Spatial and Temporal Variation in the Air Quality Index during COVID-19 in Punjab, Haryana and Delhi, India

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The Geo-spatial and temporal fluctuation of gaseous and particle pollutants over the whole countrywide lockdown period and the same month in the previous year 2019 (September to November) was estimated using geospatial approaches. The Central Pollution Control Board provided data on six fixed contaminants (CPCB). Within this framework, 2019 and 2020 air pollution statistics (PM 10 , PM 2.5 , O3, NOx, SO 2 , and CO 2 ) were examined. The Air Quality Index's (AQI) spatial temporal distribution makes the difference between the lockdown and unlocks times quite evident. According to the results, the COVID-19 lockout caused the air quality to improve from extremely poor to satisfactory in 2019 and from satisfactory to good in 2020. Based on the findings, it will be determined that industry and automobiles have a big role in raising the concentration of pollutants. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences Physical sciences/Materials science Air Quality Spatial and Temporal Pollutants Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Measuring air quality in relation to its impact on human health is the primary goal of air quality indices. This is usually a quality index for the day. The Environmental Protection Agency (EPA) (1999) has suggested a daily AQI. It is described in terms of the six primary types of common pollutants: particulate matter (PM 10 ) and (PM 2.5 ), carbon monoxide (CO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ), and sulphur dioxide (SO 2 ). The primary causes of air pollution are automobiles and industrial smoke emissions. When dangerous gases and smoke combine with the atmosphere, the air becomes contaminated and loses quality. This is known as air pollution. The widely used concept known as the "air quality index" is used to quantify the degree of air pollution. The US EPA created the Air Quality Index as a method to gauge air pollution levels (S. Gowtham et al ., 2015). In addition to being a major risk to human health, air pollution is becoming a major hazard to the environment. The World Health Organization (WHO) estimates that air pollution affects 80% of people, who live in urban areas, and that 56% of high-income nations' cities and 98% of low- and middle-income countries' cities do not adhere to WHO standards. It is estimated that the mortality rate from ambient air pollution is above 4.2 million (WHO 2016 ). Transportation, industry, and the burning of biomass are examples of anthropogenic activities that contribute significantly to air pollution (Singh et al., 2021 ). Anthropogenic activities are said to be responsible for around 80% of the pollution growth (IQ Air 2021). Therefore, restricting human activity would have led to a reduction in air pollution levels, as evidenced by observations made both globally and regionally during the COVID-19-driven lockdown in 2020 (Bao et al ., 2020, Ranjan et al., 2020 , Sharma, S., et al., 2020 , Siddiqui, A., et al., 2020 , Srivastava, S., et al., 2020 , Bera, B., et al., 2021 , Hashim, B. M., et al., 2021 ). Early in January, the Indian government began screening visitors from China and released an alert for them. The Indian Prime Minister declared the Janata curfew, which would run from 7 a.m. to 9 p.m. on March 22, 2020, due to a spike in COVID-19 cases (The Economic Times, 2020). After two days, the Indian government declared a total statewide lockdown, which would last from 24 March to April 2020 and prohibit all internal and foreign travel, rail travel, and automobile travel except from necessities ( https://www.bbc.com/news/world/asia/india ). Roads in India were desolate during the total shutdown, with the exception of emergency vehicles. Since April is when India harvests its winter wheat crop and plants its vegetable crops at their height each year, the government has loosened restrictions on farmers' movement during the second phase of lockdown, which runs from April 15 to May 3, 2020. The air quality is declining as a result of the Indian government's continued, lenient extension of the lockdown in some areas, which has led to the opening of domestic flights, some rail, roads, and automobile transportation. Delhi and other major cities in the Indo-Gangetic Plains (IGP) have worse air quality due to the burning of agricultural leftover by farmers in various areas and the long-term movement of dust during the pre-monsoon season. Sharma et al. have examined the effects of lockdown on air quality during the dates of March 15, 2020, to April 14, 2020, using data from the Central Pollution Control Board 7. According to an examination of air pollutants taken from satellite data for April 2019 and 2020 over Haryana, India, PM 10 saw the largest drop, followed by PM 2.5 , SO 2 , NO 2 , CO 2 , and CH 4 , and the air quality index (AQI) improved (Singh, D., et al., 2022 ). According to real-time monitoring of many air pollutants, the COVID-19 lockout produced a significant decrease in petrol emission rates in April and May of 2020. Burning fossil fuels has been seen to be low in consumption, and daily worldwide CO 2 emissions in April were − 17% lower than the 2019 average (Le Quéré, C. et al., 2020 ). Materials and Methods Study area The study was carried out in three states: Delhi, which is located at 28° 70′ N latitude and 77°10′E longitude, Haryana, which is located between 27°39′ and 30°35′ N latitude and between 74°28′ and 77°36′ E longitude, and Punjab, which is located between 29°30′ and 32°32′ N latitude and 73°55′ to 76°50′ E longitudes. The states of Haryana and Uttar Pradesh surround Delhi. Haryana is located in the northern region of India and has a geographical area of 44,212 sq km, or 1.34% of the country's total area. The state of Punjab covers 50,362 square kms (19,445 square miles), or 1.53% of the country's total geographical area. Delhi is 1,483 square km in size. Significant growth has been observed in the manufacturing sector, transportation, economics, industrial smoke emissions, and burning of agricultural residues. But the problem of growth-related air pollution has gotten much worse. The state's air quality can range from good to severe depending on the month and season. It is imperative to carry out the present investigation and analysis of the temporal and geographical aspects of air pollutants in order to improve the air quality in Delhi, Punjab, and Haryana. Data Sources The six air pollutants included in the monitoring station data used in this study were nitrous oxide (NO X ), sulphur dioxide (SO 2 ), carbon monoxide (CO 2 ), fine particulate matter (PM 2.5 ), coarse particulate matter (PM 10 ), and ozone (O 3 ) (National, AQI). The data were obtained from the Central Pollution Control Board (CPCB) site. Every hour, data are downloaded and averaged from measurements done every 24 hours. Data for some districts Punjab and Haryana were unavailable. A without dimensions indicator that provides a quantitative description of air quality is the AQI. The Central Control Pollution Board states that the AQI was determined using the different factors (PM 10 , PM 2.5 , O 3 , NOx, SO 2 , and CO 2 ) provided on the CPCB website. The AQI standards were imposed by the Ministry of Environment, Forests, and Climate Change. An AQI of more than 50 indicates an increase in the concentration of the main pollutant. The six categories that make up the AQI an as follows: 0–50, 51–100, 101–200, 201–300, 301–400, and 401–500. The associated pollution levels are, in order, good, satisfactory, moderate, poor, extremely poor, and severe. A without dimensions indicator that provides a quantitative description of air quality is the AQI. The Central Control Pollution Board states that the AQI was determined using the different factors (PM10, PM2.5, O3, NOx, SO 2 , and CO 2 ) provided on the CPCB website. The AQI standards were imposed by the Ministry of Environment, Forests, and Climate Change. An AQI of more than 50 indicates an increase in the concentration of the main pollutant. (Fig. 1 ) shows that the six categories that make up the AQI are as follows: 0–50, 51–100, 101–200, 201–300, 301–400, and 401–500. The associated pollution levels are, in order, good, satisfactory, moderate, poor, extremely poor, and severe (National, AQI, 2015). The less wealthy the air quality, greater the AQI. The mathematical equation for calculating sub-indices of AQI is as follows: \(\text{I}\text{p}=\frac{(\text{I}\text{H}\text{I}-\text{I}\text{L}\text{O})}{(BPHI-BPLO)}\times \left(CP-BPLO\right)+ILO\) where I P is AQI for pollutant “P” (Rounded to the nearest integer), C P the actual ambient concentration of pollutant “P”, BP HI the upper-end breakpoint concentration that is greater than or equal to C P , BP LO the lower end breakpoint concentration that is less than or equal to C P , I LO the sub-index or AQI value corresponding to BP LO , I HI the sub-index or AQI value corresponding to BP HI (National, AQI, 2015). Data processing MS-Excel was used to analyze the data by entering daily information on various contaminants. Using geospatial techniques, the spatial and temporal fluctuations of gaseous and particle pollutants were calculated over the three months (September to November) of COVID-19 in the year 2019–2020. By translating the monthly (September to November) individual pollutants from the average daily data, the air quality index for every 10 days was calculated. The air quality index was computed by converting the monthly individual pollutants from the average daily data. The temporal and geographical amount of air pollution was investigated using statistical analysis and Arc GIS. Arc GIS software (Version 10.4, available at the Geo-informatics lab, Department of Agricultural Meteorology, Chaudhary Charan Singh, Haryana Agricultural University, Hisar, Haryana; published by the Environmental Systems Research Institute (ESRI), Redlands, California, USA) is used to support the spatial analysis method for spatial characterization(ESRI). Result and Discussion Statues of AQI in 2019–2020 during September The atmospheric concentrations of nitrogen oxides (NO X ), sulphur dioxide (SO 2 ), carbon monoxide (CO 2 ), fine particulate matter (PM 2.5 ), coarse particulate matter (PM 10 ), and ozone (O 3 ) change over time due to variations in the weather and the amount of air pollution emitted. The connection between emission intensity, meteorological factors, and ambient air pollution concentration levels. Figure 2 depicts the temporal fluctuations in the AQI Index in Delhi, Punjab, and Haryana from September 1 to September 10, 2019. It should be noted that for a while, AQI figures for several districts were unavailable Take data on air quality in Punjab and Haryana, for example. In Panchkula, Haryana, the AQI is good quality; during the month, it has been determined to be severe in Delhi and the central part of Haryana, poor and moderate in other places of Punjab and Haryana, and continuing the same trend. Mid-September 2020 had good and satisfactory results for Punjab, Haryana, and Delhi on the AQI Index; however, the first and last month ten days showed a similar pattern of moderate and satisfactory results. AQI Status in … At 10 days period in September months in 2019–2020 Statues of AQI in 2019–2020 during October Figure 3 illustrated the temporal variations in the ten days average of AQI in Punjab, Haryana and Delhi, from October 2019–2020. The AQI has been found to be poor in Delhi and the middle portion of Haryana, poor and moderate in some areas of Punjab and Haryana, Good in Panchkula in Haryana, and following the same trend throughout the month. Illustrates the changes in the AQI Index over time in Delhi, Punjab, and Haryana between October 1, 2020, and October 10, 2020. It should be mentioned that AQI data for a number of areas were temporarily unavailable. Consider information on the quality of the air in Punjab and Haryana. In Punjab, Haryana, and Delhi, the AQI has been determined to be moderate; in October of previous year, the AQI showed the same pattern in Punjab, but in Haryana and Delhi, it was poor and very poor. AQI Status in … At 10 days period in October months in 2019–2020 Statues of AQI in 2019–2020 during November The variations in the AQI concentrations of observed in Delhi, Haryana and Punjab along with trend analysis. The corresponding values of the AQI concentration levels of can be found in Fig. 4 from October 1, 2020, and October 10, 2020. These analyses provide insights into the changes in the AQI concentration levels over time. In Punjab the AQI has been determined to be Poor; in October of previous year, the AQI showed in Haryana and Delhi it was very poor and severe. But the last month of November the AQI Moderate in Punjab and some part of Haryana but other part of Haryana and Delhi the AQI is poor. AQI Status in … At 10 days period in November months in 2019–2020 Discussion Spatial variation in AQI in Punjab, Haryana and Delhi In 2019, observed moderate to poor to very poor air quality in Punjab, while Haryana and Delhi had poor to very poor air quality due to industrial, stable environmental conditions for air pollution containment, construction that produced a significant amount of pollution in NCR cities, and increased turbulence activity from September to November, according to results reported by (Bhankhar et al. 2002). The lockdown period in 2020, which prevented work on automobiles, industries, and other construction projects, as well as cyclonic activity, heat convection maximums, and unpredictable environmental conditions from September to November, caused the air quality index to drop from satisfactory to good quality. Conclusion The outcome demonstrated that during the lockdown, the quality of the air improved. During the whole lock period in 2019, the air quality was worse than in 2020. The findings showed that the areas with the highest concentration of industrial areas—Punjab, Haryana, and Delhi—saw improvements in the air quality index. According to the survey, the AQI Serve was very poor in other districts of Punjab and Haryana and well developed in Delhi and the National Capital Region (NCR), which includes Gurugram, Faridabad, Palwal, Karnal, and Mahedergarh. Additionally, it was discovered that during the lockdown, the air temperature decreased in proportion to the reduction in greenhouse gas emissions. Important information on future urban growth and pollution management is provided by the research. In addition, there is a dearth of quantitative research on air quality and an abundance of elements, including weather and human activity that influence air quality. Future research is required to limit extrapolation error and investigate the links between other driving variables and air pollution for additional metropolitan areas by combining data from remote sensing and ground monitoring. Declarations Author Contribution Mr. S.K gives an idea about this research and helps in the collection of data from the CPCB site. All figureand table analysis and written work done by him. Ms. A.A. helped in downloading and arranging data,helped in download and anaysis in data and help in making map and graph. Acknowledgement I especially thankful to Central Pollution Control Board for provided data on site https:// app. cpcbc cr. com/ AQI_India_ Iframe/. I thankful the Department of Agricultural Meteorology to provide meteorological data and fortheir guidance, constant encouragement and fruitful suggestion at all stages of research work. Data Availability Data collected from Central Control Pollution Board (CPCB) on daily basis on free of cost as available opensourceat web-link http://app.cpcbccr.com/AQI_India/ References Bera, B., Bhattacharjee, S., Shit, P. K., Sengupta, N. & Saha, S. Significant impacts of COVID-19 lockdown on urban air pollution in Kolkata (India) and amelioration of environmental health. Environ. Dev. Sustain. 23(5), 6913–6940 (2021). Bao, R. & Zhang, A. Does lockdown reduce air pollution? Evidence from 44 cities in northern China. Sci. Total Environ. 731, 139052 (2020). Bhanarkar, A. D., Gajghate, D. G. & Hasan, M. Z. Air pollution concentrations in Haryana subregion, India. Bull. Environ. Contam. Toxicol. 69 (5), 0690–0695 (2002). Corona virus: India enters ’total lockdown’ after spike in cases, 23 March 2020. https://www.bbc.com/news/world/asia/india ESRI, DeLorme, NAVTEQ, Tom Tom, Inter map Pcorp, GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, Kasdaster NL Ordnance. Survey, ESRI Japan, METI and the GIS User Community. Hashim, B. M., Al-Naseri, S. K., Al-Maliki, A. & Al-Ansari, N. Impact of COVID-19 lockdown on NO2, O3, PM2.5 and PM1.0 concentrations and assessing air quality changes in Baghdad, Iraq. Sci. Total Environ. 754, 141978 (2021). IQ Air. World air quality report regions and city ranking. (2019). https://gaspgroup.org/airquality/?gad_source=1&gclid=EAIaIQobChMI4rLGjOmThAMVBYJLBR3mZgCWEAAYASAAEgKYVfD_BwE Accessed 16 Mar 2021. Le Quéré, C. et al. Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement. Nat. Clim. Chang. 1, 1–7 (2020). National air quality index. https:// app. cpcbc cr. com/ AQI_ India_ Iframe. National air quality index, final report. (2015). http://app.cpcbccr.com/ccr_docs/FINAL-REPORT_AQI_.pdf Ranjan, A. K., Patra, A. K. & Gorai, A. K. Effect of lockdown due to SARS COVID-19 on aerosol optical depth (AOD) over urban and mining regions in India. Sci. Total Environ. 745, 141024 (2020). Singh, D., Dahiya, M., Kumar, R. & Nanda, C. Sensors and systems for air quality assessment monitoring and management: A review. J. Environ. Manage. 289, 112510 (2021). S. Gowtham and K. Anjali, 2015, Ambience of Air Quality Analysis using AQI: IJIRST –International Journal for Innovative Research in Science & Technology| Volume 1 | Issue 10 | ISSN (online): 2349-6010. Singh, D., Nanda, C. & Dahiya, M. State of air pollutants and related health risk over Haryana India as viewed from satellite platform in COVID-19 lockdown scenario. Spat. Inf. Res. 30(1), 47–62 (2022). Sharma, S., Zhang, M., Gao, J., Zhang, H. & Kota, S. H. Effect of restricted emissions during COVID-19 on air quality in India. Sci. Total Environ. 728, 138878 (2020). Siddiqui, A., Halder, S., Chauhan, P. & Kumar, P. COVID-19 pandemic and city-level nitrogen dioxide (NO 2 ) reduction for urban centre’s of India. J. Indian Soc. Remote Sens. 48(7), 999–1006 (2020). Srivastava, S., Kumar, A., Bauddh, K., Gautam, A. S. & Kumar, S. 21-day lockdown in India dramatically reduced air pollution indices in Lucknow and New Delhi, India. Bull. Environ. Contam. Toxicol. 105(1), 9–17 (2020). Somani, M., Srivastava, A. N., Gummadivalli, S. K. & Sharma, A. Indirect implications of COVID-19 towards sustainable environment: An investigation in Indian context. Bioresour. Technol. Rep. 11, 100491 (2020). The Economic Times, 23 March 2020 https://economictimes.indiatimes.com/news/politics-and-nation/after-janata-curfew-india-gets-ready-for-long WHO. WHO Global Urban Ambient Air Pollution Database (WHO, 2016). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4089995","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":289392739,"identity":"ac4211b2-1241-4cc4-a6be-7769ccc43dee","order_by":0,"name":"Surender 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5","display":"","copyAsset":false,"role":"figure","size":105802,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Result and Discussion section.\u003c/p\u003e","description":"","filename":"key.png","url":"https://assets-eu.researchsquare.com/files/rs-4089995/v1/7ecff7c28382838290db223c.png"},{"id":54455352,"identity":"7e1bbf00-a338-4b3f-a8bc-8ae60282d87c","added_by":"auto","created_at":"2024-04-10 18:59:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":917911,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4089995/v1/6700a0d3-31bb-4525-a318-f5feb501f3ee.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Spatial and Temporal Variation in the Air Quality Index during COVID-19 in Punjab, Haryana and Delhi, India","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMeasuring air quality in relation to its impact on human health is the primary goal of air quality indices. This is usually a quality index for the day. The Environmental Protection Agency (EPA) (1999) has suggested a daily AQI. It is described in terms of the six primary types of common pollutants: particulate matter (PM\u003csub\u003e10\u003c/sub\u003e) and (PM\u003csub\u003e2.5\u003c/sub\u003e), carbon monoxide (CO\u003csub\u003e2\u003c/sub\u003e), nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e), ozone (O\u003csub\u003e3\u003c/sub\u003e), and sulphur dioxide (SO\u003csub\u003e2\u003c/sub\u003e). The primary causes of air pollution are automobiles and industrial smoke emissions. When dangerous gases and smoke combine with the atmosphere, the air becomes contaminated and loses quality. This is known as air pollution. The widely used concept known as the \"air quality index\" is used to quantify the degree of air pollution. The US EPA created the Air Quality Index as a method to gauge air pollution levels (S. Gowtham \u003cem\u003eet al\u003c/em\u003e., 2015). In addition to being a major risk to human health, air pollution is becoming a major hazard to the environment. The World Health Organization (WHO) estimates that air pollution affects 80% of people, who live in urban areas, and that 56% of high-income nations' cities and 98% of low- and middle-income countries' cities do not adhere to WHO standards. It is estimated that the mortality rate from ambient air pollution is above 4.2\u0026nbsp;million (WHO \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Transportation, industry, and the burning of biomass are examples of anthropogenic activities that contribute significantly to air pollution (Singh et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Anthropogenic activities are said to be responsible for around 80% of the pollution growth (IQ Air 2021). Therefore, restricting human activity would have led to a reduction in air pollution levels, as evidenced by observations made both globally and regionally during the COVID-19-driven lockdown in 2020 (Bao \u003cem\u003eet al\u003c/em\u003e., 2020, Ranjan et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Sharma, S., et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Siddiqui, A., et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Srivastava, S., et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Bera, B., et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Hashim, B. M., et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Early in January, the Indian government began screening visitors from China and released an alert for them. The Indian Prime Minister declared the Janata curfew, which would run from 7 a.m. to 9 p.m. on March 22, 2020, due to a spike in COVID-19 cases (The Economic Times, 2020). After two days, the Indian government declared a total statewide lockdown, which would last from 24 March to April 2020 and prohibit all internal and foreign travel, rail travel, and automobile travel except from necessities (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/world/asia/india\u003c/span\u003e\u003cspan address=\"https://www.bbc.com/news/world/asia/india\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Roads in India were desolate during the total shutdown, with the exception of emergency vehicles. Since April is when India harvests its winter wheat crop and plants its vegetable crops at their height each year, the government has loosened restrictions on farmers' movement during the second phase of lockdown, which runs from April 15 to May 3, 2020. The air quality is declining as a result of the Indian government's continued, lenient extension of the lockdown in some areas, which has led to the opening of domestic flights, some rail, roads, and automobile transportation. Delhi and other major cities in the Indo-Gangetic Plains (IGP) have worse air quality due to the burning of agricultural leftover by farmers in various areas and the long-term movement of dust during the pre-monsoon season. Sharma et al. have examined the effects of lockdown on air quality during the dates of March 15, 2020, to April 14, 2020, using data from the Central Pollution Control Board 7. According to an examination of air pollutants taken from satellite data for April 2019 and 2020 over Haryana, India, PM\u003csub\u003e10\u003c/sub\u003e saw the largest drop, followed by PM\u003csub\u003e2.5\u003c/sub\u003e, SO\u003csub\u003e2\u003c/sub\u003e, NO\u003csub\u003e2\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, and CH\u003csub\u003e4\u003c/sub\u003e, and the air quality index (AQI) improved (Singh, D., et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). According to real-time monitoring of many air pollutants, the COVID-19 lockout produced a significant decrease in petrol emission rates in April and May of 2020. Burning fossil fuels has been seen to be low in consumption, and daily worldwide CO\u003csub\u003e2\u003c/sub\u003e emissions in April were \u0026minus;\u0026thinsp;17% lower than the 2019 average (Le Qu\u0026eacute;r\u0026eacute;, C. et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eThe study was carried out in three states: Delhi, which is located at 28\u0026deg; 70\u0026prime; N latitude and 77\u0026deg;10\u0026prime;E longitude, Haryana, which is located between 27\u0026deg;39\u0026prime; and 30\u0026deg;35\u0026prime; N latitude and between 74\u0026deg;28\u0026prime; and 77\u0026deg;36\u0026prime; E longitude, and Punjab, which is located between 29\u0026deg;30\u0026prime; and 32\u0026deg;32\u0026prime; N latitude and 73\u0026deg;55\u0026prime; to 76\u0026deg;50\u0026prime; E longitudes. The states of Haryana and Uttar Pradesh surround Delhi. Haryana is located in the northern region of India and has a geographical area of 44,212 sq km, or 1.34% of the country's total area. The state of Punjab covers 50,362 square kms (19,445 square miles), or 1.53% of the country's total geographical area. Delhi is 1,483 square km in size. Significant growth has been observed in the manufacturing sector, transportation, economics, industrial smoke emissions, and burning of agricultural residues. But the problem of growth-related air pollution has gotten much worse. The state's air quality can range from good to severe depending on the month and season. It is imperative to carry out the present investigation and analysis of the temporal and geographical aspects of air pollutants in order to improve the air quality in Delhi, Punjab, and Haryana.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData Sources\u003c/h2\u003e \u003cp\u003eThe six air pollutants included in the monitoring station data used in this study were nitrous oxide (NO\u003csub\u003eX\u003c/sub\u003e), sulphur dioxide (SO\u003csub\u003e2\u003c/sub\u003e), carbon monoxide (CO\u003csub\u003e2\u003c/sub\u003e), fine particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e), coarse particulate matter (PM\u003csub\u003e10\u003c/sub\u003e), and ozone (O\u003csub\u003e3\u003c/sub\u003e) (National, AQI). The data were obtained from the Central Pollution Control Board (CPCB) site. Every hour, data are downloaded and averaged from measurements done every 24 hours. Data for some districts Punjab and Haryana were unavailable. A without dimensions indicator that provides a quantitative description of air quality is the AQI. The Central Control Pollution Board states that the AQI was determined using the different factors (PM\u003csub\u003e10\u003c/sub\u003e, PM\u003csub\u003e2.5\u003c/sub\u003e, O\u003csub\u003e3\u003c/sub\u003e, NOx, SO\u003csub\u003e2\u003c/sub\u003e, and CO\u003csub\u003e2\u003c/sub\u003e) provided on the CPCB website. The AQI standards were imposed by the Ministry of Environment, Forests, and Climate Change. An AQI of more than 50 indicates an increase in the concentration of the main pollutant. The six categories that make up the AQI an as follows: 0\u0026ndash;50, 51\u0026ndash;100, 101\u0026ndash;200, 201\u0026ndash;300, 301\u0026ndash;400, and 401\u0026ndash;500. The associated pollution levels are, in order, good, satisfactory, moderate, poor, extremely poor, and severe. A without dimensions indicator that provides a quantitative description of air quality is the AQI. The Central Control Pollution Board states that the AQI was determined using the different factors (PM10, PM2.5, O3, NOx, SO\u003csub\u003e2\u003c/sub\u003e, and CO\u003csub\u003e2\u003c/sub\u003e) provided on the CPCB website. The AQI standards were imposed by the Ministry of Environment, Forests, and Climate Change. An AQI of more than 50 indicates an increase in the concentration of the main pollutant. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e) shows that the six categories that make up the AQI are as follows: 0\u0026ndash;50, 51\u0026ndash;100, 101\u0026ndash;200, 201\u0026ndash;300, 301\u0026ndash;400, and 401\u0026ndash;500. The associated pollution levels are, in order, good, satisfactory, moderate, poor, extremely poor, and severe (National, AQI, 2015). The less wealthy the air quality, greater the AQI.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe mathematical equation for calculating sub-indices of AQI is as follows:\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{I}\\text{p}=\\frac{(\\text{I}\\text{H}\\text{I}-\\text{I}\\text{L}\\text{O})}{(BPHI-BPLO)}\\times \\left(CP-BPLO\\right)+ILO\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere I\u003csub\u003eP\u003c/sub\u003e is AQI for pollutant \u0026ldquo;P\u0026rdquo; (Rounded to the nearest integer), C\u003csub\u003eP\u003c/sub\u003e the actual ambient concentration of pollutant \u0026ldquo;P\u0026rdquo;, BP\u003csub\u003eHI\u003c/sub\u003e the upper-end breakpoint concentration that is greater than or equal to C\u003csub\u003eP\u003c/sub\u003e, BP\u003csub\u003eLO\u003c/sub\u003e the lower end breakpoint concentration that is less than or equal to C\u003csub\u003eP\u003c/sub\u003e, I\u003csub\u003eLO\u003c/sub\u003e the sub-index or AQI value corresponding to BP\u003csub\u003eLO\u003c/sub\u003e, I\u003csub\u003eHI\u003c/sub\u003e the sub-index or AQI value corresponding to BP\u003csub\u003eHI\u003c/sub\u003e (National, AQI, 2015).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData processing\u003c/h2\u003e \u003cp\u003eMS-Excel was used to analyze the data by entering daily information on various contaminants. Using geospatial techniques, the spatial and temporal fluctuations of gaseous and particle pollutants were calculated over the three months (September to November) of COVID-19 in the year 2019\u0026ndash;2020. By translating the monthly (September to November) individual pollutants from the average daily data, the air quality index for every 10 days was calculated. The air quality index was computed by converting the monthly individual pollutants from the average daily data. The temporal and geographical amount of air pollution was investigated using statistical analysis and Arc GIS. Arc GIS software (Version 10.4, available at the Geo-informatics lab, Department of Agricultural Meteorology, Chaudhary Charan Singh, Haryana Agricultural University, Hisar, Haryana; published by the Environmental Systems Research Institute (ESRI), Redlands, California, USA) is used to support the spatial analysis method for spatial characterization(ESRI).\u003c/p\u003e \u003c/div\u003e"},{"header":"Result and Discussion","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eStatues of AQI in 2019\u0026ndash;2020 during September\u003c/h2\u003e\n\u003cp\u003eThe atmospheric concentrations of nitrogen oxides (NO\u003csub\u003eX\u003c/sub\u003e), sulphur dioxide (SO\u003csub\u003e2\u003c/sub\u003e), carbon monoxide (CO\u003csub\u003e2\u003c/sub\u003e), fine particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e), coarse particulate matter (PM\u003csub\u003e10\u003c/sub\u003e), and ozone (O\u003csub\u003e3\u003c/sub\u003e) change over time due to variations in the weather and the amount of air pollution emitted. The connection between emission intensity, meteorological factors, and ambient air pollution concentration levels. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the temporal fluctuations in the AQI Index in Delhi, Punjab, and Haryana from September 1 to September 10, 2019. It should be noted that for a while, AQI figures for several districts were unavailable Take data on air quality in Punjab and Haryana, for example. In Panchkula, Haryana, the AQI is good quality; during the month, it has been determined to be severe in Delhi and the central part of Haryana, poor and moderate in other places of Punjab and Haryana, and continuing the same trend. Mid-September 2020 had good and satisfactory results for Punjab, Haryana, and Delhi on the AQI Index; however, the first and last month ten days showed a similar pattern of moderate and satisfactory results.\u003c/p\u003e\n\u003cp\u003eAQI Status in \u0026hellip; At 10 days period in September months in 2019\u0026ndash;2020\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eStatues of AQI in 2019\u0026ndash;2020 during October\u003c/h2\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e illustrated the temporal variations in the ten days average of AQI in Punjab, Haryana and Delhi, from October 2019\u0026ndash;2020. The AQI has been found to be poor in Delhi and the middle portion of Haryana, poor and moderate in some areas of Punjab and Haryana, Good in Panchkula in Haryana, and following the same trend throughout the month. Illustrates the changes in the AQI Index over time in Delhi, Punjab, and Haryana between October 1, 2020, and October 10, 2020. It should be mentioned that AQI data for a number of areas were temporarily unavailable. Consider information on the quality of the air in Punjab and Haryana. In Punjab, Haryana, and Delhi, the AQI has been determined to be moderate; in October of previous year, the AQI showed the same pattern in Punjab, but in Haryana and Delhi, it was poor and very poor.\u003c/p\u003e\n\u003cp\u003eAQI Status in \u0026hellip; At 10 days period in October months in 2019\u0026ndash;2020\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eStatues of AQI in 2019\u0026ndash;2020 during November\u003c/h2\u003e\n\u003cp\u003eThe variations in the AQI concentrations of observed in Delhi, Haryana and Punjab along with trend analysis. The corresponding values of the AQI concentration levels of can be found in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e from October 1, 2020, and October 10, 2020. These analyses provide insights into the changes in the AQI concentration levels over time. In Punjab the AQI has been determined to be Poor; in October of previous year, the AQI showed in Haryana and Delhi it was very poor and severe. But the last month of November the AQI Moderate in Punjab and some part of Haryana but other part of Haryana and Delhi the AQI is poor.\u003c/p\u003e\n\u003cp\u003eAQI Status in \u0026hellip; At 10 days period in November months in 2019\u0026ndash;2020\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSpatial variation in AQI in Punjab, Haryana and Delhi\u003c/h2\u003e \u003cp\u003eIn 2019, observed moderate to poor to very poor air quality in Punjab, while Haryana and Delhi had poor to very poor air quality due to industrial, stable environmental conditions for air pollution containment, construction that produced a significant amount of pollution in NCR cities, and increased turbulence activity from September to November, according to results reported by (Bhankhar et al. 2002). The lockdown period in 2020, which prevented work on automobiles, industries, and other construction projects, as well as cyclonic activity, heat convection maximums, and unpredictable environmental conditions from September to November, caused the air quality index to drop from satisfactory to good quality.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe outcome demonstrated that during the lockdown, the quality of the air improved. During the whole lock period in 2019, the air quality was worse than in 2020. The findings showed that the areas with the highest concentration of industrial areas\u0026mdash;Punjab, Haryana, and Delhi\u0026mdash;saw improvements in the air quality index. According to the survey, the AQI Serve was very poor in other districts of Punjab and Haryana and well developed in Delhi and the National Capital Region (NCR), which includes Gurugram, Faridabad, Palwal, Karnal, and Mahedergarh. Additionally, it was discovered that during the lockdown, the air temperature decreased in proportion to the reduction in greenhouse gas emissions. Important information on future urban growth and pollution management is provided by the research. In addition, there is a dearth of quantitative research on air quality and an abundance of elements, including weather and human activity that influence air quality. Future research is required to limit extrapolation error and investigate the links between other driving variables and air pollution for additional metropolitan areas by combining data from remote sensing and ground monitoring.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMr. S.K gives an idea about this research and helps in the collection of data from the CPCB site. All figureand table analysis and written work done by him. Ms. A.A. helped in downloading and arranging data,helped in download and anaysis in data and help in making map and graph.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eI especially thankful to Central Pollution Control Board for provided data on site https:// app. cpcbc cr. com/ AQI_India_ Iframe/. I thankful the Department of Agricultural Meteorology to provide meteorological data and fortheir guidance, constant encouragement and fruitful suggestion at all stages of research work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData collected from Central Control Pollution Board (CPCB) on daily basis on free of cost as available opensourceat web-link http://app.cpcbccr.com/AQI_India/\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBera, B., Bhattacharjee, S., Shit, P. K., Sengupta, N. \u0026amp; Saha, S. Significant impacts of COVID-19 lockdown on urban air pollution in Kolkata (India) and amelioration of environmental health. \u003cem\u003eEnviron. Dev. Sustain. \u003c/em\u003e23(5), 6913\u0026ndash;6940 (2021). \u003c/li\u003e\n\u003cli\u003eBao, R. \u0026amp; Zhang, A. Does lockdown reduce air pollution? Evidence from 44 cities in northern China. \u003cem\u003eSci. Total Environ. \u003c/em\u003e731, 139052 (2020).\u003c/li\u003e\n\u003cli\u003eBhanarkar, A. D., Gajghate, D. G. \u0026amp; Hasan, M. Z. Air pollution concentrations in Haryana subregion, India. \u003cem\u003eBull. Environ. Contam. Toxicol. \u003c/em\u003e\u003cstrong\u003e69\u003c/strong\u003e(5), 0690\u0026ndash;0695 (2002).\u003c/li\u003e\n\u003cli\u003eCorona virus: India enters \u0026rsquo;total lockdown\u0026rsquo; after spike in cases, 23 March 2020. https://www.bbc.com/news/world/asia/india\u003c/li\u003e\n\u003cli\u003eESRI, DeLorme, NAVTEQ, Tom Tom, Inter map Pcorp, GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, Kasdaster NL Ordnance.\u003c/li\u003e\n\u003cli\u003eSurvey, ESRI Japan, METI and the GIS User Community.\u003c/li\u003e\n\u003cli\u003eHashim, B. M., Al-Naseri, S. K., Al-Maliki, A. \u0026amp; Al-Ansari, N. Impact of COVID-19 lockdown on NO2, O3, PM2.5 and PM1.0 concentrations and assessing air quality changes in Baghdad, Iraq. \u003cem\u003eSci. Total Environ. \u003c/em\u003e754, 141978 (2021).\u003c/li\u003e\n\u003cli\u003eIQ Air. World air quality report regions and city ranking. (2019). https://gaspgroup.org/airquality/?gad_source=1\u0026amp;gclid=EAIaIQobChMI4rLGjOmThAMVBYJLBR3mZgCWEAAYASAAEgKYVfD_BwE Accessed 16 Mar 2021.\u003c/li\u003e\n\u003cli\u003eLe Qu\u0026eacute;r\u0026eacute;, C. \u003cem\u003eet al. \u003c/em\u003eTemporary reduction in daily global CO2 emissions during the COVID-19 forced confinement. \u003cem\u003eNat. Clim.\u003c/em\u003e \u003cem\u003eChang. \u003c/em\u003e1, 1\u0026ndash;7 (2020).\u003c/li\u003e\n\u003cli\u003eNational air quality index. https:// app. cpcbc cr. com/ AQI_ India_ Iframe. \u003c/li\u003e\n\u003cli\u003eNational air quality index, final report. (2015). http://app.cpcbccr.com/ccr_docs/FINAL-REPORT_AQI_.pdf\u003c/li\u003e\n\u003cli\u003eRanjan, A. K., Patra, A. K. \u0026amp; Gorai, A. K. Effect of lockdown due to SARS COVID-19 on aerosol optical depth (AOD) over urban and mining regions in India.\u003cem\u003e Sci. Total Environ. \u003c/em\u003e745, 141024 (2020).\u003c/li\u003e\n\u003cli\u003eSingh, D., Dahiya, M., Kumar, R. \u0026amp; Nanda, C. Sensors and systems for air quality assessment monitoring and management: A review. \u003cem\u003eJ. Environ. Manage. \u003c/em\u003e289, 112510 (2021).\u003c/li\u003e\n\u003cli\u003eS. Gowtham and K. Anjali, 2015, Ambience of Air Quality Analysis using AQI: IJIRST \u0026ndash;International Journal for Innovative Research in Science \u0026amp; Technology| Volume 1 | Issue 10 | ISSN (online): 2349-6010.\u003c/li\u003e\n\u003cli\u003eSingh, D., Nanda, C. \u0026amp; Dahiya, M. State of air pollutants and related health risk over Haryana India as viewed from satellite platform in COVID-19 lockdown scenario. \u003cem\u003eSpat. Inf. Res. \u003c/em\u003e30(1), 47\u0026ndash;62 (2022). \u003c/li\u003e\n\u003cli\u003eSharma, S., Zhang, M., Gao, J., Zhang, H. \u0026amp; Kota, S. H. Effect of restricted emissions during COVID-19 on air quality in India. \u003cem\u003eSci. Total Environ. \u003c/em\u003e728, 138878 (2020).\u003c/li\u003e\n\u003cli\u003eSiddiqui, A., Halder, S., Chauhan, P. \u0026amp; Kumar, P. COVID-19 pandemic and city-level nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e) reduction for urban centre\u0026rsquo;s of India. \u003cem\u003eJ. Indian Soc. Remote Sens. \u003c/em\u003e48(7), 999\u0026ndash;1006 (2020).\u003c/li\u003e\n\u003cli\u003eSrivastava, S., Kumar, A., Bauddh, K., Gautam, A. S. \u0026amp; Kumar, S. 21-day lockdown in India dramatically reduced air pollution indices in Lucknow and New Delhi, India. \u003cem\u003eBull. Environ. Contam. Toxicol. \u003c/em\u003e105(1), 9\u0026ndash;17 (2020).\u003c/li\u003e\n\u003cli\u003eSomani, M., Srivastava, A. N., Gummadivalli, S. K. \u0026amp; Sharma, A. Indirect implications of COVID-19 towards sustainable environment: An investigation in Indian context. \u003cem\u003eBioresour. Technol. Rep. \u003c/em\u003e11, 100491 (2020).\u003c/li\u003e\n\u003cli\u003eThe Economic Times, 23 March 2020 https://economictimes.indiatimes.com/news/politics-and-nation/after-janata-curfew-india-gets-ready-for-long\u003c/li\u003e\n\u003cli\u003eWHO. \u003cem\u003eWHO Global Urban Ambient Air Pollution Database \u003c/em\u003e(WHO, 2016).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Air Quality, Spatial and Temporal, Pollutants","lastPublishedDoi":"10.21203/rs.3.rs-4089995/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4089995/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe assessment of Delhi, Haryana, and Punjab's air quality is given in this paper. The Geo-spatial and temporal fluctuation of gaseous and particle pollutants over the whole countrywide lockdown period and the same month in the previous year 2019 (September to November) was estimated using geospatial approaches. The Central Pollution Control Board provided data on six fixed contaminants (CPCB). Within this framework, 2019 and 2020 air pollution statistics (PM\u003csub\u003e10\u003c/sub\u003e, PM\u003csub\u003e2.5\u003c/sub\u003e, O3, NOx, SO\u003csub\u003e2\u003c/sub\u003e, and CO\u003csub\u003e2\u003c/sub\u003e) were examined. The Air Quality Index's (AQI) spatial temporal distribution makes the difference between the lockdown and unlocks times quite evident. According to the results, the COVID-19 lockout caused the air quality to improve from extremely poor to satisfactory in 2019 and from satisfactory to good in 2020. Based on the findings, it will be determined that industry and automobiles have a big role in raising the concentration of pollutants.\u003c/p\u003e","manuscriptTitle":"Spatial and Temporal Variation in the Air Quality Index during COVID-19 in Punjab, Haryana and Delhi, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-10 18:35:32","doi":"10.21203/rs.3.rs-4089995/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dd423fce-9f1e-473c-9ca5-5f7d767ecf19","owner":[],"postedDate":"April 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30473969,"name":"Earth and environmental sciences/Climate sciences"},{"id":30473970,"name":"Earth and environmental sciences/Environmental sciences"},{"id":30473971,"name":"Physical sciences/Materials science"}],"tags":[],"updatedAt":"2024-04-10T18:43:35+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-10 18:35:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4089995","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4089995","identity":"rs-4089995","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}