Source apportionment of fine and coarse particles at a roadside and urban background site in London during the 2012 summer ClearfLo campaign

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.

Exploring the interplay between particulate matter capture, wash-off, and leaf traits in green wall species

The study investigated inter-species variation in particulate matter (PM) accumulation, wash-off, and retention on green wall plants, with a focus on leaf characteristics. Ten broadleaf plant species were studied in an experimental green wall. Ambient PM concentrations remained relatively stable throughout the measurement period: PM1: 16.60 ± 9.97 μgm-3, PM2.5: 23.27 ± 11.88 μgm-3, and PM10: 39.59 ± 25.72 μgm-3. Leaf samples were taken before and after three rainfall events, and PM deposition was measured using Scanning Electron Microscopy (SEM). Leaf micromorphological traits, including surface roughness, hair density, and stomatal density, exhibited variability among species and leaf surfaces. Notably, I.sempervirens and H.helix had relatively high PM densities across all size fractions. The study underscored the substantial potential of green wall plants for atmospheric PM removal, with higher Wall Leaf Area Index (WLAI) species like A.maritima and T.serpyllum exhibiting increased PM accumulation at plant level. Rainfall led to significant wash-off for smaller particles, whereas larger particles exhibited lower wash-off rates. Leaf micromorphology impacted PM accumulation, although effects varied among species, and parameters such as surface roughness, stomatal density, and leaf size did not consistently affect PM deposition. The composition of deposited particles encompassed natural, vehicular, salt, and unclassified agglomerates, with minimal changes after rainfall. Air Pollution Tolerance Index (APTI) assessments revealed that I.sempervirens displayed the highest air pollution tolerance, while O.vulgare had the lowest. APTI showed a moderate positive correlation with PM deposition across all fractions. The study concluded that the interplay of macro and micromorphology in green wall plant species determines their PM removal potential. Further research is needed to identify the key leaf characteristics for optimal green wall species selection for effective PM removal.

High-time resolution PM2.5 source apportionment assisted by spectrum-based characteristics analysis

Characteristics extraction and anomaly analysis based on frequency spectrum can provide crucial support for source apportionment of PM2.5 pollution. In this study, an effective source apportionment framework combining the Fast Fourier Transform (FFT)- and Continuous Wavelet Transform (CWT)-based spectral analyses and Positive Matrix Factorization (PMF) receptor model is developed for spectrum characteristics extraction and source contribution assessment. The developed framework is applied to Beijing during the winter heating period with 1-h time resolution. The spectrum characteristics of anomaly frequency, location, duration and intensity of PM2.5 pollution can be captured to gain an in-depth understanding of source-oriented information and provide necessary indicators for reliable PMF source apportionment. The combined analysis demonstrates that the secondary inorganic aerosols make relatively high contributions (50.59 %) to PM2.5 pollution during the winter heating period in Beijing, followed by biomass burning, vehicle emission, coal combustion, road dust, industrial process and firework emission sources accounting for 15.01 %, 11.00 %, 10.70 %, 5.31 %, 3.88 %, and 3.51 %, respectively. The source apportionment result suggests that combining frequency spectrum characteristics with source apportionment can provide consistent rationales for understanding the temporal evolution of PM2.5 pollution, identifying the potential source types and quantifying the related contributions.

Using Explainable Machine Learning to Interpret the Effects of Policies on Air Pollution: COVID-19 Lockdown in London

Activity changes during the COVID-19 lockdown present an opportunity to understand the effects that prospective emission control and air quality management policies might have on reducing air pollution. Using a regression discontinuity design for causal analysis, we show that the first UK national lockdown led to unprecedented decreases in road traffic, by up to 65%, yet incommensurate and heterogeneous responses in air pollution in London. At different locations, changes in air pollution attributable to the lockdown ranged from -50% to 0% for nitrogen dioxide (NO2), 0% to +4% for ozone (O3), and -5% to +0% for particulate matter with an aerodynamic diameter less than 10 μm (PM10), and there was no response for PM2.5. Using explainable machine learning to interpret the outputs of a predictive model, we show that the degree to which NO2 pollution was reduced in an area was correlated with spatial features (including road freight traffic and proximity to a major airport and the city center), and that existing inequalities in air pollution exposure were exacerbated: pollution reductions were greater in places with more affluent residents and better access to public transport services.

Estimating the geographical patterns and health risks associated with PM2.5-bound heavy metals to guide PM2.5 control targets in China based on machine-learning algorithms

PM2.5 is the main component of haze, and PM2.5-bound heavy metals (PBHMs) can induce various toxic effects via inhalation. However, comprehensive macroanalyses on large scales are still lacking. In this study, we compiled a substantial dataset consisting of the concentrations of eight PBHMs, including As, Cd, Cr, Cu, Mn, Ni, Pb and Zn, across different cities in China. To improve prediction accuracy, we enhanced the traditional land-use regression (LUR) model by incorporating emission source-related variables and employing the best-fitted machine-learning algorithm, which was applied to predict PBHM concentrations, analyze geographical patterns and assess the health risks associated with metals under different PM2.5 control targets. Our model exhibited excellent performance in predicting the concentrations of PBHMs, with predicted values closely matching measured values. Noncarcinogenic risks exist in 99.4% of the estimated regions, and the carcinogenic risks in all studied regions of the country are within an acceptable range (1 × 10-5-1 × 10-6). In densely populated areas such as Henan, Shandong, and Sichuan, it is imperative to control the concentration of PBHMs to reduce the number of patients with cancer. Controlling PM2.5 effectively decreases both carcinogenic and noncarcinogenic health risks associated with PBHMs, but still exceed acceptable risk level, suggesting that other important emission sources should be given attention.

Curbside particulate matter and susceptibility to SARS-CoV-2 infection

Background

Biologic plausibility for the association between exposure to particulate matter (PM) less than 10 μm in aerodynamic diameter (PM10) and coronavirus disease 2019 (COVID-19) morbidity in epidemiologic studies has not been determined. The upregulation of angiotensin-converting enzyme 2 (ACE2), the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) entry receptor on host cells, by PM10 is a putative mechanism.

Objective

We sought to assess the effect of PM10 on SARS-CoV-2 infection of cells in vitro.

Methods

PM10 from the curbside of London's Marylebone Road and from exhaust emissions was collected by cyclone. A549 cells, human primary nasal epithelial cells (HPNEpCs), SARS-CoV-2-susceptible Vero-E6 and Calu3 cells were cultured with PM10. ACE2 expression (as determined by median fluorescent intensity) was assessed by flow cytometry, and ACE2 mRNA transcript level was assessed by PCR. The role of oxidative stress was determined by N-acetyl cysteine. The cytopathic effect of SARS-CoV-2 (percentage of infection enhancement) and expression of SARS-CoV-2 genes' open reading frame (ORF) 1ab, S protein, and N protein (focus-forming units/mL) were assessed in Vero-E6 cells. Data were analyzed by either the Mann-Whitney U test or Kruskal-Wallis test with the Dunn multiple comparisons test.

Results

Curbside PM10 at concentrations of 10 μg/mL or more increased ACE2 expression in A549 cells (P = .0021). Both diesel PM10 and curbside PM10 in a concentration of 10 μg/mL increased ACE2 expression in HPNEpCs (P = .0022 and P = .0072, respectively). ACE2 expression simulated by curbside PM10 was attenuated by N-acetyl cysteine in HPNEpCs (P = .0464). Curbside PM10 increased ACE2 expression in Calu3 cells (P = .0256). In Vero-E6 cells, curbside PM10 increased ACE2 expression (P = .0079), ACE2 transcript level (P = .0079), SARS-CoV-2 cytopathic effect (P = .0002), and expression of the SARS-CoV-2 genes' ORF1ab, S protein, and N protein (P = .0079).

Conclusions

Curbside PM10 increases susceptibility to SARS-COV-2 infection in vitro.

Historical trends of traditional, emerging, and halogenated polycyclic aromatic hydrocarbons recorded in core sediments from the coastal areas of the Yellow and Bohai seas

Historical trends of polycyclic aromatic hydrocarbons (PAHs) contamination were reconstructed from eleven sediment cores located in intertidal zones of the Yellow and Bohai seas for a period encompassing the last 80 years. The analysis encompassed 15 traditional PAHs (t-PAHs), 9 emerging PAHs (e-PAHs), and 30 halogenated PAHs (Hl-PAHs), including 10 chlorinated PAHs (Cl-PAHs) and 20 brominated PAHs (Br-PAHs). Concentrations of target PAHs were highest in industrial and municipal areas situated along the coast of the Bohai Sea, including Huludao, Yingkou, Tianjin, and Dandong, constituting a substantial mass inventory. All target PAHs showed increasing trends since the 1950s, reflecting the development history of South Korea and China. High molecular weight PAHs accumulated in sampling sites more than low molecular weight PAHs. A positive matrix factorization model showed that the PAH sources were coal and gasoline combustion (35%), diesel combustion (33%), and biomass combustion (32%). Over the last 80 years, the contribution of coal and gasoline combustion increased in all regions, while diesel combustion and biomass combustion varied across regions and over time. Toxicity equivalence values were highest for t-PAHs (>99% contribution), followed by Cl-PAHs, Br-PAHs, and e-PAHs. Concentrations of t-PAHs in Eastern Asia seas have increased since the 1900s, particularly in intertidal areas compared to subtidal areas. The intertidal zone removed 83% of the total flux of PAHs originating from land and thus appears to serve as a buffer zone against marine pollution. Overall, this study provides novel knowledge on the historical trends and sources of PAHs on a large scale, along with insights for future coastal management.

Spatial distributions of PM10-bound metal elements in the central part of western Taiwan and their potential emission sources and the carcinogenic health risks

This study aimed to investigate the spatial distribution of metal elements in PM10 and their potential sources and associated health risks over a period of two years in eight locations in the central part of western Taiwan. The study revealed that the mass concentration of PM10 and the total mass concentration of 20 metal elements in PM10 were 39.0 μg m-3 and 4.74 μg m-3, respectively, with total metal elements accounting for approximately 13.0% of PM10. Of the total metal elements, 95.6% were crustal elements (Al, Ca, Fe, K, Mg, and Na), with trace elements (As, Ba, Cd, Cr, Co, Cu, Ga, Mn, Ni, Pb, Sb, Se, V, and Zn) contributing only 4.4%. Spatially, the inland areas exhibited higher PM10 concentrations due to lee-side topography and low wind speeds. In contrast, the coastal regions exhibited higher total metal concentrations because of the dominance of crustal elements from sea salt and crustal soil. Four primary sources of metal elements in PM10 were identified as sea salt (58%), re-suspended dust (32%), vehicle emissions and waste incineration (8%), and industrial emissions and power plants (2%). The positive matrix factorization (PMF) analysis results indicated that natural sources like sea salt and road dust contributed up to 90% of the total metal elements in PM10, while only 10% was attributed to human activities. The excess cancer risks (ECRs) associated with As, Co, and Cr(VI) were greater than 1 × 10-6, and the total ECR was 6.42 × 10-5. Although only 10% of total metal elements in PM10 came from human activities, they contributed to 82% of the total ECR.

Diesel exhaust particles exposure induces liver dysfunction: Exploring predictive potential of human circulating microRNAs signature relevant to liver injury risk

Diesel exhaust particles (DEP) pollution should be taken seriously because it is an extensive environmental and occupational health concern. Exploring early effect biomarkers is crucial for monitoring and managing DEP-associated health risk assessment. Here, we found that serum levels of 67 miRNAs were dysregulated in DEP exposure group. Notably, 20 miRNAs were identified as each having a significant dose-response relationship with the internal exposure level of DEP. Further, we revealed that the DEP exposure could affect the liver function of subjects and that 7 miRNAs (including the well-known liver injury indicator, miR-122-5p) could serve as the novel epigenetic-biomarkers (epi-biomarkers) to reflect the liver-specific response to the DEP exposure. Importantly, an unprecedented prediction model using these 7 miRNAs was established for the assessment of DEP-induced liver injury risk. Finally, bioinformatic analysis indicated that the unique set of miRNA panel in serum might also contribute to the molecular mechanism of DEP exposure-induced liver damage. These results broaden our understanding of the adverse health outcomes of DEP exposure. Noteworthy, we believe this study could shed light on roles and functions of epigenetic biomarkers from environmental exposure to health outcomes by revealing the full chain of exposure-miRNAs-molecular pathways-disease evidence.

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

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

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 (N_tot) 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 N_tot, 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 N_tot 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.

Determination of optimal height of barriers to reduce the amount of pollution in the viaduct settings in an idealized urban canyon: a numerical study

In this work, we numerically investigate the process of atmospheric air pollution in idealized urban canyons along the road in the presence of a viaduct, taking into account different height of barriers. To solve this problem, the 3D Reynolds-averaged Navier-Stokes equations (RANS) were used. The closure of this system of equations was achieved by using various turbulent models. The verification of the mathematical model and the numerical algorithm was carried out using a test problem. The obtained results using various turbulent models were compared with experimental data and calculated results of other authors. The main problem considered in this work is characterized as follows: assessment of emissions of pollutants between buildings using barriers of various types in the presence of a viaduct. Computational results have shown that the barrier viaduct plays a large role in improving air quality in urban canyons. So, for example, a barrier erected on a viaduct with a height of 2 m reduces the concentration value to a cross-section x = 84 by more than 2 times in comparison with the case of a complete absence of protective barriers. A similar situation was observed with barriers erected above the earth's surface: located along the road, they also significantly reduce the value of the concentration of pollutants. Thus, the presence of barriers in both cases is necessary to prevent the dispersion and deposition of pollutants.

Seasonal and vertical characteristics of particulate and elemental concentrations along diverse street canyons in South India

The impact of street geometries on vertical dispersion of PMs (PM_2.5 and PM₁₀) in (1) non-street canyon (NSC), (2) street canyon (SC), and (3) street canyon with viaduct (SCV) was studied during four seasons. The chemical composition of the species was analysed for source apportionment. The mass concentration of PMs in canyons was in the order of SCV > SC > NSC, implicating the canyon effect. Independent of height, most of the PM concentrations in SC and SCV violated the National Ambient Air Quality Standards (NAAQS) and exceeded the World Health Organization (WHO) guidelines in all three street geometries. The vertical concentration trend of PMs was significant during winter and summer seasons in NSC and SC. The vertical trend of both PMs was significant during summer and monsoon seasons in SCV. The seasonal change in PMs' vertical trend was influenced by atmospheric stability, wind velocities associated with street morphology, and emission sources. The ratio of PM_2.5/PM₁₀ indicated the dominance of PM₁₀ in all three locations. Among the estimated species, Fe (crustal and vehicle) and Na (sea salt and crustal) were abundant in PM_2.5 and PM₁₀, respectively. Estimation of enrichment factor (EF) revealed that most of the emission sources were anthropogenic in PM_2.5 and natural in PM₁₀. Principal component analysis (PCA) showed crustal/soil dust, vehicular emission, and sea salt to the common source profile for PMs. Specific contribution of smoking activity contributed to Be and Tl in PM_2.5, which may be considered a site-specific source.

Impact of short-term control measures on air quality: A case study during the 7th Military World Games in central China

The 7th Military World Games held in Wuhan (WH) in Oct 2019 provided an opportunity to clarify the impact of short-term control measures on air quality. Fine particulate matters (PM_2.5) were collected in WH, Huangshi (HS), and Huanggang (HG) during the control (Oct 13-28, 2019) and non-control periods (Oct 29- Nov 5, 2019). The results showed that air quality was good during the control period, with the concentrations of PM_2.5 and gaseous pollutants being below the Grade Ⅱ of China Ambient Air Quality Standard. Concentrations of PM_2.5 and its major chemical components in the control period were significantly lower than those in the non-control period, with reductions ranging from 17% (trace elements) to 46% (elemental carbon). However, higher contributions of secondary components such as SO₄^2-, NO₃^-, NH₄⁺ and secondary organic carbon (SOC) to PM_2.5 were observed during the control period, suggesting the important role of secondary transformation. Potential source contribution function (PSCF) of PM_2.5 showed that the main source regions were potentially located in surrounding cities Hubei Province, but regional transport can't be ignored. Six sources were identified by positive matrix factorization (PMF) for both control and non-control period. The contributions of combustion emissions and vehicle emissions were amplified in the control period, while the contribution of construction dust increased significantly when the control measures ended. Emission reductions contributed more to PM_2.5 concentration decrease in WH (55%) than that in HS (51%) and HG (49%), which was consistent with the stricter control measures implemented in WH. These results indicated that short-term controls were effective at lowering PM_2.5 concentration. However, the elevated contributions of secondary aerosols and the influence of regional transport on the study areas also need to be paid attention for air quality improvement in the future.

Comparison of concentrations of chemical species and emission sources PM2.5 before pandemic and during pandemic in Krakow, Poland

Observations of air pollution in Krakow have shown that air quality has been improved during the last decade. In the presented study two factors affecting the physicochemical characteristic of PM_2.5 fraction at AGH station in Krakow were observed. One is the ban of using solid fuels for heating purposes and the second is COVID-19 pandemic in Krakow. The PM_2.5 fraction was collected during the whole year every 3rd day between 2nd March 2020 and 28th February 2021 at AGH station in Krakow. In total 110 PM_2.5 fraction samples were collected. The chemical composition was determined for these samples. The elemental analysis was performed by energy dispersive X-ray fluorescence (EDXRF) technique, ions analysis was performed by ion chromatography (IC) and black carbon by optical method. In order to identify the emission sources the positive matrix factorization (PMF) was used. The results of such study were compared to similar analysis performed for PM_2.5 for the period from June 2018 to May 2019 at AGH station in Krakow. The PM_2.5 concentration dropped by 25% in 2020/2021 in comparison to 2018/2019 at this station. The concentrations of Si, K, Fe, Zn and Pb were lowering by 43-64% in the year 2020/2021 in comparison to 2018/2019. Cu, Mn, Zn and Pb come from mechanical abrasion of brakes and tires while Ti, Fe, Mn and Si are crustal species. They are the indicators of road dust (non-exhaust traffic source). Moreover, the annual average contribution of traffic/industrial/soil/construction work source was reduced in 2020/2021 in comparison to 2018/2019. As well the annual average contribution of fuels combustion was declining by 22% in 2020/2021 in comparison to 2018/2019. This study shows that the ban and lockdown, during COVID-19 pandemic, had significant impact on the characteristic of air pollution in Krakow.

Quantifying factors affecting contributions of roadway exhaust and non-exhaust emissions to ambient PM10-2.5 and PM2.5-0.2 particles

Traffic-related particulate matter (PM) plays an important role in urban air pollution. However, sources of urban pollution are difficult to distinguish. This study utilises a mobile particle concentrator platform and statistical tools to investigate factors affecting roadway ambient coarse particle (PM_10-2.5) and fine particle (PM_2.5-0.2) concentrations in greater Boston, USA. Positive matrix factorization (PMF) identified six PM_10-2.5 sources (exhaust, road salt, brake wear, regional pollution, road dust resuspension and tyre-road abrasion) and seven fine particle sources. The seven PM_2.5-0.2 sources include the six PM_10-2.5 sources and a source rich in Cr and Ni. Non- exhaust traffic-related sources together accounted for 65.6% and 29.1% of the PM_10-2.5 and PM_2.5-0.2 mass, respectively. While the respective contributions of exhaust sources were 10.4% and 20.7%. The biggest non-exhaust contributor in the PM_10-2.5 was road dust resuspension, accounting for 29.6%, while for the PM_2.5-0.2, the biggest non-exhaust source was road-tyre abrasion, accounting for 12.3%. We used stepwise general additive models (sGAMs) and found statistically significant (p < 0.05) effects of temperature, number of vehicles and rush hour periods on exhaust, brake wear, road dust resuspension and road-tyre abrasion with relative importance between 19.1 and 62.2%, 12.5-42.1% and 4.4-42.2% of the sGAM model's explained variability. Speed limit and road type were also important factors for exhaust, road-tyre and brake wear sources. Meteorological variables of wind speed and relative humidity were significantly associated with both coarse and fine road dust resuspension and had a combined relative importance of 38% and 48%. The quantifying results of the factors that influence traffic-related sources can offer key insights to policies aiming to improve near-road air quality.

Modeling of the effects of porous and solid barriers along the road from traffic emissions in idealized urban street canyons

In this paper, numerical modeling of concentration propagation using various types of barriers and trees with porosity properties in an idealized urban canyon to protect nearby houses was considered. To solve this problem, a modification of the Reynolds-averaged Navier-Stokes equations is used to take into account the porous medium. To validate the mathematical model and the numerical algorithm, a test problem was solved without taking into account various barriers with a source of pollution. After validation, the main problem was solved, describing the emission process of pollutants between houses using different types of grass barriers and trees with different porosity properties. The numerical simulation data were compared with the calculated values using various types of grass barriers and trees. Taking into account the optimal properties of porous trees in combination with barriers, it was found that height of the barrier itself has a minor role in the spread of pollutants.

Comparative Study of PM10 Concentrations and Their Elemental Composition Using Two Different Techniques during Winter—Spring Field Observation in Polish Village

The aims of this study were to determine the concentrations and elemental composition of PM10 in the village of Kotórz Mały (Poland), to analyse their seasonal variability, to determine the sources of pollutant emissions and to compare the consistency of the results obtained using different methods. Sampling and weather condition measurements were carried out in the winter (January–February) and spring (April) of 2019. Two combinations of different techniques were used to examine PM10 concentrations and their chemical composition: gravimetric method + atomic absorption spectrometry (GM+AAS) and continuous particle monitor + energy dispersive X-ray fluorescence (CPM+EDXRF). In winter, the average concentrations of PM10 measured by the GM and CPM were similar (GM 44.3 µg/m3; CPM 34.0 µg/m3), while in spring they were clearly different (GM 49.5 µg/m3; CPM 29.8 µg/m3). Both AAS and EDXRF proved that in both seasons, Ca, K and Fe had the highest shares in the PM10 mass. In the case of the lowest shares, the indications of the two methods were slightly different. Factor analysis indicated that air quality in the receptor was determined by soil erosion, coal and burning biomass, and the combustion of fuels in car engines; in the spring, air quality was also affected by gardening activities.

A Review of Road Traffic-Derived Non-Exhaust Particles: Emissions, Physicochemical Characteristics, Health Risks, and Mitigation Measures

Implementation of regulatory standards has reduced exhaust emissions of particulate matter from road traffic substantially in the developed world. However, nonexhaust particle emissions arising from the wear of brakes, tires, and the road surface, together with the resuspension of road dust, are unregulated and exceed exhaust emissions in many jurisdictions. While knowledge of the sources of nonexhaust particles is fairly good, source-specific measurements of airborne concentrations are few, and studies of the toxicology and epidemiology do not give a clear picture of the health risk posed. This paper reviews the current state of knowledge, with a strong focus on health-related research, highlighting areas where further research is an essential prerequisite for developing focused policy responses to nonexhaust particles.

Size-resolved, quantitative evaluation of the magnetic mineralogy of airborne brake-wear particulate emissions

Exposure to particulate air pollution has been associated with a variety of respiratory, cardiovascular and neurological problems, resulting in increased morbidity and mortality worldwide. Brake-wear emissions are one of the major sources of metal-rich airborne particulate pollution in roadside environments. Of potentially bioreactive metals, Fe (especially in its ferrous form, Fe²⁺) might play a specific role in both neurological and cardiovascular impairments. Here, we collected brake-wear particulate emissions using a full-scale brake dynamometer, and used a combination of magnetic measurements and electron microscopy to make quantitative evaluation of the magnetic composition and particle size of airborne emissions originating from passenger car brake systems. Our results show that the concentrations of Fe-rich magnetic grains in airborne brake-wear emissions are very high (i.e., ~100-10,000 × higher), compared to other types of particulate pollutants produced in most urban environments. From magnetic component analysis, the average magnetite mass concentration in total PM₁₀ of brake emissions is ~20.2 wt% and metallic Fe ~1.6 wt%. Most brake-wear airborne particles (>99 % of particle number concentration) are smaller than 200 nm. Using low-temperature magnetic measurements, we observed a strong superparamagnetic signal (indicative of ultrafine magnetic particles, < ~30 nm) for all of the analysed size fractions of airborne brake-wear particles. Transmission electron microscopy independently shows that even the larger size fractions of airborne brake-wear emissions dominantly comprise agglomerates of ultrafine (<100 nm) particles (UFPs). Such UFPs likely pose a threat to neuronal and cardiovascular health after inhalation and/or ingestion. The observed abundance of ultrafine magnetite particles (estimated to constitute ~7.6 wt% of PM_0.2) might be especially hazardous to the brain, contributing both to microglial inflammatory action and excess generation of reactive oxygen species.

Insights into Elemental Composition and Sources of Fine and Coarse Particulate Matter in Dense Traffic Areas in Toronto and Vancouver, Canada

Traffic is a significant pollution source in cities and has caused various health and environmental concerns worldwide. Therefore, an improved understanding of traffic impacts on particle concentrations and their components could help mitigate air pollution. In this study, the characteristics and sources of trace elements in PM_2.5 (fine), and PM_10-2.5 (coarse), were investigated in dense traffic areas in Toronto and Vancouver, Canada, from 2015–2017. At nearby urban background sites, 24-h integrated PM samples were also concurrently collected. The PM_2.5 and PM_10-2.5 masses, and a number of elements (i.e., Fe, Ba, Cu, Sb, Zn, Cr), showed clear increases at each near-road site, related to the traffic emissions resulting from resuspension and/or abrasion sources. The trace elements showed a clear partitioning trend between PM_2.5 and PM_10-2.5, thus reflecting the origin of some of these elements. The application of positive matrix factorization (PMF) to the combined fine and coarse metal data (86 total), with 24 observations at each site, was used to determine the contribution of different sources to the total metal concentrations in fine and coarse PM. Four major sources were identified by the PMF model, including two traffic non-exhaust (crustal/road dust, brake/tire wear) sources, along with regional and local industrial sources. Source apportionment indicated that the resuspended crustal/road dust factor was the dominant contributor to the total coarse-bound trace element (i.e., Fe, Ti, Ba, Cu, Zn, Sb, Cr) concentrations produced by vehicular exhaust and non-exhaust traffic-related processes that have been deposited onto the surface. The second non-exhaust factor related to brake/tire wear abrasion accounted for a considerable portion of the fine and coarse elemental (i.e., Ba, Fe, Cu, Zn, Sb) mass at both near-road sites. Regional and local industry contributed mostly to the fine elemental (i.e., S, As, Se, Cd, Pb) concentrations. Overall, the results show that non-exhaust traffic-related processes were major contributors to the various redox-active metal species (i.e., Fe, Cu) in both PM fractions. In addition, a substantial proportion of these metals in PM_2.5 was water-soluble, which is an important contributor to the formation of reactive oxygen species and, thus, may lead to oxidative damage to cells in the human body. It appears that controlling traffic non-exhaust-related metals emissions, in the absence of significant point sources in the area, could have a pronounced effect on the redox activity of PM, with broad implications for the protection of public health.

Bioaccessibility and public health risk of heavy Metal(loid)s in the airborne particulate matter of four cities in northern China

Atmospheric coarse particulate matter (PM₁₀) enriched with heavy metal(loid)s could pose potentially significant health risk to humans, while accurate health risk assessment calls for characterization of their bioaccessibility, besides the total contents. The health risk of major toxic heavy metal(loid)s in the PM₁₀ from four large cities in northern China via inhalation was investigated based on their total contents and bioaccessibility. The annual mean concentrations of PM-bound Zn, As, Pb, and Mn in the atmosphere of the four cities were 650, 305, 227, and 177 ng⋅m^-3, respectively. The levels of heavy metal(loid)s in the PM₁₀ were generally higher in winter but lower in summer in all four cities, which resulted primarily from the emissions associated with coal combustion for district and household heating and the unfavorable meteorological conditions in winter. The bioaccessibility of heavy metal(loid)s in the PM₁₀ ranged from 0.9 to 48.7%, following the general order of Mn > Co > Ni > Cd > Cu > As > Cr > Zn > Pb. Based on their total contents in the PM₁₀, most heavy metal(loid)s posed significant public health risk via inhalation exposure in the four cities. However, after accounting for the bioaccessibility of metal(loid)s, the non-carcinogenic risk of most metal(loid)s was negligible, except for As in the PM₁₀ of Jinzhong, while only the carcinogenic risk posed by Cr and As in the PM₁₀ exceeded the acceptable level. These findings demonstrate the importance of characterizing the bioaccessibility of airborne PM-bound heavy metal(loid)s in health risk assessment and could guide the on-going efforts on reducing the public health risk of PM₁₀ in northern China.

Characteristics and source attribution of PM2.5 during 2016 G20 Summit in Hangzhou: Efficacy of radical measures to reduce source emissions

A field campaign was conducted to study the PM_2.5 and atmospheric gases and aerosol's components to evaluate the efficacy of radical measures implemented by the Chinese government to improve air quality during the 2016 G20 Summit in Hangzhou China. The lower level of PM_2.5 (32.48 ± 11.03 µg/m³) observed during the control period compared to pre-control and post-control periods showed that PM_2.5 was alleviated by control policies. Based on the mass concentrations of particulate components, the emissions of PM_2.5 from local sources including fossil fuel, coal combustion, industry and construction were effectively reduced, but non-exhaust emission was not reduced as effectively as expected. The accumulation of SNA (SO₄^2-, NO₃^-, NH₄⁺) was observed during the control period, due to the favourable synoptic weather conditions for photochemical reactions and heterogeneous hydrolysis. Because of transboundary transport during the control period, air masses from remote areas contributed significantly to local PM_2.5. Although, secondary organic carbon (OC_sec) exhibited more sensitivity than primary organic carbon (OC_pri) to control measures, and the increased nitrogen oxidation ratio (NOR) implied the regional transport of aged secondary aerosols to the study area. Overall, the results from various approaches revealed that local pollution sources were kept under control, indicating that the implementation of mitigation measures were helpful in improving the air quality of Hangzhou during G20 summit. To reduce ambient levels of PM_2.5 further in Hangzhou, regional control policies may have to be taken so as to reduce the impact of long-range transport of air masses from inland China.

How human mega-events influence urban airborne PM2.5 pollution: A systematic review and meta-analysis

Air pollution caused by PM_2.5 particles is a critical issue for public health that adversely affects people living in urban cities. Short-term Mega-events such as international meetings, sports tournaments, and traditional festivals can profoundly influence the local air quality. However, the extent of these influences and their role in improving or deteriorating the local air quality is still unclear. By collecting relative research from 75 publications based on more than 37 cities worldwide, we conducted a systematic review and meta-analysis. We calculated the log response ratio (RR) of the treatment (during) and control periods (before and after) of the Mega-events. The short-term policy control measures enacted during the Mega-Events consisting of meetings caused a significant decline (by -44.06%) in the ambient PM_2.5 concentration. The mean daily PM_2.5 concentration reduced from more than 100.00 μg/m³ before the events to 60.39 μg/m³, which is below the WHO (World Health Organization) interim target - 1 (75 μg/m³). On the contrary, setting off fireworks during the festival increased the ambient PM_2.5 concentrations by 89.57% on average, with a mean daily value of 254.22 μg/m³. The variations in the effects of all event types on the air quality were primarily influenced by the background PM_2.5 concentrations, with a negative correlation throughout. Moreover, the impact of events with policy control measures was also influenced by the year of the event, level of control, and location (suburban/urban) of the monitoring sites. Our findings provide evidence of the potential of human intervention on PM_2.5 pollution reduction. We further highlight the crucial role of background pollution level in implementing policies during the Mega-events, which can benefit the environmental governance of developing countries.

Chemical source profiles of fine particles for five different sources in Delhi

Increasing emissions from sources such as construction and burning of biomass from crop residues, roadside and municipal solid waste have led to a rapid increase in the atmospheric concentrations of fine particulate matter (≤2.5 μm; PM_2.5) over many Indian cities. Analyses of their chemical profiles are important for receptor models to accurately estimate the contributions from different sources. We have developed chemical source profiles for five important pollutant sources - construction (CON), paved road dust (PRD), roadside biomass burning (RBB), solid waste burning (SWB), and crop residue burning (CPB) - during three intensive campaigns (winter, summer and post-monsoon) in and around Delhi. We obtained chemical characterisations of source profiles incorporating carbonaceous material such as organic carbon (OC) and elemental carbon (EC), water-soluble ions (F^-, Cl^-, NO₂^-, NO₃^-, SO₄^2-, PO₄^3-, Na⁺ and NH₄⁺), and elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Br, Rb, Sr, Ba, and Pb). CON was dominated by the most abundant elements, K, Si, Fe, Al, and Ca. PRD was also dominated by crustal elements, accounting for 91% of the total analysed elements. RBB, SWB and CPB profiles were dominated by organic matter, which accounted for 94%, 86.2% and 86% of the total PM_2.5, respectively. The database of PM emission profiles developed from the sources investigated can be used to assist source apportionment studies for accurate quantification of the causes of air pollution and hence assist governmental bodies in formulating relevant countermeasures.

Strong evidence for the continued contribution of lead deposited during the 20th century to the atmospheric environment in London of today

Although leaded gasoline was banned at the end of the last century, lead (Pb) remains significantly enriched in airborne particles in large cities. The remobilization of historical Pb deposited in soils from atmospheric removal has been suggested as an important source providing evidence for the hypothetical long-term persistency of lead, and possibly other pollutants, in the urban environment. Here, we present data on Pb isotopic composition in airborne particles collected in London (2014 to 2018), which provide strong support that lead deposited via gasoline combustion still contributes significantly to the lead burden in present-day London. Lead concentration and isotopic signature of airborne particles collected at a heavily trafficked site did not vary significantly over the last decade, suggesting that sources remained unchanged. Lead isotopic composition of airborne particles matches that of road dust and topsoils and can only be explained with a significant contribution (estimate of 32 ± 10 to 43 ± 9% based on a binary mixing model) of Pb from leaded gasoline. The lead isotopes furthermore suggest significant contributions from nonexhaust traffic emissions, even though isotopic signatures of anthropogenic sources are increasingly overlapping. Lead isotopic composition of airborne particles collected at building height shows a similar signature to that collected at street level, suggesting effective mixing of lead within the urban street canyon. Our results have important implications on the persistence of Pb in urban environments and suggest that atmospheric Pb reached a baseline in London that is difficult to decrease further with present policy measures.

Sources of indoor PM2.5 gross α and β activities measured in 340 homes

Particle radioactivity (PR) exposure has been linked to adverse health effects. PR refers to the presence of α- and β-emitting radioisotopes attached to fine particulate matter (PM_2.5). This study investigated sources contributing to indoor PM_2.5 gross α- and β-radioactivity levels. We measured activity from long-lived radon progeny radionuclides from archived PM_2.5 samples collected in 340 homes in Massachusetts during the period 2006-2010. We analyzed the data using linear mixed effects models and positive matrix factorization (PMF) analysis. Indoor PM_2.5 gross α-activity levels were correlated with sulfur (S), iron (Fe), bromine (Br), vanadium (V), sodium (Na), lead (Pb), potassium (K), calcium (Ca), silicon (Si), zinc (Zn), arsenic (As), titanium (Ti), radon (²²²Rn) and black carbon (BC) concentrations (p <0.05). Indoor PM_2.5 β-activity was correlated with S, As, antimony (Sb), Pb, Br and BC. We identified four indoor PM_2.5 sources: outdoor air pollution (62%), salt aerosol source (14%), fireworks and environmental tobacco smoke (7%) and indoor mixed dust (17%). Outdoor air pollution was the most significant contributor to indoor PM_2.5 α- and β-activity levels. The contributions of this source were during the summer months and when windows were open. Indoor mixed dust was also found to contribute to PM_2.5 α-activity. PM_2.5 α-activity was further associated with radon during winter months, showing radon's important role as an indoor source of ionizing radiation.

Macrozoobenthic community responses to sedimentary contaminations by anthropogenic toxic substances in the Geum River Estuary, South Korea

We investigated the sedimentary pollution by persistent toxic substances (PTSs) and their potential impacts on the macrobenthic faunal community in the Geum River Estuary, South Korea. Sediment and benthic macrofauna samples were collected from eight sites every two months during the period of February to December in 2015. Target PTSs encompassed metals (Cd, Cr, Cu, Hg, Ni, Pb, and Zn), one metalloid (As), polycyclic aromatic hydrocarbons (PAHs), and alkylphenols (APs). The significant difference to the environment of the inner and outer parts of the estuary (p < 0.05) was found with relatively high concentrations of PTSs in sediment from the inner estuary. The concentrations of Cu and Zn exceeded the sediment quality guidelines of Korea representing a potential risk to aquatic organisms. The primary source of PAHs was by-products of diesel and gasoline combustion (37%), followed by a coke oven (32%) and oil-burning (31%). The macrofaunal community was spatially distinguished between the inner and outer parts of the estuary (p < 0.05), regardless of the season. In the inner part of the estuary, the density of the macrofaunal community was high, due to the increased opportunistic species and/or some indicator species (organic polluted or enrichment), implying that the given environment was disturbed. Among the environmental parameters analyzed by the distance-based linear model (DistLM), salinity, chlorophyll-a, and nutrient concentrations were found to be key factors controlling the changes in macrofaunal community structure. Such changes in the closed estuary system would indicate that each taxonomic group had to adjust to lower salinities and alternative food sources. Overall, the distribution of PTSs and macrozoobenthic communities in the Geum River Estuary collectively reflected the environmental gradients caused by surrounding activities in the inner part of the estuary together with direct effects by the irregular inflow of freshwater.

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.

Association of systemic inflammation and coagulation biomarkers with source-specific PM2.5 mass concentrations among young and elderly subjects in central Tehran

In this study, we investigated the association between short-term exposure to different sources of fine particulate matter (PM_2.5) and biomarkers of coagulation and inflammation in two different panels of elderly and healthy young individuals in central Tehran. Five biomarkers, including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF) were analyzed in the blood samples drawn every 8 weeks from the subjects between May 2012 and May 2013. The studied populations consisted of 44 elderly individuals at a retirement home as well as 40 young adults residing at a school dormitory. Positive Matrix Factorization (PMF)-resolved source-specific PM_2.5 mass concentrations and biomarker levels were used as the input to the linear mixed-effects regression model to evaluate the impact of exposure to previously identified PM sources at retirement home and school dormitory in two time lag configurations: lag 1-3 (1-3 days before the blood sampling), and lag 4-6 (4-6 days before the blood sampling). Our analysis of the elderly revealed positive associations of all biomarkers (except hsCRP) with particles of secondary origin in both time lags, further corroborating the toxicity of secondary aerosols formed by photochemical processing in central Tehran. Moreover, industrial emissions, and road dust particles were positively associated with WBC, sTNF-RII, and IL-6 among seniors, while vehicular emissions exhibited positive associations with all biomarkers in either first- or second-time lag. In contrast, most of the PM_2.5 sources showed insignificant associations with biomarkers of inflammation in the panel of healthy young subjects. Therefore, findings from this study indicated that various PM_2.5 sources increase the levels of inflammation and coagulation biomarkers, although the strength and significance of these associations vary depending on the type of PM sources, demographic characteristics, and differ across the different time lags. Implications: Tehran, the capital of Iran with a population of more than 9 million people, has been facing serious air pollution challenges as a result of extensive vehicular, and industrial activities in the previous years. Among various air pollutants in Tehran, fine particulate matters (PM_2.5, particles with aerodynamic diameters < 2.5 µm) are known as one of the most important critical pollutants, causing several adverse health impacts including lung cancer, respiratory, cardiovascular, and cardiopulmonary diseases. Therefore, a number of studies in the area have tried to investigate the adverse health impacts of exposure to PM_2.5. However, no studies have ever been conducted in Tehran to examine the association between specific PM_2.5 sources and biomarkers of coagulation and systemic inflammation as indicators of cardiovascular disorders. Indeed, this is the first study in the area investigating the association of source-specific PM_2.5 with biomarkers of inflammation including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF). Our results have important implications for policy makers in identifying the most toxic sources of PM_2.5, and in turn designing schemes for mitigating adverse health impacts of air pollution in Tehran.

Quantification of Non-Exhaust Particulate Matter Traffic Emissions and the Impact of COVID-19 Lockdown at London Marylebone Road

This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data were used to determine the traffic increment (roadside–background) and covered a range of meteorological conditions, seasons, and driving styles, as well as the influence of the COVID-19 “lockdown” on non-exhaust concentrations. Non-exhaust particulate matter (PM)10 concentrations were calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc), and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 “dilution approach”. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicate that non-exhaust emission factors were dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds, and meteorological conditions, as well as advanced source apportionment of the PM measurement data, were undertaken to enhance our understanding of these important vehicle sources.

Source apportionment of magnetite particles in roadside airborne particulate matter

Exposure to airborne particulate matter (PM) is associated with pulmonary, cardiovascular and neurological problems. Magnetite, a mixed Fe²⁺/Fe³⁺ oxide, is ubiquitous and abundant in PM in urban environments, and might play a specific role in both neurodegeneration and cardiovascular disease. We collected samples of vehicle exhaust emissions, and of heavily-trafficked roadside and urban background dusts from Lancaster and Birmingham, U.K. Then, we measured their saturation magnetic remanence and used magnetic component analysis to separate the magnetite signal from other contributing magnetic components. Lastly, we estimated the contributions made by specific traffic-related sources of magnetite to the total airborne magnetite in the roadside environment. The concentration of magnetite in exhaust emissions is much lower (3-14 x lower) than that in heavily- trafficked roadside PM. The magnetite concentration in petrol-engine exhaust emissions is between ~0.06 and 0.12 wt%; in diesel-engine exhaust emissions ~0.08-0.18 wt%; in background dust ~0.05-0.20 wt% and in roadside dust ~0.18-0.95 wt%. Here, we show that vehicle brake wear is responsible for between ~68 and 85% of the total airborne magnetite at the two U.K. roadside sites. In comparison, diesel-engine exhaust emissions account for ~7% - 12%, petrol-engine exhaust emissions for ~2% - 4%, and background dust for 6% - 10%. Thus, vehicle brake wear is by far the most dominant source of airborne magnetite in the roadside environment at the two sites examined. Given the potential risk posed, post-inhalation, by ultrafine magnetite and co-associated transition metal-rich particles to human cardiovascular and neurological health, the high magnetite content of vehicle brake wear might need to be reduced in order to mitigate such risk, especially for vulnerable population groups.

Indoor particulate air pollution from open fires and the cognitive function of older people

Exposure to indoor air pollution is known to affect respiratory and cardiovascular health, but little is known about its effects on cognitive function. We measured the concentrations and magnetite content of airborne particulate matter (PM) in the indoor environment arising from burning peat, wood or coal in residential open fires. Highest indoor PM_2.5 concentrations (60 μg/m³ i.e. 2.4 times the WHO-recommended 24-h mean) occurred when peat was burned, followed by burning of coal (30 μg/m³) and wood (17 μg/m³). Conversely, highest concentrations of coarser PM (PM_10-2.5) were associated with coal burning (20 μg/m³), with lower concentrations emitted during burning of wood (10 μg/m³) and peat (8 μg/m³). The magnetic content of the emitted PM, greatest (for both PM size fractions) when coal was burned, is similar to that of roadside airborne PM. Exposure to PM, and to strongly magnetic airborne PM, can be greater for individuals spending ~5 h/day indoors with a coal-burning open fire for 6 months/year compared to those commuting via heavily-trafficked roads for 1 h/day for 12 months/year. Given these high indoor PM and magnetite concentrations, and the reported associations between (outdoor) PM and impaired neurological health, we used individual-level data from The Irish Longitudinal Study on Ageing (TILDA) to examine the association between the usage of open fires and the cognitive function of older people. Using a sample of nearly seven thousand older people, we estimated multi-variate models of the association between cognitive function and open fire usage, in order to account for relevant confounders such as socio-economic status. We found a negative association between open fire usage and cognitive function as measured by widely-used cognitive tests such as word recall and verbal fluency tests. The negative association was largest and statistically strongest among women, a finding explained by the greater exposure of women to open fires in the home because they spent more time at home than men. Our findings were also robust to stratifying the sample between old and young, rich and poor, and urban and rural.

Particulate matter exchange between atmosphere and roads surfaces in urban areas

The deposition and the re-suspension of particulate matter (PM) in urban areas are the key processes that contribute not only to stormwater pollution, but also to air pollution. However, investigation of the deposition and the re-suspension of PM is challenging because of the difficulties in distinguishing between the resuspended and the deposited PM. This study created two Bayesian Networks (BN) models to explore the deposition and the re-suspension of PM as well as the important influential factors. The outcomes of BN modelling revealed that deposition and re-suspension of PM10 occurred under both, high-traffic and low-traffic conditions, and the re-suspension of PM2.5 occurred under low-traffic conditions. The deposition of PM10 under low-volume traffic condition is 1.6 times higher than under high-volume traffic condition, which is attributed to the decrease in PM10 caused by relatively higher turbulence under high-volume traffic conditions. PM10 is more easily resuspended from road surfaces compared to PM2.5 as the particles which larger than the thickness of the laminar airflow over the road surface are more easily removed from road surfaces. The increase in wind speed contributes to the increase in PM build-up by transporting particulates from roadside areas to the road surfaces and the airborne PM2.5 and PM10 increases with the increase in relative humidity. The study outcomes provide a step improvement in the understanding of the transfer processes of PM2.5 and PM10 between atmosphere and urban road surfaces, which in turn will contribute to the effective design of mitigation measures for urban stormwater and air pollution.

Combining Cluster Analysis of Air Pollution and Meteorological Data with Receptor Model Results for Ambient PM2.5 and PM10

Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM2.5 and PM10. We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.

Current contamination status of traditional and emerging persistent toxic substances in the sediments of Ulsan Bay, South Korea

Contamination status of traditional and emerging persistent toxic substances (PTSs) in sediments and their major sources were investigated in Ulsan Bay, Korea. A total of 47 PTSs, including 15 traditional PAHs, ten styrene oligomers (SOs), six alkylphenols (APs), and 16 emerging PAHs (E-PAHs) were analyzed. Concentrations of traditional PAHs, SOs, and APs ranged from 35 to 1300 ng g^-1 dry weight (dw), 30 to 3800 ng g^-1 dw, and 30 to 430 ng g^-1 dw, respectively. For the last 20 years, PTSs contamination in the bay area has been improved. However, 12 E-PAHs were widely detected in sediments, with a maximum of 240 ng g^-1 dw (for benzo[e]pyrene) at the creek site. These E-PAHs seemed to originate from surrounding activities, such as biomass combustion, mobile sources, and diesel combustion. Due to environmental concerns for E-PAHs, further research on the potential toxicity, distribution, and behavior of these compounds should be implemented.

Neighbourhood-scale dispersion of traffic-induced ultrafine particles in central London: WRF large eddy simulations

Traffic-generated ultrafine particles (UFPs) in the urban atmosphere have a high proportion of their composition comprised of semi-volatile compounds (SVOCs). The evaporation/condensation processes of these SVOCs can alter UFP number size distributions and play an important role in determining the fate of UFPs in urban areas. The neighbourhood-scale dispersion (over distances < 1 km) and evolution of traffic-generated UFPs for a real-world street network in central London was simulated by using the WRF-LES model (the large eddy simulation mode of the Weather Research and Forecasting modelling system) coupled with multicomponent microphysics. The neighbourhood scale dispersion of UFPs was significantly influenced by the spatial pattern of the real-world street emissions. Model output indicated the shrinkage of the peak diameter from the emitted profile to the downwind profile, due to an evaporation process during neighbourhood-scale dispersion. The dilution process and the aerosol microphysics interact with each other during the neighbourhood dispersion of UFPs, yielding model output that compares well with measurements made at a location downwind of an intense roadside source. The model captured the total SVOC concentrations well, with overestimations for gas concentrations and underestimations for particle concentrations, particularly of the lighter SVOCs. The contribution of the intense source, Marylebone Road (MR) in London, to concentrations at the downwind location (as estimated by a model scenario with emissions from MR only) is comparable with that of the rest of the street network (a scenario without emissions from MR), implying that both are important. An appreciable level of non-linearity is demonstrated for nucleation mode UFPs and medium range carbon SVOCs at the downwind receptor site.

Source apportionment of size-segregated atmospheric particles and the influence of particles deposition in the human respiratory tract in rural and urban locations of north-east India

Aerosol samples were collected using eight stage non-viable Andersen cascade impactor at three urban and two rural sites in north-east India during 2018 covering three seasons i.e., winter, summer and monsoon. The size-segregated samples collected in the selected locations were carefully analysed in terms of deposition in human respiratory tract using inhalation and deposition curves. Seasonal variation of fractional deposition of particulate matter (PM) in human respiratory tract was observed. For example, during winter, in one of the urban sites i.e., S3 (0.61) the maximum deposition was in Pulmonary (P) region, while in the case of other sites, the maximum deposition was in Nasopharyngeal (NOPL) region. Regional deposition in P was high in S1 and S3 when compared with other sites. Vehicular emissions was dominant in both S1 and S3 in P, while biomass burning being dominant in S3 which could be the reason for maximum deposition in P. Positive matrix factorization (PMF) revealed five to eight factors at each individual site in NOPL, tracheobronchial (TB) and P regions: biomass burning (accounting for 7-32% of PM), coal combustion (14-27%), construction dust (9-25%), dust emissions (17-28%), industrial emissions (12-26%), oil refinery (18%), secondary aerosols (17-33%) and vehicular emissions (12-39%). Dominant sources in urban and rural areas were vehicular emissions and dust emissions, respectively. Therefore, the present study highlights the importance of analyzing source apportionment of PM at ultrafine scale and forms a basis upon which the future air quality studies and mitigation strategies can be formulated in this region.

WITHDRAWN: Allergic mechanisms of asthma are enhanced during the summer with oxidant PM10 components

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Chemical characterization and source apportionment of ambient nanoparticles: a case study in Hanoi, Vietnam

PM_0.1 has been believed to have adverse short- and long-term effects on human health. However, the information of PM_0.1 that is needed to fully evaluate its influence on human health and environment is still scarce in many developing countries. This is a comprehensive study on the levels, chemical compositions, and source apportionment of PM_0.1 conducted in Hanoi, Vietnam. Twenty-four-hour samples of PM_0.1 were collected during the dry season (November to December 2015) at a mixed site to get the information on mass concentrations and chemical compositions. Multiple linear regression analysis was utilized to investigate the simultaneous influence of meteorological factors on fluctuations in the daily levels of PM_0.1. Multiple linear regression models could explain about 50% of the variations of PM_0.1 concentrations, in which wind speed is the most important variable. The average concentrations of organic carbon (OC), elemental carbon (EC), water-soluble ions (Ca²⁺, K⁺, Mg²⁺, Na⁺, NH₄⁺, Cl^-, NO₃^-, SO₄^2-, C₂O₄^2-), and elements (Be, Al, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Sb, Ba, Tl, Pb, Na, Fe, Mg, K, and Ca) were 2.77 ± 0.90 μg m^-3, 0.63 ± 0.28 μg m^-3, 0.88 ± 0.39 μg m^-3, and 0.05 ± 0.02 μg m^-3, accounting for 51.23 ± 9.32%, 11.22 ± 2.10%, 16.28 ± 2.67%, and 1.11 ± 0.94%, respectively. A positive matrix factorization model revealed the contributions of five major sources to the PM_0.1 mass including traffic (gasoline and diesel emissions, 46.28%), secondary emissions (31.18%), resident/commerce (12.23%), industry (6.05%), and road/construction (2.92%).

Long-term trends in PM2.5 mass and particle number concentrations in urban air: The impacts of mitigation measures and extreme events due to changing climates

Urbanisation and industrialisation led to the increase of ambient particulate matter (PM) concentration. While subsequent regulations may have resulted in the decrease of some PM matrices, the simultaneous changes in climate affecting local meteorological conditions could also have played a role. To gain an insight into this complex matter, this study investigated the long-term trends of two important matrices, the particle mass (PM_2.5) and particle number concentrations (PNC), and the factors that influenced the trends. Mann-Kendall test, Sen's slope estimator, the generalised additive model, seasonal decomposition of time series by LOESS (locally estimated scatterplot smoothing) and the Buishand range test were applied. Both PM_2.5 and PNC showed significant negative monotonic trends (0.03-0.6 μg m^-3. yr^-1 and 0.40-3.8 × 10³ particles. cm^-3. yr^-1, respectively) except Brisbane (+0.1 μg m^-3. yr^-1 and +53 particles. cm^-3. yr^-1, respectively). For the period covered in this study, temperature increased (0.03-0.07 °C.yr^-1) in all cities except London; precipitation decreased (0.02-1.4 mm. yr^-1) except in Helsinki; and wind speed was reduced in Brisbane and Rochester but increased in Helsinki, London and Augsburg. At the change-points, temperature increase in cold cities influenced PNC while shifts in precipitation and wind speed affected PM_2.5. Based on the LOESS trend, extreme events such as dust storms and wildfires resulting from changing climates caused a positive step-change in concentrations, particularly for PM_2.5. In contrast, among the mitigation measures, controlling sulphur in fuels caused a negative step-change, especially for PNC. Policies regarding traffic and fleet management (e.g. low emission zones) that were implemented only in certain areas or in a progressive uptake (e.g. Euro emission standards), resulted to gradual reductions in concentrations. Therefore, as this study has clearly shown that PM_2.5 and PNC were influenced differently by the impacts of the changing climate and by the mitigation measures, both metrics must be considered in urban air quality management.

Investigating the impacts of coal-fired power plants on ambient PM2.5 by a combination of a chemical transport model and receptor model

Aimed at evaluating the impacts of coal-fired power plants on urban air quality and human health, a one-month intensive observation campaign was conducted in a typical polluted city located in the 2 + 26 city cluster (Beijing, Tianjin and 26 other cities) of the North China Plain in December 2017. The observation results illustrated that the coal-fired power plant in this city increased the monthly average fine particulate matter (PM_2.5) concentration by ~5% at the city scale. The impacts differed under various diffusion conditions. A three-dimensional nested air quality condition model (the Nested Air Quality Perdition Model System or NAQPMS) with source apportionment was employed to analyze the impacts. The results indicated that power plants had the largest effect on regional air quality during the severe-pollution period, while any influence could be ignored during periods with excellent dissipation under robust winds. PM_2.5 contributed by the power plant mainly occurred below 150 m, diffused 100 km away, and reached a level of approximately 5 μg m^-3 during the light-pollution period. During the accumulation period, the plume reached a height of 500 m, diffused to the downwind area approximately 100 km away within half a day, and contributed at most 40 μg m^-3 to PM_2.5. The affected area expanded to 250 km during the severe-pollution period, and the contribution to PM_2.5 was at least 10 μg m^-3 at different distances. The affected height reached approximately 500 m, with PM_2.5 exceeding 10 μg m^-3, mainly constrained below 150 m. Overall, regional integrated control strategies should be implemented for the power plants in the 2 + 26 city cluster during pollution episodes to further improve air quality.

Seasonal characteristics of aerosols (PM2.5 and PM10) and their source apportionment using PMF: A four year study over Delhi, India

The present study attempts to explore and compare the seasonal variability in chemical composition and contributions of different sources of fine and coarse fractions of aerosols (PM_2.5 and PM₁₀) in Delhi, India from January 2013 to December 2016. The annual average concentrations of PM_2.5 and PM₁₀ were 131 ± 79 μg m^-3 (range: 17-417 μg m^-3) and 238 ± 106 μg m^-3 (range: 34-537 μg m^-3), respectively. PM_2.5 and PM₁₀ samples were chemically characterized to assess their chemical components [i.e. organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSICs) and heavy and trace elements] and then used for estimation of enrichment factors (EFs) and applied positive matrix factorization (PMF5) model to evaluate their prominent sources on seasonal basis in Delhi. PMF identified eight major sources i.e. Secondary nitrate (SN), secondary sulphate (SS), vehicular emissions (VE), biomass burning (BB), soil dust (SD), fossil fuel combustion (FFC), sodium and magnesium salts (SMS) and industrial emissions (IE). Total carbon contributes ∼28% to the total PM_2.5 concentration and 24% to the total PM₁₀ concentration and followed the similar seasonality pattern. SN and SS followed opposite seasonal pattern, where SN was higher during colder seasons while SS was greater during warm seasons. The seasonal differences in VE contributions were not very striking as it prevails evidently most of year. Emissions from BB is one of the major sources in Delhi with larger contribution during winter and post monsoon seasons due to stable meteorological conditions and aggrandized biomass burning (agriculture residue burning in and around the regions; mainly Punjab and Haryana) and domestic heating during the season. Conditional Bivariate Probability Function (CBPF) plots revealed that the maximum concentrations of PM_2.5 and PM₁₀ were carried by north westerly winds (north-western Indo Gangetic Plains of India).

Characterization of atmospheric PM2.5 sources at a Central European urban background site

For the purposes of this work, a first in Poland, full-year collection of daily PM_2.5 (particulate matter with aerodynamic diameter smaller than 2.5 μm) samples was chemically analyzed to determine the contents of elemental and organic carbon, water-soluble inorganic ions and 21 minor and trace elements in PM in an urban background site in Warsaw. Annual mean PM_2.5 concentration reached 18.8 μg/m³, with the lowest levels in summer (11.5 μg/m³ on average) and the highest in winter (27.5 μg/m³), with several episodes reaching over 80 μg/m³. Strong seasonal differences were observed mainly for the contents of nitrate and secondary organic carbon (SOC), while sulphate showed the least variability. Secondary species constituted on average 45% of PM_2.5 mass, suggesting large influence of regional and long-range transport of pollutants. Source apportionment with the use of positive matrix factorization (PMF) method, supported by the analysis of enrichment factors, led to identification of six main sources of PM_2.5 origin: residential combustion (fresh & aged aerosol) (46% of PM_2.5 mass), traffic exhaust (21%) and non-exhaust (10%) emissions, mineral dust/construction works (12%), high-temperature processes (8%) and steel processing (3%). Including primary organic carbon (POC) and SOC as two separate constituents helped to distinguish between the primary and secondary sources of the aerosol. The identification of sources was also supported by investigating their yearly and weekly profiles, as well as the correlation of PM constituents with meteorological conditions, which are one of the main drivers of heat generation activities. We found that the most distinctive markers of PM sources in Warsaw are SOC, Cl^- and As for residential combustion, NH₄⁺, Sb and POC for road transport, Ca and Mg for construction works and SO₄^2- for long-range transport of PM.

Hazardous trace elements in thoracic fraction of airborne particulate matter: Assessment of temporal variations, sources, and health risks in a megacity

The deleterious health effects of thoracic fractions seem to be more related to the chemical composition of the particles than to their mass concentration. The presence of hazardous materials in PM₁₀ (e.g., heavy metals and metalloids) causes risks to human health. In this study, twelve trace elements (Cd, Cr, Pb, Zn, Cu, Ni, Sn, Ba, Co, As, V, and Sb) in 315 samples of ambient PM₁₀ were analyzed. The samples were collected at an urban background site in a Latin American megacity (Bogota, Colombia) for one year. The concentrations and temporal variabilities of these elements were examined. According to the results, Cu (52 ng/m³), Zn (44 ng/m³), Pb (25 ng/m³), and Ba (20 ng/m³) were the traces with the highest concentrations, particularly during the dry season (January to March), which was characterized by barbecue (BBQ) charcoal combustion and forest fires. In addition, the differences between the results of weekdays and weekends were identified. The determined enrichment factor (EF) indicated that Zn, Pb, Sn, Cu, Cd, and Sb mainly originated from anthropogenic sources. Moreover, a speciation analysis of inorganic Sb (EF > 300) was conducted, which revealed that Sb(V) was the main Sb species in the PM₁₀ samples (>80%). Six causes for the hazardous elements were identified based on the positive matrix factorization (PMF) model: fossil fuel combustion and forest fires (60%), road dust (19%), traffic-related emissions (9%), copper smelting (8%), the iron and steel industry (2%), and an unidentified industrial sector (2%). Furthermore, a health risk assessment of the carcinogenic elements was performed. Accordingly, the cancer risk of inhalation exposure to Co, Ni, As, Cd, Sb(III), and Pb was negligible for children and adults at the sampling site. For adults, the adjusted Cr(VI) level was slightly higher than the minimal acceptable risk level during the study period (1.4 × 10^-6).

The nexus between air pollution, green infrastructure and human health

Cities are constantly evolving and so are the living conditions within and between them. Rapid urbanization and the ever-growing need for housing have turned large areas of many cities into concrete landscapes that lack greenery. Green infrastructure can support human health, provide socio-economic and environmental benefits, and bring color to an otherwise grey urban landscape. Sometimes, benefits come with downsides in relation to its impact on air quality and human health, requiring suitable data and guidelines to implement effective greening strategies. Air pollution and human health, as well as green infrastructure and human health, are often studied together. Linking green infrastructure with air quality and human health together is a unique aspect of this article. A holistic understanding of these links is key to enabling policymakers and urban planners to make informed decisions. By critically evaluating the link between green infrastructure and human health via air pollution mitigation, we also discuss if our existing understanding of such interventions is sufficient to inform their uptake in practice. Natural science and epidemiology approach the topic of green infrastructure and human health very differently. The pathways linking health benefits to pollution reduction by urban vegetation remain unclear and the mode of green infrastructure deployment is critical to avoid unintended consequences. Strategic deployment of green infrastructure may reduce downwind pollution exposure. However, the development of bespoke design guidelines is vital to promote and optimize greening benefits, and measuring green infrastructure's socio-economic and health benefits are key for their uptake. Greening cities to mitigate pollution effects is on the rise and these need to be matched by scientific evidence and appropriate guidelines. We conclude that urban vegetation can facilitate broad health benefits, but there is little empirical evidence linking these benefits to air pollution reduction by urban vegetation, and appreciable efforts are needed to establish the underlying policies, design and engineering guidelines governing its deployment.

Airborne, Vehicle-Derived Fe-Bearing Nanoparticles in the Urban Environment: A Review

Airborne particulate matter poses a serious threat to human health. Exposure to nanosized (<0.1 μm), vehicle-derived particulates may be hazardous due to their bioreactivity, their ability to penetrate every organ, including the brain, and their abundance in the urban atmosphere. Fe-bearing nanoparticles (<0.1 μm) in urban environments may be especially important because of their pathogenicity and possible association with neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases. This review examines current knowledge regarding the sources of vehicle-derived Fe-bearing nanoparticles, their chemical and mineralogical compositions, grain size distribution and potential hazard to human health. We focus on data reported for the following sources of Fe-bearing nanoparticles: exhaust emissions (both diesel and gasoline), brake wear, tire and road surface wear, resuspension of roadside dust, underground, train and tram emissions, and aircraft and shipping emissions. We identify limitations and gaps in existing knowledge as well as future challenges and perspectives for studies of airborne Fe-bearing nanoparticles.

Ultrafine particles and PM2.5 in the air of cities around the world: Are they representative of each other?

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM_2.5 (mass concentration of particles with aerodynamic diameter < 2.5 μm) and factors that influence their concentrations. Hourly average PNC and PM_2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 10³ to 19.5 × 10³ particles·cm^-3 and from 7.0 to 65.8 μg·m^-3 for PNC and PM_2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM_2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM_2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM_2.5 demonstrated that a high PNC level does not lead to a high PM_2.5, and vice versa. The particle number-to-mass ratio (in units of 10⁹ particles·μg^-1) ranged from 0.14 to 2.2, >1 for roadside sites and <1 for urban background sites with lower values for more polluted cities. The Pearson's r ranged from 0.09 to 0.64 for the log-transformed data, indicating generally poor linear correlation between PNC and PM_2.5. Therefore, PNC and PM_2.5 measurements are not representative of each other; and regulating PM_2.5 does little to reduce PNC. This highlights the need to establish regulatory approaches and control measures to address the impacts of elevated UFP concentrations, especially in urban areas, considering their potential health risks.

Sources and Temporal Variations of Coarse Particulate Matter (PM) in Central Tehran, Iran

In this study, we used the positive matrix factorization (PMF) model to evaluate the sources of ambient coarse particulate matter (PM) and their temporal variations in two sampling sites, i.e., a school dormitory and a retirement home, located in central Tehran. 24-h ambient PM samples were collected using low-volume air samplers from May 2012 to June 2013. The collected filters were analyzed for their chemical components, including water-soluble ions, metals, and trace elements, which were used as the input to the PMF model. Our results indicated annual averages of 45.7 ± 3.8 µg/m3 and 36.2. ± 4.0 µg/m3 for coarse PM at the School dormitory and Tohid retirement home, respectively. Moreover, higher ambient coarse PM mass concentrations were observed in the warm season (53.3 ± 5.8 µg/m3 for school dormitory and 43.1 ± 6.1 µg/m3 for Tohid retirement home) as opposed to the cold season (41.4 ± 4.7 µg/m3 for school dormitory and 28.7 ± 4.6 µg/m3 for Tohid retirement home). Our PMF analysis also identified road dust, soil, and industry, and atmospherically processed coarse PM as the three sources of ambient coarse PM in central Tehran. Road dust, soil, and industry were the major sources of ambient coarse PM, contributing respectively to 74 ± 9% and 19 ± 2% of the total coarse PM mass concentration, while atmospherically aged aerosols had a rather minimal contribution of 7 ± 1% to total coarse PM mass concentration. The temporal trends of the resolved factors also revealed higher contributions of road dust to total ambient coarse PM during warm season as opposed to cold season, due to the increased resuspension rate from road surfaces as a result of higher wind speeds, and temperatures, combined with lower relative humidity. Similarly, higher resuspension rate of mechanically originated particulates resulted in higher warm-season time contributions of the soil factor. Results of this study clearly revealed the key role of road dust and non-tail pipe emissions on ambient coarse PM mass concentrations in crowded areas of central Tehran, and have important implications on the potential health impacts that can be caused by these difficult to mitigate sources of coarse PM.