<p>The COVID-19 pandemic provided a unique opportunity to examine how varying levels of social and economic activity influence air quality (AQ). While existing studies mostly focused on short-term AQ improvements during lockdowns, limited attention has been given to the spatiotemporal characteristics and synergistic effects of air pollutants (AP) (PM_2.5, CO, NO₂, O₃, and SO₂) and carbon dioxide (CO₂) emissions before and after the pandemic. Aiming to evaluate the trend differences, spatiotemporal aggregation characteristics, and co-effects of AP and CO₂ before and after the pandemic across 369 Chinese cities, this study develops a methodological framework combining polynomial function fitting to compare inter-city temporal trends, K-means clustering to identify regional spatiotemporal patterns, and a co-effect control coordinate system to evaluate co-effects of AQ and CO₂ reduction. Daily AP data and CO₂ emissions were analyzed for January to June in 2019–2021. Results show that CO₂ and NO₂ exhibited broadly consistent trends across cities, while CO and PM_2.5 showed similar inter-city patterns. CO₂ emissions in eastern, northern, and northeastern China declined substantially in 2020. PM_2.5 and CO decreased markedly in the Yellow River downstream and Bohai Rim region and remained lower even after policy relaxation. O₃ concentrations increased in the Central Plains and southeastern coastal cities during the pandemic, whereas SO₂ declined continuously. Lockdown measures in 2020 achieved significant effects in synergistically reducing AP and CO₂ emissions. AP reductions exceeding 10%, with declines of 14.65% in SO₂ and 13.71% in NO₂. However, CO, NO₂, and CO₂ emissions rebounded nationwide in 2021. This study reveals regional heterogeneity in AP and CO₂ responses to pandemic lockdown measures and highlights that reduction co-effects achieved during lockdowns were temporary, providing new insights to support targeted, sustained joint control strategies for AP and CO₂.</p>