# Replication code and data for: Aging in a warming world: global projections of cumulative and acute heat exposure of older adults

# Replication code and data for: Aging in a warming world: global projections of cumulative and acute heat exposure of older adults By Giacomo Falchetta, Enrica De Cian, Ian Sue Wing and Deborah Carr Software requirements: - R v4.3+: https://cran.r-project.org/bin/windows/base/ - RStudio: v2023.06.0+: https://posit.co/download/rstudio-desktop/ - Package dependencies: raster, sf, tidyverse, rasterVis, rgdal, maptools, pbapply, terra, knitr, kableExtra, modelsummary, openxlsx, xtable, ggforce, maptools, weights, spatstat, rworldmap, scales, patchwork, stars, viridis, devtools, stargazer, readxl, nominatimlite, urbnmapr To replicate the analysis: - Clone the replication code repository from https://github.com/giacfalk/aging_climate - Download input data from this Zenodo data repository - Download all the 1km age and gender-stratified global population counts rasters from the following WorldPop page https://hub.worldpop.org/geodata/summary?id=24798 and put them in a subdirectory of the working directory called "AGEPOP" - Run the "project_pop.R" script to generate gridded age-stratified population data for each SSP scenario - Run the "compare_pop_projections.R" file to compare the generated gridded age-stratified population data with an array of pre-existing sources from different countries and produce a summary comparison table (NOTE: before running the script, decompress the "new_comparison_data.zip" folder into the working directory) - Run "projections_exposure_m.R" to quantify heat exposure and generate the figures and tables reported in the paper To process the data and run succesfully, the script requires a computer with at least 32GB RAM. The running time varies based on CPU characteristics, but a runtime of at least 2 hours should be expected to generate all the output data, figures, and tables. All output files are saved in the working directory. Manuscript under peer review. Upon publication, a link to the paper will be made available at this repository. ___ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

# 本研究配套复现代码与数据集：《变暖世界中的老龄化：老年群体累积性与突发性热暴露的全球预测》
作者：Giacomo Falchetta、Enrica De Cian、Ian Sue Wing 与 Deborah Carr

软件需求：
- R v4.3+：https://cran.r-project.org/bin/windows/base/
- RStudio v2023.06.0+：https://posit.co/download/rstudio-desktop/
- 依赖包：raster、sf、tidyverse、rasterVis、rgdal、maptools、pbapply、terra、knitr、kableExtra、modelsummary、openxlsx、xtable、ggforce、maptools、weights、spatstat、rworldmap、scales、patchwork、stars、viridis、devtools、stargazer、readxl、nominatimlite、urbnmapr

复现分析步骤：
- 从 https://github.com/giacfalk/aging_climate 克隆本复现代码仓库
- 从本项目关联的Zenodo数据仓库下载输入数据集
- 从WorldPop平台的以下页面 https://hub.worldpop.org/geodata/summary?id=24798 下载所有1km分辨率分年龄与性别的全球人口计数栅格数据，并将其放置于工作目录下名为"AGEPOP"的子目录中
- 运行"project_pop.R"脚本，以生成对应各社会经济共享路径（Shared Socioeconomic Pathways, SSP）场景的栅格化分年龄人口数据
- 运行"compare_pop_projections.R"文件，将生成的栅格化分年龄人口数据与多国现有多类数据源进行比对，并生成汇总比对表（注意：运行该脚本前，需将"new_comparison_data.zip"解压至工作目录）
- 运行"projections_exposure_m.R"以量化热暴露水平，并生成论文中刊载的全部图表与表格

运行说明：
本脚本需在至少配备32GB内存的计算机上方可成功完成数据处理与流程执行。运行时长因CPU性能差异有所波动，生成全部输出数据、图表及表格预计至少需要2小时。所有输出文件均保存至当前工作目录中。

稿件状态与公开说明：
本稿件目前处于同行评审阶段。正式发表后，本仓库将公布论文的公开链接。

本作品采用知识共享署名-非商业性使用-相同方式共享4.0国际许可协议进行许可。