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The emergency response to the COVID-19 pandemic had an extreme exogenous impact on society and the economy. This paper aims to explore the impacts of the national emergency response and the subsequent emergency response termination on air quality and its policy implications through regression discontinuity design (RDD) estimation by employing panel data on daily air quality from January 1, 2019, to July 31, 2020, for 290 cities in China. The empirical results showed that the emergency response resulted in a significant decrease in most of the major pollutant concentrations within a short time frame, and the average air quality index (AQI) decreased by approximately 11.0%. The concentrations of PM 2.5 , PM 10 , SO 2 , NO 2 , and CO decreased by approximately 18.8%, 13.1%, 13.5%, 11.1% and 6.7%, respectively, while the O 3 concentration did not change significantly. Further causal analysis found that mandatory traffic restrictions and the shutdown of industries were two important factors that contributed greatly to air quality improvement. Moreover, since the process of returning to normal daily activities and promoting the economy were gradual, the results showed that air pollution did not rebound immediately after the government called for the "resumption of production and work" and announced the "termination of the emergency response". Our findings suggest that to achieve a substantial and sustainable improvement in air quality, it is necessary to continuously implement strict emission control routines and take co-control measures for various VOCs precursors of ozone. [Display omitted] • Emergency response to COVID-19 (ER) had spill-over effect on air quality. • Empirical analysis was made with RDD to evaluate the impact of ER on air quality. • AQI and PM 2.5 , PM 10 , SO 2 and NO 2 concentrations decreased by approximately 10%. • Traffic restrictions and shutdown of industries during ER were important factors. • Socioeconomic resumption and ER termination did not affect air quality. [ABSTRACT FROM AUTHOR]

COVID-19 can be considered as the largest public health incident since 2019, posing disturbances to the medical, economic, and social systems. Understanding different levels of city resilience to the impact of COVID-19 on sustainable urban development is therefore essential. In this paper, we analyzed the evolution of the pandemic, the recovery of urban activities and major drivers of urban resilience to COVID-19 based on urban activity patterns derived from NO 2 monitoring stations from 217 cities in China. It is observed that nearly all urban activities have been affected by the epidemic with a reduced NO 2 emission, indicating a significant decline in the intensity of urban activity. The recovery patterns of human activity among different cities show that: (1) northern cities where low-resilience cities agglomerated have been severely affected. As of April 31, 2020, 12 northern cities have not recovered to pre-epidemic levels; (2) about three-quarters of the cities went through multiple stages to return to the pre-pandemic level, which related to both pandemic stress and prevention measures; (3) about 46.04% of the cities experienced increasing activity patterns that exceeded the pre-epidemic activity level. It is also observed that urban resilience can behave quite differently driven by variations in green coverage, economic aggregate, employment security, and medical system. Our study highlights the potential of an elevated urban resilience by optimizing the urban layout, improving the quantity and quality of green space, and enhancing the medical system. [Display omitted] • Most of the southern cities of China show higher urban activity than pre-pandemic. • Low/high-resilient urban agglomerations located in the north-northeast/south China. • Most cities undergo two stages of recovery at the beginning and end of March 2020. • Urban greenery is positively correlated to urban resilience. • Hospital capacity, instead of number, is more crucial to urban resilience. [ABSTRACT FROM AUTHOR]

Resilience has a critical role to promote human well-being in turbulent environments. However, extensive interventions and stimulus measures not only achieve resilience goals with numerous unacceptable consequences, but also highlight the narrow definition of resilience. The study proposes the concept of resilience effectiveness to constrain the unsustainability of resilience in concept and practice. The resilience effectiveness of Chinese cities in the early stages of the pandemic is first implemented for evaluation based on input-output relationship, and then patterns and determinants are investigated using the GIS methods and the geographically optimal zones-based heterogeneity (GOZH) model. The study finds that the average resilience effectiveness is not high, indicating that China's strong resilience is the loss of safety, greenness, inclusiveness, and efficiency in the early stage of the pandemic. Resilience effectiveness has significant spatial heterogeneity and is dominated by innovation ability. The optimal geographic zones of Chinese cities for resilience effectiveness are identified, revealing that it is a complex and multifactorial process. This paper broadens resilience research and provides implications for city planning in the post-pandemic era. [ABSTRACT FROM AUTHOR]