Real-time air pollution (PM2.5) measurements in Education City, Doha, Qatar: Evaluating data from two different photometric monitors

Abstract

Background: Given the health hazards posed by particulate matter 2.5 (PM2.5), the need exists for simple, cost-effective, and real-time methods to monitor air quality with high spatio-temporal resolution. Direct-reading photometric detection is one modality of real-time PM2.5 monitoring. However, photometric data often require post hoc correction factors specific to individual manufacturers, meteorological conditions, and particle sizes and compositions. Methods: We methodically compared and evaluated PM2.5 concentration values collected by two different photometric monitors (TSI Environmental Monitor 8540 and MetOne ES-642) in Education City, Doha, Qatar. We analyzed the data collected by the two monitors in two different locations in September and December 2019, and side-by-side for two weeks in February 2020. Correlation and linear regression analyses were conducted to determine correction factors between the two monitors. Results and Discussion: The results indicate that both monitors reported almost identical trends in PM2.5 concentration, while the TSI monitor exaggerated the values by approximately twofold. When correlation-based corrections were applied, data from the two monitors matched almost perfectly for all comparison periods. As correction factors between PM2.5 sensors may vary based on in situ conditions, calibration must therefore be conducted on a case-by-case basis. However, our methodologies could constitute a template for future development of cross-calibration strategies. In addition, we determined average PM2.5 concentrations in Education City for each study period. These values were lower than those previously reported for other locations in Qatar during similar seasons. Conclusions: Our findings emphasize the relevance of the microenvironment when assessing PM2.5 levels for public health purposes. This investigation is expected to support and inform air quality management and mitigation strategies.