five

Buildings: Future Demand: Cooling Demand with Deep Retrofit

收藏
Los Angeles Planning Department Data Hub2025-12-18 更新2026-04-25 收录
下载链接:
https://laep-datahub-alpha-cityhall.hub.arcgis.com/datasets/cityhall::buildings-future-demand-cooling-demand-with-deep-retrofit-
下载链接
链接失效反馈
官方服务:
资源简介:
Author: Skenario Labs & Arup Creation date: 2023 Date of source data harvest: 2023 Temporal coverage: 2023 Spatial Resolution: Output Area Geometry: Polygon Source data URL: Buildings Baseline Cooling Demand Data terms of use: Dataset available to download and reuse, with appropriate attribution. Data attribution: - Dataset processed by Arup as part of the West London sub-regional LAEP, 2023. - Office for National Statistics licensed under Open Government Licence v3.0. - Contains OS data © Crown copyright and database right, 2023. - Skenario Labs, 2023. Workflow Diagram: Available: png Comments: The data and analysis developed for the sub-regional LAEP was undertaken using data available at the time and will need to be refined for a full Phase 2 LAEP. Whilst every effort has been made to ensure the quality and accuracy of the data, the Greater London Authority is not responsible for any inaccuracies and/or mistakes in the information provided. The modelling used the building cooling demand baseline mapped in the Current Demand chapter and applies building fabric retrofit measures for the two following scenarios: Shallow retrofit: Building automation and BMS; Building services interventions such as recommissioning of ventilation and cooling systems; Internal solar control devices (blinds); Replacement of/additional glazing; Air tightness improvements; and Roof/loft insulation. Deep retrofit: Everything modelled in the shallow retrofit scenario; External solar control devices (brie solei, light shelves); Window replacement ; Improve external wall insulation; and Mineral wool insulation below floor.
提供机构:
GREATER LONDON AUTHORITY
创建时间:
2025-04-03
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作