Integrating Low-cost Sensor Systems and Networks to Enhance Air Quality Forecasting and Reanalysis Applications

Air quality forecasting is essential for protecting public health and the environment. The World Meteorological Organization (WMO) has developed initiatives like the Global Air Quality Forecasting and Information System (GAFIS), the Sand and Dust Storms Warning Advisory and Assessment System (SDS-WAS) and the Vegetation Fire and Smoke Pollution Warning Advisory and Assessment System (VFSP-WAS) to enhance forecasting capabilities.  

In this context, low-cost air quality sensor systems (LCS) are transformative tools in modern air quality management, offering new opportunities to complement traditional monitoring methods. By integrating LCS data with established systems, such as satellite observations and reference-grade instrumentation, the reliability and applicability of air quality data for forecasting can be significantly enhanced. 

A key strength of LCS is their ability to expand the spatial and temporal reach of monitoring networks. However, their use must address inherent limitations in accuracy and precision. Co-locating LCS with reference-grade monitors is essential to quantify uncertainties and ensure data quality. This calibration step enables the deployment of LCS in advanced applications like air quality forecasting. Successfully implementing LCS networks for global, regional, or urban forecasting requires careful planning to ensure adequate spatial coverage, data quality, and timely updates, as well as seamless integration with other systems for actionable insights.  

The World Meteorological Organization (WMO) has been instrumental in coordinating global efforts to optimize LCS deployment. Through guidelines, best practices, and integration frameworks, the WMO supports national and regional initiatives to enhance air quality management. A recent WMO report (WMO, 2024) underscores the importance of incorporating LCS into comprehensive monitoring frameworks for supporting air quality forecasting and reanalysis applications. 

Ongoing advancements in LCS technology and standardization—led by organizations like WMO —are vital to unlocking their full potential. These efforts promise a more equitable and effective approach to air quality management, ensuring that LCS contribute meaningfully to global strategies for monitoring and forecasting. The present contribution will overview the main outcomes of the WMO’s 2024 report on the use of LCS for air quality forecasting and reanalysis applications. 

References:  

WMO, UNEP and IGAC; Integrating Low-cost Sensor Systems and Networks to Enhance Air Quality Applications, 2024, https://library.wmo.int/idurl/4/68924