Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China

Abstract

The COVID-19 pandemic provides an opportunity to study the effects of urban lockdown policies on the variation in pollutant concentrations and to characterize the recovery patterns of urban air pollution under the interruption of COVID-19 lockdown policies. In this paper, interruption-recovery models and regression discontinuity design were developed to characterize air pollution interruption-recovery patterns and analyze environmental impacts of the COVID-19 lockdown, using air pollution data from four Chinese metropolises (i.e., Shanghai, Wuhan, Tianjin, and Guangzhou). The results revealed the air pollutant interruption-recovery curve represented by the three lockdown response periods (Level I, Level II and Level III) during COVID-19. The curve decreased during Level I (A 25.3%–48.8% drop in the concentration of NO 2 has been observed in the four metropolises compared with the same period in 2018–2019.), then recovered around reopening, but decreased again during Level III. Moreover, the interruption-recovery curve of the year-on-year air pollution difference suggests a process of first decreasing during Level I and gradually recovering to a new equilibrium during Level III (e.g., the unit cumulative difference of NO 2 mass concentrations in Shanghai was 21.7, 22.5, 11.3 (μg/m 3 ) during Level I, II, and III and other metropolises shared similar results). Our findings reveal general trends in the air quality externality of different lockdown policies, hence could provide valuable insights into air pollutant interruption-recovery patterns and clear scientific guides for policymakers to estimate the effect of different lockdown policies on urban air quality.

“New Normal”: The Dynamics of Air Pollutants on the Interruption–Recovery Pattern Related to the COVID-19 Pandemic in Recife, Northeastern Brazil

“…The findings of this study point to the recovery of air pollutant concentrations to a level probably equivalent to that prior to the COVID-19 Pandemic, when we take into account the comparison of pollutant concentrations between 2020 and 2021 and when comparing the values observed and expected based on meteorological variables. This pattern of recovery was also observed in numerous places (Cai et al 2021;Wang et al 2021) and consistent with the resumption of human activities, especially those related to services, education and leisure, which considerably increase vehicular traffic in large cities, as is the case of Recife.…”

Covid-19 Policy Convergence in Response to Knightian Uncertainty

“…Politicians were deeply concerned that the wrong policy choices made with limited information would diminish public trust and their electoral fortunes (Chatzopoulou and Exadaktylos, 2021; Zahariadis et al, 2022). In contrast, policymakers insulated from electoral uncertainty enjoyed greater policy freedom (see Cai et al, 2021). Understanding how problem definition, policy options, and political calculations (Kingdon, 2010) inform policy outcomes requires that we include those cases where we know little or nothing of value on some or all these dimensions.…”

To what extent the traffic restriction policies can improve its air quality? An inspiration from COVID-19

“…The lockdown policy during COVID-19 could also be regarded as a disturbance to the normal operation of a city. Some studies have examined the interruption-recovery patterns of urban air pollution under the impact of COVID-19 pandemic (Cai et al 2021 ).…”