With the advancement of industrialization and the acceleration of urbanization, air pollution has become a major environmental health issue worldwide. However, the subtype-specific associations between air pollution and influenza virus infection remains unclear. In this nationwide individual-level case-crossover study, conditional logistic regression models combined with distributed lag models were applied to quantify the associations between exposure to PM2.5, PM10, O3, CO, NO2, SO2 and influenza virus infection in China. From 2013 to 2017, we included 257,763 laboratory-confirmed influenza-positive cases that had residential address information at the street or township level or finer, of which 177,794 (68.98%) were infected by influenza A. Our results indicated that for each 10 μg/m3 increase in PM2.5, PM10, CO, NO?, and SO?, the cumulative 7-day (lag06) effects on influenza virus infection increased by 1.54% (95% CI: 1.33-1.76%), 1.05% (95% CI: 0.90-1.19%), 0.11% (95% CI: 0.10-0.13%), 4.68% (95% CI: 4.10-5.26%), and 4.34% (95% CI: 3.84-4.83%), whereas O3 showed a significant protective effect, with 10 μg/m3 increase, the cumulative influenza virus infection would decreased by 2.96% (95% CI: 2.60-3.32%). The associations between all six air pollutants and influenza A virus infection were stronger than those for influenza B virus infection. With per 10 μg/m3 increase in PM2.5 the cumulative 7-day risk of influenza A and B virus infection increased by 1.92% (95% CI: 1.66-2.18%) and 0.75% (95% CI: 0.37-1.13%), respectively. Given the rapid urbanization process in China, our findings support professionals in developing public health policies that balance socioeconomic development with the environmental burden of influenza.