Spatiotemporal dynamics of global population and heat exposure (2020-2100): based on improved SSP-consistent population projections

作     者：Li, Mengya Zhou, Bing-Bing Gao, Minyi Chen, Yimin Hao, Ming Hu, Guohua Li, Xia 

作者机构：East China Normal Univ Sch Geog Sci Minist Nat Resources Key Lab Spatial Temporal Big Data Anal & Applicat 500 Dongchuan Rd Shanghai 200241 Peoples R China Ocean Univ China Sch Int Affairs & Publ Adm 238 Songling Rd Qingdao 266100 Peoples R China Sun Yat Sen Univ Sch Geog & Planning 135 West Xingang Rd Guangzhou 510275 Peoples R China Sun Yat Sen Univ Guangdong Key Lab Urbanizat & Geosimulat 135 West Xingang Rd Guangzhou 510275 Peoples R China East China Normal Univ Sch Geog Sci Minist Educ Key Lab Geog Informat Sci 500 Dongchuan Rd Shanghai 200241 Peoples R China 

出 版 物：《ENVIRONMENTAL RESEARCH LETTERS》 (环境研究快报)

年 卷 期：2022年第17卷第9期

页      面：094007-094007页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 0706[理学-大气科学] 

基　　金：Key National Natural Science Foundation of China 

主　　题：gridded global population projections Shared Socioeconomic Pathways (SSPs) extreme heat climate variability and global change sustainable development 

摘      要：To address future environmental change and consequent social vulnerability, a better understanding of future population (FPOP) dynamics is critical. In this regard, notable progress has been made in producing FPOP projections that are consistent with the Shared Socioeconomic Pathways (SSPs) at low resolutions for the globe and high resolutions for specific regions. Building on existing endeavors, here we contribute a new set of 1 km SSP-consistent global population projections (FPOP in short for the dataset) under a machine learning framework. Our approach incorporates a recently available SSP-consistent global built-up land dataset under the Coupled Model Intercomparison Project 6, with the aim to address the misestimation of future built-up land dynamics underlying existing datasets of future global population projections. We show that the overall accuracy of our FPOP outperforms five existing datasets at multiple scales and especially in densely-populated areas (e.g. cities and towns). Followingly, FPOP-based assessments of future global population dynamics suggest a similar trend by population density and a spatial Matthew effect of regional population centralization. Furthermore, FPOP-based estimates of global heat exposure are around 300 billion person-days in 2020 under four SSP-Representative Concentration Pathway (RCPs), which by 2100 could increase to as low as 516 billion person-days under SSP5-RCP4.5 and as high as 1626 billion person-days under SSP3-RCP8.5-with Asia and Africa contributing 64%-68% and 21%-25%, respectively. While our results shed lights on proactive policy interventions for addressing future global heat hazard, FPOP will enable future-oriented assessments of a wide range of environmental hazards, e.g. hurricanes, droughts, and flooding.