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An In-Field Assessment of the P.ALP Device in Four Different Real Working Conditions: A Performance Evaluation in Particulate Matter Monitoring.

Giacomo FantiFrancesca BorghiDavide CampagnoloSabrina RovelliAlessio CarminatiCarolina ZellinoAndrea CattaneoEmanuele CaudaAndrea SpinazzèDomenico Maria Cavallo
Published in: Toxics (2024)
This study aimed to assess the performance, in terms of precision and accuracy, of a prototype (called "P.ALP"-Ph.D. Air Quality Low-cost Project) developed for monitoring PM 2.5 concentration levels. Four prototypes were co-located with reference instrumentation in four different microenvironments simulating real-world and working conditions, namely (i) office, (ii) home, (iii) outdoor, and (iv) occupational environments. The devices were evaluated for a total of 20 monitoring days (approximately 168 h) under a wide range of PM 2.5 concentrations. The performances of the prototypes (based on the light-scattering working principle) were tested through different statistical methods. After the data acquisition and data cleaning processes, a linear regression analysis was performed to assess the precision (by comparing all possible pairs of devices) and the accuracy (by comparing the prototypes against the reference instrumentation) of the P.ALP. Moreover, the United States Environmental Protection Agency (US EPA) criteria were applied to assess the possible usage of this instrumentation, and to evaluate the eventual error trends of the P.ALP in the data storage process, Bland-Altman plots were also adopted. The outcomes of this study underlined that the P.ALP performed differently depending on the microenvironment in which it was tested and, consequently, on the PM 2.5 concentrations. The device can monitor PM 2.5 variations with acceptable results, but the performance cannot be considered satisfactory at extremely low and remarkably high PM 2.5 concentrations. Thanks to modular components and open-source software, the tested device has the potential to be customized and adapted to better fit specific study design needs, but it must be implemented with ad hoc calibration factors depending on the application before being used in field.
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