Objective To explore the spatiotemporal characteristics of pulmonary tuberculosis (TB) in China and its macro influencing factors, and to provide a theoretical basis for the formulation of TB prevention and control measures. Methods The data of tuberculosis incidence in China from 2011 to 2020 were collected. A two-stage distributed lag nonlinear model (DLNM) was constructed to assess the lag effect and nonlinear relationship of meteorological factors on TB incidence, and a hierarchical Bayesian spatiotemporal model was used to analyze the relationship between population, economic factors, health services, and TB incidence. Results TB incidence in China was on a downward trend, with spatial clustering, and there were intensifying hotspots (Sichuan Province) and persistent hotspots(Liaoning Province, Shaanxi Province). The attributable fractions of low temperature(<6.7 ℃), low relative humidity(<55.59%), high wind speed(>3.00 m/s), and short sunshine duration(<2.7 hours) were 14.44%, 5.75%, 3.30%, and 7.88%, respectively. The urbanization rate(RR=1.009, 95% CI: 1.007-1.012) and the night light index (RR=1.009, 95% CI: 1.007-1.013) were positively correlated with TB incidence, while the number of hospital beds(RR=0.996, 95% CI: 0.994-0.998) and the proportion of elderly population (RR=0.973, 95% CI: 0.969-0.979) were negatively correlated with it. Conclusion The TB incidence in China has generally shown a downward trend. Attention should be paid to the prevention and control of hotspots, and the monitoring of macro influencing factors should be strengthened to take intervention measures as early as possible.