Abstract
Governmental policies, regulations, and responses to the pandemic can benefit from a better understanding of people's resulting behaviours before, during, and after COVID-19. To avoid the inelasticity and subjectivity of survey datasets, several studies have already used some objective variables like air pollutants to estimate the potential impacts of COVID-19 on the urban transportation system. However, the usage of reactant gases and a narrow time scale might weaken the results somehow. Here, both the objective passenger volume of public transport and the concentration of private traffic emitted black carbon (BC) from 2018 to 2023 were collected/calculated to decipher the potential relationship between public and private traffic during the COVID-19 period. Our results indicated that the commuting patterns of citizens show significant (p < 0.01) different patterns before, during, and after the pandemic. To be specific, public transportation showed a significant (p < 0.01) positive correlation with private transportation before the pandemic. This public transportation was significantly (p < 0.01) affected by the outbreaks of COVID-19, showing a significant (p < 0.01) negative correlation with private transportation. Such impacts of the virus and governmental policy would affect the long-term behaviour of individuals and even affect public transportation usage after the pandemic. Our results also indicated that such behaviour was mainly linked to the governmental restriction policy and would soon be neglected after the cancellation of the restriction policy in China.