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City-level population projection for China under different pathways from 2010 to 2100.
Zhang, Shangchen; Zhao, Mengzhen; Liu, Zhao; Yang, Fan; Lu, Bo; Zhao, Zhenping; Gu, Kuiying; Zhang, Shihui; Lei, Mingyu; Zhang, Chi; Wang, Can; Cai, Wenjia.
Afiliación
  • Zhang S; Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
  • Zhao M; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
  • Liu Z; School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, 100102, China.
  • Yang F; Center for Population and Development Studies, Renmin University of China, Beijing, 100872, China.
  • Lu B; National Climate Center, China Meteorological Administration, NO. 46, Zhongguancun Nandajie, Haidian District, Beijing, China.
  • Zhao Z; National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing, 100050, China.
  • Gu K; Vanke School of Public Health, Tsinghua University, Beijing, 100084, China.
  • Zhang S; Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
  • Lei M; Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
  • Zhang C; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
  • Wang C; State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, 100084, China.
  • Cai W; Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China. wcai@tsinghua.edu.cn.
Sci Data ; 10(1): 809, 2023 11 17.
Article en En | MEDLINE | ID: mdl-37978198
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.

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Sci Data Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Sci Data Año: 2023 Tipo del documento: Article País de afiliación: China