Mass spectra features of biomass burning boiler and coal burning boiler emitted particles by single particle aerosol mass spectrometer

Insights into the seasonal characteristics of single particle aerosols in Chengdu based on SPAMS

To investigate the seasonal characteristics in air pollution in Chengdu, a single particle aerosol mass spectrometry was used to continuously observe atmospheric fine particulate matter during one-month periods in summer and winter, respectively. The results showed that, apart from O3, the concentrations of other pollutants (CO, NO2, SO2, PM2.5 and PM10) were significantly higher in winter than in summer. All single particle aerosols were divided into seven categories: biomass burning (BB), coal combustion (CC), Dust, vehicle emission (VE), K mixed with nitrate (K-NO3), K mixed with sulfate and nitrate (K-SN), and K mixed with sulfate (K-SO4) particles. The highest contributions in both seasons were VE particles (24%). The higher contributions of K-SO4 (16%) and K-NO3 (10%) particles occurred in summer and winter, respectively, as a result of their different formation mechanisms. S-containing (K-SO4 and K-SN), VE, and BB particles caused the evolution of pollution in both seasons, and they can be considered as targets for future pollution reduction. The mixing of primary sources particles (VE, Dust, CC, and BB) with secondary components was stronger in winter than in summer. In summer, as pollution worsens, the mixing of primary sources particles with 62 [NO3]- weakened, but the mixing with 97 [HSO4]- increased. However, in winter, the mixing state of particles did not exhibit an obvious evolution rules. The potential source areas in summer were mainly distributed in the southern region of Sichuan, while in winter, besides the southern region, the contribution of the western region cannot be ignored.

Unequal toxic effects of size-segregated single particles emitted from typical industrial plants, vehicles, and road dust

The health risks of particulate matters (PMs) associated with their chemical components and sizes have attracted increasing attention. However, the toxic effect of critical toxic components in size-segregated PMs from specific emission source remains unclear. We present the toxicity of size-segregated elements in PMs via integrating toxic analysis and online single-particle measurements of real-world industrial plants, vehicles, and road dust. The number fractions of elemental carbon (EC)- and Fe-containing particles were 5-11 and 3-12 folds greater than those of other metal-containing particles, respectively. A unimodal distribution with the peak at 0.4 µm was observed for the toxic metals emitted from industrial plants and road dust, while the distribution was relatively flat for vehicles. When integrating the abundance with toxicity of metals, especially Mn, Cu, V, and Fe, the peak for PM toxicity occurred at 0.4 µm for road dust, 0.4-0.7 µm for industrial plants, and 0.8 µm for vehicle-emitted PM. The inhalation risk in the alveolar region increased for these source-emitted PMs due to the efficient deposition of toxic PMs within 0.4-0.8 µm. These results reveal the complex coupling of health risks and size distributions of PMs, and further highlight that the health-oriented control of air pollution should consider PM1.

Mapping the constituent preference of tree species for capturing particulate matter on leaf surfaces using single-particle mass spectrometry and supervised machine learning

Respiratory health is negatively influenced by the dimensions and constituents of particulate matter (PM). Although mass concentration is widely acknowledged to be key to assessing dust retention by urban trees, the role of plant leaves in filtering PM from the urban atmosphere, particularly regarding the particle dimensions and chemical constituents of retained PM on the leaf, remains elusive. Here we combined single-particle aerosol mass spectrometry and a particle resuspension chamber to investigate how urban tree species capture PM constituents. Results indicate that leaves are efficient in capturing relatively larger particles (1.0-2.0 μm). Compositionally, airborne particles were mostly composed of elemental carbon (EC, 20%), organic carbon (OC, 17%), and secondary reaction products (13%). However, leaf surfaces revealed a preference for retaining crustal species, comprising 55% of captured particulates. Notably, specific tree species demonstrated varied affinities for different PM constituents: Osmanthus fragrans Lour. predominantly captured levoglucosan (LEV), indicative of its efficiency against biomass burning particles, whereas Cinnamomum camphora (L.) J.Presl and Sabina chinensis var. kaizuca W.C.Cheng & W.T.Wang were more effective in capturing heavy metals (HMs). XGBoost modelling identified indicator ions, e.g., CN-, NO3-, NO2-, PO3-, with SHAP values surpassing 0.035, suggesting a preferential adsorption of these ions among different tree species. These findings demonstrate that the particulate capture efficiency of urban tree species varies with species-specific leaf properties, particularly in their ability to selectively adsorb particles containing hazardous constituents such as LEV and HMs. This study provides a scientific basis for the strategic selection of tree species in urban forestry initiatives aimed at improving air quality and public health.

Selective capture of PM2.5 by urban trees: The role of leaf wax composition and physiological traits in air quality enhancement

Human health risks from particles with a diameter of less than 2.5 µm (PM2.5) highlight the role of urban trees as bio-filters in air pollution control. However, whether the size and composition of particles captured by various tree species differ or not remain unclear. This study investigates how leaf attributes affect the capture of PM2.5, which can penetrate deep into the lungs and pose significant health risks. Using a self-developed particulate matter (PM) resuspension chamber and single-particle aerosol mass spectrometer, we measured the size distribution and mass spectra of particles captured by ten tree species. Notably, Cinnamomum camphora (L.) J.Presl and Osmanthus fragrans Lour. are more effective at capturing particles under 1 µm, which are most harmful because they can reach the alveoli, whereas Ginkgo biloba L. and Platanus × acerifolia (Aiton) Willd. tend to capture larger particles, up to 1.6 µm, which are prone to being trapped in the upper respiratory tract. Leaf physiological traits such as stomatal conductance and water potential significantly enhance the capture of larger particles. The Adaptive Resonance Theory neural network (ART-2a) algorithm classified a large number of single particles to determine their composition. Results indicate distinct inter-species variations in chemical composition of particles captured by leaves. Moreover, we identified how specific leaf wax compositions-beyond the known sticky nature of hydrophobic waxes-contribute to particle adhesion, particularly highlighting the roles of fatty acids and alkanes in adhering particles rich in organic carbon and heavy metals, respectively. This research advances our understanding by linking leaf physiological and wax characteristics to the selective capture of PM2.5, providing actionable insights for urban forestry management. The detailed exploration of particle size and composition, tied to specific tree species, enriches the current literature by quantifying how and why different species contribute variably to air quality improvement. This adds a crucial layer of specificity to the general knowledge that trees serve as bio-filters, offering a refined strategy for planting urban trees based on their particulate capture profiles.

Characterizing leaf-deposited particles: Single-particle mass spectral analysis and comparison with naturally fallen particles

The size and composition of particulate matter (PM) are pivotal in determining its adverse health effects. It is important to understand PM's retention by plants to facilitate its atmospheric removal. However, the distinctions between the size and composition of naturally fallen PM (NFPM) and leaf-deposited PM (LDPM) are not well-documented. Here we utilize a single-particle aerosol mass spectrometer, coupled with a PM resuspension chamber, to analyze these differences. We find that LDPM particles are 6.8-97.3 % larger than NFPM. Employing a neural network algorithm based on adaptive resonance theory, we have identified distinct compositional profiles: NFPM predominantly consists of organic carbon (OC; 31.2 %) and potassium-rich components (19.1 %), whereas LDPM are largely composed of crustal species (53.9-60.6 %). Interestingly, coniferous species retain higher OC content (11.5-13.7 %) compared to broad-leaved species (0.5-1.2 %), while the levoglucosan content exhibit an opposite trend. Our study highlights the active role of tree leaves in modifying PM composition beyond mere passive capture, advocating for a strategic approach to species selection in urban greening initiatives to enhance PM mitigation. These insights provide guidance for urban planners and environmentalists in implementing nature-based solutions to improve urban air quality.

Microscopic Characterization of Individual Aerosol Particles in a Typical Industrial City and Its Surrounding Rural Areas in China

Transmission electron microscopy was used to analyze individual aerosol particles collected in Lanzhou (urban site) and its surrounding areas (rural site) in early 2023. The results revealed that from the pre-Spring Festival period to the Spring Festival period, the main pollutants at the urban site decreased significantly, while the PM2.5 and SO2 concentrations increased at the rural site. During the entire sampling period, the main particles at the urban site were organic matter (OM), secondary inorganic aerosols (SIA), and OM-SIA particles, while those at the rural site were OM, SIA, and soot particles. The degree of external mixing of single particles in both sites increased from the pre-Spring Festival period to the Spring Festival period. The proportion of the OM particles increased by 11% at the urban site, and the proportion of SIA particles increased by 24% at the rural site. During the Spring Festival, the aging of the soot particles was enhanced at the urban site and weakened at the rural site. At the urban site, the SIA particle size was more strongly correlated with the thickness of the OM coating during the pre-Spring Festival period, while the correlation was stronger at the rural site during the Spring Festival.

Brake wear-derived particles: Single-particle mass spectral signatures and real-world emissions

Brake wear is an important but unregulated vehicle-related source of atmospheric particulate matter (PM). The single-particle spectral fingerprints of brake wear particles (BWPs) provide essential information for understanding their formation mechanism and atmospheric contributions. Herein, we obtained the single-particle mass spectra of BWPs by combining a brake dynamometer with an online single particle aerosol mass spectrometer and quantified real-world BWP emissions through a tunnel observation in Tianjin, China. The pure BWPs mainly include three distinct types of particles, namely, Ba-containing particles, mineral particles, and carbon-containing particles, accounting for 44.2%, 43.4%, and 10.3% of the total BWP number concentration, respectively. The diversified mass spectra indicate complex BWP formation pathways, such as mechanical, phase transition, and chemical processes. Notably, the mass spectra of Ba-containing particles are unique, which allows them to serve as an excellent indicator for estimating ambient BWP concentrations. By evaluating this indicator, we find that approximately 4.0% of the PM in the tunnel could be attributable to brake wear; the real-world fleet-average emission factor of 0.28 mg km^-1 veh^-1 is consistent with the estimation obtained using the receptor model. The results presented herein can be used to inform assessments of the environmental and health impacts of BWPs to formulate effective emissions control policies.

Ambient particle characteristics by single particle aerosol mass spectrometry at a coastal site in Hong Kong: a case study affected by the sea-land breeze

The sea-land breeze (SLB) circulation plays a vital role in the transport of atmospheric pollutants in coastal cities. In this study, a single particle aerosol mass spectrometer (SPAMS) and combined bulk aerosol instruments were deployed to investigate the ambient particle characteristic at a suburban coastal site in Hong Kong from February 22 to March 10, 2013. Significant SLB circulations were captured from March 6-10, 2013, during the campaign. During the SLB periods, air quality worsened, with PM_2.5 concentrations reaching a peak of 55.6 μg m^-3 and an average value of 42.8 ± 4.5 μg m^-3. A total of 235,894 particles were measured during the SLB stage. Eight major sources were identified by investigating the mixing states of the total particles, including the coal-burning related particles (48.1%), biomass burning particles (6.7%), vehicle emission-related particles (16.4%), sea salt (9.2%), ship emission particles (2.7%), dust/steeling industries (3.7%), waste incineration (6.3%), and road dust (3.9%). It was noteworthy that the PM_2.5 concentrations and particle numbers increased sharply during the transition of land wind to the sea breeze. Meanwhile, the continental sourced pollutants recirculated back to land resulting in a cumulative increase in pollutants. Both individual and bulk measurements support the above results, with high contributions from coal burning, biomass burning, bulk K⁺, and NO₃ ^-, which were probably from the regional transportation from the nearby area. In contrast, the ship and vehicle emissions increased during the SLB period, with a high sulfate concentration partially originating from the ship emission. In this study, field evidence of continental-source pollutants backflow to land with the evolution of sea breeze was observed and helped our current understanding of the effect of SLB on air quality in the coastal city.

Influence of Ambient Atmospheric Environments on the Mixing State and Source of Oxalate-Containing Particles at Coastal and Suburban Sites in North China

Photodegradation is a key process impacting the lifetime of oxalate in the atmosphere, but few studies investigated this process in the field due to the complex mixing and sources of oxalate. Oxalate-containing particles were measured via single-particle aerosol mass spectrometry at coastal and suburban sites in Qingdao, a coastal city in North China in the summer of 2016. The mixing state and influence of different ambient conditions on the source and photodegradation of oxalate were investigated. Generally, 6.3% and 12.3% of the total particles (by number) contained oxalate at coastal and suburban sites, respectively. Twelve major types of oxalate-containing particles were identified, and they were classified into three groups. Biomass burning (BB)-related oxalate–K and oxalate–carbonaceous particles were the dominant groups, respectively, accounting for 68.9% and 13.6% at the coastal site and 72.0% and 16.8% at the suburban site. Oxalate–Heavy metals (HM)-related particles represented 14.6% and 9.3% of the oxalate particles at coastal and suburban sites, respectively, which were mainly from industrial emissions (Cu-rich, Fe-rich, Pb-rich), BB (Zn-rich), and residual fuel oil combustion (V-rich). The peak area of oxalate at the coastal site decreased immediately after sunrise, while it increased during the daytime at the suburban site. However, the oxalate peak area of Fe-rich particles at both sites decreased after sunrise, indicating that iron plays an important role in oxalate degradation in both environments. The decay rates (k) of Fe-rich and BB-Fe particles at the coastal site (−0.978 and −0.859 h−1, respectively), were greater than those at the suburban site (−0.512 and −0.178 h−1, respectively), owing to the high-water content of particles and fewer oxalate precursors. The estimated k values of oxalate peak area for different ambient conditions were in the same order of magnitude, which can help establish or validate the future atmospheric models.

Effects of air pollution control devices on volatile organic compounds reduction in coal-fired power plants

Air pollution control devices (APCDs) have been fitted to many coal-fired power plants to decrease the impacts of pollutants generated during coal combustion. APCDs remove conventional pollutants but also decrease volatile organic compound (VOC) emissions. In this study, flue gas samples were collected from different points in seven typical coal-fired power and two industrial boilers, and the VOC concentrations in the flue gas samples were determined by gas chromatography-mass spectrometry (GC-MS). Selective catalytic reduction (SCR) systems and electrostatic precipitators (ESP) can synergistically remove VOCs, the mean removal rate of VOCs by ESP was 42% ± 9%. This was caused by the catalyst in SCR systems and the condensation process in the ESP. Wet flue gas desulfurization (WFGD) affected different VOCs in different ways, increasing the halogenated hydrocarbons and aromatic hydrocarbons concentrations but decreasing the oxygenated VOCs concentrations by 12%. Wet electrostatic precipitators (WESP) increased VOC emissions. By calculating Ozone formation potential (OFP), aromatic hydrocarbons are important contributors to ozone production. The emission factor of the power plant was 0.69 g/GJ, and the Chinese annual emission was about 1.2 × 10⁴ t. VOCs emissions in different regions were affected by factors such as the economy and population. VOC emissions can be decreased by using the most appropriate unit load and improving the VOC removal efficiencies of the APCDs.

Cause analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China

To analyse the cause of the atmospheric PM_2.5 pollution that occurred during the COVID-19 lockdown in Nanning, Guangxi, China, a single particulate aerosol mass spectrometer, aethalometer, and particulate Lidar coupled with monitoring near-surface gaseous pollutants, meteorological conditions, remote fire spot sensing by satellite and backward trajectory models were utilized during 18–24 February 2020. Three haze stages were identified: the pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP). The dominant source of PM_2.5 in the PPP was biomass burning (BB) (40.4%), followed by secondary inorganic sources (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganic sources, which contributed 56.1% of the total PM_2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in the PPP was higher than that in the other two periods. Analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning City could be one of the main factors. A planetary boundary layer-relative humidity-secondary particle matter-particulate matter positive feedback mechanism was employed to elucidate the atmospheric processes in this study. This study highlights the importance of understanding the role of BB, secondary inorganic sources and meteorology in air pollution formation and calls for policies for emission control strategies.

Short-term effects of size-fractionated particulate matters and their constituents on renal function in children: A panel study

Evidence available on the effects of size-fractionated particulate matters and their constituents on children's renal function is lack. We conducted a longitudinal panel study among 144 children aged 4-12 years with up to 3 repeated visits from 2018 to 2019. We estimated the effects of size-fractionated particle number counts (PNCs) and their 13 constituents on estimated glomerular filtration rate (eGFR) over different lag times with linear mixed-effects models and Bayesian kernel machine regression. We found the inverse dose-responsive associations of 3 sizes PNCs with eGFR were the strongest at lag 2 day. Compared to PNC_0.5, PNC₁ and PNC_2.5 showed stronger and similar effects on eGFR reduction. On average, an interquartile range increase in PNC_0.5, PNC₁ and PNC_2.5 were significantly associated with 1.70%, 2.82% and 2.76% decrease in eGFR, respectively. Girls were more susceptible to the toxicity of PNC₁ and PNC_2.5 exposure on eGFR. Several constituents including organic carbon (OC), Mg⁺, PO₃^- and HC₂O₄^- in 3 sizes PNCs were robustly and consistently linked to eGFR reduction at lag 2 day. Moreover, the cumulative effects of different constituents on lower eGFR were significant, when they were all at or above a size-independent threshold (the 60th, 65th, and 70th percentiles in PNC_0.5, PNC₁ and PNC_2.5 constituents, respectively), compared to their median value. And only OC displayed a significantly detrimental effect on eGFR when all the other constituents were fixed at 25th, 50th, and 75th percentiles. In summary, short-term exposure to PNCs were size-dependent related to reduced eGFR in dose-responsive manner among healthy children, and OC might play a more important role in PNC-induced nephrotoxicity than others.

Assessment of sources and pollution state of trace and toxic elements in street dust in a metropolitan city

Street dust and urban soil samples are significant part of environmental compartments to evaluate the contamination levels in urban and industrial zones. This study was carried out to ascertain the concentrations of trace and toxic elements in Izmir street dusts collected from 20 different sites dominating by industrial (four sites), residential (seven sites) and traffic (nine sites) areas, and also to figure out the exposure of adults and children to the elemental toxicity in dust. In order to measure the total and soluble concentrations of elements, the dust samples were analyzed with ICP-MS methodology. The results indicated that concentrations of anthropogenic-based elements are homogenously spread out in whole Izmir city in a similar way to crustal-based elements. This indicates that traffic and residential heating were dominant pollutant sources throughout the city dusts. The health risk assessment showed that elemental non-carcinogenic risks are lower than limit value. However, the cancer risks exceed the acceptable level for As and Cr. According to source apportionment analysis, seven factors were defined for trace elements for all site data.

The characteristics and mixing states of PM2.5 during a winter dust storm in Ningbo of the Yangtze River Delta, China

Dust particulates play an essential role for the nucleation, hygroscopicity and also contribute to aerosol mass. We investigated the chemical composition, size distribution and mixing states of PM_2.5 using a single-particle aerosol mass spectrometer (SPAMS), Monitor for AeRosols and Gases (MARGA), and off-line membrane sampling from 2018.1.24 to 2018.2.20 at a coastal supersite in Ningbo, a port city in Yangtze River Delta, China. During the study campaign, the eastern part of China had experienced a wide range of cooling, sandstorm, and snowfall processes. The entire sampling campaign was categorized into five sub-periods based on the levels of PM_2.5 and the ratios of PM_2.5/PM₁₀, namely clean (T1), heavy pollution (T2), light pollution (T3), dust (sandstorm) (T4) and cleaning pollution (T5) period. After comparing the average mass spectrum for each period, it shows that the primary ions, such as Ca²⁺and SiO₃^-, rarely coexist with each other within a single particle, but secondary ions generally coexist with these primary ions. Furthermore, the coexistence of each two different ions within a particle does not show distinct variation for the whole study periods. All these suggest that the absorption and partitioning of gaseous contaminants into the surface of primary aerosol through heterogeneous reactions are the major pathways of aging and growth of aerosol; and the merging of particles through collisions usually is insignificant. Although the absolute concentrations of nitrate and sulfate all increased with the PM_2.5 concentrations, the relative equivalent concentrations of NO₃^- and SO₄^2- displayed opposite trends; the relative contribution of sulfate decreased and that of nitrate increased as the increase of pollution. During the dust period, the relative equivalent concentrations of calcium and/or potassium ions in PM_2.5 are significantly higher. This study provided deep insights about the mixing states and characteristics of particulate after long-range transport and a visualization tool for aerosol study.

Characteristics of single atmospheric particles in a heavily polluted urban area of China: size distributions and mixing states

To investigate the chemical composition, size distribution, and mixing state of aerosol particles on heavy pollution days, single-particle aerosol mass spectrometry was conducted during 9-26 October 2015 in Xi'an, China. The measured particles were classified into six major categories: biomass burning (BB) particles, K-secondary particles, elemental carbon (EC)-related particles, metal-containing particles, dust, and organic carbon (OC) particles. BB and EC-related particles were the dominant types during the study period and mainly originated from biomass burning, vehicle emissions, and coal combustion. According to the ambient air quality index, two typical episodes were defined: clean days (CDs) and polluted days (PDs). Accumulation of BB particles and EC-related particles was the main reason for the pollution in Xi'an. Most types of particle size were larger on PDs than CDs. Each particle type was mixed with secondary species to different degrees on CDs and PDs, indicating that atmospheric aging occurred. The mixing state results demonstrated that the primary tracers were oxidized or vanished and that the amount of secondary species was increased on PDs. This study provides valuable information and a dataset to help control air pollution in the urban areas of Xi'an. Graphical abstract.

Refined source apportionment of coal combustion sources by using single particle mass spectrometry

In this study, samples of three typical coal combustion source types, including Domestic bulk coal combustion (DBCC), Heat supply station (HSS), and Power plant (PP) were sampled and large sets of their mass spectra were obtained and analyzed by SPAMS during winter in a megacity in China. A primary goal of this study involves determining representative size-resolved single particle mass spectral signatures of three source types that can be used in source apportionment activities. Chemical types describe the majority of the particles of each source type were extracted by ART-2a algorithm with distinct size characteristics, and the corresponding tracer signals were identified. Mass spectral signatures from three source types were different from each other, and the tracer signals were effective in distinguishing different source types. A high size-resolution source apportionment method were proposed in this study through matching sources' mass spectral signatures to particle spectra in a twelve days ambient sampling to source apportion the particles. Contributions of three source types got different size characteristics, as HSS source got higher contribution in smaller sizes, But PP source got higher contributions as size increased. Source contributions were also quantified during two typical haze episodes, and results indicated that HSS source (for central-heating) and DBCC source (for domestic heating and cooking) may contribute evidently to pollution formation.