Author: Priyanshu Tyagi, Amity Law School, Noida
Not only from a social and economic perspective, but also in terms of human health and the environment, the COVID-19 pandemic has had a significant global impact. To confine transmission of the infection, the Indian government upheld a total cross country lockdown with the exception of fundamental administrations and supplies in stages from 25 Walk to 31 May 2020. During this time, air quality in and around New Delhi, one of the world’s most polluted cities, was also affected.
The point of the current review was to survey and comprehend the effect of four unique lockdown stages (LD1, LD2, LD3 and LD4) on five air poisons (particulate matter (PM) PM2.5, PM10, nitrogen oxide (NOx), sulfur dioxide (SO2) and ozone (O3)) contrasted with before lockdown (BLD) at 13 air observing stations in and around New Delhi.
Contamination fixations diminished during LD1 contrasted with BLD aside from O3 at all stations. PM2.5 and PM10 remained either near or higher than the Public Surrounding Air Quality Norms (NAAQS) because of winning high velocity breezes. During lockdown stages, NO2 diminished, while O3 reliably expanded at all stations. This was dumbfounding as O3 is framed through photochemical responses among NOx and unstable natural mixtures. Head part examination (PCA) separated two head parts (PC1 and PC2) which made sense of up to 80% of aggregate difference in information. PM2.5, PM10 and NO2 were related with PC1, while PC2 had loadings of either O3 just or O3 and SO2 relying on checking station.
The current study found that during lockdown phases, air pollutants decreased, but these decreases were specific to the pollutant(s) and site(s). The planetary boundary layer increased two times during lockdown compared to the BLD phase, so the drop in pollutant concentrations during lockdown could not be entirely attributed to lockdown conditions. These restrictions may be used to control air pollution in the future, but they should be approached with caution.
The World Health Organization (WHO) announced on January 5, 2020, the outbreak of a new virus known as SARS-CoV-2 (coronavirus), and later declared it a global pandemic on March 12, 2020.1,2 In India, the number of infections has reached 9.8 million, and 140 000 people have died as of December 12, 2020, since the first case of COVID-19 in India was reported on January 30, 2020, in the state of Kerala3. India, like other nations, has implemented lockdown strategies to Industrial operations, governmental and private institutions, offices, shopping centers, and air, rail, and road transportation were restricted. Just fundamental administrations (clinical, banking, everyday consumables, media, correspondences and so on.) remained functional throughout the lockdown phases. Scientists studying air pollution thought that the sudden and unexpected lockdown was a good thing for the fight against pollution.4,5,6,7,8,9 After the lockdown started on January 23, 2020, Wuhan, China, saw a reduction of nearly 63% and 35% in the concentrations of nitrogen dioxide (NO2) and particulate matter (PM) in the air, respectively, with little effect on sulfur dioxide (SO2) and carbon monoxide (CO).10 Southampton, England, saw a 92% reduction in NO2 emissions
On March 22, 2020, India imposed a complete lockdown known as the Janta Curfew. Complete lockdown phase 1 (LD1), which lasted from March 25 to April 14, 2020, imposed a nearly complete ban on all activities with the exception of essential supplies. Select industrial and agricultural activities were permitted in LD2 (15 April–3 May 2020), while industrial and construction activities and other limited operations were permitted in LD3 (4 May–17 May 2020) and LD4 (18 May–31 May 2020). Previous reports showed that during the Janta curfew, pollution levels in New Delhi dropped by nearly 44% for PM10, 8% for PM2.5, 44% for nitrogen oxide (NOX), and 32% for carbon monoxide (CO).12 This sharp drop in pollution levels was caused by restrictions on transportation services, construction work, and industrial activities. Air quality file (AQI) values shifted between good to direct during the lockdown deliberately works in the Public Capital District (NCR) of New Delhi.12 Generally, diminishes of 43%, 31%, 18%, and 10% in PM2.5, PM10, NO2, and CO levels, separately, were accounted for during lockdown in India, though ozone (O3) showed a 17% increment in focus and SO2 showed site-explicit variations.5 Kolkata, in eastern India, encountered a decrease of 24% to 45% in outflows of CO during lockdown because of restricted modern discharges and transport services.13 Likewise, AQI at Silicon Valley (Bengaluru) in southern India improved from the ‘risky’ classification after lockdown.14 An almost 40-half decrease in NO2 levels were accounted for in New Delhi and Mumbai during lockdown.4,15 During lockdown, particulate matter fixations were at the most minimal kept levels in the past 20 years.4,15 A critical decrease in air poisons was seen during lockdown contrasted with 2017 and 2019 information over Kanpur, the Indo-Gangetic Plain and northern India.16,17 The lockdown gave a chance to notice and concentrate on the effects of diminished emanations from various sources on encompassing air quality. Future efforts to reduce air pollution may benefit from such studies. Because New Delhi and the areas around it are among India’s most polluted, the purpose of this study was to compare the response of criterion pollutants during lockdown phases to the same period in previous years and the period immediately preceding it.
In the current review, the reactions of five standards poisons: For the time leading up to the lockdown, PM10, PM2.5, SO2, NOx, and O3 were observed and analyzed (BLD: 1 to 24 March 2020), as well as the various lockdown phases: LDs 1 (from 25 March to 14 April 2020), 2 (from 15 April to 3 May 2020), 3 (from 4 to 17 May 2020), and 4 (from 18 to 31 May 2020) Data on air quality from March to May 2020 were compared to data from the same time period in 2019 for comparison.
The current review was completed utilizing auxiliary information gathered from the Focal Contamination Control Board (CPCB) for five measures toxins during the period before lockdown (BLD) and during various periods of lockdown in and around New Delhi. Meteorological information (temperature, relative mugginess, planetary limit layer and wind speed) were utilized to figure out their conceivable job in varieties in mass groupings of contaminations. Moreover, head part investigation (PCA) was utilized to separate the quantity of head parts in view of between poison affiliations and every part was doled out as a potential source.
When compared to the BLD phase, the LD1 phase saw an overall decrease in concentrations of all pollutants across all monitoring stations. Depending on the pollutant(s) and location(s), the concentrations in LD2 and LD3 either remained the same or increased or decreased.
During BLD, the concentrations of PM2.5 and PM10 exceeded NAAQS standards over New Delhi (Anand Vihar, Narela, IGIA-T3, Najafgarh, Okhla, and Jahagirpuri) and the surrounding monitoring stations (Bahadurgarh, Gurugram, Faridabad, and Noida), with the exception of Sonipat, Panipat, and Karnal. Normal decrease in PM2.5 and PM10 focuses over New Delhi differed from 20 to 60% during LD1 contrasted with BLD because of unexpected limitations on open development, modern movement, and public vehicle Lower concentrations at monitoring stations (Sonipat and Karnal) along the northern national highway were due to restrictions on emission sources and precautions taken by the general public to restrict unnecessary movement prior to lockdown. Lower concentrations at monitoring stations (Sonipat and Karnal) along the northern national highway were due to restrictions on emission sources and precautions taken by the general public to restrict unnecessary movement before lockdown. PM10 concentrations were largely associated with resuspension of road dust, local emissions, and construction Local factors like plowing in fields and industrial activities could have contributed to the rise in particle concentrations at Panipat during LD1. PM2.5 and PM10 concentrations increased slightly during LD2 after LD1 due to the gradual lifting of restrictions on certain activities. These high concentrations at other stations (Bahadurgarh, Gurugram, Faridabad, Noida) around New Delhi could be caused by construction activities around these stations, wind-blown dust, or local resuspension of particles, as has also been reported previously for this region.18,19,20 Additional increases in PM2.5 and PM10 concentrations during LD3 and LD4 could be attributed to further relaxation on public and vehicular movement, resuspension of surface dust, and biomass burning in and around the monitoring stations. Additionally, the duration of LD2 coincided with the onset of strong south-west winds, which could bring intermittent dust storms and amplify concentrations of PM2.5 and PM10.18,19,20. According to Jain and Sharma, lockdown in New Delhi resulted in significant reductions of 41% and 52% in the concentrations of PM2.5 and PM10, respectively.24 A decline of 45% was observed in PM2.5 concentration in Wuhan city, China as a result of the pandemic.2 The decrease in PM2.5 and PM10 concentrations at all stations due to lockdown clearly indicated that lockdown acted as a ventilator for the ambient atmosphere, although PM10 and PM2.5 were not within NAAQS Over north India, high concentrations of PM2.5 and PM10 compared to WHO and NAAQS limits may be linked to location. Due to the strong winds that prevailed, the study period overlapped with the onset of intermittent dust storms. Again, restrictions were to blame for the decrease in PM2.5 and PM10 levels compared to the same time period in 2019. At the Panipat site, a slight increase in PM concentrations was observed due to local factors like coal-based thermal power plants operating during the lockdown period and emissions being reinstated.
Along with emissions from power plants and industries, vehicle emissions are a major source of NOx (NO and NO2). O3, a secondary criteria air pollutant, is produced when NOx and volatile organic compounds (VOCs) undergo photochemical reactions. The presence of sufficient sunlight for the photochemical reaction facilitates the formation of O3 in the ambient atmosphere during the summer. The concentration of NO2 continued to decrease at all monitoring stations during LD 1 in comparison to BLD as a result of restrictions on vehicular movement other than for essential services. In a similar vein, the lockdown resulted in a 50% decrease in the concentration of NO2 in New Delhi.24 The thermal power plant that was operating near Fridabad during the lockdown may have contributed to this decrease, whereas the increase in NO2 may have been caused by small-scale industries of essential goods and agricultural fields around Sonipat. In a similar vein, the intensification of restrictions and the resumption of industrial operations during LD3 and LD4 could account for the rise in NO2 levels.
During lockdown phases, O3 remained lower than required standards at all stations due to restrictions on vehicle movement and limited NO2 emissions. The availability of NOx and VOCs may be the cause of the increase in O3 concentrations throughout New Delhi, with the exception of Narela, during LD1. NOx emissions from wetlands or crop residue burning may have had an impact on the monitoring stations along national highways (Karnal and Bahadurgarh), resulting in increased O3 formation during lockdown phases. Vehicles, oil refineries, thermal power plants, and the fertilizer industry were among the sources of NO2 in Panipat.27,28 Similar to Panipat and Jahangirpuri, an increase of 7% in O3 concentrations has been observed in New Delhi, while an increase of 3% has been observed in Chennai. also reported an increase in O3 concentrations during the lockdown in China’s Wuhan city.29 The increase in O3 concentrations in 2020 compared to the same time last year may have been caused by a decrease in particulate matter concentrations, which allowed more sunlight to penetrate the atmosphere. This increased photochemical activity led to an increase in O3 formation. Industries and coal-based thermal power plants are responsible for nearly 27% of SO2 concentrations in and around New Delhi.27 However, SO2 concentrations at all stations During LD2 and LD4, emissions from the city’s thermal power plant, fertilizer company, and oil refineries may have caused slight changes in SO2 concentrations at the Panipat and Karnal stations.30,31 The lockdown clearly affected the lowest SO2 concentration at the IGIA-T3. The labor class’s migration, which involves using coal as a cooking fuel, could be linked to lower SO2 concentrations near the Bahadurgarh, Gurugram, and Faridabad stations. Because this region is home to a large number of migratory laborers who recommenced their employment following the relaxation of economic activity restrictions, the resumption of activities may have resulted in an increase in SO2 concentrations from BLD phase to LD4 phase around Noida station. The potential wellsprings of SO2 outflows could be nearby enterprises, coal-based power plants, and homegrown level consuming exercises. According to Singh and Sidhu, wheat residue retains 25–30 percent nitrogen and phosphorus, 35–40 percent sulfur, and 70–75 percent potassium uptake32. Due to lockdown, the concentration of SO2 decreased at all stations compared to the same time period during the previous year’s stations, where it increased during the LD period.
The prevailing meteorological variables, such as wind velocity, temperature, relative humidity, and the planetary boundary layer (PBL), control the concentrations of pollutants in the surrounding atmosphere. Increases in PBL height are thought to be an indication of an open and unstable atmosphere, so the slight decrease in pollutant concentrations during lockdown may not necessarily be due to or indicate a decrease in pollutant emissions. In general, high wind speed and low relative humidity assist in the dispersal of air pollutants in comparison to a stagnant atmosphere.5,33 Pollutant concentrations ought to have been reduced by half during the lockdown period given that the PBL increased by more than one hundred percent and that the lockdown’s emission rates were comparable. As opposed to this hypothesis, contamination focuses were not brought down by half under expanded PBL level during lockdown. Also, a speed up at a portion of the stations might have contributed particles in encompassing air by means of re-suspension of surface residue. As a result, it can be concluded that the lockdown as well as the prevailing meteorological conditions, such as an increase in PBL and high wind speed, were responsible for lower pollution levels. This suggests that pollutant concentrations in the ambient atmosphere were not only reduced as a result of lower emissions of pollutants during the lockdown period, but that metrological variables also played a significant role in bringing down pollution levels.34
Only two components, PC1 and PC2, were extracted from all monitoring stations, with the exception of Karnal and Noida, where only one component was extracted because the majority of pollution sources were inoperable during lockdown. PC1 and PC2 may collectively account for nearly 80 percent of the variance in the data; the remaining variance may be related to other pollutants that were not taken into consideration in this study. The PCA analysis revealed a complicated circumstance. While the additions of NO2 and SO2 to PC1 were site-specific, PM2.5 and PM10 remained associated with a single component, which is attributed to transported dust or re-suspended dust. This could be caused by the uneven burning of coal during lockdown or by the movement of vehicles. Due to their proximity to essential service shops or larger populations, some stations saw more traffic. In a similar vein, there was a greater spread of domestic coal burning in the vicinity of stations that served predominantly migrant and poor populations. At some stations, it was impossible to examine the relationship between O3 and PC2 or SO2 due to the current data. Atomic oxygen, produced by photo-dissociation of NO2, is required for the formation of O3. It was possible that there was an unidentified source of atomic oxygen, and the possibility that chemical transformation of SO2 could yield atomic oxygen has not yet been investigated or established. Negative loadings of O3 in PC2 at the Gurugram, Bahadurgarh, and Noida sites, which share a border with New Delhi.
Air quality superior altogether in and around New Delhi after the execution of lockdown contrasted with before lockdown. Nonetheless, upgrades in air quality because of lockdown were checking station and toxin explicit. Poison fixations began expanding gradually, especially after LD2, because of unwinding of horticultural and modern movement limitations. At stations along public interstates, air quality was at first better because of the joined impact of modern shut down and restricted vehicular development however began to deteriorate by virtue of unwinding of limitations and restarting of exercises. The NO2 and O3 greatest fixations shifted across all locales during the whole review time frame, despite the fact that NO2 is areas of strength for a for O3 development. Head part examination separated two head parts (PC1 and PC2) and made sense of up to 80% combined change in the information. Among all toxins, PM2.5, PM10, and NO2 were related with PC1, while PC2 had loadings of either O3 just or both O3 and SO2. Meteorological boundaries, especially wind speed, impacted PM10 fixations through transport of residue and re-suspension of surface residue.
The diminishing in contamination levels couldn’t be made sense of completely founded on limitations on discharge sources during lockdown. Sped up and PBL were likewise potential explanations behind dispersal of toxins and lower fixations in surrounding environment. Diminished contamination load because of lockdown might prompt upgrades in human wellbeing, yet watchfulness ought to be taken with execution of such lockdowns later on, as they adversely affect the financial and social climate of the country.
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