Data Preprocessing

If you have your own emission data, CINEI provides tools to check and standardize it into the required format before integration.

CINEI Standard Format

import cinei
cinei.show_cinei_standard()

Property	Requirement
Format	NetCDF (.nc)
Dimensions	`(month, lat, lon)`
Month	integer 1–12
Units	ton/grid/month
Resolution	flexible (regridded to 0.25° in `emis_union`)

Required sector variables

CINEI variable	CEDS input	MEIC input	HTAP/other
`power`	energy	power	—
`residential`	residential + solvents	residential	—
`industry`	industrial	industry	—
`transportation`	transportation	transportation	—
`agriculture`	agriculture	agriculture	—
`shipping`	ships	—	shipping
`waste`	—	—	waste
`aviation`	—	—	aviation
`sum`	computed automatically

Note

sum does not include aviation — consistent with CINEI v1 methodology.

Step 1: Check your data

import cinei

# Check a NetCDF file
report = cinei.check_user_data('/path/to/my_emission.nc')
print(report['status'])   # 'ok', 'warning', or 'error'
print(report['issues'])
print(report['suggestions'])

# Check a txt/csv file
report = cinei.check_user_data('/path/to/my_emission.txt')

Step 2: Standardize NetCDF

# Auto-standardize (fixes dims and sector names automatically)
out = cinei.standardize_netcdf('/path/to/my_emission.nc')

# With manual sector mapping (when auto-detection fails)
out = cinei.standardize_netcdf(
    '/path/to/my_emission.nc',
    sector_mapping={
        'agr_emis':  'agriculture',
        'ind_emis':  'industry',
        'pow_emis':  'power',
        'res_emis':  'residential',
        'tra_emis':  'transportation',
        'shp_emis':  'shipping',
    }
)

Tip

Missing sectors are automatically filled with zeros. The sum variable is always recomputed from all available sectors.

Step 3: Convert txt to NetCDF

# Auto-convert (column names auto-detected)
out = cinei.txt_to_netcdf('/path/to/my_emission.txt')

# With manual column mapping
out = cinei.txt_to_netcdf(
    '/path/to/my_emission.txt',
    lat_col='latitude',
    lon_col='longitude',
    month_col='mon',
    sector_cols={
        'agr': 'agriculture',
        'ind': 'industry',
        'pow': 'power',
        'res': 'residential',
        'tra': 'transportation',
    }
)

Expected txt format:

lat    lon     month  agr     ind     pow     res     tra
10.05  70.05   1      0.12    0.45    0.33    0.21    0.67
10.05  70.05   2      0.11    0.44    0.31    0.20    0.65
...

Accepted sector name aliases

CINEI automatically maps common alternative names:

CINEI standard	Accepted aliases
`agriculture`	agr, agri, act, agricultural
`industry`	ind, idt, industrial, manufacturing
`power`	pwr, ene, energy, electricity
`residential`	res, rdt, domestic, household
`transportation`	tra, tpt, transport, road, traffic
`shipping`	shp, ship, marine
`waste`	wst, swd, solid_waste
`aviation`	avi, air, aircraft
`sum`	total, tot, all, anthro