Air Sensor Data Analysis
Students learn to use air quality sensors, collect real data, analyze patterns, and make evidence-based recommendations for improving indoor air quality.
8
Lessons
8-10
Class Periods
Med
Materials Cost
4
NGSS Standards
Essential Question
How can we use sensor data to understand, monitor, and improve the air we breathe?
Lessons
-
1→Introduction to Air Quality Sensors
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2→CO2 as a Ventilation Indicator
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3→PM2.5 Monitoring
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4→Designing a Monitoring Study
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5→Collecting Classroom Data
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6→Graphing and Visualization
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7→Statistical Analysis
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8→Presenting Findings and Recommendations
Key Concepts
CO2 Monitoring
- Outdoor: ~420 ppm
- Good indoor: <800 ppm
- Moderate: 800-1500 ppm
- Poor: >1500 ppm
PM2.5 Monitoring
- Good: 0-12 μg/m³
- Moderate: 12-35 μg/m³
- Unhealthy for sensitive: 35-55 μg/m³
- Unhealthy: >55 μg/m³
Data Analysis Skills
- Time-series graphing
- Calculating averages
- Identifying patterns
- Comparing conditions
Evidence-Based Decisions
- Data supports claims
- Quantify improvements
- Make recommendations
- Communicate findings
Materials Needed
- CO2 monitor (e.g., Aranet4, CO2.click, or similar) - at least 1 per class
- PM2.5 sensor (e.g., PurpleAir, IQAir, or similar) - optional but recommended
- Spreadsheet software (Google Sheets, Excel)
- Graph paper or graphing software
- Data recording sheets
Budget option: Many activities can use publicly available data from PurpleAir or AirNow if sensors are unavailable.
Standards Alignment
| Standard | Description |
|---|---|
| MS-ESS3-3 | Apply scientific principles to design a method for monitoring human impact |
| MS-ETS1-4 | Develop a model to generate data for iterative testing |
| 6.SP.B.4 | Display numerical data in plots; summarize distributions |
| 8.SP.A.1 | Construct and interpret scatter plots; describe patterns |