CARBOMICA — CARBOn Mitigation Intervention for healthCare fAcilities

A resource-allocation modelling tool for healthcare decision-makers who need to reduce their facility's carbon footprint within real budget constraints.

Funded by: European Union — Horizon Europe Grant No. 101057843 Project: HIGH Horizons — Heat Indicators for Global Health Coordinator: Ghent University (Stanley Luchters) Partners: Wits Planetary Health (ZA) · CeSHHAR Zimbabwe (ZW) · Aga Khan Health Service Kenya (KE) · Burnet Institute (AU)

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What CARBOMICA does

Given a facility's current carbon emissions and a budget ceiling, CARBOMICA identifies the optimal package of carbon mitigation interventions through three comparative scenarios:

Scenario	Logic
Full coverage	All interventions applied — shows maximum possible reduction
Fixed budget	Cheapest interventions first until budget is exhausted
Optimised	Greedy knapsack: maximises tCO₂e reduced per USD spent

Health managers can compare scenarios side-by-side to make evidence-grade investment decisions aligned with SDGs, national climate policy, and EU funding criteria.

The tool builds on ATOMICA (a resource-allocation simulation framework), adapting its optimisation engine for the healthcare sustainability context. Carbon emission data follows the AKDN Carbon Management Tool methodology, covering 10 emission categories across Scope 1, 2, and 3.

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Emission categories (10 — matching AKDN methodology)

#	Category	Scope
1	Grid electricity	2
2	Grid / piped gas	1
3	Bottled gas (LPG)	1
4	Liquid fuel (diesel)	1
5	Vehicle fuel — owned fleet	1
6	Business travel	3
7	Anaesthetic gases	1
8	Refrigeration gases (HFCs)	1
9	Waste management	3
10	Medical inhalers (MDI propellants)	1

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CARBOMICA intervention library

Eight evidence-based interventions from the HIGH Horizons D3.7 case studies:

Intervention	Primary SDGs	Typical LMIC payback
Solar PV System	7, 13	5 years
Low-GWP Anaesthetic Gases	3, 13	18 months
LED Lighting Upgrade	7, 11	2 years
Medical Waste Segregation	3, 12	12 months
Water-Efficient Fixtures	6, 11	3 years
Low-GWP Refrigerant Conversion	13	4 years
Switch to Dry-Powder Inhalers	3, 13	12 months
Fleet & Travel Optimisation	11, 13	18 months

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Current study sites

Facility	Country	Type
Mt Darwin District Hospital	Zimbabwe	District hospital
Aga Khan Hospital Mombasa	Kenya	Provincial hospital
Chris Hani Baragwanath Academic Hospital	South Africa	Central hospital
Mashonaland Central Provincial Hospital	Zimbabwe	Provincial hospital
Soweto Community Health Centre	South Africa	Health centre
Kenyatta National Hospital Nairobi	Kenya	Central hospital

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Technical stack

• Backend: Django 5.1 · Python 3.12 · SQLite (dev) · PostgreSQL (prod)
• Optimisation engine: appname/modeling.py — CarbomicaOptimizer class
• Frontend: Bootstrap 5 · Plotly.js (CDN, no server-side Dash)
• Deployment: Heroku (Procfile + whitenoise for static files)

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Local setup

git clone https://github.com/Logic06183/Carbomica_App_Django.git
cd Carbomica_App_Django
pip install -r requirements.txt
python manage.py migrate
python manage.py seed_demo_data          # loads representative LMIC demo data
python manage.py createsuperuser         # for /admin access
python manage.py runserver

Open http://127.0.0.1:8000

Environment variables (optional for local dev)

Variable	Default	Notes
DATABASE_URL	SQLite	Set for PostgreSQL in production
DJANGO_SECRET_KEY	insecure default	Override in production
DJANGO_DEBUG	True	Set False in production

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Key published deliverables

1. CARBOMICA tool report (D3.7) — Luchters S et al. (2024). DOI: 10.5281/zenodo.12730527

2. Carbon emission assessment (D2.11) — Sulaiman Z et al. (2024). DOI: 10.5281/zenodo.12703876

3. Evaluation protocol (D5.7) — Luchters S et al. (2024). DOI: 10.5281/zenodo.12819289

4. COP28 case study — ClimaHealth resource library

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Project website

https://www.high-horizons.eu/reducing-emissions/