Multivariable Determinants of Indoor PM2.5 and Infiltration Factors in 48 Residential Buildings Across Eight Northern Chinese Cities: A Seasonal Monitoring and Linear Mixed-Effects Modelling Study

Abstract

Indoor exposure to fine particulate matter (PM2.5) is a major environmental-health concern in Northern China, where severe ambient pollution, coal-based district heating and diverse residential building stocks coexist. Previous studies have been constrained by small numbers of independent residences, limited geographic coverage, and predominantly pairwise (bivariate) analyses. This study presents a seasonal monitoring campaign covering 48 residences across eight Northern Chinese cities. Paired indoor and outdoor PM2.5 was measured at 5 min intervals and aggregated to 31,094 valid hourly observations (from 32,256 scheduled hourly slots after exclusion of 1162 h with missing or invalid 5 min readings) over seven consecutive days in four seasons, alongside building, behavioural and meteorological covariates. Because repeated hourly measurements are clustered within residences, the primary analysis is a linear mixed-effects model (LMM) with a residence-level random intercept and a first-order autoregressive residual structure (marginal R2 = 0.71; conditional R2 = 0.91; intra-class correlation = 0.34), supported by ordinary-least-squares (OLS) models with CR2 finite-cluster-robust standard errors and a daily average sensitivity analysis. Adjusted LMM coefficients indicate that outdoor PM2.5 (β = 0.872, p < 0.001), window-open fraction (β = 0.548, p < 0.001) and cooking events (β = 0.046, p < 0.001) were positively, and air-purifier operation (purifier-on fraction β = −0.902, p < 0.001) was negatively, associated with indoor PM2.5; continuous purifier operation was associated with 59.4% lower indoor PM2.5 (an observational association, not a causal effect). Building-level infiltration factors (F_inf) averaged 0.28 ± 0.15. Estimated outdoor contributions to indoor PM2.5 ranged from 54.8% to 66.3% across an assumed penetration factor of p = 0.6–1.0 (60.7% at p = 0.8), peaking in the heating season. The mass-balance analysis estimated a median deposition rate of 0.53 h−1 and a median air change rate of 0.52 h−1 (window-open periods > 2 h−1); these are model-derived, not directly measured quantities. These findings provide multivariable, cluster-aware evidence for envelope airtightness, informed window operation and correct air-purifier use to reduce residential PM2.5 exposure in Northern China.