Population size, age structure, and ageing of Chinese cities from 2000 to 2100

City-scale data on population size and age structure are essential for urban planning, public service provision, and disaster risk assessment. However, existing population datasets for China are mainly available at national or administrative-unit scales, while data representing individual cities remain limited. Here, we developed a dataset of population size, age structure, and population ageing for 326 major Chinese cities from 2000 to 2100. Historical urban population data were derived by aggregating age- and sex-specific population grids within built-up areas after systematic calibration using census data. Future population data were generated using the cohort-component method to simulate urban demographic change under five Shared Socioeconomic Pathway (SSP) scenarios. The resulting dataset provides consistent information on historical changes and future trajectories in urban population size, age structure, and ageing across China. Historical backcasting showed that the mean absolute percentage errors (MAPE) for total population and the population aged 65 years and older in 2020 were below 10%, while the error in the projected share of the older population was below 1 percentage point. The dataset also showed strong agreement with existing population datasets, with Pearson’s correlation coefficients exceeding 0.9. This dataset provides a basis for investigating urban population change and ageing in China and can support studies of urban disaster risk, public service demand, and sustainable urban development. Given China’s rapid urbanization and continuing population ageing, the long-term demographic trajectories of its cities also provide useful evidence for understanding global urban population transitions and their social and environmental implications.This datasat contains age- and sex-specific population data for 326 Chinese cities represented by a consistent set of fixed city boundaries, together with the principal R modules documenting the data-production workflow. The dataset includes historical population data for 2000, 2010, and 2020; a simulated population for 2020; and population projections under five Shared Socioeconomic Pathway (SSP) scenarios from 2025 to 2100 at five-year intervals. Population values refer to the population within the fixed city boundaries used by this dataset. They should not be interpreted as the population of the entire prefecture-level administrative area.