3.1 Changes in AOD Levels for the COVID-19 Period
As shown in Figure 2 a and b, after the outbreak of covid-19, the AOD levels of Fujian province, Guangzhou province, Zhejiang province, and Beijing increased in February compared with that in January, while the AOD in other regions decreased.
The ground monitoring AQI and PM2.5 data for Guangzhou (the capital of Fujian Province) from January to February 2020 were counted in 10-d intervals (the monthly difference of AOD was greater than 0), as shown in Figure 3a; daily AOD (January 1, 2020), 10-d AOD (early January 2020), and monthly AOD (January 2020) data are shown in Figure 3b; No data area in early February in 2020 and difference greater than 0 area is shown in Figure 3c.
It can be seen from Figure 3a that the AQI and PM2.5 of Guangzhou City decreased successively in early, middle, and late January, and then rebounded after reaching its lowest value in the first 10 d of February (also shown in Figure 3a). Significant amounts of AOD data were missing (Figures 3b and c). The AOD in February increased more than that in January was largely located in the areas where AOD data were missing in the first 10 days of February (Figures 3c). The AOD data of Guangzhou city from early and middle January 2020 were seriously missing (with high AQI and PM2.5 levels), and the AOD data from early February were missing completely (the lowest point), which may have led to the monthly AOD in February being larger than that in January.
3.2 Cities air quality
a AOD for 5 cities from Jan. to Apr. 2020 b. AQI, PM2.5 and NO2 in Wuhan in 2020 and 2019
Figure 4a shows the AQI in February 2020 after the outbreak of COVID-19 had decreased significantly compared with that in January, except for Beijing and especially Jinan. The AQI in Jinan decreased from 140.8 in January 2020 to 76.9 in February, reaching the lowest monthly mean value in the same period since observation records began being kept (2014). In February and March 2020, the AQI was relatively low and rebounded significantly in April.
Figure 4b shows that all parameters dropped precipitously after the lockdown on January 23, 2020; the NO2 value (which mainly comes from exhaust gas) in Q1 2020, in particular, was much lower than that in Q1 2019. According to Amap, on April 8, 2020 (end of lockdown), the PCDI of Wuhan increased by 7.87% compared with the previous day, and even exceeded the value on April 8, 2019; in other words, the data reveal that human activities have a great impact on air quality.
3.3 Impact of people's activities on air quality
Figure 5 AQI and main human activities in Jinan City from January 1, 2020 to April 30, 2020.
It can be seen from Figure 5 that the areas of high AQI value corresponded to people's activities from January 24, 2020 (when Shandong Province launched its first-level response to the major public health paroxysmal incident of COVID-19) to April 30, 2020. That is to say, the AQI that peaked during the epidemic period were closely related to people's activities.
Table 1
Correlation coefficient between AQI, PM2.5 and NO2 with PCDI
|
Fitting method
|
AQI
|
PM2.5
|
NO2
|
PCDI
|
Linear
|
0.3284
|
0.4820
|
0.8091
|
Quadratic polynomial
|
0.3345
|
0.4950
|
0.8402
|
The correlation coefficient between AQI, PM2.5, and NO2 with PCDI is reported in Table 1 and all P values are <0.05. This demonstrates that AQI, PM2.5, and NO2 have a positive correlation with PCDI. According to the source analysis of PM2.5 in Beijing, Jinan, and Hangzhou, exhaust gases surpassed coal combustion as the main source of PM2.5 pollution in cities, and some industries were shut down during COVID-19, which led to the high correlation between PCDI and NO2. Source analysis of PM2.5 also indicated that exhaust emissions had a great impact on urban air quality.