Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China

Characterizing the emission trends and pollution evolution patterns during the transition period following COVID-19 at an industrial megacity of central China

After the resumption of work and production following the COVID-19 pandemic, many cities entered a "transition phase", characterized by the gradual recovery of emission levels from various sources. Although the overall PM2.5 emission trends have recovered, the specific changes in different sources of PM2.5 remain unclear. Here, we investigated the changes in source contributions and the evolution pattern of pollution episodes (PE) in Wuhan during the "transition period" and compared them with the same period during the COVID-19 lockdown. We found that vehicle emissions, industrial processes, and road dust exhibited significant recoveries during the transition period, increasing by 5.4%, 4.8%, and 3.9%, respectively, during the PE. As primary emissions increased, secondary formation slightly declined, but it still played a predominant role (accounting for 39.1∼ 43.0% of secondary nitrate). The reduction in industrial activities was partially offset by residential burning. The evolution characteristics of PE exhibited significant differences between the two periods, with PM2.5 concentration persisting at a high level during the transition period. The differences in the evolution patterns of the two periods were also reflected in their change rates at each stage, which mostly depend on the pre-PE concentration level. The transition period shows a significantly higher value (8.4 μg m-3 h-1) compared with the lockdown period, almost double the amount. In addition to local emissions, regional transport should be a key consideration in pollution mitigation strategies, especially in areas adjacent to Wuhan. Our study quantifies the variations in sources between the two periods, providing valuable insights for optimizing environmental planning to achieve established goals.

Pollution characteristics, source apportionment, and health risk assessment of PM10 and PM2.5 in rooftop and kerbside environment of Lanzhou, NW China

To investigate air pollution in the kerbside environment and its associated human health risks, a study was conducted in Lanzhou during December 2018, as well as in April, June, and September 2019. The research aimed to characterize the composition of PM10 and PM2.5, including elements, ions, and carbonaceous components, at both rooftop and kerbside locations. Additionally, source apportionment and health risk assessment were conducted. The results showed that the average mass concentrations of PM10 on the rooftop were 176.01 ± 83.23 μg/m3, and for PM2.5, it was 94.07 ± 64.89 μg/m3. The PM10 and PM2.5 levels at the kerbside are 2.21 times and 1.79 times, respectively, greater than those on the rooftop. Moreover, the concentrations of elements, ions, and carbonaceous components in kerbside PM were higher than those at the rooftop location. Chemical mass closure analysis identified various sources, including organic matter, mineral dust, secondary ions, other ions, elements, and other components. In comparison to rooftop particulate matter (PM), mineral dust makes a more substantial contribution to kerbside PM. Secondary ions show an opposite trend, making a greater contribution to rooftop PM. The contribution of organic components within PM of the same particle size remains relatively consistent. The outcome of the health risk assessment indicates that Co, Cd, and As in PM within the kerbside and rooftop environments do not pose a notable carcinogenic risk. However, Al and Mn do present specific non-carcinogenic risks, particularly in the kerbside environment. Furthermore, children experience elevated non-carcinogenic risk compared to adults. These findings can serve as a scientific foundation for formulating policies within the local health department.

Insight Study of Trace Elements in PM2.5 During Nine Years in Delhi, India: Seasonal Variation, Source Apportionment, and Health Risks Assessment

This study investigated the concentrations, seasonal variations, sources, and human health risks associated with exposure to heavy elements (As, Al, Pb, Cr, Mn, Cu, Zn, and Ni) of PM2.5 at an urban location of Delhi (28° 38' N, 77° 10' E; 218 m amsl), India, from January 2013 to December 2021. The average mass concentration of PM2.5 throughout the study period was estimated as 127 ± 77 µg m-3, which is exceeding the National Ambient Air Quality Standards (NAAQS) limit (annual: 40 µg m-3; 24 h: 60 µg m-3). The seasonal mass concentrations of PM2.5 exhibited at the order of post-monsoon (192 ± 110 µgm-3) > winter (158 ± 70 µgm-3) > summer (92 ± 44 µgm-3) and > monsoon (67 ± 32 µgm-3). The heavy elements, Al (1.19 µg m-3), Zn (0.49 µg m-3), Pb (0.43 µg m-3), Cr (0.21 µg m-3), Cu (0.21 µg m-3), Mn (0.07 µg m-3), and Ni (0.14 µg m-3) exhibited varying concentrations in PM2.5, with the highest levels observed in the post-monsoon season, followed by winter, summer, and monsoon seasons. Six primary sources throughout the study period, contributing to PM2.5 were identified by positive matrix factorization (PMF), such as dust (paved/crustal/soil dust: 29.9%), vehicular emissions (17.2%), biomass burning (15.4%), combustion (14%), industrial emissions (14.2%), and Br-rich sources (9.2%). Health risk assessments, including hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR), were computed based on heavy elements concentrations in PM2.5. Elevated HQ values for Cr and Mn linked with adverse health impacts in both adults and children. High carcinogenic risk values were observed for Cr in both adults and children during the winter and post-monsoon seasons, as well as in adults during the summer and monsoon seasons. The combined HI value exceeding one suggests appreciable non-carcinogenic risks associated with the examined elements. The findings of this study provide valuable insights into the behaviour and risk mitigation of heavy elements in PM2.5, contributing to the understanding of air quality and public health in the urban environment of Delhi.

Identification of potential source regions and long-range transport routes/channels of marine PM2.5 at remote sites in East Asia

Long-range transport (LRT) of air masses in East Asia and their impacts on marine PM2.5 were explored. Situated in the leeward region of East Asia, Taiwan Island marked by its elevated Central Mountain Range (CMR) separates air masses into two distinct air currents. This study aims to investigate the transport of PM2.5 from the north to the leeward region. Six transport routes (A-F) were identified and further classified them into three main channels (i.e. East, West, and South Channels) based on their transport routes and potential sources. Green Island (Site GR) and Hengchun Peninsula (Site HC) exhibited similarities in their transport routes, with Central China, North China, and Korean Peninsula being the major source regions of PM2.5, particularly during the Asian Northeastern Monsoons (ANMs). Dongsha Island (Site DS) was influenced by both Central China and coastal regions of East China, indicating Asian continental outflow (ACO) as the major source of PM2.5. The positive matrix factorization (PMF) analysis of PM2.5 resolved that soil dust, sea salts, biomass burning, ship emissions, and secondary aerosols were the major sources. Northerly Channels (i.e. East and West Channels) were primarily influenced by ship emissions and secondary aerosols, while South Channel was dominated by oceanic spray and soil dust. The results of W-PSCF and W-CWT analysis indicated that three remote sites experienced significant contributions from Central China in the highest PM2.5 concentration range (75-100%). In contrast, PM2.5 in the 0-25% and 25-50% ranges primarily originated from the open seas, with ship emissions being the prominent source. It suggested that northern regions with heavy industrialization and urbanization have impacts on high PM2.5 concentrations, while open seas are the main sources of low PM2.5 concentrations.

Source apportionment of PM2.5 using PMF combined online bulk and single-particle measurements: Contribution of fireworks and biomass burning

Fireworks (FW) could significantly worsen air quality in short term during celebrations. Due to similar tracers with biomass burning (BB), the fast and precise qualification of FW and BB is still challenging. In this study, online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM2.5 and specific chemical species by positive matrix factorization (PMF) during the Chinese New Year in Hong Kong in February 2013. With combined information, fresh/aged FW (abundant 140K2NO3+ and 213K3SO4+ formed from 113K2Cl+ discharged by fresh FW) can be extracted from the fresh/aged BB sources, in addition to the Second Aerosol, Vehicles + Road Dust, and Sea Salt factors. The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region. The fresh BB/FW contributed 39.2% and 19.6% to PM2.5 during the Lunar Chinese New Year case. However, the contributions of aged FW/BB enhanced in the last two episodes due to the aging process, evidenced by high contributions from secondary aerosols. Generally, the fresh BB/FW showed more significant contributions to nitrate (35.1% and 15.0%, respectively) compared with sulfate (25.1% and 5.9%, respectively) and OC (14.8% and 11.1%, respectively) on average. In comparison, the aged FW contributed more to sulfate (13.4%). Overall, combining online bulk and single-particle measurement data can combine both instruments' advantages and provide a new perspective for applying source apportionment of aerosols using PMF.

Environmentally persistent free radicals in PM2.5 from a typical Chinese industrial city during COVID-19 lockdown: The unexpected contamination level variation

The outbreak of COVID-19 has caused concerns globally. To reduce the rapid transmission of the virus, strict city lockdown measures were conducted in different regions. China is the country that takes the earliest home-based quarantine for people. Although normal industrial and social activities were suspended, the spread of virus was efficiently controlled. Simultaneously, another merit of the city lockdown measure was noticed, which is the improvement of the air quality. Contamination levels of multiple atmospheric pollutants were decreased. However, in this work, 24 and 14 air fine particulate matter (PM2.5) samples were continuously collected before and during COVID-19 city lockdown in Linfen (a typical heavy industrial city in China), and intriguingly, the unreduced concentration was found for environmentally persistent free radicals (EPFRs) in PM2.5 after normal life suspension. The primary non-stopped coal combustion source and secondary Cu-related atmospheric reaction may have impacts on this phenomenon. The cigarette-based assessment model also indicated possible exposure risks of PM2.5-bound EPFRs during lockdown of Linfen. This study revealed not all the contaminants in the atmosphere had an apparent concentration decrease during city lockdown, suggesting the pollutants with complicated sources and formation mechanisms, like EPFRs in PM2.5, still should not be ignored.

Characterization and sources of water-soluble inorganic ions during sulfate-driven and nitrate-driven haze on the largest loess accumulation plateau

With the rapid reduction of anthropogenic SO2 emissions, the critical driver of haze in China has shifted from being dominated by sulfate to alternating sulfate and nitrate. Haze induced by different driver species may differ in the chemical forms of water-soluble inorganic ions (WSIIs). The unique topography and high-emission industrial agglomeration of the Loess Plateau determine its severe local PM2.5 pollution and influence global weather patterns through the outward export of pollutants. PM2.5 samples were conducted in Pingyao, on the eastern Loess Plateau of China, in autumn and winter. The average mass of PM2.5 was 88.82 ± 57.37 μg/m3; sulfate, nitrate, and ammonium were the dominant component. The chemical form of the ion was dominated by (NH4)2SO4, NH4NO3, NaNO3 and KNO3 during the nitrate-driven (ND) haze, while (NH4)2SO4, NH4HSO4, NH4NO3, NaNO3 and KNO3 were predominant species during the sulfate-driven (SD) haze. Heterogeneous oxidation reactions dominated the mechanism of sulfate formation. Primary sulfate emissions or other generation pathways contributed to sulfate formation during the SD haze. The gas-phase homogeneous reaction of NO2 and NH3 dominates the nitrate generation during the ND haze. The heterogeneous reactions also played an essential role during the SD haze. Nitrate aerosol (42.30%) and coal and biomass combustion (23.23%) were the dominant sources of WSIIs during the ND haze. In comparison, nitrate aerosol (31.80%) and sulfate aerosol (25.08%) were considered the primary control direction during the SD haze. The chemical characteristics and sources of aerosols under various types of haze differ significantly, and knowledge gained from this investigation provides insight into the causes of heavy haze.

Bioavailability and regional transport of PM2.5 during heavy haze episode in typical coal city site of Fenwei Plain, China

Despite the decrease in anthropogenic emissions, haze episodes were still frequent in the Fenwei Plain, which was identified as one of the three key areas for air pollution control. Herein, PM_2.5 samples were collected to investigate the influence of festival effect during the Chinese Spring Festival from February 2rd to 13th, 2019, in Linfen on the Fenwei Plain. The characteristics of element pollution, enrichment factor, source apportionment, regional transport of PM_2.5, and health risk assessment were discussed. Meanwhile, the simulated lung fluid method (SLF) was carried out to accurately assess the inhalation risks of heavy metals (HMs). Results indicated that the average concentration of PM_2.5 was 195.6 μg·m^-3 during the studying period. Road fugitive dust (15.6%), firework burning source (25.6%), industrial emission (30.5%), and coal combustion (28.3%) were identified by positive matrix factorization (PMF) modeling. Using the HYSPLIT trajectory model, air masses from the central Shaanxi, southern Hebei, and northern Henan were the dominant transport paths during the Spring Festival, which contributed 21.9 and 41.2% of total trajectories, respectively. The findings that high PSCF and CWT levels were found in central Shaanxi, southern Hebei, and northern Henan were confirmed. The SLF mean bioaccessibility (%) of the solubility of particulate metals was in order of Mn > Ni > Sb > Ba > Zn > Pb > Cr. However, the carcinogenic risk value of Cr was the highest, exceeding the maximum acceptable risk. The present study provided important information for further analyzing the air pollution cause of Fenwei Plain.

A systematic review on mitigation of common indoor air pollutants using plant-based methods: a phytoremediation approach

Environmental pollution, especially indoor air pollution, has become a global issue and affects nearly all domains of life. Being both natural and anthropogenic substances, indoor air pollutants lead to the deterioration of the ecosystem and have a negative impact on human health. Cost-effective plant-based approaches can help to improve indoor air quality (IAQ), regulate temperature, and protect humans from potential health risks. Thus, in this review, we have highlighted the common indoor air pollutants and their mitigation through plant-based approaches. Potted plants, green walls, and their combination with bio-filtration are such emerging approaches that can efficiently purify the indoor air. Moreover, we have discussed the pathways or mechanisms of phytoremediation, which involve the aerial parts of the plants (phyllosphere), growth media, and roots along with their associated microorganisms (rhizosphere). In conclusion, plants and their associated microbial communities can be key solutions for reducing indoor air pollution. However, there is a dire need to explore advanced omics technologies to get in-depth knowledge of the molecular mechanisms associated with plant-based reduction of indoor air pollutants.

Identifying and quantifying PM2.5 pollution episodes with a fusion method of moving window technique and constrained Positive Matrix Factorization

PM_2.5 pollution episodes rapidly and significantly deteriorate the air quality and are a critical concern worldwide. This study developed a fusion method based on the moving window dataset technique and constrained Positive Matrix Factorization (PMF) to differentiate and characterize potential factors in a PM_2.5 episode case assuming having one new contributor. The hourly PM_2.5 compositions of elements, ions and carbonaceous components, were collected from September to December 2020 in Taipei, Taiwan. Constraint targets based on the bootstrap analysis result of a PMF model using a long-term input dataset were imposed on the modeling of each moving window to ensure similar features of the retrieved factors. The constituents of an additionally differentiated factor to the episode, which was identified as regional transport, were stable among each moving window that covered the occurrence of the episode as revealed by the profile matching index. The results showed that the largest contributor to the PM_2.5 mass during the episode period of 12/12/2020 was regional transport (61%), whereas that of 12/13 was the regular pollution of industry/ammonium sulfate related (43%). According to our review of the literature, this study is the first to apply both the moving window technique and constrained PMF to characterize the episode. The findings provide valuable information that can be used to explore the causes of PM_2.5 episodes and implement air pollution control strategies.

The protective effects of taurine and fish oil supplementation on PM2.5-induced heart dysfunction among aged mice: A random double-blind study

As it is nearly impossible to reduce PM2.5 concentrations in most cities to safe limits in a short period of time, dietary supplementation presents a promising approach for mitigating the adverse effects of PM2.5 exposure. A cross-sectional study showed that the elderly population of Linfen (PM2.5: 102 μg/m3) exhibited significantly lower serum taurine levels, as well as higher oxidative stress levels and cardiovascular health risks, than the corresponding population in Guangzhou (PM2.5: 39 μg/m3). We conducted a random double-blind study on aged mice that employed a "real-world" PM2.5 exposure system to simulate the conditions of Linfen with the aim of investigating the protective effects of taurine and fish oil supplementation on PM2.5-induced heart dysfunction. When compared with the placebo group, supplementation with taurine and fish oil not only maintained normal taurine levels, but also suppressed oxidative stress and inflammation in aged mice subjected to high concentrations of PM2.5. Variations in heart rate, contractile function, cardiac oxidative stress, inflammation and fibrosis among different groups of aged mice were used to clarify the beneficial effects of taurine and fish oil supplementation. Our results not only revealed the protective effects of taurine and fish oil supplementation on heart dysfunction induced by PM2.5 exposure from the aged mice experiments and also provided new means for the elderly to resist PM2.5 pollution at the individual level.

Variation of pollution sources and health effects on air pollution before and during COVID-19 pandemic in Linfen, Fenwei Plain

Stringent pollution control measures are generally applied to improve air quality, especially in the Spring Festival in China. Meanwhile, human activities are reduced significantly due to nationwide lockdown measures to curtail the COVID-19 spreading in 2020. Herein, to better understand the influence of control measures and meteorology on air pollution, this study compared the variation of pollution source and their health risk during the 2019 and 2020 Spring Festival in Linfen, China. Results revealed that the average concentration of PM_2.5 in 2020 decreased by 39.0% when compared to the 2019 Spring Festival. Organic carbon (OC) and SO₄^2- were the primary contributor to PM_2.5 with the value of 19.5% (21.1%) and 23.5% (25.5%) in 2019 (2020) Spring Festival, respectively. Based on the positive matrix factorization (PMF) model, six pollution sources of PM_2.5 were indicated. Vehicle emissions (VE) had the maximum reduction in pollution source concentration (28.39 μg· m^-3), followed by dust fall (DF) (11.47 μg· m^-3), firework burning (FB) (10.39 μg· m^-3), coal combustion (CC) (8.54 μg· m^-3), and secondary inorganic aerosol (SIA) (3.95 μg· m^-3). However, the apportionment concentration of biomass burning (BB) increased by 78.7%, indicating a significant increase in biomass combustion under control measures. PAHs-lifetime lung cancer risk (ILCR) of VE, CC, FB, BB, and DF, decreased by 44.6%, 43.2%, 34.1%, 21.3%, and 2.0%, respectively. Additionally, the average contribution of meteorological conditions on PM_2.5 in 2020 increased by 20.21% compared to 2019 Spring Festival, demonstrating that meteorological conditions played a crucial role in located air pollution. This study revealed that the existing control measures in Linfen were efficient to reduce air pollution and health risk, whereas more BB emissions were worthy of further attention. Furthermore, the result was conducive to developing more effective control measures and putting more attention into unfavorable meteorological conditions in Linfen.

Source Identification and Superposition Effect of Heavy Metals (HMs) in Agricultural Soils at a High Geological Background Area of Karst: A Case Study in a Typical Watershed

Exogenous sources and the superposition effect of HMs in agricultural soils made the idenfication of sources complicated in a karst area. Here, a typical watershed, a research unit of the karst area, was chosen as the study area. The smaller-scale study of watersheds allowed us to obtain more precise results and to guide local pollution control. In this study, sources of HMs in agricultural soil were traced by a CMB model. Superposition effects were studied by spatial analysis of HMs and enrichment factor (EF) and chemical fraction analysis. The average concentrations of Cd, Pb, Cr, Cu, Ni and Zn in surface soils were 8.71, 333, 154, 51.7, 61.5 and 676 mg∙kg^-1, respectively, which exceeded their corresponding background values. The main sources of Cd, Pb and Zn in agricultural soil were rock weathering, atmospheric deposition and livestock manure, and their contributions were 47.7%, 31.0% and 21.2% for Cd; 7.63%, 78.7% and 13.4% for Pb; and 17.0%, 52.3% and 28.1% for Zn. Cr mainly derived from atmospheric deposition (73.8%) and rock weathering (20.0%). Cu and Ni mainly came from livestock manure (81.3%) and weathering (87.5%), respectively, whereas contributions of pesticides and fertilizers were relatively limited (no more than 1.04%). Cd, Pb, Zn and Cu were easily enriched in surface soils near the surrounding pollution sources, whereas Cr and Ni were easily enriched in the high-terrain area, where there was less of an impact of anthropogenic activities. The superposition of exogenous sources caused accumulation of Cd, Pb and Zn in topsoil, contaminated the subsoil through leaching and improved bioavailability of Cd and Pb, causing high ecological risk for agricultural production. Therefore, Cd and Pb should be paid more attention in future pollution control.

Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2.5 pollution

PM_2.5 pollution is a complex process mainly affected by emission sources and meteorological conditions. However, it is hard to accurately assess the effects of emission sources and meteorological conditions on the variation of PM_2.5 concentrations in the complex atmospheric environment. In this study, the Random Forest model with Shapley Additive exPlanations (RF-SHAP) and Partial Dependence Plot (RF-PDP) was combined with Positive Matrix Factorization (PMF) to evaluate the impacts of various factors on PM_2.5 pollution. The results show that anthropogenic emissions and meteorological conditions contributed about 67% (40.5 μg/m³) and 33% (19.7 μg/m³) to variation in PM_2.5 concentrations, respectively. Specifically, secondary nitrate (SN) had the greatest impact among all sources (about 45%). Hence, we further explore the impacts of the primary sources and meteorological conditions on SN formation. Coal combustion and vehicle emissions significantly contribute to the formation of SN by providing a large number of precursor NO_X. Additionally, the RF-PDP method was further employed to estimate the synergistic effects of primary sources and meteorological conditions on SN formation. The results help reveal strategies to simultaneously reduce SN by controlling primary emissions under suitable meteorological conditions. This work also suggests that the machine learning model can utilize online datasets well and provide a reliable approach for analyzing the causes of PM_2.5 pollution.

The seasonal variation, characteristics and secondary generation of PM2.5 in Xi'an, China, especially during pollution events

As an important central city in western China, Xi'an has the worst atmospheric pollution record in China and many measures have been taken to improve the air quality in the past few years. In this study, PM_2.5 samples were collected across four seasons from 2017 to 2018 in Xi'an. Organic carbon and elemental carbon, water soluble ions, and elements were monitored to assess the air quality. The average annual PM_2.5 concentration was (134.9 ± 48.1 μg/m³), with the highest concentration in winter (188.8 ± 93.2 μg/m³), and lowest concentration in summer (71.2 ± 12.1 μg/m³). The secondary generation of sulfate (SO₄^2-) and nitrate (NO₃^-) was strong in spring, and secondary organic carbon (SOC) was formed in all seasons. The compositions of PM_2.5 changed greatly during a sandstorm occurred and the Spring Festival. The sandstorm played a positive role in removing local pollutant NO₃^-, but also increased the concentration of SO₄^2-, however both the concentration of SO₄^2- and NO₃^- greatly increased by secondary generation during Spring Festival. Potential source analysis showed that during the sandstorm, pollutants were transported over a long distance from the northwest of China, whereas it was mainly from the local and surrounded emissions during the Spring Festival. Except Ca²⁺ and geological dust (GM), the other components in PM_2.5 increased significantly on the day of the Spring Festival. During sampling time in Xi'an, the positive matrix factorization (PMF) model analysis showed that PM_2.5 mainly came from vehicle emission, coal combustion, and biomass burning.

A hybrid methodology to quantitatively identify inorganic aerosol of PM2.5 source contribution

It is difficult to identify inorganic aerosol (IA) (primary and secondary), the main component of PM_2.5, without the significant tracers for sources. We are not aware of any studies specifically related to the IA's local contribution to PM_2.5. To effectively reduce the IA load, however, the contribution of local IA sources needs to be identified. In this work, we developed a hybrid methodology and applied online measurement of PM_2.5 and the associated compounds to (1) classify local and long-range transport PM_2.5, (2) identify sources of local PM_2.5 using PMF model, and (3) quantify local source contribution to IA in PM_2.5 using regression analysis. Coal combustion and iron ore and steel industry contributed the most amount of IA (~42.7%) in the study area (City of Taichung), followed by 32.9% contribution from oil combustion, 8.9% from traffic-related emission, 4.6% from the interactions between agrochemical applications and combustion sources (traffic-related emissions and biomass burning), and 2.3% from biomass burning. The methodology developed in this study is an important preliminary step for setting up future control policies and regulations, which can also be applied to any other places with serious local air pollution.

Significant contribution of secondary particulate matter to recurrent air pollution: Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China

Particulate matter (PM) pollution in high emission regions will affect air quality, human health and climate change on both local and regional scales, and thus attract worldwide attention. In this study, a comprehensive study on PM_2.5 and its chemical composition were performed in Yuncheng (the most polluted city of Fen-Wei Plain of China) from November 28, 2020 to January 24, 2021. The average concentration of PM_2.5 was 87.8 ± 52.0 μg/m³, which were apparently lower than those observed during the same periods of past five years, attributable to the clean air action plan implemented in this region. NO₃^- and organic carbon (OC) were the dominant particulate components, which on average contributed 22.6% and 16.5% to PM_2.5, respectively. The fractions of NO₃^-, NH₄⁺, OC and trace metals increased while those of crustal materials and elemental carbon decreased with the degradation of PM_2.5 pollution. Six types of PM_2.5 sources were identified by the PMF model, including secondary inorganic aerosol (35.3%), coal combustion (28.7%), vehicular emission (20.7%), electroplating industry (8.6%), smelt industry (3.9%) and dust (2.8%). Locations of each identified source were pinpointed based on conditional probability function, potential source contribution function and concentration weighted trajectory, which showed that the geographical distribution of the sources of PM_2.5 roughly agreed with the areas of high emission. Overall, this study provides valuable information on atmospheric pollution and deems beneficial for policymakers to take informed action to sustainably improve air quality in highly polluted region.

Year-round observation of atmospheric inorganic aerosols in urban Beijing: Size distribution, source analysis, and reduction mechanism

To investigate particle characteristics and find an effective measure to control severe particle pollution, year-round observation of size-segregated inorganic aerosols was conducted in Beijing from January to December, 2016. The sampled atmospheric particles all presented bimodal size distribution at four pollution levels (clear, slight pollution, moderate pollution and severe pollution), and peak values appeared at the size range of 0.7-2.1 μm and >9.0 μm, respectively. As dominant particle compositions, NO₃^-, SO₄^2-, and NH₄⁺ in four pollution levels all showed significant peaks in fine mode, especially at the size range of 1.1-2.1 μm. Secondary inorganic aerosols accounted for about 67.6% (36.3% (secondary sulfates) + 31.3% (secondary nitrates)) of the total sources of fine particles in urban Beijing. Severe pollution of fine particles was mainly caused by the air masses transported from nearby western and southern areas, which are industrial and densely populated region, respectively. Sensitivity tests further revealed that the control measures focusing on ammonium emission reduction was the most effective for particle pollution mitigation, and fine particles all showed nonlinear responses after reducing ammonium, nitrate, and sulfate concentrations, with the fitting curves of y = -120.8x - 306.1x² + 290.2x³, y = -43.5x - 67.8x², and y = -25.8x - 110.4x² + 7.6x³, respectively (y and x present fine particle mass variation (μg/m³) and concentration reduction ratio (CRR)/100 (dimensionless)). Overall, our study presents useful information for understanding the characteristics of atmospheric inorganic aerosols in urban Beijing, as well as offers policy makers with effective measure for mitigating particle pollution.

Exploring the Sensitivity of Visibility to PM2.5 Mass Concentration and Relative Humidity for Different Aerosol Types

Fine particle (PM2.5) mass concentration and relative humidity (RH) are the primary factors influencing atmospheric visibility. There are some studies focused on the complex, nonlinear relationships among visibility, PM2.5 concentration, and RH. However, the relative contribution of the two factors to visibility degradation, especially for different aerosol types, is difficult to quantify. In this study, the normalized forward sensitivity index method for identifying the dominant factors of visibility was used on the basis of the sensitivity of visibility to PM2.5 and RH changes. The visibility variation per unit of PM2.5 or RH was parameterized by derivation of the visibility multivariate function. The method was verified and evaluated based on 4453 valid hour data records in Tianjin, and visibility was identified as being in the RH-sensitive regime when RH was above 75%. In addition, the influence of aerosol chemical compositions on sensitivity of visibility to PM2.5 and RH changes was discussed by analyzing the characteristics of extinction components ((NH4)2SO4, NH4NO3, organic matter, and elemental carbon) measured in Tianjin, 2015. The result showed that the fitting equation of visibility, PM2.5, and RH, separately for different aerosol types, further improved the accuracy of the parameterization scheme for visibility in most cases.

Composition and sources of particulate matter in the Beijing-Tianjin-Hebei region and its surrounding areas during the heating season

This paper aimed to analyze the composition and pollution sources of particulate matter (PM) in the Beijing-Tianjin-Hebei region and its surrounding areas (henceforth the BTH region) during the heating season to support the mitigation and control of regional air pollution. Manual monitoring data from the China National Environmental Monitoring Network for Atmospheric PM in the BTH region were collected and analyzed during the 2016 and 2018 heating seasons. The positive definite matrix factor analysis (PMF) model was used to analyze the PM sources in BTH cities during the heating season. The main PM components were organic matter (OM), nitrate (NO₃^-), sulfate (SO₄^2-) and ammonium salt (NH₄⁺). Direct emission sources have decreased since 2016, indicating the effectiveness of governmental controls on these sources; however, secondary pollution showed an increasing trend, suggesting control measures should be strengthened. Daily regional average concentrations of OM, SO₄^2-, NH₄⁺, elemental carbon (EC), chloride (Cl^-) and trace elements all showed similar trends. When air quality worsened, the concentrations of the main PM components increased, but trends of change varied among components. In 2018, concentrations of OM and chloride were highest in the Taihang Mountains, and NO₃ concentrations were highest in Anyang, Hebi, Jiaozuo and Xinxiang. The SO₄^2- concentration was highest in the southern section of the Taihang Mountains. The NH₄⁺ and EC concentrations were generally highest in the central and southern regions. The concentration of crustal substances was highest in some cities in the north and central parts of the BTH region. In the 2018 heating season, the pollution level of five transmission channels showed an increasing trend in the Northwest, Southeast, Yanshan, South and Taihang Mountain channels. These findings provide a scientific basis for the continued management of atmospheric PM pollution.

High contribution of vehicle emissions to fine particulate pollutions in Lanzhou, Northwest China based on high-resolution online data source appointment

The quantitative estimation of urban particulate matter (PM) sources is essential but limited because of various reasons. The hourly online data of PM_2.5, organic carbon (OC), elemental carbon (EC), water-soluble ions, and elements from December 2019 to November 2020 was used to conduct PM source appointment, with an emphasis on the contribution of vehicle emissions to fine PM pollution in downtown Lanzhou, Northwest China. Vehicle emissions, secondary formation, mineral dust, and coal combustion were found to be the major PM sources using the positive matrix factorization model. The seasonal mean PM_2.5 were estimated to be 72.8, 39.2, 24.3, and 43.6 μg·m^-3 and vehicle emissions accounted for 35.7%, 25.8%, 30.0%, and 56.6% in winter, spring, summer, and autumn, respectively. Vehicle emissions were the largest source of PM considering the high PM pollution in winter and its significantly large contribution in autumn. Furthermore, the contribution of vehicle emissions increased with increasing PM in winter and autumn. Vehicle emissions were also the most important source of EC, accounting for 70.3%, 91.0%, 83.5%, and 93.7% of the total EC in winter, spring, summer, and autumn, respectively. With the reduction in industrial emissions and increase in vehicle numbers in China in recent years, vehicle emissions are going to be the largest source of urban PM pollution. To sustainably improve air quality in Lanzhou and other Chinese cities, efforts should be made to control vehicle emissions such as promoting clean-energy vehicles and encouraging public transportation.

Tracing riverine sulfate source in an agricultural watershed: Constraints from stable isotopes

The sulfate pollution in water environment gains more and more concerns in recent years. The discharge of domestic, municipal, and industrial wastewaters increases the riverine sulfate concentrations, which may cause local health and ecological problems. To better understand the sources of sulfate, this study collected water samples in a typical agricultural watershed in East Thailand. The source apportionment of sulfide was conducted by using stable isotopes and receptor models. The δ³⁴S_SO4 value of river water varied from 1.2‰ to 16.4‰, with a median value of 8.9‰. The hydrochemical data indicated that the chemical compositions of Mun river water were affected by the anthropogenic inputs and natural processes such as halite dissolution, carbonate, and silicate weathering. The positive matrix factorization (PMF) model was not suitable to trace source of riverine sulfate, because the meaning of the extracted factors seems to be vague. Based on the elemental ratio and isotopic composition, the inverse model yielded the relative contribution of sulfide oxidation (approximately 46.5%), anthropogenic input (approximately 41.5%), and gypsum dissolution (approximately 12%) to sulfate in Mun river water. This study indicates that the selection of models for source apportionment should be careful. The large contribution of anthropogenic inputs calls an urgent concern of the Thai government to establish effective management strategies in the Mun River basin.

Potential health risks of inhaled toxic elements and risk sources during different COVID-19 lockdown stages in Linfen, China

Levels of toxic elements in ambient PM_2.5 were measured from 29 October 2019 to 30 March 2020 in Linfen, China, to assess the health risks they posed and to identify critical risk sources during different periods of the COVID-19 lockdown and haze episodes using positive matrix factorization (PMF) and a health-risk assessment model. The mean PM_2.5 concentration during the study period was 145 μg/m³, and the 10 investigated toxic elements accounted for 0.31% of the PM_2.5 mass. The total non-cancer risk (HI) and total cancer risk (TCR) of the selected toxic elements exceed the US EPA limits for children and adults. The HI for children was 2.3 times that for adults for all periods, which is likely due to the high inhalation rate per unit body weight for children. While the TCR for adults was 1.7 times that of children, which is mainly attributed to potential longer exposure duration for adults. The HI and TCR of the toxic elements during full lockdown were reduced by 66% and 58%, respectively, compared to their pre-lockdown levels. The HI and TCR were primarily attributable to Mn and As, respectively. Health risks during haze episodes were significantly higher than the average levels during COVID-19 lockdowns, though the HI and TCR of the selected toxic elements during full-lockdown haze episodes were 68% and 17% lower, respectively, than were the levels during pre-lockdown haze episodes. During the study period, fugitive dust and steel-related smelting were the highest contributors to HI and TCR, respectively, and decreased in these emission sources contributed the most to the lower health risks observed during the full lockdown. There, the control of these sources is critical to effectively reduce public health risks.

Health risks of inhaled selected toxic elements during the haze episodes in Shijiazhuang, China: Insight into critical risk sources

PM_2.5 in Shijiazhuang was collected from October 15, 2018 to January 31, 2019, and selected toxic elements were measured. Five typical haze episodes were chosen to analyze the health risks and critical risk sources. Toxic elements during the haze episodes accounted for 0.33% of PM_2.5 mass. Non-cancer risk of toxic elements for children was 1.8 times higher than that for adults during the haze episodes, while cancer risk for adults was 2.5 times higher than that for children; cancer and non-cancer risks were primarily attributable to As and Mn, respectively. Health risks of toxic elements increased during the growth and stable periods of haze episodes. Non-cancer and cancer risks of toxic elements during the haze stable periods were higher than other haze stages, and higher for children than for adults during the stable period. Mn was the largest contributor to non-cancer risk during different haze stages, while As was the largest contributor to cancer risk. Crustal dust, vehicle emissions, and industrial emissions were critical sources of cancer risk during the clean-air periods; while vehicle emissions, coal combustion, and crustal dust were key sources of cancer risk during the haze episodes. Cancer risks of crustal dust and vehicle emissions during the haze episodes were 2.0 and 1.7 times higher than those in the clean-air periods. Non-cancer risks from emission sources were not found during different periods. Cancer risks of biomass burning and coal combustion increased rapidly during the haze growth period, while that of coal combustion decreased sharply during the dissipation period. Vehicle emissions, crustal dust, and coal combustion were significant cancer risk sources during different haze stages, cancer risk of each source was the highest during the stable period. Southern Hebei, Northern and central Shaanxi were potential risk regions that affected the health of both adults and children in Shijiazhuang.

Chemical formation and source apportionment of PM2.5 at an urban site at the southern foot of the Taihang mountains

The region along the Taihang Mountains in the North China Plain (NCP) is characterized by serious fine particle pollution. To clarify the formation mechanism and controlling factors, an observational study was conducted to investigate the physical and chemical properties of the fine particulate matter in Jiaozuo city, China. Mass concentrations of the water-soluble ions (WSIs) in PM_2.5 and gaseous pollutant precursors were measured on an hourly basis from December 1, 2017, to February 27, 2018. The positive matrix factorization (PMF) method and the FLEXible PARTicle (FLEXPART) model were employed to identify the sources of PM_2.5. The results showed that the average mass concentration of PM_2.5 was 111 μg/m³ during the observation period. Among the major WSIs, sulfate, nitrate, and ammonium (SNA) constituted 62% of the total PM_2.5 mass, and NO₃^- ranked the highest with an average contribution of 24.6%. NH₄⁺ was abundant in most cases in Jiaozuo. According to chemical balance analysis, SO₄^2-, NO₃^-, and Cl^- might be present in the form of (NH₄)₂SO₄, NH₄NO₃, NH₄Cl, and KCl. The liquid-phase oxidation of SO₂ and NO₂ was severe during the haze period. The relative humidity and pH were the key factors influencing SO₄^2- formation. We found that NO₃^- mainly stemmed from homogeneous gas-phase reactions in the daytime and originated from the hydrolysis of N₂O₅ in the nighttime, which was inconsistent with previous studies. The PMF model identified five sources of PM_2.5: secondary origin (37.8%), vehicular emissions (34.7%), biomass burning (11.5%), coal combustion (9.4%), and crustal dust (6.6%).

Review of online source apportionment research based on observation for ambient particulate matter

Particulate matter source apportionment (SA) is the basis and premise for preventing and controlling haze pollution scientifically and effectively. Traditional offline SA methods lack the capability of handling the rapid changing pollution sources during heavy air pollution periods. With the development of multiple online observation techniques, online SA of particulate matter can now be realized with high temporal resolution, stable and reliable continuous observation data on particle compositions. Here, we start with a summary of online measuring instruments for monitoring particulate matters that contains both online mass concentration (online MC) measurement, and online mass spectrometric (online MS) techniques. The former technique collects ambient particulate matter onto filter membrane and measures the concentrations of chemical components in the particulate matter subsequently. The latter technique could be further divided into two categories: bulk measurement and single particle measurement. Aerosol Mass Spectrometers (AMS) could provide mass spectral information of chemical components of non-refractory aerosols, especially organic aerosols. While the emergence of single-particle aerosol mass spectrometer (SPAMS) technology can provide large number of high time resolution data for online source resolution. This is closely followed by an overview of the methods and results of SA. However, online instruments are still facing challenges, such as abnormal or missing measurements, that could impact the accuracy of online dataset. Machine leaning algorithm are suited for processing the large amount of online observation data, which could be further considered. In addition, the key research challenges and future directions are presented including the integration of online dataset from different online instruments, the ensemble-trained source apportionment approach, and the quantification of source-category-specific human health risk based on online instrumentation and SA methods.

Air pollutant variations in Suzhou during the 2019 novel coronavirus (COVID-19) lockdown of 2020: High time-resolution measurements of aerosol chemical compositions and source apportionment

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed rigorous restrictions, which resulted in great reductions in pollutant emissions. This study examines the characteristics of air pollutants, including PM_2.5 (particles with aerodynamic diameters < 2.5 μm), gas pollutants, water-soluble ions (WSIs), black carbon (BC) and elements, as well as the source apportionment of PM_2.5 in Suzhou before, during and after the Chinese New Year (CNY) holiday of 2020 (when China was under an unprecedented state of lockdown to restrict the COVID-19 outbreak). Compared to those before CNY, PM_2.5, BC, SNA (sulfate, nitrate and ammonium), other ions, elements, and NO₂ and CO mass concentrations decreased by 9.9%-64.0% during CNY. The lockdown policy had strong (weak) effects on the diurnal variations in aerosol chemical compositions (gas pollutants). Compared to those before CNY, source concentrations and contributions of vehicle exhaust during CNY decreased by 72.9% and 21.7%, respectively. In contrast, increased contributions from coal combustion and industry were observed during CNY, which were recorded to be 2.9 and 1.7 times higher than those before CNY, respectively. This study highlights that the lockdown policy that was imposed in Suzhou during CNY not only reduced the mass concentrations of air pollutants but also modified their diurnal variations and the source contributions of PM_2.5, which revealed the complex responses of PM_2.5 sources to the rare, low emissions of anthropogenic pollutants that occurred during the COVID-19 lockdown.

Temporal and Spatial Variation of PM2.5 in Xining, Northeast of the Qinghai–Xizang (Tibet) Plateau

PM2.5 was sampled from January 2017 to May 2018 at an urban, suburban, industrial, and rural sites in Xining. The annual mean of PM2.5 was highest at the urban site and lowest at the rural site, with an average of 51.5 ± 48.9 and 26.4 ± 17.8 μg·m−3, respectively. The average PM2.5 concentration of the industrial and suburban sites was 42.8 ± 27.4 and 37.2 ± 23.7 μg·m−3, respectively. All sites except for the rural had concentrations above the ambient air quality standards of China (GB3095-2012). The highest concentration of PM2.5 at all sites was observed in winter, followed by spring, autumn, and summer. The concentration of major constituents showed statistically significant seasonal and spatial variation. The highest concentrations of organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), and water-soluble inorganic ions (WSIIs) were found at the urban site in winter. The average concentration of F− was higher than that in many studies, especially at the industrial site where the annual average concentration of F− was 1.5 ± 1.7 μg·m−3. The range of sulfur oxidation ratio (SOR) was 0.1–0.18 and nitrogen oxidation ratio (NOR) was 0.02–0.1 in Xining. The higher SO42−/NO3− indicates that coal combustion has greater impact than vehicle emissions. The results of the potential source contribution function (PSCF) suggest that air mass from middle- and large-scale transport from the western areas of Xining have contributed to the higher level of PM2.5. On the basis of the positive matrix factorization (PMF) model, it was found that aerosols from salt lakes and dust were the main sources of PM2.5 in Xining, accounting for 26.3% of aerosol total mass. During the sandstorms, the concentration of PM2.5 increased sharply, and the concentrations of Na+, Ca2+ and Mg2+ were 1.13–2.70, 1.68–4.41, and 1.15–5.12 times higher, respectively, than annual average concentration, implying that aerosols were mainly from dust and the largest saltwater lake, Qinghai Lake, and many other salt lakes in the province of Qinghai. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was utilized to study the surface components of PM2.5 and F− was found to be increasingly distributed from the surface to inside the particles. We determined that the extremely high PM2.5 concentration appears to be due to an episode of heavy pollution resulting from the combination of sandstorms and the burning of fireworks.