‘Hollandse Luchten’ (Dutch Skies) is a citizens science project that involves citizens in measuring air quality in their environment in the Province of North Holland.
above image: Waag CC0
Hi all, I am Sylke and I work at Waag Futurelab on the Hollandse Luchten project. Let me know if you have any questions about it!
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Dear @sylke
this is very kind of you.
i) Could you detail the 2 different sensors that you have been using with citizens throughout Hollandse Luchten? How do these sensors differ? Where can they be purchased?
ii) How have you been guiding citizens to use the sensors and make sense of the gathered data?
iii) How many sensors are needed to make for meaningful contrasted data? 
e.g. for a citizens use case like this that @robert.axelsson is in touch with.
Hi Sebastian,
Thank you for your questions.
i) In the first phase of Hollandse Luchten we worked with a DIY sensor kit, which we called the HoLu-kit. The PM-sensor used in the kit was the SDS011 sensor. We also used temperature and humidity sensors and in an extended kit NO2, however the extended kits all broke down within a year. Generally, the PM-measurements appeared too sensitive to humidity, even after calibration. The HoLu-kit is not commercially available, but we recorded the building process on GitHub: GitHub - waagsociety/holu-kit-20: Hollandse Luchten sensor kit
Since November 2022, we are using the SODAQ AIR sensor kit; a third iteration of the ‘Snifferbike’ sensor produced by the company SODAQ. This sensorkit uses a Sensirion PM-sensor which has been found to give more reliable data, for which no calibration is necessary. Nevertheless, we found significant deviation in the data, especially in winter, so we are working on a correction for the data.
SODAQ AIR sensors can be purchased through SODAQ but only in bulk: SODAQ AIR - SODAQ - Reimagining Air Quality Monitoring
ii) For this year we designated a measuring period of 12 months, starting in November 2022 and running until November 2023. We chose a period of a year to account for enough different weather types and wind directions to get a complete data set. At the start of the measuring period, we asked people to come up with measuring questions and each measuring group to make a measuring plan with specific locations in order to best be able to answer the measuring questions. We held an initial data analysis evening after three months and we are now working towards the final data analysis sessions for each measuring group, by making material available for people to conduct their own data analysis and answer their measuring questions. We are working on capturing this method for open data analysis in a shareable format.
iii) It depends on the size of the area you are measuring, but we have found in small towns or neighbourhoods that spreading around 10 - 15 sensors yields an interesting data set. However, as we haven’t done the final data analysis, we haven’t been able to say anything conclusive or use the data for specific means. I would recommend that you look into other use cases as well for this.
If you are measuring a specific source, you would need at least four sensors to spread around it, each in every wind direction (North, East, South, West) in order to determine whether pollution is coming from the selected source or from further afield. This is especially relevant when measuring PM2,5, as background levels can be high of themselves, making it more difficult to determine the source.
Hopefully that helps and let me know if you have any further questions. You can also take a look at the Hollandse Luchten website or the Dutch Samen Meten forum for citizen science (with a big group focusing on air quality).
Best
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Sincere thanks to you Sylke. Above guiding information by @sylke may interest you @lars.gidhagen @robert.axelsson regarding the Swedish citizen group in Kolsva that you are in touch with.
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Many thanks Silke for sharing your experiences on different PM sensors, this very needed since there are many manufactures on the market! I also saw that your Dutch Samen meten and RIVM web pages provide more info on different PM low-cost sensors.
Concerning the third item, the use of local and high quality meteorological data can facilitate the use of fewer PM sensors - even less than 4 - in order to locate the dominant sources. However, the complexity of the domain (buildings etc) is critical for the interpretation of monitored data.
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