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Published April 29, 2024 | Version V2
Dataset Open

Global high-resolution growth projections dataset for rooftop area consistent with the shared socioeconomic pathways, 2020-2050.

  • 1. Energy, Climate & Environment Program, International Institute of Applied Systems Analysis, Laxenburg, Austria
  • 2. Grantham Institute–Climate Change and the Environment, Imperial College London, London, United Kingdom.
  • 3. Environmental Research Institute, University College Cork, Cork, Ireland.
  • 4. Global Centre for Environment and Energy, Ahmedabad University, Ahmedabad, India.
  • 5. MaREI, the SFI Research Centre for Energy, Climate and Marine, University College Cork, Ireland
  • 6. Center on Global Energy Policy, Columbia University, USA

Description

Description (V2 - Latest):

To enable easy integration in the workflows, we have provided the main datasets in the following formats:

 

  • Vector dataset: Folder - Vector The global gross estimated rooftop area per FN grid cell for each SSP narrative is provided as a Geopackage (.gpkg) file (Results_Vis.gpkg) with polygon geometries at 1/8-degree spatial resolution in an EPSG:4326 coordinate system. The attribute table of this file contains FN_ID column representing the FN grid cell ID, and other columns representing the FN_ID specific assessed rooftop area. The assessed gross rooftop area columns are sequenced as BF_X_Y with X having values as 1, 2, 3, 4, and 5 for SSP1, SSP2, SSP3, SSP4, SSP5 narratives with Y representing the assessment year having values as 20, 30, 40, and 50 for years 2020, 2030, 2040, and 2050 and with km2 units. In addition, a CF column is added for each FN_ID entry that documents the Capacity Factor for rooftop solar PV based on the World Bank solar atlas.

 

  • Raster datasets:  Folder - Raster The global gross estimated rooftop area per FN grid cell for each SSP narrative is provided as a geotiff (.tif) files with LZW compression in an EPSG:4326 coordinate system. The assessed gross rooftop area datasets are sequenced as BF_X_Y with X having values as 1, 2, 3, 4, and 5 for SSP1, SSP2, SSP3, SSP4, SSP5 narratives with Y representing the assessment year having values as 20, 30, 40, and 50 for years 2020, 2030, 2040, and 2050 and with km2 units.

 

  • Numerical dataset:  Folder - Numerical The global gross estimated rooftop area per FN grid cell for each SSP narrative is provided as a parquet (.parquet) file (Results.parquet). This file contains FN_ID column representing the FN grid cell ID, and other columns representing the FN_ID specific assessed rooftop area. The assessed gross rooftop area columns are sequenced as BF_X_Y with X having values as 1, 2, 3, 4, and 5 for SSP1, SSP2, SSP3, SSP4, SSP5 narratives with Y representing the assessment year having values as 20, 30, 40, and 50 for years 2020, 2030, 2040, and 2050 and with km2 units. In addition, a CF column is added for each FN_ID entry that documents the Capacity Factor for rooftop solar PV based on the World Bank solar atlas.

 

In addition to the main datasets, we have provided additional files to enable generating the vector and numerical datasets from this study:  Folder - Models

  • M2_Model.json: This file contains the frozen parameters of the M2 model in .json format generated from XGBoost version 2.0.3
  • SSP_drivers.parquet: This file contains the driver data used for generating the main dataset in our study
  • FN_MAP.parquet: This file contains the boundary information for each fishnet grid tile in a Well Known Text (WKT) format.
  • Prediction.ipynb: This file provides a python notebook interface to generate inferencing from M2_Model.json using SSP_drivers.parquet file. In addition, this file also generates the numerical dataset and converts it into vector dataset using FN_MAP.parquet file.
  • environment.yaml: This file contains the frozen configuration of python virtual environment used to generate the results presented in this study.

 

Version history:

This version corresponds to the revised journal submission (Round 1). The version will be updated upon the completion of the review of the main manuscript.

  • This version V2 is supersedes V1 to correspond with round 1 of review.
  • The database(s) in this version is associated with a Data Descriptor paper manuscript entitled " Global high-resolution growth projections for rooftop area consistent with the shared socioeconomic pathways, 2020-2050 ", submitted to Scientific Reports Journal (https://www.nature.com/srep/)

 

Changelog:

The following files from version V1 of this dataset are now archived based on the reviews (Round 1).

  1. 1_Geospatial_Dataset_V1.gpkg
  2. 2_Countrylevel_gross_rooftop_area_V1.parquet
  3. 3_Analytics_Scripts_V1.ipynb

Files

Dataset_V2_29042024.zip

Files (353.9 MB)

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Additional details

Funding

Multi-model innovations in Integrated Assessment Modelling of Global, Chinese, and Irish energy-economy-environment-climate systems investigating deep decarbonisation pathways from the Paris Agreement to the United Nations sustainable development goals 17/NSFC/5181
Science Foundation Ireland
CircEUlar – Developing circular pathways for a EU low-carbon transition 101056810
European Commission
DIAMOND – Delivering the next generation of open Integrated Assessment MOdels for Net-zero, sustainable Development 101081179
European Commission

Software

Programming language
Python