A droplet carrying particle is desolvation, vaporization, ionization, and diffusion in an inductively coupled plasma (ICP) to form a cloud of ions. It then is detected as a mass-spectrum peak of individual particle. T...A droplet carrying particle is desolvation, vaporization, ionization, and diffusion in an inductively coupled plasma (ICP) to form a cloud of ions. It then is detected as a mass-spectrum peak of individual particle. The diameter of the particle is derived from its mass, which is calibrated using the peak area. This is the basic principle of measuring single particles using inductively coupled plasma mass spectrometry (ICP-MS). In this paper, a mathematical model describing single particles in plasma is investigated. This makes it possible to investigate the process and contributing factors of single particles measurement by ICP-MS. A series of processes are investigated, which include increasing the droplet temperature to the boiling point, desolvation of the droplets, increasing the particle temperature to the melting point, the particles are melted from a solid to the liquid, increasing the particle temperature to the boiling point, and particle vaporization. The simulation shows that both the atomic (ion) diffusion in the plasma and the incomplete vaporization of the particles are two important factors that limit the signal intensity of the particle’s mass spectrum. The experiment reveals that ICP-MS is very linear for Ag nanoparticles below 100 nm and SiO2 particles below 1000 nm. Both the simulation and experiment reveal the measurement deviation for large particles and that an increase of sampling depth can extend the diffusion time and cause signal suppression. The model can be used to study the mechanisms of monodispersed droplet or single-particle mass spectrometry, analyze the contributing parameters for single particle measurements by ICP-MS and provide a theoretical base for the optimization of single particle measurements in the practical application, such as nanoparticle devices, magnetic materials, biomedical materials additives and consumer products.展开更多
The real-time detection of the mixing states of polycyclic aromatic hydrocarbons(PAHs)and nitro-PAHs in ambient particles is of great significance for analyzing the source,aging process,and health effects of PAHs and ...The real-time detection of the mixing states of polycyclic aromatic hydrocarbons(PAHs)and nitro-PAHs in ambient particles is of great significance for analyzing the source,aging process,and health effects of PAHs and nitro-PAHs;yet there is still few effective technology to achieve this type of detection.In this study,11 types of PAH and nitro-PAH standard sampleswere analyzed using a high performance-single particle aerosolmass spectrometer(HP-SPAMS)in lab studies.The identification principles‘parent ions’and‘mass-to-charge(m/z)=77’of each compound were obtained in this study.It was found that different laser energies did not affect the identification of the parent ions.The comparative experiments of ambient atmospheric particles,cooking and biomass burning emitted particles with and without the addition of PAHs were conducted and ruled out the interferences from primary and secondary organics on the identification of PAHs.Besides,the reliability of the characteristic ions extraction method was evaluated through the comparative study of similarity algorithm and deep learning algorithm.In addition,the real PAH-containing particles from vehicle exhaust emissions and ambient particles were also analyzed.This study improves the ability of single particle mass spectrometry technology to detect PAHs and nitro-PAHs,and HP-SPAMS was superior to SPAMS for detecting single particles containing PAHs and nitro-PAHs.This study provides support for subsequent ambient observations to identify the characteristic spectrum of single particles containing PAHs and nitro-PAHs.展开更多
Surface-active organic molecules(surfactants)may influence the ability of an aerosol particle to act as a cloud condensation nuclei by reducing its surface tension.One source of organic mass in aerosol particles,which...Surface-active organic molecules(surfactants)may influence the ability of an aerosol particle to act as a cloud condensation nuclei by reducing its surface tension.One source of organic mass in aerosol particles,which may also contain surfactants,is bubble bursting on the sea surface.In order to directly compare these molecules in the ocean and aerosol particles,we developed a method using multiple solid phase extractions and high resolution mass spectrometry to characterize surface active organic molecules in both.This method has extraction efficiencies greater than 85%,75%,and 60%for anionic,cationic,and nonionic surfactant standards,respectively.In this study,we demonstrate the presence of three ionic classes of surface active organics in atmospheric aerosol particles and estuarine water from Skidaway Island,GA.With this extraction method,organic molecules from both estuarine water and atmospheric aerosol particles significantly reduced surface tension of pure water(surface tension depression of~18 m N/m)and had high ratios of hydrogen to carbon(H/C)and low ratios of oxygen to carbon(O/C),indicative of surfactants.While previous work has observed a larger fraction of anionic surface active organics in seawater and marine aerosol particles,here we show cationic surface active organics may make up a large fraction of the total surface active molecules in estuarine water(43%–47%).展开更多
To investigate the composition and possible sources of particles, especially during heavy haze pollution, a single particle aerosol mass spectrometer（SPAMS） was deployed to measure the changes of single particle spe...To investigate the composition and possible sources of particles, especially during heavy haze pollution, a single particle aerosol mass spectrometer（SPAMS） was deployed to measure the changes of single particle species and sizes during October of 2014, in Beijing. A total of 2,871,431 particles with both positive and negative spectra were collected and characterized in combination with the adaptive resonance theory neural network algorithm（ART-2a）. Eight types of particles were classified： dust particles（dust, 8.1%）, elemental carbon（EC, 29.0%）, organic carbon（OC, 18.0%）, EC and OC combined particles（ECOC, 9.5%）,Na-K containing particles（Na K, 7.9%）, K-containing particles（K, 21.8%）, organic nitrogen and potassium containing particles（KCN, 2.3%）, and metal-containing particles（metal,3.6%）. Three haze pollution events（P1, P2, P3） and one clean period（clean） were analyzed,based on the mass and number concentration of PM_（2.5）and the back trajectory results from the hybrid single particle Lagrangian integrated trajectory model（Hysplit-4 model）. Results showed that EC, OC and K were the major components of single particles during the three haze pollution periods, which showed clearly increased ratios compared with those in the clean period. Results from the mixing state of secondary species of different types of particles showed that sulfate and nitrate were more readily mixed with carbon-containing particles during haze pollution episodes than in clean periods.展开更多
Single particle-inductively coupled plasma mass spectrometry (SP-ICP-MS) is a powerful tool for size-characterization of metal-containing nanoparticles (MCNs) at environmentally relevant concentrations,however,coexist...Single particle-inductively coupled plasma mass spectrometry (SP-ICP-MS) is a powerful tool for size-characterization of metal-containing nanoparticles (MCNs) at environmentally relevant concentrations,however,coexisting dissolved metal ions greatly interfere with the accuracy of particle size analysis.The purpose of this study is to develop an online technique that couples hollow fiber ultrafiltration (HFUF) with SP-ICP-MS to improve the accuracy and size detection limit of MCNs by removing metal ions from suspensions of MCNs.Through systematic optimization of conditions including the type and concentration of surfactant and complexing agent,carrier pH,and ion cleaning time,HFUF completely removes metal ions but retains the MCNs in suspension.The optimal conditions include using a mixture of 0.05 vol.%FL-70 and 0.5 mmol/L Na2S2O_(3)(pH=8.0) as the carrier and 4 min as the ion cleaning time.At these conditions,HFUF-SP-ICP-MS accurately determines the sizes of MCNs,and the results agree with the size distribution determined by transmission electron microscopy,even when metal ions also are present in the sample.In addition,reducing the ionic background through HFUF also lowers the particle size detection limit with SP-ICP-MS (e.g.,from 28.3 to 14.2 nm for gold nanoparticles).This size-based ion-removal principle provided by HFUF is suitable for both cations (e.g.,Ag+) and anions (e.g.,AuCl_(4)^(-)) and thus has good versatility compared to ion exchange purification and promising prospects for the removal of salts and macromolecules before single particle analysis.展开更多
文摘A droplet carrying particle is desolvation, vaporization, ionization, and diffusion in an inductively coupled plasma (ICP) to form a cloud of ions. It then is detected as a mass-spectrum peak of individual particle. The diameter of the particle is derived from its mass, which is calibrated using the peak area. This is the basic principle of measuring single particles using inductively coupled plasma mass spectrometry (ICP-MS). In this paper, a mathematical model describing single particles in plasma is investigated. This makes it possible to investigate the process and contributing factors of single particles measurement by ICP-MS. A series of processes are investigated, which include increasing the droplet temperature to the boiling point, desolvation of the droplets, increasing the particle temperature to the melting point, the particles are melted from a solid to the liquid, increasing the particle temperature to the boiling point, and particle vaporization. The simulation shows that both the atomic (ion) diffusion in the plasma and the incomplete vaporization of the particles are two important factors that limit the signal intensity of the particle’s mass spectrum. The experiment reveals that ICP-MS is very linear for Ag nanoparticles below 100 nm and SiO2 particles below 1000 nm. Both the simulation and experiment reveal the measurement deviation for large particles and that an increase of sampling depth can extend the diffusion time and cause signal suppression. The model can be used to study the mechanisms of monodispersed droplet or single-particle mass spectrometry, analyze the contributing parameters for single particle measurements by ICP-MS and provide a theoretical base for the optimization of single particle measurements in the practical application, such as nanoparticle devices, magnetic materials, biomedical materials additives and consumer products.
基金financially supported by the Key-Area Research and Development Program of Guangdong Province (No. 2020B1111360001)the National Natural Science Foundation of China (NSFC) (No. 41805093, 41827804)+3 种基金the NSFC of Guangdong Province (No. 2021A1515011206)the National Key Research and Development Program of China (No. 2016YFC0200105)Guangdong Special Support Program (No. 2019BT02Z546, 2019TQ05L169)the Guangdong Enterprise Science and Technology Commissioner Project (No. GDKTP2020035200)
文摘The real-time detection of the mixing states of polycyclic aromatic hydrocarbons(PAHs)and nitro-PAHs in ambient particles is of great significance for analyzing the source,aging process,and health effects of PAHs and nitro-PAHs;yet there is still few effective technology to achieve this type of detection.In this study,11 types of PAH and nitro-PAH standard sampleswere analyzed using a high performance-single particle aerosolmass spectrometer(HP-SPAMS)in lab studies.The identification principles‘parent ions’and‘mass-to-charge(m/z)=77’of each compound were obtained in this study.It was found that different laser energies did not affect the identification of the parent ions.The comparative experiments of ambient atmospheric particles,cooking and biomass burning emitted particles with and without the addition of PAHs were conducted and ruled out the interferences from primary and secondary organics on the identification of PAHs.Besides,the reliability of the characteristic ions extraction method was evaluated through the comparative study of similarity algorithm and deep learning algorithm.In addition,the real PAH-containing particles from vehicle exhaust emissions and ambient particles were also analyzed.This study improves the ability of single particle mass spectrometry technology to detect PAHs and nitro-PAHs,and HP-SPAMS was superior to SPAMS for detecting single particles containing PAHs and nitro-PAHs.This study provides support for subsequent ambient observations to identify the characteristic spectrum of single particles containing PAHs and nitro-PAHs.
基金supported by the University of Georgia Investment in Sciences Initiative and Office of Researchthe University of Georgia Junior Faculty Seed Grant。
文摘Surface-active organic molecules(surfactants)may influence the ability of an aerosol particle to act as a cloud condensation nuclei by reducing its surface tension.One source of organic mass in aerosol particles,which may also contain surfactants,is bubble bursting on the sea surface.In order to directly compare these molecules in the ocean and aerosol particles,we developed a method using multiple solid phase extractions and high resolution mass spectrometry to characterize surface active organic molecules in both.This method has extraction efficiencies greater than 85%,75%,and 60%for anionic,cationic,and nonionic surfactant standards,respectively.In this study,we demonstrate the presence of three ionic classes of surface active organics in atmospheric aerosol particles and estuarine water from Skidaway Island,GA.With this extraction method,organic molecules from both estuarine water and atmospheric aerosol particles significantly reduced surface tension of pure water(surface tension depression of~18 m N/m)and had high ratios of hydrogen to carbon(H/C)and low ratios of oxygen to carbon(O/C),indicative of surfactants.While previous work has observed a larger fraction of anionic surface active organics in seawater and marine aerosol particles,here we show cationic surface active organics may make up a large fraction of the total surface active molecules in estuarine water(43%–47%).
基金supported by the National Natural Science Foundation of China (No.41205115)
文摘To investigate the composition and possible sources of particles, especially during heavy haze pollution, a single particle aerosol mass spectrometer（SPAMS） was deployed to measure the changes of single particle species and sizes during October of 2014, in Beijing. A total of 2,871,431 particles with both positive and negative spectra were collected and characterized in combination with the adaptive resonance theory neural network algorithm（ART-2a）. Eight types of particles were classified： dust particles（dust, 8.1%）, elemental carbon（EC, 29.0%）, organic carbon（OC, 18.0%）, EC and OC combined particles（ECOC, 9.5%）,Na-K containing particles（Na K, 7.9%）, K-containing particles（K, 21.8%）, organic nitrogen and potassium containing particles（KCN, 2.3%）, and metal-containing particles（metal,3.6%）. Three haze pollution events（P1, P2, P3） and one clean period（clean） were analyzed,based on the mass and number concentration of PM_（2.5）and the back trajectory results from the hybrid single particle Lagrangian integrated trajectory model（Hysplit-4 model）. Results showed that EC, OC and K were the major components of single particles during the three haze pollution periods, which showed clearly increased ratios compared with those in the clean period. Results from the mixing state of secondary species of different types of particles showed that sulfate and nitrate were more readily mixed with carbon-containing particles during haze pollution episodes than in clean periods.
基金supported by the National Key Research and Development Project (No.2020YFA0907400)Strategic Priority Research Program of the Chinese Academy of Sciences (No.XDPB2005)+2 种基金National Natural Science Foundation of China(No.21777178)the National Young Top-Notch Talents (No.W03070030)Youth Innovation Promotion Association of the Chinese Academy of Sciences (No.Y202011)。
文摘Single particle-inductively coupled plasma mass spectrometry (SP-ICP-MS) is a powerful tool for size-characterization of metal-containing nanoparticles (MCNs) at environmentally relevant concentrations,however,coexisting dissolved metal ions greatly interfere with the accuracy of particle size analysis.The purpose of this study is to develop an online technique that couples hollow fiber ultrafiltration (HFUF) with SP-ICP-MS to improve the accuracy and size detection limit of MCNs by removing metal ions from suspensions of MCNs.Through systematic optimization of conditions including the type and concentration of surfactant and complexing agent,carrier pH,and ion cleaning time,HFUF completely removes metal ions but retains the MCNs in suspension.The optimal conditions include using a mixture of 0.05 vol.%FL-70 and 0.5 mmol/L Na2S2O_(3)(pH=8.0) as the carrier and 4 min as the ion cleaning time.At these conditions,HFUF-SP-ICP-MS accurately determines the sizes of MCNs,and the results agree with the size distribution determined by transmission electron microscopy,even when metal ions also are present in the sample.In addition,reducing the ionic background through HFUF also lowers the particle size detection limit with SP-ICP-MS (e.g.,from 28.3 to 14.2 nm for gold nanoparticles).This size-based ion-removal principle provided by HFUF is suitable for both cations (e.g.,Ag+) and anions (e.g.,AuCl_(4)^(-)) and thus has good versatility compared to ion exchange purification and promising prospects for the removal of salts and macromolecules before single particle analysis.
