Spatioemporal variations of building sector carbon dioxide emissions from 2030 to 2060 in the GBA.

Future building carbon emission maps with a spatial resolution of 500 meters under different SSP scenarios in the Guangdong-Hong Kong-Macao Greater Bay AreaThis dataset provides high-resolution (500 meters) spatial distribution maps of building carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area in the future (up to 2060) under different shared socio-economic path (SSP) scenarios. This study is based on an integrated modeling framework, which utilizes multi-source data such as urban form (LCZ) and population distribution, and through machine learning models like support vector regression (SVR), downscales the city-level multi-scenario (including business as business BAU and carbon Neutral CN) carbon emission prediction results to a 500-meter grid. It can accurately predict the spatial distribution pattern of future building carbon emissions under different development paths, providing data support for the research on urban carbon neutrality paths, sustainable planning and climate change mitigation strategies.Future per capita building carbon emission maps with a spatial resolution of 500 meters under different SSP scenarios in the Guangdong-Hong Kong-Macao Greater Bay AreaThis dataset provides high-resolution (500 meters) spatial distribution maps of per capita building carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area in the future (up to 2060) under different shared socio-economic path (SSP) scenarios. This dataset is generated based on the prediction of total carbon emissions from buildings by dividing the predicted values of carbon emissions from each 500-meter grid by the high-resolution population prediction data within the corresponding grid. It can precisely reveal the carbon intensity and spatial equity of building usage in different regions in the future, providing key data support for formulating targeted emission reduction policies, evaluating sustainable urban development, and studying carbon neutrality strategies from the perspective of residents' lives.