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How Well Do Low-Cost Particle Sensors Monitor IAQ?

How Well Do Low-Cost Particle Sensors Monitor IAQ?

From ASHRAE Journal Newsletter, April 28, 2020

As consumer-grade, low-cost particle sensors enter the market, they could provide a way to inexpensively monitor indoor air quality and, eventually, control building systems. A study evaluated several of these sensors as part of ASHRAE Research Project 1756, Evaluation of Particle Sensors for Indoor Air Quality Monitoring and Smart Building Systems.

Recently, the researchers published an article detailing their study in Science and Technology for the Built Environment. The article, “Response of eight low-cost particle sensors and consumer devices to typical indoor emission events in a real home (ASHRAE 1756-RP),” addresses how the research team evaluated the performance of the best-performing, low-cost sensors.

Researcher Jordan Clark, Ph.D., Member ASHRAE, an assistant professor in sustainable buildings at Ohio State University, discusses the research.

1. What is the significance of this research?

Dozens of models of low-cost airborne particle sensors are now commercially available, and most offer some useful information about the amount and type of airborne particulate matter in a given environment. Many in the buildings community are looking forward to the time when such sensors are ubiquitous in smart buildings and used to characterize and control indoor environments. However, it is widely understood that performance varies substantially among the various models and among different applications in which they may be used.

This research sought to: examine the performance of several commercially available low-cost particle sensors; identify the variables that affect performance of these sensors and the needs of various applications in smart buildings; and develop methods for characterizing sensor performance that are useful for building designers, operators and occupants.

2. Why is it important to explore this topic now?

The confluence of advances in data analytics, sensor technology and computational power is paving the way for “smart” control of systems that were previously operated based on prescriptive rules or best practices. It is also making possible widespread monitoring that can teach us things we would not have had access to before.

The buildings field is no exception. Smart ventilation and air cleaning, automated maintenance, smart monitoring of indoor environments and source characterization are all being piloted and will likely become standard practice in the future. Many consumers are already using low-cost air quality monitors in their homes, and researchers are deploying them to study environmental systems. In order to make this paradigm shift, we need to understand the sensors at the heart of these strategies and ensure their performance.

3. What lessons, facts and/or guidance can an engineer working in the field take away from this research?

We learned a lot about the performance of these sensors over the course of this two-year project. In general, all sensors tested were able to give a binary indication of typical particle emission events in homes they were subjected to, and to return to baseline operation after the event. However, comparison of continuous low-cost sensor outputs with those of research-grade equipment showed performance varied widely among models and sometimes among different instances of the same model.

Some models tracked research-grade equipment tightly, and some gave signals that were only weakly correlated to research-grade equipment. The time over which these signals are averaged dramatically affected apparent performance with a time scale of at least 10 minutes being recommended and averaging times of an hour needed to ensure correlation to research-grade instruments in real environments for most sensors.

Sensors also have a fairly well-defined domain of applicability. Each sensor showed distinct lower and upper concentration bounds within which it was effective, and some showed reduced performance at very high humidity, although no significant temperature effects were measured. Most sensors perform differently when subjected to particles of different size, with particles in the 1.0–2.5 µm range giving the best performance. The size resolution of the sensor seemed to correlate well with its accuracy.

4. How can this research further the industry's knowledge on this topic?

Besides providing performance data for several models of low-cost particle sensors, both in laboratory and field tests, this research also identified several considerations that need to be taken into account when characterizing the performance of one of these sensors, and methods for doing so. These include establishment of a functional concentration range, identification of size-dependent performance, sensitivity to averaging times of sensor signals and other metrics.

5. Were there any surprises or unforeseen challenges for you when preparing this research?

We were pleasantly surprised by the performance of the best-performing low-cost sensors. They gave information in typical environments, and when subjected to typical emission events, that can be very useful in monitoring and controlling buildings. Some models were even giving useful information for particles as small as 200 nm.

We were also surprised at the degree to which post-processing of sensor signals affected apparent performance. For example, increasing the averaging time of low-cost sensor signals from a few seconds to 10 minutes dramatically improved correlation to research-grade instruments.

As far as challenges in research, it is often difficult to identify the variable that is causing a deviation in performance of these sensors. For example, the particle size and composition work in concert with ambient humidity to affect the sensor performance. Teasing out the individual contribution of each of these variables is quite a challenge, which we met to some degree by subjecting sensors to monodisperse particles and systematically varying environmental conditions.