We obtained hourly concentrations of ground-level O3, NO2, and particulate matter of 2.5 µm and smaller (PM2.5) recorded at ∼1700 stations in China during 2019–2022 from the China National Environmental Monitoring Centre (https://quotsoft.net/air/, last access: 5 July 2022). The ambient concentrations of O3, NO2 and PM2.5 are measured by an automated monitoring system at each site and reported to the China National Environmental Monitoring Centre and published online after validation (Wang et al., 2014). O3, NO2 and PM2.5are measured with UV photometry, chemiluminescence, and micro-oscillating balance or β absorption, respectively, with a detection limit of 2 ppb, 2 ppb and 2 µgm-3, respectively (https://www.mee.gov.cn/, last access: 15 September 2022). The national network has 10 stations in Shanghai in 2019–2020, most of which are situated within the city centre. Since 2021, the number of stations has increased to 20, with most newly added sites located outside the city centre (refer to Figs. 1 and S1 in the Supplement for their locations). (Note there were no data from one site (Dianshanhu) in 2021–2022; thus the data from 19 stations are available for the years 2021 and 2022). The maximum daily 8 h average (MDA8) O3 concentration was calculated for each site as the highest value of the 24 8 h moving average O3 concentrations for a given day. The daily average concentrations of the other pollutants (NO2 and PM2.5) were also calculated from the hourly data. The 14 d moving averages of the surface pollutant concentrations were calculated, as these had fewer fluctuations than daily concentrations and thus better revealed trends. Finally, the daily average mixing ratios of Ox (=O3+NO2) were calculated to account for the titration effect of nitric oxide (NO) on changes in O3 concentration.

Satellite data were used to investigate the spatiotemporal variations in tropospheric formaldehyde (HCHO) and NO2 column concentrations during the 2022 LCD period and the same period in 2021. We obtained Sentinel-5P Level 3 offline products (HCHO and NO2) using the TROPOspheric Monitoring Instrument (TROPOMI) from the Google Earth Engine (GEE; https://earthengine.google.com/, last access: 19 July 2022) cloud-based platform, which is an open-source processing system based on JavaScript (Ghasempour et al., 2021). The Sentinel-5P Level 3 offline products were converted from the original Sentinel-5P Level 2 offline data (at a resolution of 5.5×3.5 km) by GEE using the harpconvert tool (https://cdn.rawgit.com/stcorp/harp/master/doc/html/harpconvert.html, last access: 19 July 2022) and subjected to a data quality control process, in which pixels with data quality values less than 75 % for NO2 and less than 50 % for HCHO were removed. Based on the GEE platform, we imported the daily image collections of HCHO and NO2, cut them in accordance with the administrative boundary shapefiles of Shanghai (generated from publicly available geoscience data on the DataV.GeoAtlas platform; http://datav.aliyun.com/portal/school/atlas/area_generator, last access: 19 July 2022) using a .clip() script (Gorelick et al., 2017), and then averaged the values of all the remaining pixels within the city border to obtain the daily mean concentrations of HCHO and NO2. A similar satellite data processing method was used for the YRD region.

We acquired surface site meteorological data (2 m temperature, 2 m relative humidity (RH), 10 m wind direction and 10 m wind speed) from 78 weather stations in Shanghai during April–May in 2021 and 2022, together with gridded meteorological data (2 m temperature, 1000 hPa RH, downward ultraviolet (UV) radiation at the surface, total cloud cover, total precipitation and boundary layer height) from European Centre for Medium-Range Weather Forecast reanalysis v5 (ERA5) (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels, last access: 12 July 2022; https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels, last access: 12 July 2022). We calculated monthly averages of the surface-observed meteorological data in 2021 and 2022 and the changes in gridded meteorological data between 2022 and 2021 to determine the spatiotemporal variations in meteorological conditions in Shanghai and its surrounding regions.

The 24 h backward trajectories for Shanghai were calculated at 1 h intervals during April–May 2022 using MeteoInfoMap software (Wang, 2014, 2019) and meteorological data from the Global Data Assimilation System (ftp://arlftp.arlhq.noaa.gov/pub/archives/gdas1/, last access: 18 July 2022). The endpoints of the trajectories were 500 m above ground level of Shanghai (31.23∘ N, 121.47∘ E). Cluster classification was then conducted to divide the trajectories of O3 exceedance days into five groups based on the origins of air mass.

We classified the aforementioned 19 environmental monitoring sites in Shanghai into 4 types based on land use and mean HCHO/NO2 ratios (Figs. 1 and 8b). The type A sites (12 sites) are in the city centre (and almost all are within the Shanghai Outer Ring Expressway) and had the lowest HCHO/NO2 ratios; type B sites are sites in the city perimeter (4 sites) that had moderate HCHO/NO2 ratios; type C sites are semi-rural sites (2 sites) that had the largest HCHO/NO2 ratios; and the type D site (1 site) is located near the wetland park in the East Chongming Tidal Flat and is least affected by urban emissions but may be influenced by ship emissions. Based on the above classification, we conducted regression analyses between the surface MDA8 O3 concentrations and daily mean NO2 concentrations for three types of sites (A, B and C) to examine the O3 formation regime during the 2022 LCD in Shanghai's city centre and city perimeter and at semi-rural sites.

Figure 2 presents the MDA8 O3 and daily average NO2 concentrations for the first 5 months of 2021–2022 at the 19 sites in Shanghai. In April–May 2022, the concentrations of NO2, derived largely from fossil-fuel combustion, decreased by 49 % year-on-year, but the average MDA8 O3 concentrations increased by 12.5 %. (In contrast, PM2.5 concentrations fell by 30.3 % in Shanghai; Fig. S2b.) The MDA8 O3 concentrations exceeded 160 µgm-3, which is China's Ambient Air Quality Standard for O3, at 1 or more of the 19 sites on 21 d in April–May 2022, with the highest value being 200 µgm-3. The average Ox (O3+NO2) mixing ratio in April–May 2022 also increased by 2.2 % during the LCD compared with the same period in 2021 (Fig. S2a). These observations indicate that there was significant ground-level O3 pollution in Shanghai during the 2022 LCD, despite the drastic reductions in human activity. The decrease in NO2 concentrations (49 %) during the 2022 LCD was larger than the NO2 decrease during the full-scale LCD phase in 2020 (23 January–12 February), when the average NO2 concentration decreased by 30.5 % from the corresponding period in 2019 (Fig. S3b). During the 2020 LCD, the average MDA8 O3 concentrations in Shanghai increased by 13.8 % but remained far below the ambient O3 concentration standard (Fig. S3a).

Figure 3a–c show the spatial distribution of the MDA8 O3 concentrations in mainland China and the YRD region, which consists of Shanghai and three neighbouring provinces (Jiangsu, JS; Anhui, AH; and Zhejiang, ZJ), and Shanghai during the 2022 LCD, respectively. It can be seen that elevated O3 concentrations were observed at most sites in JS, in the southern part of ZJ and in the eastern part of AH. These provinces are known to have close economic ties to Shanghai.

The increase in MDA8 O3 concentrations during the 2022 LCD was not restricted to Shanghai. Figure 3d–f show the spatial distribution of changes in MDA8 O3 concentrations from 2021 to 2022 at the national, regional and city scales, respectively. The MDA8 O3 concentrations clearly increased in central and eastern regions but decreased in south-western, north-western and north-eastern regions (Fig. 3d). The YRD region recorded one of the greatest increases in MDA8 O3 concentrations (17.4 µgm-3) during the 2022 LCD (Fig. 3e). Within Shanghai, the year-on-year increase in MDA8 O3 concentrations decreased from urban to semi-rural areas, with the largest increase recorded in the Putuo district in the city centre (32.9 µgm-3) (Fig. 3f).

Figure 4 depicts the spatial distributions of TROPOMI-based tropospheric column concentrations of HCHO and NO2 and the HCHO/NO2 column ratios in the YRD region. During the 2022 LCD and compared with the same period in 2021, the column concentrations of HCHO, derived from both direct emissions and degradation of anthropogenic and natural VOCs, decreased by 10.8 % (Fig. 4a), and the NO2 column concentrations decreased by 25.1 % (Fig. 4b). The magnitudes of the reductions in HCHO and NO2 column concentrations had similar spatial distributions, with the largest reductions observed in the region's major cities (Shanghai, Suzhou, Nanjing and Hangzhou). This indicated that the reductions in both the NO2 and HCHO column concentrations were related to decreases in anthropogenic activity during the 2022 LCD. Due to a larger decrease in NO2 concentrations than in HCHO concentrations, the average HCHO/NO2 ratio increased from 2.57 in 2021 to 2.96 in 2022 in the YRD region (Fig. 4c). In Shanghai, the HCHO and NO2 column concentrations decreased by 19.4 % and 49.2 %, respectively, during the 2022 LCD (see Sect. 3.3.2 for a detailed discussion). In comparison, the TROPOMI-based HCHO and NO2 column concentrations in February 2020 showed 17 % and 38 % decreases, respectively, in the YRD region compared with the same month in 2019 (Stavrakou et al., 2021). The much larger reduction in NO2 concentrations than in HCHO concentrations during the 2022 LCD is attributable to the fact that NOx is mainly emitted by transportation activities (which exhibited the greatest decrease during the 2022 LCD) and by power generation, whereas VOCs are derived from more diverse sources. In Shanghai, the main VOC sources are vehicular exhaust; evaporation of fuels, paints and solvents; petrochemical industries; liquefied petroleum gas; and biogenic sources (Lin et al., 2020; Han et al., 2022).