Urban Aerosol Research Articles

Impact of biogenic secondary organic aerosol (SOA) loading on the molecular composition of wintertime PM2.5 in urban Tianjin: an insight from Fourier transform ion cyclotron resonance mass spectrometry

Abstract. Biomass burning is one of the key sources of urban aerosols in the North China Plain, especially during winter, when the impact of secondary organic aerosols (SOAs) formed from biogenic volatile organic compounds (BVOCs) is generally considered to be minor. However, little is known about the influence of biogenic SOA loading on the molecular composition of wintertime organic aerosols. Here, we investigated the water-soluble organic compounds in fine particulate matter (PM2.5) from urban Tianjin by ultrahigh-resolution Fourier transform ion cyclotron resonanc mass spectrometry (FT-ICR MS). Our results show that most of the CHO and CHON compounds are derived from biomass burning which are poor in oxygen and contain aromatic rings that probably contribute to light-absorbing brown carbon (BrC) chromophores. Under moderate to high SOA-loading conditions, the nocturnal chemistry is more efficient than photooxidation to generate secondary CHO and CHON compounds with high oxygen content. Under low SOA loading, secondary CHO and CHON compounds with low oxygen content are mainly formed by photochemistry. Secondary CHO compounds are mainly derived from oxidation of monoterpenes. However, nocturnal chemistry may be more productive to sesquiterpene-derived CHON compounds. In contrast, the number- and intensity-weight of S-containing groups (CHOS and CHONS) increased significantly with the increase of biogenic SOA loading, which agrees with the fact that a majority of the S-containing groups are identified as organosulfates (OSs) and nitrooxy–organosulfates (nitrooxy–OSs) that are derived from the oxidation of BVOCs. Terpenes may be potential major contributors to organosulfates and nitrooxy–organosulfates. While the nocturnal chemistry is more beneficial to the formation of organosulfates and nitrooxy–organosulfates under low SOA loading. The SOA loading is an important factor that is associated with the oxidation degree, nitrate group content and chemodiversity of nitrooxy-organosulfates. Furthermore, our study suggests that the hydrolysis of nitrooxy-organosulfates is a possible pathway for the formation of organosulfates.

Pollution Characteristics and Source Analysis of Carbon and Nitrogen Components in Ambient PM2.5 in Huangshi City

Based on stable isotope technology and a PMF model, the pollution characteristics and sources of carbon and nitrogen components in ambient PM2.5 in Huangshi City were explored. The results showed that the total carbon concentration[ρ(TC)] and the total carbon isotopic composition (δ13CTC) in ambient PM2.5 in Huangshi City both showed seasonal variation characteristics of being high in winter and low in summer, with values of (4.4±1.2) μg·m-3 and (-26.3±0.5)‰ in summer and (9.9±3.5) μg·m-3 and (-25.5±0.5)‰ in winter, respectively. The total nitrogen concentration[ρ(TN)]was significantly lower in summer[(9.1±9.1) μg·m-3]than that in winter[(62.4±26.4) μg·m-3], whereas the total nitrogen isotopic composition (δ15NTN) was obviously enriched in summer[(12.8±1.9)‰]compared with that in winter[(2.9±4.0)‰]. In addition to the contribution from local sources, the carbon and nitrogen components were mainly affected by the short-range regional emission in northern Hunan and the long-distance transport in the northwest. The MixSIAR model and the PMF model indicated that the vehicle emission source was the main source of carbon components in PM2.5, with contribution rates of 38.9% and 39.3%, respectively. MixSIAR results showed that NOx emission sources had a greater impact on nitrogen components in PM2.5 of different seasons than NH3 emission sources, and their contribution was higher in summer (80%) than that in winter (66.8%), among which the NOx emissions from coal combustion (summer:36.1%; winter:20.2%) had the largest contribution. By contrast, the PMF model indicated that the main source of nitrogen components was vehicle emissions (59.8%). Combining multiple models to overcome the uncertainty and subjectivity of single-model analysis can provide a theoretical basis for actively controlling and reducing fine particulate matter emissions and effectively dealing with urban aerosol pollution.

Formation pathways of aldehydes from heated cooking oils.

Cooking emissions account for a major fraction of urban volatile organic compounds and organic aerosol. Aldehyde species, in particular, are important exposure hazards in indoor residential and occupational environments, and precursors to particulate matter and ozone formation in outdoor air. Formation pathways of aldehydes from oils that lead to their emissions are not well understood. In this work, we investigate the underlying mechanisms involved in the formation of aldehydes from heated cooking oil emissions, through studying how antioxidants and oil composition modulate oxidation chemistry. Our results demonstrate that gaseous emissions are driven by radical-mediated autoxidation reactions in cooking oil, and the composition of cooking oils strongly influences the reaction mechanisms. Antioxidants have a dual effect on aldehyde emissions depending on the rates of radical propagation reactions. We propose a mechanistic framework that can be used to understand and predict cooking emissions under different cooking conditions. Our results highlight the need to understand the rates and mechanisms of autoxidation and other reactions in cooking oils in order to accurately predict the gas- and particle-phase emissions from food cooking in urban atmospheres.

Chemical characterization of urban aerosols in Abidjan and Korhogo (Côte d'Ivoire) from 2018 to 2020 and the identification of their potential emission sources

As part of PASMU project, equipment was installed in urban sites of Abidjan and Korhogo (Cote d'Ivoire) in West Africa with the aim of studying the chemical composition of PM2.5 aerosols and identifying the contributing emissions sources.

Real-time, single-particle chemical composition, volatility and mixing state measurements of urban aerosol particles in southwest China

To investigate the volatility of atmospheric particulates and the evolution of other particulate properties (chemical composition, particle size distribution and mixing state) with temperature, a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu, southwest China. Because of their complex sources and secondary reaction processes, the average mass spectra of single particles contained a variety of chemical components (including organic, inorganic and metal species). When the temperature rose from room temperature to 280°C, the relative areas of volatile and semi-volatile components decreased, while the relative areas of less or non-volatile components increased. Most (> 80%) nitrate and sulfate existed in the form of NH4NO3 and (NH4)2SO4, and their volatilization temperatures were 50–100°C and 150–280°C, respectively. The contribution of biomass burning (BB) and vehicle emission (VE) particles increased significantly at 280°C, which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles. With the increase in temperature, the particle size of the particles coated with volatile or semi-volatile components was reduced, and their mixing with secondary inorganic components was significantly weakened. The formation of K-nitrate (KNO3) and K-sulfate (KSO4) particles was dominated by liquid-phase processes and photochemical reactions, respectively. Reducing KNO3 and BB particles is the key to improving visibility. These new results are helpful towards better understanding the initial sources, pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.

Thermal effects on dispersion of secondary inorganic aerosols in an urban street canyon

The surface heating in complex urban areas affects concentration of secondary inorganic aerosol (SIA) via flow and chemical environment changes. Previous studies on heating effects on pollutants have focused on effect of dispersion change. However, the heating of buildings also affects SIA concentration via chemical environmental changes, such as reaction rate and thermodynamic equilibrium changes. Accordingly, we investigated the effect of heating, by not only flow changes but also chemical environment changes, on SIA using a coupled chemistry-computational fluid dynamics (CFD) model. We investigated the change of temperature and wind in each scenario to separately identify the effects caused by the chemistry and dynamics of thermal heating on reactive aerosols. We found that both the chemical and dynamical effects reduce SIA concentration. The effect of heating caused by chemical environment changes on SIA was 49.4% larger than that of flow changes, suggesting the importance of chemical reactions in aerosol calculations in urban microscale aerosol simulations, which are not considered in most CFD-based models. We conclude that chemical speciation and detailed aerosol chemistry calculations, including an inorganic aerosol thermodynamic equilibrium model, should be considered for accurately accounting for the effect of heating on urban areas.

Quantification and identification of airborne small microplastics (

The atmosphere is a significant pathway for distributing plastic particles and other micro-litter particles from their sources to other environmental compartments. There is a big gap regarding the standardized method for the quantification and identification of airborne microplastics (MPs), especially those in the range of 5–100 μm (small microplastics, SMPs) and airborne micro-litter components (MLCs), i.e., plastic additives, natural fibers and non-plastics synthetic fibers. This study aimed to develop and optimize a pre-treatment method (i.e., elutriation, oleoextraction, and purification) to extract SMPs and MLCs simultaneously from urban aerosol samples. The quantification and simultaneous chemical characterization were performed via Micro-FTIR. The method developed was then applied to two samples from different seasons, i.e., summer and late fall – winter. Micro-litter particles followed the Poisson distribution, and the fiducial limit (confidence interval) was calculated accordingly. Non-parametric statistical tests were performed to evaluate significant differences among the samples. The most abundant plastic polymers were polyethylene (HDPE) and polytetrafluoroethylene (PTFE). Among MLCs, flame retardants, UV filters, stabilizers, and rayon were identified. The results of this study will contribute significantly to establishing standardized and accredited methods to quantify and identify airborne SMPs and MLCs.

The Role Played by the Bulk Hygroscopicity on the Prediction of the Cloud Condensation Nuclei Concentration Inside the Urban Aerosol Plume in Manaus, Brazil: From Measurements to Modeled Results

This work use observed and modeled data to trace a basic model that describes how the bulk chemical composition can be used to determine the aerosol size-dependency of hygroscopicity inside the urban aerosol pollution plume from Manaus, Brazil. The procedure is then used to predict the Cloud Condensation Nuclei (CCN) concentration (NCCN) from the Aerosol Size Distribution (ASD). The work briefly described hourly averaged data of ASD, Black Carbon size distribution (BCSD), Black Carbon mass concentration (BC), NCCN, and aerosol size hygroscopicity (κ) observed about 70 km downwind of the City of Manaus, inside the amazon rain forest, during 60 days of 2014, in the course of the rainy season. It uses a description of aerosol chemical composition obtained previously in the city of São Paulo, Brazil, as starting point to formulate a model that describes how particles in the pollution plume act as CCN as a function of their sizes and bulk chemical composition. A parameterization based on a polynomial fitting is proposed to determine BCSD from the BC. The measured and parameterized BCSD agree very well with more than 98% of the observed BCSDs, presenting a correlation coefficient larger than 0.9 with observation. The parameterized BC number concentration is also very well represented, with a correlation coefficient of 0.91 and a slope of 0.99 in comparison with observations. This work also studies how soot particles are incorporated in the CCN population and propose a parameterization to represent it. Simulations suggest that the larger BC particles are only partially incorporated as CCN and BC is a constraint to the fraction of aerosols that can act as CCN in all size ranges. The simulations also suggest that the incorporation of BC as CCN is probably only effective through coagulation in the presence of the wet phase. In addition, the work compares different strategies to predict observed NCCN from ASD. It is shown that the strategy presented can substantially improve the results of comparison of modeled and measured data from as bad as 2.14 ± 0.65 to as good as 1.02 ± 0.17. This study shows that the knowledge of the bulk chemical composition can be used to predict both the size-resolved chemical composition and mixing state, reducing the number of parameters needed to predict NCCN.

Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie–Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application

Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (Vt), effective radius (Reff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval.

Evidence of non-tailpipe emission contributions to PM2.5 and PM10 near southern California highways

Particulate Matter (PM) concentrations near highways are influenced by vehicle tailpipe and non-tailpipe emissions, other emission sources, and urban background aerosols. This study collected PM2.5 and PM10 filter samples near two southern California highways (I-5 and I-710) over two weeks in winter 2020. Samples were analyzed for chemical source markers. Mean PM2.5 and PM10 concentrations were approximately 10–15 and 30 μg/m3, respectively. Organic matter, mineral dust, and elemental carbon (EC) were the most abundant PM components. EC and polycyclic aromatic hydrocarbons at I-710 were 19–26% and 47% higher than those at the I-5 sites, respectively, likely due to a larger proportion of diesel vehicles. High correlations were found for elements with common sources, such as markers for brake wear (e.g., Fe, Ba, Cu, and Zr) and road dust (e.g., Al, Si, Ca, and Mn). Based on rubber abundances, the contributions of tire tread particles to PM2.5 and PM10 mass were approximately 8.0% at I-5 and 5.5% at I-710. Two different tire brands showed significantly different Si, Zn, carbon, and natural rubber abundances.

Aerosol optical properties over an urban industrial area, Raipur, Chhattisgarh, India

Optical properties of aerosols including Aerosol optical depth (AOD), Angstrom exponent (AE) and Single scattering albedo (SSA)) were derived and analyzed for classifying the aerosols and identification of possible sources with percentage contribution over an urban-industrial city Raipur, India, during the year 2019 to 2021. The mean annual values of AOD and AE during 2019–2021 were 0.53 ± 0.2 and 1.20 ± 0.33 respectively, with the highest AOD (AE) values in summer:(0.67 ± 0.21 (0.98 ± 0.13)), spring: (0.52 ± 0.17 (0.93 ± 0.23)), autumn: (0.59 ± 0.21 (1.36 ± 0.26)) and winter: (0.44 ± 0.15 (1.49 ± 0.15)) respectively. The results revealed the dominance of finer aerosols with higher (lower) AE value during the winter (summer) season. Whereas, lower (higher) SSA values during the winter (summer) indicated the presence of absorbing types of aerosols. Based on the aerosol optical characteristics (AOD versus AE), three distinct aerosol types were discovered throughout the study period, namely mixed aerosols (60%), biomass-urban (37%), and dust aerosols (3%). To discriminate between urban and biomass burning aerosols, optical characteristics (AE versus SSA) were examined and found three main sources: mixed aerosols (71%) urban-industrial (21%) and biomass burning aerosols (8%). These findings will be useful for identifying potential sources as well as serve as an input for estimating the radiative forcing caused by regional aerosols.

PM2.5 source apportionment identified with total and soluble elements in positive matrix factorization

Source apportionments of urban aerosols identified with positive matrix factorization (PMF) are sensitive to input variables. So far, total elements were frequently included as effective factors in PMF-based source apportionment. We investigated the advances to involve soluble parts of elements in the source apportionment with four data sets of PM2.5 composition observed at a coastal city (Qingdao) in northern China: water-soluble ions plus organic and elemental carbon (IC set), the IC set plus total elements (ICTE set), the IC set plus soluble elements (ICSE set), and the IC set plus both total elements and soluble elements (ICAE set). The apportionments of six sources, including secondary sulfate, secondary nitrate, secondary oxalate, sea salt, biomass burning and dust, were identified with the IC set. In comparison, pollutants from vehicle + coal combustion, ship emissions, waste incineration and industrial activities were also identified with the ICTE, ICSE, or ICAE sets. We found that the PMF solutions of the ICAE set could distinguish aged and fresh dust, and identify fly ash and aged pollutants from industrial sources. The profiles and corresponding time series of vehicle + coal combustion, secondary aerosols, ship emissions, sea salt, and biomass burning emissions identified with the four data sets were very similar, while discrepancies were encountered for waste incineration, dust, and industrial sources. These results indicate the benefits and potentials with total and soluble elements involved in PMF-based source apportionments.

Impact of urban aerosols on the cloud condensation activity using a clustering model

The indirect effect of aerosols on climate through aerosol-cloud-interactions is still highly uncertain and limits our ability to assess anthropogenic climate change. The foundation of this uncertainty is in the number of cloud condensation nuclei (CCN), which itself mainly stems from uncertainty in aerosol sources and how particles evolve to become effective CCN. We analyze particle number size distribution (PNSD) and CCN measurements from an urban site in a two-step method: (1) we use an unsupervised clustering model to classify the main aerosol categories and processes occurring in the urban atmosphere and (2) we explore the influence of the identified aerosol populations on the CCN properties. According to the physical properties of each cluster, its diurnal timing, and additional air quality parameters, the clusters are grouped into five main aerosol categories: nucleation, growth, traffic, aged traffic, and urban background. The results show that, despite aged traffic and urban background categories are those with lower total particle number concentrations (Ntot) these categories are the most efficient sources in terms of contribution to the overall CCN budget with activation fractions (AF) around 0.5 at 0.75 % supersaturation (SS). By contrast, road traffic is an important aerosol source with the highest frequency of occurrence (32 %) and relatively high Ntot, however, its impact in the CCN activity is very limited likely due to lower particle mean diameter and hydrophobic chemical composition. Similarly, nucleation and growth categories, associated to new particle formation (NPF) events, present large Ntot with large frequency of occurrence (22 % and 28 %, respectively) but the CCN concentration for these categories is about half of the CCN concentration observed for the aged traffic category, which is associated with their small size. Overall, our results show that direct influence of traffic emissions on the CCN budget is limited, however, when these particles undergo ageing processes, they have a significant influence on the CCN concentrations and may be an important CCN source. Thus, aged traffic particles could be transported to other environments where clouds form, triggering a plausible indirect effect of traffic emissions on aerosol-cloud interactions and consequently contributing to climate change.

Measurement report: Size distributions of urban aerosols down to 1 nm from long-term measurements

Abstract. The size distributions of urban atmospheric aerosols convey important information on their origins and impacts. Their long-term characteristics, especially for sub-3 nm particles, are still limited. In this study, we examined the characteristics of atmospheric aerosol size distributions down to ∼1 nm based on 4-year measurements in urban Beijing. Using cluster analysis, three typical types of number size distributions were identified, i.e., daytime new particle formation (NPF) type, daytime non-NPF type, and nighttime type. Combining a power law distribution and multiple lognormal distributions can well represent the sharp concentration decrease of sub-3 nm particles with increasing size and the modal characteristics for those above 3 nm in the submicron size range. The daytime NPF type exhibits high concentrations of sub-3 nm aerosols together with other three modes. However, both the daytime non-NPF type and the nighttime type have a low abundance of sub-3 nm aerosol particles together with only two distinct modes. In urban Beijing, the concentration of H2SO4 monomer during the daytime with NPF is similar to that during the daytime without NPF, while significantly higher than that during the nighttime. The concentration of atmospheric sub-3 nm particles on NPF days has a strong seasonality while their seasonality on non-NPF days is less pronounced. In addition to NPF as the most important source, we show that vehicles can emit sub-3 nm particles as well, although their influence on the measured aerosol population strongly depends on the distance from the road.

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India.

The accent of the present study is determination of Urban Aerosol Pollution Island (UAPI) intensity and spatial variability in particulate matter concentration (PM10 and PM2.5) over Delhi. For analysis, the hourly concentration dataset of PM2.5 and PM10 from January 2019 to December 2020 was obtained from ten air quality monitoring stations of Delhi. Additionally, UAPI Index has been calculated to assess the intensity of particulate pollution. The daily, monthly, and annual variations in the trends of PM10, PM2.5, and UAPI index along with related meteorological parameters have been analyzed. Particulate pollution peaked majorly during two seasons, i.e., summer and winter. The highest concentration of PM10 was observed to be 426.77 µg/m3 while that of PM2.5 was observed to be 301.91 µg/m3 in January 2019 for traffic-affected regions. During winters, higher PM2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM10 concentrations led to an increment in pollution episodes during summers over most of the sites in Delhi. The UAPI index was found to be declining in 2020 over traffic affected regions (77.92 and 27.22 for 2019 and 2020, respectively) as well as in the background regions (64.91 and 19.80 for 2019 and 2020, respectively) of Delhi. Low traffic intensity and reduced pollutant emission could have been responsible for the reduction of UAPI intensity in the year 2020. The result indicates that lockdown implemented to control the COVID-19 outbreak led to an unexpected decrease in the PM10 pollution over Delhi.

The Spatial-Temporal Differentiation of Aerosol Optical Properties and Types in the Beijing–Tianjin–Hebei Region Based on the Ecological Functional Zones

Atmospheric aerosol pollution has seriously affected the ecological environment and human health in recent years. There are great differences in aerosol optical properties and types due to the influence of environmental conditions, meteorology, industrial and agricultural activities, and other factors of each ecological functional zones. Using MODIS aerosol products (including MCD19A2 and MOD04_3K), this study discussed the temporal and spatial distribution of aerosol optical depth (AOD), Ångström wavelength index (AE) and aerosol types in the Beijing–Tianjin–Hebei region (BTH region) based on the ecological functional zones from 2015 to 2020. The results showed as follows: (1) The AOD in BTH region showed an obviously spatial pattern of low in the north and high in the south, while the spatial pattern of AE was opposite to that of AOD. In addition, the dominant aerosol type of the north part was clean aerosol, the dominant aerosol type of the middle part was biomass burning or urban-industrial aerosol, while that of the other part was mixed aerosols. (2) The seasonal changes of AOD and AE indexes in each ecological functional area had obvious seasonal changes, and the AOD and AE values were highest in summer. At the same time, the proportion of biomass combustion or urban industrial aerosol was the highest in summer. (3) The ecological functional areas with fewer human activities were dominated by clean aerosols, with lower AOD and higher AE value. The ecological functional areas dominated by cities were dominated by mixed aerosols, with higher AOD. The ecological functional areas dominated by agriculture and heavy industry were dominated by biomass combustion or urban industrial aerosols, with the largest AOD. (4) Compared with 2015, the average AOD of each ecological functional area decreased significantly to 2020, and biomass combustion or urban industrial aerosols changed to mixed aerosols.

City-scale distribution of airborne antibiotic resistance genes

Concerns around urban air quality have been increasing worldwide due to large-scale urbanization. A large volume of work has been focused on the chemical pollutants in the air and their impacts on human health. However, the profile of airborne microbial contaminants, especially antibiotic resistance genes (ARGs), is largely understudied. Here, high-throughput quantitative PCR (HT-qPCR) was employed to explore the temporal and spatial distribution of airborne ARGs from 11 sites with various functional zones and different urbanization levels within Xiamen, China. A total of 104 unique ARGs and 23 mobile genetic elements (MGEs) were detected across all samples. Temporal shift was observed in the distribution of ARG profiles, with significantly higher relative abundance of ARGs detected in summer than that in spring. Temperature is the key predictor of the total relative abundance of ARGs and MGEs in summer, while PM2.5 and PM10 were the two most important factors affecting the abundance in spring. Our findings suggest that urban aerosols accommodate rich and dynamic ARGs and MGEs, and emphasize the role of temperature, air quality and anthropogenic activities in shaping the profile of ARGs.

Lockdown-induced Urban Aerosol Change over Changchun, China During COVID-19 Outbreak with Polarization LiDAR.

Depending on various government policies, COVID-19 (Corona Virus Disease-19) lockdowns have had diverse impacts on global aerosol concentrations. In 2022, Changchun, a provincial capital city in Northeast China, suffered a severe COVID-19 outbreak and implemented a very strict lockdown that lasted for nearly two months. Using ground-based polarization Light Detection and Ranging (LiDAR), we detected real-time aerosol profile parameters (EC, extinction coefficient; DR, depolarization ratio; AOD, aerosol optical depth), as well as air-quality and meteorological indexes from 1 March to 30 April in 2021 and 2022 to quantify the effects of lockdown on aerosol concentrations. The period in 2022 was divided into three stages: pre-lockdown (1–10 March), strict lockdown (11 March to 10 April), and partial lockdown (11–30 April). The results showed that, during the strict lockdown period, compared with the pre-lockdown period, there were substantial reductions in aerosol parameters (EC and AOD), and this was consistent with the concentrations of the atmospheric pollutants PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM10 (particulate matter with an aerodynamic diameter ≤ 10 µm), and the O3 concentration increased by 8.3%. During the strict lockdown, the values of EC within 0–1 km and AOD decreased by 16.0% and 11.2%, respectively, as compared to the corresponding period in 2021. Lockdown reduced the conventional and organized emissions of air pollutants, and it clearly delayed the time of seasonal emissions from agricultural burning; however, it did not decrease the number of farmland fire points. Considering meteorological factors and eliminating the influence of wind-blown dust events, the results showed that reductions from conventional organized emission sources during the strict lockdown contributed to a 30% air-quality improvement and a 22% reduction in near-surface extinction (0–2 km). Aerosols produced by urban epidemic prevention and disinfection can also be identified using the EC. Regarding seasonal sources of agricultural straw burning, the concentrated burning induced by the epidemic led to the occurrence of heavy pollution from increased amounts of atmospheric aerosols, with a contribution rate of 62%. These results indicate that there is great potential to further improve air quality in the local area, and suggest that the comprehensive use of straw accompanied by reasonable planned burning is the best way to achieve this.

Impact of reduced anthropogenic emissions on chemical characteristics of urban aerosol by individual particle analysis.

A single particle aerosol mass spectrometer was deployed in a heavily polluted area of China during a coronavirus lockdown to explore the impact of reduced anthropogenic emissions on the chemical composition, size distributions, mixing state, and secondary formation of urban aerosols. Ten particle groups were identified using an adaptive resonance network algorithm. Increased atmospheric oxidation during the lockdown period (LP) resulted in a 42.2%-54% increase in the major NaK-SN particle fraction relative to the normal period (NP). In contrast, EC-aged particles decreased from 31.5% (NP) to 23.7% (LP), possibly due to lower emissions from motor vehicles and coal combustion. The peak particle size diameter increased from 440nm during the NP to 500nm during LP due to secondary particle formation. High proportions of mixed 62NO3- indicate extensive particle aging. Correlations between secondary organic (43C2H3O+, oxalate) and secondary inorganic species (62NO3-, 97HSO4- and 18NH4+) versus oxidants (Ox=O3+NO2) and relative humidity (RH) indicate that increased atmospheric oxidation promoted the generation of secondary species, while the effects of RH were more complex. Differences between the NP and LP show that reductions in primary emissions had a remarkable impact on the aerosol particles. This study provides new insights into the effects of pollution emissions on atmospheric reactions and the specific aerosol types in urban regions.

Preventive Effect of Epigallocatechin Gallate, the Main Component of Green Tea, on Acute Lung Injury Caused by Air Pollutants.

Reducing the health hazards caused by air pollution is a global challenge and is included in the Sustainable Development Goals. Air pollutants, such as PM2.5, induce respiratory and cardiovascular disorders by causing various inflammatory responses via oxidative stress. Catechins and polyphenols, which are components of green tea, have various protective effects, owing to their antioxidant ability. The main catechin in green tea, epigallocatechin gallate (EGCG), is potentially effective against respiratory diseases, such as idiopathic pulmonary fibrosis and asthma, but its effectiveness against air-pollution-dependent lung injury has not yet been investigated. In this study, we examined the effect of EGCG on urban aerosol-induced acute lung injury in mice. Urban aerosol treatment caused increases in inflammatory cell counts, protein levels, and inflammatory cytokine expression in the lungs of ICR mice, but pretreatment with EGCG markedly suppressed these responses. Analyses of oxidative stress revealed that urban aerosol exposure enhanced reactive oxygen species (ROS) production and the formation of ROS-activated neutrophil extracellular traps (NETs) in the lungs of mice. However, ROS production and NETs formation were markedly suppressed by pretreating the mice with EGCG. Gallocatechin gallate (GCG), a heat-epimerized form of EGCG, also markedly suppressed urban aerosol-dependent inflammatory responses and ROS production in vivo and in vitro. These findings suggest that EGCG and GCG prevent acute lung injury caused by urban aerosols through their inhibitory effects on ROS production. Thus, we believe that foods and medications containing EGCG or GCG may be candidates to prevent the onset and progression of acute lung injury caused by air pollutants.