The social cost of carbon (SCC) measures the economic damage from emitting one extra ton of CO₂. Researchers face high uncertainty in this estimate. They compare three main integrated assessment models: DICE, PAGE, and FUND.
DICE uses a simple quadratic damage function. It links temperature rise directly to GDP loss. PAGE offers more flexibility. It includes probabilistic elements and regional details. FUND breaks damages into sectors. It considers factors like income and adaptation.
These models produce different SCC values. DICE often gives lower estimates. PAGE and FUND can show higher costs under certain assumptions. For example, recent DICE-2023 updates raise damages to about 3.1% of output at 3°C warming.
Uncertainty arises from damage functions. Older versions underestimate risks like tipping points or persistent effects. Updated functions incorporate new evidence. They include better data on agriculture, mortality, energy use, and sea-level rise.
Researchers apply Monte Carlo simulations. They vary key parameters like climate sensitivity and discount rates. This creates probability distributions for SCC. Results show wide ranges, sometimes from tens to hundreds of dollars per ton.
Recent syntheses push estimates higher. One comprehensive review finds a mean SCC around $284 per ton. Structural differences drive variation. Updated damage functions and persistent damages play major roles.
Policy makers use SCC for cost-benefit analysis. Higher values justify stronger climate action. Lower values suggest slower mitigation.
Comparisons reveal model strengths and limits. DICE provides clear optimization paths. PAGE handles uncertainty well. FUND captures sectoral diversity.
Overall, uncertainty remains large. Updated damage functions increase SCC estimates. They highlight the need for caution. Better models support informed decisions on emissions reduction. This approach balances economic costs with climate risks.