<p>Research on net-zero energy buildings (NZEBs) has been
largely centered around improving building energy performance, while little
attention has been given to indoor air quality. A critically important class of
indoor air pollutants are nanoaerosols – airborne particulate matter smaller
than 100 nm in size. Nanoaerosols
penetrate deep into the human respiratory system and are associated with
deleterious toxicological and human health outcomes. An important step towards
improving indoor air quality in NZEBs is understanding how occupants, their
activities, and building systems affect the emissions and fate of nanoaerosols. New developments in smart energy monitoring
systems and smart thermostats offer a unique opportunity to track occupant
activity patterns and the operational status of residential HVAC systems. In this study, we conducted a one-month field
campaign in an occupied residential NZEB, the Purdue ReNEWW House, to explore
how energy use profiles and smart thermostat data can be used to characterize
indoor nanoaerosol dynamics. A Scanning Mobility Particle Sizer and Optical
Particle Sizer were used to measure indoor aerosol concentrations and size
distributions from 10 to 10,000 nm. AC
current sensors were used to monitor electricity consumption of kitchen
appliances (cooktop, oven, toaster, microwave, kitchen hood), the air handling
unit (AHU), and the energy recovery ventilator (ERV). Two Ecobee smart thermostats informed the
fractional amount of supply airflow directed to the basement and main floor. The nanoaerosol concentrations and energy use
profiles were integrated with an aerosol physics-based material balance model to
quantify nanoaerosol source and loss processes.
Cooking activities were found to dominate the emissions of indoor nanoaerosols,
often elevating indoor nanoaerosol concentrations beyond 10<sup>4</sup> cm<sup>-3</sup>. The emission rates for different
cooking appliances varied from 10<sup>11</sup> h<sup>-1</sup> to 10<sup>14</sup>
h<sup>-1</sup>. Loss rates were found to be significantly different between AHU/ERV
off and on conditions, with median loss rates of 1.43 h<sup>-1</sup> to 3.68 h<sup>-1</sup>, respectively. Probability density
functions of the source and loss rates for different scenarios will be used in
Monte Carlo simulations to predict indoor nanoaerosol concentrations in NZEBs using
only energy consumption and smart thermostat data.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/7428872 |
| Date | 16 January 2019 |
| Creators | Jinglin Jiang (5930687) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Investigating_How_Energy_Use_Patterns_Shape_Indoor_Nanoaerosol_Dynamics_in_a_Net-Zero_Energy_House/7428872 |
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