Indonesia sizes its waste from its own IPCC row, not South-Eastern Asia's

SWEET_python/defaults_2019.py

@@ -686,6 +686,7 @@ def waste_composition_for(iso3, region):
 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,
@@ -712,6 +713,7 @@ def waste_composition_for(iso3, region):
 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,
@@ -720,6 +722,7 @@ def waste_composition_for(iso3, region):
     "Mongolia": 0.24,
     "South Korea": 0.35,
     "Brunei Darussalam": 0.32,
+    "Indonesia": 0.19,
     "Laos": 0.26,
     "Malaysia": 0.55,
     "Myanmar": 0.16,

changelog/2026-10.md

@@ -0,0 +1,29 @@
+# SWEET_python Changelog — October 2026
+
+**Highlights:** Indonesia sizes its waste from its own row of the IPCC table
+SWEET copies its per-capita waste rates from, instead of the South-Eastern Asia
+default, which was 2.4 times higher (model-output change).
+
+## Fixed
+
+- **Indonesia has a per-capita waste rate of its own** (model-output change).
+  `defaults_2019.msw_per_capita_country` copies IPCC 2019 Refinement, Vol. 5
+  Ch. 2, Table 2A.1 (Updated), 2010 column, in tonnes per person per year. All
+  167 of its rows match the IPCC's, but Indonesia's, 0.19, was never typed in.
+  Indonesia fell back to the South-Eastern Asia default, 0.46. The IPCC's source
+  for the row, What a Waste 2012, agrees: 0.52 kg per person per day is 0.19 t
+  a year.
+  - A Custom Location (`dst_baseline_blank`) in Indonesia is sized at 190,000 t
+    a year per million people, down from 460,000 (−58.7%). Its emissions fall by
+    the same share once a Custom Location in South-Eastern Asia disposes of its
+    waste ([#74](https://github.com/RMI/SWEET_python/pull/74)); until then
+    they are zero either way.
+  - WasteMAP's June 2026 cities table does not move. All 11 Indonesian cities
+    have waste figures of their own, so `load_andre_params` never reaches the
+    default for them.
+  - Climate TRACE's pipeline does not move. It drops a site with no tonnage
+    before SWEET runs.
+
+  The comments on `msw_per_capita_defaults` and `msw_per_capita_country` now
+  name the IPCC tables they come from.
+  ([#76](https://github.com/RMI/SWEET_python/pull/76))

changelog/README.md

@@ -15,6 +15,7 @@ The project does not publish semantic version tags, so releases are tracked by
 
 Newest first:
 
+- [2026-10](2026-10.md) — Indonesia sizes its waste from its own IPCC per-capita row instead of the South-Eastern Asia default, 2.4× higher (model-output change)
 - [2026-09](2026-09.md) — WasteMAP's site tool, city tool and Custom Location grow waste with the country's UN population year by year, as Climate TRACE does; big cities keep their own UN city rates (model-output change); model output frames get one fixed waste-type column order instead of a per-process one (a `set` fed the ordering, and Python randomizes set iteration per process), moving values in the last bit only, where a sum runs across the reordered columns; City DST's diversion sum stops passing pandas a keyword pandas is removing, which would have broken the model path on pandas 4 behind a misleading `AttributeError` (no output change); annual model no longer charges a flare's inefficiency twice (a hardcoded 2% slip stacked on the `flaring` destruction efficiency), so it agrees with the monthly model again and a site with gas capture emits ~3.5% less (model-output change); `gas_capture_efficiency` bounded to [0, 1], where an out-of-range value used to produce negative emissions silently; one methane density constant instead of two 9.1% apart
 - [2026-08](2026-08.md) — Single-site adst gains optional `depth` (deep-dump MCF bump) and `k_override` (caller-supplied decomposition rate) inputs, restoring the last two site-DST levers; `/sdst` flaring efficiency reaches the model again after a variable-name bug silently forced flare destruction to 0.98; annual model applies cover oxidation by emission year not deposit year, fixing biocover having no effect on closed landfills (WasteMAP #719); `City.sdst_v1_5` custom-site path holds the scenario equal to the baseline before the implementation year even when composition changes (was back-dating the new composition onto pre-implementation deposits) (model-output change); MCF consolidated into a new `SWEET_python.mcf` module and both dump types moved to the IPCC uncategorised-SWDS 0.6 (open dumps up from 0.4, controlled dumps down from 0.7), with a supplied depth now selecting the deep/shallow category (model-output change)
 - [2026-07](2026-07.md) — All ten waste types eligible for combustion (metal/glass/other added); methane-only model treats combustion as landfill diversion (model-output change)

tests/test_msw_per_capita.py

@@ -0,0 +1,53 @@
+"""Per-capita waste generation defaults (`defaults_2019.msw_per_capita_country`).
+
+The table is IPCC 2019 Refinement, Vol. 5 Ch. 2, Table 2A.1 (Updated), 2010
+column, in tonnes per person per year, converted to kg per person per day. Every
+row matched the IPCC's except one: Indonesia, which the IPCC lists at 0.19, had
+no row. A Custom Location or a cities-table city in Indonesia with no waste
+figure of its own was sized from the South-Eastern Asia default instead, 0.46,
+2.4 times the country's own row.
+"""
+
+import numpy as np
+import pytest
+
+from SWEET_python import defaults_2019
+from SWEET_python.city_params import City
+
+_POP = 1_000_000
+
+
+def _kg_per_day(tonnes_per_year):
+    return tonnes_per_year / 365 * 1000
+
+
+def test_indonesia_has_its_own_row():
+    assert defaults_2019.msw_per_capita_country["IDN"] == pytest.approx(_kg_per_day(0.19))
+
+
+def test_every_south_eastern_asian_country_the_ipcc_lists_has_a_row():
+    # Table 2A.1's South-Eastern Asia block. Cambodia and Timor-Leste are not in
+    # it, so they take the regional default.
+    ipcc_rows = {
+        "BRN": 0.32, "IDN": 0.19, "LAO": 0.26, "MYS": 0.55, "MMR": 0.16,
+        "PHL": 0.18, "SGP": 1.28, "THA": 0.64, "VNM": 0.53,
+    }
+    for iso3, tonnes_per_year in ipcc_rows.items():
+        assert defaults_2019.msw_per_capita_country[iso3] == pytest.approx(
+            _kg_per_day(tonnes_per_year)
+        ), iso3
+
+
+def test_a_custom_location_in_indonesia_is_sized_from_indonesias_row():
+    city = City("custom")
+    city.dst_baseline_blank("Indonesia", _POP, 2000.0, 27.0)
+
+    # Was 460,000: the South-Eastern Asia default, 0.46 t per person per year.
+    assert np.allclose(city.baseline_parameters.waste_mass, 0.19 * _POP)
+
+
+def test_a_country_without_a_row_still_takes_its_regions_default():
+    city = City("custom")
+    city.dst_baseline_blank("Cambodia", _POP, 2000.0, 27.0)
+
+    assert np.allclose(city.baseline_parameters.waste_mass, 0.46 * _POP)