Table 1 The effects of lockdown on air quality

From: The short-term impacts of COVID-19 lockdown on urban air pollution in China

  Treatment and control group in 2020 Control group in 2019 and 2020
  Levels Log Levels Log
  (1) (2) (3) (4) (5) (6) (7) (8)
(a) AQI
Lockdown −18.27*** −19.84*** −0.14*** −0.17***     
  (3.21) (3.13) (0.03) (0.03)     
Spring Festival in 2020      −6.93*** −6.34*** −0.06*** −0.05**
      (2.14) (2.13) (0.02) (0.02)
R2 0.503 0.515 0.581 0.601 0.459 0.469 0.519 0.541
(b) PM2.5 (μg m3)
Lockdown −12.87*** −14.07*** −0.13*** −0.17***     
  (2.60) (2.53) (0.03) (0.03)     
Spring Festival in 2020      −7.64*** −7.05*** −0.09*** −0.07**
      (1.74) (1.77) (0.03) (0.03)
R2 0.534 0.541 0.627 0.641 0.472 0.479 0.553 0.570
Weather control   Y   Y   Y   Y
City fixed effects Y Y Y Y Y Y Y Y
Date fixed effects Y Y Y Y Y Y Y Y
Year fixed effects      Y Y Y Y
Observations 19,764 19,764 19,764 19,764 27,938 27,938 27,938 27,938
Number of cities 324 324 324 324 229 229 229 229
  1. Weather controls include daily temperature, its square, precipitation and snow depth. The fixed effects indicate a set of dummy variables (see Methods). Each column in each panel represents one separate regression. In the regressions indicated in columns (1), (3), (5) and (7), we do not control for the weather conditions; in other columns, we control for the weather conditions. In columns (1), (2), (5) and (6), the outcomes of interest are the absolute values of the pollutants. In columns (3), (4), (7) and (8), we take the logarithms on the pollutants as the outcomes. Standard errors are clustered at the city level and reported below the coefficients. **P < 0.05; ***P < 0.01.