Elemental analysis of particulate matter by X-ray fluorescence methods: A green approach to air quality monitoring

This review explores X-ray fluorescence (XRF) spectrometry for elemental analysis of particulate matter (PM) for air quality monitoring. The introduction presents PM classification based on size and composition, covering various elemental analysis methods while highlighting the increasing interest in XRF due to its non-destructive, rapid, and green features. The fundamental concepts of XRF and the experimental configurations commonly used are discussed, focusing on Energy Dispersive X-Ray Fluorescence (EDXRF) and Total Reflection X-Ray Fluorescence (TXRF). PM sampling devices and substrate are described, with a specific emphasis on filtering membranes for EDXRF and reflecting substrates for TXRF. Sample preparation strategies and procedures are presented. Qualitative and quantitative analysis is described, with a particular focus on the calibration approaches implemented for PM. Finally, the challenges faced by XRF in becoming a recognized reliable analytical technique for PM analysis, comparable to other standardized techniques for PM filters analysis, while capitalizing on its green advantages

Three-year long source apportionment study of airborne particles in Ulaanbaatar using X-ray fluorescence and positive matrix factorization

The capital city of Mongolia, Ulaanbaatar, suffers from high levels of pollution due to excessive airborne particulate matter (APM). A lack of systematic data for the region has inspired investigation into the type, origin and seasonal variations of this pollution, the effects of meteorological conditions and even the time-dependence of anthropogenic sources. This work reports source apportionment results from a large data set of 184 samples each of fine (PM2.5) and coarse (PM2.5-10) fraction atmospheric PM collected over a three-year period (2014–2016) in Ulaanbaatar, Mongolia. Positive Matrix Factorization (PMF) was applied using the concentrations of 16 elements measured by an energy dispersive X-ray fluorescence spectrometer along with the black carbon content measured by a reflectometer as input data. The PMF results revealed that whereas mixed sources dominate the coarse fraction, soil and traffic sources are the principle contributors to the fine fraction. The source profiles and the seasonal variations of their contributions indicate that fly ash emanating from coal combustion mixes with traffic emissions and resuspended soil, resulting in variable chemical source profiles. Four sources were identified for both fractions, namely, soil, coal combustion, traffic and oil combustion, which respectively contributed 35%, 16%, 41% and 8% to the coarse fraction and 31%, 27%, 31% and 11% to the fine fraction. Additionally, the probable source contributions from long-range transport events were assessed via concentration-weighted trajectory analysis

Elemental characterization of PM10, PM2.5 and PM1 in the town of Genoa (Italy)

The particulate matter (PM) concentration and composition, the PM10, PM2.5, PM1 fractions, were studied in the urban area of Genoa, a coastal town in the northwest of Italy. Two instruments, the continuous monitor TEOM and the sequential sampler PARTISOL, were operated almost continuously on the same site from July 2001 to September 2004. Samples collected by PARTISOL were weighted to obtain PM concentration and then analysed by PIXE (particle induced X-ray emission) and by ED-XRF (energy dispersion X-ray fluorescence), obtaining concentrations for elements from Na to Pb. Some of the filters used in the TEOM microbalance were analysed by ED-XRF to calculate Pb concentration values averaged over 7\u201330 d periods

Source apportionment of size and time resolved trace elements and organic aerosols from an urban courtyard site in Switzerland

Time and size resolved data of trace elements were obtained from measurements with a rotating drum impactor (RDI) and subsequent X-ray fluorescence spectrometry. Trace elements can act as indicators for the identification of sources of particulate matter <10 μm (PM10) in ambient air. Receptor modeling was performed with positive matrix factorization (PMF) for trace element data from an urban background site in Zürich, Switzerland. Eight different sources were identified for the three examined size ranges (PM1-0.1, PM2.5-1 and PM 10-2.5): secondary sulfate, wood combustion, fire works, road traffic, mineral dust, de-icing salt, industrial and local anthropogenic activities. The major component was secondary sulfate for the smallest size range; the road traffic factor was found in all three size ranges. This trace element analysis is complemented with data from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (AMS), assessing the PM1 fraction of organic aerosols. A separate PMF analysis revealed three factors related to three of the sources found with the RDI: oxygenated organic aerosol (OOA, related to inorganic secondary sulfate), hydrocarbon-like organic aerosol (HOA, related to road traffic) and biomass burning organic aerosol (BBOA), explaining 60 %, 22 % and 17 % of total measured organics, respectively. Since different compounds are used for the source classification, a higher percentage of the ambient PM10 mass concentration can be apportioned to sources by the combination of both methods. © 2011 Author(s)

Feasibility of coupling a thermal/optical carbon analyzer to a quadrupole mass spectrometer for enhanced PM2.5 speciation

A thermal/optical carbon analyzer (TOA), normally used for quantification of organic carbon (OC) and elemental carbon (EC) in PM2.5 (fine particulate matter) speciation networks, was adapted to direct thermally evolved gases to an electron impact quadrupole mass spectrometer (QMS), creating a TOA-QMS. This approach produces spectra similar to those obtained by the Aerodyne aerosol mass spectrometer (AMS), but the ratios of the mass to charge (m/z) signals differ and must be remeasured using laboratory-generated standards. Linear relationships are found between TOA-QMS signals and ammonium (NH4+), nitrate (NO3-), and sulfate (SO42-) standards. For ambient samples, however, positive deviations are found for SO42-, compensated by negative deviations for NO3-, at higher concentrations. This indicates the utility of mixed-compound standards for calibration or separate calibration curves for low and high ion concentrations. The sum of the QMS signals across all m/z after removal of the NH4+, NO3-, and SO42- signals was highly correlated with the carbon content of oxalic acid (C2H2O4) standards. For ambient samples, the OC derived from the TOA-QMS method was the same as the OC derived from the standard IMPROVE_A TOA method. This method has the potential to reduce complexity and costs for speciation networks, especially for highly polluted urban areas such as those in Asia and Africa.Implications: Ammonium, nitrate, and sulfate can be quantified by the same thermal evolution analysis applied to organic and elemental carbon. This holds the potential to replace multiple parallel filter samples and separate laboratory analyses with a single filter and a single analysis to account for a large portion of the PM2.5 mass concentration

Spectral- and size-resolved mass absorption efficiency of mineral dust aerosols in the shortwave spectrum: a simulation chamber study

This paper presents new laboratory measurements of the mass absorption efficiency (MAE) between 375 and 850 nm for 12 individual samples of mineral dust from different source areas worldwide and in two size classes: PM10:6 (mass fraction of particles of aerodynamic diameter lower than 10.6 \u3bcm) and PM2:5 (mass fraction of particles of aerodynamic diameter lower than 2.5 \u3bcm). The experiments were performed in the CESAM simulation chamber using mineral dust generated from natural parent soils and included optical and gravimetric analyses. The results show that the MAE values are lower for the PM10:6 mass fraction (range 37\u2013135x10-3 m2 g-1 at 375 nm) than for the PM2:5 (range 95\u2013711x10-3 m2 g-1 at 375 nm) and decrease with increasing wavelength as lambda-AAE, where the \uc5ngstr\uf6m absorption exponent (AAE) averages between 3.3 and 3.5, regardless of size. The size independence of AAE suggests that, for a given size distribution, the oxide fraction, which could ease the application and the validation of climate models that now start to include the representation of the dust composition, as well as for remote sensing of dust absorption in the UV\u2013vis spectral region