Optimal Monitoring Designs of Indoor Fine Particulate Matter for Assessing Long‐Term Health Effects

Health risks associated with ambient fine particulate matter (PM 2.5 ) are well known; however, indoor exposure remains understudied. Although most people spend substantial time indoors, few studies have examined the health effects of indoor PM 2.5 owing to limited monitoring data. Even with the available data, monitoring is often limited to short periods because of financial and logistical constraints, hindering long‐term exposure assessment. To address these limitations, we leveraged our extended indoor PM 2.5 monitoring campaign to develop an optimal monitoring design that provides representative annual‐average concentrations with minimal effort. Real‐time PM 2.5 concentrations were collected in the homes of 130 participants enrolled in a Korean idiopathic pulmonary fibrosis cohort between 2021 and 2023. Our investigation included 27 participants who measured indoor PM 2.5 for at least 18 h over 4 days in each of the four seasons, constituting the complete monitoring design. To identify the optimal design, we created temporally reduced designs by selecting fewer seasons, days, and hours and compared the annual‐average concentrations of each subset with those from the complete design using the root mean square error (RMSE). Designs incorporating two mild or extreme seasons (spring–fall or summer–winter) showed lower RMSEs (3.46) compared with those from the other two‐season designs (6.18–8.88), one‐season designs (7.70–13.01), and three‐season designs (2.57–4.39). Although fewer‐day designs showed generally similar RMSEs, 18‐h designs yielded smaller RMSEs than 6‐h or 12‐h designs. Our findings suggest that indoor monitoring campaigns incorporating at least 18 h of sampling on any given day in two mild or extreme seasons can achieve representative long‐term indoor PM 2.5 concentrations in susceptible populations.