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Climate change has the potential to increase surface ozone (O3) concentrations, known as the “ozone–climate penalty”, through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozone–climate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15 ppb (model range 12 to 18 ppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozone–climate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx-limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low-NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozone–climate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario.

Occupants play a key role in determining final building energy consumption. Empirical evidence must support occupants' modelling. Experiments on human responses to Indoor Environmental Quality (IEQ) are usually performed in test rooms or as in-field monitoring. Between these two approaches, living laboratories, often abbreviated as living labs, represent a valid alternative due to their resemblance to real-world settings. This allows observing actual behaviours while keeping the capability to reliably monitor and control the indoor environment. This work systematically reviewed the available information from 34 living labs for human comfort studies worldwide to define the scope, characteristics, and significance of living labs, for the first time. Most of the reviewed living labs are office environments, and only a few do not involve a university research institution in their operation and management. Most of them are in Europe and the United States, whereas there is a lack of such facilities in other locations and climate zones (e.g., tropics). A larger number of comfort studies in living labs is required to clarify the differences in the knowledge acquired in these experiments compared to in-field and laboratory ones. The review shows that living labs add opportunities for testing and optimizing in-novations in human-centric solutions for comfortable green buildings. Through the living labs approach it is possible to holistically capture the influence of IEQ on occupant perception and the related response, to gather data on larger and more diverse groups of people, and to conduct multi-domain comfort studies involving multidisciplinary approaches given their real-life settings.

The Printed Optical Particle Spectrometer (POPS) is an advanced and small low-cost, light-weight, and high-sensitivity optical particle counter (OPC), particularly designed for deployed on unpiloted aerial vehicles (UAVs) and balloon sondes. We report the performance of the POPS against a reference scanning mobility particle sizer (SMPS) and an airborne passive cavity aerosol spectrometer probe (PCASP) while the POPS is operated on the ground and also while operated on a quadcopter drone, a DJI Matrice 200 V2. This is the first such documented test of the performance of a POPS instrument on a UAV. We investigate the root mean square difference (RMSD) and mean absolute difference (MAD) in particle number concentrations (PNCs) when operating on the ground and on the Matrice 200. When windspeeds are less than 2.6 m/s, we find only modest differences in the RMSDs and MADs of 2.4 % and 2.3 % respectively when operating on the ground, and to 5 % and 3 % when operating at 10m altitude. When windspeeds are greater than 2.6 m/s but less than 7.7 m/s the RMSDs and MADs increase to 10.2 % and 7.8 % respectively when operating on the ground, and 26.2 % and 19.1 %, respectively when operating at 10m altitude. No statistical difference in PNCs was detected when operating on the UAV in either ascent or descent. We also find size distributions of aerosols in the accumulation mode (here defined by diameter, d, where 0.1 ≤ d ≤ 1 µm) are relatively consistent between measurements at the surface and measurements at 10m altitude with RMSD and MAD of less than 21.6 % and 15.7 %, respectively. However, the differences between coarse mode (here defined by d > 1 µm) are universally larger than those measured at the surface with a RMSD and MAD approaching 49.5 % and 40.4 %. Our results suggest that the impact of the UAV rotors on the POPS does not unduly affect the performance of the POPS for wind speed less than 2.6 m/s, but when operating under higher wind speed of up to 7.6 m/s, larger discrepancies are noted. In addition to this, it appears that the POPS measures sub-micron aerosol particles more accurately than super-micron aerosol particles when airborne on the UAV. These measurements lay the foundations for determining the magnitude of potential errors that might be introduced into measured aerosol particle size distributions and concentrations owing to the turbulence created by the rotors on the UAV.

Environmental issues and health-benefitting design strategies have raised interest in natural and renewable building materials, resulting in an increased focus on the use of wood in built environment. The influence of wooden materials on measured and perceived indoor environment quality (IEQ) has gained attention during the past few decades, with a growing number of studies having explored the issue. This review was conducted to examine and summarise the body of research on the influence of wooden interior materials on IEQ, with an emphasis on the following themes: emissions of chemical compounds, moisture buffering of indoor air, antibacterial effects, acoustics, and psychological and physiological effects. This review found that wooden interior materials exert mainly positive or neutral effects on IEQ, such as moderating humidity fluctuations of indoor air, inducing positive feelings in occupants, and inhibiting certain bacteria. Negative effects on IEQ are limited to volatile organic compounds emitted from wood. The odour thresholds of some aldehydes and terpenes are low enough to affect the perceived IEQ. Additionally, concentrations of formaldehyde and acrolein may under certain conditions cause adverse health effects. Further studies are needed to better understand these phenomena and take advantage of the beneficial effects while hindering the unpleasant ones.

In the case of tangible cultural heritage items made of natural fibres, biodegradation due to microorganisms can lead over time to undesirable deterioration, including physical, mechanical and chemical damage as well as aesthetic alteration of materials. In this study, the antifungal activity tests were performed on 3 old maps (on silk, on canvas and on paper) using the AATCC 30-2004 test method. Map samples were immersed in a chitosan solution (10 g/l) and evaluated using Scanning Electron Microscopy (SEM) with a Field Emission Scanning Electron Microscope (ULTRA 55, ZEISS). The process showed that, due to its antimicrobial effect, chitosan treatment is effective for removing external agents and microorganisms present on fibre surfaces. The technique is simple, efficient and the results indicated that chitosan can be transformed into a very good and cheap antimicrobial solution for the conservation and preservation of heritage objects., University of Oradea [329/2021, 317/2021], The research article was produced with equal scientific involvement of all authors. We acknowledge the partially contribution of University of Oradea Grants, Competition Scientific Research of Excellence Related to Priority Areas with Capitalization through Technology Transfer: INO-TRANSFER-UO, Projects No. 329/2021; No. 317/2021.

A coordinated observational and modelling campaign targeting biogenic aerosols in the air was performed during spring 2021 at two locations in Northern Europe: Helsinki (Finland) and Siauliai (Lithuania), approximately 500 km from each other in north-south direction. The campaign started on March 1, 2021 in Siauliai (12 March in Helsinki) and continued till mid-May in Siauliai (end of May in Helsinki), thus recording the transition of the atmospheric biogenic aerosols profile from winter to summer. The observations included a variety of samplers working on different principles. The core of the program was based on 2- and 2.4--hourly sampling in Helsinki and Siauliai, respectively, with sticky slides (Hirst 24-h trap in Helsinki, Rapid-E slides in Siauliai). The slides were subsequently processed extracting the DNA from the collected aerosols, which was further sequenced using the 3-rd generation sequencing technology. The core sampling was accompanied with daily and daytime sampling using standard filter collectors. The hourly aerosol concentrations at the Helsinki monitoring site were obtained with a Poleno flow cytometer, which could recognize some of the aerosol types. The sampling campaign was supported by numerical modelling. For every sample, SILAM model was applied to calculate its footprint and to predict anthropogenic and natural aerosol concentrations, at both observation sites. The first results confirmed the feasibility of the DNA collection by the applied techniques: all but one delivered sufficient amount of DNA for the following analysis, in over 40% of the cases sufficient for direct DNA sequencing without the PCR step. A substantial variability of the DNA yield has been noticed, generally not following the diurnal variations of the total-aerosol concentrations, which themselves showed variability not related to daytime. An expected upward trend of the biological material amount towards summer was observed but the day-to-day variability was large. The campaign DNA analysis produced the first high-resolution dataset of bioaerosol composition in the North-European spring. It also highlighted the deficiency of generic DNA databases in applications to atmospheric biota: about 40% of samples were not identified with standard bioinformatic methods.

Satellite measurements in nadir and limb viewing geometry provide a complementary view of the atmosphere. An effective combination of the limb and nadir measurements can give new information about atmospheric composition. In this work, we present tropospheric ozone column datasets that have been created using a combination of total ozone columns from OMI (Ozone Monitoring Instrument) and TROPOMI (TROPOspheric Monitoring Instrument) with stratospheric ozone column datasets from several available limb-viewing instruments: MLS (Microwave Limb Sounder), OSIRIS (Optical Spectrograph and InfraRed Imaging System), MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), SCIAMACHY (SCanning Imaging Spectrometer for Atmospheric CHartographY), OMPS-LP (Ozone Mapping and Profiles Suite – Limb Profiler), and GOMOS (Global Ozone Monitoring by Occultation of Stars). We have developed further the methodological aspects of the assessment of tropospheric ozone using the residual method supported by simulations with the chemistry transport model SILAM (System for Integrated modeLling of Atmospheric coMposition). It has been shown that the accurate assessment of ozone in the upper troposphere and the lower stratosphere (UTLS) is of high importance for detecting the ground-level ozone patterns. The stratospheric ozone column is derived from a combination of ozone profiles from several satellite instruments in limb-viewing geometry. We developed a method for the data homogenization, which includes the removal of biases and a posteriori estimation of random uncertainties, thus making the data from different instruments compatible with each other. The high-horizontal- and vertical-resolution dataset of ozone profiles is created via interpolation of the limb profiles from each day to a 1∘×1∘ horizonal grid. A new kriging-type interpolation method, which takes into account data uncertainties and the information about natural ozone variations from the SILAM-adjusted ozone field, has been developed. To mitigate the limited accuracy and coverage of the limb profile data in the UTLS, a smooth transition to the model data is applied below the tropopause. This allows for the estimation of the stratospheric ozone column with full coverage of the UTLS. The derived ozone profiles are in very good agreement with collocated ozonesonde measurements. The residual method was successfully applied to OMI and TROPOMI clear-sky total ozone data in combination with the stratospheric ozone column from the developed high-resolution limb profile dataset. The resulting tropospheric ozone column is in very good agreement with other satellite data. The global distributions of tropospheric ozone exhibit enhancements associated with the regions of high tropospheric ozone production. The main datasets created are (i) a monthly 1∘×1∘ global tropospheric ozone column dataset (from ground to 3 km below the tropopause) using OMI and limb instruments, (ii) a monthly 1∘×1∘ global tropospheric ozone column dataset using TROPOMI and limb instruments, and (iii) a daily 1∘×1∘ interpolated stratospheric ozone column from limb instruments. Other datasets, which are created as an intermediate step of creating the tropospheric ozone column data, are (i) a daily 1∘×1∘ clear-sky and total ozone column from OMI and TROPOMI, (ii) a daily 1∘×1∘ homogenized and interpolated dataset of ozone profiles from limb instruments, and (iii) a daily 1∘×1∘ dataset of ozone profiles from SILAM simulations with adjustment to satellite data. These datasets can be used in various studies related to variability and trends in ozone distributions in both the troposphere and the stratosphere. The datasets are processed from the beginning of OMI and TROPOMI measurements until December 2020 and are planned to be regularly extended in the future.

Some studies show that significant uncertainties affect emission inventories, which may impeach conclusions based on air-quality model results. These uncertainties result from the need to compile a wide variety of information to estimate an emission inventory. In this work, we propose and discuss a screening method to compare two emission inventories, with the overall goal of improving the quality of emission inventories by feeding back the results of the screening to inventory compilers who can check the inconsistencies found and, where applicable, resolve errors. The method targets three different aspects: (1) the total emissions assigned to a series of large geographical areas, countries in our application; (2) the way these country total emissions are shared in terms of sector of activity; and (3) the way inventories spatially distribute emissions from countries to smaller areas, cities in our application. The first step of the screening approach consists of sorting the data and keeping only emission contributions that are relevant enough. In a second step, the method identifies, among those significant differences, the most important ones that provide evidence of methodological divergence and/or errors that can be found and resolved in at least one of the inventories. The approach has been used to compare two versions of the CAMS-REG European-scale inventory over 150 cities in Europe for selected activity sectors. Among the 4500 screened pollutant sectors, about 450 were kept as relevant, among which 46 showed inconsistencies. The analysis indicated that these inconsistencies arose almost equally from large-scale reporting and spatial distribution differences. They mostly affect SO2 and PM coarse emissions from the industrial and residential sectors. The screening approach is general and can be used for other types of applications related to emission inventories.

This paper proposes a deep learning model that integrates a convolutional neural network with a gate circulation unit that captures patterns of high-peak PM2.5 concentrations. The purpose is to accurately predict high-peak PM2.5 concentration data that cannot be trained in general deep learning models. For the training of the proposed model, we used all available weather and air quality data for three years from 2015 to 2017 from 25 stations of the National Institute of Environmental Research (NIER) and the Korea Meteorological Administration (KMA) observatory in Seoul, South Korea. Our model trained three years of data and predicted high-peak PM2.5 concentrations for the year 2018. In addition, we propose a Gaussian filter algorithm as a preprocessing method for capturing high concentrations of PM2.5 in the Seoul area and predicting them more accurately. This model overcomes the limitations of conventional deep learning approaches that are unable to predict high peak PM2.5 concentrations. Comparing model measurements at each of the 25 monitoring sites in 2018, we found that the deep learning model with a Gaussian filter achieved an index of agreement of 0.73–0.89 and a proportion of correctness of 0.89–0.96, and compared to the conventional deep learning method (average POC = 0.85), the Gaussian filter algorithm (average POC = 0.94) improved the accuracy of high-concentration PM2.5 prediction by an average of about 9%. Applying this algorithm in the preprocessing stage could be updated to predict the risk of high PM2.5 concentrations in real time.

© 2019 Accurate Computational Fluid Dynamics (CFD) simulations of Atmospheric Boundary Layer (ABL) flow are essential for a wide range of applications, including atmospheric heat and pollutant dispersion. An important requirement is that the imposed inlet boundary conditions should yield vertical profiles that maintain horizontal homogeneity (i.e. no streamwise gradients) in the upstream part of the computational domain for all relevant parameters, including temperature. Many previous studies imposed a uniform temperature profile at the inlet, which has often led to horizontal inhomogeneity of the temperature profile. This study presents a new temperature inlet profile that can yield horizontal homogeneity for neutral and near-neutral ABL conditions when used in combination with the Standard Gradient Diffusion Hypothesis (SGDH) and a temperature wall function. The horizontal homogeneity by this profile is verified by 2D Reynolds-Averaged Navier-Stokes (RANS) CFD simulations performed with the standard k-ε turbulence model and the SGDH. The approach in this paper can be extended to other types of wall functions and other RANS closure schemes for Reynolds stresses and turbulent heat fluxes. ispartof: JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS vol:191 pages:91-102 status: published

Tropospheric ozone (O-3) concentrations are observed to increase with temperature in urban and rural locations. We investigated the apparent temperature dependency of daytime ozone concentration in the Finnish boreal forest in summertime based on long-term measurements. We used statistical mixed effects models to separate the direct effects of temperature from other factors influencing this dependency, such as weather conditions, long-range transport of precursors, and concentration of various hydrocarbons. The apparent temperature dependency of 1.16 ppb ?(-1) based on a simple linear regression was reduced to 0.87 ppb ?(-1) within the canopy for summer daytime data after considering these factors. In addition, our results indicated that small oxygenated volatile organic compounds may play an important role in the temperature dependence of O-3 concentrations in this dataset from a low-NOx environment. Summertime observations and daytime data were selected for this analysis to focus on an environment that is significantly affected by biogenic emissions. Despite limitations due to selection of the data, these results highlight the importance of considering factors contributing to the apparent temperature dependence of the O-3 concentration. In addition, our results show that a mixed effects model achieves relatively good predictive accuracy for this dataset without explicitly calculating all processes involved in O-3 formation and removal.

We conduct the first 4D-Var inversion of NH3 accounting for NH3 bi-directional flux, using CrIS satellite NH3 observations over Europe in 2016. We find posterior NH3 emissions peak more in springtime than prior emissions at continental to national scales, and annually they are generally smaller than the prior emissions over central Europe, but larger over most of the rest of Europe. Annual posterior anthropogenic NH3 emissions for 25 European Union members (EU25) are 25% higher than the prior emissions and very close (3 fluxes as uni-directional emissions, while the monthly regional difference can be up to 34% (Switzerland in July). Compared to monthly mean in-situ observations, our posterior NH3 emissions from both schemes generally improve the magnitude and seasonality of simulated surface NH3 and bulk NHx wet deposition throughout most of Europe, whereas evaluation against hourly measurements at a background site shows the bi-directional scheme better captures observed diurnal variability of surface NH3. This contrast highlights the need for accurately simulating diurnal variability of NH3 in assimilation of sun-synchronous observations and also the potential value of future geostationary satellite observations. Overall, our top-down ammonia emissions can help to examine the effectiveness of air pollution control policies to facilitate future air pollution management, as well as helping us understand the uncertainty in top-down NH3 emissions estimates associated with treatment of NH3 surface exchange.

We applied data-based recurrence CFD (rCFD) to model pollutant dispersion in near-field flow configurations. In case of complex topologies, the global-domain version of rCFD fails to account for local recurrent flow features. We therefore developed a novel island-based version of rCFD, which partitions the computational domain to isolate islands of high recurrence prominence, and subsequently defines a distinct recurrence path for each of these islands. We applied island-based rCFD to pollutant dispersion for two side-by-side cubical buildings with three different gap widths in between them and a real urban environment. We showed that numerical predictions of pollutant dispersion by island-based rCFD were in excellent agreement with full CFD simulations, thus outperforming the global-domain version of rCFD. In both applications, island-based rCFD simulations ran three orders of magnitude faster than corresponding full CFD simulations. In the second application, this speed-up enabled real-time simulations on a computational grid of 10 million cells.

ilustraciones, diagramas, mapas, tablas Boundary-Layer Meteorology refers to the theoretical, numerical, and experimental framework that focuses on studying the interactions between the earth's surface and the lower troposphere. These interactions are crucial for several applications in various temporal and spatial scales. A better understanding of these interactions implies studying the structure and variability of the Atmospheric Boundary-Layer as a result of processes that are better described in the realm of a combination of fluid dynamics and thermodynamics. By definition, the ABL is turbulent, which means that the processes of mixing and exchange of energy, momentum, and scalars from the Surface Layer to the rest of the atmosphere depend on turbulence, both thermal and mechanic. In this sense, the small-scale physical processes depicted by the different terms in Turbulent Kinetic Energy budget equation modulate the characteristics of large-scale phenomena. One of the main challenges in studying the ABL dynamics is the high heterogeneity of the underlying forcing imposed by the earth's surface. Ranging from abrupt changes in orography to a wide variety of land uses and roughness elements, complex terrain is the rule rather than the exception, especially when dealing with processes involving anthropogenic modified environments. Nevertheless, most of our understanding of turbulence in the ABL is based on an idealized picture of real-life scenarios, e.g., horizontally homogeneous and flat terrains, implying that most of the exchange is vertical, and horizontal contributions are small and negligible. The main goal of this work is to identify and gain insight into the main processes between the synoptic- and micro-scale ends of the spectrum of atmospheric motions (including their cross-scale interactions) that modulate the ABL structure and dynamics over a complex and highly urbanized low-latitude valley. The Aburrá Valley is located in the Colombian Andes. The work follows an experimental approach, using multiple data sources, in order to evaluate the potential contribution of these phenomena on the boundary-layer variability in the study area. The intention is to shed some light on open questions regarding boundary-layer characteristics and some of their environmental implications over such complex terrain. The structure of this document was decided considering that, once in final form, Chapters 3, 4 and 5 will be submitted to be considered for publication in peer reviewed journals (Chapter 2 is already published). For this reason, this thesis includes four main self-contained chapters (Chapters 2 to 5) with the results of the evaluation of the boundary-layer dynamics in a highly complex terrain at different spatio-temporal scales and some of the interactions between them. La Meteorología de la Capa Límite hace referencia al marco teórico, numérico y experimental que se enfoca en estudiar las interacciones entre la superficie terrestre y la tropósfera baja. Estas interacciones son fundamentales para muchas aplicaciones en varias escalas espacio-temporales. Un mejor entendimiento de dichas interacciones implica el estudio de la estructura y variabilidad de la Capa Límite Atmosférica como resultado de procesos que son mejor descritos en el ámbito de una combinación de dinámica de fluidos y termodinámica. Por definición, la Capa Límite es turbulenta, lo cual significa que los procesos de mezcla e intercambio de energía, momentum y escalares, desde la Capa Superficial al resto de la atmósfera, dependen de la turbulencia, tanto térmica como mecánica.En este sentido, los procesos físicos de pequeña escala descritos por los términos en la ecuación de balance de la energía cinética turbulenta modulen las características de los fenómenos a mayor escala. Uno de los más grandes desafíos a la hora de estudiar las dinámicas de la Capa Límite es la alta heterogeneidad de la superficie terrestre, que van desde cambios abruptos en la orografía, hasta una amplia variedad de usos del suelo y elementos rugosos. Así, los terrenos complejos más que la excepción son la regla, especialmente cuando se trabajan con procesos que involucran modificaciones antrópicas al ambiente. Sin embargo, la gran mayoría de nuestro conocimiento en turbulencia en la Capa límite es basado en una imagen idealizada de los escenarios de la vida real, es decir, terrenos planos y horizontalmente homogéneos, lo cual implica que la mayoría de los intercambios aon verticales, y las contribuciones horizontales son pequeñas y pueden ser despreciadas. El principal objetivo de esta investigación es identificar y comprender los principales procesos de las diferentes escalas atmosféricas de movimiento (incluidas las interacciones entre escalas) los cuales modulan la estructura y dinámica de la Capa Límite en el Valle de Aburrá, ell cual es un valle altamente urbanizado ubicado en los Andes Colombianos. El trabajo sigue un enfoque experimental, usando múltiples fuentes de datos, con el objetivo de evaluar la potencial contribución de estos fenómenos en la variabilidad de la Capa límite en la zona de estudio. La intención es dar algo de luz sobre preguntas que siguen abiertas relacionadas con las características de la capa límite y algunas de sus implicaciones ambientales en un terreno tan complejo. (Texto tomado de la fuente) Doctorado Doctor en Ingeniería Meteorología de capa límite Área Curricular de Medio Ambiente

Many of the world’s major cities have implemented tree planting programs based on assumed environmental and social benefits of urban forests. Recent studies have increasingly tested these assumptions and provide empirical evidence for the contributions of tree planting programs, as well as their feasibility and limits, for solving or mitigating urban environmental and social issues. We propose that current evidence supports local cooling, stormwater absorption, and health benefits of urban trees for local residents. However, the potential for urban trees to appreciably mitigate greenhouse gas emissions and air pollution over a wide array of sites and environmental conditions is limited. Consequently, urban trees appear to be more promising for climate and pollutionadaptationstrategies than mitigation strategies. In large part, this is due to space constraints limiting the extent of urban tree canopies relative to the current magnitude of emissions. The most promising environmental and health impacts of urban trees are those that can be realized with well-stewarded tree planting and localized design interventions at site to municipal scales. Tree planting at these scales has documented benefits on local climate and health, which can be maximized through targeted site design followed by monitoring, adaptive management, and studies of long-term eco-evolutionary dynamics.

Similarities and differences in the submicron atmospheric aerosol chemical composition are analyzed from a unique set of measurements performed at 21 sites across Europe for at least one year. These sites are located between 35 and 62°N and 10° W – 26°E, and represent various types of settings (remote, coastal, rural, industrial, urban). Measurements were all carried out on-line with a 30-min time resolution using mass spectroscopy based instruments known as Aerosol Chemical Speciation Monitors (ACSM) and Aerosol Mass Spectrometers (AMS) and following common measurement guidelines. Data regarding organics, sulfate, nitrate and ammonium concentrations, as well as the sum of them called non-refractory submicron aerosol mass concentration ([NR-PM1]) are discussed. NR-PM1 concentrations generally increase from remote to urban sites. They are mostly larger in the mid-latitude band than in southern and northern Europe. On average, organics account for the major part (36–64%) of NR-PM1 followed by sulfate (12–44%) and nitrate (6–35%). The annual mean chemical composition of NR-PM1 at rural (or regional background) sites and urban background sites are very similar. Considering rural and regional background sites only, nitrate contribution is higher and sulfate contribution is lower in mid-latitude Europe compared to northern and southern Europe. Large seasonal variations in concentrations (μg/m³) of one or more components of NR-PM1 can be observed at all sites, as well as in the chemical composition of NR-PM1 (%) at most sites. Significant diel cycles in the contribution to [NR-PM1] of organics, sulfate, and nitrate can be observed at a majority of sites both in winter and summer. Early morning minima in organics in concomitance with maxima in nitrate are common features at regional and urban background sites. Daily variations are much smaller at a number of coastal and rural sites. Looking at NR-PM1 chemical composition as a function of NR-PM1 mass concentration reveals that although organics account for the major fraction of NR-PM1 at all concentration levels at most sites, nitrate contribution generally increases with NR-PM1 mass concentration and predominates when NR-PM1 mass concentrations exceed 40 μg/m³ at half of the sites., This study was partially supported by the European Union's projects ACTRIS (EU FP7-262254) and ACTRIS-2 (EU Horizon 2020–654109). COST Action CA16109 COLOSSAL, Chemical On-Line cOmpoSition and Source Apportionment of fine aerosoL, is acknowledged. The ACSM observations at Birkenes was funded by the Norwegian Ministry of Climate and Environment Strategic Institute Program. IDAEA-CSIC (3 datasets: BCN, MSA, MSY) was partially supported by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the PRISMA project (CGL 2012-39623-C02-1). The London measurements were supported by the UK National Research Council through the ClearfLo project and a PhD studentship (grant refs. NE/H008136/1 and NE/I528142/1) and the Department of Environment, Food and Rural Affairs (DEFRA). ECPL personel, namely Nikolaos Mihalopoulos, Aikaterini Bougiatioti and Iasonas Stavroulas acknowledge support by the project “Panhellenic infrastructure for atmospheric composition and climate change, PANACEA” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme” Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund). IMT Lille Douai acknowledges financial support from the CaPPA (Chemical and Physical Properties of the Atmosphere) project funded by the French National Research Agency (ANR) through the PIA (Programme d'Investissement d'Avenir) under contract ANR-11-LABX-0005-01, and two CPER projects funded by the French Ministry of Higher Education and Research, the CNRS, the Regional Council “Hauts-de-France” and the European Regional Development Fund (ERDF): Climibio, and IRENI (additionally financed by the Communauté Urbaine de Dunkerque). S. Zhang thanks IMT Lille Douai and the Regional Council “Hauts-de-France” for her PhD grant. Prague co-authors would like to acknowledge a Czech MEYS's project under INTER-EXCELENCE INTERCOST program under grant agreement LTC18068 and from European Regional Development Fund-Project under the grant ACTRIS-CZ RI (CZ.02.1.01/0.0/0.0/16_013/0001315). EPA Ireland, Department of Communications, Climate Action and Environment (DCCAE) and the European Union's Seventh Framework Programme (FP7/2007–2013) project BACCHUS under grant agreement n_603445 are acknowledged for research support at Mace Head. The physical measurements were also funded by the German Ultrafine Aerosol Network GUAN, which was jointly established with help of the German Federal Environment Ministry (BMU) grants F&E 370343200 (German title: “Erfassung der Zahl feiner und ultrafeiner Partikel in der Auβenluft”), 2008–2010, and F&E 371143232 (German title: “Trendanalysen gesundheitsgefährdender Fein-und Ultrafeinstaubfraktionen unter Nutzung der im German Ultrafine Aerosol Network (GUAN) ermittelten Immissionsdaten durch Fortführung und Interpretation der Messreihen”) 2012–2014. We also acknowledge the WCCAP (World Calibration Center for Aerosol Physics) as part of the WMO-GAW program. The WCCAP is base-funded by the German Federal Environmental Agency (Umweltbundesamt), Germany. Support by the European Regional Development Funds (EFRE – Europe funds Saxony) is gratefully acknowledged. Atmospheric measurements performed in Corsica is part of the ChArMEx project supported by CNRS-INSU, ADEME, Météo-France and CEA in the framework of the multidisciplinary programme MISTRALS (Mediterranean Integrated Studies aT Regional And Local Scales; http://mistrals-home.org/, last access: June 10, 2020). Final data processing of these measurements has been supported by the EMME-CARE (Eastern Mediterranean and Middle East Climate and Atmosphere Research Center) which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 856612 and the Cyprus Government. The measurements in Switzerland were supported by the Federal Office for the Environment. We thank the International Foundation High Altitude Research Stations Jungfraujoch and Gornergrat (HFSJG) for the opportunity to perform experiments on the Jungfraujoch.

In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O-3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism.

The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections. The authors acknowledge financial support from the Spanish Government, Grant RTI2018-354 094336-B-I00 (MCIU/AEI/FEDER, UE), the Spanish Carlos III Health Institute, COV 20/01213, and the Basque Government, Grant IT1207-19.