**1. Introduction**

In early 2020, a sudden outbreak of the coronavirus disease 2019 (COVID-19) occurred in China. This virus is highly contagious, and has caused a high mortality rate in sensitive groups. So far, the COVID-19 has not yet been completely controlled. In order to curb the spread of COVID-19, the government has implemented a series of interventions since the outbreak, including lockdowns, quarantine, travel restrictions, temporary closures of businesses and public facilities, etc. These control and emergency measures have greatly affected the human activities, economic development, social relations and natural environment [1–4].

Compared with the temporary control during major events and meetings in recent years, the control of COVID-19 pandemic is the strictest in history in both time and space. Therefore, it is possible to systematically study the impact of strict control measures implemented by the government on air quality. In recent years, some scholars have studied the impact of temporary control measures on urban air quality during major events or conferences, such as the 22nd Asia-Pacific Economic Cooperation Economic Leaders' Meeting in Beijing [5],

**Citation:** Ai, W.; Yang, X.; Liu, D.; Zhang, M.; Sun, Y.; Wang, B.; Luo, X. Impact of the Levels of COVID-19 Pandemic Prevention and Control Measures on Air Quality: A Case Study of Jiangsu Province, China. *Atmosphere* **2022**, *13*, 640. https:// doi.org/10.3390/atmos13050640

Academic Editor: Célia Alves

Received: 16 March 2022 Accepted: 15 April 2022 Published: 19 April 2022

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the 2013 Asian Youth Games [6] and 2014 Summer Youth Olympic Games in Nanjing [7], and the 2016 G20 Hangzhou summit [8]. The variations of air quality during these events demonstrate that the control measures are highly effective in alleviating air pollution.

The COVID-19 pandemic has had a significant impact on the environment, which has been studied by scholars around the world. Several studies have shown that after the measures taken by the Chinese government against the COVID-19 pandemic, air pollution reduced significantly by 12.0–52.8% [1,9–15]. Similar situations appeared in other countries. Air pollution in northeastern United States dropped by 30% after pandemic prevention and control (PPC) measures were adopted [16]. The European Environment Agency found that air pollution also decreased significantly after taking PPC measures in European cities [17]. From 16–22 March 2020, NO2 concentration in Bergamo of Italy and Barcelona of Spain respectively decreased by 47% and 55% compared with that during the same period of 2019. During the PPC period of COVID-19, NO2 concentration dropped by 25.5% in the United States [2], while NO2 and particulate matter (PM10 and PM2.5) concentrations dropped by nearly 50% in four Indian metropolises [18]. However, due to the complexity of PPC implementation, it has been found that in many countries, even in lockdown period a few pollutants' concentrations showed an increasing trend. The O3 concentration in Singapore increased by 18% during the lockdown period [19]. During the lockdown, the SO2 concentration in southern India increased slightly, and the O3 concentration increased in the Indo Gangetic plain [20]. The concentration of O3 increased greatly in Hubei and the Yangtze River Delta [21,22]. Since the start of the COVID-19 lockdown, the concentration of PM2.5 in Beijing was higher than that in the same period in history [23]. And the decline of the concentration of SO2 in Wuhan was weaker than that in history [21]. These studies have confirmed that the change in air pollution is mainly related to the slower economic growth and travel restrictions during the pandemic [1,10].

Social production and operations as well as travel restrictions are closely related to the level of PPC measures released by the government. Although many studies have confirmed that the government's PPC measures have a significant impact on air quality, however, there is still a lack of specific information on the relationship between different PPC levels and air pollution. Furthermore, the impact of the PPC levels on air quality may vary in different regions under different levels of PPC. In addition, the speed of economic recovery after the slowdown of the pandemic reflects the economic vitality of a city. The changes in air quality in different cities after the implementation of PPC measures also reflect the differences in the economic vitality of different cities, which has rarely been discussed in previous studies. In this study, the variation characteristics of air quality in different response levels to PPC measures in Jiangsu Province is studied, and the impact of PPC measures of different levels on air quality is evaluated, especially the response speed of urban air quality to PPC measures in cities with different economic development levels. By revealing the relationship between government decision-making behavior and air pollution, this study can provide references for the formulation of government PPC policies and can also help the government to develop more scientific and reasonable strategies for air pollution prevention and control.

The remainder of this paper is organized as follows. Section 2 describes the data and methods. Section 3 presents results and related discussions. Finally, the main conclusions are given in Section 4.

#### **2. Materials and Methods**

#### *2.1. Air Pollutants and Meteorological Elements*

In this study, the air quality data are from the national air quality monitoring stations of Jiangsu Environmental Monitoring Center that are located in 13 prefecture-level cities of Jiangsu. The hourly mean of all national stations in each city is taken as the hourly monitoring value of this city, and the arithmetic mean of hourly monitoring values of 13 cities is taken as the hourly monitoring value of Jiangsu. The data mainly include hourly data of SO2, NO2, CO, O3, PM10 and PM2.5 pollutants. According to the Technical Regulation on Ambient Air Quality (HJ 633—2012), we calculated the individual air quality index (IAQI) based on the arithmetic mean of each pollutant in the whole province each day, and furthermore, the daily AQI of the province was calculated. The meteorological data come from 71 national standard meteorological stations covering the whole Jiangsu Province, including hourly temperature, wind speed, precipitation, relative humidity and visibility from 2018 to 2020. The hourly means of the 71 stations were taken as the hourly monitoring values of the province. The administrative division of the study area is shown in Figure 1.

**Figure 1.** Administrative division of the study area.
