With the support of the National Natural Science Foundation of China (Grant No. 71773061, 71773062 and 71525007), the research team of professor Can WANG from the School of Environment, Tsinghua University, and associate professor Wenjia CAI from the Department of Earth System Science, Tsinghua University released data on provincial and gridded population projections at 1 km resolution for China under shared socioeconomic pathways (SSPs). This study, titled Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100, has been published on Scientific Data on March 9^th, 2020 (https://www.nature.com/articles/s41597-020-0421-y).

The SSPs were established by the international climate change research community to facilitate integrated analysis on future climate change impacts, adaptation and mitigation. Five different development pathways of future socioeconomic systems are described by the SSPs, reflecting the linkage between socioeconomic development and climate change, and serving as the basis for the Intergovernmental Panel on Climate Change (IPCC) to conduct climate change assessments. At present, international institutions have established a national-scale long-term forecasting database of socio-economic driving factors (population, GDP and urbanization rate), but there are some shortcomings. On the one hand, the data do not fully reflect the actual situation in China in the setting of scenario parameters, which results in a certain systematic bias. On the other hand, the data are at national level, which limits the spatial differentiation analysis in climate change impact and policy assessment studies, and fail to meet the actual needs of climate change research. Therefore, it is of great significance to develop a dataset of subnational and high-resolution gridded SSPs driving factors suitable for China’s national situations.

This study used a recursive multidimensional model to estimate China’s yearly provincial population with specific demographic information on sex, age, and educational attainment under SSPs from 2010 to 2100, taking into account the impact of national fertility policies and population ceiling policies to reduce the systematic bias in the results of the existing studies. The projection of provincial population was downscaled to spatially explicit population grids with a resolution of 1 km, based on the representative concentration pathway (RCP) urban grids and historical population grids. The projected provincial population, their demographic attributes and the population grids were validated and compared using data from the latest provincial and prefecture-level statistical yearbook, and the international gridded population products.

The results of this study can serve as important inputs for the studies and simulations in integrated impact assessment of future climate policies, resource demand and allocations, public health, and social equity.

Figure. Future population changes at the national level from 2010 to 2100 under five SSPs