> ## Documentation Index
> Fetch the complete documentation index at: https://code.dcycle.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Category 3: Transportation Emissions
> Quantify indirect GHG emissions from transportation of materials, products, waste, and people
## Understanding Transportation Emissions
**Category 3** under ISO 14064-1 covers indirect GHG emissions from transportation not covered in Categories 1 or 2. This includes transportation of materials, products, waste, employees, and business travelers using vehicles NOT owned or controlled by your organization.
```
┌─────────────────────────────────────────────────────────────────────────────────┐
│ CATEGORY 3: INDIRECT GHG EMISSIONS FROM TRANSPORTATION │
├─────────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────────────┐ │
│ │ BUSINESS TRAVEL │ │ EMPLOYEE │ │ FREIGHT │ │
│ │ │ │ COMMUTING │ │ TRANSPORTATION │ │
│ ├─────────────────────┤ ├─────────────────────┤ ├─────────────────────────┤ │
│ │ • Flights │ │ • Car commutes │ │ • Upstream (inbound) │ │
│ │ • Rail travel │ │ • Public transit │ │ • Downstream (outbound) │ │
│ │ • Car rentals │ │ • Cycling/walking │ │ • Third-party logistics │ │
│ │ • Taxi/rideshare │ │ • Remote work │ │ • Waste transport │ │
│ │ • Hotel stays │ │ │ │ │ │
│ └─────────────────────┘ └─────────────────────┘ └─────────────────────────┘ │
│ │
│ Transportation NOT owned/controlled by your organization │
│ │
└─────────────────────────────────────────────────────────────────────────────────┘
```
**Transportation Emission Formula**
**Transport Emissions = Distance × Emission Factor**
Or with weight:
**Freight Emissions = Distance × Weight × Emission Factor (per tonne-km)**
Where emission factors vary by transport mode, vehicle type, and load factor.
## Prerequisites
Before starting, ensure you have:
* Dcycle API credentials ([get them here](/docs/quickstart#step-1-get-your-api-key))
* Travel records (bookings, expense reports, travel agency data)
* Employee commuting survey data or estimates
* Freight shipment records (origin, destination, weight)
**Using the Dcycle App?**
Track transportation emissions through our web interface:
* [Business Travels](https://app.dcycle.io/business-travels) - Log business trips
* [Employees](https://app.dcycle.io/employees) - Track commuting patterns
## Data Map: Category 3 Requirements
```
┌─────────────────────────────────────────────────────────────────────────────────────────┐
│ CATEGORY 3 DATA REQUIREMENTS │
├─────────────────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────────────────────┐ │
│ │ BUSINESS TRAVEL │ │
│ ├─────────────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ Flight Data Ground Transport Accommodation │ │
│ │ ─────────── ──────────────── ───────────── │ │
│ │ • Origin airport • Mode (rail/car) • Hotel nights │ │
│ │ • Destination airport • Distance • Location/country │ │
│ │ • Travel class • Vehicle type • Hotel type │ │
│ │ • Round trip? │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────────────────┐ │
│ │ EMPLOYEE COMMUTING │ │
│ ├─────────────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ Employee Info Commute Details Work Pattern │ │
│ │ ───────────── ────────────── ──────────── │ │
│ │ • Employee ID • Transport mode • Days per week in office │ │
│ │ • Work location • Distance (one way) • Remote work days │ │
│ │ • Home location • Vehicle type • Period (start/end) │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────────────────┐ │
│ │ FREIGHT TRANSPORTATION │ │
│ ├─────────────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ Shipment Details Transport Mode Load Information │ │
│ │ ──────────────── ────────────── ──────────────── │ │
│ │ • Origin location • Road/Rail/Sea/Air • Weight (tonnes) │ │
│ │ • Destination • Vehicle type • Volume (m³) │ │
│ │ • Distance • Carrier details • Product category │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────────────────┘
```
## Business Travel
Track emissions from employee business trips including flights, ground transportation, and hotel stays.
### Record Flight Travel
| Field | Type | Required | Description | Example |
| ------------------ | ------ | -------- | ------------------------------------------------------------ | -------------------------------- |
| `transport_type` | string | ✅ | Type of transport | `"aircraft"` |
| `origin` | string | ✅\* | Origin airport code (IATA) | `"MAD"` |
| `destination` | string | ✅\* | Destination airport code (IATA) | `"LHR"` |
| `distance_km` | number | ✅\* | Distance in km (\*either origin+destination OR distance\_km) | `1264` |
| `start_date` | date | ✅ | Travel start date | `"2024-03-15"` |
| `end_date` | date | ✅ | Travel end date | `"2024-03-15"` |
| `travel_type` | string | ❌ | One-way or round trip | `"one_way"`, `"round"` |
| `travel_number` | int | ❌ | Number of trips (defaults to 1) | `1` |
| `renewable_energy` | string | ❌ | Uses renewable energy? | `"yes"`, `"no"`, `"do_not_know"` |
| `name` | string | ❌ | Employee name | `"John Smith"` |
| `email` | string | ❌ | Employee email | `"john@company.com"` |
**Where to get this data:**
* **Travel bookings**: Corporate travel systems, travel agencies
* **Expense reports**: Employee expense claims
* **Airport codes**: IATA 3-letter codes (e.g., MAD, LHR, JFK)
**Distance or Locations Required**
You must provide either `distance_km` OR both `origin` and `destination`. If you provide airport codes, Dcycle automatically calculates the distance.
```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}}
import requests
import os
headers = {
"Authorization": f"Bearer {os.getenv('DCYCLE_API_KEY')}",
"Content-Type": "application/json",
"x-organization-id": os.getenv("DCYCLE_ORG_ID"),
"x-user-id": os.getenv("DCYCLE_USER_ID"),
}
# Record a business flight
flight_data = {
"transport_type": "aircraft",
"origin": "MAD", # Madrid (IATA code)
"destination": "LHR", # London Heathrow (IATA code)
"travel_type": "round", # round or one_way
"start_date": "2024-03-15",
"end_date": "2024-03-15",
}
response = requests.post(
"https://api.dcycle.io/v1/business-travels",
headers=headers,
json=flight_data,
)
travel = response.json()
print(f"✅ Business flight recorded: {travel['id']}")
print(f" Route: {flight_data['origin']} → {flight_data['destination']}")
print(f" Distance: {travel['distance_km']} km")
print(f" CO₂e: {travel['co2e']} kg")
print(f" ISO 14064-1 Category: 3 (Transportation)")
```
```javascript JavaScript theme={"theme":{"light":"github-light","dark":"github-dark"}}
const axios = require('axios');
const headers = {
Authorization: `Bearer ${process.env.DCYCLE_API_KEY}`,
'Content-Type': 'application/json',
'x-organization-id': process.env.DCYCLE_ORG_ID,
'x-user-id': process.env.DCYCLE_USER_ID,
};
// Record a business flight
const flightData = {
transport_type: 'aircraft',
origin: 'MAD', // Madrid (IATA code)
destination: 'LHR', // London Heathrow (IATA code)
travel_type: 'round', // round or one_way
start_date: '2024-03-15',
end_date: '2024-03-15',
};
const response = await axios.post(
'https://api.dcycle.io/v1/business-travels',
flightData,
{ headers }
);
const travel = response.data;
console.log(`✅ Business flight recorded: ${travel.id}`);
console.log(` Route: ${flightData.origin} → ${flightData.destination}`);
console.log(` Distance: ${travel.distance_km} km`);
console.log(` CO₂e: ${travel.co2e} kg`);
console.log(` ISO 14064-1 Category: 3 (Transportation)`);
```
**Automatic Distance Calculation**
When you provide information for origin and destination, Dcycle automatically:
* Calculates the flight distance
* Determines the aircraft size category (very short, short, medium, long haul) based on Ecoinvent classification
* Applies the appropriate emission factor from Ecoinvent
### Record Rail Travel
| Field | Type | Required | Description | Example |
| ------------------ | ------ | -------- | ------------------------------------------------------------ | -------------------------------- |
| `transport_type` | string | ✅ | Type of transport | `"train"` |
| `origin` | string | ✅\* | Origin city/station | `"Madrid"` |
| `destination` | string | ✅\* | Destination city/station | `"Barcelona"` |
| `distance_km` | number | ✅\* | Distance in km (\*either origin+destination OR distance\_km) | `620` |
| `start_date` | date | ✅ | Travel start date | `"2024-04-10"` |
| `end_date` | date | ✅ | Travel end date | `"2024-04-10"` |
| `travel_type` | string | ❌ | One-way or round trip | `"one_way"`, `"round"` |
| `travel_number` | int | ❌ | Number of trips | `1` |
| `renewable_energy` | string | ❌ | Train uses renewable energy? | `"yes"`, `"no"`, `"do_not_know"` |
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Record rail travel
rail_data = {
"transport_type": "train",
"origin": "Madrid",
"destination": "Barcelona",
"travel_type": "round",
"start_date": "2024-04-10",
"end_date": "2024-04-10",
"renewable_energy": "do_not_know",
}
response = requests.post(
"https://api.dcycle.io/v1/business-travels",
headers=headers,
json=rail_data,
)
travel = response.json()
print(f"✅ Rail travel recorded: {travel['id']}")
print(f" CO₂e: {travel['co2e']} kg")
print(f" (Rail typically 80-90% lower emissions than flying)")
```
### Record Car Rental / Ground Transport
| Field | Type | Required | Description | Example |
| ---------------- | ------ | -------- | ------------------------------------------------------------ | --------------------------------------------------------- |
| `transport_type` | string | ✅ | Type of transport | `"car"` |
| `origin` | string | ✅\* | Origin location | `"Madrid"` |
| `destination` | string | ✅\* | Destination location | `"Toledo"` |
| `distance_km` | number | ✅\* | Distance in km (\*either origin+destination OR distance\_km) | `350` |
| `vehicle_size` | string | ✅ | Vehicle size (required for car) | `"small"`, `"medium"`, `"large"` |
| `fuel_type` | string | ✅ | Fuel type (required for car) | `"diesel"`, `"petrol"`, `"electric"`, `"hybrid"`, `"lpg"` |
| `start_date` | date | ✅ | Travel start date | `"2024-05-20"` |
| `end_date` | date | ✅ | Travel end date | `"2024-05-20"` |
| `travel_type` | string | ❌ | One-way or round trip | `"one_way"`, `"round"` |
| `travel_number` | int | ❌ | Number of trips | `1` |
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Record car rental
car_rental_data = {
"transport_type": "car",
"vehicle_size": "medium",
"fuel_type": "diesel",
"distance_km": 350,
"start_date": "2024-05-20",
"end_date": "2024-05-20",
}
response = requests.post(
"https://api.dcycle.io/v1/business-travels",
headers=headers,
json=car_rental_data,
)
travel = response.json()
print(f"✅ Car travel recorded: {travel['id']}")
print(f" Distance: {travel['distance_km']} km")
print(f" CO₂e: {travel['co2e']} kg")
```
## Employee Commuting
**Employee commuting** covers emissions from the transportation of employees between their homes and worksites in vehicles not owned or operated by your organization. This includes:
* **Daily commuting**: Regular home-to-work travel
* **All transport modes**: Car, public transit, cycling, walking
* **Remote work**: Zero emissions for work-from-home days
* **Carpooling**: Shared vehicle emissions (divided among passengers)
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ ISO 14064-1 CATEGORY 3: Employee Commuting │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ EMPLOYEE HOMES WORKPLACE │
│ ────────────────── ────────── │
│ │
│ ┌──────────────┐ ┌──────────────┐ │
│ │ Home │◄─── Car ──────────────► │ Office │ │
│ └──────────────┘ │ │ │
│ │ │ │
│ ┌──────────────┐ │ │ │
│ │ Home │◄─── Train ────────────► │ │ │
│ └──────────────┘ │ │ │
│ │ │ │
│ ┌──────────────┐ │ │ │
│ │ Home │◄─── Bus ──────────────► │ │ │
│ └──────────────┘ │ │ │
│ │ │ │
│ ┌──────────────┐ │ │ │
│ │ Home │◄─── Bike ─────────────► │ │ │
│ └──────────────┘ │ │ │
│ │ │ │
│ ┌──────────────┐ │ │ │
│ │ Home │──── Remote ─────────── │ (0 km) │ │
│ └──────────────┘ └──────────────┘ │
│ │
│ DAILY ROUND TRIP: │
│ • Distance (km) × 2 (round trip) │
│ • × Working days per week │
│ • × Emission factor (by transport mode) │
│ │
│ INCLUDED: NOT INCLUDED: │
│ • Daily commute • Business travel (separate) │
│ • All transport modes • Company vehicles (Category 1) │
│ • Remote work tracking • Customer/visitor travel │
│ • Carpooling emissions │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
```
**Employee Commuting vs Business Travel**
* **Employee Commuting**: Daily travel between home and work
* **Business Travel**: Trips for business purposes (meetings, conferences, site visits)
**Using the Dcycle App?**
You can track employee commuting through our web interface:
* [Send employee surveys](https://scribehow.com/shared/How_to_send_a_commuting_survey__fZX-d-N7QKO34L_6QR1RIg) ([ES](https://scribehow.com/shared/Como_enviar_una_encuesta_de_desplazamientos__V2_xj17hRVWqCfU_BKMHIQ)) - Collect data via email
* Manual entry for individual employees
* CSV bulk upload for HR data
### Data Map: Employee Commuting Overview
```
┌─────────────────────────────────────────────────────────────────────────────────────────┐
│ EMPLOYEE COMMUTING DATA REQUIREMENTS OVERVIEW │
├─────────────────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────────────────────┐ │
│ │ EMPLOYEE RECORD │ │
│ ├─────────────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ Required Fields Optional Fields │ │
│ │ ────────────────── ────────────────── │ │
│ │ • origin OR total_km • email │ │
│ │ • destination OR total_km • name │ │
│ │ • transport_type • vehicle_size │ │
│ │ • weekly_travels • fuel_type │ │
│ │ • renewable_energy │ │
│ │ • carpool (true/false) │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────────────────┐ │
│ │ COMMUTING PERIOD (Employee Historic) │ │
│ ├─────────────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ Required Fields Optional Fields │ │
│ │ ────────────────── ────────────────── │ │
│ │ • commuting_type • situation │ │
│ │ ("in_itinere") │ │
│ │ • start_date │ │
│ │ • end_date │ │
│ │ • daily_trips (default: 1) │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────────────────┐ │
│ │ CALCULATION FLOW │ │
│ ├─────────────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ Origin + Destination ──► Distance (km) [one-way] │ │
│ │ │ │ │
│ │ Weekly Travels ──────────────┼──► Working days in period │ │
│ │ │ │ │
│ │ Transport Type ──────────────┼──► Emission Factor (kg CO₂e/km) │ │
│ │ │ │ │
│ │ CO₂e = Distance × Days × Daily_Trips × EF × 2 (round trip) │ │
│ │ │ │
│ │ If carpool: CO₂e ÷ 3 (carpool factor) │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────────────────┘
```
### Weekly Travels (Working Days)
The `weekly_travels` field defines which days of the week the employee commutes:
| Day | Value | Description |
| --------- | ----- | ---------------------------- |
| Monday | `0` | Included if present in array |
| Tuesday | `1` | Included if present in array |
| Wednesday | `2` | Included if present in array |
| Thursday | `3` | Included if present in array |
| Friday | `4` | Included if present in array |
| Saturday | `5` | Included if present in array |
| Sunday | `6` | Included if present in array |
**Examples:**
| Pattern | `weekly_travels` | Description |
| ------------------- | ----------------- | ---------------------- |
| Full week (Mon-Fri) | `[0, 1, 2, 3, 4]` | Traditional 5-day week |
| 3 days/week | `[0, 2, 4]` | Mon, Wed, Fri only |
| Hybrid (2 days) | `[1, 3]` | Tue, Thu in office |
| Full remote | `[]` | Empty = no commuting |
**Remote Work / Telework**
Set `weekly_travels: []` (empty array) for fully remote employees. Dcycle will calculate zero commuting emissions for these employees.
### Transport Types
| Transport Type | Description | Typical EF Range |
| -------------- | ---------------- | -------------------- |
| `car` | Personal vehicle | 0.1-0.2 kg CO₂e/km |
| `bus` | Public bus | 0.05-0.1 kg CO₂e/km |
| `train` | Commuter rail | 0.03-0.05 kg CO₂e/km |
| `metro` | Urban subway | 0.02-0.04 kg CO₂e/km |
| `trolleybus` | Electric trolley | 0.02-0.04 kg CO₂e/km |
| `motorbike` | Motorcycle | 0.08-0.12 kg CO₂e/km |
| `bicycle` | Cycling | 0 kg CO₂e/km |
| `walk` | Walking | 0 kg CO₂e/km |
**Vehicle options for cars:**
| Vehicle Size | Fuel Type | Description |
| ------------ | -------------------------------------------------------------- | ------------ |
| `small` | `petrol`, `diesel`, `electric`, `hybrid`, `lpg`, `natural_gas` | Compact cars |
| `medium` | `petrol`, `diesel`, `electric`, `hybrid`, `lpg`, `natural_gas` | Sedans |
| `large` | `petrol`, `diesel`, `electric`, `hybrid`, `lpg`, `natural_gas` | SUVs |
**Carpooling**
When `carpool: true`, emissions are divided by 3 (average carpool occupancy). This encourages shared transportation and accurately reflects the lower per-person emissions.
### Step 1: Create Employee Records
| Field | Type | Required | Description | Example |
| ---------------- | ------- | -------- | --------------------- | ---------------------- |
| `origin` | string | ⚠️ | Home address/city | `"Madrid, Spain"` |
| `destination` | string | ⚠️ | Office address | `"Company HQ, Madrid"` |
| `total_km` | number | ⚠️ | One-way distance | `15` |
| `transport_type` | string | ✅ | Commute mode | `"car"` |
| `weekly_travels` | array | ✅ | Days in office \[0-6] | `[0, 1, 2, 3, 4]` |
| `email` | string | ❌ | Employee email | `"john@company.com"` |
| `name` | string | ❌ | Employee name | `"John Smith"` |
| `vehicle_size` | string | ❌ | For cars | `"medium"` |
| `fuel_type` | string | ❌ | For cars | `"petrol"` |
| `carpool` | boolean | ❌ | Shared vehicle | `false` |
⚠️ **Conditional requirements:**
* Either `origin` + `destination` OR `total_km` must be provided
**Where to get this data:**
* **Home location**: HR records, employee surveys
* **Transport mode**: Employee surveys
* **Working days**: HR/scheduling systems
```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}}
import requests
import os
headers = {
"Authorization": f"Bearer {os.getenv('DCYCLE_API_KEY')}",
"Content-Type": "application/json",
"x-organization-id": os.getenv("DCYCLE_ORG_ID"),
"x-user-id": os.getenv("DCYCLE_USER_ID"),
}
# Example: Employee commuting by car (5 days/week)
employee = {
"email": "john.smith@company.com",
"name": "John Smith",
"origin": "Residential Area, Madrid",
"destination": "Company HQ, Madrid Business District",
"transport_type": "car",
"vehicle_size": "medium",
"fuel_type": "petrol",
"weekly_travels": [0, 1, 2, 3, 4], # Mon-Fri
"carpool": False,
}
response = requests.post(
"https://api.dcycle.io/v1/employees",
headers=headers,
json=employee
).json()
print(f"✅ Employee created")
print(f" ID: {response['id']}")
print(f" Email: {employee['email']}")
print(f" Commute: {employee['origin']} → {employee['destination']}")
print(f" Transport: {employee['transport_type']}")
print(f" Days/week: {len(employee['weekly_travels'])}")
# Create commuting period
employee_id = response['id']
commuting_period = {
"employee_id": employee_id,
"commuting_type": "in_itinere", # Home-work commute
"start_date": "2024-01-01",
"end_date": "2024-12-31",
"daily_trips": 1, # 1 round trip per day
"origin": employee['origin'],
"destination": employee['destination'],
"total_km": 15, # One-way distance
"transport_type": employee['transport_type'],
"vehicle_size": employee.get('vehicle_size'),
"fuel_type": employee.get('fuel_type'),
"weekly_travels": employee['weekly_travels'],
"carpool": employee.get('carpool', False),
}
period_response = requests.post(
"https://api.dcycle.io/v1/employees_historic",
headers=headers,
json=commuting_period
).json()
print(f" Period: {commuting_period['start_date']} to {commuting_period['end_date']}")
print(f" Distance: {commuting_period['total_km']} km (one-way)")
print(f" CO₂e: {period_response.get('co2e', 'Calculating...')} kg")
print(f" ISO 14064-1 Category: 3 (Transportation)")
```
```javascript JavaScript theme={"theme":{"light":"github-light","dark":"github-dark"}}
const axios = require('axios');
const headers = {
'Authorization': `Bearer ${process.env.DCYCLE_API_KEY}`,
'Content-Type': 'application/json',
'x-organization-id': process.env.DCYCLE_ORG_ID,
'x-user-id': process.env.DCYCLE_USER_ID
};
// Example: Employee commuting by car (5 days/week)
const employee = {
email: 'john.smith@company.com',
name: 'John Smith',
origin: 'Residential Area, Madrid',
destination: 'Company HQ, Madrid Business District',
transport_type: 'car',
vehicle_size: 'medium',
fuel_type: 'petrol',
weekly_travels: [0, 1, 2, 3, 4],
carpool: false
};
const response = await axios.post(
'https://api.dcycle.io/v1/employees',
employee,
{ headers }
).then(res => res.data);
console.log('✅ Employee created');
console.log(` ID: ${response.id}`);
console.log(` Email: ${employee.email}`);
console.log(` Transport: ${employee.transport_type}`);
console.log(` Days/week: ${employee.weekly_travels.length}`);
console.log(` ISO 14064-1 Category: 3 (Transportation)`);
```
### Common Commuting Scenarios
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Example employees with different commuting patterns
employees = [
# Full-time office worker (car)
{
"email": "alice@company.com",
"name": "Alice Johnson",
"total_km": 20,
"transport_type": "car",
"vehicle_size": "medium",
"fuel_type": "diesel",
"weekly_travels": [0, 1, 2, 3, 4],
"carpool": False,
},
# Hybrid worker (public transit, 3 days)
{
"email": "bob@company.com",
"name": "Bob Williams",
"total_km": 12,
"transport_type": "train",
"weekly_travels": [1, 2, 3], # Tue, Wed, Thu
"carpool": False,
},
# Eco-commuter (bike)
{
"email": "carol@company.com",
"name": "Carol Davis",
"total_km": 5,
"transport_type": "bicycle",
"weekly_travels": [0, 1, 2, 3, 4],
"carpool": False,
},
# Remote worker
{
"email": "david@company.com",
"name": "David Brown",
"total_km": 0,
"transport_type": "walk", # Placeholder
"weekly_travels": [], # Fully remote
"carpool": False,
},
# Carpooler
{
"email": "emma@company.com",
"name": "Emma Wilson",
"total_km": 25,
"transport_type": "car",
"vehicle_size": "large",
"fuel_type": "petrol",
"weekly_travels": [0, 1, 2, 3, 4],
"carpool": True, # Shares ride with colleagues
},
# Electric car commuter
{
"email": "frank@company.com",
"name": "Frank Miller",
"total_km": 30,
"transport_type": "car",
"vehicle_size": "medium",
"fuel_type": "electric",
"weekly_travels": [0, 1, 2, 3, 4],
"carpool": False,
},
]
# Create all employees
for emp in employees:
response = requests.post(
"https://api.dcycle.io/v1/employees",
headers=headers,
json=emp
).json()
days = len(emp['weekly_travels'])
remote = " (Remote)" if days == 0 else ""
carpool = " [Carpool]" if emp.get('carpool') else ""
print(f" {emp['name']}: {emp['transport_type']} | {days} days/week{remote}{carpool}")
print(f" Distance: {emp['total_km']} km | CO₂e: {response.get('co2e', 'TBD')} kg/year")
print(f"\n✅ Created {len(employees)} employee records")
```
### Step 2: Send Employee Surveys
Collect commuting data directly from employees via survey:
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
import requests
import os
headers = {
"Authorization": f"Bearer {os.getenv('DCYCLE_API_KEY')}",
"Content-Type": "application/json",
"x-organization-id": os.getenv("DCYCLE_ORG_ID"),
"x-user-id": os.getenv("DCYCLE_USER_ID"),
}
# Send survey to employees
survey_request = {
"emails": [
"alice@company.com",
"bob@company.com",
"carol@company.com",
],
"survey_type": "commuting",
"message": "Please complete this short survey about your daily commute.",
}
response = requests.post(
"https://api.dcycle.io/v1/employees/survey",
headers=headers,
json=survey_request
)
if response.status_code == 200:
print(f"✅ Survey sent to {len(survey_request['emails'])} employees")
else:
print(f"❌ Failed: {response.text}")
```
**Survey Questions**
Dcycle's commuting survey asks employees:
* Home location (address or postal code)
* Primary transport mode
* Vehicle details (if car)
* Days worked in office per week
* Carpooling (yes/no)
### Step 3: Bulk Upload Employee Data
For organizations with many employees, use CSV upload:
#### CSV Format
```csv theme={"theme":{"light":"github-light","dark":"github-dark"}}
email,name,origin,destination,total_km,transport_type,vehicle_size,fuel_type,weekly_travels,carpool
alice@company.com,"Alice Johnson",,,20,car,medium,diesel,"[0,1,2,3,4]",false
bob@company.com,"Bob Williams",,,12,train,,,"[1,2,3]",false
carol@company.com,"Carol Davis",,,5,bicycle,,,"[0,1,2,3,4]",false
david@company.com,"David Brown",,,0,walk,,,"[]",false
emma@company.com,"Emma Wilson",,,25,car,large,petrol,"[0,1,2,3,4]",true
frank@company.com,"Frank Miller",,,30,car,medium,electric,"[0,1,2,3,4]",false
```
**CSV Notes:**
* `total_km` is one-way distance (home to office)
* `weekly_travels` use format `"[0,1,2,3,4]"` (JSON array as string)
* Empty `"[]"` for remote workers
* `carpool`: `true` or `false`
#### Upload CSV
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
import requests
import os
headers = {
"Authorization": f"Bearer {os.getenv('DCYCLE_API_KEY')}",
"x-organization-id": os.getenv("DCYCLE_ORG_ID"),
"x-user-id": os.getenv("DCYCLE_USER_ID"),
}
# Upload CSV file
with open("employee_commuting.csv", "rb") as f:
files = {"file": ("employee_commuting.csv", f, "text/csv")}
response = requests.post(
"https://api.dcycle.io/v1/employees/bulk/csv",
headers=headers,
files=files
)
if response.status_code == 200:
result = response.json()
print(f"✅ Uploaded {result.get('records_processed', 0)} employee records")
else:
print(f"❌ Upload failed: {response.text}")
```
### Commuting Reduction Strategies
**Reduction Strategies for Employee Commuting**
1. **Remote work policy**: Allow 2+ days WFH per week
2. **Public transit subsidies**: Incentivize train/bus use
3. **Cycle-to-work schemes**: Provide bike facilities and subsidies
4. **Carpooling programs**: Connect employees on similar routes
5. **Electric vehicle charging**: Install workplace chargers
6. **Shuttle services**: Provide company buses for major routes
7. **Flexible hours**: Avoid peak traffic (lower congestion emissions)
## Upstream Transportation
Track emissions from inbound freight - materials and products shipped TO your organization.
| Field | Type | Required | Description | Example |
| ---------------- | ------ | -------- | --------------------------- | ------------------------------------ |
| `direction` | string | ✅ | Upstream or downstream | `"upstream"` |
| `origin` | string | ✅ | Origin location | `"Shanghai, China"` |
| `destination` | string | ✅ | Destination (your facility) | `"Madrid, Spain"` |
| `transport_mode` | string | ✅ | Mode of transport | `"sea"`, `"road"`, `"rail"`, `"air"` |
| `weight_tonnes` | number | ✅ | Shipment weight | `25` |
| `date` | date | ✅ | Shipment date | `"2024-02-15"` |
**Where to get this data:**
* **Shipment details**: Supplier invoices, shipping documents
* **Weight**: Bill of lading, packing lists
* **Origin**: Supplier locations
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Record upstream freight shipment
upstream_freight = {
"direction": "upstream",
"origin": "Shanghai, China",
"destination": "Madrid, Spain",
"transport_mode": "sea",
"weight_tonnes": 25,
"date": "2024-02-15",
}
response = requests.post(
"https://api.dcycle.io/v1/transport",
headers=headers,
json=upstream_freight,
)
shipment = response.json()
print(f"✅ Upstream freight recorded: {shipment['id']}")
print(f" Route: {upstream_freight['origin']} → {upstream_freight['destination']}")
print(f" Mode: {upstream_freight['transport_mode']}")
print(f" Weight: {upstream_freight['weight_tonnes']} tonnes")
print(f" CO₂e: {shipment['co2e']} kg")
print(f" ISO 14064-1 Category: 3 (Transportation)")
```
## Downstream Transportation
Track emissions from outbound freight - products shipped FROM your organization to customers.
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Record downstream freight shipment
downstream_freight = {
"direction": "downstream",
"origin": "Madrid, Spain",
"destination": "Paris, France",
"transport_mode": "road",
"vehicle_type": "truck_40t",
"weight_tonnes": 15,
"date": "2024-03-20",
}
response = requests.post(
"https://api.dcycle.io/v1/transport",
headers=headers,
json=downstream_freight,
)
shipment = response.json()
print(f"✅ Downstream freight recorded: {shipment['id']}")
print(f" Route: {downstream_freight['origin']} → {downstream_freight['destination']}")
print(f" CO₂e: {shipment['co2e']} kg")
print(f" ISO 14064-1 Category: 3 (Transportation)")
```
**Upstream vs Downstream Classification**
* **Upstream**: Inbound goods, raw materials from suppliers, waste sent for treatment
* **Downstream**: Outbound products to customers, deliveries to distribution centers
Both are Category 3 under ISO 14064-1, but tracking separately helps identify reduction opportunities.
## Query Category 3 Emissions
Retrieve all your transportation emissions for reporting:
```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Get Category 3 emissions summary
response = requests.get(
f"https://api.dcycle.io/v1/organizations/{os.getenv('DCYCLE_ORG_ID')}/emissions",
headers=headers,
params={
"year": 2024,
"category": "transportation", # ISO 14064-1 Category 3
},
).json()
print(f"📊 Category 3: Indirect GHG Emissions from Transportation (2024)")
print(f"")
print(f" Business Travel:")
print(f" - Flights: {response['flights']:,.0f} kg CO₂e")
print(f" - Rail: {response['rail']:,.0f} kg CO₂e")
print(f" - Car/Ground: {response['ground']:,.0f} kg CO₂e")
print(f" - Hotels: {response['hotels']:,.0f} kg CO₂e")
print(f"")
print(f" Employee Commuting: {response['commuting']:,.0f} kg CO₂e")
print(f"")
print(f" Freight:")
print(f" - Upstream: {response['upstream_freight']:,.0f} kg CO₂e")
print(f" - Downstream: {response['downstream_freight']:,.0f} kg CO₂e")
print(f"")
print(f" ─────────────────────────")
print(f" TOTAL CATEGORY 3: {response['total']:,.0f} kg CO₂e")
```
## Emission Factors
Dcycle uses emission factors from **Ecoinvent 3.8 cutoff by classification** for all Category 3 transportation calculations. Factors are automatically selected based on transport type, distance, vehicle characteristics, and regional variations.
### Business Travel (Flights)
For aircraft travel, emission factors are selected based on:
* **Aircraft size category** (very short, short, medium, long haul - determined by distance following Ecoinvent classification)
* **Origin location** (regional adjustments)
* **Transport type** (aircraft)
* **Renewable energy** (if applicable)
Dcycle automatically determines the aircraft size based on flight distance:
| Distance (km) | Aircraft Size | Description |
| ------------- | ------------- | ---------------------------------- |
| 0 - 800 | `very_short` | Regional/domestic flights |
| 800 - 1,500 | `short` | Short-haul flights |
| 1,500 - 4,000 | `medium` | Medium-haul flights |
| 4,000+ | `long` | Long-haul intercontinental flights |
These distance thresholds are defined by Ecoinvent documentation for passenger air transport.
**Note:** Cabin class (economy, business, first) is NOT used in calculations. Dcycle calculates emissions based on average passenger emissions per km for each aircraft size category from Ecoinvent.
Business travel flight emissions are calculated as:
**CO₂e = Distance (km) × Emission Factor (kg CO₂e/passenger-km) × Trip Multiplier**
Where:
* **Distance**: Calculated from IATA codes or provided directly
* **Emission Factor**: Based on aircraft size category (from Ecoinvent)
* **Trip Multiplier**: 2x for round trips, 1x for one-way
**Example (Madrid to London round trip):**
```
Distance: 1,264 km (calculated from MAD → LHR)
Aircraft Size: short (800-1,500 km range per Ecoinvent classification)
EF: 0.255 kg CO₂e/passenger-km (Ecoinvent 3.8)
Trip: round (2x)
CO₂e = 1,264 × 0.255 × 2 = 645 kg CO₂e
```
### Ground Transportation (Car & Rail)
For car travel (business travel and commuting), emission factors depend on:
* **Vehicle size**: small, medium, large
* **Fuel type**: diesel, petrol, electric, hybrid, LPG, natural gas
**Calculation:**
**CO₂e = Distance (km) × Emission Factor (kg CO₂e/km)**
Where emission factors are specific to the vehicle size and fuel type combination from Ecoinvent.
For rail travel, emission factors depend on:
* **Origin location** (regional grid factors for electric trains)
* **Renewable energy** (yes, no, don't know)
Rail typically produces 80-90% lower emissions than flying for the same distance.
### Employee Commuting
**Ecoinvent 3.8+ Cut-off**
* Lifecycle emission factors by transport mode
* Regional variations where available
* Covers cars, public transit, and active transport
* Well-to-Wheel (WTW) factors including fuel production
When origin/destination are provided, distance is calculated using routing services. If geocoding fails or locations are unavailable, use `total_km` directly.
Employee commuting emissions are calculated as:
**CO₂e = Distance (km) × Days × Daily\_Trips × Emission Factor × 2 (round trip)**
Where:
* **Distance**: One-way distance from home to office
* **Days**: Number of working days in the period (based on `weekly_travels`)
* **Daily\_Trips**: Number of trips per day (default: 1)
* **Emission Factor**: Based on transport type from Ecoinvent
If `carpool: true`, the result is divided by 3 (average carpool occupancy).
**Example (Car commute, 5 days/week):**
```
Distance: 15 km (one-way)
Transport: car (medium, petrol)
Days: 250 working days/year
EF: 0.17 kg CO₂e/km
CO₂e = 15 × 250 × 1 × 0.17 × 2 = 1,275 kg CO₂e/year
```
### Freight Transportation
For freight transportation, emission factors depend on:
* **Transport mode**: road, rail, sea, air
* **Vehicle type**: truck size, ship type, aircraft type
* **Load factor**: weight transported in tonnes
**Calculation:**
**CO₂e = Distance (km) × Weight (tonnes) × Emission Factor (kg CO₂e/tonne-km)**
Emission factors from Ecoinvent account for:
* Fuel consumption per tonne-km
* Vehicle efficiency
* Empty return trips (where applicable)
Typical emission factors by transport mode (kg CO₂e per tonne-km):
| Mode | EF Range | Notes |
| ---- | ----------- | -------------------------- |
| Air | 0.5 - 1.0 | Highest emissions, fastest |
| Road | 0.05 - 0.15 | Varies by truck size |
| Rail | 0.02 - 0.05 | Low emissions for bulk |
| Sea | 0.01 - 0.03 | Lowest per tonne-km |
These are indicative ranges; actual factors depend on specific vehicle types and routes.
## Best Practices
**ISO 14064-1 Category 3 Best Practices**
1. **Prioritize by materiality**: Focus first on largest sources (usually flights and freight)
2. **Survey employees**: Conduct annual commuting surveys for accurate data
3. **Integrate booking systems**: Connect travel management systems for automatic capture
4. **Track trends**: Monitor business travel patterns to identify reduction opportunities
5. **Consider alternatives**: Rail vs. air, video conferencing vs. travel
## Next Steps
Measure emissions from purchased goods and services
Return to the main ISO 14064 tutorial