Wearable Commute Pollution Monitor Project

ISEF Category: Environmental Engineering

Subcategory: Other  ·  Difficulty: Intermediate  ·  Setup: School Lab  ·  Time: 1 to 2 Months

The Hook

Your commute may change the air you breathe more than the weather does. A few blocks on a bike can expose you to a different pollution mix than a bus ride or a car ride. That means your trip to school can become a real science experiment. You can measure it instead of guessing.

What Is It?

This project asks a simple question with a messy answer: how much pollution do you personally inhale during different ways of getting to school? You would wear or carry a small sensor device that logs carbon monoxide, fine particles, and volatile organic compounds, then compare those readings across commute modes like walking, biking, bus, and car.

Think of it like a fitness tracker for air. A step counter records movement, but this monitor records exposure. The key idea is personal exposure, which means the pollution right around your body, not just the air reported by a nearby weather station. That matters because two people in the same city can breathe very different air during the same morning.

You would not just compare raw sensor readings. You would turn the data into a dose estimate, which means exposure over time. That lets you ask better questions, like whether a shorter route with more traffic gives you a bigger dose than a longer route with cleaner streets.

Why This Is a Good Topic

This is a strong science fair topic because you can test it with real measurements, clear variables, and data you collect yourself. It connects to air quality, health, transportation, and city planning, so the project has real-world value. You can learn sensor calibration, data cleaning, graphing, and basic statistics without needing a university lab.

Research Questions

• How does commute mode affect average personal exposure to PM2.5 during the trip to school? ?
• What is the effect of walking versus biking on CO exposure along the same route? ?
• Does bus travel produce higher VOC readings than car travel during the same time window? ?
• To what extent does route choice change total pollutant dose for students who bike to school? ?
• Which commute mode shows the largest spike in particulate matter near traffic lights and busy intersections? ?
• How does time of day change commute exposure for the same mode and route? ?

Basic Materials

• ESP32 development board.
• CO sensor module suitable for low-level ambient monitoring.
• PM2.5 sensor module for fine particle measurement.
• VOC sensor module.
• Portable battery pack.
• MicroSD card module or onboard logging setup.
• USB cable for programming.
• Smartphone or laptop for timestamping and notes.
• Small enclosure or wearable case.
• Notebook for route and weather logs.
• Digital watch or phone timer.
• Access to traffic or route map data.

Advanced Materials

• ESP32 development board with data logging support.
• Reference-grade air monitor for calibration comparison.
• Low-cost particulate matter sensor with flow-stable housing.
• Electrochemical CO sensor with matching interface board.
• VOC sensor with temperature and humidity compensation.
• Temperature and humidity sensor.
• GPS module for route mapping.
• MicroSD card module.
• Battery pack with stable output.
• 3D-printed or machined enclosure.
• Data reference station access from a local air quality network.
• Calibration gases or lab-approved reference methods, if available through a university lab.

Software & Tools

• Arduino IDE: Programs the ESP32 and helps you test each sensor one at a time.
• Python: Cleans the data, calculates exposure metrics, and makes comparison graphs.
• Google Sheets: Tracks trips, labels commute mode, and checks for missing data.
• ImageJ: Helps inspect screenshots or plots if you document sensor display outputs.
• R: Supports stronger statistics if you want to compare commute modes with formal tests.

Experiment Steps

1. Define the exact exposure question and choose one route or a small set of matched routes.
2. Select the sensor signals you will trust, then plan how you will calibrate or check them against a reference.
3. Decide how you will log time, location, weather, and commute mode so your data stays comparable.
4. Build a dose metric that combines concentration with trip duration, then decide how you will compare trips fairly.
5. Plan controls for route length, traffic pattern, and sensor drift so the results reflect commute mode, not random noise.
6. Predefine the statistics and graphs you will use before you collect the first commute sample.

Common Pitfalls

• Trusting raw low-cost sensor readings without calibration, which can make one commute mode look cleaner or dirtier than it really is.
• Comparing a bike route and a bus route that use different streets, which mixes commute mode effects with route effects.
• Forgetting that humidity and temperature can shift PM2.5 and VOC sensor output, which creates fake spikes.
• Logging only average readings and missing short pollution bursts near traffic lights, buses, or idling cars.
• Wearing the device loosely or in different places on different days, which changes what air the sensors actually sample.

What Makes This Competitive

A stronger project goes beyond a simple mode comparison. You can make it more competitive by calibrating the sensors, separating route effects from commute mode effects, and using dose instead of just average concentration. Strong entries also test more than one school route, compare morning and afternoon trips, or use statistics that handle repeated measurements from the same student. That turns a neat gadget into a real exposure study.

Project Variations

• Compare indoor versus outdoor exposure for the same student route by adding a hallway, train, or sheltered-walk segment.
• Test how route choice changes exposure by comparing a busy arterial street with a lower-traffic side street for the same commute mode.
• Focus on one pollutant, such as PM2.5 or VOCs, and compare weekday, weather, or rush-hour patterns across multiple trips.

Learn More

• EPA Air Sensor Toolbox: Search the EPA site for guides on low-cost sensor use, calibration, and data interpretation.
• NOAA Air Resources Laboratory: Find background on air dispersion, weather, and pollution transport on the NOAA website.
• NASA Earthdata: Search for articles and datasets on aerosols, air quality, and satellite measurements.
• PubMed: Search for review articles on personal air pollution exposure in commuters and children.
• USGS Water Quality and Environmental Data, no direct match here is needed, so search USGS for general environmental monitoring methods and field data practices.
• MIT OpenCourseWare: Search for public materials on environmental engineering, sensing, and data analysis.