An app to estimate intensive care unit greenhouse gas emissions and motivate change!
Estimate your ICU's baseline CO2 footprint and see how much you can decrease it with changes:
- The carbon footprint of intensive care units (ICUs) is massive.
- The US healthcare system produces 8-9% of all greenhouse gas (GHG) emissions in the US - more than the entire economy of Japan.
- ICUs are particularly carbon intensive; one day of ICU treatment for septic shock (~140-170 kg CO2 equivalent) is equivalent to driving an ICE vehicle >400 miles or using electricity for 2 months in a typical home.
- Through relatively small changes in practice and equipment, individual clinicians and hospitals can realize large reductions in the overall carbon footprint.
- This calculator provides a transparent, literature-based estimate of an ICUโs carbon footprint, localized for energy mix and adjustable for clinical practices.
- This tool is intended to help clinicians and hospitals identify and realize practice improvements to meaningfully reduce GHG emissions and make their ICU more sustainable.
Try the calculator out here
- Two-tab interface:
- Baseline โ Estimate current emissions by entering ICU size, occupancy, and location.
- Interventions โ Toggle or adjust sustainability practices and instantly see reductions.
- Dynamic COโ bar: Live updates for total, savings %, and โequivalentsโ (e.g., cars, homes, trees).
- Expandable details: Each intervention shows assumptions, formula, and references.
- Modular JSON architecture: Non-technical users can edit assumptions and interventions without touching code.
| id | group | title |
|---|---|---|
| switch_iv_to_oral | pharmacy | Switch eligible IV medications to oral |
| reduce_overuse_prophylaxis | pharmacy | Avoid routine prophylaxis (e.g., PPIs) for low-risk patients |
| avoid_aggressive_electrolyte_repletion | pharmacy | Avoid aggressive electrolyte replacement when not indicated |
| antibiotic_stewardship | pharmacy | Antibiotic stewardship and early de-escalation |
| eliminate_n2o | pharmacy | Eliminate NโO use |
| eliminate_desflurane | pharmacy | Eliminate desflurane |
| mdi_to_nebulizer | respiratory | Switch MDI to nebulizer whenever clinically appropriate |
| reusable_bronchoscopy | respiratory | Shift to reusable bronchoscopes |
| disposable_stethoscopes | respiratory | Eliminate disposable stethoscopes (clean reusable stethoscopes instead) |
| avoid_overoxygenation_fine | respiratory | Titrate oxygen to target range (avoid over-oxygenation) |
| abcde_bundle | low_value_care | Implement ABCDEF (ICU Liberation) bundle |
| reduce_unnecessary_admissions | low_value_care | Avoid unnecessary ICU admissions through accurate triage |
| goals_of_care_discussion | low_value_care | Discuss goals of care on all admissions |
| peripheral_vasopressors | low_value_care | Use peripheral vasopressors when safe instead of central lines |
| avoid_overdiagnosis | low_value_care | Avoid over-investigation and routine testing (e.g. daily CXR) |
| crrt_stewardship | low_value_care | CRRT stewardship (reduce unnecessary hours) |
| early_palliative_care | low_value_care | Early palliative care consults for high-risk ICU patients |
| telepresence_transport | low_value_care | Use telepresence for meetings and follow-up when possible |
| plant_based_foods | nutrition | Increase plant-based foods for patients and staff |
| seasonal_menu_planning | nutrition | Seasonal menu planning (local & in-season foods) |
| local_sustainable_food_sourcing | nutrition | Increase local/sustainable food sourcing |
| use_natural_daylight | infrastructure | Use natural daylight (e.g. shades up) during the day |
| lights_night_dimming | infrastructure | Dim ICU lighting at night |
| switch_to_led | infrastructure | Upgrade from incandescent/halogen to modern LED lighting |
| reduce_paper_printing | infrastructure | Reduce paper printouts and forms |
| staff_commute_low_carbon | infrastructure | Incentivize lowโcarbon staff commuting (carpool, bike, transit) |
| low_emission_deliveries | infrastructure | Low-emission deliveries (EV, bike, consolidated routes) |
| onsite_solar_offset | infrastructure | Offset electricity with onsite renewables (e.g., solar) |
| demand_control_ventilation | infrastructure | HVAC: Demand-controlled or variable-air-volume ventilation |
| moderate_temp_setpoint | infrastructure | HVAC: Relax temperature set-point by 1โ3ยฐC |
| high_efficiency_equipment | infrastructure | HVAC: High-efficiency plant equipment upgrades |
| heat_recovery_system | infrastructure | HVAC: Heat recovery for ventilation/chilled-water (ERV/HRCH) |
| improved_insulation | infrastructure | Improve hospital insulation |
| segregate_biohazard_waste | waste_removal | Use biohazard waste only for visibly blood-soiled items |
| plastics_recycling_program | waste_removal | Plastics recycling program (clinical & non-clinical) |
| stock_items_outside_room | waste_removal | Stock fewer single-use items inside patient rooms |
| reusable_gowns | laundry | Switch to reusable isolation gowns |
| reduce_linen_par_levels | laundry | Reduce default linen and towel par levels |
| extend_equipment_lifespan | laundry | Repair/maintain washers/dryers/blanket warmers |
The app uses kg COโe per ICU patient-day as a core metric and converts using:
Annual_tCO2e = Beds ร Occupancy ร 365 ร (Intensity_kgCO2e_per_patient_day / 1000)
| Parameter | Value | Source |
|---|---|---|
| Reference ICU intensity | 140 kg COโe / patient-day | McGain et al., 2018; range 88โ178 |
| Category shares | Energy 0.65 โข Procurement 0.18 โข Pharma 0.10 โข Gases 0.03 โข Waste 0.02 โข Water 0.02 | Literature mean |
Interventions fall into several categories:
percent_of_categorywhich refers tolighting,energy_hvac,procurement,waste,crrt,pharma,medical gasses,- direct_savings
- per_patient_day_delta
- intensity_per_hour
- kwh_reduction
| Metric | Conversion per t COโe |
|---|---|
| Cars removed (1 yr) | 0.217 |
| Homesโ electricity (1 yr) | 0.141 |
| Acres of forest preserved | 1.19 |
| Tree seedlings grown 10 yrs | 16.5 |
The app adjusts the baseline based on the ICU size/occupancy and location, to capture variations in local temperatures (HVAC costs) and the carbon footprint of local energy sources:
Energy_kgCO2e/pd = kWh_ref/pd ร (Grid_factor_local / Grid_factor_ref) ร Climate_multiplier
Reference grid factor (US mean): 827.520 lb/MWh = 0.3755 kg COโe/kWh ZIP-specific factors: from EPA eGRID (2022โ24) Climate multiplier: derived from HDD/CDD vs. reference site (Kansas City); capped ยฑ30 %.
Each intervention is also used as part of a baseline assessment (e.g. determining if anesthetic gasses like NโO and Desflurane are used) and as a potential opportunity for improvemnet (e.g. how much GHG would be mitigated by eliminating Desflurane)
Each intervention includes:
- Calculation formula
- Assumption references
- Markdown details and citations
Placeholder coefficient (from dialysis LCA): 2.0 kg COโe / hour of CRRT runtime. Users can adjust in assumptions.json when site-specific data are available.
| Gas | GWPโโโ | Notes |
|---|---|---|
| NโO | 273 | High-impact; easily eliminated outside ORs |
| Desflurane | 2540 | Avoid entirely if possible |
| Sevoflurane | 130 | Lower GWP; minimal ICU use |
| Isoflurane | 510 | Moderate GWP |
- All greenhouse gas (GHG) emissions in this calculator are expressed in metric tons of COโ equivalent (
t COโe) per year unless otherwise specified.- Metric ton = 1,000 kg (โ 2,204.6 lb).
- The โCOโ equivalentโ unit converts non-COโ gases (e.g., CHโ, NโO, anesthetic gases) into their equivalent impact based on their 100-year Global Warming Potential (GWPโโโ) as defined by the Intergovernmental Panel on Climate Change (IPCC AR6).
- Energy use is normalized to kilowatt-hours (kWh) and multiplied by a location-specific grid emission factor (kg COโe per kWh).
- Per-patient or per-bed values are scaled to annual totals using user-provided ICU size and occupancy assumptions.
- All calculations are approximate and intended for educational and quality-improvement purposes, not for regulatory carbon accounting.
- Users should adapt grid factors and GWP values to their own jurisdiction and reference year when possible.
/ (project root)
โโ index.html # Minimal HTML shell. Loads styles & JS modules in order.
โโ styles.css # Defines appearance of website
โโ /data
โ โโ assumptions.json
โ โโ interventions.json
โ โโ zip_CO2_annotated.csv
โ โโ subregion_emissions_annotated.csv
โโ /js
โ โโ config.js # App constants (paths, color tokens, category ordering)
โ โโ utils.js # Helpers (fmt, clamp, parseCSV, zfill, svgEl, tooltip)
โ โโ state.js # Central state container; default inputs; safe mutators
โ โโ data.js # Fetch & validate data files; JSON schema checks; fallbacks
โ โโ ui.js # Init controls, tabs, drawer, buttons; updateTopBar()
โ โโ baseline.js # Grid lookup + baseline math; recalcBaseline()
โ โโ interventions.js # Build baseline practices + interventions UI; applyInterventions()
โ โโ charts.js # drawStack() + drawCompare() with safe guards & tooltips
โ โโ exports.js # Export CSV/JSON
โ โโ router.js # URL encode/decode of state; updateURLState(), applyURLState()
โ โโ main.js # Boot sequence (load data โ init UI โ baseline โ render โ apply)
โโ /schemas
โโ interventions.schema.json # Lightweight runtime validator for interventions.json (optional)
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โ โ โ build BASELINE โ โ
โ โ โ tCO2e estimate โ โ display ฮtCO2
โ โ โโโโโโโโโโโโโโโโโโโโโโบ โcharts.jsโ opportunities
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subregion_emissions.csv โ
& zip_CO2.csv โ
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โ โ converter.py โ โ โ โ
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โโโโโโโโโโโ โโโโโโโโโโโ โ build list of โ โ
โ INTERVENTIONS โ โ
interventions.csv interventions.json โ โ โ calculate ฮtCO2
โโโโโโโโโโโโโโโโโบ โ โ with INTERVENTIONS
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groups.json
- state.js - state (object): { assumptions, interventions, zipTable, subregionTable, inputs, baselinePractices, derived }
- data.js - loadAllData() โ loads all four files; normalizes interventions (defaults OFF/0); validates shapes
- ui.js - initUI(), updateTopBar()
- baseline.js - lookupGridFactor(), recalcBaseline()
- interventions.js - renderBaselinePractices(), renderInterventions(), applyInterventions()
- charts.js - drawStack(containerId, categories, title), drawCompare()
- exports.js - exportCSV(), exportJSON(), renderAssumptionsHTML()
- router.js - updateURLState(), applyURLState()
- main.js - orchestrates boot order
Use the helper script converter.py
- Convert JSON -> CSV (for editing)
python3 converter.py json-to-csv --json interventions.json \
--groups-out groups.csv \
--interventions-out interventions.csv
- Edit groups.csv and interventions.csv in Excel/Google Sheets
- Convert CSVs -> JSON (to feed back into the app)
python3 converter.py csv-to-json \
--groups groups.csv \
--interventions interventions.csv \
--json-out interventions.json
- Identity & grouping: id, group, title, type, impact_category
- Slider range (if type=slider): range_min, range_max, range_step, range_unit
- Baseline control: baseline_label, baseline_type, baseline_default_enabled, baseline_default_value, baseline_min, baseline_max, baseline_step, baseline_unit
- Calculation: calc_method, calc_formula_note
- Params (fill only what you use):
- param_kwh_per_hour_per_bed, param_grid_factor_source, param_annual_usage_kg, param_gwp100, param_annual_agent_minutes, param_agent_consumption_ml_per_min, param_density_g_per_ml, param_percent_reduction, param_category, param_scale_with_value_pct, param_kg_per_hour, param_kg_co2e_per_puff
- UI: ui_icon, ui_summary, ui_details_markdown, ui_references (use Label|URL;Another Label|URL2)
- Current Version: 0.3.5
- Schema: x.y.z where
- x is release
- y is major code changes (e.g. adding new js files)
- z is minor code changes (e.g. updating the calculation or UX)
Uses the EPA eGRID dataset to estimate regional CO2 production.
ยฉ 2025 Nick Mark, MD Please credit ICU GHG Calculator and cite underlying research when reproducing or extending the tool.
This is provided "as is" without warranty of any kind with under an MIT License.
- McGain F et al. Life cycle assessment of intensive care units in Australia and the USA. Crit Care Med. 2018;46(10):e983โe990.
- Sherman JD et al. Carbon footprint of critical care: a systematic review. BMJ Open 2024.
- NHS England. Delivering a โNet Zeroโ National Health Service. 2020.
- EPA eGRID (2022โ24). Power Profiler ZIP-to-subregion database.
- IPCC AR6 WGIII. Global Warming Potentials (100-year).
- Weppner WG et al, A Longitudinal Assessment of Greenhouse Gas Emissions From Inhaler Devices in a National Health System. JAMA. 2025. doi:10.1001/jama.2025.15638
- Rabin, AS et al, Reducing the Climate Impact of Critical Care, CHEST Critical Care
- McGain F et al, The carbon footprint of treating patients with septic shock in the intensive care unit. Crit Care Resusc. 2018
- Feldman WB et al, Inhaler-Related Greenhouse Gas Emissions in the US: A Serial Cross-Sectional Analysis. JAMA. 2025