*3.3. Impact of Pandemic Prevention and Control on Air Quality*

The reduction in air pollution is closely related to the PPC policy. During the period with first-level PPC measures, the PCRs of AQI and the concentrations of six air pollutants (SO2, NO2, CO, O3, PM10 and PM2.5) were −21.97%, 0.26%, −28.95%, −12.00%, 8.30%, −20.01% and −23.01%, respectively. During the period with second-level PPC measures, the PCRs were −17.97%, 7.55%, −11.82%, −12.30%, −9.84%, −10.71% and −25.55%, respectively. During the period with third-level PPC measures, the PCRs were −10.29%, 13.02%, 5.09%, −1.70%, −4.96%, −6.92% and −14.99%, respectively (Table 3). It can be seen that, except for SO2 and O3, the AQI and concentrations of other pollutants were significantly reduced under the PPC measures. In turn, the improvement of air quality could help reduce the spread of COVID-19 and play a positive role in PPC [33,34].

The first-level response was ordered by the State Council of the People's Republic of China, and the provincial government organized and coordinated the provincial emergency response under the unified leadership and command. The second-level response was deployed by the provincial government, and the third-level emergency plan in response was formulated by the municipal and county governments. Therefore, the control force and restriction policies in different provinces may be different, resulting in different impacts of emergency responses on air quality in different provinces. Some studies have shown that due to travel restrictions during the pandemic, AQI and concentrations of NO2, CO, PM10 and PM2.5 in cities of northern China decreased by 7.80%, 24.7%, 4.58%, 13.7% and 5.93%, respectively [1]. For cities in the Guangdong–Hong Kong–Macao Greater Bay Area, the AQI and concentrations of the above four pollutants were reduced by 37.4%, 47.0%, 24.1%, 44.8% and 40.5% during the period with first-level PPC measures and by 24.4%, 25.5%, 23.2%, 25.6% and 32.5% during the period with second-level PPC measures, which were 27.1%, 12.1%, 9.86%, 24.1% and 31.0% during the period with third-level PPC measures [24]. Therefore, the air quality in Jiangsu was more likely to be affected by the PPC policies compared with that in cities of northern China, but the sensitivity of air quality to restrictive policies was slightly lower than that in the Pearl River Delta.

NO2 was the pollutant most sensitive to the PPC policies (Figure 3). The higher the PPC level, the higher was the reduction of NO2. The PCRs of NO2 concentration under the first-, second- and third-level responses decreased by 28.95%, 11.82% and 5.09%, respectively. As the NO2 in the atmosphere is mainly from fossil fuel combustion, vehicle exhaust and industrial production emissions, with the relaxation of PPC and the recovery of normal production and living, the concentration of NO2 rose again.

The CO in the atmosphere is mainly from the incomplete combustion of fossil fuels and biofuels [11]. During the period in response to PPC measures, CO emissions from domestic boilers and power stations were significantly affected. The PCRs of CO concentrations in the first-, second- and third-level responses decreased by 12.00%, 12.30% and 1.70%, respectively. In the first- and second-level responses to PPC policies, CO was wellcontrolled. After the implementation of the third-level PPC policy, industrial production activities gradually recovered, and the CO concentration rebounded. For historical average (2018–2019), the CO concentration showed a declining trend from February to April, while there was no such obvious downward trend from February to April of 2020 due to the implementation of the PPC policy (Figure 3).

In addition, the concentration of atmospheric particulate matters (PM10 and PM2.5) also decreased significantly during the period in response to PPC measures. The main sources of PM2.5 are the residues emitted from combustion in the process of daily power generation, industrial production and vehicle exhaust emissions. PM10 comes from direct emissions from pollution sources, such as coal-burning flue gas, construction and transportation dust, smelting dust, building material dust and traffic powder. The PCRs of PM10 concentration in the first-, second- and third-level responses were reduced by 20.01%, 10.71% and 6.92%, respectively, while the reductions were 23.01%, 25.99% and 14.99% for PM2.5, respectively. Thus, the concentrations of atmospheric particulate matters decreased most obviously under the first- and second-level responses. With the recovery of production and living activities, the concentrations of particulate matters gradually approached the average value in the same period of previous years (Figure 3).

**Figure 3.** Daily variations of pollutant concentrations under different PPC levels.The shadows of dark grey, medium grey and light grey represent the L1, L2 and L3 period respectively.

*3.4. Variations of Urban Air Quality in Response to Pandemic Protection and Control Measures under Different Economic Development Levels*

Table 4 and Figure 4 show the year-on-year variations of AQI in 13 cities of Jiangsu under different levels of PPC measures. It can be seen that in 2018 and 2019, there were significant differences in air quality among 13 cities. Among them, the air quality in Xuzhou that has a large proportion of heavy industry was the worst. After the outbreak of COVID-19, the gaps in air quality among 13 cities decreased. During the period with no PPC measures, except for Nantong and Yangzhou, the AQI values in other cities all

declined, which means that the air quality generally improved in 2020. During the period with first-level PPC measures, the AQI values in all cities showed a larger magnitude of decline. Among them, Wuxi, Nanjing and Suzhou have the largest magnitudes of 40.4%, 39.7% and 38.3%, respectively, while Suqian, Huai'an and Lianyungang have the smallest magnitudes of 21.1%, 23.1% and 24.2%, respectively. During the period with second-level PPC measures, the magnitude of the AQI decline in each city was smaller than that during the period in first-level response. Among them, Yangzhou, Taizhou and Zhenjiang had the largest magnitudes of 34.3%, 32.8% and 32.4%, respectively, while Huai'an, Suqian and Lianyungang had the smallest magnitudes of 20.6%, 23.7% and 24.4%, respectively. During the period with third-level PPC measures, the decline of the AQI in each city was smaller than that during the period in second-level response. Specifically, Zhenjiang, Xuzhou, Yangzhou and Taizhou had larger magnitudes of 27.8%, 26.2%, 24.2% and 23.7%, respectively, while Lianyungang, Nantong, Huai'an and Suqian had smaller magnitudes of 11.9%, 14.0%, 15.2% and 17.8%, respectively.

The daily variations of AQI in Xuzhou, Suqian, Nanjing and Suzhou in 2020 are presented in Figure 5. It can be seen that before the outbreak of COVID-19, the air quality in southern Jiangsu (Nanjing and Suzhou) was relatively good, while the air quality in northern Jiangsu (Xuzhou and Suqian) was poor. After the implementation of the first-level PPC measures, the air quality improved significantly. After the resumption of production, the pollutant concentrations rebounded, and the differences in the air quality among different cities shrank. The cities in southern Jiangsu returned to the pre-pandemic situation more quickly.

The GDP of 13 cities from 2019 to 2020 is shown in Table 5. The GDP of cities in southern Jiangsu is relatively higher. For example, the GDPs of Suzhou and Nanjing in 2020 reached CNY 2017.05 billion and CNY 1481.795 billion, respectively, while the GDPs of cities in northern Jiangsu were relatively lower. Suqian, the city with the lowest GDP in the province, had a GDP of CNY 326.24 billion in 2020. From the perspective of industrial structure (Figure 6), the proportion of primary industry in northern Jiangsu is higher than the average level of the whole province, while the proportions of secondary and tertiary industry are lower. The situation is the opposite in southern Jiangsu [35]. Under the epidemic prevention and control measures, the industrial and vehicle emissions were limited, so the secondary industry represented by industry and the tertiary industry represented by service industry were greatly affected. Therefore, the southern Jiangsu, dominated by the secondary and tertiary industries, was more sensitive to the PPC measures.


**Table 4.** Variations of AQI in 13 prefecture-level cities of Jiangsu under different levels of pandemic prevention and control measures, and those in the same period of historical years (the data are consistent with Figure 4).

**Figure 4.** Variations of AQI in 13 prefecture-level cities of Jiangsu under different levels of pandemic prevention and control measures, and those in the same period of historical years (the data are consistent with Table 4). Three colors in the map: blue, northern Jiangsu region; orange, central Jiangsu region; pink, southern Jiangsu region.

**Figure 5.** Daily variations of AQI in Xuzhou, Suqian, Nanjing and Suzhou in 2020. The shadows of dark grey, medium grey and light grey represent the L1, L2 and L3 period respectively.

**Table 5.** GDP rankings of 13 prefecture-level cities in Jiangsu Province (data from the National Bureau of Statistics of China, http://www.stats.gov.cn/, accessed on 10 March 2022).


Therefore, the response speed of urban air quality to the PPC level varied greatly under different economic development levels and industrial structure. The southern Jiangsu, which has a higher level of economic development and is dominated by secondary and tertiary industries, had a faster response speed and a stronger responsiveness. The pollutant concentration dropped rapidly during the period under first-level PPC, the economic production recovered quickly and the economic vitality was high during the periods under second- and third-level PPC. On the contrary, the northern Jiangsu, where the level of economic development is relatively backward and the proportion of primary industry is relatively high, had a slower response speed and a weaker responsiveness. The pollutant concentrations decreased slowly during the period under first-level PPC. After the relaxation of PPC measures, it takes a longer time for the economy to recover, and thus the economic vitality will be relatively weaker.

**Figure 6.** Industrial structure distribution map of 13 cities in Jiangsu Province. The data are from the *Jiangsu Statistical Yearbook 2020*, http://tj.jiangsu.gov.cn/2020/nj20/nj2006.htm, accessed on 10 March 2022.
