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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/m3) 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. • The interruption and recovery of air pollution during the COVID-19 was evaluated. • Regression Discontinuity Design (RDD) has been used for statistical analysis. • Data of four major Chinese cites were utilized for characterizing and modelling. • The year-on-year NO 2 and PM 2.5 showed 25.3%–48.8% and 23.1%–46.2% drop separately. [ABSTRACT FROM AUTHOR]

Daytime atmospheric pollution has received wide attention, while the vertical structures of atmospheric pollutants at night play a crucial role in the photochemical process on the following day, which is still less reported. Focusing on Guangzhou, a megacity of South China, we established an unmanned aerial vehicle (UAV) equipped with micro detectors to collect consecutive high-resolution samples of fine particle (PM 2.5), submicron particle (PM 1.0), black carbon (BC) and ozone (O 3) concentrations in the atmosphere, as well as the air temperature (AT) and relative humidity (RH) within a 500 m altitude during nighttime from Oct. 24th to Nov. 6th, 2018. The measurements showed that PM 2.5 , PM 1.0 , and BC decreased with altitude and were influenced by the nighttime shallow planetary boundary layer (PBL) where BC was more accumulated and fluctuated. In contrast, O 3 was positively correlated with altitude. Backward trajectory clustering and Pasquill stability classification showed that advection and convection significantly influenced the vertical distribution of all pollutants, particularly particulate matter. External air masses carrying high concentrations of pollutants increased PM 1.0 and PM 2.5 levels by 145% and 455%, respectively, compared to unaffected periods. The ratio of BC to PM 2.5 indicated that local emissions had a minor role in nighttime particulate matter. Vertical transport caused by atmospheric instability reduced the differences in pollutant concentrations at various heights. Geodetector and generalized additive model showed that RH and BC accumulation in the PBL were significant factors influencing vertical changes of the secondary aerosol intensity as indicated by the ratio of PM 1.0 to PM 2.5. The joint explanation of RH and atmospheric stability with other variables such as BC is essential to understand the generation of secondary aerosols. These findings provide insights into regional and local measures to prevent and control night-time particulate matter pollution. [Display omitted] • PM 2.5 , PM 1.0 , BC, and O 3 are detected vertically at nighttime in Guangzhou. • The vertical decline is smooth for PM 2.5 and PM 1.0 but fluctuating for BC. • Compared to PM 2.5 and PM 1.0 , BC is more sensitive to PBL. • Higher BC and humidity near the PBL reduce the secondary aerosol intensity. [ABSTRACT FROM AUTHOR]