Event Date
Time: 8:00 am PT - 10:00 am PT
Description: The connection between Indoor air and long-term human health has been well established and accepted in the scientific community. The on-going pandemic has, however, brought to fore another dimension of indoor air - its role in disease transmission and public health. To counter indoor transmission of COVID-19, one of the important recommendations of agencies such as ASHRAE and CDC is to increase ventilation rates and decrease particle concentrations in indoor spaces. With the emergence of low-cost gas and particulate sensors, these indoor air properties can be studied and controlled with resolution not possible before. In this series of presentations by experts from academia and industry, we will explore how sensors can help improve our understanding of indoor air, ventilation, and health.
Moderated By: Suresh Dhaniyala, Clarkson University & R. Subramanian, QEERI / OSU-Efluve
Sponsored by: TSI Incorporated
Presenters:
Andy May, Ohio State University
Lisa Wang, University of Colorado
Jeff Siegel, University of Toronto
Suresh Dhaniyala, Clarkson University
Presentation Abstracts
Consumer-grade indoor air quality sensors: Limitations of standards and ventilation measurements
Consumer-grade indoor air quality sensors have experienced a rapidly growing market due in part to greater consumer awareness related to the COVID-19 pandemic. Laboratory testing and verification of these sensor types is still maturing. In the next year ASTM will release two new standards test methods for evaluating indoor consumer-grade PM2.5 and CO2 sensors. Widespread adoption of these standards will improve marketplace equity, but remaining technical issues mean that consumers and regulatory agencies should not blindly accept sensor readings. In addition, consumers are increasingly using CO2 sensors to gain knowledge about ventilation of indoor environments like classrooms as a result of pandemic related concerns. Using CO2concentrations as a human emission surrogate can be insightful, but also challenging to do accurately given the wide range of building layouts and HVAC systems that can influence results. This talk will address some of the issues related to verification of consumer-grade indoor air quality sensors and their use in ventilation evaluations. (PDF Presentation)
Evaluation of Low-Cost Particle Sensors for Use in Indoor Air Quality Monitoring and Smart Building Systems
Andy May, Assistant Professor, Ohio State University
The development of low-cost particle sensors has made the measurement of airborne particulate matter more accessible to the greater public. However, the majority of the scientific research focusing on these devices has focused on outdoor environments, even though most humans spend roughly 90% of their time indoors. In this project, we describe a project that was designed to better understand how these sensors perform in buildings, where they may encounter different sources or environmental conditions than in the outdoor environment. We will demonstrate that the majority of these sensors may have the potential to activate on-demand air cleaners. We will present results from a market survey to understand what capabilities low-cost particle sensors have with respect to building communication. We will conclude with potential challenges for the use of these low-cost sensors in building ventilation control. (PDF Presentation)
Investigating the air quality, health, and wellbeing effects of electrification in homes
Lisa Wang, University of Colorado
Natural gas was introduced to the United States the early and mid-1800s after gas manufactured from coal was first used to light the streets in Baltimore, Maryland in 1816. Natural gas has gained popularity since then, becoming a common form of heating fuel in residential homes in the 20th century along with propane and heating oil. In recent years, indoor electrification has gained popularity as a potential solution to mitigate climate change. While a transition from fossil fuels indoors may impact climate change in the long run, our hypothesis predicts that this transition will also present significant influence on the air quality in indoor environments, subsequently impacting health, and wellbeing of individuals. We deployed low cost sensors which measures PM2.5, VOC, CO, NO2, PM10 within 12 homes in the City of Boulder. Preliminary data shows that homes which are electrified may have less indoor air pollutants than those which do not. (PDF Presentation)
What did we learn from deploying low-cost particle monitors in 20 homes?
Jeff Siegel, University of Toronto
Description: We deployed low-cost optical monitors that measured the particle concentration in two bins (<2.5 µm, <0.5 µm) every hour for a year in 20 Toronto homes. Major findings include 1) indoor particle concentrations followed the same pattern as outdoor concentrations, 2) the homes had particle sources that were active from 30-50% of the time, 3) the level of filtration in the home (MERV 8-MERV 14) did not a make difference in particle concentrations likely owing to the small HVAC runtimes in these homes, and 4) some homes had distinct and large particle sources including an essential oil diffuser (Site 20) and home renovations (Site 12) that dominated their indoor concentrations. Machine learning models applied to the data offer some predictive ability that could be used for filtration control and this suggest potential future applications for low-cost monitors. (PDF Presentation)
Low-cost sensors to map the impact of ventilation in a room.
Suresh Dhaniyala, Clarkson University
The on-going COVID-19 pandemic has highlighted the role of indoor spaces in driving airborne disease transmission. Human activities such as breathing, talking, coughing and sneezing typically result in emission of particles ranging in size from 500 nm to more than 10 µm. In indoor spaces, the concentrations of these particles can accumulate over time, with the extent of the accumulation dependent on the ventilation rate. Models predicting the fate and transport of particles in built environments typically assume a fully-mixed space, i.e. the concentrations in the entire indoor space is uniform. Under this assumption, social distancing would not be possible for individuals in a room. Over summer of 2020, we deployed a high density of low-cost sensors to determine if the assumption of fully-mixed room was valid. In this presentation, I will discuss our experimental methodology, results obtained, and lessons learned about social distancing in a room. (PDF Presentation)