Spatio-Temporal Distribution of PM 2.5 and its Association with Agricultural Fires in Northern Argentina.

Agricultural burning in Tucumán, Argentina, has been a major contributor to air pollution, particularly during the dry season (April to September). This environmental issue is mainly due to the limited availability of modern machinery for sustainable harvesting, leading to heavy reliance on traditional biomass burning for crop residue management. The combustion process generates large amounts of fine particulate matter (PM_2.5), which severely affects air quality and public health. To address this challenge, an inter-institutional collaboration under the Networking Initiative Breathe2Change.org, supported by the Alexander von Humboldt Foundation, facilitated the creation of the first air quality monitoring network in Tucumán. This initiative aimed to raise awareness and provide actionable data to local communities and scientists.

A custom sensor module was designed, integrating an OPC Plantower PMS5003 sensor for real-time PM_2.5 detection, CO₂ sensors using NDIR technology, as well as humidity and temperature sensors. A forced ventilation system was also incorporated to ensure representative air circulation inside the module without affecting airflow into the OPC sensor. The network, consisting of 25 sensor modules deployed throughout the 22,500 square kilometers of Tucumán, provided continuous data collection for 12 months in 2023. The data were shared on a publicly accessible data platform, developed as part of the Breathe2Change Initiative, which facilitated both citizen consultation and analysis by the scientists involved in the project.

During an initial 3-week intercomparison phase, 10 sensor modules were assessed for consistency, yielding a high correlation (R² > 0.9), confirming the reliability of the modules. Afterward, 23 of the 25 sensors were deployed across urban, suburban, and rural areas, including regions directly affected by agricultural fires. High- and low-flow reference samplers were used to collect daily PM2.5 concentrations from August to December, coinciding with the peak biomass burning period. During this period, two of the sensor modules were co-located with the reference samplers to allow for direct comparison. This phase was essential for deriving a local correction factor for the sensors.

Results showed considerably high PM2.5 concentrations, with monthly averages exceeding 60 µg/m³ in fire-impacted areas, well above the daily limits set by the World Health Organization (WHO). Even urban areas recorded average levels of 30 µg/m³, surpassing WHO guidelines. The region’s mountainous terrain and climate further exacerbated the pollution, triggering thermal inversion phenomena that trapped pollutants near ground level. Using the corrected sensor network, spatial distribution maps of PM_2.5 were generated through Kriging interpolation, revealing a strong correlation between elevated pollutant levels and fire activity. Higher PM_2.5 concentrations were observed in the central-eastern part of the province, likely linked to sugarcane production areas, and possibly influenced by rural traffic and biomass burning. Kriging analysis confirmed this spatial trend, with a marked reduction in localized concentrations after September, likely due to rainfall events.

This study underscores the degradation of air quality during biomass burning events and the need for regulatory measures and sustainable agricultural practices to mitigate environmental and health impacts. It also highlights the potential of low-cost sensors as effective tools for monitoring air pollution in resource-limited regions.