Sources:

Data: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019RG000691
The original code for the evaluation of GWP/GTP from AR6 Table 7.SM.7 is available here: https://github.com/chrisroadmap/ar6/blob/main/notebooks/335_chapter7_generate_metrics.ipynb
The actual metrics calculations is here: https://github.com/chrisroadmap/ar6/tree/main/src/ar6/metrics

In [1]:

import pandas as pd
import numpy as np

In [2]:

data = pd.read_csv('/Users/timodiepers/Documents/Coding/timex/bw_timex/data/hodnebrog20.csv', usecols=["CASRN", "Molar mass", "Lifetime (yr)", "RE (W m-2 ppb-1)"]).dropna()

In [3]:

data

Out[3]:

	CASRN	Molar mass	Lifetime (yr)	RE (W m-2 ppb-1)
1	75-69-4	0.13736	52.0000	0.25941
2	75-71-8	0.12091	102.0000	0.31998
3	75-72-9	0.10446	640.0000	0.27752
4	76-12-0	0.20382	63.6000	0.28192
5	76-11-9	0.20382	52.0000	0.24564
...	...	...	...	...
610	141-63-9	0.38489	0.0110	0.06400
611	541-05-9	0.22248	0.0384	0.10000
612	556-67-2	0.29664	0.0274	0.12000
613	541-02-6	0.37080	0.0164	0.09800
614	540-97-6	0.44496	0.0110	0.08600

243 rows × 4 columns

In [4]:

def format_cas(cas):
    # Split the CAS number by the dash
    parts = cas.split('-')
    # Format the first part to ensure it has 6 digits
    parts[0] = parts[0].zfill(6)
    # Join the parts back together and return
    return '-'.join(parts)

M_air = 28.97e-3  # kg/mol, dry air
m_atmosphere = 5.135e18  # kg [Trenberth and Smith, 2005]

decay_multipliers_dict = {}
 
for cas, tau, M, radiative_efficiency_ppb in zip(data['CASRN'], data['Lifetime (yr)'], data['Molar mass'], data['RE (W m-2 ppb-1)']):
    
    if cas == "2551-62-4":
        tau = 1000 # Decreased lifetime of SF6 from 3200 to 1000 years. See IPCC AR6, Ch. 2.2.4.3. doi: 10.1017/9781009157896.004
    
    # for conversion from ppb to kg-CH4
    radiative_efficiency_kg = (
        radiative_efficiency_ppb * M_air / M * 1e9 / m_atmosphere
    )  # W/m2/kg-CH4;

    decay_multipliers: list = np.array(
        [
            radiative_efficiency_kg * tau * (1 - np.exp(-year / tau))
            for year in range(2000)
        ]
    ).tolist()
    
    decay_multipliers_dict[format_cas(cas)] = decay_multipliers

In [5]:

import json

In [6]:

with open('decay_multipliers.json', 'w') as f:
    json.dump(decay_multipliers_dict, f)

In [ ]: