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# %%
import pandas as pd
import numpy as np
import pycountry
import os
from pathlib import Path
# The path to the current module's directory
current_dir = Path(__file__).parent
def _find_iso3_csv() -> Path:
"""Locate iso3.csv, checking package dir, static data cache, and env var."""
# 1. Co-located with this module (editable install / local dev)
pkg_path = current_dir / "iso3.csv"
if pkg_path.exists():
return pkg_path
# 2. Static data cache used by the Climate TRACE pipeline
cache_path = Path(os.environ.get("STATIC_DATA_CACHE_DIR", "/tmp/static_data_cache")) / "iso3.csv"
if cache_path.exists():
return cache_path
# 3. Explicit override via environment variable
env_path = os.environ.get("ISO3_CSV_PATH", "")
if env_path and Path(env_path).exists():
return Path(env_path)
# Fallback: return the package path (will raise FileNotFoundError downstream)
return pkg_path
country_to_iso3 = pd.read_csv(_find_iso3_csv())
country_to_iso3 = country_to_iso3.set_index("name")["iso3"].to_dict()
# %%
waste_fraction_defaults = {
"Australia and New Zealand": [
0.259,
0.122,
0.065,
0.12,
0.029,
0.083,
0.018,
0.028,
0.0,
0.276,
1.0000001,
],
"Caribbean": [
0.469,
0.0000001,
0.024,
0.17,
0.051,
0.099,
0.05,
0.057,
0.019,
0.035,
0.9740001,
],
"Central America": [
0.627,
0,
0.003,
0.126,
0.022,
0.103,
0.027,
0.033,
0,
0.06,
1.001,
],
"Eastern Africa": [
0.444,
0.069,
0.005,
0.104,
0.03,
0.08,
0.026,
0.021,
0.004,
0.217,
1,
],
"Eastern Asia": [
0.403,
0,
0.021,
0.204,
0.01,
0.065,
0.027,
0.043,
0,
0.229,
1.002,
],
"Eastern Europe": [
0.318,
0.024,
0.025,
0.171,
0.031,
0.046,
0.007,
0.018,
0.005,
0.354,
0.999,
],
"Middle Africa": [
0.284,
0,
0,
0.08,
0.013,
0.071,
0.014,
0.011,
0.0000001,
0.527,
1.0000001,
],
"North America": [
0.202,
0.068,
0.041,
0.233,
0.039,
0.158,
0.064,
0.042,
0.016,
0.14,
1.003,
],
"Northern Africa": [
0.504,
0,
0,
0.121,
0.058,
0.138,
0.044,
0.033,
0.0000001,
0.105,
1.0030001,
],
"Northern Europe": [
0.303,
0.052,
0.018,
0.138,
0.032,
0.049,
0.014,
0.043,
0,
0.352,
1.001,
],
"Rest of Oceania": [
0.675,
0.0,
0.025,
0.06,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.7600007,
],
"South America": [
0.541,
0.033,
0,
0.124,
0.017,
0.137,
0.02,
0.03,
0.006,
0.091,
0.999,
],
"Central Asia": [
0.3,
0.014,
0.025,
0.247,
0.035,
0.084,
0.008,
0.059,
0,
0.23,
1.002,
],
"South-Eastern Asia": [
0.499,
0.01,
0.008,
0.112,
0.004,
0.102,
0.042,
0.037,
0,
0.186,
1,
],
"Southern Africa": [0.24, 0, 0, 0.145, 0.055, 0.265, 0.065, 0.09, 0, 0.14, 1],
"Southern Europe": [
0.358,
0.014,
0.012,
0.214,
0.028,
0.141,
0.02,
0.035,
0.002,
0.178,
1.002,
],
"Western Africa": [0.539, 0, 0, 0.075, 0.019, 0.064, 0.027, 0.013, 0, 0.265, 1.002],
"Western Asia": [
0.422,
0.032,
0.008,
0.153,
0.03,
0.172,
0.025,
0.034,
0.003,
0.122,
1.001,
],
"Western Europe": [
0.332,
0.027,
0.023,
0.172,
0.059,
0.205,
0.015,
0.014,
0,
0.153,
1,
],
"Southern Asia": [
0.661,
0,
0,
0.092,
0.012,
0.07,
0.009,
0.015,
0.004,
0.139,
1.002,
],
}
waste_fraction_defaults = pd.DataFrame(waste_fraction_defaults).T
waste_fraction_defaults.columns = [
"food",
"green",
"wood",
"paper_cardboard",
"textiles",
"plastic",
"metal",
"glass",
"rubber",
"other",
"total",
]
waste_fraction_defaults = waste_fraction_defaults.drop("total", axis=1)
# waste_fraction_defaults.head()
# waste_fraction_defaults = waste_fraction_defaults.T.to_dict()
waste_fractions_country = {
"Kazakhstan": [21.5, 2.8, 26.5, 0.0, 7.0, 0.0, 0.0, 16.8, 1.5, 11.8, 11.9],
"Uzbekistan": [38.4, 0.0, 22.8, 4.9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 34.0],
"China": [59.1, 0.0, 8.5, 1.6, 4.1, 0.0, 0.0, 13.0, 1.1, 4.1, 8.5],
"Japan": [26.0, 0.0, 46.0, 0.0, 0.0, 0.0, 0.0, 9.0, 8.0, 7.0, 4.0],
"Mongolia": [70.8, 0.0, 4.3, 0.0, 0.0, 0.0, 0.0, 3.8, 0.1, 3.7, 17.3],
"South Korea": [5.2, 0.0, 22.6, 6.6, 0.0, 0.0, 0.0, 0.0, 1.7, 2.3, 61.7],
"Cambodia": [65.0, 0.0, 4.0, 0.0, 0.0, 0.0, 0.0, 13.0, 1.0, 5.0, 12.0],
"Indonesia": [74.0, 0.0, 10.0, 0.0, 2.0, 0.0, 0.0, 8.0, 2.0, 2.0, 2.0],
"Laos": [54.3, 0.0, 3.3, 0.0, 0.0, 0.0, 0.0, 7.8, 3.8, 8.5, 22.3],
"Malaysia": [32.4, 0.0, 20.0, 0.0, 0.0, 0.0, 0.0, 9.8, 2.5, 3.3, 32.0],
"Myanmar": [80.0, 0.0, 4.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 14.0],
"Philippines": [41.6, 0.0, 19.5, 0.0, 0.0, 0.0, 0.0, 13.8, 4.8, 2.5, 17.8],
"Singapore": [10.1, 4.1, 15.1, 6.8, 1.9, 0.0, 0.4, 10.5, 18.6, 0.9, 31.4],
"Thailand": [48.6, 0.0, 14.6, 0.0, 0.0, 0.0, 0.0, 13.9, 3.6, 5.1, 14.2],
"Vietnam": [42.7, 5.0, 10.7, 0.0, 0.0, 0.0, 0.0, 12.9, 1.1, 5.8, 21.9],
"Bangladesh": [54.9, 0.0, 12.6, 0.0, 4.7, 0.0, 1.5, 14.7, 1.6, 1.1, 8.8],
"India": [53.0, 0.0, 6.4, 0.0, 0.0, 0.0, 0.0, 5.1, 0.2, 0.4, 35.0],
"Nepal": [80.0, 0.0, 7.0, 0.0, 0.0, 0.0, 0.0, 2.5, 0.5, 3.0, 7.0],
"Sri Lanka": [76.4, 0.0, 10.6, 0.0, 0.0, 0.0, 0.0, 5.7, 1.3, 1.3, 4.7],
"Cyprus": [34.2, 13.1, 22.5, 0.0, 0.0, 0.0, 0.0, 6.7, 0.8, 5.3, 17.4],
"Iraq": [54.8, 0.0, 7.0, 2.6, 3.5, 0.0, 0.5, 25.2, 3.0, 2.9, 0.4],
"Jordan": [52.0, 0.0, 13.0, 0.0, 0.0, 0.0, 0.0, 17.0, 1.0, 3.0, 14.0],
"Oman": [8.2, 6.1, 19.4, 1.4, 14.3, 0.0, 0.0, 31.3, 2.6, 2.9, 13.8],
"Saudi Arabia": [48.0, 0.0, 21.0, 1.0, 0.0, 0.0, 0.0, 13.0, 6.0, 4.0, 7.0],
"Palestine": [56.6, 0.0, 7.3, 0.0, 0.0, 0.0, 0.0, 14.0, 2.4, 2.0, 17.7],
"Turkiye": [48.7, 6.8, 8.1, 0.0, 2.9, 2.9, 0.0, 5.9, 1.4, 3.4, 19.9],
"United Arab Emirates": [35.4, 0.0, 24.3, 1.0, 3.2, 0.0, 1.7, 24.2, 2.4, 3.4, 4.4],
"Libya": [36.3, 0.0, 15.3, 0.0, 11.5, 0.0, 0.0, 18.6, 6.7, 3.5, 8.0],
"Tunisia": [64.4, 0.0, 8.9, 0.0, 0.0, 0.0, 0.0, 8.9, 2.0, 3.0, 12.9],
"Kenya": [64.4, 0.0, 5.9, 0.0, 0.0, 0.0, 0.0, 11.9, 1.0, 2.0, 14.9],
"Mauritius": [29.4, 34.7, 14.1, 0.0, 2.4, 0.0, 0.0, 11.7, 2.0, 1.2, 4.4],
"Tanzania": [57.1, 0.0, 10.9, 2.4, 6.7, 0.0, 0.0, 9.3, 1.9, 3.2, 8.4],
"Zambia": [39.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 7.0, 1.0, 2.0, 48.0],
"Zimbabwe": [32.0, 0.0, 18.0, 0.0, 6.0, 0.0, 2.0, 0.0, 7.0, 2.0, 33.0],
"Cameroon": [28.4, 0.0, 8.0, 0.0, 1.3, 0.0, 0.0, 7.1, 1.4, 1.1, 52.7],
"South Africa": [24.0, 0.0, 14.5, 0.0, 5.5, 0.0, 0.0, 26.5, 6.5, 9.0, 14.0],
"Ghana": [73.0, 0.0, 8.0, 0.0, 4.0, 0.0, 0.0, 8.0, 0.0, 0.0, 7.0],
"Mali": [25.0, 0.0, 4.8, 0.0, 0.0, 0.0, 0.0, 2.4, 4.8, 1.2, 61.9],
"Nigeria": [63.6, 0.0, 9.7, 0.0, 1.6, 0.0, 0.0, 8.7, 3.2, 2.6, 10.6],
"Bulgaria": [18.7, 10.0, 13.4, 1.7, 3.6, 0.0, 1.9, 0.0, 0.0, 0.0, 50.8],
"Czechia": [35.0, 0.0, 16.0, 13.0, 8.0, 0.0, 0.0, 0.0, 0.0, 0.0, 28.0],
"Hungary": [29.0, 0.0, 15.0, 0.0, 0.0, 0.0, 0.0, 17.0, 2.0, 2.0, 35.0],
"Poland": [35.9, 0.3, 14.7, 0.6, 3.7, 0.0, 0.0, 0.0, 0.0, 0.0, 44.8],
"Moldova": [29.2, 0.0, 10.1, 0.0, 1.6, 0.0, 0.0, 12.8, 1.5, 5.7, 39.0],
"Romania": [43.5, 5.3, 10.3, 1.7, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 39.2],
"Russia": [30.2, 0, 42.5, 1.5, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 21.8],
"Ukraine": [33.1, 3.8, 14.6, 1.7, 4.0, 1.1, 1.7, 6.9, 2.0, 6.9, 24.2],
"Denmark": [41.0, 4.1, 23.2, 0.0, 0.0, 0.0, 0.0, 9.2, 3.3, 2.9, 16.3],
"Estonia": [26.0, 12.0, 20.0, 3.0, 2.0, 0.0, 0.0, 9.0, 4.0, 6.0, 18.0],
"Finland": [35.1, 8.8, 20.8, 2.2, 1.7, 0.0, 0.0, 7.9, 0.0, 0.5, 23.0],
"Iceland": [41.2, 1.4, 10.3, 3.0, 3.5, 5.1, 0.0, 0.0, 0.0, 0.0, 35.4],
"Latvia": [0.0, 0.0, 6.4, 2.1, 0.0, 0.0, 0.0, 8.5, 2.4, 20.6, 60.0],
"Lithuania": [25.5, 0.0, 5.7, 1.2, 7.2, 0.0, 0.0, 0.0, 0.0, 0.0, 60.4],
"Sweden": [43.0, 10.0, 10.0, 1.0, 8.0, 3.0, 0.0, 0.0, 0.0, 0.0, 25.0],
"Croatia": [30.9, 5.7, 23.2, 1.0, 3.7, 4.0, 0.7, 22.9, 2.1, 3.7, 2.3],
"Greece": [43.1, 0.0, 22.6, 1.0, 3.3, 0.0, 0.0, 11.1, 3.2, 4.2, 11.5],
"Italy": [12.6, 0.0, 39.2, 0.0, 0.0, 0.0, 0.0, 27.6, 2.4, 5.9, 12.3],
"Portugal": [31.8, 0.0, 10.0, 0.7, 8.1, 0.0, 0.0, 12.5, 1.6, 3.2, 32.2],
"Serbia": [44.3, 0.0, 13.0, 0.0, 4.5, 4.0, 0.4, 13.9, 1.4, 4.2, 14.4],
"Slovenia": [31.8, 2.0, 22.6, 5.6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 38.0],
"Spain": [56.2, 1.8, 19.0, 0.0, 0.0, 0.0, 0.0, 10.7, 3.0, 3.3, 6.0],
"United Kingdom": [21.3, 3.5, 18.3, 5.3, 5.6, 3.1, 0.0, 18.0, 3.7, 3.0, 18.2],
"Ireland": [17.0, 4.5, 19.8, 0.0, 23.4, 6.3, 0.0, 0.0, 0.0, 0.0, 29.1],
"France": [18.8, 4.0, 14.9, 4.0, 3.0, 6.9, 0.0, 21.8, 0.0, 0.0, 26.7],
"Germany": [63.2, 0.0, 15.5, 0.0, 5.0, 0.0, 0.0, 10.4, 2.8, 3.1, 0.0],
"Luxembourg": [45.5, 5.0, 8.9, 5.0, 1.0, 5.0, 0.0, 29.7, 0.0, 0.0, 0.0],
"Netherlands": [35.0, 0.0, 26.0, 0.0, 0.0, 0.0, 0.0, 19.0, 4.0, 4.0, 12.0],
"Switzerland": [31.5, 1.7, 17.2, 1.8, 3.2, 0.0, 0.0, 44.6, 0.0, 0.0, 0.0],
"Jamaica": [62.0, 0.0, 15.0, 1.0, 5.0, 0.0, 0.0, 12.0, 2.0, 3.0, 0.0],
"Mexico": [51.4, 0.0, 13.6, 0.0, 1.5, 0.0, 0.0, 10.7, 5.1, 5.8, 12.0],
"Nicaragua": [74.8, 0.0, 9.1, 0.0, 0.0, 0.0, 0.0, 8.1, 1.0, 1.0, 6.1],
"Brazil": [53.5, 0.0, 17.6, 0.0, 0.0, 0.0, 0.0, 17.5, 2.2, 4.0, 5.3],
"Argentina": [38.8, 10.0, 13.7, 0.0, 5.0, 5.7, 1.9, 14.6, 1.8, 3.1, 5.3],
"Peru": [70.0, 0.0, 6.0, 0.0, 0.0, 0.0, 0.0, 9.0, 2.0, 2.0, 11.0],
"Canada": [18.8, 5.6, 32.3, 0.0, 0.0, 0.0, 0.0, 13.1, 3.4, 3.1, 23.7],
"United States": [21.6, 7.9, 14.3, 8.1, 7.7, 0.0, 3.1, 18.5, 9.4, 5.2, 4.2],
"Australia": [35.0, 16.5, 13.0, 1.0, 0.0, 4.0, 0.0, 16.7, 3.6, 5.6, 4.6],
"New Zealand": [16.8, 7.9, 10.9, 11.9, 5.9, 3.0, 0.0, 0.0, 0.0, 0.0, 43.6],
}
# #%%
# for country, fractions in waste_fractions_country.items():
# assert len(fractions) == 11
# assert country in lut['country'].values, country
# #%%
waste_fractions_country = {
country_to_iso3[country]: value
for country, value in waste_fractions_country.items()
}
waste_fractions_country = pd.DataFrame(waste_fractions_country).T
waste_fractions_country.columns = [
"food",
"green",
"paper_cardboard",
"wood",
"textiles",
"nappies",
"rubber",
"plastic", # singular to match waste_fraction_defaults and the model components
"metal",
"glass",
"other",
]
waste_fractions_country["other"] += waste_fractions_country["nappies"]
waste_fractions_country = waste_fractions_country.drop("nappies", axis=1)
def waste_composition_for(iso3, region):
"""Default waste-fraction Series (normalized to sum 1) for a site.
Prefer the country-specific table, but fall back to the regional default
when the country is absent OR its plastic fraction is missing/zero. Several
country rows carry no plastic data; a zero plastic share is the tell-tale
of an incomplete row that would otherwise model an implausible no-plastic
waste stream (metal/glass are small and not worth rejecting a row over).
The country table is on a 0-100 (percent) scale and the regional table on a
0-1 (fraction) scale, so we normalize before returning to make the two
interchangeable for callers (some of which feed the result straight into the
model without their own normalization step).
"""
row = None
if iso3 in waste_fractions_country.index:
candidate = waste_fractions_country.loc[iso3, :]
plastic = candidate.get("plastic")
if pd.notna(plastic) and plastic > 0:
row = candidate
# decision: waste-composition
if row is None:
row = waste_fraction_defaults.loc[region, :]
total = row.sum()
return row / total if total else row
region_lookup = {
"China": "Eastern Asia",
"Japan": "Eastern Asia",
"South Korea": "Eastern Asia",
"Mongolia": "Central Asia",
"North Korea": "Eastern Asia",
"Bangladesh": "Southern Asia",
"India": "Southern Asia",
"Nepal": "Southern Asia",
"Sri Lanka": "Southern Asia",
"Pakistan": "Southern Asia",
"Brunei Darussalam": "South-Eastern Asia",
"Cambodia": "South-Eastern Asia",
"Indonesia": "South-Eastern Asia",
"Laos": "South-Eastern Asia",
"Malaysia": "South-Eastern Asia",
"Myanmar": "South-Eastern Asia",
"Philippines": "South-Eastern Asia",
"Singapore": "South-Eastern Asia",
"Thailand": "South-Eastern Asia",
"Afghanistan": "Central Asia",
"Kazakhstan": "Central Asia",
"Tajikistan": "Central Asia",
"Turkmenistan": "Central Asia",
"Kyrgyzstan": "Central Asia",
"Uzbekistan": "Central Asia",
"Turkiye": "Western Asia",
"Armenia": "Western Asia",
"Georgia": "Western Asia",
"Azerbaijan": "Western Asia",
"Saudi Arabia": "Western Asia",
"Iran": "Southern Asia",
"Iraq": "Western Asia",
"Syria": "Western Asia",
"Lebanon": "Western Asia",
"Israel": "Western Asia",
"Kuwait": "Western Asia",
"Jordan": "Western Asia",
"Yemen": "Western Asia",
"Oman": "Western Asia",
"United Arab Emirates": "Western Asia",
"Qatar": "Western Asia",
"Bahrain": "Western Asia",
"Egypt": "Northern Africa",
"Libya": "Northern Africa",
"Tunisia": "Northern Africa",
"Algeria": "Northern Africa",
"Morocco": "Northern Africa",
"Sudan": "Northern Africa",
"South Sudan": "Northern Africa",
"Western Sahara": "Northern Africa",
"Eritrea": "Eastern Africa",
"Ethiopia": "Eastern Africa",
"Somalia": "Eastern Africa",
"Djibouti": "Eastern Africa",
"Uganda": "Eastern Africa",
"Kenya": "Eastern Africa",
"Rwanda": "Eastern Africa",
"Burundi": "Eastern Africa",
"Senegal": "Western Africa",
"The Gambia": "Western Africa",
"Guinea-Bissau": "Western Africa",
"Guinea": "Western Africa",
"Sierra Leone": "Western Africa",
"Liberia": "Western Africa",
"Cote d'Ivoire": "Western Africa",
"Ghana": "Western Africa",
"Togo": "Western Africa",
"Benin": "Western Africa",
"Nigeria": "Western Africa",
"Mali": "Western Africa",
"Burkina Faso": "Western Africa",
"Niger": "Western Africa",
"Chad": "Middle Africa",
"Central African Republic": "Middle Africa",
"Cameroon": "Middle Africa",
"Congo": "Middle Africa",
"Angola": "Middle Africa",
"Zambia": "Middle Africa",
"Gabon": "Middle Africa",
"Malawi": "Eastern Africa",
"Namibia": "Southern Africa",
"Botswana": "Southern Africa",
"Zimbabwe": "Southern Africa",
"Mozambique": "Southern Africa",
"Madagascar": "Southern Africa",
"South Africa": "Southern Africa",
"Lesotho": "Southern Africa",
"Eswatini": "Southern Africa",
"Comoros": "Eastern Africa",
"Bulgaria": "Eastern Europe",
"Croatia": "Southern Europe",
"Serbia": "Southern Europe",
"Montenegro": "Southern Europe",
"Kosovo": "Southern Europe",
"Bosnia and Herzegovina": "Southern Europe",
"Albania": "Southern Europe",
"Czechia": "Eastern Europe",
"Slovakia": "Eastern Europe",
"Slovenia": "Southern Europe",
"Romania": "Eastern Europe",
"Russia": "Eastern Europe",
"Ukraine": "Eastern Europe",
"Belarus": "Eastern Europe",
"Latvia": "Eastern Europe",
"Lithuania": "Eastern Europe",
"Estonia": "Eastern Europe",
"Poland": "Eastern Europe",
"Hungary": "Eastern Europe",
"Moldova": "Eastern Europe",
"Denmark": "Northern Europe",
"Finland": "Northern Europe",
"Sweden": "Northern Europe",
"Norway": "Northern Europe",
"Iceland": "Northern Europe",
"Cyprus": "Western Asia",
"Greece": "Southern Europe",
"Italy": "Southern Europe",
"Malta": "Southern Europe",
"Spain": "Southern Europe",
"Portugal": "Southern Europe",
"Austria": "Western Europe",
"Belgium": "Western Europe",
"Netherlands": "Western Europe",
"France": "Western Europe",
"Germany": "Western Europe",
"Ireland": "Western Europe",
"Luxembourg": "Western Europe",
"Switzerland": "Western Europe",
"United Kingdom": "Western Europe",
"The Bahamas": "Caribbean",
"Cuba": "Caribbean",
"Dominican Republic": "Caribbean",
"Saint Lucia": "Caribbean",
"Costa Rica": "Central America",
"Guatemala": "Central America",
"Belize": "Central America",
"Panama": "Central America",
"El Salvador": "Central America",
"Argentina": "South America",
"Bolivia": "South America",
"Brazil": "South America",
"Chile": "South America",
"Colombia": "South America",
"Ecuador": "South America",
"Paraguay": "South America",
"Peru": "South America",
"Uruguay": "South America",
"Venezuela": "South America",
"Canada": "North America",
"Mexico": "Central America",
"United States": "North America",
"American Samoa": "Rest of Oceania",
"Australia": "Australia and New Zealand",
"New Zealand": "Australia and New Zealand",
"Fiji": "Rest of Oceania",
"Papua New Guinea": "Rest of Oceania",
"Bhutan": "Southern Asia",
"Egypt": "Northern Africa",
"Equatorial Guinea": "Middle Africa",
"Honduras": "Central America",
"Croatia": "Southern Europe",
"Haiti": "Caribbean",
"Isle of Man": "Western Europe",
"Iran": "Southern Asia",
"Kyrgyzstan": "Central Asia",
"Kiribati": "Rest of Oceania",
"Moldova": "Eastern Europe",
"Maldives": "Southern Asia",
"Marshall Islands": "Rest of Oceania",
"North Macedonia": "Southern Europe",
"Northern Mariana Islands": "Rest of Oceania",
"Mauritania": "Western Africa",
"Nicaragua": "Central America",
"Palau": "Rest of Oceania",
"Palestine": "Western Asia",
"Solomon Islands": "Rest of Oceania",
"Slovakia": "Eastern Europe",
"Timor-Leste": "South-Eastern Asia",
"Tonga": "Rest of Oceania",
"Tuvalu": "Rest of Oceania",
"Tanzania": "Eastern Africa",
"United States": "North America",
"Venezuela": "South America",
"Vietnam": "South-Eastern Asia",
"Vanuatu": "Rest of Oceania",
"Samoa": "Rest of Oceania",
"Yemen": "Western Asia",
"Congo, The Democratic Republic of the": "Middle Africa",
"Micronesia": "Rest of Oceania",
"Guernsey": "Western Europe",
"Luxembourg": "Western Europe",
"Jersey": "Western Europe",
"Taiwan": "Eastern Asia",
"Hong Kong": "Eastern Asia",
"Macau": "Eastern Asia",
"Aruba": "Caribbean",
"Curacao": "Caribbean",
"Anguilla": "Caribbean",
"Aland Islands": "Northern Europe",
"Andorra": "Southern Europe",
"French Southern and Antarctic Lands": "Southern Africa",
"Saint Barthelemy": "Caribbean",
"Cook Islands": "Rest of Oceania",
"Cabo Verde": "Western Africa",
"Christmas Island": "Rest of Oceania",
"Monaco": "Western Europe",
"Montserrat": "Caribbean",
"Malta": "Southern Europe",
"Niue": "Rest of Oceania",
"South Georgia and the South Sandwich Islands": "South America",
"Saint Martin (French part)": "Caribbean",
"Sint Maarten (Dutch part)": "Caribbean",
"Svalbard and Jan Mayen Islands": "Northern Europe",
"Tokelau": "Rest of Oceania",
"Vatican City": "Southern Europe",
"Antigua and Barbuda": "Caribbean",
"Bouvet Island": "Rest of Oceania",
"Cocos (Keeling) Islands": "Rest of Oceania",
"Falkland Islands": "South America",
"Faroe Islands": "Northern Europe",
"Guadeloupe": "Caribbean",
"French Guiana": "South America",
"Guam": "Rest of Oceania",
"Heard Island and McDonald Islands": "Rest of Oceania",
"British Indian Ocean Territory": "Southern Asia",
"Saint Kitts and Nevis": "Caribbean",
"Liechtenstein": "Western Europe",
"Nauru": "Rest of Oceania",
"Martinique": "Caribbean",
"Pitcairn Islands": "Rest of Oceania",
"Puerto Rico": "Caribbean",
"Mayotte": "Eastern Africa",
"New Caledonia": "Rest of Oceania",
"Norfolk Island": "Rest of Oceania",
"Reunion": "Eastern Africa",
"San Marino": "Southern Europe",
"Saint Pierre and Miquelon": "North America",
"Saint Vincent and the Grenadines": "Caribbean",
"Sao Tome and Principe": "Middle Africa",
"Turks and Caicos Islands": "Caribbean",
"Trinidad and Tobago": "Caribbean",
"Virgin Islands, British": "Caribbean",
"Virgin Islands, U.S.": "Caribbean",
"Wallis and Futuna": "Rest of Oceania",
"French Polynesia": "Rest of Oceania",
"Saint Helena, Ascension and Tristan da Cunha": "Southern Africa",
"US Minor Islands": "Rest of Oceania",
"Bonaire, Sint Eustatius and Saba": "Caribbean",
"Antigua and Barbuda": "Caribbean",
"Grenada": "Caribbean",
"Barbados": "Caribbean",
"Jamaica": "Caribbean",
"Suriname": "South America",
"Dominica": "Caribbean",
"Seychelles": "Eastern Africa",
"Cayman Islands": "Caribbean",
"Guyana": "South America",
"Bermuda": "Caribbean",
"Greenland": "North America",
"Gibraltar": "Southern Europe",
"Mauritius": "Eastern Africa",
"Antarctica": "South America",
}
region_lookup_iso3 = {}
for country in region_lookup:
iso3 = country_to_iso3[country]
region_lookup_iso3[iso3] = region_lookup[country]
# tonnes/cap/yr: IPCC 2019 Refinement, Vol. 5 Ch. 2, Table 2.1 (Updated)
msw_per_capita_defaults = {
"Australia and New Zealand": 0.6,
"Caribbean": 0.78,
"Central America": 0.58,
"Central Asia": 0.34,
"Eastern Africa": 0.29,
"Eastern Asia": 0.48,
"Eastern Europe": 0.37,
"Middle Africa": 0.19,
"North America": 0.96,
"Northern Africa": 0.41,
"Northern Europe": 0.48,
"Rest of Oceania": (1.18 + 1.35)
/ 2, # Average of Melanesia and Polynesia IPCC defaults
"South America": 0.43,
"South-Eastern Asia": 0.46,
"Southern Africa": 0.33,
"Southern Asia": 0.5,
"Southern Europe": 0.47,
"Western Africa": 0.18,
"Western Asia": 0.69,
"Western Europe": 0.59,
}
msw_per_capita_defaults = {
key: (value / 365) * 1000 for key, value in msw_per_capita_defaults.items()
} # convert from tons/year to kg/day
# tonnes/cap/yr: IPCC 2019 Refinement, Vol. 5 Ch. 2, Table 2A.1 (Updated), 2010 column
msw_per_capita_country = {
"Tajikistan": 0.32,
"Turkmenistan": 0.36,
"China": 0.37,
"Japan": 0.35,
"Mongolia": 0.24,
"South Korea": 0.35,
"Brunei Darussalam": 0.32,
"Indonesia": 0.19,
"Laos": 0.26,
"Malaysia": 0.55,
"Myanmar": 0.16,
"Philippines": 0.18,
"Singapore": 1.28,
"Thailand": 0.64,
"Vietnam": 0.53,
"Bangladesh": 0.18,
"Bhutan": 0.53,
"India": 0.12,
"Iran": 0.06,
"Maldives": 0.91,
"Nepal": 0.04,
"Pakistan": 0.31,
"Sri Lanka": 1.86,
"Armenia": 0.25,
"Bahrain": 0.4,
"Cyprus": 0.69,
"Georgia": 0.62,
"Israel": 0.62,
"Jordan": 0.38,
"Kuwait": 3.05,
"Lebanon": 0.43,
"Oman": 0.26,
"Qatar": 1.25,
"Saudi Arabia": 0.47,
"Palestine": 0.38,
"Syria": 0.50,
"Turkiye": 0.41,
"United Arab Emirates": 0.61,
"Algeria": 0.44,
"Egypt": 0.5,
"Morocco": 0.53,
"Sudan": 0.29,
"Tunisia": 0.30,
"Burundi": 0.20,
"Comoros": 0.81,
"Eritrea": 0.18,
"Ethiopia": 0.11,
"Kenya": 0.11,
"Madagascar": 0.29,
"Malawi": 0.18,
"Mauritius": 0.31,
"Mozambique": 0.05,
"Reunion": 0.69,
"Rwanda": 0.19,
"Seychelles": 1.09,
"Uganda": 0.12,
"Tanzania": 0.09,
"Zambia": 0.08,
"Zimbabwe": 0.19,
"Angola": 0.18,
"Cameroon": 0.28,
"Central African Republic": 0.18,
"Chad": 0.18,
"Congo": 0.18,
"Congo, The Democratic Republic of the": 0.18,
"Gabon": 0.16,
"Sao Tome and Principe": 0.18,
"Botswana": 0.38,
"Lesotho": 0.18,
"Namibia": 0.18,
"South Africa": 0.73,
"Eswatini": 0.19,
"Benin": 0.20,
"Burkina Faso": 0.19,
"Cabo Verde": 0.18,
"Cote d'Ivoire": 0.18,
"The Gambia": 0.19,
"Ghana": 0.03,
"Mali": 0.24,
"Mauritania": 0.18,
"Niger": 0.18,
"Nigeria": 0.20,
"Senegal": 0.19,
"Sierra Leone": 0.16,
"Togo": 0.19,
"Belarus": 0.38,
"Bulgaria": 0.55,
"Czechia": 0.32,
"Hungary": 0.40,
"Poland": 0.32,
"Romania": 0.31,
"Russia": 0.34,
"Slovakia": 0.32,
"Denmark": 0.76,
"Estonia": 0.31,
"Finland": 0.47,
"Iceland": 0.48,
"Ireland": 0.62,
"Latvia": 0.32,
"Lithuania": 0.40,
"Norway": 0.47,
"Sweden": 0.44,
"United Kingdom": 0.51,
"Bosnia and Herzegovina": 0.33,
"Croatia": 0.38,
"Greece": 0.53,
"Italy": 0.55,
"Malta": 0.6,
"Montenegro": 0.54,
"Portugal": 0.52,
"Serbia": 0.36,
"Slovenia": 0.49,
"Spain": 0.51,
"North Macedonia": 0.35,
"Austria": 0.56,
"Belgium": 0.46,
"France": 0.53,
"Germany": 0.60,
"Luxembourg": 0.68,
"Netherlands": 0.57,
"Switzerland": 0.71,
"Anguilla": 1.10,
"Antigua and Barbuda": 1.39,
"The Bahamas": 1.19,
"Barbados": 1.73,
"Cuba": 0.3,
"Dominica": 0.32,
"Dominican Republic": 0.43,
"Grenada": 0.99,
"Guadeloupe": 0.60,
"Haiti": 0.37,
"Jamaica": 0.07,
"Saint Kitts and Nevis": 1.99,
"Saint Lucia": 0.25,
"Saint Vincent and the Grenadines": 0.35,
"Trinidad and Tobago": 0.58,
"Belize": 1.05,
"Costa Rica": 0.5,
"El Salvador": 0.41,
"Guatemala": 0.73,
"Honduras": 0.53,
"Mexico": 0.34,
"Nicaragua": 0.4,
"Panama": 0.44,
"Argentina": 0.37,
"Bolivia": 0.12,
"Brazil": 0.31,
"Chile": 0.35,
"Colombia": 0.35,
"Ecuador": 0.41,
"French Guiana": 0.37,
"Guyana": 1.95,
"Paraguay": 0.08,
"Peru": 0.37,
"Suriname": 0.50,
"Uruguay": 0.04,
"Venezuela": 0.42,
"Bermuda": 1.3,
"Canada": 0.85,
"United States": 0.74,
"Australia": 0.61,
"New Zealand": 0.58,
"Fiji": 0.77,
"Solomon Islands": 1.57,
"Vanuatu": 1.2,
"Tonga": 1.35,
"Hong Kong": 0.93,
"Macao": 0.62,
}
msw_per_capita_country = {
key: (value / 365) * 1000 for key, value in msw_per_capita_country.items()
} # convert from tons/year to kg/day
msw_per_capita_country = {
country_to_iso3[country]: value for country, value in msw_per_capita_country.items()
}
msw_per_capita_city = {"Hong Kong": 0.93, "Macao": 0.62}
msw_per_capita_city = {
key: (value / 365) * 1000 for key, value in msw_per_capita_city.items()
} # convert from tons/year to kg/day
k_defaults = {
"Dry": {
"food": 0.1,
"diapers": 0.1,
"green": 0.05,
"paper_cardboard": 0.02,
"textiles": 0.02,
"wood": 0.01,
"rubber": 0.01,
},
"Moderately Dry": {
"food": 0.18,
"diapers": 0.18,
"green": 0.09,
"paper_cardboard": 0.036,
"textiles": 0.036,
"wood": 0.018,
"rubber": 0.018,
},
"Moderately Wet": {
"food": 0.26,
"diapers": 0.26,
"green": 0.12,
"paper_cardboard": 0.048,
"textiles": 0.048,
"wood": 0.024,
"rubber": 0.024,
},
"Wet": {
"food": 0.34,
"diapers": 0.34,
"green": 0.15,
"paper_cardboard": 0.06,
"textiles": 0.06,
"wood": 0.03,
"rubber": 0.03,
},
"Very Wet": {
"food": 0.4,
"diapers": 0.4,
"green": 0.17,
"paper_cardboard": 0.07,
"textiles": 0.07,
"wood": 0.035,
"rubber": 0.035,
},
}
# k_defaults = pd.DataFrame(k_defaults).T
# Function to get precipitation zone from annual rainfall
def get_precipitation_zone(rainfall):
# Unit is mm
if rainfall < 500:
return "Dry"
elif rainfall < 1000:
return "Moderately Dry"
elif rainfall < 1500:
return "Moderately Wet"
elif rainfall < 2000:
return "Wet"
else:
return "Very Wet"
L_0 = {
"food": 70,
"diapers": 112,
"green": 93,
"paper_cardboard": 186,
"textiles": 112,
"wood": 200,
"rubber": 100,
}
oxidation_factor = {
"with_lfg": {
"landfill": 0.22,
"controlled_dumpsite": 0.1,
"dumpsite": 0,
"remediated_to_landfill": 0.18,
},
"without_lfg": {
"landfill": 0.1,
"controlled_dumpsite": 0.05,
"dumpsite": 0,
"remediated_to_landfill": 0.1,
},
}
# t CH4 per tonne digested (0.26 kg per short ton, EPA WARM AD chapter, 100% food
# waste, via the SWEET Excel). Methane, unlike the compost factor, which is CO2e.
# The Excel notes it leaves out methane leakage from the AD plant itself.
mef_anaerobic = 0.26 / 1000 * 1.1023
ch4_to_co2e = 28
gas_capture_efficiency = {"landfill": 0.6, "controlled_dumpsite": 0.45, "dumpsite": 0}
landfill_default_regions = set(
[
"Eastern Asia",
"Eastern Europe",
"North America",
"Northern Europe",
"Southern Europe",