Figure 1 shows the NO₂^TROPOMI averaged during three periods and the relative changes between them. “P3 versus P1” means the relative change of NO₂^TROPOMI between P3 and P1. It is clear that NO₂^TROPOMI decreased greatly in P2 relative to P1, and there is a limited recovery during P3, in accordance with a previous report ^[1]. The levels of NO₂^TROPOMI can be controlled by many factors, including anthropogenic NOx emissions, meteorology (such as sunlight, precipitation, advection, and convection), and other pollution emissions.

Table 1 shows the NO₂^TROPOMI changes in eight selected regions, which would be discussed in more detail in Section 3.3. Overall, in East China, the NO₂^TROPOMI decreased by 52% from P1 to P2 and increased by 19% from P2 to P3. The averaged NO₂^TROPOMI increase of 0.3 × 10¹⁵ molecules/cm² from P2 to P3 only recovered 14% of the NO₂^TROPOMI decrease from P1 to P2 (2.1 × 10¹⁵ molecules/cm²).

The top-down NOx emissions (as derived in Section 2.3) averaged during the three periods and the relative changes between them are shown in Figure 2 and Table 2. The top-down NOx emission for East China was estimated as 1589.3 ± 449.8 Gg/month during P1, compared to 1250.6 Gg/month estimated by the bottom-up emission inventory (MEIC). Because the focus of this research is on the relative changes of top-down emissions, the differences between top-down and bottom-up emissions are not discussed. NOx emissions decreased from P1 to P2 (Figure 2g) and increased from P2 to P3 (Figure 2h) in almost all regions in East China, consistent with emissions being the main driver of NO₂^TROPOMI changes during the periods. Overall, in East China, NOx emissions decreased by 50% from P1 to P2 and increased by 26% from P2 to P3. As a result, the NOx emissions during P3 were still 37% lower than the ones during P1. NOx emissions only recovered 206 Gg/month from P1 to P3, which was 26% of the emission decrease (794 Gg/month) from P1 to P2 (Figure 2i). Hereafter, an emission recovery refers to regain the emission decrease from P1 to P2 (i.e., P2-P1) in P3.

The top-down NOx emissions decreased most in North China and Central China (e.g., Shandong) during P2 versus P1, while those in Southwest China (e.g., Chongqing) merely changed (Table 2, Table S1).

Although top-down NOx emissions changes (P2vP1: −50%, P3vP2: 26%) were very close to NO₂^TROPOMI changes (P2vP1: −52%, P3vP2:19%) in East China, the discrepancies between the two were evident at the provincial level. Between P1 and P2, in Jilin, Chongqing, Yunnan, and Sichuan, the relative changes of NO₂^TROPOMI were −54%, −30%, −2%, and −35%, respectively, and those of top-down NOx emissions were −10%, 1%, −39%, and −20%, respectively. Between P2 and P3 in Shandong, Zhejiang, and Hunan, the relative changes of NO₂^TROPOMI were 26%, 38%, and 33%, respectively, and these of top-down NOx emissions were 48%, 67%, and 85%, respectively.

This implies that the recovery of human activity and subsequent anthropogenic emissions was much faster than what is implied by the NO₂^TROPOMI in these regions. NO₂^TROPOMI changes are dependent on both NOx emission changes and meteorological changes. For example, it is likely that increasing precipitation, higher temperature, and stronger sunlight would shorten NOx lifetime and decrease NO₂^TROPOMI after February, given fixed NOx emissions. Assuming that WRF-GC reasonably captured the meteorological impact on NO₂, NO₂^WRF-GC can serve as a baseline which shows how tropospheric NO₂ VCDs should have behaved with changing meteorology but fixed emissions. The top-down NOx emissions, which were derived partly based on NO₂^WRF-GC, were largely independent of meteorological factors. Still, the top-down NOx emissions were subject to the uncertainties of both WRF-GC, TROPOMI retrievals, and bottom-up emissions. However, as this research focuses on the relative changes of top-down NOx emissions, as long as there is no systematic bias of temporal changes of both WRF-GC simulation and TROPOMI retrievals, we consider the results presented here to be reasonable. In East China, where primary sources of NOx emissions are anthropogenic, the actual anthropogenic NOx emission changes can be better captured by top-down NOx emission changes. The changes of NO₂^TROPOMI can be significantly larger or smaller than the changes of NOx emission in individual regions. Therefore, one needs to be careful when attributing the changes of NO₂^TROPOMI solely to the changes of human activity.

Figure 3 better illustrates the top-down NOx emission changes in each region. The recovery rate can be measured by the relative changes of top-down emissions between P3 and P1, as shown by the colored contours. The contour of “relative change P3vP1 = 0%” means a full recovery from the emission decrease in P2. Most regions have decreased emissions between P1 and P2 and increased emissions between P2 and P3. Only Ningxia and Hunan have increased emissions in P3 compared to P1, while other regions have not fully recovered in P3.

To better understand the different emission reduction and recovery patterns, we examined the timeseries of daily regional top-down emissions of the eight selected regions in Figure 4. These regions serve as good examples of different emission change patterns. As the daily top-down NOx emissions have high day-to-day fluctuations, we also presented 14-day central moving averages in Figure 4 to better reflect the general trends. We included similar time-series of all regions, for more information see the Supplementary Materials. For readers’ references, we included several reference lines: the monthly emissions from the MEIC emission inventories, the dates for Wuhan lockdown, and official nationwide back-to-work day. The MEIC emissions serve as references on how the emissions should change temporally.

The official holidays for Chinese New Year were from January 24 to February 2, within P2 (January 23 to February 9). This may partly explain why we see the top-down NOx emission decreased steadily before Wuhan lockdown. Before the official holidays started, the business activities decreased as people may use paid time-off to travel back to their hometowns and unite with families. Moreover, it might be possible that some small businesses were taking extra caution and halted their operations even before Wuhan lockdown. The Chinese government prolonged the holidays to February 9 for spreading control purpose, which would certainly contribute to the emission decrease during P2.

Lin et al. (2011) estimated that the emission reduction associated with the Chinese New Year is about 10% in January 2009 using multiple satellite retrievals ^[7]. Gu et al. (2014) found that the top-down NOx emission estimated using OMI and the Global Ozone Monitoring Experiment-2 (GOME-2) retrievals decreased by 35% and 31% from January to February and increased by about 13% and 27% from February to March during 2011 in China ^[8]. Meanwhile, the bottom-up NOx emissions from MEIC showed little temporal changes in the study period (Figure 4, Table A1 in the Appendix).

In this study, we observed much more evident reduction (−50%) between P1 and P2 in East China and the emissions remained at low level during P3 compared to P1 (−37%). It is likely that a significant portion of the emission reductions are COVID-19 related.

The slow NOx emission increase during P3 after the prolonged holidays implied that the human activity was slowly recovering. During P3, the emissions only recovered 26% and might need at least a few months to reach its early January level at current rate. We would not anticipate such slow recovery after holidays under normal circumstances.

Future studies may compare the TROPOMI-based top-down NOx emission changes in early 2020 to the climatology of them to better quantify the impact of COVID-19. As of April 2020, TROPOMI NO₂ retrievals are only available at a different version for early 2019 so that they are not directly comparable.

Even if the COVID-19-related control measures such as mandatory business halt and social distance were not enforced anymore, there could be impact on the economy if people lost their jobs, businesses went bankrupt, and people spent less for fear of an economic recession. This aftershock of COVID-19 might partly explain the slow recovery during P3.

Besides the economic interruption in China, the slow recovery of NOx emissions may result from the change of foreign economies. As COVID-19 became a global pandemic, it affected the global economy besides Chinese economy. Previous studies have shown that the previous 2007–2009 global economic recession may have reduced Chinese NOx emissions by ~20% ^[7][9]. Although the exports of goods and services as a percentage of GDP decreased from 32% in 2008 to 20% in 2018 ^[10], the decreasing demand from other countries would nevertheless impact Chinese businesses focusing on exports and the domestic suppliers.

By April 19th, 2020, more than 80 countries have established lockdown or other control measures in March and early April and the lockdown continues with numerous businesses closed ^[11]. Applying the method of this study to derive the different emission changes corresponding to the different control measures would be important to (1) understand how the control measures affected the environment and (2) evaluate how to minimize the economy interruption (partly reflected by the emission changes) while controlling the spread of virus.

This study focuses on the changes of NOx since it is a better indicator of human activity. Future studies may also perform similar analyses using satellite retrievals of SO₂, CH₄, CHOCHO, and aerosol optical depth (AOD). A comprehensive analysis on different atmospheric components would help us better understand the activity changes of each sector (e.g., powerplant, industry, transportation, and residential) and their impact on the environment and climate.

The early results of NO₂^TROPOMI in East China and Wuhan were released by NASA and European Space Agency ^[1] and drew considerable attention from mass media. Although we found that the difference between the relative changes of NO₂^TROPOMI and top-down NOx emissions during the study period was limited (<10%) in East China, the difference was evident in specific provinces, as discussed in Section 3.2. Although NO₂^TROPOMI and surface NO₂ concentrations are directly measured by satellite instruments and governmental monitoring systems, they are affected by both NOx emission and meteorology. Hereby, they are not direct measures of anthropogenic activities. It is possible that these NO₂ concentration measures show different directions of changes compared to those of NOx emissions, like the case in Chongqing (Section 3.2). Future media releases may want to be cautious about the implications of NO₂^TROPOMI changes.