How Clean is Pune's Air? A Data Story

Uncovering air quality patterns across India's 8th largest city using IoT sensor data

The Story#

Pune — a bustling city of over 7 million people, home to IT hubs, educational institutions, and growing traffic congestion. But how does all this activity affect the air we breathe?

I analyzed 103,000+ sensor readings from 10 monitoring stations spread across Pune to answer one question:

Where and when is Pune's air most polluted, and what can we do about it?

By The Numbers#

103,000+
Data Points

10
Monitoring Stations

28
Parameters Tracked

May - Aug 2019
Time Period

Key Insights#

1. Pollution Hotspots Are Concentrated Near Transport Hubs#

Hadapsar Gadital and Pune Railway Station consistently show pollution levels 40-60% higher than residential areas. The chart above ranks all monitoring stations by total pollution score.

2. Rush Hour = Danger Hour#

Pollution spikes between 8-10 AM — exactly when most people commute. The bar chart shows how PM2.5, PM10, and NO₂ levels change throughout the day.

Time	Risk Level	Recommendation
5-7 AM	Low	Best for outdoor exercise
8-10 AM	High	Avoid outdoor activities
12-4 PM	Moderate	Use caution
10 PM+	Low	Safe for evening walks

3. Weekends Bring Relief#

Pollution drops by ~15% on weekends — direct proof that reduced traffic improves air quality. This insight supports policies like odd-even traffic rules.

4. Three Distinct Pollution Zones#

Using K-Means clustering, I identified three types of areas:

Zone	What It Means	Action Needed
Green	Consistently clean	Maintain current state
Caution	Occasional spikes	Enhanced monitoring
Hotspot	Chronically polluted	Urgent intervention

5. Pollutants Are Interconnected#

PM2.5 and PM10 are strongly correlated (r = 0.89), indicating they share common sources — likely vehicle emissions and construction dust. This means targeting one pollutant can reduce both.

Key Takeaways#

Location matters — Pollution varies dramatically across the city
Timing matters — Morning rush hours are the worst
Behavior matters — Weekend patterns prove we can improve air quality
Data can guide policy — Targeted interventions beat blanket rules

Recommendations#

For City Planners#

Install air purifiers at Railway Station & Bus Depots
Implement 8-10 AM traffic restrictions in hotspots
Use humidity as early warning indicator
Increase green cover along major corridors

For Residents#

Exercise before 7 AM or after 8 PM
Use air purifiers if near identified hotspots
Check AQI apps before outdoor plans
Consider cycling on weekends (cleaner air!)

Methodology#

Step	Description
Data Cleaning	Handled missing values, parsed timestamps, flagged sensor errors
EDA	Distribution analysis, temporal patterns, geographic mapping
Correlation	Identified relationships between pollutants & environment
Clustering	K-Means to group locations by pollution behavior
Thresholds	Compared against NAAQS safe limits

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