Data list

[salihakalender]

Dataset	Coverage	Pollutants	Years	Notes
Kaggle - Global Air Pollution	Global	Multiple (depends on city)	2020	Some global coverage, limited time
WHO Data	Global	Various	2010–2022	Contains missing data
IHME GBD (Health Outcomes)	Global (country level)	Linked to pollutant impact	2020–2021	For disease burden analysis
PM2.5 Dataset	Global (country level)	PM2.5 only	2010–2019	Single pollutant focus
Said’s Shared Data	Europe only	Multiple	Varies	Limited to European cities
EPA Data	United States only	Multiple	1980–2024	Rich historical data, limited to U.S. cities
WHO Mortality Data	Global (country level)	All-cause and cause-specific	2019	Country-level mortality statistics
Anenberg NS_2019 (Said shared)	Global (city level)	PM2.5	2019	PM2.5-related disease burden in global cities

[salihakalender]

Combining Multiple Datasets to Link Air Pollution Exposure and Health Outcomes: A Multi-Source, Multi-Year Data Integration

✅ 1. Kaggle Global Air Pollution (2020) + IHME GBD (2020–2021)

🔗 How do they match?

• Year alignment: both cover 2020

• Kaggle provides city-level pollutant concentrations

• IHME offers country-level health outcomes (DALYs, deaths)

• Can be linked by aggregating city-level pollution to national averages

💡 Analysis Idea:
"Can city-level air pollution levels in 2020 explain variations in national disease burdens reported in 2020–2021?"

✅ 2. PM2.5 Dataset (2010–2019) + IHME GBD (2020–2021)

🔗 How do they match?

• Country-level data

• PM2.5 exposure (2010–2019) is linked to health burden data in 2020–2021

• Enables lag effect analysis between pollution exposure and disease outcomes

💡 Analysis Idea:
"In countries with long-term high exposure to PM2.5, did we observe an increase in related diseases such as cardiovascular or respiratory illnesses in the following years?"

✅ 3. Anenberg NS_2019 (City-level PM2.5) + WHO Mortality Data (2019)

🔗 How do they match?

• Both from the year 2019

• PM2.5 exposure and disease burden at the city level (Anenberg)

• Country-level mortality statistics (WHO)

• Useful for comparing city exposure vs. country-level outcomes

💡 Analysis Idea:
"Do cities with higher PM2.5 exposure also show higher national mortality from related diseases in 2019?"

✅ 4. EPA Data (1980–2024) + IHME GBD (2020–2021)

🔗 How do they match?

• U.S.-only data

• Long-term pollutant trends from EPA

• Health outcomes from IHME

• Good for policy impact assessment over time

💡 Analysis Idea:
"Have improvements in air quality in the U.S. led to measurable improvements in health outcomes?"