Although plastic debris is constantly accumulating in aquatic environments, the impact on aquatic ecosystems is not yet fully understood. A first important step to assess the consequences of plastic debris in aquatic ecosystems is the establishment of a reliable, verified, and standardized method to quantify the amount of plastic particles in the environment. We improved the density separation approach by the construction of the so called Munich Plastic Sediment Separator (MPSS). It enables a reliable separation of different ecologically relevant size classes of plastic particles from sediment samples. A ZnCl 2 -solution (1.6-1.7 kg/L) as separation fluid allows for an extraction of plastic particles ranging from large fragments to small microplastic particles (S-MPP, <1 mm). Subsequent identification and quantification of the particles with spatial resolution down to 1 µm can be performed using Raman microspectroscopy. Our study is the first providing validated recovery rates of 100% for large microplastic particles (L-MPP, 1-5 mm) and 95.5% for S-MPP. The recovery rate for S-MPP, using the MPSS, was significantly higher than the value obtained by application of classical density separation setup (39.8%). Moreover, our recovery rates were significantly higher than those based on froth flotation (55.0% for L-MPP) commonly used in recycling industries. Hence, our improved method can be used for a reliable and time-efficient separation, identification and quantification of plastic fragments down to S-MPP. This will help foster studies quantifying the increasing contamination of aquatic environments with microplastic particles, which is a crucial prerequisite for future risk assessment and management strategies.
Multiwavelength Raman microspectroscopy (MWRM) analysis for characterization of soot structure and reactivity was developed. This new method is based on the dispersive character of carbon D mode in Raman spectra (i.e., red shift and increase in intensity at higher excitation wavelength, λ(0)). The approach was proven by investigating various diesel soot samples and related carbonaceous materials at different λ(0) (785, 633, 532, and 514 nm). In order to compare the behavior of the D mode for various samples and to derive a single parameter characterizing the soot structure, the difference of integrals for pairs of spectra collected at different λ(0) was calculated. MWRM analysis revealed substantial differences in the structural ordering which decreases from graphite, over Printex XE2 and various diesel soot samples, to spark discharge soot. To obtain the relation between structure and reactivity of soot, MWRM analysis was combined with temperature-programmed oxidation (TPO). TPO allowed us to characterize the oxidation behavior of soot in terms of the maximum emission (CO + CO(2)) temperature and reactivity index. The latter was calculated by introducing the reactivity limits: spark discharge soot containing a large amount of disorder represents the upper limit, whereas the lower limit is given by graphite powder with high structural order. The comparison of MWRM (viz., the observed Raman difference integrals) and TPO data revealed a linear correlation between soot structure and oxidation reactivity. Thus, we demonstrated for the first time the potential of MWRM for a robust and rapid prediction of diesel soot reactivity based on the structure-reactivity correlation.
Soot aerosol, which is a major pollutant in the atmosphere of urban areas, often contains not only carbonaceous matter but also inorganic material. These species, for example, iron compounds, originated from impurities in fuel or lubricating oil, additives or engine wear may change the physico-chemical characteristics of soot and hence its environmental impact. We studied the change of composition, structure, and oxidation reactivity of laboratory-produced soot aerosol with varying iron content. Soot types of various iron contents were generated in a propane/air diffusion flame by adjusting the doping amount of iron pentacarbonyl Fe(CO) 5 to the flame. Scanning electron microscopy (SEM)/energy-dispersive Xray spectroscopy (EDX) was combined with cluster analysis (CA) to separate individual particles into definable groups of similar chemical composition representing the particle types in dependence of the iron content in soot. Raman microspectroscopy (RM) and infrared spectroscopy were applied for the characterization of the graphitic soot structure, hydrocarbons, and iron species. For the analysis of soot reactivity, temperature-programmed oxidation
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