DOI: 10.57760/sciencedb.35623
title: An integrated dataset of PM2.5, elevation, and meteorological variables over China at a 10-km resolution (2000-2023)
title: 2000-2023年中国10km网格-PM2.5、海拔和气象模态融合数据集

description: The construction of this dataset aims to provide a standardized set of macro environmental input data to support the analysis of regional air quality mechanisms, correction of pollutant deviations, and development of deep learning spatiotemporal prediction models in China. In terms of data source selection, the dataset integrates high-quality data products from multiple heterogeneous sources, including the China High Quality PM2.5 dataset (CHAP), the China Regional Ground Meteorological Element Driven Dataset (CMFD V2.0), and a digital elevation model generated based on the Open Elevation API. In the process of dataset production, it is necessary to perform spatiotemporal alignment on multi-source grid data. Pre set a spatial grid of 0.1 °× 0.1 ° (approximately 10km) within the Chinese region as the standard reference grid. In terms of time scale, the original annual meteorological grid data is split into "days" to unify the time granularity. During spatial alignment operation, the 1km resolution CHAP PM2.5 data is resampled to the reference grid through nearest neighbor interpolation, and the elevation data corresponding to the latitude and longitude of the reference grid is matched using the Open Elevation API. Finally, the aligned PM2.5 concentration, elevation data, and 11 meteorological variables will be merged to generate a daily standardized NetCDF file. After cross validation with measured data from ground monitoring stations nationwide, the results showed that PM2.5 data had a high correlation with ground observations at a scale of 10km, with a determination coefficient R2 of 0.9154, fully verifying the usability and accuracy of the dataset. This dataset covers the entire region of China, with a time span from January 1, 2000 to December 31, 2023. The time resolution is daily and the spatial resolution is 10km. Each data file contains 13 core variables: PM2.5 concentration, surface elevation, temperature, surface pressure, relative humidity, wind speed, precipitation rate, rainfall, snowfall, shortwave radiation, longwave radiation, specific humidity, and black carbon. The data files are stored in the universal NetCDF (. nc) format, and it is recommended to use Python (xarry, netCDF4 library) or software such as Panoply and QGIS to read and process them. 
description: The construction of this dataset aims to provide a standardized set of macro environmental input data to support the analysis of regional air quality mechanisms, correction of pollutant deviations, and development of deep learning spatiotemporal prediction models in China. In terms of data source selection, the dataset integrates high-quality data products from multiple heterogeneous sources, including the China High Quality PM2.5 dataset (CHAP), the China Regional Ground Meteorological Element Driven Dataset (CMFD V2.0), and a digital elevation model generated based on the Open Elevation API. In the process of dataset production, it is necessary to perform spatiotemporal alignment on multi-source grid data. Pre set a spatial grid of 0.1 °× 0.1 ° (approximately 10km) within the Chinese region as the standard reference grid. In terms of time scale, the original annual meteorological grid data is split into "days" to unify the time granularity. During spatial alignment operation, the 1km resolution CHAP PM2.5 data is resampled to the reference grid through nearest neighbor interpolation, and the elevation data corresponding to the latitude and longitude of the reference grid is matched using the Open Elevation API. Finally, the aligned PM2.5 concentration, elevation data, and 11 meteorological variables will be merged to generate a daily standardized NetCDF file. After cross validation with measured data from ground monitoring stations nationwide, the results showed that PM2.5 data had a high correlation with ground observations at a scale of 10km, with a determination coefficient R2 of 0.9154, fully verifying the usability and accuracy of the dataset. This dataset covers the entire region of China, with a time span from January 1, 2000 to December 31, 2023. The time resolution is daily and the spatial resolution is 10km. Each data file contains 13 core variables: PM2.5 concentration, surface elevation, temperature, surface pressure, relative humidity, wind speed, precipitation rate, rainfall, snowfall, shortwave radiation, longwave radiation, specific humidity, and black carbon. The data files are stored in the universal NetCDF (. nc) format, and it is recommended to use Python (xarry, netCDF4 library) or software such as Panoply and QGIS to read and process them.