Low-Cost Sensor Networks and Novel Exposure Assessment to Close Air Quality Monitoring Gaps for Public Health

Air pollution is one of the largest environmental risk factors for human health, yet the ability to measure it is distributed very unevenly. Reference-grade monitoring networks are concentrated in a small number of high-income cities, while much of Africa, South Asia, Latin America, and rural areas everywhere have little or no ground-truth data. Where exposure cannot be measured, it is harder to identify who is at risk, communicate health risks, target prevention, or assess whether policies are working. This monitoring gap is therefore not only a technical problem: it is a public health equity problem, because the populations with the least data are frequently those with the highest exposures and the fewest protective interventions.Low-cost sensor networks and advanced spatial exposure modelling have emerged as practical and scalable routes to closing this gap. Deployed across urban hotspots, schools, residential neighbourhoods, and industrial corridors, distributed sensor networks can generate the high-resolution spatial and temporal exposure data that sparse formal infrastructure cannot provide. These data can support population exposure assessment, identify communities and groups who may face higher risks, and help public health practitioners and policymakers target protective action. They can also enable personal, micro-environmental, and community-level exposome characterisation across under-resourced settings. Realising this potential depends on rigorous calibration, drift correction, validation against reference instruments, data quality assurance protocols, optimal network design, and the translation of sensor data into reliable, health-relevant exposure measures.The goal of this Research Topic is to bring together research that uses low-cost sensor networks, novel exposure assessment methods, and complementary environmental data sources to characterise exposure and protect population health in under-monitored settings. We are particularly interested in work that connects monitoring innovation to public health needs and outcomes: identifying exposure patterns in vulnerable populations, linking measurements with epidemiological outcomes or estimates of disease burden, informing targeted prevention and risk communication, supporting public health surveillance and early-warning systems, and shaping clean air policy at municipal or national scales. Contributions that report solely on instrument bench testing or sensor electrical engineering, without a clear link to exposure assessment, population health, or environmental health policy and practice, fall outside the scope of this collection.We welcome Original Research, Brief Research Reports, Methods, Community Case Studies, Reviews and Mini Reviews, Perspectives, Policy Briefs, Study Protocols, and Data Reports addressing themes including, but not limited to:Design, deployment, and long-term operation of low-cost sensor networks that enable population exposure assessment and support public health planning in low- and middle-income countries and other under-monitored settings.• Calibration, drift correction, quality assurance, and validation of low-cost sensors against reference-grade instruments, with evaluation of whether the resulting data are fit for exposure assessment and public health research or decision-making.• Community-scale, school-based, and municipal sensor deployments that identify local exposure patterns, support protection of vulnerable groups, and improve public risk communication.• Integration of low-cost sensor measurements with satellite retrievals, atmospheric dispersion models, land-use regression, and meteorological reanalysis to produce high-resolution exposure estimates for environmental epidemiology, public health surveillance, and prevention planning.• Personal and micro-environmental exposure monitoring using stationary and wearable devices, including indoor air quality, household energy use, and cooking exposures, where findings inform health risk assessment or protective action.• Studies linking sensor-derived exposure data with health outcomes, including cardiorespiratory outcomes, in susceptible populations and communities facing environmental health disparities.• Use of distributed sensor networks in environmental health surveillance, real-time early-warning systems, and targeted public health mitigation interventions.• Translation of local sensor-network evidence into municipal, national, and regional air quality standards, regulatory frameworks, and clean air action plans that protect population health.• Data governance, quality assurance, open data stewardship, and sustainability in resource-limited monitoring networks, including their implications for equitable access to exposure information and its use in public health practice.By assembling this evidence, the collection aims to advance the Environmental Health and Exposome section’s focus on innovative tools and study designs for characterising the exposome, while showing how these approaches can support public health research, practice, and policy. It also supports the UN Sustainable Development Goals 3 (Good Health and Well-being), 11 (Sustainable Cities and Communities), and 13 (Climate Action). Topic editors: Dr. Francis Olawale Abulude, Irankunda Elisephane, Ph.D., Chantelle Howlett-Downing Source: https://www.frontiersin.org/research-topics/86491/low-cost-sensor-networks-and-novel-exposure-assessment-to-close-air-quality-monitoring-gaps-for-public-health