Human Perceptions in Climate Change: Interactive CO2 Simulation Data

A 100 to 200-year simulation period tested participants' ability to control atmospheric CO2 concentration. The dataset likely contains results from an interactive simulation based on the DICE-1992 model, where participants made emission decisions under different feedback delay conditions. The research was conducted by Varun Dutt at Carnegie Mellon University.

Use Cases

• Modeling human decision-making heuristics based on simulated CO2 emission choices.
• Analyzing the impact of feedback delays on control performance in climate simulations.
• Training behavioral models for climate policy using data from the described laboratory experiment.

Strengths

• Data is derived from a controlled laboratory experiment with defined conditions, such as transfer rates of 1.6% and 1.2% per year.
• Simulation is based on the established Dynamic Integrated Climate Economy (DICE)-1992 model.
• Experimental design includes two distinct temporal conditions for decision-making (every 2 or 4 years).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Carnegie Mellon University

Collection Method

Data likely gathered from a laboratory experiment using an interactive simulation tool.

Time Range

Simulation period covers 100 to 200 years.