Background: A new roof was installed in June 2015 on our typical two story house. Before that we had a gable mounted attic fan at the east end of the house. The fan has a thermostat that turns on the fan when the attic temperature goes above 105F. The fan has been working since early 2000'ish (2002-03?).
With the new roof, the contractor urged us to include the ridge vent so the roof would have adequate ventilation to honor the manufacturer's warranty. With the ridge vent, the gables were blocked off, and the fan disconnected.
Purpose:
- How hot is the attic, really? How is the attic temperature impacted other factors (weather, outside temperature, etc)
- Would and how much the attic be cooler if we turn on the attic fan again?
Part 1: Baseline
This is to answer the question -- how hot is the attic, and what are the factors?
Solution Components: To achieve the purpose, we need
- Some kind of sensor (temperature at least)
- Automated data capture so we don't have to climb to the attic every 5 minutes to read it.
- Environment data, particularly outside weather data.
- A way to analyse and visualize the data.
For the sensor, we decided to use the DHT22 which measures both temperature and humidity. We passed the DHT11, which can only go up to 50C (the attic is hotter than that). Another nice thing of the DHT22 is it is digital, we don't need to worry about the calibration.
The package looks like this, with a proto board to make some thing more permanent if we decide so.
The Make: We mounted the photon to a breadboard, plugged in a USB cable, and were ready to play with the firmware. After a few tries, we found out D0 just couldn't work, so we decided on D1. Actually we have a "prototype station", and whole thing looks more permanent.
The Coding: There are two parts, coding the photon (creating the firmware), and integration.
For the firmware, we used the DHT_sampling.ino with minor modifications.Basically it runs a loop of nFrequency seconds, read the data, and make them available either as individual datum or as a json object. In Particle Build, you can compile the code, and flash the photon with one click. This works really well.
For the integration, we used the Particle JavaScript SDK. We also grabbed the weather data from weather underground.
The Unexpected: Then we migrated the whole thing to the attic. By end of the first day, there was mounting concern that the thing may get too hot, and create a fire hazard. Decision was made to move the unit to the 2nd floor living area, and only leave the sensor in the attic. Luckily we have a pool of thermostat cable handy. We found the move was judicious, since the breadboard came off the plywood simply in one day. The glue turned didn't survive 100+ degree heat.
The Result: Once we have all the data, we loaded it to Tableau Public, It is a great software FREE, with some limitations. From July 20th to July 30th, it is a stretch of relatively hot summer days. Play with the dashboard filters, and draw your conclusion.
My Conclusion:
Post Note: Curious of the current temperature in the attic? The following is a 24 hour view updated every few minutes.
The Coding: There are two parts, coding the photon (creating the firmware), and integration.
For the firmware, we used the DHT_sampling.ino with minor modifications.Basically it runs a loop of nFrequency seconds, read the data, and make them available either as individual datum or as a json object. In Particle Build, you can compile the code, and flash the photon with one click. This works really well.
For the integration, we used the Particle JavaScript SDK. We also grabbed the weather data from weather underground.
The Unexpected: Then we migrated the whole thing to the attic. By end of the first day, there was mounting concern that the thing may get too hot, and create a fire hazard. Decision was made to move the unit to the 2nd floor living area, and only leave the sensor in the attic. Luckily we have a pool of thermostat cable handy. We found the move was judicious, since the breadboard came off the plywood simply in one day. The glue turned didn't survive 100+ degree heat.
The Result: Once we have all the data, we loaded it to Tableau Public, It is a great software FREE, with some limitations. From July 20th to July 30th, it is a stretch of relatively hot summer days. Play with the dashboard filters, and draw your conclusion.
My Conclusion:
- Staring at sunrise (7 AM'ish), the temperature starts to rise. The attic temperature rises up to 42% higher than the outside temperature.
- On average, the attic goes to 130F. On extreme days, it can be as high as 140F.
- The Attic/Outside temperature ratio:
- Varies by time of the day, obviously.
- Does NOT vary much by wind speed.
- Influenced by outside weather conditions. On July 22nd, there was rain from 7 to 8 AM, causing the outside temperature failure to rise. The rain caused the attic temperature to dip as well.
Part 2: Turn on the Fan
Would the Gable Mounted Attic Fan Lower the Attic Temperature, and by how much?
Using everything we have built so far, the only other thing we need to do is to turn on the attic fan. Before that, we need to remove the cardbox that was used to seal off the gable.
We decided to do this around 7-8 AM on Saturday, July 30th, when the attic was around a comfortable 70F or so.
We decided to do this around 7-8 AM on Saturday, July 30th, when the attic was around a comfortable 70F or so.
- The morning on Saturday (7/30) was relatively cool, with cloud covering. The afternoon became sunny, but not exactly hot.
- On Sunday 7/31st, the question was raised "are you sure the fan is working"? The only way would be to climb up and take a look. We did so around 1 PM when it was hot (so the thermostat would definitely turn the fan on). It was NOT moving.
- A trip to Home Depot became necessary. A new fan was installed between 4:30 PM - 5:30 PM on the same day.
- Monday 8/1st, the morning was cool and cloudy. The PM was partly cloudy, warm but not very hot.
- Tuesday 8/2nd, Wednesday 8/3rd are both cloudy/rainy.
- Thursday 8/4th will be sunny and hot and will be a good test.
- Other hot/warm/clear days: 8/9-11
The Result: Using the same dashboard as in Part 1, this is what we see. Filter out the data between 7/31-8/3 to remove some of the bias due to weather, and early dysfunction of the fan. We can study the data on 7/30-7/31 with a limited view of the attic atmosphere when the gable is open without the fan turned on.

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