![City in smog](/sites/g/files/omnuum10826/files/styles/hwp_21_9__1920x825/public/datasmart/files/leo_visions-sfkf6gsape0-unsplash.jpg?itok=TGVL-Hg0) # Strategies for Enhancing Air Quality and Public Health through Low-Cost Sensors August 28, 2024 [ Kanchan Yadav ](#kanchanyadav) Air pollution is a significant health concern, impacting individuals universally, and research indicates that [air pollution disproportionately affects certain demographics](https://www.who.int/news-room/spotlight/how-air-pollution-is-destroying-our-health), notably communities of color and low-income populations. Exposure to substandard air quality is [linked to both acute and chronic health issues,](https://www.epa.gov/air-research/research-health-effects-air-pollution) particularly among vulnerable groups such as the elderly, children, and pregnant women. The health risks are exacerbated for those residing near pollution sources like [factories, major roadways, and ports](https://www.epa.gov/air-research/research-near-roadway-and-other-near-source-air-pollution) with [heavy diesel truck activity](https://www.nrdc.org/sites/default/files/driving.pdf). Furthermore, [socioeconomic factors](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363288/) compound the susceptibility of low-income communities and people of color to the adverse effects of climate change. Nationally, the ["State of the Air 2024 report"](https://www.lung.org/getmedia/dabac59e-963b-4e9b-bf0f-73615b07bfd8/State-of-the-Air-2024.pdf) reveals that a significant portion of the U.S. population continues to be affected by air pollution, despite considerable efforts to improve air quality over decades. Specifically, 131.2 million Americans, constituting 39 percent of the population, reside in areas where ozone or particle pollution levels exceed health standards. This represents an increase of 11.7 million individuals from the previous year's findings. These statistics underscore ongoing [challenges in reducing air pollution](https://www.epa.gov/clean-air-act-overview/air-pollution-current-and-future-challenges) nationwide, highlighting widespread exposure to harmful pollutants and associated health risks across the country. However, these risks are not distributed equally across the United States. Air pollution in the US [disproportionately affects communities of color and those living in poverty](https://www.hsph.harvard.edu/news/press-releases/racial-ethnic-minorities-low-income-groups-u-s-air-pollution/). [Over 68.9 million people of color](https://www.lung.org/research/sota/key-findings/people-at-risk) reside in counties with failing grades for ozone and/or particle pollution, with 27.5 million in areas failing all measures. Similarly, 16 million individuals living beneath the [poverty line](https://www.worldbank.org/en/news/video/2017/04/14/what-are-poverty-lines) reside in counties failing at least one pollutant grade (which means the concentration of one pollutant exceeds the limits set by health or environmental authorities), including 5.4 million in areas failing on all counts of all pollutants. These groups face [heightened, correlated risks](https://www.hrw.org/report/2024/01/25/were-dying-here/fight-life-louisiana-fossil-fuel-sacrifice-zone) of respiratory illnesses, cardiovascular diseases, and [adverse pregnancy outcomes](https://ehp.niehs.nih.gov/doi/10.1289/EHP12880) due to exposure to unhealthy air quality, reflecting significant disparities in environmental health impacts based on socioeconomic and racial factors — and highlighting why local leaders should use an equity lens when addressing these issues. ## Advancements in Low-Cost and Portable Sensor Technology [Monitoring air quality ](https://19january2017snapshot.epa.gov/air-research/air-monitoring-measuring-and-emissions-research_.html)is crucial for effective air quality management. Monitoring helps local governments assess pollution levels, provide timely data to the public, support air quality standards, evaluate emission control strategies, track trends, and aid in health research. [Traditional approaches to monitoring air quality](https://www.sciencedirect.com/science/article/abs/pii/B9780323902663000054) have relied heavily on regulatory-grade monitoring stations and networks. These methods are characterized by their high accuracy and reliability, but they also have limitations, particularly in terms of cost, coverage, and accessibility. The state of air quality monitoring is evolving from relying on expensive, stationary equipment to utilizing [lower-cost, portable sensors](https://www.sciencedirect.com/science/article/pii/S235264832100057X) that provide high-resolution, near real-time data. These advancements are driven by recent developments in electrical engineering, including [microfabrication techniques ](https://www.sciencedirect.com/topics/engineering/microfabrication-technique)and [microelectro-mechanical systems (MEMS)](https://www.sciencedirect.com/science/article/abs/pii/S2214785321037998), which have enabled the creation of small, affordable sensors. These new sensors enhance traditional monitoring capabilities, capture spatial and temporal variability, and support health studies and community engagement. [Low-cost sensors (LCS)](https://www.epa.gov/indoor-air-quality-iaq/low-cost-air-pollution-monitors-and-indoor-air-quality) are fully operational sensor systems, comprising self-contained devices equipped with one or more sensing elements. These are often referred to as low-cost detectors or original equipment manufacturer (OEM) sensors. They include essential hardware and software components for managing control, power supply, and data, all housed within a weatherproof enclosure. These sensors are designed to detect reactive gaseous air pollutants like nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3). Additionally, some LCS also measure particulate matter (PM) and greenhouse gasses (GHG), primarily focusing on PM2.5, PM10, PM1, carbon dioxide (CO2), and methane (CH4). However, the [measurement of volatile organic compounds (VOCs) by LCS ](https://www.mdpi.com/1424-8220/17/7/1520)may lack specificity for individual compounds/ types of VOCs. The [advancement of LCS technology](https://www.unep.org/news-and-stories/press-release/low-cost-sensors-can-improve-air-quality-monitoring-and-peoples) has opened new avenues for air quality monitoring, providing a more accessible and scalable approach compared to traditional methods. These sensors are compact, portable, and cost-effective, making them [suitable for deployment in diverse settings](https://www.sciencedirect.com/science/article/pii/S235264832100057X). These sensors enable the reconstruction of air quality patterns, identification of pollution sources, and trend analysis. Their low data latency and ease of deployment, especially in areas with limited infrastructure, make them invaluable for widespread monitoring and early warning systems, supporting effective air quality forecasting critical for public health decision-making. While LCS are cheaper than traditional reference grade monitors (RGM), they often have [limitations](https://aaqr.org/articles/aaqr-23-01-oa-0010) in data quality, sensitivity, robustness, and operational lifespan. Calibration and quality control processes, along with necessary infrastructure and personnel, can increase overall costs. Despite these challenges, [LCS helps fill gaps in global and local air quality monitoring networks](https://library.wmo.int/viewer/68924/download?file=GAW-293_report_en.pdf&type=pdf&navigator=1), providing crucial data in regions lacking RGM networks, especially in low- and middle-income communities. ## Improvement in Public Health and Environmental Justice Outcomes Some instances involving LCS on a network scale are performing excellently, particularly at the city level, like the [Love My Air program in Dever](https://denvergov.org/Government/Agencies-Departments-Offices/Agencies-Departments-Offices-Directory/Public-Health-Environment/Environmental-Quality/Air-Quality/Love-My-Air?OC_EA_EmergencyAnnouncementList_Dismiss=0e0309ee-aeef-437c-b312-787c105d869f&lang_update=638560068947468833) and the [Chicago Array of Things (AoT)](https://smartchicagocollaborative.org/work/ecosystem/array-of-things-civic-engagement/). At Smart Chicago, the AoT is an urban sensing initiative, comprising a network of interactive, modular sensor units installed throughout Chicago. These sensors gather real-time data on the city's environment, infrastructure, and activities for research and public use. The AoT acts as a "fitness tracker" for the city, monitoring factors that affect livability in Chicago, such as climate, air quality, and noise. Other projects such as [Purple Air Network](https://www2.purpleair.com) and t[he South Coast Air Quality Management District (SCAQMD) Sensor Deployment](http://www.aqmd.gov/aq-spec) are successful examples of city government programs that use network-scale LCS for air quality monitoring. Another notable city-level initiative utilizing network-scale low-cost sensors is [the New York Community Air Survey (NYCCAS)](https://www.nyc.gov/site/doh/data/data-sets/air-quality-nyc-community-air-survey.page) conducted by the New York City Department of Health and Mental Hygiene in collaboration with Queens College. This survey assesses air quality differences across New York City. Air pollution measurements are taken at about 100 city locations during each session, including 15 low-income neighborhoods that would benefit from additional monitoring to understand potential sources of emissions, referred to as [environmental justice sites](https://nyccas.cityofnewyork.us/nyccas2021v9/report/2#Sites). Each site is monitored for a two-week period during each season using battery-powered pumps and filters to collect air samples. After the two-week period, monitors are collected and taken to a laboratory for analysis. The survey checks for pollutants that cause health problems, such as fine particles, nitrogen oxides, sulfur dioxide, ozone, and elemental carbon (a marker for diesel exhaust particles). One of the most successful and well-documented city programs is [Breathe London](https://www.breathelondon.org/), which began as a pilot in 2019 and was funded for four additional years in February 2020. The Breathe London program uses low-cost sensors to measure air quality across a robust resident- and community-led hyper-local network. Not only does the program provide open, detailed pollution data, it was also guided by rigorous public health research from Imperial College London. In 2022 data revealed that improvements in air pollution, attributed to the city’s low-emission zones and updated emissions standards, “[reduced the number of hospital admissions](https://www.london.gov.uk/press-releases/mayoral/cleaner-air-would-help-150000-breathe-easier) for asthma and serious lung conditions by 30 percent.” Analyzing air quality data alongside [social, economic, and demographic factors ](https://library.wmo.int/viewer/68924/download?file=GAW-293_report_en.pdf&type=pdf&navigator=1)can uncover exposure disparities within and between communities. However, challenges such as inter-unit precision, long-term stability of LCS data, and shorter operational lifetimes compared to regulatory-grade monitors (RGM) complicate long-term trend analysis. Despite these challenges, [effective environmental justice research](https://www.mdpi.com/1660-4601/19/14/8777) can still be conducted with LCS by appropriately characterizing uncertainties and using statistical techniques that account for these uncertainties. Ensuring high inter-unit precision through [pre- and post-deployment co-location studies](https://www.mdpi.com/2073-4433/14/3/540) provides robust performance metrics, allowing for reliable identification of disparities and their statistical significance. ## Empowering Communities Through Citizen Science [Citizen science projects](https://web.archive.org/web/20250207033315/https://www.airnow.gov/aqaw-2021/citizen-science-sensors/) using network-scale LCS for air quality monitoring have become popular across the United States, [empowering communities in monitoring local air quality](https://www.sciencedirect.com/science/article/pii/S2772737823000408), fostering a sense of ownership and responsibility, and directly impacting their lives. The availability of wireless networks and web services has made it easier to use these sensors for community-based participatory monitoring and data dissemination, raising public awareness and encouraging community engagement in environmental issues and crowd-sourcing efforts. These initiatives provide real-time data to academic researchers, helping to identify pollution hotspots and allowing for timely interventions to reduce exposure and improve public health. Governments can use data from LCS, especially in areas where installing regulatory-grade monitoring systems are not feasible, to demonstrate their commitment to environmental protection, enhancing transparency and accountability in addressing air quality issues. [Citizen science initiatives](https://education.nationalgeographic.org/resource/citizen-science-projects/) also promote collaboration among various government departments, community organizations, and the private sector to collectively address air quality challenges. Projects like [Air Quality Egg](https://airqualityegg.com/home) have involved residents in data collection and analysis, fostering greater awareness and action. Co-development of monitoring and mitigation strategies with communities will increase their longevity and effectiveness in responding to local needs. [Involving community members in leadership roles and establishing long-term partnerships](https://www.researchgate.net/publication/349354052_Participatory_Research_for_Environmental_Justice_A_Critical_Interpretive_Synthesis) supported by multiple funding mechanisms are identified as key factors in making substantive improvements to local air quality The deployment of network-scale LCS technology is a transformative approach to improving air quality and public health in low-income communities. These communities often suffer from high pollution exposure but lack the resources for traditional monitoring. LCS technology fills this gap by offering an affordable, accessible, and scalable solution for real-time air quality monitoring and community engagement. Collaborative efforts highlight how this data-driven approach can drive targeted interventions and environmental justice initiatives, helping communities understand air quality trends and make informed decisions about outdoor activities and necessary protections. ## About the Author ### Kanchan Yadav ![Headshot of Kanchan Yadav](/sites/g/files/omnuum10826/files/styles/hwp_1_1__100x100_scale/public/datasmart/files/ds_kanchan_pic_2.png?itok=U3o6brkk) Kanchan Yadav is an MPH student specializing in Health and Social Behavioral Sciences at the Harvard T.H. Chan School of Public Health. She holds a PhD in Physical Organic Chemistry, a Master's in Chemistry, and a Bachelor's in Biological Sciences from India. Before starting her Master's in Public Health, she worked as a program research director at a non-profit organization in India, where she led several health initiatives. Prior to this role she was a research associate at the Indian Institute of Toxicology Research, focusing on hospital waste management and water purification. She was an intern at the Institute for Technology and Global Health for the summer of 2024. See also:- [ Environment ](/topics/environment) - [ Public Health ](/topics/public-health) Share on:- [ Facebook ](#) - [ Twitter ](#) - [ Linkedin ](#)