American Association for Aerosol Research - Abstract Submission

AAAR 37th Annual Conference
October 14 - October 18, 2019
Oregon Convention Center
Portland, Oregon, USA

Abstract View


Spatiotemporal Mapping of Ultrafine Particles in Buildings with Low-Cost Sensing Networks

DANIELLE WAGNER, Brandon E. Boor, Purdue University

     Abstract Number: 827
     Working Group: Air Quality Sensors: Low-cost != Low Complexity

Abstract
A significant fraction of human exposure to ultrafine particles (UFPs) occurs indoors. UFP number concentrations cannot be inferred from PM2.5 mass concentration data from low-cost optical particle sensors. Traditionally, UFP measurements has been dependent on expensive aerosol instrumentation. Advances in the electrical detection of UFPs has made it possible to deploy low-cost UFP sensing networks in different environments. The integration of UFP sensing networks with building systems provides an unique opportunity to determine optimal building ventilation and filtration control strategies to reduce occupant UFP exposures. The objective of this study to investigate spatiotemporal trends in UFP concentrations throughout an office building and its HVAC system through deployment of a low-cost UFP sensing network.

An eight-month measurement campaign was performed at the Herrick Living Laboratories at Purdue University, which are four modern open-plan offices with precisely controlled HVAC systems. A distributed UFP sensing network was established in an office and HVAC system with four portable electrical particle charging (EPC)-based UFP sensors. Sensing nodes included: indoor air (IA), outdoor air duct (OA), supply air duct: pre-filter (SAPR), and supply air duct: post-filter (SAPO). The EPC-based UFP sensors measured total particle number and surface area concentrations from 10 to 2,500 nm at one-second time-resolution via sensitive electrometers and were calibrated against a water-based condensation particle counter. A state-of-the-art building automation system monitored and controlled the HVAC system. Variable ventilation modes were implemented to evaluate the response of the UFP sensing network to dynamically changing conditions.

The creation of a building-scale low-cost UFP sensing network identified significant spatiotemporal trends in UFP number and surface area concentrations in an occupied office and its HVAC system. Temporal patterns in UFPs at all four nodes were strongly influenced by ambient air pollution, indoor sources, and ventilation mode. The relative magnitude of UFPs at the IA and OA nodes varied depending on the strength of indoor and outdoor UFP sources. SAPR remained > SAPO, providing insight into in situ UFP removal via HVAC filtration. The UFP data will be integrated with material balance models to infer time-dependent UFP source and loss processes, as well as daily-integrated occupant exposures and I/O ratios. This pilot study can inform the development of real-time UFP-based ventilation control for commercial buildings.