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Responses to the COVID‐19 pandemic led to major reductions on air pollutant emissions in modern history. To date, there has been no comprehensive assessment for the impact of lockdowns on the vertical distributions of nitrogen dioxide (NO2) and formaldehyde (HCHO). Based on profiles from 0 to 2 km retrieved by Multi‐AXis‐Differential Optical Absorption Spectroscopy observation and a large volume of real‐time data at a suburb site in Shanghai, China, four types of machine learning models were developed and compared, including multiple linear regression, support vector machine, bagged trees (BT), and artificial neural network. Ultimately BT model was employed to reproduce NO2 and HCHO profiles with the best performance. Predictions with different meteorological and surface pollution scenarios were conducted from 2017 to 2019, for assessing the corresponding impacts on the changes of NO2 and HCHO profiles during COVID‐19 lockdown. The simulations illustrate that the NO2 decreased in 2020 by 43.8%, 45.5%, and 44.6%, relative to 2017, 2018, and 2019, respectively. For HCHO, the lockdown‐induced situation presented the declines of 28.6%, 32.1%, and 10.9%, respectively. In the comparisons of vertical distributions, NO2 maintained decreasing at all altitudes, while HCHO decreased at low altitudes and increased at high altitudes. During COVID‐19 lockdown, the reduction of NO2 and HCHO from the variation of surface pollutants was dominated below 0.5 km, while the relevant meteorological factors played a more significant role above 0.5 km. Plain Language Summary: This study evaluated the impact of COVID‐19 lockdown on the vertical distributions of NO2 and HCHO by developing the machine‐learning (ML) air pollution prediction models. The ML model allows us to quantify the timing and magnitude influencing real‐world air quality responses to surface pollution scenarios and meteorological factors. Compared with the simulations for vertical profiles in the normal scenarios, it can be found that NO2 maintained decreasing at all altitudes, while HCHO decreased at low altitudes and increased at high altitudes. In addition, the lockdown‐induced NO2 and HCHO were mainly driven by meteorological factors and surface pollutants above and below 0.5 km, respectively. Key Points: The machine learning model was applied to reproduce NO2 and HCHO profiles for the first timeQualifying the vertical distribution of reductions during COVID‐19 lockdown relative to the normal scenarioThe lockdown‐induced NO2 and HCHO were mainly driven by meteorological factors and surface pollutants above and below 0.5 km, respectively [ABSTRACT FROM AUTHOR]

The emergence of the novel corona virus and the resulting lockdowns over various parts of the world have substantially impacted air quality due to reduced anthropogenic activity. The objective of this study is to investigate the impact of COVID-19 lockdown and Spring Festival on air quality of four major cities of Yangtze River Delta (YRD) region, including Shanghai, Nanjing, Hefei, and Hangzhou. In situ measurements were taken for nitrogen dioxide (NO2), particulate matter (PM2.5) and ozone (O3). In situ measurements from 1 January to 25 April were taken two years prior to COVID-19 (2018–19), during COVID-19 lockdown (2020), and one year after the COVID-19 (2021). The results indicated that the concentration of NO2 and PM2.5 dropped considerably during the lockdown days compared to normal days while the O3 concentration showed an upsurge. The NO2 showed reduction of about 54% on average during lockdown level 1 in 2020 whereas, PM 2.5 showed reduction of about 36% through the YRD. A substantial drop was observed in concentration of NO2 during the Spring Festival holidays throughout the YRD from 2019 to 2021. [ABSTRACT FROM AUTHOR]

Reduced mobility and less anthropogenic activity under special case circumstances over various parts of the world have pronounced effects on air quality. The objective of this study is to investigate the impact of reduced anthropogenic activity on air quality in the mega city of Shanghai, China. Observations from the highly sophisticated multi-axis differential optical absorption spectroscope (MAX-DOAS) instrument were used for nitrogen dioxide (NO2) and formaldehyde (HCHO) column densities. In situ measurements for NO2, ozone (O3), particulate matter (PM2.5) and the air quality index (AQI) were also used. The concentration of trace gases in the atmosphere reduces significantly during annual Spring Festival holidays, whereby mobility is reduced and anthropogenic activities come to a halt. The COVID-19 lockdown during 2020 resulted in a considerable drop in vertical column densities (VCDs) of HCHO and NO2 during lockdown Level-1, which refers to strict lockdown, i.e., strict measures taken to reduce mobility (43% for NO2; 24% for HCHO), and lockdown Level-2, which refers to relaxed lockdown, i.e., when the mobility restrictions were relaxed somehow (20% for NO2; 22% for HCHO), compared with pre-lockdown days, as measured by the MAX-DOAS instrument. However, for 2019, a reduction in VCDs was found only during Level-1 (24% for NO2; 6.62% for HCHO), when the Spring Festival happened. The weekly cycle for NO2 and HCHO depicts no significant effect of weekends on the lockdown. After the start of the Spring Festival, the VCDs of NO2 and HCHO showed a decline for 2019 as well as 2020. Backward trajectories calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated more air masses coming from the sea after the Spring Festival for 2019 and 2020, implying that a low pollutant load was carried by them. No impact of anthropogenic activity was found on O3 concentration. The results indicate that the ratio of HCHO to NO2 (RFN) fell in the volatile organic compound (VOC)-limited regime. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 pandemic and consequent lockdowns all over the world have had various impacts on atmospheric quality. This study aimed to investigate the impact of the lockdown on the air quality of Nanjing, China. The off-axis measurements from state-of-the-art remote-sensing Multi-Axis Differential Optical Absorption Spectroscope (MAX-DOAS) were used to observe the trace gases, i.e., Formaldehyde (HCHO), Nitrogen Dioxide (NO2), and Sulfur Dioxide (SO2), along with the in-situ time series of NO2, SO2 and Ozone (O3). The total dataset covers the span of five months, from 1 December 2019, to 10 May 2020, which comprises of four phases, i.e., the pre lockdown phase (1 December 2019, to 23 January 2020), Phase-1 lockdown (24 January 2020, to 26 February 2020), Phase-2 lockdown (27 February 2020, to 31 March 2020), and post lockdown (1 April 2020, to 10 May 2020). The observed results clearly showed that the concentrations of selected pollutants were lower along with improved air quality during the lockdown periods (Phase-1 and Phase-2) with only the exception of O3, which showed an increasing trend during lockdown. The study concluded that limited anthropogenic activities during the spring festival and lockdown phases improved air quality with a significant reduction of selected trace gases, i.e., NO2 59%, HCHO 38%, and SO2 33%. We also compared our results with 2019 data for available gases. Our results imply that the air pollutants concentration reduction in 2019 during Phase-2 was insignificant, which was due to the business as usual conditions after the Spring Festival (Phase-1) in 2019. In contrast, a significant contamination reduction was observed during Phase-2 in 2020 with the enforcement of a Level-II response in lockdown conditions i.e., the easing of the lockdown situation in some sectors during a specific interval of time. The observed ratio of HCHO to NO2 showed that tropospheric ozone production involved Volatile Organic Compounds (VOC) limited scenarios. [ABSTRACT FROM AUTHOR]