Measuring air quality with IoT sensors: compliance with mandatory quality standards (Directive 2008/50/EC)
“State environmental agency finds serious quality deficiencies at measuring station” – so read at the end of last year (rbb24). What at first reads like a damning verdict for technologically new measuring methods raises various questions when considered more comprehensively: What is the standard for the quality of an air measuring device? What quality standards must be maintained if public money is spent on them?
When additional measurements are needed, the key question is “Why is measurement actually being done?”. What is to be achieved with the data? This usually goes beyond the retrospective reporting of pollutant levels. Decision-relevant information should enable targeted measures: From protecting risk groups to regulatory requirements and technical solutions. This requires sufficient coverage and granularity, both spatially and temporally.
When it is about more than personal data collection of individuals, but about municipalities carrying out measurements to officially inform citizens, to protect or to derive measures from it, a quality that complies with binding standards (such as Directive 2008/50/EC) must be maintained. As a rule, the IoT measuring devices on the market do not achieve this requirement. Hawa Dawa is the exception here and offers reliable measurement results in accordance with the quality targets of the 39th BImSchV.
The Hawa Dawa measurement method was tested last year by TÜV Süd and the test report explicitly stated, “The quality objectives of the 39th BImSchV for the orienting measurement of nitrogen dioxide are … fulfilled.” With these high-quality IoT measuring devices, data on air quality can be established area-wide and in accordance with the applicable standards as a reliable supplement to the public measuring stations. In order to achieve this resilient standard, the measurement method must be geared towards the quality of the data at all levels: In the hardware, the calibration algorithm, and the choice of location.
In an ideal world, public measuring stations could be located everywhere, providing real-time, area-wide and hourly information on air pollution levels that meet the quality standard of “equivalent measurement”. This is not feasible due to the high costs involved. In Germany, there is ONE measuring station (for NO2) per 150,000 inhabitants. In order to ensure a high spatial coverage or to measure the air at special “points of interest”, so-called passive samplers are used, whose quality meets the standard of the so-called “reference measurement”.
The idea behind these passive collectors is that they are small tubes that collect the air pollutant NO2 over a specific period. They are then removed and subsequently evaluated in a laboratory. An average value is then obtained for the past period. Certainly, these passive collectors (also called NO2 collectors) close – at least for one air pollutant (NO2) – the gap in the network of public measuring stations. Nevertheless, due to their methodology, they are not suitable to detect patterns over time or critical situations in a timely manner or to identify causes taking into account additional influencing factors.
So-called IoT measuring devices rely on modern technology here but often fail because of the reliability of the data. Nevertheless, one should not ignore how a whole field of manufacturers with the most diverse quality requirements is establishing itself here: From simple devices for typical Citizen Science projects with a clear focus on low cost to devices whose measurement method is independently verified and – like the passive collectors – meet the quality standard of “reference measurement” or “orienting measurement”. So there is no one IOT measuring device for which a uniform rating can be given.
Responsible parties must consider the cost and the demonstrated quality of the additional measurement devices if obtaining reliable air quality information is the goal.