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The Climate Inequality Paradox

Responsibility vs. Climate Vulnerability in High- and Low-Income Nations

COGS 108 — Data Science in Practice | UC San Diego | Winter 2026


Overview

This project investigates the Climate Inequality Paradox: the phenomenon where the nations least responsible for climate change suffer its consequences the most. Using three publicly available datasets spanning 2005–2023, we quantify the relationship between CO₂ emissions responsibility and climate disaster vulnerability across 164 countries and 1,932 country-year observations.


Research Question

Were higher per-capita CO₂ emissions associated with greater climate-related disaster impacts — in the form of higher mortality and reduced GDP growth — for lower-income countries than for higher-income countries between 2005 and 2023?


Key Findings

  • 19× Inequality Gap: For every ton of CO₂ a low-income country emits, it suffers nearly 19 times more human disaster loss than a high-income country for the same unit of emission
  • Emissions vs. Responsibility: High-income nations emit an average of 11.6 tons CO₂/capita — over 31× more than low-income nations at 0.37 tons
  • GDP Suppression: Low-income nations experience a ~2 percentage point GDP growth decline as disaster severity increases, while high-income economies remain essentially flat
  • Geographic Concentration: 75% of the top 20 most climate-injustice-affected nations are Low Income or Lower-Middle Income
Income Group Avg CO₂ (Tons/Capita) Avg Deaths per 100k Avg Inequality Ratio
Low Income 0.368 3.644 22.399
Lower-Middle 1.606 9.262 7.276
Upper-Middle 4.427 4.463 1.537
High Income 11.623 6.228 1.207

The Inequality Ratio

A core contribution of this project is the Inequality Ratio metric:

$$\text{Inequality Ratio} = \frac{\text{Disaster Deaths and Missing per 100k}}{\text{CO}_2 \text{ Tons per Capita}}$$

This normalizes disaster impact against emissions responsibility, enabling apples-to-apples comparison across countries with vastly different economic profiles. Rather than asking "how many people died?", it asks "how many people died per ton of CO₂ that country was responsible for emitting?"


Datasets

Dataset Source Observations
CO₂ Emissions Per Capita Our World in Data 4,085 country-years
Disaster Death Rates EM-DAT via Our World in Data 1,966 country-years
GDP Per Capita (PPP) World Bank via Our World in Data 4,005 country-years

All three datasets were merged on country code and year, restricted to 2005–2023, and filtered to real countries only (valid ISO 3-letter codes). Final merged dataset: 1,932 observations across 164 countries.


Methods

  • Exploratory Data Analysis (EDA) across income quartiles defined by pd.qcut on GDP per capita
  • Log-log scatter plots to visualize wealth-emissions and wealth-inequality relationships across several orders of magnitude
  • Median lines per income group to surface structural patterns robust to individual disaster outliers
  • OLS regression on log-scaled axes to quantify the inequality ratio trend
  • GDP growth analysis binned by disaster severity quintiles with 95% confidence intervals
  • Choropleth mapping via Plotly for geographic visualization of inequality ratios

Stack

Python Pandas Seaborn Plotly Jupyter

  • Python 3.11
  • Pandas — data wrangling and merging
  • Seaborn / Matplotlib — static visualizations
  • Plotly Express — interactive choropleth map
  • NumPy — numerical operations and log transforms

Authors

This project was completed as part of COGS 108 at UC San Diego (Winter 2026).

Author Contributions
Jacob Ortiz Analysis, Background research, Conceptualization, Data curation, Experimental investigation, Methodology, Project administration, Software, Writing
Muhammed Abdalla Software, Writing — original draft, Writing — review & editing
Katherine Chui Software, Visualization, Writing — review & editing
Iha Gadiya Analysis, Methodology, Visualization, Writing — review & editing
Jeanne Lee Background research, Conceptualization, Analysis, Methodology, Visualization, Writing, Project Administration

References

  1. "Current GHG Levels," NOAA. https://www.climate.gov/ghg/current-levels
  2. "CO₂ emissions per capita," Our World in Data. https://ourworldindata.org/grapher/co-emissions-per-capita
  3. "Climate Change," Our World in Data. https://ourworldindata.org/climate-change
  4. "Global natural disaster death rates," Our World in Data. https://ourworldindata.org/grapher/natural-disaster-death-rates
  5. "Climate Inequality Report 2023," World Inequality Lab. https://wid.world/wp-content/uploads/2023/01/CBV2023-ClimateInequalityReport-2.pdf
  6. Diffenbaugh & Burke, "Global warming has increased global economic inequality," PNAS, 2019.
  7. Zahnow et al., "Climate change inequalities: A systematic review," ScienceDirect, 2025.

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