CINEI V1.1: Python code for creating an integrated inventory of anthropogenic emission for China
This Python code aims to create an integrated anthropogenic emissions inventory for China. The code integrates existing emission inventories for uniform spatial resolution and more comprehensive sectors of human activities and speciated non-methane volatile organic compounds (NMVOCs). To accomplish this, we follow this workflow, which is provided as files of Python code: (1) The 'regridding.py' file is used to create the grid proxy in 0.25 spatial degrees for all data in different resolutions. (2) 'inte_all.py' file is used to create the NETCDF files for all types with 8 sectors and combine the national inventory for China and global inventory for region outside of China. The power generation, transportation, industry, residential sectors are from national inventory (MEIC), as well as the national-omitted sectors are from global inventories, which include shipping (from Copernicus Atmosphere Monitoring Service emissions inventory, CAMs), aviation (from Hemispheric Transport of Air Pollution inventory, HTAP), agriculture (from HTAP), and waste (from CEDS). (3) The 'VOC_species_nc.py' file is used to speciate the NMVOC emission as 20 species, following the chemical speciation of the Model for Ozone and Related chemical Tracers mechanism (MOZART), and finally to create the NETCDF file for each speciated emission. Therefore, this code works as a tool to process the emissions and make more representative inventory for policy making and application in chemistry and transport models (CTMs).
Institutions
- University of Bremen (DE)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-10
- DOI
- https://doi.org/10.5281/zenodo.15000794
- Primary Topic
- Acute Lymphoblastic Leukemia research
- Type
- article
- Field-Weighted Citation Impact
- 0.00