Front. Environ. Sci. Frontiers in Environmental Science Front. Environ. Sci. 2296-665X Frontiers Media S.A. 784959 10.3389/fenvs.2021.784959 Environmental Science Brief Research Report A Comparative Study of Particulate Matter Between New Delhi, India and Riyadh, Saudi Arabia During the COVID-19 Lockdown Period Singh et al. Particulate Matter During COVID-19 Lockdown Singh Bhupendra Pratap 1 * Eldesoky Gaber E. 2 Kumar Pramod 3 Chandra Prakash 4 Islam Md Ataul 5 Rahman Shakilur 6 1 Department of Environmental Studies, Deshbandhu College, University of Delhi, New Delhi, India 2 Chemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia 3 Department of Chemistry, Sri Aurobindo College, University of Delhi, New Delhi, India 4 Department of Biotechnology, Delhi Technological University, New Delhi, India 5 Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, United Kingdom 6 Department of Medical Elementology and Toxicology, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi

Edited by: Suvarna Sanjeev Fadnavis, Indian Institute of Tropical Meteorology (IITM), India

Reviewed by: J. Abbas, Shanghai Jiao Tong University, China

Rohini Bhawar, Savitribai Phule Pune University, India

 *Correspondence: Bhupendra Pratap Singh, bpsingh0783@gmail.com; 0000-0002-0513-9082

This article was submitted to Atmosphere and Climate, a section of the journal Frontiers in Environmental Science

 14 01 2022 2021 9 784959 28 09 2021 27 12 2021 Copyright © 2022 Singh, Eldesoky, Kumar, Chandra, Islam and Rahman. 2022 Singh, Eldesoky, Kumar, Chandra, Islam and Rahman

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Novel Coronavirus disease (COVID-19), after being identified in late December 2019 in Wuhan city of China, spread very fast and has affected all the countries in the world. The impact of lockdowns on particulate matter during the lockdown period needs attention to explore the correlation between anthropogenic and natural emissions. The current study has demonstrated the changes in fine particulate matter PM2.5, PM10 and their effect on air quality during the lockdown. The air quality before the lockdown was low in New Delhi (India) and Riyadh (Saudi Arabia), among major cities worldwide. The air quality of India is influenced by dust and sand from the desert and surrounding areas. Thus, the current study becomes important to analyse changes in the air quality of the Indian sub-continent as impacted by dust storms from long distances. The result indicated a significant reduction of PM2.5 and PM10 from 93.24 to 37.89 μg/m3 and from 176.55 to 98.87 μg/m3 during the lockdown period as compared to pre lockdown period, respectively. The study shows that average concentrations of PM10 and PM2.5 have declined by -44% and -59% during the lockdown period in Delhi. The average value of median PM10 was calculated at 33.71 μg/m3 for Riyadh, which was lower than that value for New Delhi during the same period. The values of PM10 were different for pre and during the lockdown periods in Riyadh, indicating the considerable influence on air quality, especially the concentration of PM10, from both the natural (sand and dust storms) and the anthropogenic sources during the lockdown periods. However, relatively smaller gains in the improvement of air quality in Riyadh were correlated to the imposition of milder lockdown and the predominance of natural factors over the anthropogenic factors there. The Air Quality Index (AQI) data for Delhi showed the air quality to be ‘satisfactory’ and in the green category during the lockdown period. This study attempts to better understand the impact of particulate matter on the short- and long-term air quality in Delhi during the lockdown. This study has the scope of being scaled up nationwide, and this might be helpful in formulation air pollution reduction and sustainable management policies in the future.

 COVID-19 air quality particulate matter New Delhi Riyadh Introduction

The COVID-19 originated from the city of Wuhan in China, supposedly in December 2019after the detection of the first COVID-19 positive case (Bashir et al., 2020; Chen et al., 2020). COVID-19 has become a pandemic impacting the entire population. Corona Virus causes respiratory infection in people and is known as SARS-CoV-2 (Zheng, 2020). The World Health Organisation (WHO) declared the Corona Virus outbreak a pandemic on March 11, 2020 (World Health Organisation, 2020).

Several studies have confirmed high transmissivity of the Corona Virus, which affects many people within a short period (Gautam and Trivedi, 2020; Sharma et al., 2020). As of October 04, 2021, more than 248 million people have been affected, and more than five million people have died across countries (including India) because of the COVID-19 virus (World metros, 2021; Ritchie et al., 2020). The effects of the COVID-19 pandemic went far beyond just health to economic, social, psychological, and occupational (Abbas et al., 2019; Mubeen et al., 2020; Liu et al., 2021a; Abbasi et al., 2021; Paulson et al., 2021; Wang et al., 2021). The pandemic has impacted the mental well-being of a huge proportion of the population in the form of distress, stress, and depression, as revealed by several studies (Abbas et al., 2019; Aqeel et al., 2021; Lebni et al., 2021; Local Burden of Disease, 2021). Su et al. (2021b) reported that COVID-19 induced unprecedented illness perception has caused mental disorders, including anxiety and depression, which have severely impacted individuals’ mental health. Furthermore, a study reported the relationship between the COVID-19 infection and vaccine non-adopters in terms of detection of the number of new corona cases (Su et al., 2020). Several research scholars claimed that reduced stress and depression lead to better mental health (Li et al., 2021). Better social and educational support to vulnerable individuals might help explain differences in the scale of observed mental health problems across countries. (Azadi et al., 2021; Abbas., 2021; Su et al., 2021a; Azizi et al., 2021; Abbas et al., 2019).

India ranked third after the USA and Brazil among the top countries with more than 12 million cases and more than 0.16 million deaths (Ritchie et al., 2020; world metros, 2021). In India, the Ministry of Health and Family Welfare reported the first COVID-19 case in Kerala on 30th January, 2020 (Gutam and Hens, 2020), and the first death was reported on 12th March, 2020 (World Health Organisation, 2020b). On 22nd March, 2020, the Central Government imposed an emergency “Janata Curfew” in the whole country, which was intensified by a city-scale quarantine and nationwide lockdown starting from March 24, 2020 (Khetan et al., 2020).

Since then, more restrictive measures have been introduced except for essential services, such as fire, police, and health. Then industrial activities, hospital services, and educational institutions were also suspended until further notice. The government took these steps to flatten the infection curve. Since the lockdown meant the least movement and transportation and a considerable reduction in construction activities, the air quality improved quite significantly. Similar socio-economic activity restrictions were also seen in other countries in response to the pandemic (Kerimray et al., 2020). A drop in air pollutants has been recorded because of these initiatives (Dutheil et al., 2020).

India is considered one of the most severely polluted countries globally, especially for particulate matter and dust particles. The air quality in India is impacted by meteorological parameters such as winds which bring a huge quantity of dust and sand from the desert and surrounding areas (Knippertz et al., 2007; Pye, 2015; Albugami et al., 2019). Many studies have reported variations in aerosol loading (dust particle in the atmosphere), surface cooling, and their possible relationships with meteorological factors such as rainfall, wind speed in India and East Asia (Krishnan and Ramanathan, 2002; Devara et al., 2003; Cheng et al., 2005; Prasad et al., 2006; Nakajima, 2007; George et al., 2008). The air quality of the Indian subcontinent, including the north-western part of India, is possibly influenced by the dust storms which may originate from Arabian Peninsula.

This study tried to correlate the possible changes in the air quality of Delhi with the dust storms from Arabian Peninsula (Saudi Arabia). Dust storms are common in the north-western part of the Indian subcontinent, the Arabian Peninsula, China, and the Sahara Desert (Wang, 2015). The transport of dust particles originated from the Arabian Peninsula and enter India through Afghanistan, Pakistan via land routes and through the Arabian Sea via sea routes (Middleton, 1986; Kedia et al., 2018). In addition, dust storms can severely affect air quality and particulate matter concentrations (PM2.5 and PM10). A study suggested a significant positive correlation between precipitation and the increase of dust emissions, especially in Saudi Arabia, Oman, and the Thar Desert, India (Kaskaoutis et al., 2012; Namdari et al., 2018).

Several literatures reported that the frequency and the intensity of dust storms have been increasing, which is positively associated with land-use and land-cover changes and meteorological factors in some regions of the world like the Arabian Peninsula (Yu et al., 2015; Alobaidi et al., 2017; Gherboudj et al., 2017; Almazroui et al., 2018), and the Middle-East (Rashki et al., 2012; Türkeş, 2017; Namdari et al., 2018) as well as Central Asia (Indoitu et al., 2015; Xi and Sokolik 2015). Furthermore, a positive correlation between dust and meteorological factors is attributed to dust emission over Arabian Peninsula and its transportation to the Indian subcontinent (Jin et al., 2021). In addition, the Indian subcontinent, especially northern parts of India, is a potential source of pollution originating from the Thar desert located in northwestern India (Sarkar et al., 2019; Jin et al., 2021).

A sudden halt of all anthropogenic activities (mainly transportation and industrial activities) during the lockdown measures in India improved the air quality. Several studies conducted throughout the world reported an association between short term exposure to particulate matter and COVID-19 confirmed cases such as an outbreak in over major cities of Saudi Arabia (Farahat et al., 2021) Northern Italy (Bashir et al., 2020; Report et al., 2020), China (Mehmood et al., 2020; Wang et al., 2020a; Zhu et al., 2020), in Malaysia (Suhaimi et al., 2020) and a similar result for the United States (Wu et al., 2020).

Several studies have reported a significant improvement in air quality during the lockdown period (Gautam, 2020; Zhu et al., 2020) especially, Particulate Matter PM2.5 (size <2.5 µm3) and PM10 (size <10 μm3), which are considered significant air pollutants directly associated with adverse health effects on human beings (Kumar et al., 2014a; Singh et al., 2014; Singh et al., 2021a). A study in China reported a positive association between short-term exposure to air pollution and coronavirus disease (Muhammad et al., 2020; Zhu et al., 2020). Another study in China also suggested a positive correlation between particulate matter (PM2.5 and PM10) and mortality rates of COVID-19 (Bashir et al., 2020). Another study from China has also shown that ambient temperature might play a crucial role in COVID-19 infection (Xie and Zhu, 2020). Several recent studies have highlighted a significant improvement in air quality with respect to reduction of PM2.5 by 34–73.85%, of PM10 by 40–58%, (), of NO2 by 3–79%, of CO by 2–60%, of NH3 by 30–75%, (), and of SO2 by 15–58% () in different cities across India during the lockdown period (Dutta & Jinsart, 2020; Kumari and Toshniwal, 2020; Navinya et al., 2020; Pant et al., 2020; Resmi et al., 2020; Vadrevu et al., 2020; Kumar et al., 2020; Kumar & Tyagi, 2021; Khan et al., 2021; Maji et al., 2021; Sathe et al., 2021).

Several studies have been conducted in different parts of cities to assess the impact of COVID-19 lockdown on air quality but for a short period of time (Kotnala et al., 2020 (January–March 2020); Kumar, 2020 (March–May 2020); Kumar et al., 2020 (March–April 2015–2020); Mahato et al., 2002 (3 March–14 April 2020); Navinya et al., 2020 (1 February–3 May 2019–2020); Srivastava et al., 2020 (1st–20th February and 24 March–14 April 2020). The present investigation was an attempt to evaluate the changes in the level of the particulate matter before and during the complete lockdown period (1 January–31th May 2020)

Northwest Indian sub-continent faces the adverse impacts of dulust particles, including particulate matter from distant places like Saudi Arabia and meteorological parameters such as wind and precipitation. Both of these factors played a crucial role in the deterioration of the air quality in India. Therefore, the present investigation attempted to evaluate the changes in the level of the particulate matter before (January 1, 2020 to 23rd March, 2020) and during the entire lockdown period (24th March, 2020 to May 31, 2020) in Delhi India. Hence, the present study also aims to evaluate the levels of particulate matter in two different cities (New Delhi and Riyadh) during the lockdown period (1st January to May 31, 2020). Further, the study compared the concentration of particulate matter for pre-lockdown and during the lockdown periods and explored the potential natural and anthropogenic emission sources.

Further, the study aims to increase the scientific rigor of research in this area. However, some of the limitations of the current manuscript required access to meteorological parameters, including rainfall, relative humidity, solar radiation, and wind speed. These limitations can be tackled in future studies with larger sample sizes and the inclusion of more factors in the analysis to draw exciting results.

 Materials and Methods

To investigate the effect of restricted mobility on the concentration levels of particulate matter in the ambient atmosphere of Delhi (India) and Riyadh (Saudi Arabia), we utilized the air quality index (AQI) data from the respective Air Quality Monitoring Stations. The pandemic situation was classified into two periods, before lockdown and during lockdown for both the cities (Delhi and Riyadh). The time for Delhi, India before lockdown (between 1st January, 2020, and 24th March, 2020) was termed as ‘pre-lockdown’ period, and the time between 25th March and May 31, 2020 was termed as ‘during-lockdown’ period. The time for Riyadh, Saudi Arabia before lockdown (between January 2020, and March 2020) was termed as “pre-lockdown” period, and the time between March and May 2020 was termed as ‘during-lockdown’ period. So, in the current study authors have studied and compared the air quality in both these cities in a comparable time frame.

Data and Sources

The hourly and daily data on air pollutants were obtained from the online portal of the Central Pollution Control Board (CPCB), particularly the data for PM10 (size of particulate matter <10 microns), PM2.5 (size of particulate matter <2.5 microns), and meteorological parameters. In this paper, we focused and collected secondary data for only PM10 and PM2.5 from 1st January, to 31st May, 2020 to determine the relative changes (in %) in air quality from the CPCB monitoring site (https://app.cpcbccr.com/ccr/#/caaqm-dashboard-all/caaqm-landing). In addition, the data on PM10 for Riyadh, Saudi Arabiawere procured from the World Air Quality Index from 1st January to April 10, 2020 (https://aqicn.org/data-platform/covid19/). CPCB in India provides high-quality data through rigorous quality assurance or quality control (QA/QC) programs via scientific sampling, analysis, and calibration (Mahato et al., 2002).

Air Quality Index (AQI) is a tool for identifying the pollutant criteria and is also used to report the severity of air pollution to the public. In addition, AQI plays an important role in deliberating an individual pollutant into a whole index using the aggregation method (Ott, 1978).

AQI India provides air pollution data with a real-time Air Quality Index for various air pollutants. The National Ambient Air Quality Standard (NAAQS) revised AQI by considering eight parameters, namely, PM10, PM2.5, NO2, SO2, CO, O3, NH3, and Pb for a short term (up to 24 hourly average) period (Kumar et al., 2014b; CPCB, 2016). An AQI is used to provide information about the quality of air in terms of pollution level. It is directly associated with public health. The public health risk increases with an increase in the AQI level. Six AQI categories have been defined for health risk, namely, “Good”, “Satisfactory”, “Moderately polluted”, “Poor”, “Very Poor”, and “Severe”.

Further, this index provides information to the public who are sensitive to air pollution (Beig et al., 2010). To identify the overall improvement in air quality over Delhi, AQI was calculated, and details of AQI are available elsewhere (Sharma et al., 2020). The AQI is divided into five categories: good (0–50), satisfactory (51–100), moderate (101–200), poor (201–300), very poor (301–400), and severe (401–500) respectively. AQI method that provides sub-index approach using six criteria pollutants (i.e. PM10, PM2.5, SO2, NO2 CO and O3) were converted into AQI standard value. The AQI for each pollutant was calculated by the following formula given by Sahu & Kota (2017). A Q I i = IHI − ILO BreakHI − BreakLO   x   ( Ci − BreakLO ) + ILO where C i is the observed concentration of the pollutant “i”; BreakHI and BreakLO are breakpoint concentrations, greater and smaller to C i; and I HI and I LO are corresponding AQI ranges.

For the final calculation of AQI for individual pollutants, at least a minimum of three pollutants for the AQI value is required. In this study, we have also considered the daily average values of other pollutants (NOX and O3) to calculate AQI values. The formula for calculating the AQI value was presented in the Supplementary File. The AQI values for particulate matter (PM2.5 and PM10) before and during lockdown were calculated corresponding to the other pollutants.

 Data Analysis and Procedure

The present study analyzed the total data (n = 152 and n = 90) for a monitoring station, North Campus, Delhi University, New Delhi, and Riyadh, Saudi Arabia, to evaluate the variable changes in particulate matter in the comparative time frame. Time series plotting techniques were used to investigate variable changes over time during the pre and lockdown period. Statistical Package for the Social Sciences (SPSS) software was used to perform the statistical analysis (version 26.0 SPSS Inc., Chicago, IL, United States). The wind rose plot was drawn using Lake Environment software with wind speed input parameters.

 Results and Discussion PM<sub>2.5</sub> and PM<sub>10</sub> Levels in New Delhi, India

In the present paper, particulate matter (PM2.5 and PM10) levels have shown a significant decline from January to May 2020 during the pandemic situation (Figure 1). According to Singh & Kumar (2021) the continuous reduction in the levels of particulate matter (PM2.5 and PM10) was observed in subsequent months during the complete lockdown caused by the restriction of non-essential services such as transport and complete closure of markets and industrial activities. Average concentrations of PM2.5 and PM10 were 123.24 µgm-3 and 151.24 µgm-3, respectively, in North Campus, Delhi University. The maximum concentrations of PM2.5 and PM10 were 178.2 µgm−3 and 335.43 µgm−3 respectively during the month of February, whereas the minimum were 12.36 µgm−3 and 23.06 µgm−3 during the month of May. In addition, the lowest mean concentrations were 31.42 µgm−3 and 100.16 µgm−3, respectively, during the month of April (Supplementary Figure S1). Thus, the concentration of PM2.5 was observed far below the prescribed standard value of CPCB (40 µgm−3) in the month of April. The significant reduction in PM2.5/10 was caused by restrictions on the use of private vehicles and other non-essential transportation, halt on construction and industrial activities. This led to a general reduction of anthropogenic PM pollution (Klimont et al., 2017). The linear decline in the average concentration of PM2.5 was reported even in New York (µgm−3) from December 2019 to March 2020 (Chauhan and Singh 2020). Singh et al. (2021b) claimed that the mean concentrations of PM2.5 and PM10 were slightly higher during the month of May owing to the start of use of necessary transportation and controlled industrial activities in non-containment zones in Delhi. (Supplementary figure S2).

The box plot for concentration of PM2.5 and PM10 during the pandemic, North Campus Delhi University.

The present study focused on determining drastic changes in the concentrations of air pollutants, especially particulate matter PM2.5 and PM10 concentrations, during the pandemic situation in India, including Delhi. The PM2.5 and PM10 concentrations significantly declined from January 2020 to May 2020 during the pandemic situation in Delhi. A constant decline in the PM2.5 and PM10 concentrations was observed in subsequent months due to complete lockdown, during which international and trains, traffic activities, markets, and industrial activities were suspended. The average concentrations of PM2.5 and PM10 in the pre-lockdown period were observed to be 93.24 µgm−3 and 176.55 µgm−3, whereas, during the lockdown period, they were 36.09 µgm−3 and 98.87 µgm−3, respectively (Figure 2). Several recent studies on Delhi reported similar results for PM2.5 concentration values; Singh et al., 2021 (41.41 µgm-3), Dutta and Jinsart, 2020 (42.15 µgm-3), Chaudhary et al., (33.09–122.2 µgm-3), Roy and Balling (46.5–39.1 µgm-3). This significant reduction was mainly attributable to government’s orders on non-use of private vehicles and other non-essential transportation since transport sector is the primary source of particulate matter in the atmosphere.

The box plot for concentration of PM2.5 and PM10 during pre- and during the lockdown period, North Campus Delhi University.

The maximum value of PM2.5 and PM10 in the pre-lockdown period was calculated to be 215.5 µgm−3 and 369.94 µgm−3 whereas, during the lockdown period, it was estimated to be 88.5 µgm−3 and 93.24 µgm−3 respectively during the month of April. In terms of minimum concentrations of PM2.5 and PM10, pre-lockdown values were recorded to be 17.84 µgm−3 and 43.82 µgm−3 respectively during the month of March; whereas, during the lockdown period, these respective values were 12.36 µgm−3 and 23.03 µgm−3 during the month of April (Supplementary Figure S3). The present study shows that average concentrations of PM2.5 and PM10 declined by -59% and -44%, respectively, during the lockdown period in Delhi.

According to Kerimra, spatial reduction in the value of PM2.5 varied between 6 and 34% during the lockdown period in Almaty, Kazakhstan (Kerimray et al., 2020). A study conducted in Zaragoza, Spain, also reported a decline in the concentration of PM2.5 by -58% during March 2020 compared with February 2020. Similar changes were also observed in Beijing and other cities of China during the lockdown period (Sharma et al., 2020). Another study found a reduction in the concentration of PM10 in urban areas and traffic areas by -27.8% and -31%, respectively, in Barcelona (Spain) during their lockdown periods (Tobias et al., 2020). Thus, the significant reduction in the concentration of PM2.5 and PM10 during the lockdown period could also be attributed to a lower frequency of temperature inversion, atmospheric temperature, increasing wind speeds, and changes in wind direction.

 Role of Meteorological Parameters

The meteorological parameters such as temperature, mixing height, wind speed, and rainfall played a significant role in changing PM2.5 and PM10 levels during the lockdown period. PM2.5 and PM10 levels were observed to rise in the second week of phase-I of lockdown, primarily attributed to changes in meteorological conditions over Delhi and NCR.

Due to the onset of summers, the temperature started to increase with an average temperature of 20.9 °C on March 16, 2020 to 30.4 ºC on 1st May 2020, leading to dry and dusty conditions. Moreover, it was reported that a mild dust storm from the western part of the country and even from the gulf regions hit Delhi on 14th–15th April 2020, thus rapidly increasing the PM10 levels in Delhi and NCR. It is important to mention here that meteorological factors with average mixing height and wind speed improved the level of PM2.5 and PM10 for pre-lockdown and lockdown phases against the same periods in the previous year. Wind speed and mixing height were also higher in the first lockdown phase than pre-lockdown levels. Spells of light to moderate rains were also recorded in Delhi NCR on 5th March, 14th March, 27th March, 28th—29th March, 17th, and 18th April, 25th and 26th April, and 3rd May during 2020, assisting in air quality improvement (CPCB, 2020).

The salient findings from several recent studies worldwide, including India and Saudi Arabia, during the lockdown period are presented in Table 1. A negative correlation between concentrations of PM2.5, PM10, and ambient temperature was reported during the lockdown period, which indicated vertical dispersion of PM pollutants caused by high temperature (Singh et al., 2016; Singh et al., 2021c). The present study revealed a significant negative correlation between wind speed and particulate matter pollutants which possibly indicated the predominance of local sources as well as transportation of dust particles from longer distances over Delhi during the pre-lockdown period (Supplementary Table S1). The wind rose for Delhi during the lockdown period was depicted in the Figure 3. The wind rose blow from north-east much of the time during the lockdown period. This westerly wind and rainfall along the Mediterranean Sea could play a possible role in washing out the particulate matter during March, which led to further decline of the PM pollutant from the ambient atmosphere (Singh & Kumar, 2021).

Several recent studies across the world during the lockdown period.

The study area (city, country) Key findings for PM2.5 and PM10 Author (year)
Present Study (Delhi, India) Average concentrations for PM2.5 and PM10 during the lockdown period were observed to be 36.09 μg/m3 and 98.87 μg/m3, respectively Present Study
Delhi (India) Average concentrations for PM2.5 and PM10 were varied from 41.14 to 60.56 μg/m3 and 86.81–169.32 μg/m3 for different lockdowns in Delhi, India, respectively. Singh & Kumar (2021)
Delhi (India) Reductions in PM2.5 (39%) and PM10 (60%) as compared to 2019. Mahato et al. (2002)
Delhi (India) A similar study conducted in Delhi, the result showed that PM2.5 and PM10 levels declined up to 55–65% during the lockdown period Garg et al. (2021)
Delhi (India) The average concentrations of atmospheric air pollutants PM2.5 and PM10 were reduced to 42.15 μg/m3, and 128.68 μg/m3 and where 73.85%, and 46.48% lower than pre-COVID-19 levels. Dutta & Jinsart (2020)
Chennai (India) overall PM2.5 values decreased for the lockdown (ranging from ∼32–187%), weekly analysis shows the variation in reduction/increase. Singh and Tyagi (2020)
Uttar Pradesh (India) A significant reduction in the ground-level pollution load of PM2.5 and PM10 has been observed during the lockdown period in Uttar Pradesh. Kumar (2021)
Uttar Pradesh and the Delhi-National Capital Region (India) The PM2.5 concentrations during lockdown Phase 1 were approximately 44.6% lower for cities in Uttar Pradesh and about 58.5% lower for the Delhi-NCR Goel et al. (2020)
Delhi, Mumbai, Kolkata, Chennai, and Hyderabad (India) The average concentration levels of PM2.5 and PM10 have decreased nationwide by 33%, and 34% respectively during the nationwide lockdown compared to their concentration levels before the lockdown. Verma and Kamyotra (2021)
Delhi, Mumbai, Kolkata, and Bangalore (India) Concentration declined in PM2.5 (∼41%) and PM10 (52%). Jain & Sharma, (2020)
Delhi, Mumbai, Kolkata, and Chennai (India) The findings conclude a significant improvement in air quality with respect to a reduction of 49–73%, 17–63%, in the mean concentration of PM2.5 and PM10, respectively. Pant et al. (2020)
India (22 different cites) Reduction in concentration for PM2.5 (43%) and PM10 (31%) Sharma et al. (2020)
Dwarka river basin within Jharkhand and West Bengal (India) PM10 concentration was reduced from 189-278 μg/m3in the pre-lockdown period to 50–60 μg/m3. Mandal & Pal (2020)
Lucknow, and New Delhi, (India) PM2.5 concentration for Lucknow and New Delhi declined from 54–222 and 47–204 μg/m3 during the lockdown period (25th March to 14 April, respectively. Srivastava et al. (2020)
Gujarat (India) The concentrations of PM2.5 and PM10 were reduced by 38–78%, and 32–80%, in Gujarat respectively. Selvam et al. (2020)
Mecca, Madinah, and Jeddah (Saudi Arabia) No major changes in PM10 were observed, whereas other findings were 44% reduction in NO2 and 16% reduction in CO concentrations during COVID-19 restrictions. Farahat et al. (2020)
Makkha city (Saudi Arabia) Findings indicate the presence of a significant decrease of concentration rates during the lockdown period, compared with the pre-pandemic period, by 26.34% for SO2, 28.99% for NO2, 26.24% for CO, 11.62% for O3, and 30.03% for PM10. Morsy et al. (2020)
Riyadh, Makkha, and Jeddah (Saudi Arabia) The percentage changes in concentrations of CO (33.60%) and SO2 (44.16%) were higher in Jeddah; PM10 (91.12%) in Riyadh, while NO2 (44.35%) and O3 (18.98%) were highest in Makkah Aljahdali et al. (2021)
Eastern Province (Saudi Arabia) The Eastern Province, Saudi Arabia experienced significant concentration reductions at varying rates for PM10 (21–70%), CO (5.8–55%), and SO2 (8.7–30%), while O3 concentrations showed increasing rates ranging between 6.3 and 45%. Anil & Alagha (2020)
Riyadh (Saudi Arabia) After sandstorm, the air pollutants, CO level increased by 84.25%; PM2.5: 76.71%; O3: 40.41%; NO2: 12.03%; and SARS-CoV-2 cases increased by 33.87%. However, the number of deaths decreased by 22.39%. (Meo, 2021)
Global countries (34 countries including Saudi Arabia) On a global average basis, a 34.0% reduction in NO2 concentration and a 15.0% reduction in PM2.5 were estimated during the strict lockdown period (until April 30, 2020). Global average O3 concentration increased by 86.0% during this same period. Torkmahalleh et al. (2020)
Cairo, Egypt and Riyadh (Saudi Arabia) The results demonstrated that the lockdown was associated with a reduction in NO2 by 40.3 and 23% in Riyadh and Cairo, respectively. Abdelsattar et al. (2021)
China and Europe (France, Germany, Spain, and Italy) Decreased PM2.5 in 367 cities (18.9 μg/m3), and Wuhan (-1.4 μg/m3) Zambrano-Monserrate et al. (2020)
New York, Los Angeles, Zaragoza, Rome, Dubai, Delhi, Mumbai, Beijing, and Shanghai Declined PM2.5 concentration in Delhi (35%), Mumbai (14%), Beijing (50%), Shanghai (50%), Dubai (11%), New York (32%), Los Angeles (4%), and Zaragoza and Rome (no changes). Chauhan & Singh (2020)
Spain (Barcelona) Decline PM10 concentration in Spain from -28% to -31%. Tobias et al. (2020)
Malaysia and Southeast Asia Reduced concentration in PM10 for (industrial: 28–39%, urban: 26–31%), and PM2.5 (industrial: 20–42%, urban: 23–32%) respectively. Kanniah et al. (2020)
Southern European cities (Nice, Rome, Valencia and Turin) and Wuhan (China) Declined in PM2.5 and PM10 (∼8% in Europe and ∼42% in Wuhan) at urban stations, respectively. Sicard et al. (2020)
Yangtze River Delta Region (China) Reductions in PM2.5 (27–46%) in China. Li et al. (2020)
44 cities in northern China The AQI for PM2.5, and PM10, decreased by 6.76%, and 5.93%, respectively. Bao & Zhang, (2020)
Almaty (Kazakhstan) Reduction in PM2.5 (21%, spatial variations: 6–34%). Kerimray et al. (2020)
Northern China Reduction in PM2.5 (29 ± 22%), and (31 ± 6%) in Northern China and Wuhan respectively. Shi & Brasseur (2020)
Sale City (Morocco) PM10 was reduced by 75% in Sale City. Otmani et al. (2020)
China (Beijing, Shanghai, Guangzhou, and Wuhan) Decreased PM2.5 in Beijing, Shanghai, Guangzhou, and Wuhan by 9.23, 6.37, 5.35, and 30.79 μg/m3, respectively. Wang et al. (2020b)

Wind rose diagram for Delhi monitoring station.

 PM<sub>10</sub> Levels in Riyad, Saudi Arabia

The maximum and minimum median values in Riyadh were 245 µgm−3, and 6.0 µgm−3, respectively, during the same period. The average median of PM10 during the lockdown period was 33.71 µgm−3. A similar result for Riyadh was reported (24.10 ± 4.78 µgm−3) during the lockdown period by Aljahdali et al., 2021. The value of PM10 was observed much lower than the standard value (80 µgm−3 annual means) by prescribed Presidency of Meteorology and Environment (PME) (Munir et al., 2016).

The present study finds no major changes in particulate matter pre- and post-lockdown periods in Riyad, Saudi Arabia, which could be due to frequent dust events during the same period. Farahat also suggested similar findings over major cities (Mecca, Jeddah, Madinah) of Saudi Arabia during the Hajj Period of 2019–2020, where the winds played a crucial role in the transportation of dust (Farahat et al., 2021). Another study conducted in the Eastern Province of Saudi Arabia experienced a significant reduction in the concentration of PM10 (21–70%) during the lockdown period (Anil & Alagha, 2020). Morsy indicated a considerable decrease in concentration levels during the lockdown period, compared with the pre-pandemic period, by 30.3% for PM10 in Makkah city, Saudi Arabia (Morsy et al., 2021). The flatted peak of PM10 during the pandemic lockdown period was interpreted by the commitment of Makkah residents due to precautionary measures of COVID-19.

Furthermore, preventive measures such as curfew enforcement had contributed to lowering the level of particulate matter to a great extent in the capital of Riyadh. The complete lockdown and restricted industrial activities and vehicular movement resulted in a significant reduction in air pollutants, as recorded by some air quality monitoring stations located throughout the city (Saudi Gazette, 2020). A comparative graph between New Delhi (India) and Riyadh (Saudi Arabia) for particulate matter has been presented in Figure 4 during the pandemic lockdown periods.

Comparative study of PM10 for Riyadh and New Delhi during the pandemic periods.

 Air Quality Index

Delhi is considered as one of the most polluted cities on the Earth, with transport (41%), industry (18.61%), power plants (4.92%), and residential emissions (2.96%) being the major contributing factors. The levels of PM2.5 and PM10 in Delhi drastically declined during the pandemic. The AQI data for the present study shows that the mean concentrations of PM2.5 and PM10 in the pre-lockdown period were 93.24 µgm-3 (indicating ‘poor’ air quality) 176.55 μgm−3 (indicating “moderately polluted” air quality) respectively. The average values of PM2.5 and PM10 during the lockdown period were found to be 37.89 μgm−3 and 98.87 μgm−3 respectively, indicating a “satisfactory” green category of air quality equivalent to a few of the European cities during the lockdown period (Table 2). The drastic change in Delhi’s air quality could be attributed to a decrease in socio-economic activities in the city. The concentrations of PM2.5 and PM10 decreased by 59 and 44% during the lockdown period: a marked improvement in air quality. A similar finding was reported with a maximum reduction of 49% in AQI value in Delhi (Sharma et al., 2020). This led to a drastic improvement of the AQI values in Delhi. The air quality levels drastically improved because of the complete absence of major sources of primary air pollutants, such as emissions from vehicles, industry, construction, and brick kilns, during the lockdown period.

National AQI classes, range, health impacts and health breakpoints for the seven pollutants (Scale: 0–500).

Pre-lockdown During lockdown
AQI category (range) Associated Heath Impacts PM10PM2.5 24-h 24-h PM10PM2.5 24-h PM1024-h PM2.5 24-h 24-h
Good (0–50) Minimal Impact 0–50 0–50
Satisfactory (51–100) Minor breathing discomfort to sensitive people 31–60 51–100 58 99
Moderately Polluted (101–200) Breathing discomfort to the people with lung disease 61–90 101–250 151
Poor (201–300) Breathing discomfort to the people with prolonged exposure 91–120 251–350
Very Poor (301–400) Breathing illness to the people with prolonged exposure 121–250 251–430 211
Sever (401–500) Respiratory effects even on healthy people 250+ 430+

Apart from this, another study focused on exploring adverse effects on global public health and social media’s indispensable role in providing the correct information in the COVID-19 health crisis (NeJhaddadgar et al., 2020; Liu et al., 2021b). A study claimed that human–pathogen interactions, such as data from Unit 731, can help epidemiologists better understand pandemics of COVID-19’s scale (Su et al., 2021a; Su et al., 2021b).

 Conclusion

The outcome of lockdown on air quality was assessed from 1st January, 2020 to 31st May, 2020 for New Delhi (India) and from 1st January, 2020 to 10th April, 2020 for Riyadh (Saudi Arabia). The significant reduction in the concentration levels of PM2.5 and PM10 was caused by restrictions on the usage of private vehicles, suspension of non-essential transportation, construction, and industrial activities during the pandemic. The reduction in the concentration value of PM2.5 was calculated to be more than the value of PM10 during the lockdown period, which indicates that traffic was a significant source for the emission of PM2.5. Average concentrations of PM2.5 and PM10 were calculated to be 123.24 μg/m3 and 151.24 μg/m3, respectively, in North Campus, Delhi University. Average concentrations of PM2.5 and PM10 in the pre-lockdown period were observed to be 93.24 μg/m3 and 176.55 μg/m3, respectively, whereas, during the lockdown period, their respective concentrations were 37.89 μg/m3 and 98.87 μg/m3. The values of PM10 showed different trends in Riyadh compared to New Delhi, indicating significant influence from natural (sand and dust storms) and anthropogenic sources during the lockdown periods. This could be attributed to no major changes for particulate matter for pre-and during the lockdown periods. The COVID-19 provided a rare opportunity to countries, including India, to collect air pollution baseline data during the nationwide lockdown. Air pollutants from transport, industries, and commercial activities were reduced significantly during this period. This baseline data could be very relevant to air pollution reduction policies.

Despite this, there are several challenges in the present study, particularly in selecting only one monitoring station. This is a small-scale study with a limited number of sites, which shows significant results. A detailed analysis with a greater number of monitoring stations is desirable. Identification of the sources of air pollution may be incomplete, and certain temporal aspects need to be further studied. In addition, meteorological parameters play a significant role in the transmission of COVID-19 that need to be examined in detail. The non-enforcement of India’s anti-pollution laws is one of the major factors contributing to the high pollution load in India. More research emphasizing these areas is needed. The government should make efforts to maintain positive air quality by instituting advanced emission control technologies because it can significantly improve the environment and thus the health of the people.

The relationship between the air quality and COVID-19 induced lockdowns is significant, subject to the strength of local meteorological and other natural factors. For example, the magnitude of improvement in the air quality in Delhi, shown by a drastic reduction in the concentration of air pollutants, especially PM2.5 and PM10, is mainly correlated with the on-ground implementation of the lockdown and prevalence of support local factors, including meteorological factors like wind speed etc. However, relatively smaller gains in the improvement of air quality in Riyadh are correlated to the imposition of milder lockdown and the predominance of natural factors over the anthropogenic factors there.

The paper conveys the positive impact of lockdowns on air quality in metropolitan cities. The gains are subject to many factors, two of which have been established in the current study in the form of the intensity of lockdown and prevalence and relative strength of local meteorological and natural factors against their anthropogenic counterparts.

 Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

 Author Contributions

BS: Conceptualization, introduction analysis, methodology section. GE: Analysis of the result and discussion for particulate matter for Saudi Arabia. PK: Framing the fine particulate matter associated with New Delhi. PC: Conceptualise the Air Quality Index of the current manuscript. MI improves the quality of the current draft, Writing review and editing. SR: Preparing a literature review and table for a comparative study between New Delhi India and Riyadh, Saudi Arabia

 Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

The authors are grateful to the Researchers Supporting Project No. (RSP-2021/161). King Saud University, Riyadh, Saudi Arabia. The first author thanks Ms. Sonia Kumari and Dr. Sadaf Nazneen for insightful discussion and valuable suggestions during the preparation of the paper. The authors also appreciate Ms. Pallvi Rana, Ms. Nishtha Mittal, and Ms. Pooja deep proofreading the current manuscript.

 Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fenvs.2021.784959/full#supplementary-material

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