PM2.5 Sensor Network for Home Infiltration

ISEF Category: Environmental Engineering

Subcategory: Pollution Control  ·  Difficulty: Intermediate  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

Tiny particles move through your home like smoke through a cracked door. You cannot see most PM2.5, but your lungs can still feel it. With a few low-cost sensors, you can measure how much outdoor pollution gets inside and which home features seem to change that path.

What Is It?

PM2.5 means tiny airborne particles that are 2.5 micrometers wide or smaller. That is far thinner than a human hair. These particles can come from traffic, wildfire smoke, cooking, and dust. A sensor network helps you track where the particles are outside and where they end up indoors.

Think of your house like a sieve with different mesh sizes. Some homes let more outdoor air slip inside. Others stay tighter, or their HVAC system changes how air moves. The indoor-outdoor infiltration ratio tells you how much outdoor PM2.5 makes it indoors compared with what the outside sensor sees. If the ratio is high, the building likely lets in more outdoor particles. If it is low, the building blocks more of them or filters them better.

Your project can test whether building age, window type, floor level, HVAC setup, or air filter use predicts that ratio. You can use a PurpleAir sensor, a DIY SDS011 node, or both, then compare trends across homes. The real goal is not just measuring air. You are trying to explain why some homes trap pollution better than others.

Why This Is a Good Topic

This topic works well because you can measure it with affordable sensors, real homes, and clear math. You can change the question without changing the whole project, which makes it flexible for a first research attempt. It connects to wildfire smoke, traffic pollution, asthma, and home ventilation, so the real-world stakes are easy to explain. You can also learn sensor calibration, data cleaning, regression, and environmental statistics in one project.

Research Questions

• How does building age affect the indoor-outdoor PM2.5 infiltration ratio across homes with similar outdoor exposure?
• What is the effect of HVAC filter type on the indoor-outdoor PM2.5 infiltration ratio during the same outdoor pollution event?
• Does window-opening behavior change the indoor-outdoor PM2.5 infiltration ratio more than floor level does?
• To what extent do homes with forced-air HVAC systems differ from homes without them in PM2.5 infiltration coefficient?
• Which home features, such as insulation, window type, or number of exterior doors, best predict indoor PM2.5 levels after outdoor spikes?
• How does the agreement between a PurpleAir sensor and a DIY SDS011 node change when sensors are placed indoors versus outdoors?

Basic Materials

• PurpleAir sensor or DIY SDS011 PM2.5 sensor node.
• One outdoor sensor placement case or weather-safe enclosure.
• Indoor sensor mount or stand at breathing height.
• Smartphone or laptop for data access.
• Spreadsheet software for logging and plotting data.
• Home feature survey form for building age, HVAC type, and window type.
• Thermometer and humidity meter for context data.
• Measuring tape for documenting sensor placement distances.

Advanced Materials

• PurpleAir sensor with API access or downloadable data exports.
• DIY SDS011 PM2.5 nodes with microcontroller logger.
• Outdoor-rated enclosure with screened intake path.
• Reference-grade or school-owned aerosol monitor for comparison if available.
• Anemometer or local weather station access for wind and ventilation context.
• HEPA filter or portable air cleaner for intervention testing.
• Calibration aerosols or co-location setup for sensor cross-checking.
• Statistical software for regression and mixed-effects modeling.

Software & Tools

• Google Sheets: Organizes sensor logs, home feature data, and initial plots.
• R or Python: Fits regression models and compares infiltration ratios across homes.
• ImageJ: Helps if you analyze photos of sensor placement or room layout.
• PurpleAir map and data export tools: Provide outdoor PM2.5 context and time-matched readings.
• NOAA Air Resources Laboratory data: Helps you compare local weather and smoke conditions with your sensor trends.

Experiment Steps

1. Define the exact outcome you will measure, such as indoor-outdoor PM2.5 ratio or infiltration coefficient, and choose one time window for comparison.
2. Select a small set of home features to test, then turn each one into a clear variable you can record the same way in every home.
3. Plan sensor placement so indoor and outdoor readings line up in time, height, and distance from local pollution sources.
4. Build a data table that pairs PM2.5 readings with weather, HVAC status, and window behavior so you can control for obvious confounders.
5. Choose a comparison strategy, such as simple regression or multiple regression, before collecting data so your sample size matches the analysis.
6. Decide how you will check sensor agreement, handle missing data, and flag outlier spikes before you start your fieldwork.

Common Pitfalls

• Mixing indoor cooking events into your infiltration data, which makes home pollution look like outdoor infiltration.
• Placing the outdoor sensor too close to a vent, driveway, or grill, which inflates the outdoor baseline.
• Comparing homes that do not share the same smoke event or traffic window, which breaks the time alignment.
• Ignoring humidity effects on low-cost PM sensors, which can skew readings during damp weather.
• Using too few homes or too few pollution spikes, which leaves your regression too weak to support a pattern.

What Makes This Competitive

A stronger project does more than compare two sensor readings. You can stand out by co-locating sensors for calibration, using time-matched outdoor events, and testing several home features at once instead of one at a time. A careful regression model with uncertainty bars, outlier checks, and clear controls will look much stronger than a simple before-and-after chart. If you add a filter or window-opening intervention, you also get a design angle, not just an observation study.

Project Variations

• Compare infiltration ratios between homes with central HVAC and homes that rely on window units.
• Test whether wildfire smoke days produce different indoor-outdoor PM2.5 relationships than traffic-heavy weekdays.
• Analyze how portable air cleaners change the infiltration coefficient in a single home over repeated outdoor spikes.

Learn More

• US EPA Air Sensor Toolbox: Find guidance on low-cost particle sensors, calibration, and field checks by searching the EPA Air Sensor Toolbox page.
• NOAA Air Resources Laboratory: Find smoke, weather, and atmospheric data sources through NOAA to match outdoor pollution events.
• NIH PubMed: Search for review articles on PM2.5 infiltration, indoor air quality, and low-cost sensor validation.
• USGS Water and air data resources: Use USGS environmental data portals for context on local conditions and monitoring methods.
• MIT OpenCourseWare Environmental Engineering courses: Search MIT OpenCourseWare for classes on air pollution and environmental measurement methods.