Exploring the long-term performance of air purifiers in removing particulate matter and formaldehyde across different residential environments

Household air purifiers are widely used to enhance indoor air quality. However, limited information exists regarding the factors that influence their long-term performance. This study investigates the impact of various residential environments on the long-term efficacy of air purifiers. We deployed household air purifiers in three distinct environments: oily fumes (Group A), non-oily fumes (Group C), and a mixture of oily and non-oily fumes (Groups B-I and B-II). The selected air filter consisted of melt-blown polypropylene and activated carbon, materials commonly employed in commercial applications. The results demonstrated that the control efficiency of air purifiers in non-oily fume environments surpassed that in oily fume environments. After 12 months of operation, particulate matter (PM) concentrations rose by 92.7% and 76.5% in oily and non-oily fume environments, respectively. This increase was primarily attributed to the loss of electrostatic attraction in the polypropylene material due to the organic matter in oily particulate matter. After operating for 1000 h, the clean air delivery rate (CADR) attenuation rates for particulate matter were 70.6%, 19.9%, 16.7%, and 12.5% in Groups A, B-I, B-II, and C, respectively. The CADR attenuation rates for formaldehyde were 80.6%, 48.4%, 38.9%, and 37.3% in the same groups. Additionally, we developed a real-time prediction model for the service life of air purifiers using data from online sensors. When operated for 12 h daily at varying PM concentrations, the filters had an expected service life of 29–97 days in non-oily fume environments and 66–220 days in oily fume environments. [Display omitted] •Long-term performances of air purifier in different residential environments were performed.•Decay rate of performance over time in different residential environments was determined.•Oily particles loading on electret filters will significantly reduce efficiency.•A real-time prediction model for service life of air purifiers was developed.