Quadratic-Baseline Partitioning of Indoor PM$_{2.5}$ Using a Low-Cost Optical Sensor During a Facade Retrofit Case Study

A quadratic-baseline algorithm was developed to partition indoor particulate matter (PM$_{2.5}$) sources using data from a single low-cost sensor without outdoor reference. A Temtop LKC–1000S+ (2nd generation) optical particle counter ($R^{2} > 0.90$ versus Federal Equivalent Method (FEM) (U.S. EPA designation) GRIMM Aerosol Technik) was deployed for 48 days during a facade retrofit. The algorithm reproduced background periods with a mean absolute error of 2.3 µg m$^{-3}$ and resolved daily PM$_{2.5}$ dose shares for facade work, cooking, and passive accumulation (31%, 24%, and 45%). During the plastic barrier stage, the PM$_{2.5}$ baseline doubled, highlighting the tradeoff between dust shielding and background elevation. This framework enables affordable, real-time indoor air quality diagnostics in occupied retrofits. Robust baseline fitting made it possible to account for sensor limitations at low concentrations. However, the generalizability of the findings is limited by the study design (single subject, only internal measurements), which necessitates further validation with external monitoring.