# CO2 Emissions — Test Project Configuration
#
# Data size: ~50,000+ rows x 70+ columns (real data from Our World in Data)
# Download: python dev/test-datasets/download.py --dataset climate
#
# Project name:
co2-emissions-analysis

# Data path:
/home/mrichardson/Projects/Urika/dev/test-datasets/climate/data

# Description:
Global CO2 emissions data from Our World in Data, covering 200+ countries from 1750 to
present. Variables include annual CO2 emissions (total and per capita), emissions by fuel
type (coal, oil, gas, cement, flaring), cumulative emissions, population, GDP, energy
consumption, and other climate-related indicators. The goal is to identify the key drivers
of CO2 emission changes over time and across countries, and to model which economic and
energy factors best predict a country's emission trajectory.

# Research question:
What economic and energy factors best predict CO2 emissions per capita across countries, and
how have these relationships changed over time?

# Mode:
exploratory

# Web search:
no

# Venv:
no

# Knowledge suggestions:
Add the data-description.md from dev/test-datasets/climate/knowledge/. Optionally add
references on the Kaya identity, Environmental Kuznets Curve, or IPCC emissions modelling.
