Abstract
The concerns related to particulate matter’s health effects alongside the increasing demands from citizens for more participatory, timely, and diffused air quality monitoring actions have resulted in increasing scientific and industrial interest in low-cost particulate matter sensors (LCPMS). In the present paper, we discuss 50 LCPMS models, a number that is particularly meaningful when compared to the much smaller number of models described in other recent reviews on the same topic. After illustrating the basic definitions related to particulate matter (PM) and its measurements according to international regulations, the device’s operating principle is presented, focusing on a discussion of the several characterization methodologies proposed by various research groups, both in the lab and in the field, along with their possible limitations. We present an extensive review of the LCPMS currently available on the market, their electronic characteristics, and their applications in published literature and from specific tests. Most of the reviewed LCPMS can accurately monitor PM changes in the environment and exhibit good performances with accuracy that, in some conditions, can reach R2 values up to 0.99. However, such results strongly depend on whether the device is calibrated or not (using a reference method) in the operative environment; if not, R2 values lower than 0.5 are observed.
Highlights
The impact of anthropic activities on environmental integrity and their deleterious consequences on human health have pushed more and more citizens, all over the world, to organize and become informed about the quality of the air they breathe; such a change in social attitudes has been greatly accelerated by the internet’s diffusion [1,2]
For PM2.5, the results indicate that both random forest (RF) and feed forward neural network (FFNN) improved the correlation coefficient from R = 0.53 to R = 0.63 compared to the best coefficient achieved with basic calibration
The research on the health effects of particulate matter has focused on lower particle size fractions (i.e.,
Summary
The impact of anthropic activities on environmental integrity and their deleterious consequences on human health have pushed more and more citizens, all over the world, to organize and become informed about the quality of the air they breathe; such a change in social attitudes has been greatly accelerated by the internet’s diffusion [1,2]. The promising results observed far have fostered intense efforts to define the regulatory frame for these nodes, primarily the specifications these nodes have to satisfy to ensure proper data quality objectives (DQO) and to what extent the data produced can be effectively used to improve the RS monitoring network and respond to citizens’ demands [22,23,24,25,26,27] Such low-cost nodes rely on solid-state chemical sensors for gaseous air pollution monitoring, a class of electronic devices that has been investigated and developed since the 1960s [28,29,30]; these sensors use relatively less popular low-cost PM sensors (LCPMS). Outdoor air quality monitoring Emissions monitoring Construction site monitoring Mining site monitoring Port and bulk handling terminals Fence line monitoring Brownfield developments IoT hardware intelligence Checking pollution “hotspots” Personal exposure monitoring
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