Uncommon chemical species in PM2.5 and PM10 and its potential use as industrial and vehicular markers for source apportionment studies

Recent Developments in the Determination of PM2.5 Chemical Composition

Fine particulate matter (named PM_2.5) has become a prominent and dangerous form of air pollution. The chemical composition of PM_2.5 mainly includes inorganic elements, water soluble ions, elemental carbon (EC), organic carbon (OC), and organic compounds. The detection method for inorganic elements mainly includes X ray fluorescence, inductively coupled plasma-atomic emission spectrometry, and inductively coupled plasma mass spectrometry. As for water soluble ions, ion chromatography is the most common detection method. EC and OC are usually detected by carbon analyzer. The organic compounds are determined by gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry. In this paper, the merits and drawbacks of each analytical methods for the determination of PM_2.5 chemical composition are summarized. This review also includes our discussion on the improvement of the analytical accuracy for the determination of PM_2.5 chemical composition owing to the development of reference materials.

Source identification of exhaust and non-exhaust traffic emissions through the elemental carbon fractions and Positive Matrix Factorization method

Our study implies the importance of exhaust and non-exhaust emissions in a highway road tunnel, which is crucial to assess their impacts on air quality, human health, climate and developing functional methods for controlling. The total suspended particulates (TSP) and road dust (RD) samples were collected by PUF samplers and manually sweeping, respectively. Campaigns were performed in the summer and winter of 2014 in a highway road tunnel in Bolu, Turkey. Chemical analyses were presented to characterize the contents of organic carbon (OC) fractions (OC1,2,3,4), elemental carbon (EC) fractions (EC1,2,3,4,5,6), polycyclic aromatic hydrocarbons (PAHs) and metals (Al, Ba, Ca, Cu, Mg, Mn, Pb, Sr, Cr and Fe) in the collected TSP and RD samples. Positive matrix factorization (PMF) and orthogonal (Deming) regression analysis were applied to find out the exhaust and non-exhaust vehicle emissions of metal and carbonaceous species in the tunnel. The results showed that the identified source profiles included resuspended road dust (43%), non-exhaust emissions (37%), diesel exhaust emissions (13%), and gasoline exhaust emissions (7%). The relationship between emission markers of metal species and EC carbon fractions was supported by correlation studies. Among these EC fractions, EC4 and EC2 were the most abundant fractions in aerosol and RD samples, respectively and so they highly represented the diesel and non-exhaust emissions. Besides, the EC1 fraction was the indicator of gasoline-fueled emissions. Lower EC1 and higher soot-EC contribution obtained in tunnel aerosol (AS) samples showed the dominance of diesel-fueled vehicles in the tunnel. The data represented herein would help to identify the characteristic of vehicle emissions.

The mineralogical composition of coarse and fine particulate material, their fate, and sources in an industrialized region of southeastern Brazil

The particulate matter (PM) in the atmosphere may be composed of many elements and compounds, including toxic species and hazardous materials, which demand effective control of its emissions, starting with the knowledge of the sources. In this sense, the mineralogical analysis of the PM might be a powerful tool. Here, we present a comprehensive mineralogical characterization of the coarse and fine PM in an industrialized city southeast of Brazil, including a discussion about the transport, deposition, and potential sources associated. Elemental and mineralogical analyses by EDXRF and RSr-XRD were performed on SPM, TSP, PM₁₀, and PM_2.5. The results showed distinct mineralogical composition depending on the PM size. Mineral phases in SPM and TSP were majorly composed of hematite and quartz, while PM₁₀ and PM_2.5 were majorly composed of carbon, halite, sulfates, and carbon. The results show hazardous mineral phases associated with respiratory injuries in all PM size classes, such as hematite, pyrite, EC, and quartz. The XRD analysis also revealed primary particles of sulfate in the region close to industrial sources.

Experimental Characterization Protocols for Wear Products from Disc Brake Materials

The increasing interest in the emission from the disc brake system poses new challenges for the characterization approaches used to investigate the particles emitted from the wearing out of the relevant tribological systems. This interest stems from different factors. In the first place, a thorough characterization of brake wear particles is important for a complete understanding of the active tribological mechanisms, under different testing and servicing conditions. This information is an important prerequisite not only for the general improvement of brake systems, but also to guide the development of new materials for discs and brake pads, responding better to the specific requirements, including not only performance, but also the emission behavior. In this review paper, the main material characterization protocols used for the analyses of the brake wear products, with particular regard for the airborne fraction, are presented. Reliable results require investigating the fine and ultrafine particles as concerns their composition together with their structural and microstructural aspects. For this reason, in general, multi-analytical protocols are very much recommended.

Tracing iron ore tailings in the marine environment: An investigation of the Fundão dam failure

This work aims to characterize, in mineral and chemical terms, the ore tailings related to the Mariana disaster (MG, Brazil), occurred on 5 November 2015, and assess its correlation with sediments found in the continental shelf adjacent to the Doce River mouth (ES, Brazil). This study uses samples of tailings and seabed sediments collected at the mouth of the Doce River from 2012 to 2019. Elemental compositions of all samples were determined by X-ray fluorescence measurements; however, Synchrotron Resonant X-Ray Diffraction proved to be a remarkable technique to characterize the crystallographic phases of iron present in sediments. Studies and analyzes of the sediment samples showed that the tailings have a notable feature of the iron-crystallographic phases, mainly observed in the period after the Fundão dam failure, as compared with sediments collected in the period before. This set of iron-containing mineral phases, here called the Iron Mineralogical Set (IMS), consists of the main phases of hematite and magnetite and the minority phases of goethite and greenalite and it is used as a marker of tailings. Mass ac magnetic susceptibility measures supported the concept of the IMS as a marker. It is suggested a relationship between the content of the IMS in the sediment samples as a function of the measures of mass magnetic susceptibility. The IMS had shown the influence of tailings on the sea bed sediment indicating that there is no possibility, at the current stage, of predicting how many years this material will still be at the seabed.

The role of receptor models as tools for air quality management: a case study of an industrialized urban region

Evidence suggesting the association between the atmospheric particulate matter (PM) and health problems stress the need for the establishment of policies and actions aiming the improvement of air quality. As a start point, the knowledge of the main PM contributors is fundamental. Receptor models are frequently used for the identification and apportionment of local sources, nevertheless, some features of these models must be considered. For instance, whether the region has sources with similar chemical profiles and/or whether there is source temporal or spatial similarity, which can generate collinearity, affecting the sensibility of the models. In this work, it is presented some study of cases showing some strengths of the chemical mass balance model (CMB), such as to infer specific sources acting over specific locations in a same region, and its weaknesses for separating collinear sources. Besides, this work shows some study of cases reporting that the identification of specific PM markers (organic, inorganic, and crystallographic) and determined in the receptor samples can lead to better sources separation and improvements in the interpretation of the results using positive matrix factorization model. This work also highlights for the importance of the information provided by receptor models, in which should be carefully considered by the environmental agencies for decision-making concerning air quality management.

Association between the incidence of acute respiratory diseases in children and ambient concentrations of SO2, PM10 and chemical elements in fine particles

The aim of this study consists of investigating the effects of the SO₂, PM₁₀, inorganic chemical elements and black carbon (BC) present in fine particulates on the acute outcomes of respiratory diseases in children up to 12 years of age living in Brazilian urban area in the southern hemisphere during the winter (2013) and summer (2013-2014) months. SO₂ and PM₁₀ concentration data were obtained from six air quality monitoring stations spatially distributed in the area. PM_2.5 samples were collected at the same locations with a MiniVol sampler over a 24-h period on alternating days. The PM_2.5 components were analysed using the energy dispersive X-ray fluorescence and reflectance techniques. Hospital care and admission events due to acute respiratory diseases (n = 8,987) of the coded groups JJ00-JJ99 of the International Code of Diseases (ICD-10) were obtained from three hospitals (one public and two private hospitals). To quantify the association of acute respiratory disease events with pollutant concentrations, a generalized additive model (GAM) with a Poisson distribution was applied. The results showed a greater risk of acute respiratory events due to exposure to SO₂ with a relative risk of 1.28 (95% CI: 1.22-1.34) and to PM₁₀ with a risk of 1.14 (95% CI: 1.09-1.20) on the day of exposure (lag 0). The chemical constituents present in the fine particles with the highest risk for acute respiratory diseases were Si with a risk of 1.22 (95% CI: 1.15-1.29), S with a risk of 1.09 (95% CI: 1.06-1.12), Ti with a risk of 1.09 (95% CI: 1.01-1.17), BC with a risk of 1.07 (95% CI: 1.03-1.11), Se with a risk of 1.03 (95% CI: 0.96-1.10) and Ni with a risk of 1.03 (95% CI: 0.96-1.10).