The application of Raman spectroscopy combined with multivariable analysis on source apportionment of atmospheric black carbon aerosols

A comprehensive SERS, SEM and EDX study of individual atmospheric PM2.5 particles in Chengdu, China

Characterization of atmospheric fine particulate matter (PM_2.5) in large cities has important implications for the study of their sources and formation mechanisms, as well as in developing effective measures to control air pollution. Herein, we report a holistic physical and chemical characterization of PM_2.5 by combining surface-enhanced Raman scattering (SERS) with scanning electron microscopy (SEM) and electron-induced X-ray spectroscopy (EDX). PM_2.5 particles were collected in a suburban area of Chengdu, a large city in China with a population over 21 million. A special SERS chip composed of inverted hollow Au cone (IHAC) arrays was designed and fabricated to allow direct loading of PM_2.5 particles. SERS and EDX were used to reveal the chemical composition, and particle morphologies were analyzed from SEM images. SERS data of atmospheric PM_2.5 indicated qualitatively the presence of carbonaceous particulate matter, sulfate, nitrate, metal oxides and bioparticles. The EDX showed the presence of the elements C, N, O, Fe, Na, Mg, Al, Si, S, K, and Ca in the collected PM_2.5. Morphology analysis showed that the particulates were mainly in the form of flocculent clusters, spherical, regular crystal shaped or irregularly shaped particles. Our chemical and physical analyses also revealed that the main sources of PM_2.5 are automobile exhaust, secondary pollution caused by photochemical reactions in the air, dust, emission from nearby industrial exhaust, biological particles, other aggregated particles, and hygroscopic particles. SERS and SEM data collected during three different seasons showed that carbon-containing particles are the principal sources of PM_2.5. Our study demonstrates that the SERS based technique, when combined with standard physicochemical characterization methods, is a powerful analytical tool to determine the sources of ambient PM_2.5 pollution. Results obtained in this work may be valuable to the prevention and control of PM_2.5 pollution in air.

From multi to single-particle analysis: A seasonal spectroscopic study of airborne particulate matter in Zaragoza, Spain

It is distinguished that deficient outdoor air quality is responsible for substantial health and climate issues. The aim of our study was to investigate the air quality in the city of Zaragoza (Spain) by characterizing atmospheric particulate matter (PM₁₀) during two seasons (winter and spring). PM₁₀ samples were collected in 2022 in quartz filters through a low-volume sampler and chemically analysed by complementary analytical techniques: Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), Laser Induced Breakdown Spectroscopy (LIBS), Raman Spectroscopy (RS) and Field Emission Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (FESEM-EDS). Results have revealed, together with a temperature inversion phenomenon in winter, the presence of both natural (Al, Ca, Mg, Ti, Sr, Fe, etc.) and anthropogenic particles. The latter mainly formed by black carbon with an origin on fossil fuel combustion emissions. Additionally, chemical analyses of PM₁₀ filters showed the presence of three types of microplastics suspended in the air of the city: polyethylene terephthalate (PET), polyamides (PA) and polystyrene (PS). The results obtained from this research are of special interest to take into account for future air quality policies, particularly those with the aim of reducing air pollution in cities.

Industrial wastewater source tracing: The initiative of SERS spectral signature aided by a one-dimensional convolutional neural network

The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and important features. Surface-enhanced Raman scattering (SERS) has long been recognized as an optical method that can provide fingerprint-like chemical information at the single-molecule level. Here, the advanced one-dimensional convolutional neural network (1D-CNN) approach was applied to accurately identify the SERS spectral signature of industrial wastewaters for source tracing. A total of 66,000 SERS spectra were acquired from wastewaters of 22 factories across 10 industrial categories at three excitation wavelengths after data augmentation. The dataset was used to train a 1D-CNN model consisting of three convolutional layers to achieve adequate feature extraction of SERS spectra. As a proof-of-concept, multimixed wastewater samples were used to simulate practical pollution scenarios and evaluate the application potential of the model. The SERS-1D-CNN platform can identify the amount and factory information of wastewaters in multimixed samples, which achieves a recognition accuracy rate of 97.33%. The results suggest that even in a complex and unknown water environment, the 1D-CNN model can accurately identify industrial wastewaters in precollected datasets, exhibiting excellent potential in pollution source tracing.

Raman spectroscopy for profiling physical and chemical properties of atmospheric aerosol particles: A review

Atmosphere aerosols have significant impact on human health and the environment. Aerosol particles have a number of characteristics that influence their health and environmental effects, including their size, shape, and chemical composition. A great deal of difficulty is associated with quantifying and identifying atmospheric aerosols because these parameters are highly variable on a spatial and temporal scale. An important component of understanding aerosol fate is Raman Spectroscopy (RS), which is capable of resolving chemical compositions of individual particles. This review presented strategic techniques, especially RS methods for characterizing atmospheric aerosols. The nature and properties of atmospheric aerosols and their influence on environment and human health were briefly described. Analytical methodologies that offer insight into the chemistry and multidimensional properties of aerosols were discussed. In addition, perspectives for practical applications of atmospheric aerosols using RS are featured.

Constructing a Raman and surface-enhanced Raman scattering spectral reference library for fine-particle analysis

Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scattering (SERS) are often used to analyze the composition of fine particles to determine their physical and chemical properties as well as reaction mechanisms. However, there is no comprehensive Raman spectral library of fine particles. Furthermore, various studies that used SERS for fine-particle composition analysis showed that the uniqueness of the SERS substrates and different excitation wavelengths can produce a different spectrum for the same fine-particle component. To overcome this limitation, we conducted SERS experiments with a portable Raman spectrometer using two common SERS substrates (silver (Ag) foil and gold nanoparticles (Au NPs)) and a 785 nm laser. Herein, we introduced three main particle component types (sulfate-nitrate-ammonium (SNA), organic material, and soot) with a total of 39 chemical substances. We scanned the solid Raman, liquid Raman, and SERS spectra of these substances and constructed a fine-particle reference library containing 105 spectra. Spectral results indicated that for soot and SNA, the differences in characteristic peaks mainly originated from the solid-liquid phase transition; Ag foil had little effect on this difference, while the Au NPs caused a significant red shift in the peak positions of polycyclic aromatic hydrocarbons. Moreover, with various characteristic peak positions in the three types of spectra, we could quickly and correctly distinguish substances. We hope that this spectral library will aid in the future identification of fine particles.

Large contribution from worship activities to the atmospheric soot particles in northwest China

Worship activities like burning joss paper during the Chinese Hanyi festival is a common, traditional custom in northwest China. However, the pollutants of e.g., soot particles, released from joss paper burning and the corresponding impacts on urban air quality were poorly investigated, which can be a particular concern since these activities are conducted in an uncontrolled manner. In this study, a long time-of-flight (LToF) soot particle aerosol mass spectrometry (SP-AMS) was deployed to characterize the refractory black carbon (rBC) emitted from the joss paper burning, as well as crop residue, coal combustion, and traffic during the Hanyi Festival in mid-November 2020 in the northwestern city of Xi'an in China. Large difference (from <5% to >100%) in the fragmentation patterns (C_n⁺) for the measured rBC from different source emissions were found when compared to the reference Regal Black. Using the receptor model of positive matrix factorization (PMF) with the multilinear engine (ME-2) algorithm, the obtained rBC mass spectra were used as the anchoring profiles to evaluate the emission strengths of different source types to the atmospheric rBC. Our results show that the burning of joss paper accounted for up to 42% of the atmospheric rBC mass, higher than traffic (14-17%), crop residue (10-17%), coal (18-20%) during the Hanyi festival in northwest China. Moreover, we show that the overall air quality can be worsened due to the practice of uncontrolled burning of joss paper during the festival, which is not just confined to the people who do the burning. Although worship activities occur mainly during festival periods, the pollution events contributed by joss paper burning may pose an acute exposure risk for public health. This is particularly important since burning joss paper during worship activities is common in China and most Asian countries with similar traditions.

Characterization of atmospheric aerosols in the Antarctic region using Raman Spectroscopy and Scanning Electron Microscopy

The non-destructive spectroscopic characterization of airborne particulate matter (PM) was performed to gain better knowledge of the internal structures of atmospheric aerosols at the particle level in the Antarctic region, along with their potential sources. PM and soil samples were collected during the 2016-2017 austral summer season at the surroundings of the Spanish Antarctic Research Station "Gabriel de Castilla" (Deception Island, South Shetland Islands). PM was deposited in a low-volume sampler air filter. Raman spectroscopy (RS) and Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (SEM-EDS) were used to determine the elemental and molecular composition of the individual aerosol and soil particles. Filter spectra measured by these techniques revealed long-range atmospheric transport of organic compounds (polystyrene and bacteria), local single and cluster particles made of different kinds of black carbon (BC), exotic minerals (polyhalite, arcanite, niter, ammonium nitrate, syngenite and nitrogen, phosphorus, and potassium (NPK) fertilizer), and natural PM (sea salts, silicates, iron oxides, etc.). In addition to the filter samples, forsterite and plagioclase were discovered in the soil samples together with magnetite. This is the first report of the presence of a microplastic fiber in the Antarctic air. This fact, together with the presence of other pollutants, reflects that even pristine and remote regions are influenced by anthropogenic activities.

Highly sensitive and selective detection of glutathione using ultrasonic aided synthesis of graphene quantum dots embedded over amine-functionalized silica nanoparticles

Glutathione (GSH) is the most abundant antioxidant in the majority of cells and tissues; and its use as a biomarker has been known for decades. In this study, a facile electrochemical method was developed for glutathione sensing using voltammetry and amperometry analyses. In this study, a novel glassy carbon electrode composed of graphene quantum dots (GQDs) embedded on amine-functionalized silica nanoparticles (SiNPs) was synthesized. GQDs embedded on amine-functionalized SiNPs were physical-chemically characterized by different techniques that included high resolution-transmission electron microscopy (HR-TEM), X-ray diffraction spectroscopy (XRD), UV-visible spectroscopy, Fourier-transform infrared spectroscopy(FTIR), and Raman spectroscopy. The newly developed electrode exhibits a good response to glutathione with a wide linear range (0.5-7 µM) and a low detection limit (0.5 µM) with high sensitivity(2.64 µA µM-1). The fabricated GQDs-SiNPs/GC electrode shows highly attractive electrocatalytic activity towards glutathione detection in the neutral media at low potential due to a synergistic surface effect caused by the incorporation of GQDs over SiNPs. It leads to higher surface area and conductivity, improving electron transfer and promoting redox reactions. Besides, it provides outstanding selectivity, reproducibility, long-term stability, and can be used in the presence of interferences typically found in real sample analysis.

Using Micro-Raman Spectroscopy to Investigate Chemical Composition, Mixing States, and Heterogeneous Reactions of Individual Atmospheric Particles

Measuring the chemical composition of individual atmospheric aerosol particles can provide direct evidence of their heterogeneous reactions and mixing states in the atmosphere. In this study, micro-Raman spectroscopy was used to measure the chemical composition of 1200 individual atmospheric particles in 11 samples collected in Beijing air. (NH₄)₂SO₄, NH₄NO₃, various minerals, carbonaceous species (soot and organics), and NaNO₃ were identified in the measured particles according to their characteristic Raman peaks. These species represented the main components of aerosol particles. In individual particles, NH₄NO₃ and (NH₄)₂SO₄ either existed separately or were internally mixed. Possible reaction pathways of CaCO₃ particles in the atmosphere were proposed based on the results of this study and laboratory simulations on heterogeneous reactions in the literature. CaCO₃ reacted with N- and S-containing (nitrogen- and sulfur-containing) acidic gases to produce Ca(NO₃)₂ and CaSO₄. Ca(NO₃)₂ further reacted with S-containing acidic gases and oxidants to produce CaSO₄. Of the soot-containing particles, 23% were internal mixtures of soot and inorganic material. Of the organics-containing particles, 57% were internal mixtures of organic and inorganic materials. Micro-Raman spectroscopy directly identified functional groups and molecules in individual atmospheric particles under normal ambient conditions, rendering it a powerful tool for measuring the chemical composition of individual atmospheric particles with a diameter of ≥1.0 μm.

Nanostructure and reactivity of soot particles from open burning of household solid waste

The main purpose of this work was to quantify and characterize chemically and morphologically the emission of soot particles from the open burning of several common solid waste including paperboard, wood, peel, chemical fiber, polyethylene (PE) and polyvinyl chloride (PVC). The experiment was conducted in a laboratory-scale open-burning combustor with a dilution sampling system to obtain soot particles. The thermogravimetric profiles (TGA) showed an increasing order of oxidation reactivity: PE > PVC > fiber > paper ≈ peel > wood. High resolution transmission electron microscopy (HRTEM) images revealed more detailed information about the morphology and the particle size of soot aggregates. Subsequent quantification of nanostructure by fringe analysis showed that plastics generated soot particles with the looser carbon layers with higher tortuosity compared to the three kind of biomass. Raman spectroscopy further confirms the observed differences. In addition, wood soot exhibited the highest content of C-OH group (17.5%) among the six samples (X-Ray photoelectron spectroscopy, XPS), whereas PE and PVC soot exhibited the highest absorption peaks of aliphatic C-H groups (Fourier transform infrared spectroscopy, FTIR). Comparative analysis revealed that the interlayer distance was more important on the evaluation of reactivity than soot morphologies. The present work concluded that the physiochemical characteristics of soot particles releasing during open burning are strongly depending on waste composition and provided new data for the understanding of soot emissions from open burning.

A novel 100% aqueous solution near-infrared ratiometric fluorescent CN- probe based on 1,4-dihydropyridines, with a large fluorescent emission peak shift

1,4-Dihydropyridines are a class of drugs with a wide range of biological activities and pharmacological effects. However, there are few reports on its optical activity, especially its application on fluorescent CN^- probe. In this experiment, we designed and synthesized a fluorescent probe based on 1,4-dihydropyridines to detect CN^-. Interestingly, the probe exhibited outstanding properties such as 100% water soluble, near infrared, ratiometric, fast response, high selectivity and anti-interference ability for other ions. The color change indicated that the probe can be used for naked eye identification. In particular, the probe showed a super large fluorescent emission peak shift (260 nm). In addition, the reaction mechanism of the probe has been studied by ¹H NMR titration, high resolution mass spectrometry and theoretical calculations.