Urban Air Quality: Navigating Hyperlocal Challenges with Emerging Technologies

About this Research Topic

Background

Air pollution is a pervasive environmental challenge, particularly in urban areas where population densities and associated demands for energy, transportation, and infrastructure continue to rise. Unlike large scale atmospheric variables, air pollution concentrations can vary sharply over short spatial and temporal scales due to diverse and localized emission sources. This inherent variability necessitates high-resolution monitoring to understand and manage air quality effectively at the hyperlocal level. Traditional air quality monitoring relies on regulatory-grade instrumentation, which, while accurate, is expensive and limited in spatial coverage—especially in low- and middle-income countries (LMICs) where infrastructure and resources are often constrained.

In recent years, low-cost air pollution sensors have emerged as transformative tools that offer affordable, scalable, and portable monitoring solutions. Their growing accessibility opens new avenues for widespread deployment, democratizing air quality monitoring and enabling granular insights into pollution exposure at the neighborhood or street level. To date, much of the scientific focus has centered on calibration techniques and correction algorithms to improve the accuracy of low-cost sensor data. However, there remains a significant gap in the literature regarding the application of this data to address real-world air quality management challenges. This special issue seeks to bridge that gap by bringing together interdisciplinary research on the effective use of low-cost sensor data for hyperlocal air pollution assessment, source identification, and exposure mitigation.

We aim to highlight current challenges and opportunities in leveraging low-cost sensor networks to inform decision-making at municipal and community levels. Key themes of the Research Topic include (but not limited to): the integration of low-cost sensor data into regulatory frameworks; methodologies for identifying pollution hotspots and sources; citizen science and community-led monitoring initiatives; and the role of interdisciplinary collaboration in translating data into actionable interventions.

Moreover, this Research Topic invites contributions that explore the social and economic implications of hyperlocal air pollution monitoring. We are interested in research that evaluates how sensor-generated data can support the design and implementation of targeted mitigation strategies, promote environmental justice, and empower communities to advocate for cleaner air. Ultimately, the goal of this Research Topic is to advance the science and practice of hyperlocal air quality management by harnessing the potential of low-cost sensing technologies.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review

Keywords: Urban Air Quality. Climate Change. Air Pollution. Emissions.

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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