Towards carbon neutrality: mapping mass retrofit opportunities in Cambridge, UK
Data files
Jan 15, 2025 version files 2.36 MB
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EPC_and_above.xlsx
944.17 KB
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File_1_-_IMD2019_Index_of_Multiple_Deprivation.xlsx
1.41 MB
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README.md
2.53 KB
Abstract
This study proposes a methodology and a proof of concept to target and prioritise mass retrofitting of residential buildings in the UK using open building datasets that combines fabric energy efficiency and fuel poverty to meet the Net-Zero targets. The methodological framework uses a series of multivariate statistical and geo-spatial methods that consider both socio-economic and physical attributes. In addition, thermal imaging is implemented to provide insights at the building scale. We define a Hard to Decarbonise (HtD) metric to enable the clustering of different residential types to establish retrofitting priorities. Using Cambridge, UK, as a case study, five neighbourhoods were identified and characterised to help determine decarbonisation intervention priorities. We found that two of five clusters of neighbourhoods are HtD and require more policy support from government for the implementation of retrofit strategies. The achieved framework has the potential to inform policy and decision-making. Of relevance, it is applicable to different urban contexts.
README: Towards carbon neutrality: mapping mass retrofit opportunities in Cambridge, UK
https://doi.org/10.5061/dryad.3tx95x6r0
Description of the data and file structure
Towards carbon neutrality: mapping mass retrofit opportunities in Cambridge, UK
Files and variables
File: File_1_-_IMD2019_Index_of_Multiple_Deprivation.xlsx
Description: Index for multiple deprivation details the relative deprivation in small areas in England called lower super output areas (LSOA).
Variables
- LSOA code (2011)
- LSOA name (2011)
- Local Authority District code (2019)
- Local Authority District name (2019)
- Index of Multiple Deprivation (IMD) Rank
- Index of Multiple Deprivation (IMD) Decile
File: EPC_and_above.xlsx
Description: Describes the Energy Performance Certificates (EPC) of grade C or above at the LSOA levels.
Variables
- Lower super output area (LSOA) code\ Lower super output area (LSOA) name\ Percentage of dwellings with an EPC rating of C or higher
Code/software
- Excel was used to generate categoric variables and was used to create 230107_Cat data which is used loaded to R (step 2 below);
- R statistical package was used for all the analysis. R is required to run MCA and AHC; the script was created using R studio version 4.2.1.\ Annotations are provided throughout the script through 1) required packages 2) library loading, 2) data loading, 3) analyses, and 4) figure creation.\ It was used to run the Multiple Correspondence Analysis (MCA) and the Agglomerative Hierarchical Clustering (AHC).
- Excel was used to run the Clustering Enrichment (CE) based on an Over-representation analysis using hypergeometric analysis and is required to read 230513_Hypergeoemetric analysis_K5. The file includes 1) a sheet to process the hypergeometric analysis and 2) a sheet to where the the summary figure were generated.
Access information
Other publicly accessible locations of the data:
- Other data used in the study uses publically available datasets which are available here https://github.com/sdgresearch/Cambridge-HtD
These include
- Land Surface Temperature (LST) from Landsat 8 in Google Earth Engine
- Percentage of fuel poor households (FP)
- Predominant building period (PBP) Dwelling ages and Prices from Consumer Data Research Centre
Data was derived from the following sources:
- NA
Methods
Open dataset was used for the analysis. Thermal images of buildings were collected through reconnaisance survey. It was processed using statistical methods.