Simulating indoor concentrations of NO2 and PM2.5 in multi-family housing for use in health-based intervention modeling

摘要

Residents of low-income multi-family housing can have elevated exposures to multiple environmental pollutants known to influence asthma. Simulation models can characterize the health implications of changing indoor concentrations, but quantifying the influence of interventions on concentrations is challenging given complex airflow and source characteristics. In this study, we simulated concentrations in a prototype multi-family building using CONTAM, a multi-zone airflow and contaminant transport program. Contaminants modeled included PM2.5 and NO2, and parameters included stove use, presence and operability of exhaust fans, smoking, unit level, and building leakiness. We developed regression models to explain variability in CONTAM outputs for individual sources, in a manner that could be utilized in simulation modeling of health outcomes. To evaluate our models, we generated a database of 1000 simulated households with characteristics consistent with Boston public housing developments and residents, and compared the predicted levels of NO2 and PM2.5 and their correlates with the literature. Our analyses demonstrated that CONTAM outputs could be readily explained by available parameters (R² between 0.89 and 0.98 across models), but that one-compartment box models would mischaracterize concentrations and source contributions. Our study quantifies the key drivers for indoor concentrations in multi-family housing and helps to identify opportunities for interventions.