Frequent low visibility, haze pollution caused by heavy fine particulate matter (PM2.5) loading, has been entailing significant environmental issues and health risks in China since 2013. A ...substantial fraction of bioaerosols was observed in PM (1.5–15%) during haze periods with intensive pollution. However, systematic and consistent results of the variations of bioaerosol characteristics during haze pollution are lacking. The role of bioaerosols in air quality and interaction with environment conditions are not yet well characterized. The present article provides an overview of the state of bioaerosol research during haze episodes based on numerous recent studies over the past decade, focusing on concentration, size distribution, community structure, and influence factors. Examples of insightful results highlighted the characteristics of bioaerosols at different air pollution levels and their pollution effects. We summarize the influences of meteorological and environmental factors on the distribution of bioaerosols. Further studies on bioaerosols, applying standardized sampling and identification criteria and investigating the influence of mechanisms of environmental or pollution factors on bioaerosols as well as the sources of bioaerosols are proposed.
Display omitted
•Understanding the spatial and temporal distribution and dynamic variations of bioaerosols.•Comparing the characteristics of bioaerosols on haze and non-haze days.•Investigating the influences of meteorological and environmental factors on bioaerosols.
This review emphatically discussed the characteristics of bioaerosols during haze episodes in China, as well as influence factors.
Alternative-fueled vehicles have been introduced to solve the problem of the energy crisis and address air pollution. However, typical pollutants (e.g., methane and methanol) are emitted through ...combustion of the alternative fuel. In this study, the concentrations of regulated pollutants (CO, NO) and unregulated pollutants (CH
4
, methanol, formaldehyde, and 8 NMHC species) in the exhaust from methanol, CNG, and gasoline-fueled vehicles (MV, NGV, and GV) were measured systematically on a chassis dynamometer during an in-use vehicle driving cycle. The emission factors of these gaseous pollutants were calculated, and the ozone formation potential (OFP) of each ozone precursor measured in this work was evaluated with the MIR scale. The results showed that NO and NMHC species exhausted from the MV and NGV decreased significantly than that from the GV. However, the unburned pollutants exhausted from MV and NGV warrant attention. For the OFPs, CO was the largest contributor for all tested vehicles. Formaldehyde was ranked the second for the MV and NGV. Among the tested vehicles, the OFPs of NGV were the lowest. The results are helpful in quantitating analysis of the vehicle emissions and evaluating the impacts of alternative-fueled vehicles on atmospheric environment.
Size, morphology, and composition of airborne particles strongly affect human health and visibility, precipitation, and the kinetic characteristics of particles. In this study, the morphology and ...chemical composition of particles emitted from conventional (diesel and gasoline) and alternative (CNG and methanol) fuel vehicles were characterized through scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). The SEM images revealed that the size of primary particles (without agglomeration) was approximately 10 nm in the exhaust from all the tested vehicles. The particles emitted from gasoline vehicle (GV), CNG vehicle (CNGV), and methanol vehicle (MV) had the same median diameter, 62 nm, which was smaller than those from heavy diesel vehicle (HDV) and light diesel vehicle (LDV). Soot was observed in the HDV, LDV, and GV samples but not in the CNGV and MV. The fractal dimension, which was used to quantify the degree of irregularity of soot, was 1.752 ± 0.014, 1.789 ± 0.076, and 1.769 ± 0.006 in the exhaust from HDV, LDV, and GV samples, respectively. The particles discharged by all tested vehicles contained the elements C, O, Fe, and Na. The main element in the samples of HDV, LDV, and GV was C, while O was the main element in the samples of alternative fuel vehicles. The profiles of minor elements were more complex in the emissions of alternative fuel vehicles than those in the emissions of conventional fuel vehicles. The results improved our understanding of the morphology and elemental composition of particles emitted from vehicles powered by diesel, gasoline, CNG, and methanol.
Display omitted
•Spatial autocorrelation and clustering characteristics of city-level PM2.5 levels were observed.•The resonance cycles of PM2.5 concentrations with each influence factor were ...identified.•The influence of long-term driving elements on PM2.5 is quantitatively explored.•LUCC coupled with other factors had a large influence on PM2.5 concentrations.
High-intensity human socioeconomic activities in Xi’an have caused fine particulate matter (PM2.5) pollution. Understanding the spatial and temporal patterns and key factors influencing PM2.5 concentration was the basic step for taking targeted measures. Thus, spatial analysis techniques are used to reveal the temporal and spatial distribution characteristics of PM2.5 in Xi’an over a long time series; wavelet analysis and Geo-detector models are applied to assess the strength of the association between meteorological and socio-economic conditions on PM2.5 concentrations. The results illustrated that the average PM2.5 concentration was 40.13 μg/m3 in 2004 and peaked at 62.06 μg/m3 in 2011, before failing to 38.77 μg/m3 by 2018. The PM2.5 concentration distribution had a characteristic of high in winter and autumn but low in spring and summer, presenting a U-shaped profile. The main distribution of PM2.5 concentrations was oriented in a northeast-southwest direction, with obvious spatial autocorrelation and spatial aggregation characteristics. The resonance cycles of the meteorological and socioeconomic elements and PM2.5 concentrations were synchronous and divergent at different scales. U-wind was the influencing factor on PM2.5 concentration with a positive correlation coefficient of 0.9. Before 2011, the interaction of temperature (Tem) and relative humidity (RH) had the greatest impact on PM2.5 concentrations. Additionally, the land use and cover change (LUCC) coupled with other factors had a large influence on PM2.5 concentrations. These relationships can shed new light on the underlying mechanisms of PM2.5 contamination at the city level, assisting relevant departments in developing effective PM2.5 pollution management strategies.
Chemical compositions of particulate matter (PM) from traffic emissions vary by region and with time. Therefore, it is necessary to obtain local mobile source profiles of PM to support regional ...researches for vehicle emission control policy, source apportionment modeling, etc. In this study, PM_(2.5) and PM_(10) samples were collected from a highway tunnel in Xi’an in northwestern China. The chemical composition, specifically, the OC, EC, water-soluble ions, and elements, was analyzed in detail to (1) provide local PM profiles for a mixed vehicle fleet, (2) identify the origins of different elements in the tunnel environment, and (3) determine the associated factors influencing the profiles. The PM_(2.5) profiles in the tunnel were identified as OC (34.10%), EC (11.96%), water-soluble ions (18.22%), and elements (27.73%), while the PM_(10) profiles included OC (28.48%), EC (8.59%), water-soluble ions (14.17%), and elements (33.36%), respectively. The origins of the elements in the tunnel were classified into three categories by the receptor modeling approach: resuspended road dust and brake wear, vehicle exhaust and tire wear, and tailpipe emissions from diesel vehicles (DV). The mass fractions of OC, EC, and elements originating from resuspended road dust and brake wear were mainly affected by vehicle driving conditions (i.e., uphill/downhill and speed), whereas the mass content of bromine (Br) was influenced by the proportion of DV in the fleet.
Regional atmospheric environmental problems have become increasingly prominent due to continuous urbanization in China. In this study, the Weather Research and Forecasting (WRF) model coupled with ...the California Puff (CALPUFF) air quality model was applied to analyze the spatial distribution and inter-city transport of primary and secondary PM2.5 concentrations from vehicles in the Guanzhong Plain (GZP) in January 2019. The results show that the secondary PM2.5 concentration emitted by vehicles was more easily dispersed than primary PM2.5. The maximum hourly average concentrations of primary PM2.5, secondary inorganic aerosol (SIA), and secondary organic aerosol (SOA) were about 18, 9, and 2 µg/m3, respectively. Exhaust emission and secondary NO3− were the main contributors to the total PM2.5 concentration from vehicles, accounting for about 52% and 32%, respectively. The maximum contribution of vehicle emissions to the ambient PM2.5 concentration was about 19%. Inter-city transport contributed about 33% of the total PM2.5 concentration from vehicles in cities in the GZP on average. Among the PM2.5 components transported in each city, SIA was the most abundant, followed by primary PM2.5, and SOA was the least. These findings will provide valuable insights for mitigating the regional PM2.5 pollution caused by near-surface sources in urban agglomerations.
Biomorphic silicon carbide–mullite ceramics were prepared from beech wood using liquid Si infiltration and molten salts synthesis. The resulting mullite whiskers coating, as well as the growth ...mechanism in molten Al2(SO4)3–Na2SO4 environment, have been investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR) techniques. The biomorphic SiC ceramics derived from the beech wood template have coarse pore walls consisting of β-SiC grains with diameters ranging from 5 μm to 20 μm. After the molten salts reactions between biomorphic SiC substrate and mixture molten salts (Al2(SO4)3–Na2SO4), porous Silicon carbide–mullite ceramics with cilia-like microstructure were obtained. This unique structure has potential application in hot gases filters. An oxidation–dissolution cycle was proposed to explain the mullite whiskers growth in molten salts environment.
Biomorphic silicon carbide–mullite ceramics with cilia-like microstructure prepared from beech wood using liquid Si infiltration (LSI) and molten salts reactions (MSR) processes. Mullite whiskers with nanometer-sized diameters and micrometer-sized lengths grow on the surface of SiC substrate, and the biomorphic silicon carbide–mullite ceramics inherit the porous microstructure originated from biomorphic SiC ceramics and beech wood. The mullite whiskers grow on the pores' surface of biomorphic SiC to form cilia-like surface, and this special structure can be used for hot gases filter. Display omitted
•Biomorphic silicon carbide–mullite ceramics were prepared.•An oxidation–dissolution mechanism was proposed to explain the coating formation.•The unique structure has potential application in hot gases filter.
With the rapid increase of the vehicle population in the Guanzhong Plain (GZP), the fine particulate matter (PM2.5) emitted by vehicles has an impact on regional air quality and public health. The ...spatial distribution of primary and secondary PM2.5 concentrations from vehicles in GZP in January and July 2017 was simulated in this study by using the Weather Research and Forecasting (WRF) model and the California Puff (CALPUFF) air quality model. The contributions of vehicle-related emission sources to total PM2.5 concentrations were also calculated. The results show that although the emissions of primary PM2.5, NOx, and SO2 in July were greater than those in January, the hourly average concentrations of primary and secondary PM2.5 in January were significantly higher than those in July. The highest concentrations of primary and total PM2.5 were mostly located in the urban areas of Xi’an and Xianyang in the central region of GZP. The contributions of exhaust emissions, secondary nitrates, brake wear, tire wear, and secondary sulfate to the total PM2.5 concentrations in GZP were 50.37%, 34.76%, 10.79%, 4.06%, and 0.04% in January and 71.91%, 11.14%, 11.89%, 5.03%, and 0.03% in July, respectively. These results will help us to further control PM2.5 pollution caused by vehicles.
Serious air pollution events have frequently occurred in China associated with the acceleration of urbanization and industrialization in recent years. Exposure to atmospheric particulate matter (PM) ...of high concentration can lead to adverse effects on human health. Airborne bacteria are important constituents of microbial aerosols and contain lots of pathogens. However, variations in bacterial community structure in atmospheric PM of different sizes (PM2.5, PM10 and TSP) have not yet been explored. In this study, PM samples of different sizes were collected during the hazy days from Jul.2016 to Apr.2017 to determine bacterial diversity and community structure. Samples from soils and leaf surfaces were also collected to determine potential sources of bacterial aerosols. High-throughput sequencing technology was used generate bacterial community profiles, where we determined their diversity and abundances in the samples. Results showed that the dominant bacterial community structures in PM2.5, PM10 and TSP were strongly similar. Compared with non-haze days, the relative abundances of most bacterial pathogens on the haze days did not increase. Meanwhile, temperature, O3 and NO2 had more significant effects on bacterial community than the other environmental factors. Source tracking analysis indicated that the airborne bacteria might be not from local environment. It may come from the entire city or other regions by long distance airflow transport. Results of this study improved our understanding of the influence of bioaerosols on human health and the potential sources of airborne microbes.
The distribution of bacterial communities with meteorological factors in different sample. Display omitted
•Bacteria community structures in PM2.5, PM10 and TSP on hazy days were examined.•High-throughput sequencing method was used for bacterial community profiles.•Source tracking analysis was used to explore sources of airborne microbes.•The bacterial abundance and diversity in different particle sizes are different.•Haze pollution had no significant effects on bacterial community structures.
Vehicle emissions are affected by factors such as vehicle type, fuel quality, and engine repair. Therefore, mobile source profiles should be established based on a characteristic fleet for a specific ...region. This study characterised the chemical composition of PM2.5 emitted from motor vehicles that are commonly used in Xi'an through dynamometer tests. The tested fleet included light duty diesel vehicles (LDDVs; eight sample sets), heavy duty diesel vehicles (HDDVs; six sample sets), light duty gasoline vehicles (LDGVs; eight sample sets), one natural gas vehicle (NGV; four sample sets) and one methanol vehicle (MV; two sample sets). Similarities and differences among the source profiles were compared and evaluated. Overall, carbon species (13.14–59.11%) were the major components of PM2.5 for each type of vehicle, and the content of organic carbon (OC) was generally higher than that of elemental carbon (EC). Moreover, NO3− (18.577–220.062 mg·g−1) was the dominant water-soluble ion and the Ca2+ (2.429–17.209 mg·g−1) and Na+ (1.966–20.798 mg·g−1) contents in PM2.5 were high. In terms of elements, the PM2.5 emitted from various types of vehicles consisted of abundant Al (2.183–94.949 mg·g−1), Fe (0.567–12.297 mg·g−1), and Zn (0.659–5.195 mg·g−11). In addition, the PM2.5 profiles were significantly affected by fuel type. In general, emissions from the LDGVs and NGV exhibited higher contents of OC (477.0–479.1 mg·g−1). The greatest fractions of water-soluble ions (32.94%) and total elements (11.74%) were observed in emissions from the NGV and MV, respectively. For the same type of vehicle, the OC/EC ratio was possibly dependent on the emission standards. The PM2.5 emitted from the LDDVs with stricter emission standards exhibited higher OC/EC ratios, whereas the OC/EC ratios displayed a decreasing trend for the LDGVs under more stringent emission standards.
Display omitted
•PM2.5 profiles of conventional and alternative fuel vehicles were characterised.•Gasoline and natural gas vehicles emitted higher contents of OC.•The highest fraction of water-soluble ions was observed from the NGV.•The highest percentage of elements was observed from the MV.•The OC/EC ratio was impacted by the emission standards for the same type of vehicle.
PDF
