Special Issue on Carbonaceous Aerosols in the Atmosphere (I)

Olga B. Popovicheva This email address is being protected from spambots. You need JavaScript enabled to view it.1, Marina A. Chichaeva2, Roman G. Kovach2, Ekaterina Yu. Zhdanova2, Victor M. Stepanenko3,2,4, Alexander Varentsov3,2,4, Nikolay S. Kasimov2 

1 Scobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, 119991, Russia
2 Faculty of Geography, Lomonosov Moscow State University, Moscow, 119991, Russia
3 Research Computing Center, Lomonosov Moscow State University, Moscow, 119991, Russia
4 Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, 119017, Russia


Received: November 29, 2023
Revised: January 31, 2024
Accepted: February 7, 2024

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.230266  


Cite this article:

Popovicheva, O.B., Chichaeva, M.A., Kovach, R.G., Zhdanova, E.Y., Stepanenko, V.M., Varentsov, A., Kasimov, N.S. (2024). Impact of Wave COVID-19 Responses on Black Carbon Air Pollution in Moscow Megacity Background. Aerosol Air Qual. Res. 24, 230266. https://doi.org/10.4209/aaqr.230266


HIGHLIGHTS

  • The most distinct responses of first COVID-19 wave in Moscow megacity.
  • BC source changes indicate strength of restriction measures.
  • Strict self-isolation led to the migration of population forcing to use BB.
  • No change in transport and economical activities during third COVID-19 wave.
 

ABSTRACT


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 (ВС) 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%) was in opposite the highest 20% due to the city population migration to countryside and increased residential heating in a surrounding Moscow region. During the recovery period the 88% change of BC occurred with respect to lockdown. BCff component associated with emissions from fossil fuel (FF) combustion showed 100% increase. BB% dropped down to 13%, typical summer level. Decrease of traffic and industrial enterprise emissions during lockdown led to the change of BC daily and weekly trends. During the lockdown 2021 the mean BC increased despite a high number of pandemic cases. The absence of the impact of third wave COVID-19 response on black carbon showed the different levels of restriction strength implemented in the northern largest European megacity during various pandemic waves.


Keywords: Restriction, Economical activity, Transport, Biomass burning, Residential heating


1 INTRODUCTION


Following the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for COVID-19 and its spread over the world, the World Health Organization declared a global pandemic in March 2020. Because a lack of available treatment and vaccination in 2020 and to combat further spread of the virus, the prevention measures included social and working restrictions which were introduced in many countries in so-called lockdown periods. After first lockdown periods in 2020, waves of the COVID-19 pandemic have surged through communities; the world has experienced how to endure lockdowns and a shakeup of economics, employment force, and resources. Finally, air pollution and mortality has long been recognized as a high risk factor for COVID-19 impacts (Pansini and Fornacca, 2021). 

In contrast to societal impacts, air quality was improved in many countries of Asia, Europe, and America, where the strict lockdowns were applied (Adams, 2020; Navinya et al., 2020; Xu et al., 2020; Ambade et al., 2021). The period which involved stoppage of educational and recreational activities showed the most significant reduction for fresh traffic emissions and their aerosol products in terms of ultrafine nuclei particles and nitrates (40–50%) (Eleftheriadis et al., 2021). Black carbon (BC) is mainly emitted from incomplete combustion of fossil fuel (FF) and biomass burning (BB) by transport, power production sources, industry, residential heating, and wildfires (Petzold et al., 2013). Fossil fuel combustion was found to be the major contributing source to BC levels during both the warm and cold period. Long-range transport from the surrounding regions, together with local meteorology and atmospheric boundary layer dynamics, has been identified as main factors affecting BC concentrations in the urban environment (Tiwari et al., 2013; Ramachandran et al., 2021). BC is the most dangerous and toxic aerosol component from the point of view of the impact on public health, in comparison with other sources (Wang et al., 2014). BC has become one of the most significant indicators of the pandemic environment impacts. Its averaged emissions declined 11% (20% in Italy, 32% in Germany, 20% in Spain) during lockdowns over Europe, as compared to the same period in previous 5 years (Evangeliou et al., 2021). Traffic BC emissions dropped by 35% (Grivas et al., 2020) and 47% (Panda et al., 2020) during quarantine, in comparison with the period before the epidemic. In a city isolated from air pollution transport or industrial sources, traffic flows reduced by 60–80% led to a reduction in BC of 55–75% (Patel et al., 2020). Various impacts on BC before and after COVID-19 pandemic were observed (Dehhaghi et al., 2023; Liñán-Abanto et al., 2023).

However, various cities showed the different levels of fine particulate mass decrease with various impact from sectors of different economic and population activity, also the absence of any pandemic-related changes (Adams, 2020). Pollution was slightly enhanced particularly in Eastern Europe where residential biomass burning (BB) was increased because lower air temperature occurred at that time (Evangeliou et al., 2021). BC from both FF and BB emissions showed an increase governed mostly by residential emission where population use biomass and oil for heating (Eleftheriadis et al., 2021). The BCff component, associated with emissions from FF combustion, showed a decrease of 33% as well. FF contribution was low as compared to wood burning during lockdown in the Indian large city (Ambade et al., 2021). Due to reduced emissions, the relative fraction of FF to total BC dropped to 71% during the lockdown in East China (Lin et al., 2021). The impact of wood burning during lockdown was confirmed by measurements of the absorption Angstrom exponent (AAE) that was higher in lockdown than in the same period of previous years (Grivas et al., 2020).

Temporal reductions in pollutions levels could not be directly attributed to lockdown due to favorable meteorological variations during that period. In some cases, levels of the studied air pollutants did not appear to be strongly dependent on meteorological irregularities or inter-annual trends (Eleftheriadis et al., 2021). However, severe air pollution events occurred in North China Plain during the pandemic of coronavirus diseases due to unfavorable meteorological conditions whereas almost all avoidable activities were prohibited in China (Wang et al., 2020).

Moscow is one of the most densely populated megacities in Europe. Lockdown provided an opportunity to measure a change in the atmospheric pollution in Moscow by the decrease of air quality index since the end of February 2020 (Hartwell et al., 2021). In April 2020, 30%–50% decrease of CO, NO2, NO, SO2, and PM10 was declared (Ginzburg et al., 2020; Chubarova et al., 2021). During lockdown period from 30 March until 8 June, the significant decrease in the concentration of major pollutants (NO2, CO, PM10) was recorded and associated to meteorology-related impact like rainy weather and Arctic air intrusions (Chubarova et al., 2021; Skorokhod et al., 2022). Changes in the concentrations of PM10-bound potentially toxic elements was observed in comparison with the period of economic and traffic recovery (Serdyukova et al., 2023). In Popovicheva et al. (2021) the BC components were examined, while FF impact was reasonably decreased, the surprised increase of BB contribution to BC was observed. Notably, that it occurred in the northern megacity where gas-fueled centralized heating supply operates during the cold seasons and biomass is not used by population for any type of activity. Such finding as well as the BC response to the COVID-19 waves in next year needs the estimates of various economic and population activities related to different levels of restrictions implemented in a megacity.

An aim of this study is to evaluate the wave pandemic response on air pollution related to black carbon and its sources in Moscow megacity. A thorough assessment of BC concentrations are performed to quantify the lockdown-related changes during the first COVID-19 wave in comparison to the recovery period in 2020, at the same time in the next year 2021 as well as against the previous 2019. Sources and relative contributions of FF combustion and BB are determined by an aethalometer model. BCff and BCbb component changes present the source-related responses on various restriction level restrictions during the wave COVID-19 lockdowns. BC temporal variations are analyzed according to diurnal and weekly trends and atmospheric boundary layer dynamics. Evaluation on how representative the wave responses with respect to the general variability of weather patterns and air mass transportation factors affecting aerosol levels is also important to present here.

 
2 METHODS


 
2.1 Study Area

Moscow megacity (55°45′N; 37°37′E at the city center) (map in Fig. 1) is located in the middle of the East European Plain. It covers an area of 2561 km2 and has a registered population exceeding 13.8 million. Moscow is the northernmost between the largest European cities; it is characterized by a humid continental climate (Dfb according Köppen climate classification). Moderate average air temperatures, low solar UV radiation levels, and good ventilation make the accumulation of primary emitted pollutants and the photochemical formation of secondary pollutants is not intensive (Elansky et al., 2014). Moscow has a developed transport, heat and power, and industrial infrastructure that use fossil fuels (gas, diesel, gasoline). While automobilization is growing in Moscow, intensive implementation of higher ecological classes of engines and better quality of fuel promote the improvement of vehicle ecological parameters (Bityukova and Mozgunov, 2019). Transport statistics for 2019, 2020, and 2021 in Moscow megacity is presented in Supplementary Material (SM). Standards below Euro-5 have been banned since January 2016. Because of the climate, there is a specific concern for particular emission sources such as a central heating system operating during a cold period. Heat and power plants, and residential sector in a city are almost totally supplied with natural gas (it composes 96.7% of fuel consumption). Biomass does not used either for industrial, domestic heating, or individual purposes in Moscow, in opposite to many European and Asian cities (Nava et al., 2015; Diapouli et al., 2017; Zhang et al., 2017). However, in a huge region around a city the biomass can be used for heating of country houses, during garden cleaning and other activities. Coal consumption by heat plants has significantly decreased during last years, different from Asian part of Russia (Bityukova et al., 2021).

Fig. 1. Map of Moscow megacity. Insert on the right is the area of Moscow State University campus. Sampling site at Meteorological Observatory of Moscow State University (MO MSU) (55°42′N; 37°31′E) is indicated. Aerosol Compex MSU is on a photo. Fig. 1. Map of Moscow megacity. Insert on the right is the area of Moscow State University campus. Sampling site at Meteorological Observatory of Moscow State University (MO MSU) (55°42′N; 37°31′E) is indicated. Aerosol Compex MSU is on a photo.

Annual average particulate matter (PM) is comparable to large European cities but lower than in Asian megacities (Cheng et al., 2016). There are no particularly critical issues about atmospheric pollution in Moscow urban background, in comparison to evaluated large European and Canadian cities (Popovicheva et al., 2024; Zappi et al., 2023). BC measurements addressed the level of air pollution in the city downtown substantially lower than in Beijing (Golitsyn et al., 2015). BC concentrations in spring in Moscow urban background were found comparable to Helsinki city, the less polluted city in Europe (Popovicheva et al., 2020b). First assessments of sources relating to traffic, heat and power plants, and industry were based on seasonal BC data and spectral light absorption in 2018 and 2019 (Popovicheva et al., 2020b; Popovicheva et al., 2022a).

Fires are traditionally high in spring when temperature rises; agriculture practice with a purpose to remove the last year grass on the fields is widespread in this season, it impacts the aerosol properties as well (Chubarova et al., 2011). The biggest impact on BC and aerosol composition in a megacity was observed during extreme wildfires in 2010 (Popovicheva et al., 2014) and peat burning in 2014 (Popovicheva et al., 2019). BB impact was observed in spring 2017, especially during May holidays from 1 to 10 May 2017 in Popovicheva et al. (2020a), and in spring 2018–2019 in Popovicheva et al. (2020b). High BB impact was recorded from the spectral dependence of the aerosol light attenuation and the estimate for Absorption Angstrom Exponent (AAE) in autumn and winter 2019–2020 in (Popovicheva et al., 2022a); it was related to pronounced BB in residential areas surrounding a city, including the heating and waste burning.

 
1.2 Lockdown and Recovery Periods

In Moscow, a number of reported COVID-19 cases increased from April to June 2020, daily maximum approached 6703 (Fig. S1). By the beginning of summer the situation was stabilized. Quarantine in Moscow lasted from 26 March to 12 May. Forced self-isolation and non-working days were announced for all activities, with the exception of grocery stores and pharmacies. Passes were introduced that gave permission to the movement of personal vehicles around the city, they allowed to go out onto the streets for personal needs no more than 2 times a week. After 12 May the enterprises received permissions to work and since 1 June Moscow began to ease the strict restrictions on movement and work of the population. The cancellation of passes took place on June 09, 2020. On 10 June, the recovery period began. By 18 June it was announced that business activity returned to its former normal course following the total return to the usual city activity.

Traffic statistics reports that a number of cars in 2020 was by 5% less than in 2019, see SM for details. Data taken from TomTom maps and traffic data system provide the hour-by-hour congestion averaged for each day of week for previous and COVID-19 impacted years. They show the congestion of roads in April 2020 has significantly decreased, about 4 times in comparison with the same period in 2019 (Fig. S2).

Second wave of COVID-19 cases started on 19 November 2020 and lasted to 22 January 2021 year (Fig. S1). The record of 9108 for a number of cases per day was broken on 18 June 2021 during the third pandemic wave. From 12 June 2021 non-working days were announced in Moscow, they were extended until 20 June 2021. During third wave lockdown period the employers were obliged to ensure the vaccination of 60% of all employees. Admission to catering establishments was allowed only upon presentation of a QR code. For employers, a forced and mandatory transfer of 30% of employees to a remote work format was introduced. This requirement was relevant until August 13. After this date, most employees legally returned to full-time work. In 2021, a number of cars increased if compare to 2020. Moreover, the passenger flow structure was changed toward to the increase of private transport. Freight transport was banned from entering not only the center of Moscow but also the Moscow ring road, see SM. For the transit of trucks in the Moscow Region the traffic was launched along the Central Ring Road.

 
1.3. Sampling Campaign, Measurements, and Data Analyses

The measurement campaign was conducted at the Aerosol Complex located at Meteorological Observatory of Moscow State University (MO MSU), southwest of Moscow city (Fig. 1). The residential area and a highway takes place about 800 m south of the observatory, industrial areas situate at a distance of 3 km and greater. Thus, Aerosol Complex is not directly affected by local pollution sources such as large transport roads or industrial facilities. This enabled the revealing the trends of aerosol composition as parameters of background urban pollution (Chubarova et al., 2014) and classified the site as an urban background according the accepted site classification (Putaud et al., 2010).

An aerosol sampling system was installed at the pavilion of the Aerosol Complex. Inlet supplied by PM2.5 impactor takes place proximately 1.5 m above the roof and 4 m above the ground, it supports the real-time BC monitoring with air flow at 5 L min−1. Aethalometer АЕ33 (Magee Scientific, Aerosol d.o.o.) was used to measure the light attenuation caused by particles depositing on two filter spots at different flow rates (Drinovec et al., 2015) and at seven wavelengths from ultraviolet (370 nm) to infrared (950 nm). The “dual spot” technique was applied for real-time loading effect compensation. The light-absorbing content of carbonaceous aerosols at 880 nm was reported as equivalent black carbon concentration (eBC), which is determined for each time interval from the change in the light attenuation at a wavelength λ of 880 nm, using a mass absorption cross-section of 7.7 m2 g1. Precision of AE33 measurements is < 10%, the limit of detection is 40 ng m3 at 1 min time resolution, the measurement uncertainty for eBC is 27%.

Difference in spectral absorption of emissions from high-temperature combustion of fossil fuel (FF) and low-temperature biomass burning (BB) dependes on the wavelength. The eBCff and eBCbb components were estimated based on the aethalometer model (Sandradewi et al., 2008). It is assumed that the absorption coefficient babs(λ) is a sum of babs(λ)bb and babs(λ)ff fractions. Model is based on the difference in absorption coefficient wavelength dependency assuming that absorption due to FF and BB emissions follow λ1 and λ2 spectral dependencies, respectively. The exponents which describe the spectral dependence are αff = 1 for fossil fuel and αbb = 2 for biomass, λ = 470 and 950 nm are used. Portion of biomass burning BB% is estimated as

  

Biomass burning and fossil fuel BC fractions are then calculated as

 

Absorption Angstrom Exponent (AAE) was calculated for 470 nm and 950 nm wavelengths:

 

For the detailed AAE treatment see elsewhere (Popovicheva et al., 2022b).

PM10 mass concentrations were provided by Mosecomoniroring service operated at the territory of Meteorological station MSU, using TEOM 1405 (Thermo Fisher Scientific, US). For meteorological parameters the data from a service of Meteorological Observatory MSU were used (http://www.momsu.ru/english.html). In order to describe the variability of meteorological parameters during the study period, we calculated the deviations of their means from climatic values estimated for the period from 1981 to 2010, called as “climate normal”.

The global atmospheric reanalysis ERA5 (Hersbach et al., 2020) with the ECMWF IFS hydrodynamic model version CY41R2 was used for boundary layer height (BLH) estimations. The methodology is described in the model version (ECMWF, 2016). The reanalysis data are available on a latitude-longitude grid with a step of 0.25°; a linear interpolation of data from the nearest grid nodes to the MO MSU location (55.707005°N, 37.521840°E) was performed.

Pollution rose is a variant of a wind rose that is useful for considering pollutant concentrations by wind direction, or more specifically the percentage time the concentration is in a particular range. Pollution rose techniques is well-known as an informative way for identifications what is the direction of the source that the highest pollutant concentrations are associated.

Backward trajectories (BWT) were generated using NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model of the Air Resources Laboratory (ARL) (Stein et al., 2015) with the horizontal resolution 1° × 1° of latitude and longitude and archived meteorological data from GDAS (http://www.arl.noaa.gov/ready). The potential source areas were investigated using 48 hours back BWT for air masses arriving each one hour at 500 m height above ground level (A.G.L.).

Сluster analysis of trajectory data is an effective method of grouping the trajectories by combining the geographically close data, it takes into account the features of seasonal atmospheric circulation. The angular method was selected in which the matrix of angular distances shows how similar are two points of the BWT in dependence on their angle with respect to the initial location (Cui et al., 2021).

Concentration weighted trajectory (CWT) analysis is an effective tool that is combined with BWT data and pollutant concentrations to trace the source origin (Bian et al., 2018). For each grid cell, the mean concentration of a pollutant species is calculated as follows:

 

where Cij is the average weighted concentration in the grid cell (i, j), i and j are grid indices, k is the index of trajectory, N is the total number of trajectories used, Ck is the pollutant concentration measured upon arrival of k trajectory, and τijk is the residence time of k trajectory in a grid cell (i, j). A high value of Cij means that air parcels passing over cell (i, j) would cause high concentrations at the receptor site.

Fire information was obtained from Resource Management System (FIRMS) operated by the NASA/GSFC Earth Science Data Information System (ESDIS) (https://firms.modaps.eosdis.nasa.​gov/map). It is based on satellite observations which register the thermal spots (open fires) with temperature above 2000 K. For the best identification of fire location data, this work uses data arrays on the spatial location of fire centers from the Visible Infrared Imaging Radiometer Suite (VIIRS). Daily maps were related to the computed trajectories, providing a picture of the geographical location of each cluster fires in areas where the frequency of passing BWT’s were more than 20%.

The measurement campaign started from 15 April 2020. With the purpose to follow the dynamics of restriction measures and corresponding atmosphere pollution response, the period of first wave lockdown is defined from 15 April to 31 May 2020 (LP2020) (Fig. S1). The period from 1 June to 31 August 2020 is related to a recovery period (RP2020) (Fig. S1). In order to compare the impacts of wave COVID-19 responses on black carbon, we analyze the same dates, i.e., from 15 April to 31 August in 2021 year. However, at the same time in 2021 the lockdown period (LP2021) took place from to 1 June to 31 August and followed the pre-lockdown period (PLP2021) from 15 April to 31 May (Fig. S1). A choice of the reference period against which changes are evaluated is an important issue. In our study, BC data collected at the Aerosol Complex MSU in 2019 years (Popovicheva et al., 2022a) was used for comparison with the same periods of 2020 and 2021 years.

 
3 RESULTS AND DISCUSSION


 
3.1 Meteorological Conditions

Air pollutants are affected significantly by variability in meteorological processes and air mass transportation. A seasonal BC and meteorological pattern in 2019 with differences observed between spring and summer has been documented in Popovicheva et al. (2022a). Here we present the meteorological parameters and cluster analysis of trajectory data during lockdown and recovery periods in 2020, pre-lockdown and lockdown in 2021. Mean temperature, pressure, wind speed, precipitation, and height of the atmospheric boundary layer during lockdown LP2020 and recovery RP2020, pre-lockdown PLP2021 and lockdown LP2021 periods as well as the climatic normal are presented in Table S1. А change of means for the same times in 2021 versus 2020 is estimated.

Temperature, atmospheric pressure, and their deviations from the climate normal are shown in Fig. S3. The period of lockdown LP2020 was eventually extended from the end of April until beginning of June, 2020.It fell in spring time when temperature and radiation were rising. Mean air temperature during spring time of LP2020 was less than in PLP2021, 9.3°C and 12.2°С, respectively, but both were close to the climate normal of 11.9°С. This makes these periods equivalent in terms of requirements for residential heating. Summer time of RP2020 was characterized by smaller mean temperature, 18.5°С, than in LP2021, although higher than climate normal 18.0°C during both periods. Atmospheric pressure slightly increased in the same periods of 2021 compared to 2020 that could result in the greater accumulation of pollution in 2021. Abnormally large amount of precipitation was observed in all studied periods, especially in May and June of 2020 when daily precipitation exceeded 40 mm on some days (Fig. S4) and strongly exceeded (more than 3 times) the climate normal 56 mm (Table S1). Less precipitation occurred in the spring period PLP2021 in comparison with LP2020, by 15%. The similar decreasing trend was observed for the summer periods, by 25%.

The local meteorology is considered by analysis of the air circulation conditions using wind roses (Fig. S5). During LP2020 the wind from S–W, N–W, and N–E directions prevailed, with speeds up to 7 m s1; it was changed to E–S–W and western directions during PRP2020. The less contrasting wind conditions were observed in summer periods of RP2020 and LP2021. We note that the wind speed in spring time was higher than in summer time for both years, as well as in 2020 versus 2021. The daily and seasonal variation in aerosol concentrations depends on the dynamics of the atmospheric boundary layer which is determined by processes of heating/cooling, shear mixing, and photochemical activity. Mean boundary layer height (BLH) did not change between the same seasons of both years and slightly changed from spring to summer time.

One considers as a reference period for concentration of air pollutant species the same period from previous years (Eleftheriadis et al., 2021; Evangeliou et al., 2021). Looking at the weather conditions during the same periods of our study in previous 2019, temperatures were at 14.9°C and 18.1°C in spring and summer times, respectively. Significantly higher temperature than the climate normal in spring time of 2019 points to a level where the use of residential heating could be reduced greatly, whereas during the first COVID-19 wave in 2020 it was similar to those during pre-lockdown of the third 2021 wave.

 
3.2 Air Mass Long-range Transportation

The long-range air mass transport may play a role in affecting the levels of incoming pollutants in a megacity (Liu et al., 2018). Cluster analyses of backward trajectories indicates the major directions of air mass transportation during lockdown LP2020 and recovery RP2020, pre-lockdown PLP2021 and lockdown LP2021, as described in details in SM. Backward trajectories in each cluster are presented in Fig. S6. Fig. 2 shows the frequencies of 48-h BWT in relation to the total number of analyzed trajectories for four clusters identified for study periods of 2020 and 2021. During spring time of LP2020 the highest frequencies (> 20%) of BWTs occurred in the northwestern direction for the main cluster C1. Directions of the highest BWT frequencies changed to western-southwestern and northwestern for C2 and C3, and to southern for C4, respectively. Summer time of RP2020 was characterized by the highest frequencies of BWTs in western and northern directions for C1 and C2 clusters, and in southeastern and southern directions for C3 and C4 clusters, respectively. In PLP2021, the prevailed northwestern direction of air mass transportation was recorded also for the main C1 cluster. Directions of BWT highest frequencies were changed to south and southwest for C2 and C3, respectively, whereas to the opposite northwestern direction (with respect to LP2020) for C4. In LP2021 we observed the same highest BWT frequencies directions in northwest, south, and southwest for C1, C3, and C4, respectively, but a change to east for C2.

Fig. 2. 48-h BWT frequencies (%) of four clusters during lockdown LP2020 and recovery RP2020 periods of 2020, pre-lockdown PLP2021 and lockdown periods LP2021 in 2021. Fire locations related to the time of BWT pass are indicated by stars, MO MSU site is marked.

Fig. 2. 48-h BWT frequencies (%) of four clusters during lockdown LP2020 and recovery RP2020 periods of 2020, pre-lockdown PLP2021 and lockdown periods LP2021 in 2021. Fire locations related to the time of BWT pass are indicated by stars, MO MSU site is marked.

The majority of wildfire emissions have been recorded in the European part of Russia from March to late May (Huang et al., 2015). Satellite data of fire activities occurred in the regions surrounding Moscow at the same time of BWT pass are shown in Fig. 2. Number of fires for study periods is presented in Table S2. The biggest spring fire account was in LP2020 in the southern directions from Moscow, 315 and 810 for C2 and C4 clusters, respectively. At same time during PLP2021 the maximum number of fires (2663) was recorded in the southern directions for C2 cluster. In RP2020 the highest number of summer fires was recorded also on south, 753 for C3 and 348 for C4. During LP2021 it approached 674 for C3 cluster. Considering that a number of fires at the same time when BWT passed can act as an indicative parameter of affecting the levels of incoming pollutants in a megacity, the transport pattern of pre-lockdown PLP2021 indicated the potential highest impact.

 
3.2 BC and PM10 Concentrations

Time series of air quality concentration in terms of eBC mass during the study periods of 2020 and 2021 are displayed in Fig. 3; eВС means are presented in Table 1. А change of the mean eBC concentration during RP2020 with respect to LP2020 period, and during LP2021 with respect to PLP2021 is estimated as LP&RP and LP&PLP, respectively. With a negative sign of a change we observe a reduction, the positive sign indicates an increase. The eBC concentrations during LP2020 were characterized by episodes of low values with 0.3 µg m–3 during forced self-isolation and non-working day. High values with a maximum of 4.6 µg m–3 was observed when enterprises received permissions to work. The eBC mean concentration was 0.9 ± 0.7 µg m–3. During RP2022 of the recovery to normal activity, the 88% of eBC change was recorded: on average eBC increased up to 1.6 ± 1.4 µg m–3. Hypothesis t-testing in this study is used to examine whether the difference between periods is statistically different. A t-test shows difference of –9.7, (p-value < 2.2e-16) for eBC during LP2020 as compared to RP2020.

Fig. 3. 24-h time series of (a) PM10, (b) eBC and (c) BB%, (d) FF%, and (e) AAE during lockdown LP2020 and recovery RP2020 periods in 2020, and pre-lockdown PLP2021 and lockdown LP2021 in 2021.Fig. 3. 24-h time series of (a) PM10, (b) eBC and (c) BB%, (d) FF%, and (e) AAE during lockdown LP2020 and recovery RP2020 periods in 2020, and pre-lockdown PLP2021 and lockdown LP2021 in 2021.

Table 1. Mean ± std. for eBC, eBCff, and eBCbb component, and PM10 mass concentrations (in µg m–3) and BB% (in %) during lockdown (LP2020) and recovery (RP2020) periods of 2020, and pre-lockdown (PLP2021) and lockdown (LP2021) periods in 2021. Duration of periods is indicated. Change (%) during RP with respect to LP period is LP&RP, during LP with respect to PLP is LP&PLP.

The impact of abnormally large amount of precipitation was associated with meteorology-related impact on changes aerosol pollution during lockdown in Moscow in (Chubarova et al., 2021Skorokhod et al., 2022). It should be noted that if we remove from the dataset the periods of rain, the mean eBCno rain concentrations do not change significantly (t = –0.3, p-value < 2.2e-16) and the change LP&RP remains the same (Table 1). The mean eBC during PLP2021 was 0.8 ± 0.6 µg m–3, it increased to 1.4 ± 0.9 µg m–3 during LP2021 despite the proposed decrease during lockdown after pre-lockdown when non-working days and remote working format were announced in Moscow.

Of a particular interest is the variability of eBC concentrations during lockdown of 2020 (from 15 April to 31 May), at the same time in 2021 (pre-lockdown) and in previous 2019 year. The median eBC reached a maximum of 0.15 µg m–3 in 2019, it fell to 0.8 µg m–3 in 2020 (Fig. S7). t-test shows a significant deference (t = 10.7, p-value < 2.2e-16). The lower level in 2020 reasonably related to social and working restrictions of first COVID-19 wave. The lowest median eBC of 0.5 µg m–3 occurred during pre-lockdown period of third COVID-19 wave in 2021 Сhanges in none of the meteorological parameters can explain such a low value: nor the increase in pressure, nor the decrease of precipitation and BLH (Tables S1 and S2). If consider a number of fires and road congestion as the indicative measures, the increase of fires with respect to 2020 and almost similar road congestion as in 2019 also cannot support the lowest median eBC during pre-lockdown period of 2021. Probably, the total urban emissions have been decreased. The structure of passenger and freight traffic has changed significantly probably due to transport legislation at that time (see SM).

The median eBC during recovery of 2020 (from 1 July to 31 August), in the same time in 2021 (lockdown) and previous 2019 are shown in Fig. S7. In 2020 it was 1.2 µg m–3 and just slightly less than 1.5 µg m–3 in 2019. Similar median eBC levels during recovery of 2020 and lockdown of 2021 occurred. Meteorological parameters and number of fires were remaining similar at those times, the precipitation decreased by 25%. However, the mean eBCno rain concentration did not change significantly in RP2020 and LP2021 periods in comparison with eBC (Table 1). Such conclusion indicates the absence of significant change in emissions, transport and economical activities during lockdown of third COVID-19 wave.

PM10 mass is widely used as the air pollution metrics however its usage in pandemic - related studies did not always show the positive impact of COVID-19. Time series of PM10 mass during the study periods of 2020 and 2021 are displayed in Fig. 3. Mean PM10 mass during LP2020 was 15 ± 8 µg m–3 (Table 1). It slightly (by 20%) increased to 18 ± 10 µg m–3 during RP2020. This indicates the recovery period does not show a strong first COVID-19 wave impact onto PM10. Prominent impact of soil re-suspension on increased PM mass has been usually recorded in springtime at the MO MSU (Gubanova et al., 2018). Mean PM10 mass during PLP2021 was 11 ± 10 µg m–3. It increased up to 17 ± 9 µg m–3 during the third wave lockdown LP2021, despite the expected drop because of restriction measures.

 
3.4 BC Source Apportionment

The contribution of fossil fuel and wood burning to BC concentrations was quantified through the application of the multi-wavelength aethalometer model (Diapouli et al., 2017; Liu et al., 2018; Mousavi et al., 2018). eBCff concentrations were significantly higher than eBCbb (Fig. 4) due to the dominant contribution to the Moscow megacity atmosphere pollution from fossil fuel (diesel, gasoline, and gas) combustion in transport engines, industrial plants, and heating system in comparison with BB for any seasons and years. During lockdown LP2020 the mean ВСff was 0.7 ± 0.6 µg m–3, in 3.5 times higher than the mean ВСbb of 0.2 ± 0.1 µg m–3 (Table 1). From LP2020 to RP2020, there was a significant increase for BCff by 100% that indicates the recovery impact of traffic as well as economic activity related to the fuel consumption and energy production sectors. The road congestion, the indicative measure of traffic, has significantly decreased in April and May 2020, about 7 and 2.5 times, respectively, in comparison with the same period in 2019 whereas in June and July 2020 it was fully approached the same level as in 2019 (Fig. S2). There was no change for the mean BCbb from LP2020 to RP2020, it became 7 times less than BCff during the recovery period. Such difference in changes of eBC components indicates the strongly different first COVID-19 wave responses from two combustion sources relating to strict social and working restrictions.

Fig. 4. BCff and ВСbb concentrations during (a) lockdown LP2020 and recovery RP2020 periods in 2020 and (b) pre-lockdown PLP2021 and lockdown LP2021 in 2021.Fig. 4. BCff and ВСbb concentrations during (a) lockdown LP2020 and recovery RP2020 periods in 2020 and (b) pre-lockdown PLP2021 and lockdown LP2021 in 2021.

Portions of biomass burning BB% and fossil fuel combustion FF% are shown in Table 1 and Fig. S8. Time series of BB% indicates a significant decrease from 25% at the beginning to 15% at the end of LP2020 (Fig. 3), with the mean 20 ± 9%. FF% in opposite increased from 75% to 85%, with the mean 80 ± 1%. Considering that in Moscow city the gas-fueled centralized heat supply operates for both residential and industrial sectors, biomass is not used by population for heating or other type of activity, sources of high BB pollution in spring are either due to wood burning in a residential sector of the Moscow surrounding region or fires occurred around a city (Popovicheva et al., 2022a). We note that during lockdown 2020, when the most strict self-isolation restrictions was implemented, a significant number of Moscow citizens was forced to migrate from a city and live in the country houses around a megacity where burning of biomass for heating and garbage cleaning is widespread. An increased populations in the Moscow region during lockdown was confirmed by observation of the unusual for Moscow agglomeration spatial distribution of the higher total concentration of nitrogen dioxide NO2 and carbon monoxide CO in the atmospheric column in comparison with less one in Moscow city and nearby suburbs (Skorokhod et al., 2022).

The gross number of fires in all cluster directions of air mass transportation during LP2020 was 1355 (Table S2). It decreased down to 1136 during summer time RP2020 when the significant increase of mean air temperature from the relatively low 9.3°C during spring time of LP2020 to 18.5°C was observed (Table S1). The decreased mean BB% of 13 ± 3% during RP2020 characterizes the summer time in the Moscow region that is also the vacation time for the Moscow citizens.

During pre-lockdown PLP2021 the mean ВСff was 0.7 ± 0.5 µg m–3, almost at the same level as in previous first COVID-19 wave spring period. Whereas the mean ВСbb was only 0.05 ± 0.1 µg m–3 and 140 times less despite the relatively low air temperature 12.2°C in the same spring time. BB% showed the low level 5 ± 5%, typical for spring time when a low number of citizens accommodate in the region around a city. Although a number of fires were 4 times more during this time, apparently the long transportation of agriculture fire smoke did not impact much on BCbb level.

The impact of wood burning and wildfires during study periods can be confirmed by the estimation of absorption Angstrom exponent (AAE), using Eq. (5). Time variation of AAE during study periods is shown in Fig. 3. During lockdown 2020 the mean AAE was high, 1.3 ± 0.06 (Table 1), corresponding to high BB% of 20 ± 9%. It just slightly decreased to 1.2 ± 0.05 in summer of 2020. Low AAE of 0.9 ± 0.2 was in 2021 relating to low level of BB% (5 ± 5%), see above. Notably, that this value is typical for spring in the Moscow megacity (Popovicheva et al., 2022a).

From PLP2021 to LP2021, there was a significant increase of BCff by 85%, in despite of expected decrease because the third COVID-19 wave period. FF% slightly decreased from 95% to 90% that indicates the absence of any significant impact of lockdown restriction measures on transport and economic activity at that time. The road congestion was unchanged in 2021, in comparison with 2019 in the study periods (Fig. S2).

 
3.5 BC Diurnal and Weekly Trends

The diurnal evolution of aerosols is influenced by the variation in atmospheric boundary layer (ABL) and source strengths of emissions (Ramachandran and Rajesh, 2007; Tiwari et al., 2013).

The BLH exhibits a definitive diurnal structure, its evolution over land is closely coupled with the heating of the surface by the Sun radiation. Diurnal dynamics of the BLH averaged over the studied periods is shown in Figs. 5(a) and 5(b). The higher BLH is from midday to the afternoon, increasing the atmospheric dilution capability for air pollutants and lowering the aerosol concentrations. Daily variations of the BLH height in spring time of LP2020 and PRP2021 were similar, approached a maximum around 1600 m at 15:00 and a minimum around 300–400 m at night. Change to summer time decreased the BLH during RP2020 by 300 m in the afternoon and by 200 m at night in comparison with LP2020 that could result to increasing the aerosol concentrations in recovery vs. lockdown period. In summer of 2021, decreasing the BLH during LP2021 by 200 m was observed only in nocturnal hours.

Fig. 5. Diurnal variations of hourly boundary layer height (a, b) BLH, (c, d) eBC concentrations, and (e, f) BB% during LP2020 and RP2020, and PLP2021 and LP2021.Fig. 5. Diurnal variations of hourly boundary layer height (a, b) BLH, (c, d) eBC concentrations, and (e, f) BB% during LP2020 and RP2020, and PLP2021 and LP2021.

During the lockdown LP2020, the daily eBC variation differed significantly from the recovery period RP2020 by lower hourly averaged values and flat dynamics with the absence of a morning maximum (t = –5.4, p-value = 4.06e-06) (Fig. 5(c)). Such a diurnal variation occurred due to the low traffic intensity and moderate economic activity in a city. The similar decreased BC absorption and the absence of a peak on the traffic rush hours was observed in other cities during lockdown (Lin et al., 2021). At night, the eBC level rose to 1.4 µg m–3, similar to nocturnal values measured in the spring of 2017–2018 (Popovicheva et al., 2020b). Such high level at night is the result of the peculiarities of the regulation of cargo transportation in Moscow where the entry of heavy duty vehicles into the city center is limited during the day, see SM for transport statistics. During the recovery RP2020, a significant increase in eBC concentrations (t = 10.2, p-value = 7.3e-12) was observed at any time of the day as well as a change in the shape of the diurnal cycle due to the recovery of economic activity and traffic (Fig. 5(d)). The diurnal variation of the FF% during lockdown LP2020 was typical for a large city, with the morning peak and minimum in the afternoon. For the BB% it was distinguished by a long daily maximum near 22% (see Fig. 5(e)). Since the spring time of 2020 characterized by the low air temperature and high migration of citizens, such result corresponds to intensive heating of country houses and garden cleaning in the region surrounding a city. In summer during the recovery RP2020 the average daily temperature increased, the using of biomass burning fell, and the diurnal variation leveled off.

During lockdown LP2021 the daily eBC variation differed from the pre-lockdown PLP2021 by higher hourly averaged values (Fig. 5(d)). Shape of diurnal trend with a morning peak was similar for both periods, indicating no strong change in traffic intensity and economic activity occurred during the third COVID-19 wave. The higher hourly averaged values and shape differences of BB% during lockdown LP2021 vs. pre-lockdown PLP2021 were similar to that observed during LP2020 vs. recovery RP2020 lockdown (Fig. 5(f)). t-test shows a significant different of BB% t = 19, p-value < 2.2e-16 (LP2021 to PLP2021) and t = 17.4, p-value < 2.2e-16 (LP2020 to RP2020). But the level of BB% was significantly less in 2021, the daily maximum approached only 11% because the lockdown of third COVID-19 wave occurred in summer time when BB for heating was not significant and migration of population was not prominent.

The working activity of the population is clearly related to the emissions from urban sources. The weekly variation of the eBC concentration during lockdown LP2020 shows the lowest level in the middle of the week and its increase to the weekend (Fig. S9(a)) as it could be expected in the situation of long nonworking days during the period of significant restrictions. The recovery in economic activity during RP2020 changed the weekly trend: eBC high concentrations shifted to working days that are typical for the normal population activity. The flat weekly eBC trend observed during RP2020 is typical for the summer vacation period when there is practically no difference in emissions from transport and enterprises between working days and weekends. High BB% during working days of LP2020 (Fig. S9(b)) once more proves the migration of population out of the city during lockdown whereas its increase towards the weekend days in both LP2020 and RP2020 indicates the higher population during weekends in the region around Moscow. The higher hourly averaged eBC and its prominent peak in Thursday during LP2021 (Fig. S9(c)) stresses the absence of a significant impact of restriction measures on working activities at that time. Almost flat shape of weekly variations of BB% during both LP2021 and PRP2021 support the conclusion about the low migration and population activity in the area surrounding a city in 2021.

 
3.6 BC Local and Regional Sources

Fig. 6 shows the BC pollution roses during study periods, providing a graphical representation of the source variation for the MO MSU site. During lockdown LP2020 the high eBC concentrations 3–14 µg m–3 were observed from the Ochakovo industrial zone in the southwest as well as from the combined heat and power plant, asphalt and concrete factories in the southeast (Popovicheva et al., 2021). The highest eBC more than 4 µg m–3 was originated in the northwest and northeast. During recovery RP2020 the maximum eBC increased to 8–10 µg m–3 in the northwestern direction. Whereas during PLP2020 the eBC sources of highest 2–3 µg m–3 concentrations were in northwestern and southeastern direction, the eBC pollution roses during lockdown LP2021 showed the homogeneously distributed sources in all directions.

Fig. 6. eBC pollution roses during study periods.Fig. 6. eBC pollution roses during study periods.

Source region analyses allows the addressing the air mass origin and estimating the relative importance of emitters in different regions (Molnár et al., 2017). BC aerosol pollution transport relates to the atmospheric circulation and spatial distribution of regional sources. Air masses arriving to a city may impact the urban air quality, especially if the direction of their long-range transportation well correlates with fire-affected area. We use the CWT modeling, Eq. (6), to provide the estimate for the origin of regional sources for observed high eBC concentrations at the MO MSU site. In spring the summer agriculture and wildfires may occur in the region around Moscow, providing the strong impact on eBC concentration level. The residential sector can impact with using of biomass burning for house heating and cleaning the gardens.

Fig. 7 shows the regional distribution of eBC sources, estimated by CWT analyses during study periods of 2020 and 2021. During lockdown LP2020, source regions of spring high concentrations (above 3.0 µg m–3) were located in the southwest and southeast of Moscow. They are associated with FF and BB - relating activity of regional population during the first COVID-19 wave. The biggest number of agriculture fires occurred in the southeastern direction from Moscow (Table S2).

Fig. 7. Regional distribution of eBC sources, estimated by concentration weighted trajectory (CWT) analysis, during (a) LP 2020, (b) RP2020, (c) PLP 2021, and (d) LP2021 for MO MSU site.Fig. 7. Regional distribution of eBC sources, estimated by concentration weighted trajectory (CWT) analysis, during (a) LP 2020, (b) RP2020, (c) PLP 2021, and (d) LP2021 for MO MSU site.

Smoke emissions made a significant contribution from the northwest in C1, the southwest in C2, the northeast in C3, and from the south in C4 cluster (Fig. 2). Source regional distribution for BB% higher than 24% covered the large area of European part of Russia (Popovicheva et al., 2021).

During recovery RP2020, the total area of summer high eBC was significantly increased; it extended far to the north and south, encompassing the large FF and BB sources. Recovered economical, social and working activities as well as summer time turned the regional BC sources distribution to the normal features. Forest fires were recorded almost in the south of Moscow at that time (Fig. 2), their total number decreased (Table S2).

During pre-lockdown PLP2021, the total area of spring high eBC was negligible in comparison with the same time of previous year. Especially the disappearing of eBC sources near Moscow is prominent to note, those were so high due to the mass migration of Moscow citizens out of a city during lockdown of 2020. Such observation well correlates with a decrease of BB% down 5% at that time (Table 1) almost because the low residential heating activity during PLP2021. There was only the stretched area with a loop toward southeast, most probably related to strong wildfires in C2 cluster (Fig. 2). Summer time of 2021, even related to lockdown of the third wave COVID-19, in opposite the expectation of decreasing, demonstrated the high eBC concentration sources in largely extended area. That area was larger than in previous summer, despite the strongly decrease the total number of fires (Table S2). This finding shows the limited restriction impacts on the regional eBC source distribution during the third COVID-19 wave.

 
4 CONCLUSIONS


Moscow, one of the largest European megacity, has endured COVID-19 lockdowns and a shakeup of economics, traffic, and employment force during 2020 and 2021 years. We analyze how the wave COVID-19 responses have been related to different economic and population activities using black carbon and its source-related components as the best indicators of urban air quality change. BC temporal variation showed the most distinct impacts of the first COVID-19 wave lockdown in spring 2020, if compare with the same time of previous 2019 year and a summer period of recovery after 1 June 2020. Mean BC concentration fell by 88% due to the strict restrictions on personal movement and work of the population, in relation to many non-working days and road congestion decreasing. Typical for large cities two peak BC daily structure leveled off. BC weekly cycle showed the lowest concentrations in the middle of the week and increase to the weekend. There were no BC changes associated with the possible meteorology-related impact of abnormally large amount of precipitation during spring and summer 2020. Despite the non-use any kind of biomass in the northern city due to the central heating system operation, the biggest lockdown impact occurred on the portion of biomass burning BB% which increased up to 25% in spring 2020. Strict self-isolation was the main reason for migration of a significant part of population to areas surrounding a city at that spring time when biomass was widely used for residential heating. The similar BB lockdown impact was observed in cities with major contributions from non-traffic related sources where the population used the increased amount of biomass for residential heating whereas the restriction measures led to the migration of Moscow population forcing to use BB in the region around a city.

In the same periods of 2021 the third COVID-19 wave occurred. During spring pre-lockdown the mean BC was even less than in 2020; in summer it increased by 87% despite the expected decrease due to restriction measures. Absence of any changes in daily BC trend, higher concentrations on weekdays relating to the largest combustion emissions on working days, and the strong traffic congestion demonstrates the absence of any significant change in emissions, transport and economical activities during lockdown of third COVID-19 wave. BB% showed the low level 5 ± 5%, typical for spring time when a low number of citizens accommodate in the region around a city, although a gross number of fires in all air mass transportation clusters was a few times more than in spring 2020 during this time. BB% increased to the typical summer level up to 10 ± 5%. Such difference in changes of BC and its two sources during third COVID-19 wave indicates that non-working days, requirements of QR code, and remote work format were not such strong restriction measures as in 2020, despite a higher number of pandemic cases.


ACKNOWLEDGMENTS


The RSF project #19-77-3004-П funding for the aethalometer methodology implementation is appreciated. Analyses of daily and weekly trends were carried out under support of the grant of the Ministry of Science and Higher Education of the Russian Federation (No.075–15–2021–574). E. Zhdanova thanks the research program of Moscow State University (MSU) "Weather and climatic processes of the various spatio-temporal scales under anthropogenic impact", project no. 121051400081-7. Research was carried out with equipment of MSU Shared Research Equipment Center “Technologies for obtaining new nanostructured materials and their complex study” and National Project "Science".


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