TY - JOUR
T1 - City-level population projection for China under different pathways from 2010 to 2100
AU - Zhang, Shangchen
AU - Zhao, Mengzhen
AU - Liu, Zhao
AU - Yang, Fan
AU - Lu, Bo
AU - Zhao, Zhenping
AU - Gu, Kuiying
AU - Zhang, Shihui
AU - Lei, Mingyu
AU - Zhang, Chi
AU - Wang, Can
AU - Cai, Wenjia
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Cities play a fundamental role in policy decision-making processes, necessitating the availability of city-level population projections to better understand future population dynamics and facilitate research across various domains, including urban planning, shrinking cities, GHG emission projections, GDP projections, disaster risk mitigation, and public health risk assessment. However, the current absence of city-level population projections for China is a significant gap in knowledge. Moreover, aggregating grid-level projections to the city level introduces substantial errors of approximately 30%, leading to discrepancies with actual population trends. The unique circumstances of China, characterized by comprehensive poverty reduction, compulsory education policies, and carbon neutrality goals, render scenarios like SSP4(Shared Socioeconomic Pathways) and SSP5 less applicable. To address the aforementioned limitations, this study made three key enhancements, which significantly refines and augments our previous investigation. Firstly, we refined the model, incorporating granular demographic data at the city level. Secondly, we redesigned the migration module to consider both regional and city-level population attractiveness. Lastly, we explored diverse fertility and migration scenarios.
AB - Cities play a fundamental role in policy decision-making processes, necessitating the availability of city-level population projections to better understand future population dynamics and facilitate research across various domains, including urban planning, shrinking cities, GHG emission projections, GDP projections, disaster risk mitigation, and public health risk assessment. However, the current absence of city-level population projections for China is a significant gap in knowledge. Moreover, aggregating grid-level projections to the city level introduces substantial errors of approximately 30%, leading to discrepancies with actual population trends. The unique circumstances of China, characterized by comprehensive poverty reduction, compulsory education policies, and carbon neutrality goals, render scenarios like SSP4(Shared Socioeconomic Pathways) and SSP5 less applicable. To address the aforementioned limitations, this study made three key enhancements, which significantly refines and augments our previous investigation. Firstly, we refined the model, incorporating granular demographic data at the city level. Secondly, we redesigned the migration module to consider both regional and city-level population attractiveness. Lastly, we explored diverse fertility and migration scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85177086440&partnerID=8YFLogxK
U2 - 10.1038/s41597-023-02735-6
DO - 10.1038/s41597-023-02735-6
M3 - Article
C2 - 37978198
AN - SCOPUS:85177086440
SN - 2052-4463
VL - 10
JO - Scientific data
JF - Scientific data
IS - 1
M1 - 809
ER -