Black carbon in spring aerosols of Moscow urban background

At present, air pollution by the smallest suspended particles (aerosols) is recognized as one of the most important environmental problems. Particulate matter characterized by a small aerodynamic diameter of less than 10 pm (PM10) contains environmentally hazardous components and it is recommended by the World Health Organization (WHO) as an air quality indicator. In accordance with the WHO air quality standards for PM10, a daily mean maximum permissible mass concentration of 50 pg/m³ is established (Who 2005). Black carbon (BC) is the light-absorbing component of aerosols, warming the atmosphere and thus affecting the Earth's radiation balance on a global scale (Bond et al. 2013). Estimates suggest that BC is the second most critical factor, following by carbon dioxide, contributing to global warming by direct forcing (Jacobson 2010). BC has drawn a considerable attention because of its environmental significance (Ramachandran and Rajesh 2007; Ahmed et al. 2014; Diapouli et al. 2017).

BC is mainly present in aerosols in urban environment (Mousavi et al. 2018), and thus it concerns local air quality and population health (Janssen et al. 2011). BC-containing particles are small enough to be readily inhaled into the human body and affects the respiratory system leading to exacerbate respiratory, cardiovascular, and allergic diseases, thus relating to adverse health effects (Pope III and Dockery 2006; Steiner et al. 2013). Epidemiological evidence links the exposure to BC with cardiopulmonary hospital admissions and mortality (WHO 2012).

Assessments of the ability for BC to affect the environment and health require a comprehensive study of the aerosol composition as well as a deep understanding of aerosol-related impacts. The comprehensive characterization of aerosols in the urban atmosphere makes it possible to identify sources of pollution and assess the consequences of effects of their emissions on air quality and human health. BC is increasingly recognized as the most important pollution contributor originating from anthropogenic activities, such as fossil fuel combustion (transport, energy production, residential heating) and biomass burning (domestic and wildfires). Diesel exhaust, which comprises high amounts of BC, is classified as a carcinogen for humans by the International Agency for Research on Cancer (IARC). Impact of traditional agriculture biomass burning (BB) activities on regional air quality is a major environmental concern, indicating that it may profoundly affect public health in urban areas (Popovicheva et al. 2017b).

BC emissions are found particularly large in most urbanized Asian cities where the rapid industrial and economic development has been accompanied by serious fine particle pollution of the atmosphere (Ohara et al. 2007; Chen et al. 2014). For US and European cities the source apportionment approach is intensively developed in order to estimate the most significant and dangerous combustion sources (Herich et al. 2011; Healy et al. 2017). An actual review on the status of ambient pollution in global megacities showed that the five most polluted megacities are Delhi, Cairo, Xi'an, Tianjin and Chengdu, all of which had an annual average concentration of PM2.5 greater than 89 pg/m³ (Cheng et al. 2016). European megacities (London, Moscow and Paris) had much lower annual average concentrations between 18 and 21 pg/m³. However, these concentrations still are above the air quality guideline set by WHO to 10 μg/m3 (WHO 2005).

Moscow megacity is the leader among all large cities of Russia on total number of inhabitants. However, for Moscow the situation is currently complicated by the existing lack of the aerosol composition and BC pollution assessments. High anthropogenic emissions of PM in Moscow can occur due to traffic, industry, heating, waste recycling, and construction. Additionally, secondary aerosol formation and long transportation can impact the particulate loading and composition, as it was occurred during an extreme smoke events related to intensive wildfires near the city (Popovicheva et al. 2014; Popovicheva et al. 2019).

However, Environmental Protection Agency "Mosecomonitoring'' conducts the measurements for only PM10 and PM2.5 mass concentrations at some monitoring stations. The analysis of measured daily mean PM10 concentrations and calculated ones by chemical transport model CHIMERE showed the high temporal variability reflecting the influence of local sources and atmospheric processes (Kuznetsova et al. 2011; Gubanova et al. 2018). Presently, BC is not a subject of the consistent monitoring, it is remaining as a topic of a few scientific research performed in the Moscow center (Golitsyn et al. 2015; Kopeikin et al. 2018).

The purpose of this study is the analysis of the aerosol pollution related to BC in total PM10 mass in the urban background of the Moscow megacity. Spring season is chosen because this time is characterized by an elevated number of BC sources including the seasonal agriculture fires in surrounding areas and residential BB around the city. We measure and examine the diurnal variability of BC concentrations under real conditions of the diversity of urban sources of emissions and meteorological factors. Wind speed and direction affect BC concentrations while air mass transportation from fire-affected regions support the increased level of BC pollution in spring in the urban background.

MATERIALS AND METHODS

Measurement site

Moscow megacity covers an area of 2 561 km² and has a registered population exceeding 12.5 million in 2018. It is the largest city of Russia, and generally represents a typical urban area. Presently, in Moscow megacity 26 gaseous and particulate pollutants (PM10 and PM2.5) are under continuous measurements (Kul'bachevskii 2017). Around 630 industrial enterprises of various branches of mechanical engineering and metal working, power engineering, chemistry and petrochemistry, light and food industry, production of construction materials (including 30 000 stationary emissions sources) are registered. Around 50% of all pollutant emissions from industrial sources are emitted by enterprises producing and redistributing energy, gas, and water. Gaseous Automobile transport exhaust composes 95% of total city emissions. According the reports from the Moscow Committee of environmental protection and natural resources and the Department of the Federal State Statistics Service, industrial production zones occupy around 17% of the city area, from stationary sources fourteen biggest enterprises provide up to 85% of gross pollution (Bityukova and Saulskaya 2017) while transport emissions compose up to 93 % of gross pollution from mobile sources (Kul'bachevskii 2017). In total industrial emissions the processing productions, the production of oil products, and the production and power distribution of gas and water are dominated while gas composes 96.7% of fuel consumption. The biggest fractions of industrial emissions are NO_x (50%), CO (15%,), SO₂ (16%) and 11% of volatile organic compounds. The Moscow city often faces serious traffic congestion problems because of the increased vehicle numbers; the total count of vehicles was registered as much as 4.6 million by the end of 2017 (Kul'bachevskii 2017). High speed of construction in Moscow additionally increases the aerosol loading in the atmosphere.

Black carbon mass concentration measurements were conducted at the rooftop of two-story building of the Meteorological Observatory of Moscow State University (MO MSU). MO is located at the territory of the MSU campus, southwest of the Moscow city (55°07'N, 37°52'E) (Fig. 1).

It takes place in an area of hills Vorobievy Gory which is well ventilated. There is no any industrial plants or commercial areas nearby (Fig. 2). At about 800 m to the north from the MO MSU there is the residential area and to the north-west the Lomonosovsky prospect highway is located. The closed industrial enterprises are central and quarter heating stations, and industrial areas which take place at the distance of 3 km and longer from the MSU. Therefore, MO MSU is considered operated as an urban background site.

Data collection

Aerosol equivalent BC concentrations (eBC) were measured using the portable aethalometer custom made by MSU/CAO. In this instrument the light attenuation caused by the particles depositing on a quartz fiber was analyzed at three wavelengths (450, 550, and 650 nm). eBC concentrations were determined by converting the time-resolved light attenuation to EBC mass at 650 nm and characterized by a specific mean mass attenuation coefficient as described elsewhere (Popovicheva et al. 2017a). Calibration parameter for quantification eBC mass was derived during parallel long­term measurements against an AE33 aethalometer (Magee Scientific) that operates at the same three wavelengths. Attenuation coefficient b_atn, is defined as

b_atn   = A δ ATN V                                                  (1)

where A is the filter exposed area, V is the volume of air sampled, and 5ATN is the light attenuation defined as follows:

δ ATN = In(I₀ /1)                                                          (2)

where I₀ and I is the light intensity transmitted through unexposed and exposed parts of the filter, respectively. Good linear correlation between the aethalometer's attenuation coefficient b_atn, and the eBC concentrations calculated with the AE33 aethalometer (at 660 nm) was achieved (R² = 0.92). This allowed the estimation of eBC mass concentrations using the regression slope and intercept between b_atn at 650 nm and eBC of the AE33 aethalometer at 660 nm:

EBC = 3.3 *10⁵ * A * δATN / V                                     (3)

where 3.3 x 10⁵ is the correction factor that includes the specific mass absorption coefficient for the MSU aethalometer calibrated against the AE33 aethalometer. Equation (3) assumes the mass absorption cross-section (MAC) adopted by AE33 equal to 9.89 m² g, values for A and V used to be in m² and m³. The constant MAC value adopted here is an approximation, assuming a uniform state of mixing for BC in atmospheric aerosol. This can be considered as a valid assumption in case of background aerosol measurements performed in this study. The level of uncertainty of eBC measurements was 30 ng/m³ for a 6 min integration time. Aethalometer filters were changed manually, when ATN approach the threshold value around 70 that corresponds the twice decreasing of light intensity transmitted.

Measurements were performed from 17 April to 25 May of 2017 and from 19 April to 23 May of 2018. Continuous measurements of meteorological parameters (temperature, relative humidity, pressure, precipitation, wind speed and wind direction) were performed each 3 hours routinely by MO MSU meteorological service. PM10 mass concentrations were collected by Mosecomonitoring using the tampered element oscillating microbalance TEOM 1400a (Thermo Environmental Instruments Inc., USA). These data were used for the comprehensive database of whole sampling runtime.

In spring time fires are usually observed on the South of the Moscow city, the agriculture practice with a purpose to remove the last year grass on the fields is widespread in this season. Biomass burning in residential areas around city is pronounced, especially during May holidays from 1 to 10 May. Therefore, air mass arriving to urban area due to long-range transportation may impact the air quality of the city, especially if direction of their transportation well correlates with fire- affected regions. To evaluate the air mass transportation impact the 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 coordinate resolution equal to 1° x 1° of latitude and longitude. The potential source areas were investigated using 2-day backward trajectories for air masses arriving each 12 hours to the MO MSU at 500 m heights above sea level (A.S.L.). Fire information was obtained from Resource Management System (FIRMS), operated by the NASA/GSFC Earth Science Data Information System (ESDIS). It is based on satellite observations which register the open flaming with temperature above 2000 К. Daily maps were related to the computed trajectories, providing a clear picture of the geographical location of fires, with the several kilometer resolutions. A number of fires which could affect air masses transported to the MO MSU was calculated as a sum of fires occurred at distance 0.5° on both latitude and longitude from BTW. The number of fires passed by BWT was estimated as the sum of the amounts of all points of fire caught on the back trajectories points or in their neighborhood of no further than 0.5° along the latitude and longitude. Number of fires indicates the BB-influenced days.

RESULTS AND DISCUSSION

Diurnal BC patterns

The diurnal eBC mass concentrations measured in spring seasons of 2017 and 2018 are shown in Figure 3. On a daily basis of 2017, there is an increase in concentrations starting from 04:00, and the relatively prominent morning peak occurs at 7:00-09:00. eBC concentrations are found to be the smallest during midday until the evening, around 19:00. After this time the gradual increase of eBC is observed, reaching the maximum at 21:00-22:00. During 2018, the mean diurnal BC mass concentration is found to be constant from midnight to 04:00, the poorly noticeable peak occurs at around 05:00, and after the gradual decrease is marked until 20:00. Morning peak similar observed in spring of 2017 is not observed anymore in spring of 2018. The diurnal variation in mean BC mass concentrations is appeared around 1 pg/m³, approaching maximum 2 and 1.8 and minimum 0.9 and 0.5 pg/m³ during spring of 2017 and 2018, respectively.

The atmospheric abundance of BC is affected by both the stability of the boundary layer and anthropogenic activities in an urban environment (Ramachandran and Rajesh 2007). The nocturnal boundary layer depth is shallower than its daytime counterpart by a factor of 3-5. The development of a well- mixed layer height begins from 08:00, reaching maximum value around 14:00, decreases after 17:00, and later drops to the lowest level at night. The surface inversion after sunset results in the accumulation of BC, causing even higher concentrations in the late evening. It should be note that in many urban areas the evening peak is happened between 21:00 and 22:00 (Ramachandran and Rajesh 2007; Kozlov et al. 2011; Chen et al. 2014).

In large cites the BC morning peak is well observed for diurnal mass concentrations; it is attributed to the combined influence of the lower mixing layer height and vehicle traffic enhancement in the morning (Ramachandran and Rajesh 2007; Kozlov et al. 2011; Chen et al. 2014). The minimum BC concentrations are found during midday when there are fewer anthropogenic BC emissions, while the deeper boundary layer leads to a faster dispersion resulting in a dilution of BC concentrations at midday.

Diesel and petrol are the major fossil fuels used for road transportation, the main part of the diesel vehicles are heavy- duty vehicles. Diesel vehicles are known to produce much more BC than the vehicles which run on gasoline (Weingartner et al. 1997). Heavy duty (e.g., trucks, buses etc.) diesel vehicle can contribute an average 42% BC to particulate matter (Reddy and Venkataraman 2002). Vehicles which run on leaded petrol and unleaded petrol (which do not have catalytic convertors) can give rise to 6 and 23% of BC in PM mass. They include two-wheelers such as scooters, motor bikes in addition to cars. In Moscow, a mixture of all vehicles runs on the roads and contributes to BC. In 2017 the Uniform interdepartmental information and statistical system (www.fedstat.ru) reported around 4640 000 vehicles, including 90.4 and 8.5 % of light and heavy duty cars and trucks, respectively, as well as 1,1 % of buses.

Stable high mean BC concentration from midnight to pre-dawn is observed especially prominent in 2018 (Fig. 3). Such diurnal profile is different from observed in large Russian city Tomsk (Kozlov et al. 2011) and Indian city Ahmedabad (Ramachandran and Rajesh 2007), and in megacity Athens (Diapouli et al. 2017). One reason may be related to increased emissions from diesel trucks (especially after 22:00) which could contribute to the higher BC concentration in the late evening (Garland et al. 2008). Here we should confirm that there is a restriction for heavy duty cargo vehicles to entry the Moscow city center during daytime, they are allowed to bring cargo only after midnight. Therefore, probably stable high BC observed later evening and during night time is due to the significant impact of diesel running vehicle emissions (almost from heavy duty cargo transport) in Moscow megacity.

Relationships between BC and meteorological parameters

The physical and chemical processes of BC emission, transformation, transportation, and accumulation in the atmosphere relate to meteorological conditions, i.e. wind speed and direction, transport of air masses, and the intensity of precipitation. The wind roses at MO MSU in both 2017 and 2018 spring seasons show the relatively homogeneous distribution of the wind direction during the sampling period, with the prevailing south-west direction and with a repeatability frequency up to 10% in this direction (Fig. 4). This finding confirms the observations of the South-West prevailing wind direction in the air layer from 40 to 500 m for the period of 2004-2014 at the MO MSU (Lokoshchenko 2015). The western component of the wind strengthens in spring and summer, that means that the South- Southwest direction is registered more rarely, and the West-Southwest one, more frequently.

The highest frequency of eBC pollution, around 13%, is found during northern wind, according to the eBC pollution roses (Fig. 5), when eBC mass concentrations approached 7 and 5 pg/m³ in 2017 and 2018, respectively. Other directions of SW (225°), NW (315°), and NE (45°) relating to the high frequency of 6, 5, and 8%, respectively, indicate the most relevant emission source locations. Analysis of the geographical locations on a map shows that in the direction of SW (270-225°) the industrial area ''Ochakovo'' is located, and two quarter thermal stations take place in the direction of NNW and NW (around 335°), central heating plants can pollute MO MSU from north and NE (45°) (Fig. 2).

Wind speed is an important factor affecting BC concentrations: higher wind speeds contribute to stronger BC dispersion. It is probable that due to higher wind speeds BC produced from local sources are transported to other locations. Such phenomenon is typically observed in polluted urban area (Chen et al. 2014). It was found from BC measurements made in urban sites in Toronto that low wind speeds lead to much less dispersion of BC and the traffic emissions remain concentrated around the emission site (Sharma et al. 2002). It was also noted that as the traffic density was relatively constant through the measurement period, higher wind speeds have a dilution effect on BC. Correlation between wind speeds and BC mass concentrations may give an indication of the proximity of BC sources at the measurement site, while the absence of significant correlation shows that the BC originates from distant sources.

A regression of BC mass concentrations with wind speed at MO MSU during spring seasons yield a negative regression coefficient (slope) -0.51 and -0.41, respectively (Fig. 6). This indicates that with increase in wind speeds the BC mass concentrations would decrease, as seen. Such correlation between wind speeds and BC mass concentrations gives an indication of the intensive BC sources in a megacity.

Seasonal PM10 variations

The time series of РМ10 mass concentrations over the whole period of observation is depicted in Fig. 7 and 8 for two- year spring seasons. In 2017, 1h mean РМ10 concentrations showed a strong variation from lowest of 8 μg/m³ up to the highest value of 82 μg/m³, on average 22±16 μg/m³. In 2018, the PM10 variations from 2 to 90 μg/m³ were even more frequent but on short-term, on average 26±16 μg/m³. These values are comparable to PM10 concentrations averaged over warm season (May-September) obtained from the data for 236 urban background monitors in Europe in the periods of 2003-2006, on averaged amounts to 19.9 g/m³ (Konovalov et al. 2009). For spring periods of 2014 and 2016 PM10 concentrations was 30.0 and 25.4 pg/m³, and 22.5 and 17.8 pg/m³ in the Moscow center and at the suburban station, respectively; the difference of 26% between their average values is caused by an addition from urban sources (Kopeikin et al. 2018).

During spring seasons of our study PM10 concentrations exceeded the daily mean maximum permissible mass concentrations from one to seven times in 2017 and 2018, respectively. The longest episode of the highest PM10 was observed at MO MSU from 30 April until 3 May of 2017, on average 55±19 μg/m³. Almost at the same days, from 29 April until 2 May the ambient temperature has approached an abnormally high level for this season, + 21 °C (Fig. 9). In observation period of 2018, the permissive maximum PM10 values were exceeded seven times. the ambient temperature has approached + 21°C twice, on 1 and 18 May.

Such exceeding of the air quality standards can occur during meteorological conditions unfavorable for pollutant dispersion, passage of cold atmospheric fronts, and arrival of air masses polluted by fires around the city (Kuznetsova et al. 2011). Analysis of location impact showed that the maximum PM10 concentration was observed at the stations in the eastern sector of the Moscow city and less often in the west of Moscow, at the MO MSU station (Kuznetsova et 21 Apr 26 Apr OlMay 06 May IIMay 16 May 21 May al. 2011). This apparently reflects both local sources and a windward position in respect to the prevailing urban transfer. In the Moscow suburban station in Zelenograd city, both measured and calculated daily mean PM10 concentration was almost always lower than at all urban stations, which confirms that a megalopolis is a significant source of aerosol emissions. Observation of PM10 in summer showed a distinct correlation between short-term episodes of high PM10 with the local temperature maximums (Kuznetsova et al. 2011).

A substantial positive correlation between temperature variations and PM10 measurements at the European stations in the summer months was also established from the numerical analysis (Konovalov et al. 2009). The existence of this correlation can be attributed to the fact that, as a rule, high-temperature periods are followed by an anticyclonic (blocking) situations promoting the build-up of the atmospheric pollutants (Kuznetsova et al. 2011). The PM10 concentration maximum is reached directly before or at the moment of the passage of cold front after the period of stagnation. A high PM10 concentration can also be a result of the wind uplift of aerosols due to wind strengthening before the front passage in a warm sector of a cycle with sufficient precipitation and the air mass change, whereas the situation was preceded by dry weather favorable for the soil erosion.

In our study we observe relatively good correlation between high PM10 and the local temperature maximums, with correlation coefficient R2 equal 0.68 and 0.57 for 2017 and 2018, respectively (Fig. 10). It is expected that intensive precipitation may lead to strengthened wet aerosol deposition. Analysis of 24-h PM10 variation with daily precipitation, shown on Fig. 10, indicates the decrease of PM10 in relation with days of rain. The most prominently this phenomenon is observed for 18-20 May when during the period of the most intensive rains (more than 7.4 mm) we observed the lowest PM10 mass (around 13 pg/m³).

Seasonal BC and level of pollution variations

The time series of 1-h mean eBC concentrations over the spring periods of sampling show the high eBC variability, ranged from 0.1 up to 5 and 10 pg/m³, on average 1.5+1.3 and 1.1+0.9 pg/m³, in 2017 and 2018, respectively (Fig. 7 and 8). Observations performed in the Moscow center showed the averaged BC concentrations of 4.4 and 1.7 pg/m³ while on suburban background station they were consistently less than 3.0 and 1.05 pg/m³, in spring 2014 and 2016 (Kopeikin et al. 2018).

Table 1 presents the mean BC concentrations obtained during the spring seasons at MO MSU, and rural and remote sites in different world locations. Comparisons show BC at MO MSU is lower than in European large cities like London (2.7 pg/m³) (Kendall et al. 2001) and Budapest (2.95 pg/ m3) (Salma et al. 2004). However, the sites in these cities are classified as urban ones taking place in the city center. The closest to the measured BC value for MO MSU we find with the spring mean BC in the less polluted city in the Europe Helsinki, 1.03 pg/m³ (Jarvi et al. 2008). The biggest BC was observed in the Indian and Chinese cities: around 5.5 and 8.8 pg/m³ in Dhanbad, the coal capital of India, and Guangzhou, the biggest megacity of South China (Singh et al. 2015) and (Wu et al. 2013), respectively.

Episodes of BC pollution can be identified by the increased ratio of eBC to PM10 (eBC/PM10). In 2017, the highest ratio more than 40% was observed from 27 April to 2 May, and around 9 and 13 May (Fig. 7). High temperature in the period of observations approaching a maximum at those days (Fig. 9) could relate to intensive biomass burning in the region around a city. Analyses of BWT arrived to the MO MSU during sampling period shows the highest number (48.9%) originating from North-West of the Moscow city. The remaining BWT arrived from North-East (28.1%), North - West (16.9%), and South - East (6.2%). Analyses of days of air mass transportation through fire areas demonstrates that the biggest number of open flaming fires occurred on 26 April, 1-5 May (Fig. 10). Figure 11 shows the BWT arrived on 29 April and 2 May from areas with most intensive agriculture fires in south of Russia and Western Europe. Relation of abnormal temperature and the biggest number of open fires to the highest eBC/PM10 at the days around 2 May confirms the reason of the BC pollution episode on urban background level. In the days of the biggest precipitations (07, 11, and 16 May) the low eBC/PM10 rations around 3-5 % were observed, relating to the washout effect.

In 2018, the level of pollution related to eBC/PM10 showed the periodically repeated increased values of eBC/ PM10, up to 10 % (Fig. 8). Analyses of BWT arrived to the MO MSU during sampling period shows the highest number (34%) originating from north-east of the Moscow city. The remaining BWT arrived from South - West and North - West (25%), and South - East (16%). The biggest number of open flaming fires occurred in the South-East direction from the Moscow area at the days 20, 24-25 April, and 1 May (Fig. 10). Figure 11 shows the BWT arrived on 25 April and 1 May from areas of most intensive agriculture fires in South of Russia and Western Europe. Such observations confirm that high atmospheric pollutions in Moscow are mainly caused by the transport of pollutions from the regions with intense emissions over a distance of hundred kilometers (Golitsyn et al. 2015).

CONCLUSIONS

Measurements performed at the Meteorological Observatory MSU improve the luck of the analysis for the aerosol pollution related with BC as the most important pollution contributor in total PM10 mass in the urban background of Moscow megacity. The highest level of BC pollution, up to 40%, was observed in the days of the May holiday in Russia, related with abnormal high temperature and intensive agriculture fires in the south of Russia and biomass burning around the city. Diurnal profile in the spring season is observed to be different from other large cities: we note stable high BC at night, the less pronounced morning peak in comparison with nocturne BC concentrations, and significant increase of mean diurnal BC late in the evening. As Moscow is an urban, industrialized and densely populated city, the diurnal variations in BC mass concentrations can mainly be attributed to the vehicular emissions and transport from the surrounding regions. Mean spring BC concentrations at urban background of Moscow megacity are observed similar to one in European cities and significantly lower than in industrialized Asian cities, in well relations with intensive transport and using of gas, diesel, and gasoline instead of coal in Asia.