Kaya Identity Calculator
Calculate CO₂ emissions using the Kaya Identity equation. Analyze the relationship between population, economic development, energy use, and carbon emissions for climate modeling.
Kaya Identity Factors
Select a preset or choose "Custom" to enter your own values
Total population of the region or country
Gross Domestic Product per person in US dollars
Energy consumption per dollar of GDP (kWh per USD)
CO₂ emissions per unit of energy (kg CO₂ per kWh)
Kaya Identity Equation
CO₂ Emissions Results
Total CO₂ Emissions
173.04 billion kg
Per Capita Emissions
22 kg
Total GDP
$85.16 trillion
Total Energy
121.78 trillion kWh
International Comparison
Per capita CO₂ emissions (kg/person/year)
✅ Below world average - good environmental performance
Understanding the Kaya Identity
What is the Kaya Identity?
The Kaya Identity is a mathematical equation that expresses the relationship between human activities and CO₂ emissions. It breaks down total emissions into four key factors that drive climate impact.
The Four Factors
- • Population (P): Total number of people
- • GDP per Capita (G/P): Economic prosperity
- • Energy Intensity (E/G): Energy efficiency
- • Carbon Intensity (F/E): Clean energy adoption
Climate Policy Applications
The IPCC uses the Kaya Identity for climate modeling and policy analysis. It helps identify which factors contribute most to emissions and guide mitigation strategies.
Reduction Strategies
- • Population: Education and family planning
- • GDP/Capita: Sustainable development
- • Energy Intensity: Efficiency improvements
- • Carbon Intensity: Renewable energy transition
IPAT vs Kaya Identity
IPAT Equation (1967)
- • I: Environmental Impact
- • P: Population
- • A: Affluence (vague concept)
- • T: Technology (hard to quantify)
Conceptual framework but difficult to measure
Kaya Identity (1989)
- • F: CO₂ Emissions (measurable)
- • P: Population (census data)
- • G/P: GDP per capita (economic data)
- • E/G: Energy intensity (statistical data)
- • F/E: Carbon intensity (energy data)
Quantifiable factors with available data sources