Urban air quality is influenced by the removal of particulate matter through dry deposition, yet this process is often simplified in models, potentially underestimating the role of vertical building surfaces. This study investigates the impact of aerosol deposition on building walls on PM2.5 concentrations and the deposition budget within the urban canopy. We utilized a Large Eddy Simulation model coupled with a Lagrangian Particle Transport module to simulate aerosol dispersion in randomized urban configurations corresponding to Local Climate Zones (LCZs) 4, 5, and 6. The results indicate that under the considered conditions, vertical walls can act as a primary sink for PM2.5, capturing over 70% of deposited particles downwind from sources in high-rise environments. We observed a non-linear sensitivity of airborne concentrations to wall deposition efficiency; a relatively low capture probability (10%) reduced near-surface concentrations by 25-30%. Furthermore, for fine and coarse particles (up to similar to 20 mu m), the uncertainty in wall deposition parameterization appeared to outweigh the influence of particle physical properties on dispersion patterns. These findings suggest that neglecting wall deposition may lead to overestimation of urban pollution levels, highlighting the importance of refining particle-wall interaction parameterizations in air quality models.

As urban areas grow, understanding the impact of built environments on aerosol distribution is crucial for accurate monitoring and forecasting of urban air quality and for development of mitigation strategies. In this study we use a modern approach, which combines micro-scale Large Eddy Simulation with Local Climate Zones (LCZ) classification to simulate the transport of Lagrangian aerosol particles in different urban configurations. The study simulates several urban configurations based on LCZ classification, specifically open LCZ types, varying in building height and aspect ratio: LCZ 4 (high-rise), LCZ 5 (mid-rise), LCZ 6 (low-rise). Both regular and randomized urban development configurations were examined to understand the impact of building geometry on particle dispersion. The transport of particulate matter emitted from a linear source within a street canyon has been simulated under neutral atmospheric conditions.The study reveals that the orientation of buildings significantly influences the distribution of particles. Structures parallel to the wind add horizontal dispersion, while those perpendicular promote vertical mixing. Variations in particle concentrations in randomized configurations highlight the role of architectural heterogeneity in turbulence development and aerosol dispersion. In the absence of regular homogeneous structures, the aggregated block- and district-scale geometry of buildings strongly influences aerosol transport. In randomized urban configurations, the large-scale morphological characteristics of different LCZ types have a significantly greater effect on particle dispersion than the local geometrical differences between configurations within the same LCZ.Future research is recommended to take into account diverse meteorological conditions and a wider range of LCZ types to enhance the accuracy and applicability of this approach.The work is supported by RSF grant 24-17-00155.

This paper presents a technique for measuring the temperature of an inhomogeneous underlying surface using unmanned aerial vehicles (UAVs). To test the proposed technique, measurements over various landscapes are presented: dunes in an arid zone, a temperate swamp, a subarctic city, and a combination of natural and anthropogenic landscapes in the Arctic. A measuring complex based on a DJI Mavic 2 Zoom quadrocopter with a Flir TAU 2R thermal camera is used. Methods for correcting emerging hardware errors and artefacts have been developed. To obtain detailed data on the spatial distribution of the surface brightness temperature, the orthomosaic construction method is used. Thermal maps of surfaces with surface height inhomogeneities (dunes), moisture inhomogeneity (swamps), and urban areas in polar and subpolar conditions are obtained at different times of the day. It is shown that thermal contrasts can reach the first tens of degrees Celsius within an area of 10–20 ha, both under the background of daytime heating and nighttime cooling of the surface, and could have a significant effect on the spatial distribution of the heat transfer characteristics of the atmosphere and the underlying surface. These methods are recommended for constructing surface thermal maps using thermal imaging technology.

Globally the impact of COVID-19 lockdown on environmental pollution is evidenced. How significant it was due to social and working restrictions during different pandemic waves is still uncertain. Aerosol black carbon (BC) in the Moscow megacity background is measured during first wave COVID-19 lockdown and recovery periods in spring and summer of 2020, and at the same times in 2021 when pre-lockdown and lockdown of the third pandemic wave occurred. Economic and population activities in conjunction with meteorological parameters and air mass transportation are evaluated by studying the variability and concentration levels of black carbon. Because the strict social and working restrictions in lockdown 2020 the mean BC concentration dropped down to 1.5 ± 0.9 µg m−3. The portion of biomass burning (BB

The ability to take into account the thermal inhomogeneity of the surface in atmospheric models is an important task, since a difference in the surface temperature significantly affects the formation of turbulent fluxes. In this paper, an assessment is made of the influence of the thermal inhomogeneity of a wetlands surface on the accuracy of calculating heat fluxes, and a methodology is proposed for taking it into account for the classical Monin-Obukhov similarity theory (MOST). The basis of the work was the data collected during the IAP RAS expedition to the Mukhrino field station from June 11 to June 23, 2022. As part of the expedition, three pulsation measuring complexes were deployed on eddy covariance tower located above wetland micro-landscapes, which differ in the degree of watering: ryam, ridges and swamp. Regular aerial IR surveys of two polygons with a homogeneous and heterogeneous surface were carried out used the DJI Mavic 2 Pro copter and the Flir TAU 2R IR camera. In the course of processing the collected data, a detailed temperature map of the surface of the studied polygons was obtained, footprints for each tower were calculated, and the contribution of the allocated micro-landscapes to the formation of the measured heat flux was estimated. The heat fluxes calculated by the MOST with and without thermal inhomogeneity of the surface. Results were compared with the fluxes obtained by the eddy covariance method. Finally, the estimate was obtained of the effectiveness of the method proposed by the authors for taking into account the thermal inhomogeneity of the surface for modeling turbulent fluxes. This work was supported in part by the Russian Science Foundation grant no. 22-47-04408.

This paper presents results of development of a numerical model of Lagrangian particle transport, as well as results of application of parallel computation methods to improve the efficiency of the software implementation of this model. The model is a software package that allows the transport and deposition of aerosol particles to be calculated taking into account properties of particles and the input data that describe atmospheric conditions and underlying surface geometry. The dynamic core, physical parameterizations, numerical implementation, and algorithm of the model are described. Results of successful verification of the model on analytical solutions are presented. Initially, the model was used for less computationally intensive problems. In this paper, given the need to use the model in more computationally intensive problems, we optimize the sequential software implementation of the model, as well as develop its software implementations that use parallel computing technologies (OpenMP, MPI, and CUDA). The results of testing different implementations of the model show that the optimization of the most computationally complex blocks in its sequential version can reduce the execution time by 27%. At the same time, the use of parallel computing technologies allows us to achieve acceleration by several orders of magnitude. The use of OpenMP in the dynamic block of the model provides almost 4-fold acceleration of this block; the use of MPI, almost 8-fold acceleration; and the use of CUDA, almost 16-fold acceleration (all other conditions being equal). We also give some recommendations on the choice of a parallel computing technology depending on the properties of a computing system.

The surface roughness lengths for momentum, z_0u , and heat, z_0T , are key parameters for modeling the momentum, mass and energy exchange between underlying surface and the atmosphere. Established approach predicts the dependency of the ratio C=ln( z_0u/z_0T) on the roughness Reynolds number Re_s , confirmed earlier for a number of surface types. This paper for the first time evaluates such a relationship based on the eddy covariance data collected on a boreal fen dominated by moss and sedge vegetation. It is shown that the best parameterization is provided by two dependencies: C=0.359 Re_s^1/4+0.711 and C=0.032 Re_s^1/2+1.706 . The significant sensitivity of these dependencies to longwave emissivity was revealed. We generalized this issue to linear analysis of parameter uncertainties in the MOST formulas. This analysis suggested, that the surface temperature errors contribute more to C evaluation compared to heat flux uncertainties, the former being affected also by mismatch between footprints of radiation and eddy covariance measurements. The practical solutions to minimize the issue are proposed. Comparison of our measurement data and obtained dependencies for C with known functions C(Re_s) for other types of surface from literature demonstrated that grassland and cropland surface types are the closest to fen in terms of z_0u/z_0T .

This work is devoted to the development of a numerical model of the transport of aerosol particles in the atmospheric boundary layer, as well as its application in idealized cases and studies with a realistic urban surface. Air quality and the distribution of pollutants is one of the major urban problems, and measurement methods can be limited in the complex geometry of the city, which motivates the development of modeling methods. The model uses the Lagrangian approach to modeling, taking into account the size and mass of each particle, the possibility of aerosol deposition and their collision with various surfaces. The particle motion equation takes into account various parameters of the atmosphere: wind direction and speed, turbulent characteristics. The influence of turbulence on the motion of aerosols can be taken into account in the model using several parametrizations – stochastic Lagrangian models of zero and first order. It is possible to simulate a huge number of particles at the same time. The algorithm is implemented in the C++ programming language. The model can be used as a separate tool that requires information about the state of the atmosphere as input data - these can be measurement data, results of hydrodynamic modeling, analytically given values. Numerous experiments have been carried out in this mode. The model was verified on exact analytical solutions for light and heavy particles, on the data of field measurements of the concentrations of dust and sand particles. Calculations were carried out in conditions of idealized geometry of buildings (urban canyons) and in conditions of real urban development. For this, input data from RANS and LES models were used. The developed algorithm can also be used as a module connected to hydrodynamic models. In this mode, it is possible to use the input data on atmospheric parameters with the maximum resolution in time and space. By connecting to the LES model, high-resolution simulations of aerosol transport in realistic urban environments were performed. The work is supported by Russian Ministry of Science and Higher Education, agreement No. 075-15-2021-574 (megagrant leaded by M.Kulmala in Moscow State University, WP4), No. 075-15-2019-1621, by RSF grant 21-17-00249, by RFBR grants 20-05-00776 and 19-05-50110.

A new 21-meter eddy covariance tower is installed in the Meteorological observatory of Moscow State University in November 2019. It includes 3 levels with METEK sonic anemometers. The mast is located inside the urban area and makes it possible to analyze the structure of atmospheric turbulence in a heterogeneous urban condition. The measurement data from November 2019 to May 2020 are processed. Turbulent fluctuations of the wind velocity components are found to increase with height within 20 meters above the surface. The turbulent kinetic energy is proportional to the square of the averaged horizontal wind speed. The drag coefficient is determined by the type of footprint surface, with a value of 0.08 and 0.05 for urbanized and vegetated surfaces, respectively. The "turbulent flux of heat flux" is reasonably well predicted by diagnostic relation with heat flux, skewness and standard deviation of vertical speed, suggesting significant contribution of coherent structures to turbulent fluxes. The daily amplitude of the temperature variance increases with the daily amplitude of the average temperature. The paper considers the conditions for the applicability of the Monin-Obukhov similarity theory to the calculation of turbulent fluxes over a heterogeneous urban landscape.

The paper presents the results of one-way coupling of a large eddy simulation model and an atmospheric composition and diffusion complex SILAM. This study investigates a possibility of large eddy simulation time data coarsening (filtering) for use in SILAM for microscale calculations. Experiments with scalar tracers with a limited lifetime are carried out under conditions of convective boundary layer. A comparison between the calculations with filtered and nonfiltered data demonstrate that time data coarsening is possible without a significant loss in accuracy for tracers whose lifetime is much longer than the coarsening scale and the timestep of the filtered data.

This paper presents the development and application of a numerical Lagrangian model of the transport of aerosol particles in the urban boundary layer of the atmosphere with a high spatial resolution. The development of the model is motivated by the limited measurement methods for observing aerosol concentrations in urban environments, both in terms of coverage density and in terms of accuracy and representativeness. The growing interest of the world community in the problems of monitoring air pollution in cities and the atmospheric distribution of biologically active aerosols also became a motivating factor. The model uses the equation of motion to calculate the trajectory of a particle suspended in the air. It is based on Newton's second law and takes into account the forces of gravity, buoyancy and air resistance. The influence of stochastic turbulent eddies on the particle motion is taken into account in the model by using turbulent parameterizations. The effect of turbulence is important when describing the motion of particles in this model, since aerosols have a size much smaller than the grid step of the input data and can stay inside one cell for a long time, being under the influence of subgrid vortices. In this model, three parameterizations are implemented: a simple Gaussian model, a random displacement model, and a random walk model. In all three, the pulsation velocity component is a normally distributed random variable, but in the first two parameterizations it is generated at each time step of the Lagrangian model. In the last one, the interaction time of the particle with the turbulent vortex is introduced, during which the pulsation velocity component acting on the particle remains constant, characterizing the effect of a particular vortex. Additionally, a version of the model based on the Langevin equation has been implemented to more accurately account for the effect of turbulence on particle motion. The developed numerical model is implemented in a program code in the C++ programming language and allows one to calculate individual trajectories of motion and concentrations of particles. Input data (wind speed components, turbulence characteristics and others) can be set analytically or imported from hydrodynamic models. The model has been successfully tested and verified on several idealized analytical solutions – an equivalence is obtained in terms of the concentration field. Experiments have also been carried out to reproduce the transport of particles in a series of urban canyons, including particles with a finite half-life that simulate the COVID-19 virions (SARS-CoV-2). Based on the results of the calculations, the influence of stratification, particle size and lifetime on the transport of aerosols in a typical urban environment was estimated. The work is partially supported by RFBR grants 18-05-60126 and 19-05-50110.

Experimental field campaigns are an essential part of atmospheric research, as well as of university education in the field of atmospheric physics and meteorology. Experimental field observations are needed to improve the understanding of the surface-atmosphere interaction and atmospheric boundary layer (ABL) physics and develop corresponding model parameterizations. Information on the ABL wind profiles is essential for the interpretation of other observations. However, wind profile measurements above the surface layer remain challenging and expensive, especially for the field campaigns performed in remote places and harsh conditions. In this study, we consider the experience of using two low-cost methods for the wind profiling, which may be easily applied in the field studies with modest demands on logistical opportunities, available infrastructure, and budget. The first one is a classical and well-known method of pilot balloon sounding, i.e., when balloon is treated as a Lagrangian particle and tracked by theodolite observations of angular coordinates. Second one is based on a vertical sounding with a popular and relatively cheap mass-market quadcopter DJI Phantom 4 Pro and utilizes its built-in opportunity to restore the wind vector from quadcopter tilt angles. Both methods demonstrated reasonable agreement and applicability even in harsh weather conditions and complex terrain. Advantages and shortcomings of these methods, as well as practical recommendations for their use are discussed. For the drone-based wind estimation, the importance of calibration by comparison to high-quality wind observations is shown.

Skin temperature (Ts) plays a central role in shaping the land surface energy balance and is also widely available from remote sensing for model evaluation and data assimilation. Both offline land models and land–atmosphere coupled models still have difficulty in realistically simulating or predicting Ts. In the case of an inhomogeneous surface, under the same atmospheric conditions, there are patches of different skin temperature and different daily variability. This observational study reports variations of surface fluxes (turbulent, radiative, and soil heat) and ancillary atmospheric/surface/soil data based on in-situ measurements conducted at Mukhrino field station located in the middle taiga zone of the West Siberian Lowland. To measure the surface temperature, we used an infrared camera (TIR, ~8–14 mkm wavelength range) based on an unmanned aerial vehicle. This UAV-based system provides high-resolution multi-sensors data acquisition. It also provides maximal flexibility for data collection at low cost with minimal atmospheric influence, minimal site disturbance, flexibility in measurement planning, and ease of access to study sites (e.g., peatlands) in contrast with traditional data collection methods. e demonstrate that the temperature of the boggy surface has significant variability: depending on the time of day, temperature contrasts can reach more than 10 degrees, which is associated with different surface moisture and albedo. A technique has been developed for restoring the surface albedo from the data of IR measurements. Ground measurements have shown that the variations of temperature and humidity across the subsurface layer can be very large. Furthermore, these variations are directly related to the concept of a difference between the roughness length for momentum versus that for heat. Information about the ratio of z0/z0h is necessary in order to be able to use surface skin temperature from satellite remote sensing for the computation of surface fluxes. The relationship between the difference in skin temperature and soil contact temperature with the heat balance, especially with sensible heat fluxes and heat flux through the soil, is considered. The parametrizations obtained in this work can be used in Earth System models to represent wetland ecosystems. The work was supported by RFBR grant 18-05-60126, by the Moscow Center for Fundamental and Applied Mathematics and within the grant of the Tyumen region Government in accordance with the Program of the World-Class West Siberian Interregional Scientific and Educational Center (National Project "Nauka").

This paper presents a description, verification, and application of a model simulating the transport of aerosol particles with different properties in the urban boundary layer by using a Lagrangian approach. The model takes input fields of air flow characteristics from arbitrary external models or analytical solutions and allows estimating the movement, sedimentation, and decay of particles. In this paper, the accuracy of the model is successfully estimated on the basis of exact analytical solutions. Simulations are made for a series of urban canyons under different conditions of stratification and wind speed to assess the effects of these meteorological parameters on particle transport in urban areas. Under similar conditions, the transport of particles simulating SARS-CoV-2 coronavirus particles is calculated.

This study considers experience in use of crowdsourced meteorological observations from the world’s biggest network of citizen weather stations (CWSs), Netatmo, for urban climate research and applied monitoring services on the example of Moscow megacity. Crowdsourcing paradigm is an emerging alternative to the development of expensive urban meteorological networks. We have experimentally evaluated the uncertainties of the Netatmo temperature observations and regard them as being acceptable when the stations are shadowed from the sun. In order to filter out the misrepresentative observations, a quality-control algorithm has been developed. Within more than 1500 CWSs in the Moscow region, only about 25% meet this quality control, which is still one order of magnitude higher than the number of official Roshydromet weather stations in the study area. Such amount of data opens new opportunities for spatially-resolving urban climate studies and for applied services. As an example of the latter, we present a prototype of a web-mapping application for a near-real-time temperature monitoring system in Moscow. The application’s backend includes automatic services for downloading of observations from Netatmo and official Roshydromet networks, as well as for database maintaining. The processed data are visualized interactively in a web browser. The application is available on the Internet at http://carto.geogr.msu.ru/mosclim/. It will be further developed to include a real-time thermal comfort assessment based on the contemporary PET and UTCI biometeorological indices, a visualization of the interpolated fields, and other improvements.

The article is devoted to various aspects of the use of unmanned aerial vehicles (UAV) for the study of the atmospheric boundary layer. The characteristics of the atmospheric boundary layer, measured using the UAV, are considered. The types of devices and measuring systems used are presented. The characteristics of measuring systems installed on a fixed-wing aircraft and copter UAVs developed in the A.M. Obukhov Institute of Atmospheric Physics RAS (IAP RAS) are presented. A brief overview of a number of the IAP RAS measurement campaigns is given. The prospects of using UAV in meteorology and atmospheric physics are considered

This paper reports on various aspects of the urban heat island (UHI) of the Moscow megacity - its spatial and temporal variability and linkages with human thermal comfort. Firstly, we analyze long-term trends of air temperature, UHI intensity and thermal stress indices based on meteorological observations over the period 1977-2018. We show that the city exhibits 40% higher rates of summertime climate warming than the countryside, as well as higher rates of human thermal comfort deterioration. Secondly, we present a new approach for spatially-resolving urban climate studies and real-time monitoring applications based on the usage of crowdsourced air temperature data from Netatmo citizen weather stations (CWSs). The CWSs provide uncertified and often misrepresentative data. However, their quality could be controlled by application of statistically-based algorithms. Additionally, we have experimentally evaluated uncertainties of the Netatmo temperature observations and regard them to be acceptable for UHI studies. Observations from more than 1500 CWSs as well as reference observations were used to analyze spatial patterns of the summertime nocturnal UHI. Both types of data shown an UHI covering the whole city and its suburbs, with a tendency of a temperature decrease with the distance from the city center.

Abstract This paper presents a model simulating the transport of particles of various sizes and masses in complex atmospheric boundary layer domains over urban areas by using a Lagrangian approach. The model takes input fields of air velocity and turbulence characteristics from various external RANS, LES, or DNS models (in this study, ENVI-met model is used), and includes a parameterization of subgrid stochastic velocity fluctuations. It allows us to estimate the movement of particles, their sedimentation, accumulation on the surface, and the variability of these processes depending on meteorological conditions. The results of test numerical experiments for aerosol transport over an idealized urban canopy are presented. The model has shown a good degree of qualitative conformity with the ENVI-met model.