Oral Presentation Abstracts

Policy and Air Quality Management

Low cost PM sensors – A local air quality agency perspective

By: Lance Giles, Air Monitoring and Data Quality Coordinator, Lane Regional Air Protection Agency

Summary: Low cost sensors are now readily available for collecting PM data. These sensors are being purchased
and used by private citizens, but, is there a place for these sensors in a regulatory agency toolbox? Lane
Regional Air Protection Agency (LRAPA) has attempted to answer this question for itself. Multiple examples of use of low-cost PM sensors and data comparison will be presented.

Towards the traceability of air sensor monitoring: technology breakthrough and protocol development for air quality management applications

By: Zhi Ning, Associate Professor, The Hong Kong University of Science and Technology

Summary: With the booming needs of environmental monitoring applications, high performance sensors play an important role, and effective quality control and quality assurance (QAQC) protocols become a critical component in different applications to ensure data quality objectives meet the project needs. This talk presents the most recent technology development for low cost gas sensors with highlights on the breakthrough in eliminating the impact from ambient temperature and humidity factors, and the attempt to develop the traceability of sensor based air monitoring to match with reference analyser monitoring.  Based on the development of sensor technology, this talk will also share our experience on the lab and field protocols for applications of long term outdoor air monitoring, large scale mobile monitoring by gas sensors,  personal exposure assessment and smart law enforcement for emission control etc. 

Scaling-up Low-cost Sensor Evaluation and Network Integration: the Paris / Ile-de-France Experience

By: Sophie Moukhtar, Coordinator of International Relations, Airparif

Summary: Over the past years, the technological advancements of pollution sensors enable the development of novel networks that equip buildings, street furniture, vehicles or citizens. Nevertheless, the appropriation of the measurement by the general public does not automatically imply becoming a specialist of air quality. As such, a real risk is emerging of data privatization and disqualification of experts.

The multiplication of data sources is also a great opportunity for the evolution of air quality monitoring. Airparif end goal is to be able to channel and integrate the data generated by these diverse measurement sources within a unified monitoring framework, in the service of the collective interest. To this end, appropriate answers to the following questions need to be found: How to evaluate the reliability of these sensors? How to collect and assimilate the data in order to improve accuracy and coverage and to provide reliable local information? What is the specific contribution that these novel technologies can bring to monitoring, communication, and raising awareness?

In the absence of norms and performance standards, Airparif has developed, through its platform for open innovation – AIRLAB, an evaluation methodology based on the principle of the challenge, by coupling metrology and ergonomics criteria.

Multiple projects involving fixed, mobile, or portable low-cost sensor systems are also currently deployed by Airparif. These field experimentations allow us to draw initial insights into the potential gain obtained through sensor multiplication in terms of monitoring, personal exposure characterization, and education.

Performance Targets

Can we set performance targets for low cost sensors?

By: John Saffell, AlphaSense

Summary: Air quality (AQ) networks and personal monitors using low cost sensors are generating results at a rapidly expanding rate. But can these results be accepted as valid measurements? We can rephrase this question: do air quality sensors and sensor systems meet their performance targets?
We first review performance targets that have been set for gases, particles and VOCs. Targets can be based on national or international concentration limits, sensor technology capabilities, typical concentrations, limits of detection, or laboratory and field validation capabilities. Performance targets should also depend on the application: reference and equivalent measurements, fixed site urban networks, mobile monitoring, IAQ, personal exposure or citizen science. We consider how the total measurement error should reflect the application.
Users of low cost AQ sensors often request a performance certificate to a national or international standard; there are test standards for reference and equivalent analytical systems, but to date there are no test standards for low cost AQ sensors. CEN 264, Working Group 42 has been working since 2015 on a classification and validation performance standard for low cost gas and particle sensors. The first draft is available March 2020 and allows classification of low cost sensors from near-equivalence capability and simpler classification of citizen science AQ boxes.  EDF and ASTM in North America are also working towards standards for AQ networks. We discuss progress.
Work with UNEP over the last years in Nairobi and other LMIC locations has reminded us of other issues that must be included when considering performance targets. The sensor system alone can be tested and validated in the lab, but field validation of performance must also include siting and deployment, sensor drift and regular field validation. A final consideration is the geographical location and diurnal and seasonal patterns which strongly affect field measurement quality. 

Challenges and Opportunities for Resonator-based PM MEMS Mass Sensors

By: Igor Paprotny, University of Illinois

Summary: Recent emergence of resonator-based real-time PM mass sensing technologies based on microelectromechanical systems (MEMS) and air-microfluidics has the potential to bring real-time gravimetric PM mass sensing at a fraction of the cost of traditional bench-top air-quality instrumentation. In this work, we present the results of comprehensive testing of several different types of resonator-based MEMS PM sensors, and discuss the opportunities and several challenges that need to be overcome for the successful future adoption of this new technology. Combined with theoretical analysis we discuss some of the application-specific design trade-offs, in particular addressing the issues of data-quality, long-term stability, reliability, and cost. 

Exposure & Health

Source Characterization & Identification

Identification of high-emitting heavy-duty diesel trucks with low-cost sensors and the plume capture method 

By: Thomas Kirchstetter, Adjunct Professor, University of California, Berkeley

Summary: Low-cost air pollution sensors that are small and power conservative enable measurements in places that would be difficult with larger and higher-cost analyzers that are traditionally used in research or regulatory settings. One such application is a lower-cost system that can be widely deployed to identify high-emitting heavy-duty diesel trucks that may be disproportionately responsible for a majority of the on-road fleet's total emissions. Before such systems can be deployed, it is necessary to evaluate the limitations of low-cost sensors under these sampling conditions. In this talk, an evaluation of the performance of a variety of black carbon and carbon dioxide sensors is presented, in the application of quantifying black carbon emission factors from in-use trucks using the plume capture method. In this method, sensors are exposed to rapidly changing pollutant concentrations (i.e., concentration peaks) associated with short duration sampling of vehicle exhaust, and sensor performance may be different than it is when sampling ambient air or during calibration. When measuring short duration peaks, the mid-cost LI-COR LI-820 overstates peak concentration and thus peak area, resulting in fuel-based black carbon emission factors that are biased low. We find that there is more variability in the performance among several filter-based absorption photometer black carbon sensors than there is among several infrared absorption spectrometer carbon dioxide sensors. When identifying high-emitting trucks, the low-cost SBA-5 (PP Systems) performs about as well as the LI-7000 (LI-COR) carbon dioxide analyzer that costs 10× higher. Conversely, considerable disagreement in the classification of high-emitting trucks arises due to varying performance of black carbon sensors (Magee Scientific AE33, AethLabs MA300, and UC Berkeley ABCD).

Quantifying hydrocarbons with sensor arrays in communities near sources

By: Michael Hannigan, Professor, University of Colorado, Boulder

Summary: Oil and gas production has increased dramatically over the past decade. These production activities are often located in close proximity to human populations. Communities located adjacent to the production activities can experience concerns over the industrial activities; these concerns often include the perception that their health is being negatively impacted by airborne emissions. The air quality sensor community has developed tools to assess pollutants on the National Ambient Air Quality Standards list (O3, CO, NOx, SO2, particulate matter) but there has been less focus on hydrocarbons; however, for those communities hydrocarbon sensing is the need. Additionally, for those communities, where there are often multiple potentially impactful sources, understanding the relative importance of each source type is vital to mitigating the impacts. To assess hydrocarbon concentrations, we have explored different sensor combinations on a sensor array, different calibration algorithms, and different co-location protocols. In addition to quantifying the total non-methane hydrocarbons, we have assessed the ability to quantify subsets of hydrocarbons as well as source type contributions to the total. The results and implications of these explorations will be presented.

Inferring aerosol sources using multi-pollutant, low-cost air quality sensors 

By: David Hagan, Research Associate, Department of Civil and Environmental Engineering, MIT

Summary: Low-cost sensors offer the opportunity to measure urban air quality at a spatiotemporal scale finer than ever before. While our understanding of their performance has increased in recent years, most of these devices are still used as stand-in replacements for existing infrastructure – to monitor and report concentrations of gas- and particle-phase pollutants as time series. Considering most low-cost sensor integrations couple multiple gas-phase sensors alongside an optical particle measurement, there exists an opportunity to leverage these measurements against one another to extract potentially useful information. This work highlights the potential for using low-cost sensors to identify types and sources of aerosols via an unsupervised learning approach using data collected in Delhi, India.


Innovative Technologies and Applications

Use of portable sensors to characterize microscale street atmospheric flows

By: Aron Jazcilevich, Ph.D, Universidad Nacional Autónoma de México

Summary: Environmental atmospheric problems at street scale provide a time and space dichotomy: On one hand we have a slow-moving wind, transporting regional pollution, and on the other, the discharge of fast-changing vehicular emission flows. Street concentration fields change substantially in short periods of time and space distances, since they are subject to nearby turbulent sources. Pollution fields due to immediate vehicular sources on both sides of the road are thus poorly correlated.  This situation poses a problem for wind tunnels and Computational Fluid Dynamics (CFD) modeling, generally designed for specific flow velocities. In street level acute exposure or pollution apportioning studies, is thus necessary to obtain atmospheric flow data in the 1:1 scale. Portable real time sensors (low cost or otherwise) can be used to obtain this flow data.

Experiments using real-time laser nephelometers and sonic anemometers to obtain roadside flow data will be described. With the aid of digital filtering, detailed concentration information regarding particle and gas distributions will be presented. The fine time (in seconds) and space (in cm) scale data obtained this way provides valuable information for exposure and computational (mainly CFD) applications at street level scales. 

Using IoT to Measure Outdoor Air Quality in Africa

By: Kirah Theuri, Technologist, Code for Africa

Summary: This presentation will include a showcase of how Code for Africa is measuring outdoor air quality across major African cities using  air quality kits  assembled in their civic labs. These kits each have 2 sensors, the SDS011 Particulate Matter(PM) sensor which measures PM10 and PM2.5 (Newer kits are now using the PlanTower PMS5003 sensor which measures PM1, PM2.5 and PM10), and the DHT22 Temperature and Relative Humidity sensor. A network of over 100 sensors has already been deployed across the continent. This technology was borrowed from Code for Germany, and africanised - for instance, we modified the kits to use alternate power sources available in the continent like solar, and communication to GSM and radio in place of WiFi. The data these sensors collect is then shared on open endpoints, which are accessible to  the general public. It is mainly used by local communities to check how polluted the air is, and also by those living in areas with poor air quality to fight for action to be taken against parties contributing to the same.

Use of Networked Sensors

Using Networked Air Quality Sensors to Understand Neighborhood-Scale Differences in Particulate Matter Concentration During Pollution Episodes

By: Kerry Kelly, Assistant Professor, Chemical Engineering, University of Utah

Summary: Northern Utah periodically experiences the highest levels of fine particulate matter (PM2.5) in the nation, and the geospatially sparse regulatory monitors in this rapidly growing urban region struggle to capture neighborhood-scale differences in PM2.5 levels, in part due to this region’s complex terrain.  The rapid proliferation of low-cost air-quality sensors offers great promise for providing highly resolved air-quality measurements.  However, data quality remains a challenge, and strategies for assimilating this imperfect data are still being developed.  Here, we describe a layered framework that includes: (1) the development of a low-cost PM sensor network that incorporates the University’s own sensors, called AirU, PurpleAir data, and state regulatory measurements; (2) the laboratory and field calibration of the PM sensors; (3) the development and application of event-specific calibration factors; (4) the detection and screening of erroneous sensor data; (5) the strategies for assimilation of the data from more than 200 low-cost and state regulatory sensors using a Gaussian process model to estimate PM2.5 levels and uncertainty dynamically throughout the modeling domain; and (6) the dynamic visualization of the model to communicate PM2.5 levels to the public. The community can view the visualizations through a public-facing website, and they can freely access the sensor data through an API. Thus far, this network has generated a rich set of PM measurements, capturing several severe PM episodes resulting from persistent cold air pools, fireworks, wildfires, and dust events. The results illustrate dramatic geospatial differences in PM2.5 concentration during some of these episodes that would not have been observed from the regulatory monitors alone.  This infrastructure is currently being used by research collaborators studying environmental justice, asthma exacerbations, and simulation of wildfire plumes. 

Performance evaluation and field deployment of a large PurpleAir sensor network in India

By: Joshua Apte, Assistant Professor, University of Texas at Austin

Summary: Low-cost sensors offer the potential to fill critical air quality knowledge gaps in polluted, low-income settings. Real-world data on the long-term performance of such sensor systems under high concentrations is needed. We present here an analysis of ~ 20 months of long-term data collected using a suite of 60 PurpleAir monitors deployed to urban and rural field sites in North and South India. Large-scale colocation tests suggest that the PurpleAir has very high precision under moderately polluted Indian conditions (PM2.5 ~ 30-60 µg m-3), with very good sensor-to-sensor agreement (median R2 ~ 0.99, median slope     ~ 0.98). Co-location with MetOne BAM FRM PM2.5 monitors generally revealed superior sensor performance for 24h averages relative to hourly data. Seasonal comparisons in Delhi with BAM data indicated good performance for the PurpleAir sensor during the more polluted autumn, winter, and spring seasons (R2 ~ 0.85-0.90), with error metrics implying an ability to resolve ~ 20-30% concentration differences among distinct locations. We have deployed ~ 50 sensors to a diverse set of rural, residential, and source-oriented locations across Bangalore, India, and will present here an analysis of the spatiotemporal patterns that is facilitated by this sensor network. 

Love My Air Denver – a growing hybrid air monitoring network for many applications

By: Michael Ogletree, Air Quality Program Manager, Department of Public Health and Environment, City and County of Denver

Summary: Cities around the world are finding ways to use air sensors for a range of applications. Beginning in 2019, The City & County of Denver has been growing its air monitoring network incorporating different types of technologies from different manufacturers and agencies. This hybrid air monitoring network consists of 6 reference stations, 25+ air sensors, and 5 mid-tier instruments. Denver worked collaboratively with a private company to develop an air sensor-specific platform that allows for dynamic network calibration allowing for more accurate data from the lower cost sensors in the network.

To manage the complex network, an air management platform allows for dynamic network calibration to create accurate data from the different lower-cost sensors in the network. This hybrid network is being used a range of applications from general awareness, school interventions, traffic monitoring, and more. This presentation will focus on the technical challenges and resulting approaches that have been developed to produce reliable and accurate air sensor data. In addition, we will also address some of the other important aspects of the project include health messaging, outreach to teachers, principals, and parents.

Funding Opportunities

Engaging diverse communities to advance environmental public health with low-cost sensors

By: Liam O'Fallon, Health Science Specialist, National Institute of Environmental Health Sciences 

Summary: The National Institute of Environmental Health Sciences (NIEHS) advances biomedical research through a variety of grant mechanisms and programs in support of its mission and strategic plan. The institute has an interest in the development and use of low-cost sensors to help better understand the environmental exposures community residents face in the places they live, work, and play. This research is promoted through Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs, as well as through grant programs that bring researchers and community residents together to address local environmental health concerns. In this presentation, participants will hear about the different programs, their goals, and examples of projects that have been funded. In addition, participants will learn more about the application process at the NIH and best practices for submitting grant proposals. 

Leveraging Citizen Science and STEM Education to Diversify Program Resources

By: Calvin Cupini, Citizen Science Program Manager, Clean Air Carolina


Clean Air Carolina is a 15 year old 501(c)3 statewide organization based in Charlotte, NC connecting impacted communities with information needed to protect their health and advocate for change. The organization focuses on climate, health, and environmental justice through non-partisan programming, events, education, and research partnerships. 

The AirKeepers Citizen Science program engages students, teachers, and the general public participating in monitoring hyper-local levels of air pollution using the latest citizen science technology on the market. Clean Air Carolina is creating a community level monitoring network across the entire state of North Carolina, with a sensor host in nearly every county in North Carolina.  The expansion of this kind of work was made possible thanks to declining cost in Citizen Science tools, as well as a diverse range of funding sources. 

This presentation will cover the revenue story of the growth of the program from it’s beginning in 2016 with a multi-year foundation grant, to today with a self sustaining model of multiple funding streams. Our approach utilizes public and private funding, as well as a modular approach to funding initiatives in multiple specific pieces to increase sustainability and reduce risk.  This will include the selection strategy for finding funding we use, novel funding opportunities we’ve derived along the way, and a list of failed grants and what we’ve learned.  The goal of the presentation is to offer a fund-seeking perspective to the panel and share our experience finding funding in less common ways. 

Air Sensor Technology Applications of Relevance to Electricity and Energy Facilities

By: Stephanie Shaw, Principal Technical Leader, Electrical Power Research Institute

Summary: The recent proliferation of inexpensive chemical and physical sensors has opened many opportunities for researchers, community groups, educators and industrial facilities to monitor environmental parameters in the ambient atmosphere, within facility boundaries or in residential or commercial buildings. Sensors may offer benefits over traditional monitors that require substantial infrastructure for their support, such as lower capital investments, low power requirements, ease of deployment and operation, and ability to more densely monitor areas of interest. The Electric Power Research Institute (EPRI) has been evaluating sensors for potential use to inform electricity and energy facility operations over the past several years. The air quality applications considered ranged from detecting dust from materials handling operations at power plants, to determining the value of sensor sites for use as community benefit monitoring stations, testing the feasibility of using UAV platforms for GHG measurement at power plants and natural gas infrastructure, and assessment of indoor air quality. Other environmental sensor applications evaluated by EPRI include groundwater and geotechnical monitoring. An overview of the experimental evaluations and results will be presented, along with the overarching perspective EPRI has developed for sensor use by industrial facilities.

Returns on Information: Beliefs and Realities

By: Jessica Seddon, Global Lead, Air Quality, WRI Ross Center for Sustainable Cities

Summary: Presentation will discuss perceptions and realities about the social returns on funding for air quality sensing. It will discuss current trends in funding and suggest some areas for redirecting funding to improve the impact of investments in air quality measurement and pollution characterization. 

Youth Education & Development

Indoor Air Quality

Integration and Performance of Home Energy and IEQ Monitoring and their Relationships to Residential Air Pollution Exposures

By: Ellison Carter, Assistant Professor, Colorado State University

Summary: Increasingly, housing interventions designed to address energy inefficiency are being evaluated for their potential to achieve other indirect benefits, including reductions in exposure to air pollution through improvements to indoor air quality. Home energy efficiency upgrades have the potential to positively influence indoor air and environmental quality through multiple pathways. Yet, only a limited number of studies have been able to bring evidence to bear on these hypotheses. Several obstacles to this work include a lack of clarity or consensus around energy and environmental indicators to track and a limited understanding of how methods and tools that are low-burden to implement in a large number of homes perform over sufficient follow up periods. The proposed presentation will draw from several pilot studies designed for long-term (months) monitoring of indoor air and environmental quality indicators (e.g., PM2.5, CO2, light, noise) and residential energy use (e.g., hourly and sub-hourly energy use, disaggregated by appliance/source) at high spatial and temporal resolution among households that vary with respect to housing condition and tenure. In addition to reporting on long-term performance of the sensor networks in homes and spatial and temporal patterning in indoor air and environmental quality, we will present preliminary results evaluating associations between home-based air pollution exposures and patterns of energy use and indoor environmental quality. We expect this work should ultimately narrow key knowledge gaps on relationships between housing and health by leveraging an existing field-based housing study and developing foundational datasets needed for larger-scale housing studies. 

Utilizing Low-Cost Monitors for IAQ Assessment in Homes and Schools

By: Brett Singer, Staff Scientist and Indoor Environment Group Leader, Lawrence Berkeley National Laboratory

Summary: The availability of low-cost air quality monitors (LCMs) presents new opportunities for improving our understanding of air pollutant sources, hazards and control effectiveness in homes, schools, and other buildings. This presentation will provide example applications and findings from recent Berkeley Lab research projects. A Fall 2018 study showed that six LCMs available in the US and/or China were able to semi-accurately quantify (within factor of 2) common particle sources including frying food, incense, snuffing candles and vacuuming. However, all of the LCMs mostly or completely missed important sources that only emitted particles below about 0.25 um diameter, including broiling food, candles burning, and toasting. Professional monitors that used similar optical detection principles but cost 15-30x as much performed similarly. When deployed for studies in single-detached homes and in low-income apartments, LCMs provided data of similar quality as professional instruments including the TSI DustTrak II-8530 and MetOne BT645. The lower cost of the LCMs facilitated their deployment in multiple locations with the homes, providing valuable information about spatial resolution of PM over time. CO2 sensing by LCMs enables real-time monitoring to assess the adequacy of ventilation in homes or classrooms. However, the automatic baseline correction used in some low-cost CO2 sensors can introduce error in homes in which CO2 does not routinely reach outdoor levels, either because of continuous occupancy or because of low outdoor air exchange rates. These errors can be avoided with intentional calibration. We used two monitors with low-cost NO2 sensors to detect and semi-quantify peaks associated with gas stove use, but shifting baselines made quantitation of exposure concentrations infeasible. Months-long monitoring inside and outside of classrooms with low-cost PM sensors enabled an assessment of the benefits of upgrading HVAC filters from MERV8 to MERV13. 

Challenges and opportunities of indoor air quality sensors informed by field monitoring campaigns in Chicago, IL

By: Brent Stephens, Associate Professor and Department Chair, Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology

Summary: In this work I will summarize findings from several recent indoor air quality field monitoring campaigns in Chicago in which suites of “mid-grade” instruments (in terms of cost and accuracy) have been deployed in tall buildings, in 41 homes with asthmatic residents, and upcoming in 2020, in 80 homes of military veterans with chronic obstructive pulmonary disease (COPD). The suite of “mid-grade” sensors has included MetOne GT-526S optical particle counters (OPCs), Aeroqual Series 500 monitors with NO2 sensor heads, Aeroqual SM50 OEM OZU ozone sensors, Extech SD800 CO2 monitors, and Lascar EL-USB-CO CO monitors. Comparisons against each other and laboratory-grade reference instruments show promising accuracy, albeit with several caveats that can limit utility. Simultaneous deployment in the outdoor air intakes along the height of a tall building further demonstrate utility, but again with caveats based on sensor accuracy and calibration issues. Simultaneous indoor and outdoor measurements in 41 occupied homes in Chicago, IL further reveal challenges and opportunities in using this sensor suite, and comparisons of size-resolved PM mass concentrations estimated using the MetOne GT-526S OPCs co-located size-resolved gravimetric PM samples collected using Sioutas Personal Cascade Impactors deployed in a subset of home visits provides novel comparisons between instruments. Preliminary results show reasonable correlations between the OPC estimates and actual size-resolved mass-based concentrations (e.g., PM0.5, PM1, and PM2.5), but that correlations vary highly between home visits likely because of (i) differences in indoor particle density and/or shapes and/or (ii) the vast majority of PM mass was observed in the size bin smaller than 0.25 µm (which is below the detection limit of ~0.3 µm of the OPCs). Overall, this work is expected to provide useful insights into challenges and opportunities for using “mid-grade” IAQ sensors in field campaigns.

Deploying Air Quality Sensors by Communities

Communication and Interpretation of AQ Data