This paper explores the performance of smartphone cameras as low-cost and easily accessible tools to provide information about the levels and origin of particulate matter (PM) in ambient air. We tested the concept by digital analysis of the images of daily PM10 (particles with diameters 10 µm and smaller) samples captured on glass fibre filters by high-volume aerosol samplers at urban and rural locations belonging to the air quality monitoring network of Extremadura (Spain) for one year. The images were taken by placing the filters inside a box designed to maintain controlled and reproducible light conditions. Digital image analysis was carried out by a mobile colour-sensing application using red, green, blue/hue, saturation, value/hue, saturation, luminance (RGB/HSV/HSL) parameters, that were processed through statistical procedures, directly or transformed to greyscale. The results of the study show that digital image analysis of the filters can roughly estimate the concentration of PM10 within an air quality network, based on a significant linear correlation between the concentration of PM10 measured by an official gravimetric method and the colour parameters of the filters’ images, with better results in the case of the saturation parameter (SHSV). The methodology based on digital analysis can discriminate urban and rural sampling locations affected by different local particle-emitting sources and is also able to identify the presence of remote sources such as Saharan dust outbreaks in both urban and rural locations. The proposed methodology can be considered as a useful complement to the aerosol sampling equipment of air quality network field units for a quick estimation of PM10 in the ambient air, through a simple, accessible and low-cost procedure, with further miniaturization potential.

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Pb is a relevant atmospheric pollutant, mainly associated to particulate matter (PM). In this work, an ultrasound probe-assisted microextraction (UAME) pretreatment methodology has been optimized and validated for the extraction of Pb from atmospheric particulate matter samples before determination by ICP-MS. Factors that influence the ultrasonic extraction procedure were evaluated and optimized using a Box-Behnken design in conjunction with a response surface methodology, by assaying a PM certified reference material. The optimum conditions obtained for the Pb extraction are 62.5% of sonication amplitude, 200 s of sonication time, 47.5% v/v HNO3 as extracting medium, and sample/solvent ratio of 35 mg/mL. The US-probe assisted extraction methodology was applied to real PM from active and passive sampling for the extraction of Pb and other relevant elements such As, Cd and Cu. Analytical results demonstrated that ultrasonic microextraction is an efficient tool for the extraction of Pb and Cu from atmospheric samples, faster and greener than standard high temperature acid digestion.