Hygroscopic properties of particulate matter and effects of their interactions with weather on visibility
Wan-Sik Won, Rosy Oh, Woojoo Lee, SungKwan Ku, Pei‐Chen Su, Yong‐Jin Yoon
Abstract
Abstract The hygroscopic property of particulate matter (PM) influencing light scattering and absorption is vital for determining visibility and accurate sensing of PM using a low-cost sensor. In this study, we examined the hygroscopic properties of coarse PM (CPM) and fine PM (FPM; PM 2.5 ) and the effects of their interactions with weather factors on visibility. A censored regression model was built to investigate the relationships between CPM and PM 2.5 concentrations and weather observations. Based on the observed and modeled visibility, we computed the optical hygroscopic growth factor, $$f\left( {RH} \right)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>f</mml:mi> <mml:mfenced> <mml:mrow> <mml:mi>RH</mml:mi> </mml:mrow> </mml:mfenced> </mml:mrow> </mml:math> , and the hygroscopic mass growth, $$GM_{VIS}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>G</mml:mi> <mml:msub> <mml:mi>M</mml:mi> <mml:mrow> <mml:mi>VIS</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , which were applied to PM 2.5 field measurement using a low-cost PM sensor in two different regions. The results revealed that the CPM and PM 2.5 concentrations negatively affect visibility according to the weather type, with substantial modulation of the interaction between the relative humidity (RH) and PM 2.5 . The modeled $$f\left( {RH} \right)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>f</mml:mi> <mml:mfenced> <mml:mrow> <mml:mi>RH</mml:mi> </mml:mrow> </mml:mfenced> </mml:mrow> </mml:math> agreed well with the observed $$f\left( {RH} \right)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>f</mml:mi> <mml:mfenced> <mml:mrow> <mml:mi>RH</mml:mi> </mml:mrow> </mml:mfenced> </mml:mrow> </mml:math> in the RH range of the haze and mist. Finally, the RH-adjusted PM 2.5 concentrations based on the visibility-derived hygroscopic mass growth showed the accuracy of the low-cost PM sensor improved. These findings demonstrate that in addition to visibility prediction, relationships between PMs and meteorological variables influence light scattering PM sensing.