Metadata record for the article: Analysing the life cycle greenhouse (GHG) emissions of cities: decoupling density from tallness

<b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related article: “Decoupling density from tallness in analysing the life cycle greenhouse gas emissions of cities”. The related study proposes a method that decouples density and tallness of buildings in urban environments and allows each to be analysed individually when estimating life cycle greenhouse gas (GHG) emissions. Type of data: quantitative analysis of life cycle greenhouse gas (GHG) emissions Sample size: 5000 synthetically generated urban environments (5 different cases with 1000 urban environments per case) Sampling strategy: The urban environments are generated through stochastic modelling, which relies on input data collected from real buildings, cities and neighbourhoods. <b>Data access</b> All code and supporting data can be accessed via <i>GitHub</i> at https://github.com/jayarehart/Denser-Taller. Static versions of the two data files included in the <i>GitHub </i>repository have also been included with this <i>figshare </i>data record (downloaded from <i>GitHub </i>on 24/05/2021). These files are ‘fixed_area.xlsx’ and ‘fixed_pop.xlsx’. Additional supplementary data and notes are available in the files ‘supplementary_methods.xlsx’ (Excel spreadsheet with multiple tabs) and ‘supplementary_notes.pdf’, which are publicly available in the <i>Mendeley Data </i>repository at https://doi.org/10.17632/kj3zn5nx6b.1, as well as together with this <i>figshare </i>data record. <b>Corresponding author(s) for this study</b> Francesco Pomponi, Resource Efficient Built Environment Lab (REBEL), Edinburgh Napier University. [e-mail].**摘要**<br>本元数据记录详细提供了支撑相关学术论文《Decoupling density from tallness in analysing the life cycle greenhouse gas emissions of cities》各项论断的数据集细节。本相关研究提出了一种可解耦城市环境中建筑密度与建筑高度的分析方法，能够在估算生命周期温室气体（GHG）排放时，分别对二者进行独立分析。<br>数据类型：生命周期温室气体（GHG）排放定量分析<br>样本量：共计5000个合成生成的城市环境样本（分为5组不同场景，每组包含1000个城市环境样本）<br>采样策略：本研究通过随机建模生成城市环境样本，建模所用输入数据均采集自真实建筑、城市与街区。<br>**数据获取途径**<br>所有代码与配套数据集均可通过*GitHub*平台获取，链接为：https://github.com/jayarehart/Denser-Taller。该*GitHub*仓库中包含的两个数据文件的静态版本也已随本*figshare*数据记录一同提供（于2021年5月24日从*GitHub*下载），这两个文件分别为`fixed_area.xlsx`与`fixed_pop.xlsx`。额外的补充数据与说明文件可通过`supplementary_methods.xlsx`（含多个工作表的Excel表格）与`supplementary_notes.pdf`获取，这些文件已公开存放在*Mendeley Data*仓库中，链接为https://doi.org/10.17632/kj3zn5nx6b.1，同时也随本*figshare*数据记录一同提供。<br>**本研究通讯作者**<br>Francesco Pomponi，爱丁堡龙比亚大学资源高效建成环境实验室（Resource Efficient Built Environment Lab, REBEL），邮箱：[e-mail]。