Inhalation of particulate matter (PM) present in indoor atmospheres has been associated with poor health and wellbeing of occupants. Here we report the characteristics of airborne PM collected from ...twenty-two air-conditioned childcare centres in Singapore. Airborne PM were collected using cascade impactors and characterized for morphology, elemental composition, endotoxin levels, ability to generate abiotic reactive oxygen species, and oxidative stress-dependent cytotoxicity in BEAS-2B cell lines. The mass concentrations of ultrafine particles (PM0.06-1) were more abundant than that of larger particles (PM1-4, PM4-20, and PM20-35 particles). PM20-35 and PM4-20 were irregularly shaped particles, PM1-4 particles had membranous flaky structures and PM0.06-1 particles were pseudo-spherical with the occasional presence of crystalline structures. Carbonaceous matter dominated PM20-35 particles, and the abundance of inorganic salts, iron and sulfur increased with decreasing PM size. Measured endotoxin levels were especially higher in PM4-20 particles. Compared to other particle size fractions, PM0.06-1 particles generated the highest ROS and were also the most potent in generating intracellular ROS in BEAS-2B cell lines. However, total mass concentrations, elemental compositions, abiotic responses, and PM collected from centres with split air-conditioning systems and no active outdoor air supply (SAC) were not statistically different compared with PM collected from centres with air conditioning with mechanical ventilation (ACMV). In conclusion, our study showed obvious distinctions in mass concentrations, morphology, elemental compositions, and cytotoxic potential of different sized particles collected from childcare centres, where the smallest particles (PM0.06-1) exhibited higher hazard potential.
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•Collection and characterization of particulate matter (PM) from indoor atmospheres of childcare centres•The mass concentrations of ultrafine particles (PM0.06-1) were higher than that of larger particles.•Endotoxin levels were highest in PM4-20 particles, while carbonaceous matter dominated PM20-35 particles.•PM0.06-1 particles generated the highest ROS compared to other particle size fractions.•A dose-dependent increase in inflammatory potential was observed for PM1-4 and PM0.06-0.25 particles.
Surveys of carbon:nitrogen:phosphorus ratios are available now for major groups of biota and for various aquatic and terrestrial biomes. However, while fungi play an important role in nutrient ...cycling in ecosystems, relatively little is known about their C:N:P stoichiometry and how it varies across taxonomic groups, functional guilds, and environmental conditions. Here we present the first systematic compilation of C:N:P data for fungi including four phyla (Ascomycota, Basidiomycota, Glomeromycota, and Zygomycota). The C, N, and P contents (percent of dry mass) of fungal biomass varied from 38 to 57%, 0.23 to 15%, and 0.040 to 5.5%, respectively. Median C:N:P stoichiometry for fungi was 250:16:1 (molar), remarkably similar to the canonical Redfield values. However, we found extremely broad variation in fungal C:N:P ratios around the central tendencies in C:N:P ratios. Lower C:P and N:P ratios were found in Ascomycota fungi than in Basidiomycota fungi while significantly lower C:N ratios (
< 0.05) and higher N:P ratios (
< 0.01) were found in ectomycorrhizal fungi than in saprotrophs. Furthermore, several fungal stoichiometric ratios were strongly correlated with geographic and abiotic environmental factors, especially latitude, precipitation, and temperature. The results have implications for understanding the roles that fungi play in function in symbioses and in soil nutrient cycling. Further work is needed on the effects of actual
growth conditions of fungal growth on stoichiometry in the mycelium.
Atmospheric particulates were sampled in Hefei City, China from October 2016 to January 2017 to compare chemical compositions and sources of PM2.5 (particle size smaller than 2.5 μm) and PM10 ...(particle size smaller than 10 μm). The mean levels of PM2.5 and PM10 were 81 and 109 μg/m3, which are higher than the health threshold levels regulated by national and international standards. During the sampling period, AQI (Air Quality Index) was strongly correlated with PM2.5 (Pearson's coefficient r = 0.94) rather than PM10 concentrations. The PM2.5/PM10 ratios were approximately 0.7, revealing the characteristics of fine particle pollution. Pollution elements (S, Zn, Cu and Pb) took up a large proportion of the composition and had high enrichment factors of 437, 385, 20 and 53, respectively, in PM10. Coal combustion and high-tech manufacture industry discharges were suggested to be the main pollution sources of both PM2.5 and PM10. The PM2.5/PM10 ratios of anthropogenic element concentrations were much higher than ratios of earth crust element. As compared to PM10, S and Pb in PM2.5 had larger EFs, indicating that pollution elements were predominantly enriched in PM2.5. Furthermore, a paired sample t-test confirmed similar sources of PM2.5 and PM10. Our study provides basic database to evaluate the heavy metal pollution status of atmospheric particulates in Chinese cities.
•PM in Hefei showed severe level of pollution arising from industry and fuel burning.•PM2.5 than PM10 were identified as prime carriers of atmospheric pollutants.•The correlation analysis, cluster analysis and paired t-test were used.
Dust storms have great impacts on air quality and climate. Dust can influence cloud microphysical properties and determine their radiative forcing and precipitation. Asian dust storms (ADS) are ...important sources of global aerosol. However, the physiochemical characteristics of dust from ADS at a single particle level are less understood, and the exact particles that can serve as ice nucleating particles (INPs) remain unclear. Here, we present the physicochemical properties and ice nucleation ability of dust particles collected in Beijing during two major ADS in March 2021. The particles from two ADS were classified into Illite, Kaolinite, Feldspar, Quartz, Chlorite, Mixed-dust, and Non-dust particles, which contributed 28.6 % ± 3.3 %, 20.0 % ± 3.9 %, 12.3 % ± 2.3 %, 11.1 % ± 2.8 %, 9.8 % ± 0.8 %, 13.7 % ± 1.8 %, and 4.4 % ± 1.7 % in number, respectively. On average, the ADS particles formed ice crystals via deposition ice nucleation from relative humidity with respect to ice (RHice) of 112 % ± 1 % at 250 K to 154 % ± 15 % RHice at 205 K. Part of the samples also formed ice via immersion freezing between 230 K and 250 K. Among the 149 identified INPs, Clay-like particles (Chlorite, Illite, and Kaolinite) contributed 71.1 % ± 6.2 % in number and followed by Mixed-dust-like particles (16.9 % ± 8.7 %) and Feldspar-like particles (10.4 % ± 6.3 %). Enrichment factor for each particle type is calculated as the ratio of its number fractions in INPs and the aerosol population. It ranges from 0.6 ± 0.7 to 1.3 ± 2.2. The contribution of each particle type to INP was correlated with its fraction in the population. These results imply that each particle type can serve as INP. Clay-like particles are the dominant INPs during the ADS. We conducted ice nucleation kinetic analysis and provided parameterizations of heterogeneous ice nucleation rate coefficient and contact angle for ADS. These parameterizations can be used in the modeling study to evaluate the impact of ADS in atmospheric ice crystal formation in clouds.
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•Clay, Feldspar, and Quartz contribute 58 %, 12 %, and 11 % in number, respectively.•Asian dust particles can form ice via deposition nucleation and immersion freezing.•INP contribution of each particle type correlates to its fraction in the population.
Element constitution and distribution in tissues and body fluids have increasingly become key pieces of information in life sciences and medicine, and trace elements may be successfully used as ...disease biomarkers. Here, we review the most recent advances in inductively coupled plasma mass spectrometry (ICP-MS) and the related state-of-the-art instrumentation and methods (e.g. single-particle and single-cell determination capabilities) used to expand the application of trace element information to the study of diseases. Advanced statistical tools and machine learning used for evaluating, diagnosing, and treating different diseases has highlighted the importance of trace elements in clinical research. In this manuscript, we review recently published studies involving trace element analysis and machine learning applied to better understanding clinical conditions and pathologies, and discuss some perspectives for this field.
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•The state-of-the-art of trace elemental analysis in tissues and body fluids is reviewed.•The most recent developments in ICP-MS instrumentation are discussed.•Single-cell and single-particle ICP-MS methods enable analysis at cell level.•Advances in elemental distribution imaging enhance medical research.•Statistical tools combined with elemental composition used for disease modeling.
In medium/high entropy alloys, their mechanical properties are strongly dependent on the chemical-elemental composition. Thus, searching for optimum elemental composition remains a critical issue to ...maximize the mechanical performance. However, this issue solved by traditional optimization process via “trial and error” or experiences of domain experts is extremely difficult. Here we propose an approach based on high-throughput simulation combined machine learning to obtain medium entropy alloys with high strength and low cost. This method not only obtains a large amount of data quickly and accurately, but also helps us to determine the relationship between the composition and mechanical properties. The results reveal a vital importance of high-throughput simulation combined machine learning to find best mechanical properties in a wide range of elemental compositions for development of alloys with expected performance.
Southeast Asia has become a hotspot of anthropogenic particulate matter (PM) emissions due to increased coal combustion, high-temperature industrial operations, vehicular traffic, and agricultural ...biomass burning. Lead (Pb), a criteria pollutant, bound to such PM can be hazardous when inhaled, even at extremely low concentrations. Precise and accurate source apportionment of atmospheric Pb is thus, critical in order to minimize its exposure. This study investigates the sources of atmospheric Pb in Singapore aerosol samples (PM10) using Pb isotopes and elemental composition as tracers of contamination sources. PM10 aerosol sampling was conducted over a period of 1 year from June 2017 to May 2018 to capture the seasonal variations in sources of atmospheric Pb. Elemental concentrations reveal particularly high enrichment factors for Pb, Cu, V, Ni and Zn, especially when under the influence of southwest (SW) and inter monsoon (IM) winds. Pb isotopic ratios across the three seasons (206/207Pb = 1.147˗1.150 and 208/207Pb = 2.420˗2.428) are not significantly different. The Pb isotopic signatures and V/Ni ratios for all three seasons overlap with those of gasoline, diesel and ship emissions. Moreover, V/Pb values of more than unity for SW and IM winds suggest influence of transboundary coal combustion emissions particularly from Indonesia. Consequently, using Pb isotopic fingerprints and elemental ratios, we find that the primary sources of atmospheric Pb are vehicular & ship emissions, heavy oil combustion, transboundary coal combustion emissions, waste incineration and recirculation of historic leaded gasoline.
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•Pb isotope ratios and metal concentrations delineate the sources of atmospheric Pb.•High EFs of Pb in Singapore aerosols of all 3 seasons indicate anthropogenic origin.•Pb isotopic compositions of PM10 are similar across 3 seasons.•Pb sources are car & ship exhaust, coal burning, incineration ash, past leaded fuel.
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