitigation Plan by evaluating the present-day spatial variation (2015-2019) and trends (2008-2019) for seven ground-level ozone (O3) metrics relevant for human/ecosystems exposure and regulatory purposes. Results indicate that the spatial variation of O3 depends on the part of the O3 distribution being analyzed. Metrics associated with moderate O3 concentrations depict an increasing O3 gradient between the northern and Mediterranean coasts due to climatic factors, while for metrics considering the upper end of the O3 distribution, this climatic gradient tends to attenuate in favor of hotspot regions pointing to relevant local/regional O3 formation. A classification of atmospheric regions in Spain is proposed based on their O3 pollution patterns, to identify priority areas (or O3 hotspots) where local/regional precursor abatement might significantly reduce O3 during pollution episodes. The trends assessment reveals a narrowing of the O3 distribution at the national level, with metrics influenced by lower concentrations tending to increase over time, and those reflecting the higher end of the O3 distribution tending to decrease. While most stations show no statistically significant variations, contrasting O3 trends are evident among the O3 hotspots. The Madrid area exhibits the majority of upward trends across all metrics, frequently with the highest increasing rates, implying increasing O3 associated with both chronic and episodic exposure. The Valencian Community area exhibits a mixed variation pattern, with moderate to high O3 metrics increasing and peak metrics decreasing, while O3 in areas downwind of Barcelona, the Guadalquivir Valley and Puertollano shows no variations. Sevilla is the only large Spanish city with generalized O3 decreasing trends. The different O3 trends among hotspots highlight the need for mitigation measures to be designed at a local/regional scale to be effective. This approach may offer valuable insights for other countries developing O3 mitigation plans.

Effects of Desert Dust and Sandstorms on Human Health: A Scoping Review.

Desert dust and sandstorms are recurring environmental phenomena that are reported to produce serious health risks worldwide. This scoping review was conducted to identify the most likely health effects of desert dust and sandstorms and the methods used to characterize desert dust exposure from the existing epidemiological literature. We systematically searched PubMed/MEDLINE, Web of Science, and Scopus to identify studies that reported the effects of desert dust and sandstorms on human health. Search terms referred to desert dust or sandstorm exposure, names of major deserts, and health outcomes. Health effects were cross-tabulated with study design variables (e.g., epidemiological design and methods to quantify dust exposure), desert dust source, health outcomes and conditions. We identified 204 studies that met the inclusion criteria for the scoping review. More than half of the studies (52.9%) used a time-series study design. However, we found a substantial variation in the methods used to identify and quantify desert dust exposure. The binary metric of dust exposure was more frequently used than the continuous metric for all desert dust source locations. Most studies (84.8%) reported significant associations between desert dust and adverse health effects, mainly for respiratory and cardiovascular mortality and morbidity causes. Although there is a large body of evidence on the health effects of desert dust and sandstorms, the existing epidemiological studies have significant limitations related to exposure measurement and statistical analysis that potentially contribute to inconsistencies in determining the effect of desert dust on human health.

Coronavirus Disease 2019 and Airborne Transmission: Science Rejected, Lives Lost. Can Society Do Better?

This is an account that should be heard of an important struggle: the struggle of a large group of experts who came together at the beginning of the COVID-19 pandemic to warn the world about the risk of airborne transmission and the consequences of ignoring it. We alerted the World Health Organization about the potential significance of the airborne transmission of SARS-CoV-2 and the urgent need to control it, but our concerns were dismissed. Here we describe how this happened and the consequences. We hope that by reporting this story we can raise awareness of the importance of interdisciplinary collaboration and the need to be open to new evidence, and to prevent it from happening again. Acknowledgement of an issue, and the emergence of new evidence related to it, is the first necessary step towards finding effective mitigation solutions.

Levels and drivers of urban black carbon and health risk assessment during pre- and COVID19 lockdown in Augsburg, Germany.

This study aimed to evaluate the levels and phenomenology of equivalent black carbon (eBC) at the city center of Augsburg, Germany (01/2018 to 12/2020). Furthermore, the potential health risk of eBC based on equivalent numbers of passively smoked cigarettes (PSC) was also evaluated, with special emphasis on the impact caused by the COVID19 lockdown restriction measures. As it could be expected, peak concentrations of eBC were commonly recorded in morning (06:00-8:00 LT) and night (19:00-22:00 LT) in all seasons, coinciding with traffic rush hours and atmospheric stagnation. The variability of eBC was highly influenced by diurnal variations in traffic and meteorology (air temperature (T), mixing-layer height (MLH), wind speed (WS)) across days and seasons. Furthermore, a marked "weekend effect" was evidenced, with an average eBC decrease of ∼35% due to lower traffic flow. During the COVID19 lockdown period, an average ∼60% reduction of the traffic flow resulted in ∼30% eBC decrease, as the health risks of eBC exposure was markedly reduced during this period. The implementation of a multilinear regression analysis allowed to explain for 53% of the variability in measured eBC, indicating that the several factors (e.g., traffic and meteorology) may contribute simultaneously to this proportion. Overall, this study will provide valuable input to the policy makers to mitigate eBC pollutant and its adverse effect on environment and human health.