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First in-Lab Testing of a Cost-Effective Prototype for PM 2.5 Monitoring: The P.ALP Assessment.

Authors :
Fanti, Giacomo
Borghi, Francesca
Wolfe, Cody
Campagnolo, Davide
Patts, Justin
Cattaneo, Andrea
Spinazzè, Andrea
Cauda, Emanuele
Cavallo, Domenico Maria
Source :
Sensors (14248220); Sep2024, Vol. 24 Issue 18, p5915, 17p
Publication Year :
2024

Abstract

The goal of the present research was to assess, under controlled laboratory conditions, the accuracy and precision of a prototype device (named 'P.ALP': Ph.D. Air-quality Low-cost Project) developed for PM<subscript>2.5</subscript> concentration level monitoring. Indeed, this study follows a complementary manuscript (previously published) focusing on the in-field evaluation of the device's performance. Four P.ALP prototypes were co-located with the reference instrument in a calm-air aerosol chamber at the NIOSH laboratories in Pittsburgh, PA (USA), used by the Center for Direct Reading and Sensor Technologies. The devices were tested for 10 monitoring days under several exposure conditions. To evaluate the performance of the prototypes, different approaches were employed. After the data from the devices were stored and prepared for analysis, to assess the accuracy (comparing the reference instrument with the prototypes) and the precision (comparing all the possible pairs of devices) of the P.ALPs, linear regression analysis was performed. Moreover, to find out the applicability field of this device, the US EPA's suggested criteria were adopted, and to assess error trends of the prototype in the process of data acquisition, Bland–Altman plots were built. The findings show that, by introducing ad hoc calibration factors, the P.ALP's performance needs to be further implemented, but the device can monitor the concentration trend variations with satisfying accuracy. Overall, the P.ALP can be involved in and adapted to a wide range of applications because of the inexpensive nature of the components, the small dimensions, and the high data storage capacity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
18
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
179964579
Full Text :
https://doi.org/10.3390/s24185915