Egypt Emissions Trend & Climate Inequality Dashboard

An interactive dashboard exploring Egypt's emissions trajectory through a climate justice lens

🚀 Live Demo • Data Source: Our World in Data • AI: OpenRouter • Visualizations: Plotly.js

The Climate Justice Story

Egypt presents a compelling case of climate injustice — where vulnerability vastly exceeds responsibility.

Key Statistics (2023)

Metric	Egypt	Global Average	Implication
CO₂ per capita	2.19 t	4.71 t	54% below average
Global CO₂ share	0.64%	—	1/3 of population share
Population	114 million	—	Growing at ~2M/year
GDP per capita	$3,457 (nominal)	—	Developing nation

Why This Matters

Egypt contributes less than 0.7% of global CO₂ emissions
Hosts COP27 (2022)** and committed to 42% renewable electricity by 2035
One of the world's most climate-vulnerable coastal zones faces sea-level rise
Despite Zohr gas discovery (2015) making Egypt a net exporter, fossil fuels still account for 90%+ of electricity

Dashboard Features

1. Emissions Trend Analysis

Interactive line charts showing Egypt's CO₂ emissions from 2001-2023 with:

Total emissions (Mt CO₂) with historical phases
Per capita emissions (t CO₂/person) normalized by population
CAGR calculations for each historical period

Historical Phases:

Period	Phase	CAGR	Key Events
2001-2010	Pre-Arab Spring	+5.4%/yr	Rapid industrialization
2011-2015	Post-Crisis	+0.6%/yr	Arab Spring, political transition
2016-2019	Reform & Zohr	-1.5%/yr	Zohr gas online, IMF reform
2020-2023	COVID & Recovery	+0.5%/yr	Pandemic, global recovery

2. Fuel Mix Breakdown (CO₂/GHG Toggle) with Historical Timeline

Explore emissions by source with a toggle between:

CO₂ Mode: Coal, Oil, Gas, Cement, Flaring
GHG Mode: Full greenhouse gas breakdown including methane (CH₄), nitrous oxide (N₂O)

Interactive Timeline Animation: Features an integrated scrubber and playback ▶ controls allowing you to see the exact Donut Chart distribution for any year. As the Donut chart animates, a sweeping timeline synchronizes across the Stacked Area historical series (2001-2023) to show how fuel reliance evolved over two decades!

Key Insight: The Zohr gas field (discovered 2015, online 2017) led to Egypt becoming a net gas exporter by 2019 — explaining the emissions decline during 2016-2019.

3. Global Comparison with Year Filter

Compare Egypt's performance against different country groups across 2001-2023:

Tier	Countries	Purpose
Peers	India, Morocco, Pakistan, Indonesia	Similar development stage
Regional	Saudi Arabia, Iran, Iraq, South Africa	Geographic neighbors
Responsibility	USA, China, Germany, World	Historical emitters

Four Comparison Charts:

Per Capita Bar — Sorted descending with world average reference line and dynamic gradient shading
GDP vs CO₂ Scatter — Advanced linear scaling with area-proportional population bubbles (sizeref scaling)
HDI-Adjusted Emissions — CO₂ per capita / HDI score (live HDI data from UNDP Data API)
Carbon Intensity — CO₂ per million USD GDP (using nominal US$ from World Bank API)

4. AI-Powered Insights

Generated using free-tier LLMs via OpenRouter, providing:

Trend analysis with key drivers
Country comparison insights
Emission source breakdown analysis
Climate justice reflection

5. Global Context Panel

Quick reference metrics showing:

GDP per capita (nominal USD, not PPP)
vs Global Average (-54% less)
Share of Global Emissions (0.64%)

Technical Architecture

flowchart TD
    subgraph Backend [Flask Backend]
        direction LR
        A[app.py<br>Routes] ~~~ B[data_utils.py<br>Data Logic] ~~~ C[ai_service.py<br>OpenRouter API]
    end

    subgraph LocalCache [Local CSV Cache]
        direction LR
        D1[(OWID Data<br>owid_emissions.csv)]
        D2[(UNDP Data<br>undp_hdi_scores.csv)]
        D3[(World Bank Data<br>worldbank_gdp.csv)]
    end

    subgraph Templates [Jinja2 Templates]
        direction LR
        E[base.html<br>Layout & CSS] ~~~ F[index.html<br>Dashboard UI]
    end

    subgraph Frontend [Plotly Frontend]
        direction LR
        G(Line Charts) ~~~ H(Donut Chart) ~~~ I(Bar Charts) ~~~ J(Scatter Plot)
    end

    Backend --> LocalCache
    Backend --> Templates
    Templates --> Frontend

Tech Stack

Component	Technology	Purpose
Backend	Python Flask	API endpoints, data processing
Data (Primary)	Pandas, OWID CSV	Core emissions metrics
Data (External API)	`requests` module	Dynamic HDI (UNDP HDR API) & Nominal GDP (World Bank API)
Frontend	HTML/CSS/JavaScript	Dashboard UI, Animation loops
Charts	Plotly.js	Interactive visualizations
AI	OpenRouter API	Natural language insights
Dev Assistant	Opencode Big Pickle	HTML/CSS/JS implementation
Fonts	Plus Jakarta Sans, Outfit, DM Mono	Typography

API Reference

Core Endpoints

Endpoint	Method	Parameters	Description
`/`	GET	—	Main dashboard
`/api/countries`	GET	—	List available countries
`/api/summary/<code>`	GET	`code`: ISO code	Country summary
`/api/trend/<code>`	GET	`code`, `metric`: co2/ghg	Trend statistics
`/api/comparison/<code>`	GET	`code`, `tier`, `year`	Comparison data
`/api/emission-sources/<code>`	GET	`code`, `mode`, `year`	Source breakdown

AI Endpoints

Endpoint	Method	Parameters	Description
`/api/ai/trend/<code>`	GET	`code`, `metric`	Trend insight
`/api/ai/comparison/<code>`	GET	`code`, `tier`	Comparison insight
`/api/ai/sources/<code>`	GET	`code`, `mode`	Sources insight
`/api/ai/reflection/<code>`	GET	`code`	Climate reflection

Example API Calls

# Get Egypt summary
curl http://localhost:5000/api/summary/EGY

# Get comparison data for 2015
curl "http://localhost:5000/api/comparison/EGY?tier=peers&year=2015"

# Get emission sources in GHG mode
curl "http://localhost:5000/api/emission-sources/EGY?mode=ghg&year=2023"

Setup Instructions

Prerequisites

Python 3.8+
pip (Python package manager)

Installation

Clone the repository

git clone <repository-url>
cd emission_trend_analysis

Create virtual environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install dependencies
```
pip install -r requirements.txt
```

Configure environment variables

cp .env.example .env
# Edit .env and add your OpenRouter API key (optional, for AI features)

Run the dashboard
```
python app.py
```
Open in browser
```
http://localhost:5000
```

Environment Variables

Create a .env file:

# OpenRouter API Key (optional - AI features won't work without it)
# Get free key at: https://openrouter.ai/
OPENROUTER_API_KEY=your_api_key_here

# UNDP HDR API Key (required for dynamic HDI metric charts)
HDR_API_KEY=HDR-68M2Tq4FVFxNBTfVHszAALekyuaFxQ4u

# Optional: Flask configuration
FLASK_ENV=development
FLASK_DEBUG=1

Deploying to Vercel

This application is ready to be deployed to Vercel out of the box (configured via vercel.json and app.py).

Push your repository to GitHub.
Log into Vercel and click Add New Project.
Import your GitHub repository.
Add your OPENROUTER_API_KEY to the Environment Variables section.
Click Deploy.

Data Sources & Citations

Primary Data

Source	Description	URL
Our World in Data	CO₂ & GHG emissions dataset	github.com/owid/co2-data
Global Carbon Project	Emissions data provider	globalcarbonproject.org
UNFCCC	GHG inventories	unfccc.int

Economic & Human Data APIs

Source	Description	Built-In Integration
World Bank API	GDP per capita (nominal USD) `NY.GDP.PCAP.CD`	Data automatically fetched and cached
UNDP HDR API	Human Development Index (HDI)	Live fetched tracking for over 190 countries

Policy References

Source	Description
IEA	World Energy Outlook 2023
IPCC	AR6 Climate Change 2023 Synthesis Report
ICAP	Emissions Trading Worldwide Status Report 2023
UNEP	Emissions Gap Report 2024
CCPI	Climate Change Performance Index 2024

Climate Policy Context

Egypt's Climate Commitments

COP27 Host (2022): Egypt hosted the UN Climate Change Conference in Sharm El-Sheikh
NDC Target: 42% renewable electricity by 2035
Zohr Gas Field: Discovery (2015) made Egypt a net gas exporter by 2019
Vulnerability: One of world's most climate-vulnerable coastal zones

Historical Context

Event	Year	Impact on Emissions
Arab Spring	2011	Political instability, growth slowdown
IMF Currency Reform	2016	Economic adjustment, energy reforms
Zohr Gas Online	2017	Natural gas surplus, exports begin
COVID-19	2020	Global emissions dip
COP27	2022	International climate spotlight

Project Structure

emission_trend_analysis/
├── app.py                 # Flask application & routes
├── data_utils.py          # Data processing functions
├── ai_service.py          # OpenRouter AI integration
├── requirements.txt       # Python dependencies
├── .env.example           # Environment template
│
├── data/
│   ├── cache/
│   │   ├── owid_emissions.csv  # OWID data (cached)
│   │   └── undp_hdi_scores.csv # UNDP data (cached)
│   │   └── worldbank_gdp.csv   # World Bank data (cached)
│   ├── fetch_data.ipynb   # Data fetching notebook
│   ├── analysis.ipynb     # Analysis notebook
│   └── countries.ipynb    # Country config notebook
│
├── templates/
│   ├── base.html          # Base template (CSS, layout)
│   └── index.html         # Main dashboard page
│
├── static/
│   └── egypt_hero.jpg     # Hero background image
│
├── CODE_EXPLANATION.md    # Technical documentation
└── README.md              # This file

Key Features Explained

CO₂ vs GHG Toggle

The dashboard supports two emission views:

CO₂ Mode: Only carbon dioxide emissions
GHG Mode: Full greenhouse gas inventory including methane (CH₄) and nitrous oxide (N₂O)

Non-CO₂ Calculation:

Other GHGs = Total GHG (excl. LUCF) - (Coal + Oil + Gas + Cement + Flaring)

Calculated using GWP100 metric via OWID/IPCC methodology.

HDI-Adjusted Emissions

This metric combines CO₂ per capita with Human Development Index to assess climate justice:

HDI-Adjusted = CO₂ per capita / HDI Score

Lower values = more efficient human development per unit of CO₂

Example values (2023):

Country	CO₂/capita	HDI	Adjusted
Egypt	2.19	0.731	3.0
India	2.13	0.645	3.3

CAGR Calculation

Compound Annual Growth Rate calculated from actual data:

CAGR = (End Value / Start Value)^(1/years) - 1

Not hardcoded estimates — computed from OWID time series data.

Development Notes

Adding New Countries

Update data_utils.py with country code and HDI score
Add to TIER_COMPARISONS for comparison groups
Create country description in index.html countryDescriptions object

Modifying Charts

All Plotly charts use a shared configuration (PB object) in index.html:

const PB = {
    paper_bgcolor: 'rgba(0,0,0,0)',
    plot_bgcolor: 'rgba(0,0,0,0)',
    font: { family: 'Plus Jakarta Sans', ... },
    margin: { t: 16, r: 16, b: 48, l: 56 },
    // ...
};

AI Service

The AI service uses free-tier models via OpenRouter. Rate limiting (2-second intervals) prevents API overuse. Prompts are optimized for concise, actionable insights.

License

This project is for educational and research purposes. Data sourced from Our World in Data under their license terms, and Human Development Index data from the United Nations Development Programme (UNDP).

Acknowledgments

Main Data: Our World in Data - Global Carbon Project
HDI Data: United Nations Development Programme (UNDP) - Human Development Index & PHDI
AI: OpenRouter - Free tier LLM access for dashboard insights
AI Development Assistant: Opencode Big Pickle - Used for HTML, CSS, and JavaScript implementation assistance
Visualizations: Plotly
Fonts: Google Fonts - Plus Jakarta Sans, Outfit, DM Mono

Built for TISS Mumbai - Climate Change, Sustainability & Development Assignment

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
data		data
static		static
templates		templates
.env.example		.env.example
.gitignore		.gitignore
CODE_EXPLANATION.md		CODE_EXPLANATION.md
README.md		README.md
ai_service.py		ai_service.py
app.py		app.py
data_utils.py		data_utils.py
requirements.txt		requirements.txt
vercel.json		vercel.json

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