> ## 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.

# Core Concepts

> Understand the fundamental concepts of emissions tracking and environmental data management

# Core Concepts

Understanding these fundamental concepts will help you use the Dcycle API effectively and interpret your emissions data correctly.

## Carbon Accounting Basics

### What is CO2 Equivalent (CO2e)?

CO2 equivalent (CO2e) is a standardized metric that allows different greenhouse gases to be compared on a common scale.

Not all greenhouse gases have the same warming effect. For example:

* **1 kg of Methane (CH4)** = 28 kg CO2e
* **1 kg of Nitrous Oxide (N2O)** = 265 kg CO2e
* **1 kg of SF6** = 23,500 kg CO2e

<Info>
  Dcycle automatically converts all gases to CO2e using IPCC AR6 Global Warming Potential (GWP) values over a 100-year timeframe.
</Info>

### Example Calculation

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Manual calculation
ch4_emissions = 10  # kg of methane
gwp_ch4 = 28  # AR6 100-year GWP

co2e = ch4_emissions * gwp_ch4
# Result: 280 kg CO2e

# Dcycle does this automatically
response = api.calculate_emissions(
    methane=10,
    # Returns: {"co2e": 280, "breakdown": {...}}
)
```

## Emission Scopes

The GHG Protocol divides emissions into three scopes to help organizations understand their carbon footprint:

### Scope 1: Direct Emissions

Emissions from sources owned or controlled by your organization.

**Examples:**

* Company-owned vehicles (fleet)
* On-site fuel combustion (boilers, generators)
* Manufacturing processes
* Fugitive emissions (refrigerants, leaks)

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Track Scope 1 with Dcycle
# Fleet emissions
vehicle_emissions = api.track_vehicle_consumption(...)

# Facility fuel combustion
facility_emissions = api.track_facility_fuel(...)
```

### Scope 2: Indirect Energy Emissions

Emissions from purchased electricity, heating, or cooling.

**Examples:**

* Electricity consumption in offices
* District heating/cooling
* Purchased steam

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Track Scope 2 with Dcycle
# Upload utility invoices
invoice_emissions = api.upload_invoice(
    type="electricity",
    consumption=5000,  # kWh
    period="2024-01"
)
```

### Scope 3: Other Indirect Emissions

All other indirect emissions in your value chain.

**Examples:**

* **Upstream**: Purchased goods, business travel, employee commuting, waste disposal
* **Downstream**: Product transportation, end-of-life treatment, franchises

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Track Scope 3 with Dcycle
# Purchased goods
purchase_emissions = api.track_purchases(...)

# Logistics (upstream/downstream)
shipment_emissions = api.calculate_shipment(...)

# Waste disposal
waste_emissions = api.track_waste(...)
```

### Scope Summary

<CardGroup cols={3}>
  <Card title="Scope 1" icon="building">
    **Direct emissions**

    You own and control the source
  </Card>

  <Card title="Scope 2" icon="plug">
    **Energy indirect**

    You purchase the energy
  </Card>

  <Card title="Scope 3" icon="globe">
    **Other indirect**

    Your value chain
  </Card>
</CardGroup>

## Emission Factors

An emission factor is a coefficient that quantifies emissions per unit of activity.

### What is an Emission Factor?

```
Emissions = Activity Data × Emission Factor
```

**Example:**

```
Diesel consumption: 100 liters
Emission factor: 2.68 kg CO2e/liter
Total emissions: 100 × 2.68 = 268 kg CO2e
```

### Types of Emission Factors

<AccordionGroup>
  <Accordion title="Standard Factors">
    Pre-calculated factors from databases like DEFRA, ADEME, or EPA.

    **Used for**: Generic activities without specific supplier data

    **Accuracy**: Medium to High (depends on database quality)

    **Example**: "Diesel fuel combustion" = 2.68 kg CO2e/liter
  </Accordion>

  <Accordion title="Spend-Based Factors">
    Factors based on monetary value (\$/€ spent).

    **Used for**: When physical data is unavailable

    **Accuracy**: Low (high uncertainty)

    **Example**: "IT services" = 0.15 kg CO2e/€
  </Accordion>

  <Accordion title="Custom Emission Factors">
    Supplier-specific factors from EPDs or LCA studies.

    **Used for**: Supplier-verified data, PPAs, specific processes

    **Accuracy**: Very High (supplier-verified)

    **Example**: "Recycled aluminum - Supplier ABC" = 2.15 kg CO2e/kg

    See the [Custom Emission Factors guide](/guides/advanced/custom-emission-factors) for details.
  </Accordion>
</AccordionGroup>

### Dcycle's Emission Factor Database

Dcycle maintains an extensive database with:

* **15,000+** emission factors
* **50+** countries
* **Multiple methodologies** (DEFRA, ADEME, EPA, GHG Protocol)
* **Regular updates** following latest IPCC guidelines

## ISO 14083 Standard

ISO 14083 is the international standard for quantifying and reporting greenhouse gas emissions from transport operations.

### Key Principles

<Steps>
  <Step title="Well-to-Wheel (WTW) Methodology">
    Includes both fuel production (Well-to-Tank) and vehicle operation (Tank-to-Wheel).

    ```
    Total Emissions = WTT Emissions + TTW Emissions
    ```
  </Step>

  <Step title="Distance-Based Calculation">
    Emissions = Distance × Load × Emission Factor

    Accounts for both empty and loaded trips.
  </Step>

  <Step title="Transport Chain Allocation">
    For shipments with multiple legs (truck → ship → truck), emissions are allocated proportionally.
  </Step>

  <Step title="Default Values">
    When specific data is unavailable, ISO 14083 provides default load factors and emission factors.
  </Step>
</Steps>

### Example: ISO 14083 Calculation

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Dcycle automatically follows ISO 14083
response = api.calculate_shipment(
    origin="Madrid, Spain",
    destination="Barcelona, Spain",
    toc="van_diesel",  # Transport Operation Category
    load=1000,
    load_unit="kg",
    year=2024
)

# Response includes ISO 14083 breakdown
{
    "co2e": 245.5,  # Total WTW emissions
    "distance_km": 620.0,
    "methodology": "ISO 14083",
    "breakdown": {
        "ttw": 215.3,  # Tank-to-Wheel (direct)
        "wtw": 30.2    # Well-to-Tank (upstream)
    }
}
```

### Transport Operation Categories (TOC)

ISO 14083 defines standard vehicle categories:

| Category    | Description              | Example          |
| ----------- | ------------------------ | ---------------- |
| Van         | Light commercial vehicle | Delivery van     |
| Rigid       | Single-unit truck        | Box truck        |
| Articulated | Tractor-trailer          | Semi-truck       |
| Rail        | Freight train            | Container train  |
| Maritime    | Cargo ship               | Container vessel |
| Air         | Cargo aircraft           | Freight plane    |

## GHG Protocol

The Greenhouse Gas Protocol is the most widely used international accounting standard for greenhouse gas emissions.

### Core Principles

1. **Relevance**: Report emissions appropriate to the organization's needs
2. **Completeness**: Include all emission sources within boundaries
3. **Consistency**: Use consistent methodologies for comparisons
4. **Transparency**: Document assumptions and data sources
5. **Accuracy**: Reduce uncertainties as much as possible

### Organizational Boundaries

<CardGroup cols={2}>
  <Card title="Equity Share" icon="percent">
    Account for emissions based on % ownership
  </Card>

  <Card title="Operational Control" icon="gears">
    Account for 100% of emissions from controlled operations
  </Card>

  <Card title="Financial Control" icon="dollar-sign">
    Account for operations with financial control
  </Card>
</CardGroup>

## Uncertainty and Data Quality

Not all emissions data is equally accurate. Understanding uncertainty helps prioritize data improvement efforts.

### Data Quality Hierarchy

```
1. Primary Data (Measured)           ← Highest accuracy
   └─ Direct measurements, supplier EPDs

2. Secondary Data (Calculated)
   └─ Standard emission factors, industry averages

3. Tertiary Data (Estimated)
   └─ Spend-based factors, proxies

4. Extrapolated Data (Assumed)      ← Lowest accuracy
   └─ Historical trends, benchmarks
```

### Reducing Uncertainty

<Steps>
  <Step title="Start with what you have">
    Use spend-based factors to establish baseline
  </Step>

  <Step title="Collect primary data">
    Gather utility bills, fuel receipts, supplier data
  </Step>

  <Step title="Request supplier-specific factors">
    Ask suppliers for EPDs or product carbon footprints
  </Step>

  <Step title="Use custom emission factors">
    Replace generic factors with verified supplier data
  </Step>
</Steps>

### Uncertainty Grades in Dcycle

When using custom emission factors, track uncertainty:

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
custom_factor = {
    "ef_name": "Supplier ABC Aluminum",
    "uncertainty_grade": 15,  # 15% uncertainty (high confidence)
    "additional_docs": "EPD No. ABC-2024-001, Bureau Veritas verified",
    # ...
}

# Track data quality over time
# Prioritize improving factors with >50% uncertainty
```

## Biogenic vs. Fossil Emissions

Different carbon sources have different climate impacts.

### Fossil Emissions

Carbon from underground reserves (oil, gas, coal).

**Impact**: Adds NEW carbon to atmosphere
**Reporting**: Always included in total emissions
**Example**: Diesel fuel, natural gas

### Biogenic Emissions

Carbon from biomass (wood, crops, organic waste).

**Impact**: Part of natural carbon cycle (carbon was recently in atmosphere)
**Reporting**: Often reported separately
**Example**: Biogas, biomass burning, composting

### Why It Matters

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Waste treatment example
landfill_methane = {
    "source": "organic_waste",
    "ch4_emissions": 10,  # kg
    "type": "biogenic"     # Was recently atmospheric CO2
}

diesel_combustion = {
    "source": "fossil_fuel",
    "co2_emissions": 268,  # kg
    "type": "fossil"       # New atmospheric carbon
}
```

<Info>
  Dcycle tracks biogenic and fossil emissions separately when relevant (e.g., waste management, energy from biomass).
</Info>

## Next Steps

Now that you understand the core concepts, explore how to apply them:

<CardGroup cols={2}>
  <Card title="Calculate Emissions" icon="calculator" href="/guides/emissions/overview">
    Learn how to calculate emissions for different activities
  </Card>

  <Card title="Custom Emission Factors" icon="chart-line" href="/guides/advanced/custom-emission-factors">
    Use supplier-specific data for accurate tracking
  </Card>

  <Card title="Quickstart" icon="rocket" href="/docs/quickstart">
    Make your first API call
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference/introduction">
    Explore all available endpoints
  </Card>
</CardGroup>