Moscow Megacity Research Articles

Contamination assessment and source identification of metals and metalloids in submicron road dust (PM1) in Moscow Megacity.

The content of 39 metals and metalloids (MMs) in submicron road dust (PM1 fraction) was studied in the traffic zone, residential courtyards with parking lots, and on pedestrian roads in parks in Moscow. The geochemical profiles of PM1 vary slightly between different types of roads and courtyards but differ significantly from those in parks. In Moscow, compared to other cities worldwide, submicron road dust contains less As, Sb, Mo, Cr, Cd, Sn, Tl, Ca, Rb, La, Y, U, but more Cu, Zn, Co, Fe, Mn, Ti, Zr, Al, V. Relative to the upper continental crust, PM1 is highly enriched in Sb, Zn, Cd, Cu, W, Sn, Bi, Mo, Pb. In the courtyards, where contact between pollutants and the population is most frequent and occurs over an extended period, the level of PM1 pollution with MMs (from strong to extreme) is comparable to that on large roads. Source identification was conducted using correlations, elemental ratios, and absolute principal component analysis with multiple linear regression (APCA-MLR). In the traffic zone, non-exhaust and exhaust vehicle emissions contribute significantly to the MM concentrations in PM1 (especially for Bi, Sb, Sn, V, Fe, Cu, W, Mo); soil particles, abrasion of steel surfaces, industrial emissions, tire and road wear with carbonate dust resuspension contribute less. In the courtyards, the contribution of the road wear with carbonate dust resuspension and soil particles increases by up to 16% due to the poor condition of the road surface, frequent construction works, and large contact areas of roads with soils. In parks, the contribution of anthropogenic sources sharply decreases by 20-48% due to the increased soil resuspension rate. The spatial distribution pattern of MMs in submicron road dust should aid in the development of more effective road surface washing strategies, ultimately minimizing the risk to public health.

Potentially hazardous elements in atmospheric precipitation during the warm season (May–September) of 2019 in Moscow

Atmospheric precipitation acts as a significant pathway for pollutants from the atmosphere to the Earth’s surface, and analyzing urban precipitation data on intensity, fallout regime, transfer patterns, and solid particle content helps identify pollution sources. For the first time in the Moscow megacity, the levels of soluble forms of potentially hazardous elements (PHEs) in atmospheric precipitation were studied during the whole summer season of May–September 2019. The concentrations of Al, As, B, Ba, Be, Bi, Cd, Ce, Co, Cu, Fe, La, Li, Mn, Ni, P, Pb, Rb, Sb, Sn, Sr, and Zn were determined using inductively coupled plasma mass spectrometry and atomic emission spectroscopy methods. The research underscores the crucial role of atmospheric precipitation in washing PHEs out of the atmosphere. In May and September, concentrations of PHEs surpass the warm-season average. Notable contamination in May stems from elevated traffic during vacations, extensive burning of plant debris and wood, and pollen transport. Summer months are characterized by reduced forest and agricultural fires, traffic, and increased vegetation, leading to lower PHE concentrations, especially in July, with typical amount of precipitation contributing to pollutant dispersion. Elevated PHE levels in September are observed due to increased traffic load, biomass burning, and the expansion of unvegetated soil areas. Rainwater is enriched with Sb, Pb, Cd, Zn, Cu, B, Bi, P, and Sr, sourced from vehicle emissions, soil particles, industry, construction dust, biomass burning, and forest fires. Moderate enrichment with Ba, Mn, Ni, Co, and Sn also occurs episodically. Regression analysis highlights solid particles’ role as a major PHE source in rainwater, with the longer antecedent dry periods and the higher acidity level of rain intensifying the accumulation of PHEs. Long-range transport plays a lesser role, with Southern and Northern Europe, Western Siberia, and the central part of European Russia contributing meaningfully.

Urban heat and pollution island in the Moscow megacity: Urban environmental compartments and their interactions

Cities are highly interconnected systems where specific interactions between various urban environments occur due to the Urban Heat Island (UHI) and Urban Pollution Island (UPI) effects. Four compartments of the environment (atmospheric air, road dust, streamflow, and people) are discussed for Moscow city. Long-term meteorological, radiative, air quality, and precipitation measurements, the non-hydrostatic regional numerical COSMO model, and extensive hydrological and geochemical sampling were used. To characterize mortality and UPI interaction, a family of distributed lag non-linear models (DLNM) was applied. The study reveals increased aerosols concentrations which reduce the incoming solar radiation and increase the atmospheric longwave radiation. UHI strengthens the low-troposphere convergence due to urban breeze circulation and atmospheric circulation due to elevated surface roughness, the effect which leads to 11.6% heaviest precipitation increase compared to background values. Increased precipitation doubles streamflow rates and enhances the contribution of rain floods to annual flow. Similar geochemical associations with Sb, W, Zn, Cd, Pb, and Cu were found in aerosol PM10, indicating transport and road dust impact. Finally, associations between high temperatures and human mortality which are generally stronger at high levels of air pollution for both PM10 and NO2, and for lag 1 day and 2–6 days are discussed.

Long-term variations of aerosol optical depth according to satellite data and its effects on radiation and temperature in the Moscow megacity

The rapid development of large megacities, coupled with emission regulations, can lead to long-term variations in aerosol optical depth over urban area which has an impact on radiation and temperature. This study aims to evaluate the radiation effects of aerosol pollution in Moscow and its surrounding areas using MAIAC data obtained from MODIS satellite data for three distinct periods: 2000–2006, 2007–2014, and 2015–2021. A methodology has been developed to incorporate MCD19A2/MODIS data with some additional information from the AERONET Moscow MSU site into the COSMO non-hydrostatic weather forecast model. The aerosol radiative and temperature effects were estimated for cloudless conditions. The highest aerosol optical depth with an average of 0.18 were observed during the 2007–2014 over the newly developed Moscow territory during the active building construction period. In the most recent period, from 2015 to 2021, the mean AOD decreased to 0.1. This reduction resulted in an increase of net shortwave radiation at the bottom of the atmosphere by 15–20 W/m2 and a slight rise in surface air temperature of 0.08 °C compared to 2007–2014. The parameterizations were proposed for net radiation and air temperature at 2 m as a function of aerosol optical depth and solar zenith angle at low surface albedo.

Impact of Wave COVID-19 Responses on Black Carbon Air Pollution in Moscow Megacity Background

Impact of Wave COVID-19 Responses on Black Carbon Air Pollution in Moscow Megacity Background

Machine Learning for Simulation of Urban Heat Island Dynamics Based on Large-Scale Meteorological Conditions

This study considers the problem of approximating the temporal dynamics of the urban-rural temperature difference (ΔT) in Moscow megacity using machine learning (ML) models and predictors characterizing large-scale weather conditions. We compare several ML models, including random forests, gradient boosting, support vectors, and multi-layer perceptrons. These models, trained on a 21-year (2001–2021) dataset, successfully capture the diurnal, synoptic-scale, and seasonal variations of the observed ΔT based on predictors derived from rural weather observations or ERA5 reanalysis. Evaluation scores are further improved when using both sources of predictors simultaneously and involving additional features characterizing their temporal dynamics (tendencies and moving averages). Boosting models and support vectors demonstrate the best quality, with RMSE of 0.7 K and R2 > 0.8 on average over 21 years. For three selected summer and winter months, the best ML models forced only by reanalysis outperform the comprehensive hydrodynamic mesoscale model COSMO, supplied by an urban canopy scheme with detailed city-descriptive parameters and forced by the same reanalysis. However, for a longer period (1977–2023), the ML models are not able to fully reproduce the observed trend of ΔT increase, confirming that this trend is largely (by 60–70%) driven by megacity growth. Feature importance assessment indicates the atmospheric boundary layer height as the most important control factor for the ΔT and highlights the relevance of temperature tendencies as additional predictors.

Does size matter? Modelling the cooling effect of green infrastructures in a megacity during a heat wave

The vulnerability of urban ecosystems to global climate change becomes a key issue in research and political agendas. Urban green infrastructures (UGIs) are widely considered as a nature-based solution to mitigate climate change and adapt to local urban climate anomalies in cities. However, UGI-induced cooling effect depends on the size, location and geometry of green spaces, and such dependencies remain overlooked. This research aimed to investigate the cooling effect of UGIs of different size under extreme conditions of 2021 summer heat wave for the case of Moscow megacity (Russia) using a numerical mesoclimatic model COSMO. UGIs objects were assigned to one of the four size categories (S, M, L and XL) based on their area. Their cooling effects at the local, non-local and city scales were evaluated based on comparison between the model outcomes for the realistic land cover and simulations for which UGI of a particular size category were replaced by the built-up areas typical for their surroundings. The highest cooling effect was observed for XL size UGIs, which reduced the local heat-wave-averaged air temperatures by up to 3.4 °C, whereas for the S size UGIs it did not exceed 2 °C. The cooling effectiveness for XL category was higher than for S category by 23 % inside the green spaces (locally), by 40–90 % in the buffer zones around the green space (non-locally) and by 35 % for the whole city. More effective cooling of large UGIs is partially explained by their stronger park breeze effect, i.e., impact on the airflow increasing the divergence over green spaces. However, when standardized to the population affected by cooling, the M size UGIs made the strongest contribution to the thermal environment where people live and work. The stronger non-local cooling induced by the largest UGI objects cannot compensate for their remoteness from the built environment.

Aerosol pollution of the Moscow megacity by polyaromatic hydrocarbons: Seasonal variability and toxicological risks

Research on air pollution in large cities by polycyclic aromatic hydrocarbons (PAHs) is one of the priority tasks for assessing air quality and environmental risks to public health. The chemical composition of aerosols sampled in spring (2018), 2019, and winter (2019–2020) at the Aerosol Complex of Moscow State University, located on the background territory of the Moscow Megacity, is analyzed. Sixteen priority PAH compounds were identified using gas chromatography, mass spectrometry, and high-performance liquid chromatography. The median value of the total concentration of the 16 PAHs (Σ16PAH) increases from the spring season (1.43 ng/m3) to the fall season (1.68 ng/m3) and then to the winter season (2.47 ng/m3). Based on the diagnostic relationships of PAHs, the dominant contribution of transport, industrial enterprises, and the heating system to the total emissions was determined. Pollution roses indicate the location of sources of maximum concentrations of low-, medium-, and high-molecular PAHs. Pollution episodes are distinguished: in the spring of 2018 under the influence of the transport of smoke plumes of agricultural fires and in the fall of 2019 as a result of petrogenic emissions and an increase in biomass burning in the residential sector around Moscow. In the winter and fall seasons, the highest values of carcinogenic (0.45 and 0.42) and mutagenic (0.58 and 0.55) equivalents for benzo(a)pyrene were recorded in comparison with the spring season (0.26 and 0.38). The lifetime risk of developing lung cancer, calculated from the data for three seasons, is 0.5 cases per one million people.

ЗАГРЯЗНЕНИЕ МОСКОВСКОГО МЕГАПОЛИСА: МОНИТОРИНГ ХИМИЧЕСКОГО СОСТАВА МИКРОЧАСТИЦ В СИСТЕМЕ “АТМОСФЕРА - СНЕГ - ДОРОЖНАЯ ПЫЛЬ - ПОЧВЫ - ПОВЕРХНОСТНЫЕ ВОДЫ”

A methodological framework for a system of ecological and geochemical monitoring of urban landscapes has been developed based on a joint analysis of the chemical composition of microparticles in transit (atmospheric aerosol and precipitation, river water and suspended sediments) and depositing (road dust, snow and soil covers, bottom sediments) environments. For automated monitoring on the territory of the Lomonosov Moscow State University Meteorological Observatory, the Aerosol Complex has been created, and seasonal variations in mass concentrations of PM10, black carbon, metals, metalloids, and polycyclic aromatic hydrocarbons in atmospheric aerosol and precipitation in the Moscow megacity has been analyzed. In the aerosol-precipitation subsystem, a high washout capacity of precipitation with respect to Pb, Sb, As, Ni, Mg, K, Al, and S in the aerosols has been revealed. The enrichment of PM10 with metals and metalloids decreases in the snow-road dust-soil series, and Sb, W, Bi, Sn, Cd, Cu, Pb, Mo, and Zn are accumulated in PM10 in all three environments. The particles of PM10 suspended matter and of the Moskva River bottom sediments play a key role in transport and accumulation of Pb, Cu, Ni, and V.

Moscow Megacity Pollution: Monitoring of Chemical Composition of Microparticles in the Atmosphere–Snow–Road Dust–Soil–Surface Water System

Moscow Megacity Pollution: Monitoring of Chemical Composition of Microparticles in the Atmosphere–Snow–Road Dust–Soil–Surface Water System

Assessment of sources, environmental, ecological, and health risks of potentially toxic elements in urban dust of Moscow megacity, Russia

Potentially toxic elements (PTEs) in urban dust of Moscow megacity and related risks have been studied. 78 samples were collected in the Moscow downtown in sites with different anthropogenic load, namely, major highways, residential area, and recreation zones. The concentrations of PTEs in urban dust were determined by ICP-MS and ICP-AES. Then, environmental, ecological and health risks of PTEs in urban dust were assessed. In addition, potential sources of PTEs in dust were identified. It is shown that Moscow dust is mainly contaminated by Sb, Zn, Pb, Cd, Cu, Sn, and Mo, which according to the data of principal component and correlation analyses can be attributed to anthropogenic sources (non-exhaust vehicle emissions). Potential ecological risk factor demonstrates that Cu, Mo, and Cd have moderate potential ecological risks in 13% of studied area, while Sb has this risk in 62% of area. Potential ecological risk indices indicate that 41% of studied territory is of moderate ecological risk. Concerning the human risks through ingestion, dermal contact, and inhalation pathways, PTEs in Moscow dust have no significant non-carcinogenic risks for adults. However, the value of total hazard index for children is 1.8 showing that non-carcinogenic risks may occur. Moreover, possible carcinogenic risks caused by Cr are evaluated. The finding of the present study can be used for ecological management in the megacity to reduce both ecological and human risks. A special attention should be given to periods of hot and dry weather and to traffic-related emissions.

Major ions and potentially toxic elements in atmospheric precipitation during the COVID-19 lockdown in Moscow megacity

For the first time, the change in the physicochemical properties, ions composition, concentrations, and ratio of soluble and insoluble potentially toxic elements (PTEs), as well as sources contribution to the content of PTEs using principal component analysis with multiple linear regression (PCA-MLR) were determined in the Moscow precipitation before, during and after the lockdown (January–July 2020). The impact of the lockdown on the precipitation composition was ambivalent. The decrease in the precipitation pollution with PTEs (by 10–99% for soluble PTEs and 9–61% for insoluble ones) was caused by the purification of the atmosphere from aerosols during their long-term washing out by precipitation and a decrease in anthropogenic emissions. Air advection to Moscow from the suburbs, where wood, coal, household and agricultural wastes were burned, on the contrary, contributed to the growth of precipitation pollution with insoluble P, Pb, Cd, soluble P, Ag, Pb, Sb, As, Cd, as well as [Cl−] and [K+]. After the lockdown, the restoration of the level of precipitation pollution by PTEs occurred gradually due to the time lag between the increase in atmospheric pollution and the washing out of aerosols by precipitation, as well as dilution by exceptional rainfall amount. Faster restoration rates of insoluble PTEs compared to soluble ones are associated with the rapid increase in the activity of the urban source (road and construction dust, industrial and traffic emissions). The lifting lockdown restrictions reduced the contribution of industrial sources to the content of soluble PTEs forms (from 38–66% to 6%) due to an increase in the contribution of road dust and non-exhaust emissions, soil particles resuspension, waste and fuel combustion, and vehicle emissions. A decrease in the contribution of vehicle emissions, road dust resuspension, and construction dust to the content of insoluble PTEs from winter to summer due to the lockdown influence and a large amount of precipitation in late spring and early summer was confirmed. The results highlighted the need for further studies of the chemical composition and properties of precipitation in the city in similar periods for the correct separation of the influence of social, economic, emission, meteorological, and physicochemical factors on the content and the ratio of PTEs forms.

Columnar and surface urban aerosol in the Moscow megacity according to measurements and simulations with the COSMO-ART model

Abstract. Urban aerosol pollution was analyzed over the Moscow megacity region using the COSMO-ART (COSMO – COnsortium for Small-scale MOdelling, ART – Aerosols and Reactive Trace gases) online coupled mesoscale model system and intensive measurement campaigns at the Moscow State University Meteorological Observatory (MSU MO, 55.707∘ N, 37.522∘ E) during the April–May period in 2018 and 2019. We analyzed mass concentrations of particulate matter with diameters smaller than 10 µm (PM10), black carbon (BC) and aerosol gas precursors (NOx, SO2, CHx) as well as columnar aerosol parameters for fine and coarse modes together with different meteorological parameters, including an index characterizing the intensity of particle dispersion (IPD). Both model and experimental datasets have shown a statistically significant linear correlation of BC with NO2 and PM10 mass concentrations, which indicates mostly common sources of emissions of these substances. There was a pronounced increase in the BC/PM10 ratio from 0.7 % to 5.9 %, with the decrease in the IPD index related to the amplification of the atmospheric stratification. We also found an inverse dependence between the BC/PM10 ratio and columnar single-scattering albedo (SSA) for the intense air mixing conditions. This dependence together with the obtained negative correlation between wind speed and BC/PM10 may serve as an indicator of changes in the absorbing properties of the atmosphere due to meteorological factors. On average, the relatively low BC / PM10 ratio (for urban regions) of 4.7 % is the cause of the observed relatively high SSA = 0.94 in Moscow. Using long-term parallel aerosol optical depth (AOD) measurements over the 2006–2020 period at the MSU MO and under upwind clean background conditions at Zvenigorod Scientific Station (ZSS) of the IAP RAS (55.7∘ N, 36.8∘ E), we estimated the urban component of AOD (AODurb) and some other parameters as the differences at these sites. The annual mean AODurb at 550 nm was about 0.021 with more than 85 % of the fine aerosol mode. The comparisons between AODurb obtained from the model and measurements during this experiment have revealed a similar level of aerosol pollution of about AODurb=0.015–0.019, which comprised 15 %–19 % of the total AOD at 550 nm. The urban component of PM10 (PM10urb) was about 16 µg m−3 according to the measurements and 6 µg m−3 according to the COSMO-ART simulations. We obtained a pronounced diurnal cycle of PM10urb and urban BC (BCurb) as well as their strong correlation with the IPDs. With the IPD index change from 3 to 1 at night, there was about a 4 times increase in PM10urb (up to 30–40 µg m−3) and a 3 times increase in BCurb (up to 3–3.5 µg m−3). At the same time, no pronounced daily cycle was found for the columnar urban aerosol component (AODurb), although there was a slight increase in model AODurb at night.

Seasonal, Weekly, and Diurnal Black Carbon in Moscow Megacity Background under Impact of Urban and Regional Sources

Moscow megacity has a big gap in assessment of air quality, resulting in severe aerosol pollution. Black carbon (BC) concentrations over different timescales, including weekly and diurnal, are studied during four seasons of 2019–2020 at urban background site. Seasonal BC varies from 0.9 to 25.5 μg/m3 with a mean of 1.7 ± 1.4 μg/m3. Maximum mean BC equal to 2.2 ± 1.8 μg/m3 was observed in spring. Diurnal trends of black carbon concentrations differ in spring/summer and autumn/winter periods, they exhibit morning and evening peaks corresponding to traffic combined with the boundary layer height effect. The weekly cycle of BC characterizes the highest amount of combustion-related pollution on working days and the characteristics of population migration from a city for weekend. Seasonal pollution roses show the direction of the highest BC contamination. For identification of BC sources relating to traffic, heat and power plants, and industry around the site, polar plots are used. The spectral dependence of the aerosol light attenuation provides the estimate for Absorption Angstrom Exponent (AAE). We use the AAE above 1.3 and high frequency of AAE observation above 1 in order to support the assessment for a contribution of biomass burning in the region around Moscow in autumn and winter as well as of agriculture fires and wildfires in warm seasons. Air masses arriving to a city from fire-affected regions in spring and summer impact urban air pollution.

Atmospheric transport of dust aerosol from arid zones to the Moscow region during fall 2020

<abstract> <p>We analyzed the unique episode of long-range dust/sand atmospheric aerosol transport from the arid zones of the southern European territory of Russia, i.e. the Northern Caspian and Astrakhan regions and the Kalmykia Republic, to the Moscow region during fall 2020. Intensive complex experiments were carried out at the A.M. Obukhov Institute of Atmospheric Physics of the Russian Academy of Sciencesin the center of Moscow through different seasons during 2020–2021 to study the composition of near-surface aerosols in the Moscow megacity. The experimental data are considered to take into account the synoptic features and meteorological conditions. Abnormally high values of near-surface aerosol mass concentrations in Moscow were registered during the period from 6 to 14 of October 2020 under stable anti-cyclonic conditions, with calm or quiet/light wind (1–2 m/s), and under the conditions of the dominance of southeastern air mass transport. At the same time, the average daily mass concentration of aerosol particles PM<sub>10</sub> exceeded the Maximum Permissible Concentration (MPC) value (60 µg/m<sup>3</sup>) by 1.5–4.5 times, and the number of large (micron) particles increased by an order or more. Comparative analysis of aerosol elemental composition in Moscow (during this episode) and in Kalmykia (according to observations in July 2020) showed high correlation for terrigenous elements' patterns. The aerosol origin for this episode was confirmed by performing long-range trajectory analysis of air mass transport (HYSPLIT model), and by using MERRA-2 reanalysis data for dust aerosol spatial distribution.</p> </abstract>

Quantifying Local and Mesoscale Drivers of the Urban Heat Island of Moscow with Reference and Crowdsourced Observations

Urban climate features, such as the urban heat island (UHI), are determined by various factors characterizing the modifications of the surface by the built environment and human activity. These factors are often attributed to the local spatial scale (hundreds of meters up to several kilometers). Nowadays, more and more urban climate studies utilize the concept of the local climate zones (LCZs) as a proxy for urban climate heterogeneity. However, for modern megacities that extend to dozens of kilometers, it is reasonable to suggest a significant contribution of the larger-scale factors to the temperature and UHI climatology. In this study, we investigate the contribution of local-scale and mesoscale driving factors of the nocturnal canopy layer UHI of the Moscow megacity in Russia. The study is based on air temperature observations from a dense network consisting of around 80 reference and more than 1,500 crowdsourced citizen weather stations for a summer and a winter season. For the crowdsourcing data, an advanced quality control algorithm is proposed. Based on both types of data, we show that the spatial patterns of the UHI are shaped both by local-scale and mesoscale driving factors. The local drivers represent the surface features in the vicinity of a few hundred meters and can be described by the LCZ concept. The mesoscale drivers represent the influence of the surrounding urban areas in the vicinity of 2–20 km around a station, transformed by diffusion, and advection in the atmospheric boundary layer. The contribution of the mesoscale drivers is reflected in air temperature differences between similar LCZs in different parts of the megacity and in a dependence between the UHI intensity and the distance from the city center. Using high-resolution city-descriptive parameters and different statistical analysis, we quantified the contributions of the local- and mesoscale driving factors. For selected cases with a pronounced nocturnal UHI, their respective contributions are of similar magnitude. Our findings highlight the importance of taking both local- and mesoscale effects in urban climate studies for megacities into account. Furthermore, they underscore a need for an extension of the LCZ concept to take mesoscale settings of the urban environment into account.

A new approach to study the long-term urban heat island evolution using time-dependent spectroscopy

This study presents a new approach to study long-term temperature and urban heat island intensity (UHII) evolution based on the method of time-depended spectroscopy on the example of Moscow megacity. In contrast to standard spectroscopy, this method allows analyzing the changes of the amplitude Fourier spectrum of the time series along the study period. Applying the novel method to the air temperature series for the period of 1977-2020, we demonstrate that ongoing changes of the mean temperature and UHII are accompanied by the changes of their spectra, including the spectral amplitudes corresponding to diurnal, annual and synoptic-scale oscillations. Such changes are complex, often non-linear, and seasonally asymmetric. Steady upward trends are found for summer season, for the spectral amplitudes of diurnal temperature and UHII oscillations, and synoptic-scale UHII oscillations. Spectral amplitudes of annual temperature and UHII oscillations experiences V-shaped dynamics with an increase since 1990th. For UHII such pattern reflects a switch between regimes with wintertime or summertime UHI maximum. Presented results provides an evidence that observed intensification of Moscow's UHI is forced not only by urban growth, but also by changing background meteorological conditions, which are becoming more favorable to UHI appearance in summer and less favorable in winter.

Air Pollution in Moscow Megacity: Data Fusion of the Chemical Transport Model and Observational Network

Comparisons of observational data obtained at the Moscow Ecological Monitoring network (MEM) with numerical simulations using a chemical transformation and transport model (SILAM—System for Integrated modeLling of Atmospheric coMposition) showed that the errors in determining the gaseous pollutant concentrations in the urban atmosphere have a more complex structure than those assumed under the conventional algorithms of data assimilation. These errors are statistically nonstationary; they show a pronounced diurnal cycle and a significant lifetime. The statistical features of errors in numerical calculations also depend upon the type of pollutants, i.e., the chemical reactions in which they participate. Our analysis showed that the simulation errors are not small: the ratios of calculated and measured concentrations (even for daily averages at all measuring stations) may vary in a wide range. For the chemically active pollutants, the intradiurnal error variations may reach 100%. The diurnal cycle of such errors was found to vary according to seasons (in our case, summer and winter). The analysis of statistical properties of the errors, including their temporal and spatial variability, allows one to correct and adequately forecast the air pollution in the metropolis area at lead times up to three days in advance.

Citizen weather stations data for monitoring applications and urban climate research: an example of Moscow megacity

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.

Urban heat island of the Moscow megacity: the long-term trends and new approaches for monitoring and research based on crowdsourcing data

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. As a prototype a monitoring application, based on CWS data, we developed a web-service for real-time temperature mapping in Moscow, which is available at http://carto.geogr.msu.ru/mosclim/.