The
integration of Internet of Things (IoT)-enabled sensors and
building energy management systems (BEMS) into smart buildings offers
a platform for real-time monitoring of myriad factors that shape indoor
air quality. This study explores the application of building energy
and smart thermostat data to evaluate indoor ultrafine particle dynamics
(UFP, diameter ≤ 100 nm). A new framework is developed whereby
a cloud-based BEMS and smart thermostats are integrated with real
time UFP sensing and a material balance model to characterize UFP
source and loss processes. The data-driven framework was evaluated
through a field campaign conducted in an occupied net-zero energy
buildingthe Purdue Retrofit Net-zero: Energy, Water, and Waste
(ReNEWW) House. Indoor UFP source events were identified through time-resolved
electrical kitchen appliance energy use profiles derived from BEMS
data. This enabled determination of kitchen appliance-resolved UFP
source rates and time-averaged concentrations and size distributions.
BEMS and smart thermostat data were used to identify the operational
mode and runtime profiles of the air handling unit and energy recovery
ventilator, from which UFP source and loss rates were estimated for
each mode. The framework demonstrates that equipment-level energy
use data can be used to understand how occupant activities and building
systems affect indoor air quality.