Evaluation of a low-cost dryer for a low-cost optical particle counter

Abstract. The use of low-cost sensors for air quality measurements has become very popular in the last few decades. Due to detrimental effects particulate matter (PM) on human health, PM like photometers and optical particle counters (OPCs) are widespread have been widely investigated. negative high relative humidity (RH) fog events mass concentration readings these types well documented. In literature, different solutions problems – correction models based Köhler theory or machine learning algorithms applied. this work, an pre-conditioning method a thermal dryer OPC is presented. This study was done two parts. first part conducted laboratory test under scenarios. one scenario, drying efficiency investigated presence fog. second experiments with hygroscopic aerosols were determine which extent reverts growth particles. study, PM10 PM2.5 concentrations compared gravimetric continuous federal equivalent (FEM) instrument field. feasibility using univariate linear regression (ULR) correct data during field measurement also evaluated. Finally, comparison between dryer, without FEM real event results show that sensor at its inlet measured average 64 % 59 less particles, respectively. outcomes conditions reveal, however, excess heating instrument. demonstrated more in-depth temperature profile inside dryer. by ULR showed reduction maximum absolute error (MAE) from 4.3 µg m−3 (raw data) 2.4 (after correction). make evident increase MAE after correction: 1.9 raw 3.2 m−3. light results, could be cost-effective add-on revert effect readings. However, special care needed when designing produce similar readings, as temperatures may irreversibly change sampled evaporating most volatile species thus deliver underestimated New versions aiming should focus maintaining RH 50 avoid reaching higher than 40 ∘C system. we believe dryers promising future application citizen science, networks supplemental monitoring, epidemiological studies.