Abstract
Accurate and reliable subnational and spatially explicit population projections under shared socioeconomic pathways (SSPs) for China will be helpful for understanding long-term demographic changes and formulating targeted mitigation and adaptation policies under climate change. In this study, national and provincial populations for China by age, sex, and education level to 2100 under five SSPs were estimated using the population-development-environment model. These parameters include fertility, mortality, migration, and education and consider the most recent birth policy in China. To quantify these projections spatially, the gridded population was provided at 1 km × 1 km by spatial downscaling. Results show the national population is highest under SSP3, with 1.71 × 109 people in 2100. Guangdong, Henan, and Shandong are the most populous in SSP1, 2, 4, 5, while Guangxi is the most populous province in SSP3, reaching 1.54 × 108 people. The differences in education level among scenarios are obvious, especially in 2100 where education level for SSP1 and SSP5 is the highest. The spatial distribution of population varies across the country, with the majority of the population concentrated in southern and eastern China, especially in the coastal regions. Our results under different SSPs could provide a reference to project disaster risks, formulate relevant policies and guide sustainable development from a long-term perspective.
Highlights
Increasing greenhouse gas emissions as a result of human activity are considered the main cause of global warming [1]
Using population data from the sixth nacensuscensus of China in 2010, we provide detailed population projections according to age, tional of China in 2010, we provide detailed population projections according to sex, and education in provinces as well as the spatially estimated population age, sex, and education in 31 provinces as well as the spatially estimated population at at aa resolution of 1 km × 1 km of China annually during the period 2011–2100 under five resolution of 1 km × 1 km of China annually during the period 2011–2100 under five difdifferent shared socioeconomic pathways (SSPs) scenarios
The trend of total population change under the five SSPs is similar to the projections from Institute for Applied Systems Analysis (IIASA), which indicate the highest value of population occurring to the projections from IIASA, which indicate the highest value of population occuraround 2030 [8]
Summary
Increasing greenhouse gas emissions as a result of human activity are considered the main cause of global warming [1]. Apart from total population size, the structure (age, sex, and education level) and distribution of the population are important factors in climate and global environmental change research. These are important sources of population heterogeneity, and their changing composition is directly relevant in the anticipation of socioeconomic challenges to mitigate and adapt to climate change. Population aging is considered a highly important socioeconomic challenge under climate change which will significantly increase the cost of adaptation but can only be quantitatively addressed if the age structure
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