#!/usr/bin/env python
# coding: utf-8

# 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


# 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)


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