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In recent years, the PALM 6.0 modelling system has been rapidly developing its capability to simulate physical processes within urban environments. Some examples in this regard are energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, a plant-canopy model to consider the effects of plants on flow (thermo)dynamics, and a chemistry transport model to enable simulation of air quality. This study provides a thorough evaluation of modelled meteorological, air chemistry, and ground and wall-surface quantities against dedicated in situ measurements taken in an urban environment in Dejvice, Prague, the Czech Republic. Measurements included monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared cameras, and monitoring of wall heat fluxes. Large-eddy simulations (LES) using the PALM model driven by boundary conditions obtained from a mesoscale model were performed for multiple days within two summer and three winter episodes characterized by different atmospheric conditions.For the simulated episodes, the resulting temperature, wind speed, and chemical compound concentrations within street canyons show a realistic representation of the observed state, except that the LES did not adequately capture night-time cooling near the surface for certain meteorological conditions. In some situations, insufficient turbulent mixing was modelled, resulting in higher near-surface concentrations. At most of the evaluation points, the simulated surface temperature reproduces the observed surface temperature reasonably well for both absolute and daily amplitude values. However, especially for the winter episodes and for modern buildings with multilayer walls, the heat transfer through walls is not well captured in some cases, leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, the study corroborates model dependency on the accuracy of the input data. In particular, the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land surface temperatures at grass surfaces strongly depend on the initial soil moisture, wall-surface temperatures depend on the correct setting of wall material parameters, and concentrations depend on detailed information on spatial distribution of emissions, all of which are often unavailable at sufficient accuracy. The study also points out some current model limitations, particularly the implications of representing topography and complex heterogeneous facades on a discrete Cartesian grid, and glass facades that are not fully represented in terms of radiative processes.Our findings are able to validate the representation of physical processes in PALM while also pointing out specific shortcomings. This will help to build a baseline for future developments of the model and improvements of simulations of physical processes in an urban environment.

Fine particulate matter (PM2.5) pollution remains a critical health issue in Europe. While numerous studies have quantified the spatio-sectoral sources of urban PM, the temporal origin has received minimum attention. This study addresses this gap by developing a Temporal Source Apportionment approach within the CAMx chemical transport model to quantify the long-term contributions of emissions from the preceding 14 d to PM concentrations, focusing on the 2010–2019 period and Central Europe. The novelty of the study lies in a long term and continuous adoption of TSA unlike previous attempts to quantify the age distribution of polluting aerosol that focused on selected air pollution periods. The results show that current-day emissions dominate winter PM2.5, contributing 30 %–60 % on average, while day-1 emissions add further 20 %–30 %. Contributions decrease with emission age, falling below 5 % after 3 d and becoming negligible beyond 7 d. Secondary inorganic aerosols and primary organic aerosols exhibit similar patterns, although for winter nitrate levels, the highest contribution comes from day-1 emissions, reflecting the time needed for chemical formation. Summer contributions are smaller due to enhanced mixing and faster removal, whereas biogenic emissions also contribute largely, giving anthropogenic emissions a smaller role. Importantly, while the average contribution of older emissions is low, occasional episodes show substantial impacts: day-4 emissions can contribute up to 10 %, and even week-old emissions can add 2 % in winter. These findings emphasize that adverse air quality episodes are influenced not only by same-day emissions but also by pollution accumulated from previous days resulting from past emissions. Effective mitigation policies on PM pollution must therefore consider reducing emissions several days in advance of predicted pollution episodes, rather than relying solely on same-day interventions.

Urban areas are hot spots of intense emissions, and they influence air quality not only locally but on a regional or even global scale. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local- and regional-scale meteorological conditions. These are influenced by the presence of urbanized land surface via the so-called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw) how the urban emission impact (UEI) is modulated by the UCMF for present-day climate conditions (2015–2016) using two regional climate models, the regional climate models RegCM and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem; its meteorological part), and two chemistry transport models, Comprehensive Air Quality Model with Extensions (CAMx) coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by a rural one, while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban-emission-induced changes in near-surface concentrations of NO2, O3 and PM2.5. We found increases in NO2 and PM2.5 concentrations over cities by 4–6 ppbv and 4–6 µg m−3, respectively, meaning that about 40 %–60 % and 20 %–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions, and the rest is the result of emissions from the surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40 %–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases of around −2 to −4 ppbv (about 10 %–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air pollution is much stronger, and the modulation of UEI is also larger for such situations. Finally, we evaluated the contribution of the urbanization-induced modifications of vertical eddy diffusion to the modulation of UEI and found that it alone is able to explain the modeled decrease in the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional footprint of urban emissions. Ignoring these meteorological changes can lead to the strong overestimation of UEI.

Rural-to-urban transformation (RUT) is the process of turning a rural or natural land surface into an urban one, which brings about important modifications in the surface, causing well-known effects like the urban heat island (UHI), reduced wind speeds, and increased boundary layer heights. Moreover, with concentrated human activities, RUT introduces new emission sources which greatly perturb local and regional air pollution. Particulate matter (PM) is one of the key pollutants responsible for the deterioration of urban air quality and is still a major issue in European cities, with frequent exceedances of limit values. Here we introduce a regional chemistry–climate model (regional climate model RegCM coupled offline to chemistry transport model CAMx) study which quantifies how the process of RUT modified the PM concentrations over central Europe including the underlying controlling mechanisms that contribute to the final PM pollution. Apart from the two most studied ones, (i) urban emissions and (ii) urban canopy meteorological forcing (UCMF; i.e. the impact of modified meteorological conditions on air quality), we also analyse two less studied contributors to RUT's impact on air quality: (iii) the impact of modified dry-deposition velocities (DVs) due to urbanized land use and (iv) the impact of modified biogenic emissions due to urbanization-induced vegetation modifications and changes in meteorological conditions which affect these emissions. To calculate the magnitude of each of these RUT contributors, we perform a cascade of simulations, whereby each contributor is added one by one to the reference state, while focus is given on PM2.5 (particulate matter with diameter less then 2.5 µm). Its primary and secondary components, namely primary elemental carbon (PEC), sulfates (PSO4), nitrates (PNO3), ammonium (PNH4), and secondary organic aerosol (SOA), are analysed too. The validation using surface measurements showed a systematic negative bias for the total PM2.5, which is probably caused by underestimated organic aerosol and partly by the negative bias in sulfates and elemental carbon. For ammonium and nitrates, the underestimation is limited to the warm season, while for winter, the model tends to overestimate their concentrations. However, in each case, the annual cycle is reasonably captured. We evaluated the RUT impact on PM2.5 over a sample of 19 central European cities and found that the total impact of urbanization is about 2–3 and 1–1.5 µg m−3 in winter and summer, respectively. This is mainly driven by the impact of emissions alone causing a slightly higher impact (1.5–3.5 and 1.2–2 µg m−3 in winter and summer), while the effect of UCMF was a decrease at about 0.2–0.5 µg m−3 (in both seasons), which was mainly controlled by enhanced vertical eddy diffusion, while increases were modelled over rural areas. The transformation of rural land use into an urban one caused an increase in dry-deposition velocities by around 30 %–50 %, which alone resulted in a decrease in PM2.5 by 0.1–0.25 µg m−3 in both seasons. Finally, the impact of biogenic emission modifications due to modified land use and meteorological conditions caused a decrease in summer PM2.5 of about 0.1 µg m−3, while the winter effects were negligible. The total impact of urbanization on aerosol components is modelled to be (values indicate winter and summer averages) 0.4 and 0.3 µg m−3 for PEC, 0.05 and 0.02 µg m−3 for PSO4, 0.1 and 0.08 µg m−3 for PNO3, 0.04 and 0.03 µg m−3 for PNH4, and 0 and 0.05 µg m−3 for SOA. The main contributor of each of these components was the impact of emissions, which was usually larger than the total impact due to the fact that UCMF was counteracted with a decrease. For each aerosol component, the impact of modified DV was a clear decrease in concentration, and finally, the modifications of biogenic emissions impacted SOA predominantly, causing a summer decrease, while a very small secondary effect of secondary inorganic aerosol was modelled too (they increased). In summary, we showed that when analysing the impact of urbanization on PM pollution, apart from the impact of emissions and the urban canopy meteorological forcing, one also has to consider the effect of modified land use and its impact on dry deposition. These were shown to be important in both seasons. For the effect of modified biogenic emissions, our calculations showed that they act on PM2.5 predominantly through SOA modifications, which only turned out to be important during summer.

The paper evaluates the long-term (2007–2016) impact of biogenic volatile organic compound (BVOC) emissions on urban ozone patterns over central Europe, specifically focusing on the contribution of urban vegetation using a regional climate model coupled offline to a chemistry transport model. BVOCs are emitted by terrestrial ecosystems, and their impact is considered especially important over NOx-rich environments such as urban areas. The study evaluates the impact of BVOC emissions on ozone (O3), formaldehyde (HCHO), and hydroxyl radical (OH) near-surface concentrations, showing an increase in summer ozone by 6 %–10 % over large areas in central Europe due to their emissions. It also demonstrates a substantial increase in formaldehyde concentrations. Additionally, the impact of BVOC emissions on hydroxyl radical concentrations shows a decrease over most of the modeled region by 20 %–60 %, with some increases over urban areas. Impacts on peroxy radicals (HO2 and higher RO2) are shown too. Importantly, the study explores the partial role of urban vegetation in modulating ozone and evaluates its contribution to the overall ozone formation due to all BVOC emissions. The findings reveal that urban BVOC emissions contribute to around 10 % of the total impact on ozone and formaldehyde concentrations in urban areas, indicating their significant but localized influence. The study also conducts sensitivity analyses to assess the uncertainty arising from the calculation of the urban fraction of BVOC emissions. The results show that the impact of urban BVOC emissions responds to their magnitude nearly linearly, with variations up to 4-fold, emphasizing the importance of accurately quantifying the urban BVOC fluxes. Overall, the study sheds light on the intricate relationship between urban vegetation, BVOC emissions, and their impact on atmospheric chemistry, providing valuable insights into the regional chemistry of BVOC emissions over central Europe and the causes of urban ozone pollution.

Wind-blown dust (WBD) emitted by the Earth’s surface due to sandblasting can potentially have important effects on both climate and human health via interaction with solar and thermal radiation, reducing air quality. Apart from the main dust “centres” around the world, like deserts, dust can be emitted from partly vegetated mid- and high-latitude areas like Europe if certain conditions are suitable (strong winds, bare soil, reduced soil moisture, etc.). Using a wind-blown dust model (WBDUST) along with a chemical transport model (Comprehensive Air-quality model with Extensions, CAMx) coupled to a regional climate model (Weather Research and Forecasting, WRF), this study is one of the first to provide a model-based estimate of such emissions over Europe as well as the long-term impact of WBD emissions on the total particulate matter (PM) concentrations for the 2007–2016 period. We estimated average WBD emissions of about 0.5 and 1.5 Mgyr-1km-2 in fine and coarse modes. Maximum emissions occur over Germany, where the average seasonal fine- and coarse-mode emission flux can reach 0.5 and 1 gs-1km-2, respectively. Large variability is seen in the averaged daily emissions with values of up to 2 gs-1km-2 for the coarse-mode aerosol on selected days. The WBD emissions increased the modelled winter PM2.5 and PM10 concentrations by up to 10 and 20 µg m−3, respectively, especially over Germany, where the highest emissions occur. The impact on other seasons is lower. Much higher impacts are modelled, however, on selected days when occasionally the urban PM2.5 and PM10 concentrations are increased by more than 50 and 100 µg m−3. The comparison with measurements revealed that if WBD is considered, the summer biases are reduced; however, the winter PM is overestimated even more greatly (so the bias increases). We identified a strong overestimation of the modelled wind speed (the maximum daily wind is almost 2 times higher in WRF than the measured ones) suggesting that WBD emissions are also overestimated – hence the enhanced winter PM biases. Moreover, we investigated the secondary impacts of the crustal composition of fine WBD particles on secondary inorganic aerosol (SIA): sulfates (PSO4), nitrates (PNO3) and ammonium (PNH4). Because the water pH value, and thus the uptake of the gaseous precursors of SIA, is perturbed and because the increased aerosol surface serves as an oxidation site, we modelled seasonal PSO4 and PNO3 concentrations increased by up to 0.1 µg m−3 and PNH4 ones decreased by up to −0.05 µg m−3, especially during winter. In terms of average daily impact, these numbers can, however, reach much larger values of up to 1–2 µg m−3 for sulfates and nitrates, while the decrease in ammonium due to WBD can reach −1 µg m−3 on selected days. The sensitivity test on the choice of the inorganic equilibrium model (ISORROPIA vs. EQuilibrium Simplified Aerosol Model V4, EQSAM) showed that if EQSAM is used, the impact on SIA is slightly stronger (by a few 10 %) due to larger number of cations considered for water pH in EQSAM. Our results have to be regarded as a first estimate of the long-term WBD emissions and the related effects on PM over Europe. Due to the strong positive wind bias and hence strong WBD emissions, we should consider these results as an upper bound. More sensitivity studies involving the impact of the driving meteorological fields, WBD model choice and the input data used to describe the land surface need to be carried out in future to better constrain these emissions.

This study explores the uncertainties in modeling organic aerosol (OA) over Central Europe, focusing on the roles of chemical mechanisms, emission parameterizations, and boundary conditions. Organic aerosols, particularly secondary organic aerosols (SOAs), significantly influence climate, health, and visibility, comprising up to 90 % of submicron particulate matter. Using the Comprehensive Air Quality Model with Extensions (CAMx) coupled with the Weather Research and Forecast Model, sensitivity analyses were conducted to assess the impact of intermediate-volatility organic compounds (IVOCs), semi-volatile organic compounds (SVOCs), and chemical boundary conditions on primary and secondary organic aerosol concentrations. Model evaluation against organic carbon measurements over the Czech Republic showed that including source-specific IVOC and SVOC emissions significantly improved CAMx's performance, particularly when using the 1.5-dimensional Volatility Basis Set framework with activated chemical aging. For example, the domain-averaged SOA concentrations increased by up to 1.17 µg m−3 during summer when both IVOC and SVOC emissions were included. Furthermore, incorporating OA into the boundary conditions enhanced model predictions, with the accuracy of modeled organic carbon concentrations significantly improved during summer at some monitoring sites. Despite these improvements, challenges remain due to uncertainties in emission estimates, parameterization schemes, and the spatial resolution of the models. The findings underscore the importance of refined parameterizations for IVOC and SVOC emissions, higher temporal and spatial resolution in chemical boundary conditions, and better representation of chemical aging. Addressing these gaps in future studies will further enhance the understanding and prediction of OA dynamics in regional air quality modeling.

Fine particulate matter (PM2.5) is among the air pollutants representing the most critical threat to human health in Europe. For designing strategies to mitigate this kind of air pollution, it is essential to identify and quantify the sources of its components. Here, we utilized the regional chemistry transport model CAMx (Comprehensive Air Quality Model with Extensions) to investigate the relationships between emissions from different categories and the concentrations of PM2.5 and its secondary components over Central Europe during the period 2018–2019, both in terms of the contributions of emission categories calculated by the particle source apportionment technology (PSAT) and the impacts of the complete removal of emissions from individual categories (i.e., the zero-out method). During the winter seasons, emissions from other stationary combustion (including residential combustion) were the main contributor to the domain-wide average PM2.5 concentration (3.2 µg m−3), and their removal also had the most considerable impact on it (3.4 µg m−3). During the summer seasons, the domain-wide average PM2.5 concentration was contributed the most by biogenic emissions (0.57 µg m−3), while removing emissions from agriculture–livestock had the most substantial impact on it (0.46 µg m−3). The most notable differences between the contributions and impacts for PM2.5 were associated with emissions from agriculture–livestock, mainly due to the differences in nitrate concentrations, which reached up to 4.5 and 1.25 µg m−3 in the winter and summer seasons, respectively. We also performed a sensitivity test of the mentioned impacts on PM2.5 on two different modules for secondary organic aerosol formation (SOAP and VBS), which showed the most considerable differences for emissions from other stationary combustion (in winter) and road transport (in summer).

Cities and urban areas are well-known for their impact on meteorological variables and thereby modification of the local climate. Our study aims to generalize the urban-induced changes in specific meteorological variables by introducing a single phenomenon – the urban meteorology island (UMI). A wide ensemble of 24 model simulations with the Weather Research and Forecasting (WRF) regional climate model and the Regional Climate Model (RegCM) on a European domain with 9 km horizontal resolution were performed to investigate various urban-induced modifications as individual components of the UMI. The results show that such an approach is meaningful, because in nearly all meteorological variables considered, statistically significant changes occur in cities. Besides previously documented urban-induced changes in temperature, wind speed and boundary-layer height, the study is also focused on changes in cloud cover, precipitation and humidity. An increase in cloud cover in cities, together with a higher amount of sub-grid-scale precipitation, is detected on summer afternoons. Specific humidity is significantly lower in cities. Further, the study shows that different models and parameterizations can have a strong impact on discussed components of the UMI. Multi-layer urban schemes with anthropogenic heat considered increase winter temperatures by more than 2 ∘C and reduce wind speed more strongly than other urban models. The selection of the planetary-boundary-layer scheme also influences the urban wind speed reduction, as well as the boundary-layer height, to the greatest extent. Finally, urban changes in cloud cover and precipitation are mostly sensitive to the parameterization of convection.

The regional climate model RegCM4 extended with the land surface model CLM4.5 was coupled to the chemistry transport model CAMx to analyze the impact of urban meteorological forcing on surface fine aerosol (PM2.5) concentrations for summer conditions over the 2001–2005 period, focusing on the area of Europe. Starting with the analysis of the meteorological modifications caused by urban canopy forcing, we found a significant increase in urban surface temperatures (up to 2–3 K), a decrease of specific humidity (by up to 0.4–0.6 gkg−1), a reduction of wind speed (up to −1 ms−1) and an enhancement of vertical turbulent diffusion coefficient (up to 60–70 m2s−1). These modifications translated into significant changes in surface aerosol concentrations that were calculated by a “cascading” experimental approach. First, none of the urban meteorological effects were considered. Then, the temperature effect was added, then the humidity and the wind, and finally, the enhanced turbulence was considered in the chemical runs. This facilitated the understanding of the underlying processes acting to modify urban aerosol concentrations. Moreover, we looked at the impact of the individual aerosol components as well. The urbanization-induced temperature changes resulted in a decrease of PM2.5 by −1.5 to −2 µg m−3, while decreased urban winds resulted in increases by 1–2 µg m−3. The enhanced turbulence over urban areas resulted in decreases of PM2.5 by −2 µg m−3. The combined effect of all individual impact depends on the competition between the partial impacts and can reach up to −3 µg m−3 for some cities, especially when the temperature impact was stronger in magnitude than the wind impact. The effect of changed humidity was found to be minor. The main contributor to the temperature impact is the modification of secondary inorganic aerosols, mainly nitrates, while the wind and turbulence impact is most pronounced in the case of primary aerosol (primary black and organic carbon and other fine particle matter). The overall as well as individual impacts on secondary organic aerosol are very small, with the increased turbulence acting as the main driver. The analysis of the vertical extent of the aerosol changes showed that the perturbations caused by urban canopy forcing, besides being large near the surface, have a secondary maximum for turbulence and wind impact over higher model levels, which is attributed to the vertical extent of the changes in turbulence over urban areas. The validation of model data with measurements showed good agreement, and we could detect a clear model improvement in some areas when including the urban canopy meteorological effects in our chemistry simulations.