Mismatch between solar resource endowment and PV development in China: provincial-level dataset (2020)

Dataset This dataset provides a comprehensive provincial-level assessment of solar energy resources, photovoltaic (PV) development, and associated spatial equity indicators for mainland China for the year 2020. It was compiled to support the analysis and conclusions of the manuscript "Mismatch Between Solar Resource Endowment and Photovoltaic Development in China: A Provincial Assessment of Accessibility and Inequality." ### Files in this Dataset * **`china_pv_equity_data_2020.csv`**: The main dataset containing the final calculated indicators for each of the 31 mainland provinces.* **`Grid50km_Pop_2020.zip`**: A compressed archive containing the processed 50km gridded population data for China in shapefile (.shp) format.* **`china_province_boundaries.zip`**: A compressed archive containing the administrative boundaries for the 31 mainland provinces of China in shapefile (.shp) format. ### Variable Descriptions **1. For `china_pv_equity_data_2020.csv`:** | Column Name | Description || :--- | :--- || `province_ID` | Unique numerical identifier for each province. || `province_name` | Name of the province in Pinyin. || `Region` | Regional classification: 'E' for Eastern, 'W' for Western. || `PV_Acc` | Population Weighted PV Accessibility (PVaccess). || `Rad_Acc` | Population Weighted Solar Radiation Accessibility (Radaccess). || `Index_coord` | Coordination Index (`PV_Acc` - `Rad_Acc`). || `PV_Gini` | Intra-provincial Gini coefficient for PV development. || `Rad_Gini` | Intra-provincial Gini coefficient for solar resources. || `Index_exac` | Inequality Exacerbation Index (`PV_Gini` - `Rad_Gini`). || `GDP in 2020` | Gross Domestic Product in 2020 (Unit: 100 million CNY). | **2. For `Grid50km_Pop_2020.shp` (within the .zip file):** | Field Name | Description || :--- | :--- || `FID_Provin` | Numerical identifier for the province. Same as 'province_id' in other datasets. || `Name` | The name of the province in which the 50km grid cell is located. || `Only` | Unique identifier for each 50km grid cell. || `COUNT` | The number of 1km WorldPop grid cells that fall within the 50km grid cell. || `SUM` | The total population within the 50km grid cell, aggregated from 1km WorldPop data. || `Shape_Leng` | The perimeter of the grid cell polygon. || `Shape_Area` | The area of the grid cell polygon. | **3. For `china_province_boundaries.shp` (within the .zip file):** | Field Name | Description || :--- | :--- || `Name` | Name of the province. || `province_id` | Unique numerical identifier for the province. || `Region` | Regional classification ('E' or 'W'). | Code/software All data processing, spatial analysis, and indicator calculations were performed using a combination of ArcGIS Pro, Microsoft Excel, and Python 3 (utilizing libraries such as Pandas, GeoPandas, and NumPy). The key processing steps included: Aggregating the 1-km resolution WorldPop population data to a 50-km grid to create the Grid50km_Pop_2020 dataset. Spatially joining and summarizing the raw photovoltaic distribution and solar radiation data within each provincial boundary. Calculating the Population Weighted Exposure (PWE) based indices (PV_Acc, Rad_Acc) for each province using the 50km gridded population data as weights. Calculating the intra-provincial Gini coefficients (PV_Gini, Rad_Gini) based on the spatial distribution of resources/infrastructure and population within each province. Compiling all final indicators and socioeconomic data into the china_pv_equity_data_2020.csv file. Access information Other publicly accessible locations of the data: Population spatial distribution data: The "WorldPop Global Project Population Data" is openly available from the WorldPop project website at: https://www.worldpop.org Solar resource data: The "National Solar Radiation Database (NSRDB)" is openly available from the U.S. National Renewable Energy Laboratory (NREL) at: https://nsrdb.nrel.gov Geographical data: The administrative boundary data for provinces are available from the National Geographic Center of China at: https://www.ngcc.cn/ Socioeconomic data: The provincial GDP data are available in the "China Statistical Year-book-2021," published by the National Bureau of Statistics of China at: http://www.stats.gov.cn/sj/ndsj/2021/indexeh.htm Photovoltaic spatial distribution data: Lyu, X. et al. (2024) in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (DOI: 10.1109/JSTARS.2024.3468627)