I am a new user, so first of all I want to say hi to everyone!
A few weeks ago I launched two smog sensors: one with a dryer for high humidity conditions, the second one without a dryer. I want to collect measurements to try to replace the heater with the software solution (mainly I want to test machine learning).
I am looking for datasets with the same solution (two sensors, with- and without dryer) to compare results and extend my own dataset, which won’t have enough data until next year. Maybe someone has such a set and can share it or knows where to find them? I have seen a few publications on Researchgate, but the data are nowhere to be found and contact with the authors is difficult.
Thanks for your help!
We have just set up a heated smog sensor and have two of the Nettigo unheated kits that are produced specifically for the Sensor Community. All three are co-located. We are noticing a variation between all three SDS011s. I have yet to analyse the data fully to determine if it is more than the 5% that is expected. Are you running the unheated smog sensor with the Nettigo board? Our data from the SDS011 on the Nettigo heated system reads lower than anticipated even at low humidity. The data is interesting and I shall post more in this forum later. There are quite a few scientific papers out there I particularly like Laquai et al https://www.researchgate.net/publication/351245900_Comparison_of_a_Computational_Method_for_Correcting_the_Humidity_Influence_with_the_Use_of_a_Low-Cost_Aerosol_Dryer_on_a_SDS011_Low-Cost_PM-Sensor
They discuss the need for a calibration with a reference sensor and to check the humidity of the particle chamber. I don’t know if this fits with your machine learning but it seems that heating isn’t the full solution to the inaccuracies at high humidity, but it could be a start .
I hope this is helpful.
Thanks for your reply. My smog sensors are Nettigo Air Monitor with slight changes and own software. SDS011 sensors reading are indeed different even at low humidity but the difference is probably small enough.
I know the publication by Mr Laquai and Ms Kroseberg, also I was looking for a contact and dataset of twin-SDS011 box, but I have no information on this
From the paper; I am not sure if the twin system was run for a very long time. You could contact the lead for the group in Stuttgart (https://www.ifk.uni-stuttgart.de/en/institute/team/Vogt-00002/.)
I recently posted here our preliminary results from our three sensors and, unfortunately for us, the variation between the sensors is quite large (looks like about 40%) this should be sorted out with a calibration factor. However, we do not have a reference system so I am assuming an average of the three (below 70% humidity) gives the most accurate value of actual PM2.5.
Clearly, like you we are just starting out with the heated system but we would be happy to share our data with you if it would be helpful. Perhaps check out my last post first as our information might not be suitable for your purposes.
Thank you for the tip to write to Dr.-Ing. Vogt. He gave me the contact to the author of the publication, but to this day I have not received an answer. So I will wait until next year and just use my own dataset.
I also noticed differences in humidity measurement between both SHT35 sensors. Over 80% relative humidity the difference is even about 5 percent points. I am considering whether to add another module with the HYT221 and SHT35-F.
I’m really interested in your results. Comparing my unheated SDS011 & SPS30 vs the heated Nettigo SDS011 and Tera NPM (internal heating) show no significant improvement of the heated devices at high humidity.
It is a shame you have not heard back yet from the author of the paper. We have been running our sensors for 2 months now. Of course it has been very dry in the U.K. but there seems to be a difference. I will post more about this in a few days.
I am not sure of your location but in the U.K. there seems to be a difference…even in the recent dry conditions.
Is the heater always on in your experiment?
No the heater only comes on when the RH% is around 70% it then cycles on and off to maintain the RH at 70%.
It is a bit complicated to explain but we have 3 sensors 73072, 53261 and 53245. 73072 is heated as I described above (it is the Nettigo heated system). They are all set up in the same location. The reading that they all give differs from each other but the heated sensor, for some reason, has a much lower value. I have taken the average of the readings from the last 2 months that were at or below 70% RH, at all of the %RH and above 70% RH. I have then calibrated the output so that all of the readings at or below 70% RH are the same. I then applied the relevant calculated calibration factor to all of the other average values for each of the sensors including the standard error. This I have plotted on the bar chart. This might not be a good method but from this chart it appears that only the data from the heated system (73072) correlate for all of the 3 %RH average values. I therefore conclude that the difference above 70%RH is significant for unheated systems.
I have the charts for the uncalibrated data if you are interested. I do intend to write these results up more fully but I hope this information helps with the conversation.
Yes, it helps a lot, thank you. It would be interesting to see what happens when the pollution goes much higher than this.
I’ll be looking forward for your write up. I also intend at some point, when I have more time, to present a case of why citizen science is important, and why the more official initiatives cannot be blindly trusted.