AgentSkillsCN

Calculate Carbon Footprint

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SKILL.md

Skill: Calculate Carbon Footprint

Domain

energy_sustainability

Description

Calculates organizational carbon footprint across Scope 1, 2, and 3 emissions using GHG Protocol methodology for ESG reporting.

Tags

carbon, emissions, GHG, sustainability, ESG, climate, environmental

Use Cases

  • •Annual emissions reporting
  • •Carbon reduction planning
  • •Scope 3 supply chain analysis
  • •Offset requirement calculation

Proprietary Business Rules

Rule 1: Scope Classification

Categorization of emissions by GHG Protocol scopes.

Rule 2: Emission Factor Application

Activity-specific emission factor selection and calculation.

Rule 3: Data Quality Scoring

Assessment of calculation certainty based on data sources.

Rule 4: Reduction Opportunity Identification

Analysis of high-impact reduction opportunities.

Input Parameters

  • •organization_id (string): Organization identifier
  • •reporting_period (dict): Start and end dates
  • •scope1_activities (list): Direct emission activities
  • •scope2_data (dict): Purchased energy data
  • •scope3_categories (list): Value chain emissions
  • •baseline_year (dict): Baseline comparison data

Output

  • •total_emissions (float): Total CO2e in metric tons
  • •emissions_by_scope (dict): Breakdown by scope
  • •intensity_metrics (dict): Normalized metrics
  • •reduction_opportunities (list): Identified reductions
  • •data_quality_score (float): Calculation confidence

Implementation

The calculation logic is implemented in carbon_calculator.py and references data from CSV files:

  • •scope1.csv - Reference data
  • •scope2.csv - Reference data
  • •scope3.csv - Reference data
  • •thresholds.csv - Reference data
  • •gwp_values.csv - Reference data
  • •parameters.csv - Reference data.

Usage Example

python
from carbon_calculator import calculate_footprint

result = calculate_footprint(
    organization_id="ORG-001",
    reporting_period={"start": "2025-01-01", "end": "2025-12-31"},
    scope1_activities=[{"type": "natural_gas", "quantity": 50000, "unit": "therms"}],
    scope2_data={"electricity_kwh": 1000000, "grid_region": "US-WECC"},
    scope3_categories=[{"category": "business_travel", "data": {"air_miles": 500000}}],
    baseline_year={"year": 2020, "total_emissions": 5000}
)

print(f"Total Emissions: {result['total_emissions']} tCO2e")

Test Execution

python
from carbon_calculator import calculate_footprint

result = calculate_footprint(
    organization_id=input_data.get('organization_id'),
    reporting_period=input_data.get('reporting_period', {}),
    scope1_activities=input_data.get('scope1_activities', []),
    scope2_data=input_data.get('scope2_data', {}),
    scope3_categories=input_data.get('scope3_categories', []),
    baseline_year=input_data.get('baseline_year', {})
)