Air quality measurement using optical sensors
Optical sensors are often used in air measuring devices to detect certain gases or particles in the air. This is achieved either via infrared measurement or fluorescence measurement.
These measured values can be determined using optical sensors: particulates (PM₁ - PM₂,₅ - PM₁₀), carbon dioxide (CO₂), oxygen (O₂), methane (CH₄), nitrous oxide, dinitrogen monoxide) (N₂O).
Air analysis by infrared measurement
Infrared measurement uses an infrared LED and a detector, which are separated by a wall in the air measuring device and therefore never "see" each other directly. The infrared sensor (also known as an IR sensor) uses infrared light, which lies outside the visible light spectrum, to detect changes in its surroundings.
If a particle appears in the light of the LED, the detector perceives a flash and reacts to the emitted rays of the emitter (infrared LED). The detector measures the amount of reflected or emitted infrared light. The basis for this is infrared absorption. Some molecules absorb certain wavelengths of infrared radiation. The detector then determines how much light was absorbed at the specific wavelengths.
The sensor therefore counts the frequency of the light flashes. For maximum accuracy, a second measuring beam (reflection sensor) can monitor the intensity of the infrared LED, i.e. its brightness. Here, the detector measures the reflected radiation. The brighter the flashes are, the larger the respective particles are. The darker the flashes appear, the smaller the particles are. Changes in the reflected intensity therefore indicate the presence or properties of the air particles.
Analysis of air pollutants by fluorescence
Some substances can fluoresce when irradiated with light of a certain wavelength, i.e. they emit light of a different wavelength. By measuring the fluorescence intensity, the optical sensor can infer the concentration of these substances. The measured fluorescence can be used for various applications, including the detection of molecules, biomarkers, environmental pollutants or other substances. The intensity, wavelength and duration of the fluorescence provide information about the quantity, concentration or reaction kinetics of the analyzed substances.
Electrochemical sensors
Various gases can be detected and quantified using resistive sensors. For this purpose, the electrochemical sensor typically consists of three main components: a working electrode, a reference electrode and a counter electrode. The working and reference electrodes are embedded in an electrolyte that supports the ionic conductivity. When particles of the gas reach the sensor, an electrochemical reaction takes place there that is specific to the gas to be detected. This reaction changes the ion concentration in the electrolyte in the immediate vicinity of the working and reference electrodes. Whenever corresponding particles "dock " on the surface of the sensor , the substances cause a small current in the sensor - a measurable electrical signal.
The advantage of these sensor types is the individual sensitivity calibration: different electrochemical sensors are therefore specific for different gases, as the electrochemical reactions are gas-dependent. Special sensors are therefore used for the detection of carbon monoxide, sulphur dioxide, methane and other gases. The disadvantage of electrochemical sensors is a possible cross-sensitivity with other gases. This means that the respective sensors can also react to other gases and fail if they are present.
These measured values can be determined using electrochemical sensors, among other things: Sulphur dioxide (SO₂), volatile organic compounds (VOC), ammonia (NH₃), chlorine / chlorine gas (Cl₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), formaldehyde (CH₂O), hydrogen sulphide (H₂S), hydrogen (H₂).
Mold & pollen: Future air measurements with AI
To date, mould spores or pollen cannot be detected directly using an air measuring device, as they can hardly be clearly distinguished from other particles such as dust. At the moment, it is only possible to determine the conditions that promote the development of mold, such as excessive humidity and insufficient air exchange. In future, we want to change this using innovative technology. Together with Chemnitz University of Technology, air-Q is therefore researching a way to measure mold and pollen. To this end, we are further developing our sensors and looking for AI-based solutions to differentiate between particles in terms of their type and size. Artificial intelligence should enable the efficient processing and analysis of large amounts of data from various sensors and sources. By using machine learning and data analysis algorithms, we aim to identify complex patterns and correlations in the air quality data and hope to achieve more precise predictions, faster response times and improved accuracy in the detection of air pollutants.
