Journal Archive

The highest concentrations of PM₁₀ over Cairo, based on MERRA-2, were recorded in January and February 2020 with values exceeding 160 μg m^-3 followed by levels that were recorded during March and December with approximately 140 μg m^-3 (Fig. 1a). On the other hand, the lowest concentrations were observed during the summer season (June to August) with values ranging from 60 to 95 μg m^-3, which are consistent with the results of Mostafa et al. (2018). The monthly distribution of PM_2.5 followed the same pattern as PM₁₀, the highest concentrations of PM_2.5 (40 μg m^-3) were recorded during winter (December to February), while the lowest concentrations were recorded during the summer of the same period with values lower than 40 μg m^-3 (Fig. 1a).

The increase in particulate concentrations during the winter months is attributed to the state of atmospheric stability and the temperature inversions that increase during the winter season (December, January, and February) in Cairo, especially during the night periods (Abou El-Magd and Zanaty, 2021; Mostafa et al., 2018). The other peaks in the Spring months (March, April, and May) are due to the frequent dust storms that occur in this season because of the Khamasin depressions, which are associated with strong hot and dry winds carrying with dust and sand that increase PM₁₀ and PM_2.5 concentrations over many regions in Egypt (Abou El-Magd et al. 2016; Incecik and Im, 2012).

Fig. 1b shows the monthly distributions of PM₁₀ and PM_2.5 over Tehran. The highest concentrations of PM₁₀ were observed from April to July (80-85 μg m^-3), while, the lower concentrations were observed in December and January with (30-40 μg m^-3). The monthly distribution of PM_2.5 has the same behavior as PM₁₀, where April-July had high levels (more than 25 μg m^-3), while, November to January had lower levels (14-20 μg m^-3). Yousefan et al. (2020) attributed the high concentrations of particulate matter recorded during May to July months to the dust storms that occur during these months which are responsible for the peak concentrations of PM during summer in Tehran. Recently, Ravindra et al. (2022) stated that the natural emission due to dust storms during the summers causes a significant increase the concentrations of particulate matter.

The highest concentrations of PM₁₀ and PM_2.5 over Beijing are close to each other during the seasons of the year (Fig. 1c). The highest PM₁₀ and PM_2.5 concentrations occur during the months of the summer and then fall with values ranging between 60-65 μg m^-3, and 53-58 μg m^-3, respectively. When temperatures and humidity rise, winds contribute to smog during the transport of pollutants from southern industrial areas in a warm temperate (Molina et al., 2004). Whereas, the lower concentrations of PM₁₀ levels were recorded during the winter months with a value of 50 μg m^-3, and The lower concentrations of PM_2.5 were recorded during January-April with concentrations ranging between 40-44 μg m^-3. These results are in agreement with the results recorded in China (Bauwens et al., 2020).

Reanalysis of MERRA-2 data showed that the highest concentrations of PM₁₀ over Delhi were recorded from May to July (150-200 μg m^-3) followed by levels that recorded during October to December (120-150 μg m^-3) (Fig. 1d). On the other hand, the lower concentrations were observed during February, March, and September (70-90 μg m^-3). The highest concentrations of PM_2.5 were recorded in November and December (106 μg m^-3 and 90 μg m^-3, respectively). On the other hand, the lower concentrations were observed to occur in the summer months around 50 μg m^-3 (Fig. 1d). The high levels of PM₁₀ and PM_2.5 during the summer months are because of the strong dust storms carrying large amounts of windblown dust from the desert and after this period of the dust storms the rainfall is accompanied by the monsoon season from July to September which reduces levels of PM_2.5 (Molina et al., 2004). However, in the winter season, the strong surface inversions and fog cases over Delhi decrease the ability of the atmosphere to dilute the high polluted emissions (Chhikara and Kumar, 2021).

Fig. 1e shows that the highest concentrations of PM₁₀ over Mumbai occurred during the summer (June and July) with concentrations of 135 and 145 μg m^-3, respectively. There was a drastic reduction, in August, where levels reached lower than 90 μg m^-3. Moreover, the lower concentrations were observed during winter (December and January) with an average of about 55 μg m^-3. The highest concentrations of PM_2.5 were recorded during November and December to more than 40 μg m^-3, while the lower concentrations were observed during in August (about 20 μg m^-3). The reduction of PM₁₀ and PM_2.5 in August could be due to the rainfall associated with the monsoon (Chhikara and Kumar, 2020; Gupta et al., 2020).

Fig. 1f shows that the highest concentrations of PM₁₀ over São Paulo, were observed during the months from August to October with values ranging between 17-22 μg m^-3, which are accompanied by the season of lower precipitation (Nakada and Urban, 2020). On the other hand, the lower concentrations were observed during April and May (about 10 μg m^-3). The highest PM_2.5 concentrations were happened during September (15 μg m^-3), while, the lower concentrations were observed during March-May (less than 10 μg m^-3).

Fig. 2a shows that the monthly average concentrations of PM₁₀ in January, February, and March 2020 were 109, 96 μg m^-3, and 160 μg m^-3, respectively. The increase in concentrations in March could be ascribed to the frequent dust events that occurred during that month. The monthly average concentration was decreased from April to June, with the lowest concentrations recorded in May 2020 (83.2 μg m^-3), when the full lockdown applied for some consecutive days. Similarly, the monthly mean of PM_2.5 (the red line) was increased in March 2020 to approximately 45 μg m^-3, and then decreased after that reaching 25.8 μg m^-3 in June by the end of the partial lockdown.

Table 2 shows that the monthly average of PM₁₀ during the period from the beginning of March to the end of June 2020 in Cairo was about 109 μg m^-3, which is lower than the concentrations recorded in 2019 and the past ten years by about 7% and 8%, respectively. The average PM_2.5 concentration was around 32 μg m^-3 during the same months, which is lower than the concentrations for 2019 and 2010-2019 by about 0.1% and 7%, respectively (Table 3). The reductions in the concentrations of PM₁₀ and PM_2.5 over Cairo compared to 2010-2019 are illustrated in Fig. 3a (the top and bottom panels, respectively).

The average concentrations of PM₁₀ over Tehran were 30 and 90 μg m^-3, and that of PM_2.5 was 10 μg m^-3 and 30 μg m^-3 in January April, respectively (Fig. 2b). The lockdown in Tehran was implemented from the beginning of January to the end of February 2020. Surprisingly, due to that time, there was a slight, but insignificant, increase (2.5%) in levels PM₁₀ compared to 2019, however, there was a slight reduction (4.5%) in the concentrations of PM_2.5 compared with the same period in 2019 (Tables 2 and 3). Moreover, the reductions in the levels PM₁₀ and PM_2.5 were 5% and 1%, respectively, when compared to the previous ten years (Fig. 3). Surprisingly, changes in PM concentrations in Tehran were substantially smaller than the other cities. These marginal variations in PM_2.5 and PM₁₀ during lockdown could be attributed to relaxation given to government offices to operate. Moreover, the lockdown was enforced for few weeks, only, in contrast to other cities which enforced the lockdown for months. Therefore, the difference was less remarkable in Tehran, than that observed in cities with the full lockdown (Lam et al., 2022).

Fig. 2c shows that the average concentrations of PM₁₀ and PM_2.5 over Beijing during January-June 2020. The concentrations of PM₁₀ were 58.69 μg m^-3, 50.73 μg m^-3, 45 μg m^-3 and 43 μg m^-3 and the concentrations of PM_2.5 were 48.2 μg m^-3, 42.1 μg m^-3, 34.29, and 35 μg m^-3 in January, February, March, and April, respectively.

The lockdown in Beijing was implemented from the beginning of February to the end of April 2020 (Tables 2 and 3). The average concentrations of PM₁₀ and PM_2.5 during these months are lower than the levels observed in 2019 by less than 2% (Table 3). Moreover, the concentrations observed in 2020 were lower than those recorded in the previous 10 years (2010-2019) by 15% and 12%, respectively (Fig. 3).

In 2020, the overall economic situation, and social and economic (e.g. transportation and industrial production) activities were fully suspended in Beijing to control the COVID-19 epidemic, leading to a rapid reduction in the emission of air pollutants from vehicle exhaust and industrial production. During the epidemic control period, the significant decrease in human activity, especially the sharp reduction in traffic emissions (more than a 70% reduction compared with the same period in former years), led to a reduction in primary emissions of particulate matter (Yin et al., 2021). On the other hand, pollutant discharge levels in the Beijing from 2013-2019 were higher than in 2020 (Guo et al., 2021). Air quality is mainly affected by air pollution emissions and meteorological conditions. China began to significantly promote actions by which to control air pollution since 2013 (Guo et al., 2021). With the implementation of the clean air policy in the Beijing, significant declines in the concentrations of PM_2.5 and PM₁₀ occurred from 2013 to 2019. This could explain why the change between 2020 and 2019 were substantially smaller than that between 2020 and 2010-2019 (Delgado-Bonal et al., 2020). Another explanation could be the increase in frequency of dusty weather where several dusty weather events occurred from between 2010-2019 exceeded the total of the same period in 2020 (Yin et al., 2021). Moreover, the Spring Festival was suspended in 2019 (to the implementation of the clean air policy in Beijing) and 2020 (due to the lockdown), while it was carried out in the previous years (i.e. 2020-2018). These results indicate the air quality during 2020 was obviously improved compared with the same period between 2010-2019.

The average concentrations of PM₁₀ were 76.42 μg m^-3 and 77.53 μg m^-3, while those of PM_2.5 were 52.5 μg m^-3, 56.85 μg m^-3 in January and February 2020, respectively (Fig. 2d). These concentrations were significantly reduced after enforcement of the lockdown during March and April; where the average concentrations of PM₁₀ were 72.09 μg m^-3 and 74.76 μg m^-3 in March and April 2020. Similarly, average concentrations of PM_2.5 were 37.09 μg m^-3, and 35.58 μg m^-3 in these two months, respectively (Fig. 2d).

As illustrated in Tables 2 and 3, the concentrations of PM₁₀ and PM_2.5 that were observed during the lockdown in 2020 were reduced by about 21% and 14%, respectively, compared to the concentrations recorded in the same period in 2019, and by about 27%, and 20%, respectively, compared to the average duration of the last ten years, respectively, as shown in Fig. 3.

Fig. 2e shows the average concentration of PM₁₀ over Mumbai during January and February were 53 μg m^-3 for both months, and during March and April (lockdown months) they were 77 μg m^-3 and 96 μg m^-3, respectively. The average concentration of PM_2.5 during January and February was around 38 μg m^-3 for both months, and were 32.5 μg m^-3 and 35.2 μg m^-3 in March and April, respectively.

Tables 2 and 3 illustrate that levels of PM₁₀ and PM_2.5 over Mumbai, during the lockdown (March-April 2020), were reduced by about 14% and 9%, respectively when compared with the concentrations recorded in the same period in the previous year (2019), and by about 11% and 10% as compared to the average concentrations recorded during the same period in the previous ten years (2020-2019), respectively (Fig. 3).

The average concentrations of PM₁₀ over São Paulo were 20.64 and 17.04 μg m^-3 during January and February, respectively. However, during the lockdown period (March and April 2020), its concentration was 13 μg m^-3 (Table 2).

Table 3 shows that the average concentrations of PM_2.5 during January, February, March and April were 11 μg m^-3, 9 μg m^-3, 7 μg m^-3 and 8 μg m^-3, respectively. The lowest concentrations of PM₁₀ and PM_2.5 were recorded in March 2020 when the full lockdown was enforced. Moreover, these concentrations were lower than those recorded in 2019 and 2010-2019 (Tables 2 and 3). There were reductions in The concentrations of PM₁₀ and PM_2.5 were reduced by about 15% and 9%, when compared with the same period in 2019, and by 18% and 14%, as compared to the average duration of the previous ten years (2010-2019), respectively (Fig. 3).

Table 4 shows the comparison between PM₁₀ observations at two location: the Egyptian Meteorological Authority in Cairo (Egypt) and Sherif University in Tehran (Iran) with the values extracted from MERRA-2 at the same locations during the period of 2012-2014.

The statistical analysis of the measurements of PM₁₀ concentration with the values extracted from MERRA-2 during 2012-2014 shows that the root mean square error (RMSE) was 122 and 69 μg m^-3 for Cairo and Tehran, respectively, indicative of the reliability of the retrieved results. Also, there was a high correlation between MERRA-2 and PM₁₀ measurements at Cairo 0.82 with a mean bias of -3.1 μg m^-3, and the absolute percentage error of -5.6%, showing the applicability of the MERA-2 The results of Tehran were near to those of Cairo since the correlation is about 0.6 and the mean bias is -4.9 μg m^-3.

Fig. 4 shows the scatter plots and linear regressions between each reanalysis datasets obtained from MERRA-2 versus ground-based observations of PM₁₀ and PM_2.5 for Cairo during 2018-2020. The results showed significant spatial agreement between MERRA-2 and ground-based observations (R²=069 and 0.86 for PM₁₀ and PM_2.5, respectively, P<0.05). These results confirm the results of Table 3, and could depict that there is an agreement between MERRA-2 and ground-based observations on the global scale with a reasonable degree of accuracy (Lam et al., 2022; Navinya et al., 2020).

Fig. 4. 
Regression analysis between MERRA-2 dataset and surface observation of PM₁₀ (Top panel) and PM_2.5 (lower panel). The small squares indicate the monthly mean of PM (2018-2020). The solid line is the line of best fit.

Generally, Spatiotemporal analysis of the variations in the levels of criteria air pollutants revealed that there was a significant decline in the concentration of PM₁₀ and PM_2.5 in the megacities under examination. However, the magnitude of the decline in air pollutant concentrations is different in all the megacities and this is in agreement with the results of Jain and Sharma (2020). However, when compared with the WHO standards (for PM_2.5= 25 μg m^-3, PM₁₀=50 μg m^-3 based on a 24-hours average), Tehran and São Paulo are within the permissible limits for PM_2.5; whereas all the megacities violate WHO standards. Similarly, when compared in terms of PM₁₀ levels, Cairo violates WHO standards, while other megacities are within the permissible limits.

In summary, during and after the COVID-19 pandemic, there should be a concern for environmental protection and preservation. There could be an increased population movement for environmental actions such as clean air and water (Ravindra et al., 2022). Furthermore, Hassan et al. (2022) also linked COVID-19 pandemic with positive impact (clean beaches) and negative aspects (e.g. increase in household waste, reduced recycling).