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COVID-19 Lockdown-Induced Changes in NO2 Levels Across India Observed by Multi-Satellite and Surface Observations

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COVID-19 Lockdown-Induced Changes in NO2 Levels Across India Observed by Multi-Satellite and Surface Observations Atmos. Chem. Phys., 21, 5235–5251, 2021 https://doi.org/10.5194/acp-21-5235-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. COVID-19 lockdown-induced changes in NO2 levels across India observed by multi-satellite and surface observations Akash Biswal1,2, Vikas Singh1, Shweta Singh1, Amit P. Kesarkar1, Khaiwal Ravindra3, Ranjeet S. Sokhi4, Martyn P. Chipperfield5,6, Sandip S. Dhomse5,6, Richard J. Pope5,6, Tanbir Singh2, and Suman Mor2 1National Atmospheric Research Laboratory, Gadanki, AP, India 2Department of Environment Studies, Panjab University, Chandigarh 160014, India 3Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India 4Centre for Atmospheric and Climate Physics Research (CACP), University of Hertfordshire, Hatfield, UK 5School of Earth and Environment, University of Leeds, Leeds, UK 6National Centre for Earth Observation, University of Leeds, Leeds, UK Correspondence: Vikas Singh ([email protected]) Received: 1 October 2020 – Discussion started: 13 October 2020 Revised: 9 February 2021 – Accepted: 2 March 2021 – Published: 1 April 2021 Abstract. We have estimated the spatial changes in NO2 lev- urban areas as the decrease at the surface was masked by en- els over different regions of India during the COVID-19 lock- hancement in NO2 due to the transport of the fire emissions. down (25 March–3 May 2020) using the satellite-based tro- pospheric column NO2 observed by the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instru- ment (TROPOMI), as well as surface NO2 concentrations 1 Introduction obtained from the Central Pollution Control Board (CPCB) C monitoring network. A substantial reduction in NO2 levels Nitrogen oxides, NOx (NO NO2), are one of the major was observed across India during the lockdown compared air pollutants, as defined by various national environmen- to the same period during previous business-as-usual years, tal agencies across the world, due to their adverse impact except for some regions that were influenced by anomalous on human health (Mills et al., 2015). Furthermore, tropo- fires in 2020. The reduction (negative change) over the ur- spheric levels of NOx can affect tropospheric ozone forma- ban agglomerations was substantial (∼ 20 %–40 %) and di- tion (Monks et al., 2015), contribute to secondary aerosol rectly proportional to the urban size and population density. formation (Lane et al., 2008) and acid deposition, and im- Rural regions across India also experienced lower NO2 val- pact climatic cycles (Lin et al., 2015). The major anthro- ues by ∼ 15 %–25 %. Localised enhancements in NO2 asso- pogenic sources of NOx emissions include the combustion of ciated with isolated emission increase scattered across India fossil fuels in road transport, aviation, shipping, industries, were also detected. Observed percentage changes in satellite and thermal power plants (e.g. USEPA and CATC, 1999; and surface observations were consistent across most regions Ghude et al., 2013; Hilboll et al., 2017). Other sources in- and cities, but the surface observations were subject to larger clude open biomass burning (OBB), mainly large-scale for- variability depending on their proximity to the local emission est fires (e.g. Hilboll et al., 2017), lightning (e.g. Solomon et sources. Observations also indicate NO2 enhancements of up al., 2007), and emissions from soil (e.g. Ghude et al., 2010). to ∼ 25 % during the lockdown associated with fire emissions NOx hotspots are often observed over regions with large ther- over the north-east of India and some parts of the central re- mal power plants and industries as well as urban areas with gions. In addition, the cities located near the large fire emis- significant traffic volumes causing large localised emissions sion sources show much smaller NO2 reduction than other (e.g. Prasad et al., 2012; Hilboll et al., 2013; Ghude et al., 2013). Published by Copernicus Publications on behalf of the European Geosciences Union. 5236 A. Biswal et al.: COVID-19 lockdown-induced changes in NO2 levels With growing scientific awareness of the adverse impacts and the movement of the people was restricted, resulting in a of air pollution, the number of air quality monitoring sta- considerable reduction in the anthropogenic emissions. The tions has expanded to over 10 000 across the globe (Ven- restrictions were relaxed in a phased manner from the third ter et al., 2020). Additionally, multiple satellite instruments phase onwards in less affected areas by permitting activities such as the Global Ozone Monitoring Instrument (GOME) and partial movement of people (MHA, 2020). on ERS-2, the Scanning Imaging Absorption Spectrom- A decline in NO2 levels over India during the lockdown eter for Atmospheric Cartography (SCIAMACHY, 2002– has been reported from both surface observations (Singh et 2012) on Envisat, the Ozone Monitoring Instrument (OMI, al., 2020; Sharma et al., 2020; Mahato et al., 2020) and satel- 2005–present) on Aura, GOME-2 (2007–present) on MetOp, lite observations (ESA, 2020; Biswal et al., 2020; Siddiqui et and the TROPOspheric Monitoring Instrument (TROPOMI, al., 2020; Pathakoti et al., 2020) against the previous year or 2017–present) on Sentinel-5P (S5P) have monitored NO2 average of a few previous years. A detailed study by Singh pollution from the space for over 2 decades. Surface sites typ- et al. (2020) based on 134 sites across India reported a de- ically measure NO2 in concentration quantities (e.g. in units cline of ∼ 30 %–70 % in NO2 during lockdown with respect −3 of µg m ), but satellite NO2 measurements are retrieved as to the mean of 2017–2019, with the largest reduction being integrated vertical columns (e.g. tropospheric vertical col- observed during peak morning traffic hours and late evening umn density, VCDtrop). The latter is preferred for studying hours. While Sharma et al. (2020) reported a smaller de- NO2 trends and variabilities because of global spatial cov- crease (18 %) in NO2 for selected sites against the levels dur- erage and spatio-temporal coincidence with ground-based ing 2017–2019, Mahato et al. (2020) found a decrease of over measurements (Martin et al., 2006; Kramer et al., 2008; Lam- 50 % in Delhi for the first phase of lockdown against previ- sal et al., 2010; Ghude et al., 2011). NO2 has been reported ous years (2017–2019), which was also confirmed by Singh to increase in south Asian countries (Duncan et al., 2016; et al. (2020) for the extended period of analysis. The satellite- Hilboll et al., 2017; ul-Haq et al., 2017) and decrease over based studies by Biswal et al. (2020) and Pathakoti et al. Europe (van der A et al., 2008; Curier et al., 2014; Georgou- (2020) estimated the change in NO2 levels using OMI ob- lias et al., 2019) and the United States (Russell et al., 2012; servations, whereas Siddiqui et al. (2020) used TROPOMI to Lamsal et al., 2015). In the case of India, a tropospheric NO2 compute the change over eight major urban centres of India. increase was observed during the 2000s (e.g. Mahajan et al., Biswal et al. (2020) reported that the average OMI NO2 over 2015), but since 2012 it has either stabilised or even declined India decreased by 12.7 %, 13.7 %, 15.9 %, and 6.1 % dur- owing to the combined effect of economic slowdown and ing the subsequent weeks of the lockdown relative to similar adoption of cleaner technology (e.g. Hilboll et al., 2017). periods in 2019. Similarly, Pathakoti et al. (2020) reported a However, thermal power plants, megacities, large urban ar- decrease of 17 % in average OMI NO2 over India compared eas, and industrial regions remain NO2 emission hotspots to the pre-lockdown period and a decrease of 18 % against (Ghude et al., 2008, 2013; Prasad et al., 2012; Hilboll et al., the previous 5-year average. Moreover, both studies reported 2013, 2017; Duncan et al., 2016). Moreover, despite the mea- a larger reduction of more than 50 % over Delhi. Similarly, sures taken to control NOx emissions, urban areas often ex- Siddiqui et al. (2020) also reported an average reduction of ceed national ambient air quality standards in India (Sharma 46 % in the eight cities during the first lockdown phase with et al., 2013; Nori-Sarma et al., 2020; Hama et al., 2020) and respect to the pre-lockdown phase. While recent studies have thus require a detailed scenario analysis. used either only satellite observations or only surface obser- The nationwide lockdown in various countries during vations, this study goes further by adopting an integrated ap- March–May 2020, due to the outbreak of COVID-19, re- proach by combining both measurement types to investigate duced traffic and industrial activities, leading to a signifi- NO2 level changes over India in response to the COVID- cant reduction of NO2. Studies using space-based and surface 19 pandemic using OMI, TROPOMI, and surface observa- observations of NO2 have reported reductions in the range tions over different regions. As both OMI and TROPOMI of ∼ 30 %–60 % for China, South Korea, Malaysia, West- have similar local overpass times of approximately 13:30 ern Europe, and the USA (Bauwens et al., 2020; Kanniah (Penn and Holloway, 2020; van Geffen et al., 2020), diur- et al., 2020; Muhammad et al., 2020; Tobías et al., 2020; nal influences on the retrievals of NO2 for both instruments Dutheil et al., 2020; Liu et al., 2020; Huang and Sun, 2020; are similar. Moreover, as both instruments use nearly simi- Naeger and Murphy, 2020; Barré et al., 2020; Goldberg et lar retrieval schemes (i.e. differential optical absorption spec- al., 2020) against the same period in previous years, with the troscopy, DOAS), their NO2 measurements are believed to be observed reductions strongly linked to the restrictions im- comparable with a suitable degree of confidence (van Geffen posed on vehicular movement.
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