Who Is Responsible for Climate Change?

Same data. Different metrics. Different verdicts.

soft-blankets · INFO 3312 · Spring 2026

INFO 3312 · Cornell University · Spring 2026

Who Is Responsible
for Climate Change?

The answer depends on how you measure it. This project walks through four empirically valid lenses — and four different verdicts.

The Problem

“China is the world’s largest emitter.”

“But the US emits far more per person.”

“But the US caused the most damage historically.”

“But wealthy nations outsource their emissions.”

Every statement is backed by real data.

The choice of metric is never just technical — it is always also political.

Data & Approach

Our World in Data — CO₂ Emissions dataset, 2024

50,000+ observations · 1750 to present · 79 variables

Seven countries

China · United States · India · Germany · UK · Russia · Japan

Chosen to represent every fault line in the debate: large vs. small, early vs. late industrializers, producers vs. consumers.

Why Closeread scrollytelling — not Shiny, not a dashboard?

These metrics are routinely encountered in isolation. A guided narrative forces readers to hold all four lenses simultaneously.

The Four Lenses

Lens 01 · Total Emissions
Who emits the most per year? → China
Lens 02 · Per Capita
Adjusted for population → United States
Lens 03 · Cumulative
The weight of history → United States
Lens 04 · Consumption
Who owns the demand? → US / UK

Same data. Four metrics. Four different countries held responsible.

Design Decisions

Narrative architecture

We ordered the four lenses deliberately:

Total → Per capita → Cumulative → Consumption

Each lens exposes a blind spot in the previous one. By the time readers reach Lens 04, they have the context to see why consumption framing is so politically charged.

Form fits function

We chose Closeread scrollytelling over Shiny because interactivity without narrative guidance makes it harder to interpret data, not easier.

The scroll forces a reading order — and that order is the argument.

Two interactive elements added to engage the reader

Opening card reveal

Four lens cards appear one by one as readers scroll. Previews the structure, creates anticipation.

Verdict bar animation

In the conclusion, four bars fill left-to-right with staggered delays — drawing the eye sequentially through the final payoff.

Key Findings · Lenses 1 & 2

Lens 01 · Total

China surpassed the US around 2006 — but its output reflects manufacturing demand from wealthier nations, not domestic consumption.

Lens 02 · Per Capita

The US, Russia, and Germany are the real high emitters per person, reflecting car-dependent infrastructure and fossil-fuel grids.

Key Findings · Lenses 3 & 4

Lens 03 · Cumulative

The US accounts for ~23.5% of all historical emissions — the foundation of the historical responsibility argument made by developing nations.

Lens 04 · Consumption

The US and UK’s apparent domestic progress is partly an artifact of offshoring production, not genuine decarbonization.

Limitations & Reflection

What we had to work around

  • Consumption data is only available from 1990 — Lens 4 covers a shorter window than the other three
  • Seven countries capture the key fault lines but exclude most of the developing world
  • Pre-1850 cumulative estimates carry uncertainty; we treat them as lower bounds, not precise figures

What we learned

  • Closeread is a powerful tool for guided narrative — but requires careful planning of the scroll structure before writing any content
  • The metric you choose encodes a theory of fairness. It is never a neutral technical decision.

“The data cannot tell us what is fair. But it can tell us who has benefited most from the way responsibility has historically been measured — and who has not.”

Live Demo

Opening section — card reveal
Lens 3 — cumulative emissions

[https://pages.github.coecis.cornell.edu/info3312-sp26/proj-02-soft-blankets/]