Source apportionment of ambient PM2.5 in two locations in central Tehran using the Positive Matrix Factorization (PMF) model

Analysis of aerosol chemical components and source apportionment during a long-lasting haze event in the Yangtze River Delta, China

Based on the chemical composition data of a regional long-lasting haze event that occurred in the Yangtze River Delta (YRD) region from 17 December 2023 to 8 January 2024, the evolutionary characteristics of the chemical components and sources of fine particulate matter (PM2.5) under different pollution levels were comparatively analyzed using PMF (Positive Matrix Factorization) and backward trajectory analysis. SNA (NO3-, NH4+, SO42-) was found to be the primary chemical component of PM2.5, making up 63.6 % (clean days) to 69.7 % (heavy pollution) of it. The NO3- concentration was 3.14 (clean days) to 6.01 (heavy pollution) times higher than that of SO42-. NO3-, POC, Fe, Mn, Al concentrations increased, while SOC, EC, crustal elements (Ca, Si) and other water-soluble ions (WSIs) concentrations decreased as the pollution level increased. The contribution of secondary inorganics and biomass-burning emissions and industrial and ship emissions increased significantly as the pollution level increased, which accounted for 40.3 % and 36.7 %, respectively, in the heavy pollution stage. The contribution of traffic sources decreases gradually with increasing pollution levels, accounting for only 59.1 % of the light pollution stage in the heavy pollution stage. PM2.5 and its main chemical components showed similar potential source distribution, located in the northwest (Fuyang, Huainan, Nanjing), south (Taizhou, Lishui, Jiande) and north (Taizhou, Yancheng). However, distinct transport routes were observed under the different air quality levels. During the heavy pollution period, the polluted air masses primarily came from the harbor regions, whereas during the light pollution period they were transported from the southeast (Taizhou) and the North China Plain.

Source apportionment of PM2.5 using dispersion normalized positive matrix factorization (DN-PMF) in Beijing and Baoding, China

Fine particulate matter (PM2.5) samples were collected in two neighboring cities, Beijing and Baoding, China. High-concentration events of PM2.5 in which the average mass concentration exceeded 75 µg/m3 were frequently observed during the heating season. Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM2.5 as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities. Secondary nitrate had the highest contribution for Beijing (37.3 %), and residential heating/biomass burning was the largest for Baoding (27.1 %). Secondary nitrate, mobile, biomass burning, district heating, oil combustion, aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period (2019.01.10-2019.08.22) (Mann-Whitney Rank Sum Test P < 0.05). In case of Baoding, soil, residential heating/biomass burning, incinerator, coal combustion, oil combustion sources showed significant differences. The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients. Conditional Bivariate Probability Function (CBPF) was used to identify the inflow directions for the sources, and joint-PSCF (Potential Source Contribution Function) was performed to determine the common potential source areas for sources affecting both cities. These models facilitated a more precise verification of city-specific influences on PM2.5 sources. The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.

Size-segregated analysis of PAHs in Urban air: Source apportionment and health risk assessment in an Urban canal-adjacent environment

This study examines the distribution, origins, and health hazards of polycyclic aromatic hydrocarbons (PAHs) across six particle size fractions obtained from an urban rooftop location in Bangkok, Thailand. We collected PM samples using a six-stage cascade impactor at a canal boat port, trapping PAHs in particle sizes ranging from ultrafine (PM0.65-1.1) to coarse (PM7.0 and beyond) over an 11-week period. We utilized gas chromatography-mass spectrometry to quantify twelve PAH congeners. Results indicated that PAHs primarily concentrate in fine particles (PM2.1-3.3), with traffic emissions from gasoline and gasoline cars being the principal sources, augmented by emissions from diesel canal boats and industrial activities. The health risk assessment showed that the lifetime lung cancer risk (LLCR) values for all particle sizes were less than 1×10-6. This means that PAH exposure in this area has a very low cancer risk. Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) found traffic and industrial emissions as the primary sources of PAHs, with canal boats accounting for 5% of the total. These findings highlight the necessity of specific emission control regulations and advocate for the implementation of cleaner fuel alternatives and electric propulsion in canal transit to enhance urban air quality in Bangkok.

Size distribution, chemical composition and influencing factors of vehicle tire wear particles based on a novel test cycle

Tire wear particles (TWPs) are considered the one of most significant non-exhaust particle emission sources from vehicles. However, there is a lack of research on the emission characteristics of TWPs based on typical driving information. In this work, we used a high-dynamic outside wheel test platform to conduct tire wear tests on multiple types of tires based on a novel test cycle and comprehensively analyzed the differences in their emission characteristics while considering various factors, such as front/rear tire and tire type. We conducted a chemical composition analysis of TWPs. There are certain differences in the mass size distributions of TWPs from different types of tires. The emissions of PM2.5 and PM10 from the front TWPs are greater than those from the rear tire. This study provides basic data for urban atmospheric particle inventory research and a scientific basis for the development of emission standards and control strategies for TWPs.

Sources identification and health risk assessment of heavy metals in total suspended particulates (TSP) in a geochemical anomaly area influenced by historical indigenous zinc smelting activities

The superposition of heavy metals (HMs) from multiple anthropogenic sources in geochemical anomaly areas makes it difficult to discriminate prime sources in atmospheric HMs. This study utilized a combination of microscopic features, positive matrix factorisation, and Pb isotope fingerprints to trace the main sources of HMs bound to total suspended particulates (TSP) at a pollution site (Msoshui: MS) and control site (Lushan: LS) in northwestern Guizhou. The results reveal that the concentrations of Cd, Pb, Cr, As, Cu, Ni, and Zn in the TSP of LS are 3.97, 94.25, 2.93, 26.51, 3.15, 3.23, and 122.08 ng m-3, respectively, in the 5 years from 2018 to 2022, compared to 20.15, 960.28, 4.20, 41.50, 7.72, 2.95, and 1614.50 ng m-3 in that of MS. In comparison with other cities and remote areas, the concentrations of TSP-bound Cd, Pb, As, and Zn at MS and LS are high. The microscopic morphology shows that atmospheric particles of LS are primarily derived from mineral dust, whereas those of MS are mainly affected by multiple anthropogenic sources. The results of the positive matrix factorisation model (PMF) suggest that the predominant sources of TSP-bound HMs at MS are industrial sources, mixed sources (coal combustion and traffic sources), and mineral dust, reflecting the noticeable superposition of industrial sources compared to those at LS. The Pb isotope analysis demonstrates that TSP-bound Pb principally derive from surface soil (61.33%) and vehicle exhaust & dust from burning coal (38.67%) at LS, while it is mainly influenced by surface soil (29.21%), smelter dust (27.50%), and vehicle exhaust & dust from burning coal (43.29%) at MS. Moreover, it also indicates that the lingering effects of historical indigenous zinc smelting activities continue to impact the atmospheric and surface soil conditions in northwestern Guizhou Province. Risk assessment indicates that although the non-carcinogenic risk for each element is within acceptable limits, the total non-carcinogenic risk of HMs exceeds the minimal risk level, and Cd and As are the primary contributors.

Source apportionment of ultrafine particles in urban Europe

There is a body of evidence that ultrafine particles (UFP, those with diameters ≤ 100 nm) might have significant impacts on health. Accordingly, identifying sources of UFP is essential to develop abatement policies. This study focuses on urban Europe, and aims at identifying sources and quantifying their contributions to particle number size distribution (PNSD) using receptor modelling (Positive Matrix Factorization, PMF), and evaluating long-term trends of these source contributions using the non-parametric Theil-Sen's method. Datasets evaluated include 14 urban background (UB), 5 traffic (TR), 4 suburban background (SUB), and 1 regional background (RB) sites, covering 18 European and 1 USA cities, over the period, when available, from 2009 to 2019. Ten factors were identified (4 road traffic factors, photonucleation, urban background, domestic heating, 2 regional factors and long-distance transport), with road traffic being the primary contributor at all UB and TR sites (56-95 %), and photonucleation being also significant in many cities. The trends analyses showed a notable decrease in traffic-related UFP ambient concentrations, with statistically significant decreasing trends for the total traffic-related factors of -5.40 and -2.15 % yr-1 for the TR and UB sites, respectively. This abatement is most probably due to the implementation of European emissions standards, particularly after the introduction of diesel particle filters (DPFs) in 2011. However, DPFs do not retain nucleated particles generated during the dilution of diesel exhaust semi-volatile organic compounds (SVOCs). Trends in photonucleation were more diverse, influenced by a reduction in the condensation sink potential facilitating new particle formation (NPF) or by a decrease in the emissions of UFP precursors. The decrease of primary PM emissions and precursors of UFP also contributed to the reduction of urban and regional background sources.

Characterization of PM2.5 emissions from on-road vehicles in the tunnel of a major Middle Eastern city

Traffic emissions are an important source of air pollution worldwide, but in the Middle East, this problem is exacerbated by weak or no enforcement of emission regulations. Comprehensive measurements of fine PM emission factors (EFs) from road transport in the region have not yet been conducted, but such data are necessary for quantitative assessments of the health impact of transport emissions in the region. To address this need, PM2.5 samples collected inside the Salim Slam tunnel in Beirut, Lebanon were analyzed for carbonaceous matter (organic carbon (OC) and elemental carbon (EC)), water-soluble ions, elements, and selected organic compounds. The OC/EC ratio was 1.8 for the total fleet and 2.6 for light-duty vehicles (LDV), in agreement with the dominant proportion of gasoline LDV in the Lebanese fleet. A Cu/Sb ratio of 4.2 ± 0.1 was observed, offering a valuable metric for detecting brake wear emissions in subsequent studies conducted in the region. The EFs of carbonaceous matter, elements and ions generally varied by a factor 0.1 and 10 in comparison to literature values, while those for alkanes and polycyclic aromatic hydrocarbons were similar to the upper values previously reported. The average number size distribution was characterized by a single mode around 35 nm. The particles number EF (for diameters between 10 and 480 nm) was within the range of 1014-1015 particles per kg of fuel. The chemical mass balance model showed an average contribution to EF of 62% from non-exhaust sources. This study highlights the need for more enforceable stringent vehicular regulations because of the local practices (i.e., removal of catalyst) and some EF values are very high compared to other studies/countries.

Spatio-temporal distribution and source contributions of the ambient pollutants in Lucknow city, India

Clean air is imperative to the survival of all life forms on the planet. However, recent times have witnessed enormous escalation in urban pollution levels. It is therefore, incumbent upon us to decipher measures to deal with it. In perspective, the present study was carried out to assess PM10 and PM2.5 loading, metallic constituents, gaseous pollutants, source contributions, health impact and noise level of nine-locations, grouped as residential, commercial, and industrial in Lucknow city for 2019-21. Mean concentrations during pre-monsoon for PM10, PM2.5, SO2 and NO2 were: 138.2 ± 35.2, 69.1 ± 13.6, 8.5 ± 3.3 and 32.3 ± 7.4 µg/m3, respectively, whereas post-monsoon concentrations were 143.0 ± 33.3, 74.6 ± 14.5, 12.5 ± 2.1, and 35.5 ± 6.3 µg/m3, respectively. Exceedance percentage of pre-monsoon PM10 over National Ambient Air Quality Standards (NAAQS) was 38.2% while that for post-monsoon was 43.0%; whereas corresponding values for PM2.5 were 15.2% and 24.3%. Post-monsoon season showed higher particulate loading owing to wintertime inversion and high humidity conditions. Order of elements associated with PM2.5 is Co < Cd < Cr < Ni < V < Be < Mo < Mn < Ti < Cu < Pb < Se < Sr < Li < B < As < Ba < Mg < Al < Zn < Ca < Fe < K < Na and that with PM10 is Co < Cd < Ni < Cr < V < Ti < Be < Mo < Cu < Pb < Se < Sr < Li < B < As < Mn < Ba < Mg < Al < Fe < Zn < K < Na < Ca. WHO AIRQ + ascertained 1654, 144 and 1100 attributable cases per 0.1 million of population to PM10 exposure in 2019-21. Source apportionment was carried out using USEPA-PMF and resolved 6 sources with highest percent contributions including road dust re-entrainment, biomass burning and vehicular emission. It is observed that residents of Lucknow city regularly face exposure to particulate pollutants and associated constituents making it imperative to develop pollution abetment strategies.

Diel variations of airborne microbes and antibiotic resistance genes in Response to urban PM2.5 chemical properties during the heating season

Among the components of fine particulate matter (PM2.5), the contributions of airborne microorganisms and antibiotic resistance genes (ARGs) to health risks have been overlooked. Airborne microbial dynamics exhibit a unique diurnal cycle due to environmental influences. However, the specific roles of PM2.5 chemical properties resulting from fossil fuel combustion in driving circadian fluctuations in microbial populations and ARGs remain unclear. This study explored the interactions between toxic components and microbial communities during the heating period to understand the variations in ARGs. Bacterial and fungal communities showed a higher susceptibility to diel variations in PM2.5 compared to their chemical properties. Mantel tests revealed that chemical properties and microbial community interactions contribute differently to ARG variations, both directly and indirectly, during circadian fluctuations. Our findings highlight that, during the daytime, the enrichment of pathogenic microorganisms and ARGs increases the risk of PM2.5 toxicity. Conversely, during the nighttime, the utilization of water-soluble ions by the fungal community increased, leading to a significant increase in fungal biomass. Notably, Aspergillus exhibited a significant correlation with mobile genetic elements and ARGs, implying that this genus is a crucial driver of airborne ARGs. This study provides novel insights into the interplay between the chemical composition, microbial communities, and ARGs in PM, underscoring the urgent need for a comprehensive understanding of effective air pollution control strategies.

Temporal characteristics and health effects related to NO2, O3, and SO2 in an urban area of Iran

This study reports on temporal variations of NO2, O3, and SO2 pollutants and their related health effects in urban air of Khorramabad, Iran using AirQ 2.2.3 software. Based on data between 2015 and 2021, hourly NO2, O3, and SO2 concentrations increase starting at 6:00 a.m. local time until 9:00 p.m., 3:00 p.m., and 7:00 p.m. local time, respectively, before gradually decreasing. The highest monthly NO2, O3, and SO2 concentrations are observed in October, August, and September, respectively. Annual median NO2, O3, and SO2 concentrations range between 17 ppb and 38.8 ppb, 17.5 ppb-36.6 ppb, and ∼14 ppb-30.8 ppb, respectively. Two to 93 days and 17-156 days between 2015 and 2021 exhibit daily concentrations of NO2 and SO2 ≤ WHO AQGs, respectively, while 187-294 days have 8-h maximum O3 concentrations ≤ WHO AQGs. The mean excess mortality ascribed to respiratory mortality, cardiovascular mortality, hospital admissions for COPD, and acute myocardial infraction are 121, 603, 39, and 145 during 2015-2021, respectively. O3 is found to exert more significant health effects compared to SO2 and NO2, resulting in higher cardiovascular mortality. The gradual increase in NO2 and possibly O3 over the study period is suspected to be due to economic sanctions, while SO2 decreased due to regulatory activity. Sustainable control strategies such as improving fuel quality, promoting public transportation and vehicle retirement, applying subsidies for purchase of electric vehicles, and application of European emission standards on automobiles can help decrease target pollutant levels in ambient air of cities in developing countries.

The relative contributions of traffic and non-traffic sources in ultrafine particle formations in Tehran mega city

Emissions of ultrafine particles (UFPs; diameter < 100 nm) are strongly associated with traffic-related emissions and are a growing global concern in urban environments. The aim of this study was to investigate the variations of particle number concentration (PNC) with a diameter > 10 nm at nine stations and understand the major sources of UFPs (primary vs. secondary) in Tehran megacity. The study was carried out in Tehran in 2020. NOx and PNC were reported from a total of nine urban site locations in Tehran and BC concentrations were examined at two monitoring stations. Data from all stations showed diurnal changes with peak morning and evening rush hours. The hourly PNC was correlated with NOx. PNCs in Tehran were higher compared to those of many cities reported in the literature. The highest concentrations were at District 19 station (traffic) and the lowest was at Punak station (residential) such that the average PNC varied from 8.4 × 103 to 5.7 × 104 cm-3. In Ray and Sharif stations, the average contributions of primary and secondary sources of PNC were 67 and 33%, respectively. Overall, we conclude that a decrease in primary emission leads to a decrease in the total concentration of aerosols, despite an increase in the formation of new particles by photo nucleation.

Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model

Effective evaluation of water quality and accurate quantification of pollution sources are essential for the sustainable use of water resources. Although water quality index (WQI) and positive matrix factorization (PMF) models have been proven to be applicable for surface water quality assessments and pollution source apportionments, these models still have potential for further development in today's data-driven, rapidly evolving technological era. This study coupled a machine learning technique, the random forest model, with WQI and PMF models to enhance their ability to analyze water pollution issues. Monitoring data of 12 water quality indicators from six sites along the Minjiang River from 2015 to 2020 were used to build a WQI model for determining the spatiotemporal water quality characteristics. Then, coupled with the random forest model, the importance of 12 indicators relative to the WQI was assessed. The total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (CODCr), dissolved oxygen (DO), and five-day biochemical oxygen demand (BOD5) were identified as the top five significant parameters influencing water quality in the region. The improved WQI model constructed based on key parameters enabled high-precision (R2 = 0.9696) water quality prediction. Furthermore, the feature importance of the indicators was used as weights to adjust the results of the PMF model, allowing for a more reasonable pollutant source apportionment and revealing potential driving factors of variations in water quality. The final contributions of pollution sources in descending order were agricultural activities (30.26%), domestic sewage (29.07%), industrial wastewater (26.25%), seasonal factors (6.45%), soil erosion (6.19%), and unidentified sources (1.78%). This study provides a new perspective for a comprehensive understanding of the water pollution characteristics of rivers, and offers valuable references for the development of targeted strategies for water quality improvement.

The Impact of Russia-Ukraine geopolitical conflict on the air quality and toxicological properties of ambient PM2.5 in Milan, Italy

The geopolitical conflict between Russia and Ukraine has disrupted Europe's natural gas supplies, driving up gas prices and leading to a shift towards biomass for residential heating during colder months. This study assessed the consequent air quality and toxicological impacts in Milan, Italy, focusing on fine particulate matter (PM2.5, dp < 2.5 μm) emissions. PM2.5 samples were analyzed for their chemical composition and assessed for their oxidative potential using the dithiothreitol (DTT) assay across three periods reflecting residential heating deployment (RHD): pre-RHD, intra-RHD, and post-RHD periods. During the intra-RHD period, PM2.5 levels were significantly higher than those in other periods, with concentrations reaching 57.94 ± 7.57 μg/m3, indicating a deterioration in air quality. Moreover, levoglucosan was 9.2 times higher during the intra-RHD period compared to the pre-RHD period, correlating with elevated levels of elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs). These findings were compared with previous local studies before the conflict, underscoring a significant rise in biomass-related emissions. DTT assay levels during the intra-RHD were 2.1 times higher than those observed during the same period in 2022, strongly correlating with biomass burning emissions. Our findings highlight the necessity for policies to mitigate the indirect health effects of increased biomass burning emissions due to the energy crisis triggered by the geopolitical conflict.

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.

Impact of agricultural activity on PM2.5 and its compositions in elementary schools near corn and rice farms

Agricultural activity is an important source of particulate matter <2.5 μm in size (PM2.5) in rural areas. In Taiwan, many elementary schools are surrounded by farms, and studies investigating the impact of agricultural activity on air quality in schools are required. We collected PM2.5 samples from the classrooms of elementary schools near corn and rice farms during the crop cultivation stages and analyzed their concentrations and compositions to investigate whether agricultural activity affects the schools' air quality. We found that the average ratio of PM2.5/PM10 (<10 μm in particle size) was <0.6 in the school near the corn farm, and that the indoor PM2.5/PM10 ratio was significantly associated (r = 0.93, p < 0.05) with the outdoor ratio. Moreover, the potassium (K) concentration in the school near the corn farm (189.2 ± 119 ng/m3) was higher than that near the rice farm (140.9 ± 116.0 ng/m3). There were higher concentrations of K and crustal elements, and a greater crustal elements/heavy metals ratio, in the school near the corn farm during the sowing and soil covering stages than during other cultivation stages. Positive matrix factorization (PMF) results indicate that agricultural activity was a predominant contributor of PM2.5 in the schools near corn and rice farms, however, PM2.5 from industrial and traffic emissions also affected schools' air quality. In summary, agricultural activity influenced the air quality of schools, especially near the corn farm. Governments should develop air quality management policies to reduce the risk of children suffering exposure to high particle concentrations in these schools and further suggest that the impact of industrial and traffic emissions on air quality also requires attention.

Identifying the natural and agricultural impacts on the glaciochemistry of the Aru ice core on the northwestern Tibetan Plateau

Glaciochemical data sourced from ice cores in polar regions and the Alps have been extensively examined. However, quantitative studies on glaciochemical records of the Tibetan Plateau (TP) are scarce. To address this, we investigated annual variations in the major soluble ions (Ca2+, Mg2+, Na+, K+, NH4+, Cl-, NO3-, and SO42-) in the Aru ice core on the northwestern TP from 1850 to 2016. Applying a positive matrix factorization model, the sources of the major soluble ions and three factors to evaluate natural and agricultural impacts were identified. Factor 1, crustal dust with high loadings of Mg2+ (81.9 %) and Ca2+ (68.7 %), significantly positively correlated with wind speed and significantly negatively correlated with δ18O and net accumulation recorded by the ice core, suggesting that strong winds contributed to crustal dust transport from arid and semi-arid regions of Central Asia and deposition in the Aru glacier. However, relatively warm and wet climate prevented the transport of crustal dust. Factor 2 comprised salt lakes with high dominant loadings of Na+ (75.3 %), SO42- (64.1 %), Cl- (60.8 %), NO3- (52.2 %), and K+ (49.4 %). Declining lake water levels exposed salt lake minerals, which were carried to glaciers under the dynamic conditions of strong winds, whereas warming resulted in an expansion of glacial meltwater and lake water volume, which decreased the contribution of salt lake sediments. Therefore, the contribution of salt lake deposition decreased. Factor 3 was agricultural sources with a high loading of NH4+ (82 %), whose trend aligned closely with the population number and N productions from agricultural sources in South and Central Asia, suggesting that NH3 emissions from agricultural practices are a critical contributor to Factor 3. This study quantified the proportional contribution of natural and agricultural sources to glaciochemical composition, advancing our understanding of glaciochemical records in ice cores from source recognition to quantification.

BTEX in indoor air of barbershops and beauty salons: Characterization, source apportionment and health risk assessment

BACKGROUND

Volatile organic compounds, mainly BTEX, are among the pollutants of concern in beauty salons and barbershops that threaten both staff personnel and clients' health. This study aimed to determine the concentration of BTEX in barbershops and beauty salons and assess the carcinogenic and non-carcinogenic risks based on the actual risk coefficients. Also, possible sources of BTEX were determined.

METHOD

Samples were collected by passive sampling. Quantitative and qualitative measurements of BTEX compounds were performed using gas chromatography-mass spectrometry (GC-MASS). Subsequently, the health risks were assessed according to the US Environmental Protection Agency. SPSS24 software and positive matrix factorization (PMF) analysis were used for statistical analysis and source apportionment respectively.

RESULTS

Toluene is the most abundant compound in beauty salons, with a maximum concentration of 219.4 (μg/m3) in beauty salons. Results indicated that the mean ELCR value estimated for benzene regarding female staff exposure (1.04 × 10-5) was higher than that for men (4.05 × 10-6). Also, ELCR values of ethylbenzene for staff exposure were 2.08 × 10-6 and 3.8 × 10-6 for men and women, respectively, and possess possible carcinogenesis risks.

CONCLUSION

Use of solvents and cosmetic products, improper heating systems, and type of service are the sources that probably contribute to BTEX emissions in beauty salons. It is necessary to follow health guidelines and conduct continuous monitoring for their implementation, in addition to setting a mandated occupational regulation framework or air quality requirements, to improve the health conditions in beauty salons.

Characterizing the long-term occurrence and anthropogenic drivers of per- and polyfluoroalkyl substances in surface water of the Rhine River

Per- and polyfluoroalkyl substances (PFAS) raise significant concerns due to their persistence, bioaccumulation potential, and toxicity to both ecosystems and human health. However, the long-term trends of PFAS in aquatic environments remain inadequately explored. In this study, we systematically assessed the spatiotemporal distribution, periodic fluctuations, source apportionment, and risk evaluation of 12 PFAS in the Rhine River based on the long-term measuring data collected from 2007 to 2019. The study revealed that the mean concentration and mass flux of total PFAS during this period were 32.83 ng L-1 and 6.36 × 104 μg s-1, declining at an annual rate of 3.70% and 3.82%, respectively. Wavelet analysis demonstrated that the most prominent periodic oscillation of PFAS was 40-60 months. Regarding the sources of PFAS, we employed the self-organizing map (SOM) and the positive matrix factorization (PMF) model for source apportionment. The results indicated that the primary sources of PFAS were agrochemical, pharmaceutical and textile industries, accounting for 38.1% of the total concentration. The contribution from household contamination, tannery industry, and coating materials has increased annually. In contrast, the share of electrochemical fluorination and chemical recycling has shown a continuous decline. The risk quotient (RQ) and hazard quotient (HQ) calculations for three age groups indicated that PFAS exposure did not pose a significant risk to ecological or human health. Implementing source-oriented mitigation strategies is crucial to effectively reduce the ecological and human health risks of PFAS in receiving waters.

Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles

In this study, the water-solubility and sources of metals and trace elements in both fine and coarse particulate matter (PM) were investigated in Central Los Angeles. Sampling was performed in the winter, spring, and summer of 2022 at the Particle Instrumentation Unit (PIU) of the University of Southern California located in the proximity of I-110 freeway. Both fine and coarse PM samples were collected using Personal Cascade Impactors (PCIS) and chemically analyzed to determine their water-soluble and water-insoluble metal content. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were used to determine the sources of soluble and insoluble metals and obtain their contributions to total metal concentration. Our results indicate that the water-solubility of most of the metals is higher in the fine size fraction compared to the coarse fraction. Seasonal variations in the water solubility of selected metals for both coarse and fine fractions were observed, with higher water-soluble metal concentrations in summer for several species (e.g., Fe , S, Pb, Cu, La, Ni, and Al ), possibly due to higher photochemical processing, while in winter, almost all species exhibited higher insoluble fraction concentrations. The PCA and MLR analyses results showed that tire and brake wear was the most significant contributor to the total metals for both fine soluble and insoluble portions, accounting for 35% and 75% of the total metals, respectively. Combustion sources also contributed substantially to water-soluble metals for fine and coarse size ranges, representing 40% and 32% of the total metal mass, respectively. In addition, mineral dust and soil and re-suspended dust were identified as the highest contributors to coarse metals. The MLR analysis also revealed that secondary aerosols contributed 11% to the fine water-soluble metals. Our results suggest that non-tailpipe emissions significantly contribute to both coarse and fine PM metals in the Central Los Angeles region.

Heavy vehicles' non-exhaust exhibits competitive contribution to PM2.5 compared with exhaust in port and nearby areas

Heavy port transportation networks are increasingly considered as significant contributors of PM2.5 pollution compared to vessels in recent decades. In addition, evidence points to the non-exhaust emission of port traffic as the real driver. This study linked PM2.5 concentrations to varied locations and traffic fleet characteristics in port area through filter sampling. The coupled emission ratio-positive matrix factorisation (ER-PMF) method resolves source factors by avoiding direct overlap from collinear sources. In the port central and entrance areas, freight delivery activity emissions including vehicle exhaust and non-exhaust particles, as well as induced road dust resuspension, accounted for nearly half of the total contribution (42.5%-49.9%). In particular, the contribution of non-exhaust from denser traffic with high proportion of trucks was competitive and equivalent to 52.3% of that from exhaust. Backward trajectory statistical models further interpreted the notably larger-scale coverage of non-exhaust emissions in the port's central area. The distribution of PM2.5 were interpolated within the scope of the port and nearby urban areas, displaying the potential contribution of non-exhaust within 1.15 μg/m3-4.68 μg/m3, slightly higher than the urban detections reported nearby. This study may provide useful insights into the increasing percentage of non-exhaust from trucks in ports and nearby urban areas and facilitate supplementary data collection on Euro-VII type-approval limit settings.

Water quality assessment and pollution source apportionment using multivariate statistical and PMF receptor modeling techniques in a sub-watershed of the upper Yangtze River, Southwest China

Rapid industrial and agricultural development as well as urbanization affect the water environment significantly, especially in sub-watersheds where the contaminants/constituents present in the pollution sources are complex, and the flow is unstable. Water quality assessment and quantitative identification of pollution sources are the primary prerequisites for improving water management and quality. In this work, 168 water samples were collected from seven stations throughout 2018-2019 along the Laixi River, a vital pollution control unit in the upper reaches of the Yangtze River. Multivariate statistics and positive matrix factorization (PMF) receptor modeling techniques were used to evaluate the characteristics of the river-water quality and reveal the pollution sources. Principal component analysis was employed to screen the crucial parameters and establish an optimized water quality assessment procedure to reduce the analysis cost and improve the assessment efficiency. Cluster analysis further illustrates the spatiotemporal distribution characteristics of river-water quality. Results indicated that high-pollution areas are concentrated in the tributaries, and the high-pollution periods are the spring and winter, which verifies the reliability of the evaluation system. The PMF model identified five and six potential pollution sources in the cold and warm seasons, respectively. Among them, pollution from agricultural activities and domestic wastewater shows the highest contributions (33.2% and 30.3%, respectively) during the cold and warm seasons, respectively. The study can provide theoretical support for pollutant control and water quality improvement in the sub-watershed, avoiding the ecological and health risks caused by the deterioration of water quality.

Traces of black carbon sources before and after the Covid-19 outbreak in Tehran, Iran

The concentration of black carbon was measured in four sites of the industrial and high-traffic metropolis of Tehran with different land uses. Then, the contribution of biomass and fossil fuels in the emission of this pollutant was modeled using the Aethalometer model. The possible locations of important sources of black carbon dissemination were projected using PSCF and CWT models, and the results were compared in the two periods before and after the Covid-19 outbreak. Temporal variations of black carbon illustrated that BC concentration decreased in the period after the onset of the pandemic in all studied areas, and this decline was more explicit in the traffic intersection of the city. Diurnal changes of BC concentration indicated the significant impact of the application of the law banning night traffic of motor vehicles in reducing the BC concentration in this period, and probably the reduction of HDDV traffic has played the most important role in this reduction. The results related to the share of BC sources indicated that black carbon emissions are affected by an average of about 80% of fossil fuel combustion and wood combustion interferes with about 20% of BC emissions. Finally, speculations were made about the possible sources of BC emission and its urban scale transport using PSCF and CWT models, which indicated the superiority of the CWT model in terms of source segregation. The results of this analysis were further utilized to surmise black carbon emission sources based on the land use of receptor points.

The spatial analysis, risk assessment and source identification for mercury in a typical area with multiple pollution sources in southern China

Mercury (Hg) has always been a research hot spot because of its high toxicity. This study conducted in farmland near rare earth mining area and traffic facilities, which considered multiple pollution sources innovatively. It not only analyzed Hg spatial characteristics using inverse distance weighting and self-organizing map (SOM), but also assessed its pollution risk by potential ecological risk index (Er) as well as geoaccumulation index (Igeo), and identified the pollution sources with positive matrix factorization. The results showed that there was no heavy Hg pollution in most farmland, while a few sampling sites with Hg pollution were close to highway, railway station and petrol station in Xinfeng or in the farmland of Anyuan, which were divided into the cluster with highest Hg concentration in SOM. The vehicle exhaust emission and pesticide as well as fertilizer additions significantly contributed to the local Hg pollution. Besides, there was moderate pollution and high ecological risk in Anyuan assessed by Igeo and Er, respectively. In contrast, Xinfeng had the moderate and considerable ecological risks in a larger scale. The enriched Hg might harmed not only the nearby ecological environment, but also the human health when it entered human body through food chain. The three factors that contributed to mercury concentration in this area according to positive matrix factorization were natural source, traffic source and agricultural source, respectively. This study about Hg pollution in the typical area would provide scientific evidence for the particular treatment of Hg pollution from various pollution sources like traffic source, agricultural source, etc.

Comparative review of ambient air PM2.5 source apportioning studies in Tehran

Rapid urbanization and consuming lifestyles have intensified air pollution in urban areas. Air pollution in megacities has imposed severe environmental damages to human health. Proper management of the issue necessitates identification of the share of emission sources. Therefore, numerous research works have studied the apportionment of the total emissions and observed concentrations among different emissions sources. In this research, a comprehensive review is conducted to compare the source apportioning results for ambient air PM2.5 in the megacity of Tehran, the capital of Iran. One hundred seventy-seven pieces of scientific literatures, published between 2005 and 2021, were reviewed. The reviewed research are categorized according to the source apportioning methods: emission inventory (EI), source apportionment (SA), and sensitivity analysis of the concentration to the emission sources (SNA). The possible reasons for inconsistency among the results are discussed according to the scope of the studies and the implemented methods. Although 85% of the reviewed original estimates identify that mobile sources contribute to more thant 60% of Tehran air pollution, the distribution of vehicle types and modes are clearly inconsistent among the EI studies. Our review suggests that consistent results in the SA studies in different locations in central Tehran may indicate the reliability of this method for the identification of the type and share of the emission sources. In contrast, differences among the geographical and sectoral coverage of the EI studies and the disparities among the emission factors and activity data have caused significant deviations among the reviewed EI studies. Also, it is shown that the results of the SNA studies are highly dependent on the categorization type, model capabilities and EI presumptions and data input to the pollutant dispersion modelings. As a result, integrated source apportioning in which the three methods complement each other's results is necessary for consistent air pollution management in megacities.

Supplementary information

The online version contains supplementary material available at 10.1007/s40201-023-00855-0.

New insights into pollution source analysis using receptor models in the upper Yangtze river basin: Effects of land use on source identification and apportionment

To effectively control pollution and improve water quality, it is essential to accurately analyze the potential pollution sources in rivers. The study proposes a hypothesis that land use can influence the identification and apportionment of pollution sources and tested it in two areas with different types of water pollution and land use. The redundancy analysis (RDA) results showed that the response mechanisms of water quality to land use differed among regions. In both regions, the results indicated that the water quality response relationship to land use provided important objective evidence for pollution source identification, and the RDA tool optimized the procedure of source analysis for receptor models. Positive matrix decomposition (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models identified five and four pollution sources along with their corresponding characteristic parameters. PMF attributed agricultural nonpoint sources (23.8%) and domestic wastewater (32.7%) as the major sources in regions 1 and 2, respectively, while APCS-MLR identified mixed sources in both regions. In terms of model performance parameters, PMF demonstrated better-fit coefficients (R²) than APCS-MLR and had a lower error rate and proportion of unidentified sources. The results show that considering the effect of land use in the source analysis can overcome the subjectivity of the receptor model and improve the accuracy of pollution source identification and apportionment. The results of the study can help managers clarify the priorities of pollution prevention and control, and provide a new methodology for water environment management in similar watersheds.

Source apportionment and potential ecological risk assessment of heavy metals in soils on a large scale in China

The properties and sources of soil heavy metals (Pb, Zn, Cu, Cd, As, Hg, Cr, and Ni) need to be comprehensively analyzed to take effective steps to control and reduce soil pollutants. In this research, 416 soil samples were collected on a large scale in China. Two receptor models (PCA/MLR and PMF) were utilized to identify pollutant sources and quantify the contributions. The means of soil heavy metals (Zn, Cu, As, Hg, Cr, and Ni) were lower than the corresponding screening values and intervention values. Cd was greater than the intervention value, while Pb was between the screening value and the intervention value. Source apportionments suggested that mine sources were the most polluted (64.28%), followed by traffic sources (38.98%), natural sources (11.41-39.58%), industrial sources (9.8-18.65%), and agricultural sources (2.79-14.51%). Compared to the PCA/MLR model, the PMF model had a better effect in evaluating soil heavy metal pollution. It gave corresponding weights according to the data concentration and its uncertainty, which made the result reasonable. The ecological risk assessment indicated that Cd posed a significant risk, while Hg caused a mild risk and the other six heavy metals posed a low risk. The spatial distribution of ecological risk suggested that severe risk points were mainly distributed in the central area, while high-risk points were distributed in the southern region. The SRI method was developed to link pollution sources and their potential ecological risks and indicated better applicability to the PMF model. The study findings could provide guidelines for monitoring the main sources and reducing the pollution of soil heavy metals.

Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM_2.5) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OP^OH), dithiothreitol loss (OP^DTT), black carbon, and 52 metals and elements for 54 total PM_2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OP^OH: vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OP^OH, followed by 21% from brake and tire wear. Similar results were observed for the OP^DTT source apportionment. Furthermore, by linking measured PM_2.5 and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OP^OH exhibited the largest inverse social gradients, followed by OP^DTT and PM_2.5 mass. Finally, OP^OH was the metric most strongly correlated with adverse health outcome indicators.

Contamination, Source Identification, Ecological and Human Health Risks Assessment of Potentially Toxic-Elements in Soils of Typical Rare-Earth Mining Areas

The mining and leaching processes of rare-earth mines can include the entry of potentially toxic elements (PTEs) into the environment, causing ecological risks and endangering human health. However, the identification of ecological risks and sources of PTEs in rare-earth mining areas is less comprehensive. Hence, we determine the PTE (Co, Cr, Cu, Mn, Ni, Pb, Zn, V) content in soils around rare-earth mining areas in the south and analyze the ecological health risks, distribution characteristics, and sources of PTEs in the study area using various indices and models. The results showed that the average concentrations of Co, Mn, Ni, Pb and Zn were higher than the soil background values, with a maximum of 1.62 times. The spatial distribution of PTEs was not homogeneous and the hot spots were mostly located near roads and mining areas. The ecological risk index and the non-carcinogenic index showed that the contribution was mainly from Co, Pb, and Cr, which accounted for more than 90%. Correlation analysis and PMF models indicated that eight PTEs were positively correlated, and rare-earth mining operations (concentration of 22.85%) may have caused Pb and Cu enrichment in soils in the area, while other anthropogenic sources of pollution were industrial emissions and agricultural pollution. The results of the study can provide a scientific basis for environmental-pollution assessment and prevention in rare-earth mining cities.

Ecological risk assessment and sources identification of heavy metals in surface sediments of a river-reservoir system

Heavy metal contamination of river water and sediments is a global issue affecting ecological health. To reveal heavy metals' ecological risks and biological toxicity in the middle and lower Han River (MLHR), sediment samples collected in this area were analyzed based on a modified ecological risk assessment method (NIRI) and a biological toxicity assessment method. Also, Spearman correlation analysis and Positive Matrix Factorization (PMF) methods were applied to identify the potential sources of heavy metals. The results indicated that the heavy metal content significantly exceeded the background concentrations in Hubei Province. The average potential risk of heavy metals at sampling sites was: Cd > Hg > As > Pb > Cu > Zn. Consequently, high biological toxicity occurred along the MLHR due to the heavy metal enrichment. River damming and water diversion significantly enhanced the hydrologic regime variations and ecological risk in the MLHR. Moreover, two possible pollution sources of the MLHR were identified: one is a combined source of traffic pollution, agricultural pollution, and partial industrial pollution consisting of five heavy metals, Pb, Hg, Zn, Cu, and As, the other is an industrial pollution source dominated by Cd and As. This study provides insights into sediment heavy metal pollution management and ecological risk control in the MLHR and similar rivers worldwide.

Source apportionment, identification and characterization, and emission inventory of ambient particulate matter in 22 Eastern Mediterranean Region countries: A systematic review and recommendations for good practice

Little is known about the main sources of ambient particulate matter (PM) in the 22 Eastern Mediterranean Region (EMR) countries. We designed this study to systematically review all published and unpublished source apportionment (SA), identification and characterization studies as well as emission inventories in the EMR. Of 440 articles identified, 82 (11 emission inventory ones) met our inclusion criteria for final analyses. Of 22 EMR countries, Iran with 30 articles had the highest number of studies on source specific PM followed by Pakistan (n = 15 articles) and Saudi Arabia (n = 8 papers). By contrast, there were no studies in Afghanistan, Bahrain, Djibouti, Libya, Somalia, Sudan, Syria, Tunisia, United Arab Emirates and Yemen. Approximately 72% of studies (51) were published within a span of 2015-2021.48 studies identified the sources of PM_2.5 and its constituents. Positive matrix factorization (PMF), principal component analysis (PCA) and chemical mass balance (CMB) were the most common approaches to identify the source contributions of ambient PM. Both secondary aerosols and dust, with 12-51% and 8-80% (33% and 30% for all EMR countries, on average) had the greatest contributions in ambient PM_2.5. The remaining sources for ambient PM_2.5, including mixed sources (traffic, industry and residential (TIR)), traffic, industries, biomass burning, and sea salt were in the range of approximately 4-69%, 4-49%, 1-53%, 7-25% and 3-29%, respectively. For PM₁₀, the most dominant source was dust with 7-95% (49% for all EMR countries, on average). The limited number of SA studies in the EMR countries (one study per approximately 9.6 million people) in comparison to Europe and North America (1 study per 4.3 and 2.1 million people respectively) can be augmented by future studies that will provide a better understanding of emission sources in the urban environment.

Spatial distribution, source apportionment and health risk assessment of inorganic pollutants of surface water and groundwater in the southern margin of Junggar Basin, Xinjiang, China

Surface water (SW) and groundwater (GW) are crucial water supply sources in the southern margin of Junggar Basin in Xinjiang. The sources of toxic components in SW and GW and their negative effects on human health are of great concern. A total of 40 SW and 596 GW samples were collected at the oasis belt to analyze distribution, sources and potential health risks of inorganic pollutants in SW and GW. Results revealed that SW quality was severely affected by Hg, 30.0% of which had Hg concentration greater than the national drinking water standard. High Hg SW was mainly distributed near Manas County and Urumqi City. GW quality was mostly affected by SO₄^2-, 24.7% of which had SO₄^2- concentration greater than the national drinking water standard. High SO₄^2- GW primarily occurred in the northwest and middle of the study area. Source apportionment of inorganic pollutants identified geological background, municipal wastewater disposal, water-rock interaction, geological environment, geological structure and industrial emission were the prominent potential sources of inorganic pollution in SW, with contribution rates of 1.2%, 10.0%, 43.6%, 35.1%, 6.3% and 3.8%, respectively. Five potential pollution sources in GW (including geological background, municipal wastewater disposal, water-rock interaction, geological environment and aquifer burial depth) were identified, with contribution rates of 0.7%, 9.6%, 77.6%, 11.1% and 1.0%, respectively. Probabilistic health risk assessment showed that Cl^- and As in SW and GW were the main inorganic pollutants threatening human health. Non-carcinogenic risks for adults and children were negligible, while carcinogenic risks cannot be negligible. Furthermore, the contribution of potential pollution sources to health risks was quantified using positive matrix factorization coupling with health risk assessment model. Based on which, we offered the suggestion that water quality improvement in contaminated areas should be implemented in combination with pollution monitoring systems.

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.

Estimation of the fraction of soil-borne particulates in indoor air by PMF and its impact on health risk assessment of soil contamination in Guangzhou, China

The fraction of soil-borne particulates in indoor air (fspi), a principal exposure factor in health risk assessment of soil, is used to calculate the inhaled dose of contaminants in air particulates (PM₁₀) from soil. To investigate the fspi, consecutive 24-h PM₁₀ samples (n = 180) of indoor ambient were collected from September 2019 to January 2020 in Guangzhou main urban areas, China. The concentrations of twenty-six metal elements, five anions, organic carbon (OC) and elemental carbon (EC) in samples were measured. The sources of indoor ambient PM₁₀ and the value of fspi were identified by the method of Positive Matrix Factor analysis (PMF). Results showed that the main sources contributing to indoor PM₁₀ content were combustion sources (50.53%) and vehicular sources (28.17%). The soil sources (the local fspi) were 19.96%. The soil contents of indoor PM₁₀ in Guangzhou main urban areas were in accordance with those in similar monsoon climate regions, such as Malaysia. The health risks of the inhalation route were dropped by about 62% for some common brownfield contaminants (Cr (VI), Ni, Be and Cd) with the investigated local fspi in Guangzhou main urban areas, compared with using the fspi (0.8) recommended by the C-RAG model in China. The results supplied a new effective methodology for estimation of the local fspi value in health risk assessment of soil contamination in urban areas.

Source apportionment of PM2.5 in Seoul, South Korea and Beijing, China using dispersion normalized PMF

East Asian countries experience severe air pollution owing to their rapid development and urbanization induced by substantial economic activities. South Korea and China are among the most polluted East Asian countries with high mass concentrations of PM_2.5. Although the occurrence of transboundary air pollution among neighboring countries has been recognized for a long time, studies involving simultaneous ground-based PM_2.5 monitoring and source apportionment in South Korea and China have not been conducted to date. This study performed simultaneous daily ground-based monitoring of PM_2.5 in Seoul and Beijing from January to December 2019. The mass concentrations of PM_2.5 and its major chemical components were analyzed simultaneously during 2019. Positive matrix factorization (PMF) as well as dispersion normalized PMF (DN-PMF) were utilized for the source apportionment of ambient PM_2.5 at the two sites. 23 h average ventilation coefficients were applied for daily PM_2.5 chemical constituents' data. Nine sources were identified at both sites. While secondary nitrate, secondary sulfate, mobile, oil combustion, biomass burning, soil, and aged sea salt were commonly found at both sites, industry/coal combustion and incinerator were identified only at Seoul and incinerator/industry and coal combustion were identified only at Beijing. Reduction of the meteorological influences were found in DN-PMF compare to C-PMF but the effects of DN on mobile source were reduced by averaging over the 23 h sampling period. The DN-PMF results showed that Secondary nitrate (Seoul: 25.5%; Beijing: 31.7%) and secondary sulfate (Seoul: 20.5%; Beijing: 17.6%) were most dominant contributors to PM_2.5 at both sites. Decreasing secondary sulfate contributions and increasing secondary nitrate contributions were observed at both sites.

Source Apportionment of Fine Particulate Matter during the Day and Night in Lanzhou, NW China

Source apportionment of PM2.5 in Lanzhou, China, was carried out using positive matrix factorization (PMF). Seventeen elements (Ca, Fe, K, Ti, Ba, Mn, Sr, Cd, Se, Pb, Cu, Zn, As, Ni, Co, Cr, V), water-soluble ions (Na+, NH4+, K+, Mg2+, Ca2, Cl-, NO3-, SO42-), and organic carbon (OC) and elemental carbon (EC) were analyzed. The results indicated that the mean concentration of PM2.5 was 178.63 ± 96.99 μg/m3. In winter, the PM2.5 concentration was higher during the day than at night, and the opposite was the case in summer, and the nighttime PM2.5 concentration was 1.3 times higher than during the day. Water-soluble ions were the dominant component of PM2.5 during the study. PMF source analysis revealed six sources in winter, during the day and night: salt lakes, coal combustion, vehicle emissions, secondary aerosols, soil dust, and industrial emissions. In summer, eight sources during the day and night were identified: soil dust, coal combustion, industrial emissions, vehicle emissions, secondary sulfate, salt lakes, secondary aerosols, and biomass burning. Secondary aerosols, coal combustion, and vehicle emissions were the dominant sources of PM2.5. In winter, the proportions of secondary aerosols and soil dust sources were greater during the day than at night, and the opposite was the case in summer. The coal source, industrial emissions source, and motor vehicle emissions source were greater at night than during the day in winter. This work can serve as a case study for further in-depth research on PM2.5 pollution and source apportionment in Lanzhou, China.

Tailpipe and Nontailpipe Emission Factors and Source Contributions of PM10 on Major Freeways in the Los Angeles Basin

In this study, the emission factors of PM₁₀ and its chemical constituents from various contributing sources including nontailpipe and tailpipe emissions were estimated on two interstate freeways in the Los Angeles basin. PM₁₀ samples were collected on the I-110 and I-710 freeways as well as at the University of Southern California (USC) campus as the urban background site, while freeway and urban background CO₂ levels were measured simultaneously. PM₁₀ samples were analyzed for their content of chemical species which were used to estimate the emission factors of PM₁₀ and its constituents on both I-110 and I-710 freeways. The estimated values were employed to determine the emission factors for light (LDV) and heavy-duty vehicles (HDV). The quantified species were also processed by the positive matrix factorization (PMF) model to produce PM₁₀ freeway source profiles and their contribution to PM₁₀ mass concentrations. Using the PMF factor profiles and emission factors on the two freeways, we characterized the emission factors for light-duty and heavy-duty vehicles by each nontailpipe source. Our findings indicated higher nontailpipe emission factors of PM₁₀ and metal elements on the I-710 freeway compared to the I-110 freeway, due to the higher fraction of heavy-duty vehicles (HDVs) on that freeway. Furthermore, the generation of nontailpipe PM₁₀ from resuspension of road dust was twice of tire and brake wear. The results of this study provide significant insights into PM₁₀ freeway emissions and particularly the overall contribution of nontailpipe and tailpipe sources in Los Angeles, which can be helpful to modelers and air quality officials in assessing the importance of individual traffic-related emissions on the overall population exposure.

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.

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.

Insights into high concentrations of particle-bound imidazoles in the background atmosphere of southern China: Potential sources and influencing factors

Imidazoles are important constituents in atmospheric brown carbon and have gained increasing attention in the past decade. Although imidazoles have been studied widely in laboratories, the sparse field observations severely limit the understanding of imidazole's abundance and sources in the atmosphere. In this study, we measured particle-bound imidazoles and their precursors at a background forest site in the Nanling Mountains of southern China. The average concentration of imidazoles (4.17 ± 3.76 ng/m³) was found to be significantly higher than other background sites worldwide. Further analyses revealed that a majority of imidazoles (59.1%) at the site originated from secondary formation through reactions of dicarbonyls (e.g., glyoxal and methylglyoxal) and reduced nitrogen species, with relatively minor contributions from regional transport (32.8%) and biomass burning (8.1%). In addition, the key factors influencing secondary formation of imidazoles, such as relative humidity, water-soluble inorganic ions, and pH, were analyzed. Our results indicated that the secondary formation of imidazoles can be greatly enhanced under high humidity conditions, particularly during fog events. Overall, this study offers valuable insights into potential sources and influencing factors of ambient imidazoles in background atmospheres.

Impact of different sources on the oxidative potential of ambient particulate matter PM10 in Riyadh, Saudi Arabia: A focus on dust emissions

In this study, we employed Principal Component Analysis (PCA) and Multi-Linear Regression (MLR) to identify the most significant sources contributing to the toxicity of PM10 in the city center of Riyadh. PM10 samples were collected using a medium-volume air sampler during cool (December 2019-March 2020) and warm (May 2020-August 2020) seasons, including dust and non-dust events. The collected filters were analyzed for their chemical components (i.e., water-soluble ions, metals, and trace elements) as well as oxidative potential and elemental and organic carbon (EC/OC) contents. Our measurements revealed comparable extrinsic oxidative potential (P-value = 0.30) during the warm (1.2 ± 0.1 nmol/min-m3) and cool (1.1 ± 0.1 nmol/min-m3) periods. Moreover, we observed higher extrinsic oxidative potential of PM10 samples collected during dust events (~30% increase) compared to non-dust samples. Our PCA-MLR analysis identified soil and resuspended dust, secondary aerosol (SA), local industrial activities and petroleum refineries, and traffic emissions as the four sources contributing to the ambient PM10 oxidative potential in central Riyadh. Soil and resuspended dust were the major source contributing to the oxidative potential of ambient PM10, accounting for 31% of the total oxidative potential. Secondary aerosols (SA) were the next important source of PM10 toxicity in the area as they contributed to about 20% of the PM10 oxidative potential. Results of this study revealed the major role of soil and resuspended road dust on PM10 toxicity and can be helpful in adopting targeted air quality policies to reduce the population exposure to PM10.

Using a hybrid approach to apportion potential source locations contributing to excess cancer risk of PM2.5-bound PAHs during heating and non-heating periods in a megacity in the Middle East

Polycyclic aromatic hydrocarbons (PAHs) represent one of the major toxic pollutants associated with PM_2.5 with significant human health and climate effects. Because of local and long-range transport of atmospheric PAHs to receptor sites, higher global attentions have been focused to improve PAHs pollution emission management. In this study, PM_2.5 samples were collected at three urban sites located in the capital of Iran, Tehran, during the heating and non-heating periods (H-period and NH-period). The US EPA 16 priority PAHs were analyzed and the data were processed to the following detailed aims: (i) investigate the H-period and NH-period variations of PM_2.5 and PM_2.5-bound PAHs concentrations; (ii) identify the PAHs sources and the source locations during the two periods; (iii) carry out a source-specific excess cancer risk (ECR) assessment highlighting the potential source locations contributing to the ECR using a hybrid approach. Total PAHs (TPAHs) showed significantly higher concentrations (1.56-1.89 times) during the H-period. Among the identified PAHs compounds, statistically significant periodical differences (p-value < 0.05) were observed only between eight PAHs species (Nap, BaA, Chr, BbF, BkF, BaP, IcdP, and DahA) at all three sampling sites which can be due to the significant differences of PAHs emission sources during H and NH-periods. High molecular weight (HMW) PAHs accounted for 52.7% and 46.8% on average of TPAHs during the H-period and NH-period, respectively. Positive matrix factorization (PMF) led to identifying four main PAHs sources including industrial emissions, petrogenic emissions, biomass burning and natural gas emissions, and vehicle exhaust emissions. Industrial and petrogenic emissions exhibited the highest contribution (19.8%, 27.2%, respectively) during the NH-period, while vehicle exhaust and biomass burning-natural gas emissions showed the largest contribution (40.7%, 29.6%, respectively) during the H-period. Concentration weighted trajectory (CWT) on factor contributions was used for tracking the potential locations of the identified sources. In addition to local sources, long-range transport contributed to a significant fraction of TPHAs in Tehran both during the H- and NH-periods. Source-specific carcinogenic risks assessment apportioned vehicle exhaust (44.2%, 2.52 × 10^-4) and biomass burning-natural gas emissions (33.9%, 8.31 × 10^-5) as the main cancer risk contributors during the H-period and NH-period, respectively. CWT maps pointed out the different distribution patterns associated with the cancer risk from the identified sources. This will allow better risk management through the identification of priority PAHs sources.

Are standardized diesel exhaust particles (DEP) representative of ambient particles in air pollution toxicological studies?

In this study, we investigated the chemical characteristics of standardized diesel exhaust particles (DEP) and compared them to those of read-world particulate matter (PM) collected in different urban settings to evaluate the extent to which standardized DEPs can represent ambient particles for use in toxicological studies. Standard reference material SRM-2975 was obtained from the National Institute of Standards and Technology (NIST) and was chemically analyzed for the content of elemental carbon (EC), organic carbon (OC), polycyclic aromatic hydrocarbons (PAHs), inorganic ions, and several metals and trace elements. The analysis on the filter-collected DEP sample revealed very high levels of EC (i.e., ~397 ng/μg PM) which were comparable to the OC content (~405 ng/μg PM). This is in contrast with the carbonaceous content in the emitted particles from typical filter-equipped diesel-powered vehicles, in which low levels of EC emissions were observed. Furthermore, the EC mass fraction of the DEP sample did not match the observed levels in the ambient PM of multiple US urban areas, including Los Angeles (8%), Houston (~14%), Pittsburgh (~12%), and New York (~17%). Our results illustrated the lack of several high molecular weight carcinogenic PAHs in the DEP samples, unlike our measurements in major freeways of Los Angeles. Negligible levels of inorganic ions were observed in the sample and the DEP did not contain toxic secondary organic aerosols (SOAs) formed through synchronized reactions in the atmosphere. Lastly, the analysis of redox-active metals and trace elements demonstrated that the levels of many species including vehicle emission tracers (e.g., Ba, Ti, Mn, Fe) on Los Angeles roadways were almost 20 times greater than those in the DEP sample. Based on the abovementioned inconsistencies between the chemical composition of the DEP sample and those of real-world PM measured and recorded in different conditions, we conclude that the standardized DEPs are not suitable representatives of traffic emissions nor typical ambient PM to be used in toxicological studies.

Heating events drive the seasonal patterns of volatile organic compounds in a typical semi-arid city

The emission characteristics, source apportionment and chemical behavior of volatile organic compounds (VOCs) are important for strategy-making on ozone (O₃) and fine particulate matter (PM_2.5) control. Based on the continuous observation during four seasons, the seasonal characteristics, chemical reactivity and source apportionment of 116 VOCs species were studied in a typical semi-arid city with no relevant research. The results showed that the annual average concentrations of total volatile organic compounds (TVOCs) in Hohhot was 44.67 ± 46.59 ppbv with the predominant of alkanes and oxygenated volatile organic compounds (OVOCs). The sharp increment of TVOCs were explained by the elevating OVOCs and alkanes in autumn, while alkanes and alkenes in winter. The levels of alkenes presented negative and positive correlations with solar radiation and PM₁₀, respectively. The mixing ratios accounted for 30% (alkanes) and 23% (alkenes and aromatics) of the TVOCs, respectively; while their ozone formation potential (OFP) ~15% and nearly 50% (even 75% in winter), respectively, indicating that the OFP of different VOCs species depends not only on their concentrations but more importantly on their chemical activity in atmosphere. According to the seasonal source apportionment, both the high levels of short-chain alkanes, alkenes and aromatics and the increasing coal sales volume suggested that the combustion sources were the predominant in heating seasons, while solvent uses was extracted as the most predominant during non-heating seasons. In non-heating seasons, the biogenic emission sources, ranking as the second contributor, were significantly higher than heating seasons. Isoprene was the most active biogenic VOCs species, bagging test results showed that deciduous trees were the predominant contributors for isoprene (~99%), while coniferous trees and shrub for monoterpenes (>95%). It will be helpful for understanding the characteristics of VOCs in Chinese national key development areas and informing policy to control semi-arid regional VOCs air pollution.

Chemical Composition and Source Apportionment of Total Suspended Particulate in the Central Himalayan Region

The present study analyzes data from total suspended particulate (TSP) samples collected during 3 years (2005–2008) at Nainital, central Himalayas, India and analyzed for carbonaceous aerosols (organic carbon (OC) and elemental carbon (EC)) and inorganic species, focusing on the assessment of primary and secondary organic carbon contributions (POC, SOC, respectively) and on source apportionment by positive matrix factorization (PMF). An average TSP concentration of 69.6 ± 51.8 µg m−3 was found, exhibiting a pre-monsoon (March–May) maximum (92.9 ± 48.5 µg m−3) due to dust transport and forest fires and a monsoon (June–August) minimum due to atmospheric washout, while carbonaceous aerosols and inorganic species expressed a similar seasonality. The mean OC/EC ratio (8.0 ± 3.3) and the good correlations between OC, EC, and nss-K+ suggested that biomass burning (BB) was one of the major contributing factors to aerosols in Nainital. Using the EC tracer method, along with several approaches for the determination of the (OC/EC)pri ratio, the estimated SOC component accounted for ~25% (19.3–29.7%). Furthermore, TSP source apportionment via PMF allowed for a better understanding of the aerosol sources in the Central Himalayan region. The key aerosol sources over Nainital were BB (27%), secondary sulfate (20%), secondary nitrate (9%), mineral dust (34%), and long-range transported mixed marine aerosol (10%). The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses were also used to identify the probable regional source areas of resolved aerosol sources. The main source regions for aerosols in Nainital were the plains in northwest India and Pakistan, polluted cities like Delhi, the Thar Desert, and the Arabian Sea area. The outcomes of the present study are expected to elucidate the atmospheric chemistry, emission source origins, and transport pathways of aerosols over the central Himalayan region.

Insights into the source-specific health risk of ambient particle-bound metals in the Pearl River Delta region, China

Quantification of source-specific health risks of PM2.5 plays an essential role in health-oriented air pollution control. However, there is limited evidence supporting the source-based risk apportionment of particle-bound metals. In this study, source-specific cancer and non-cancer risk characterization of 12 particle-bound metals was performed in the Pearl River Delta (PRD) region, China. A combination of health risk assessment model and receptor-based source apportionment modeling with positive matrix factorization (PMF) was applied for characterizing the spatial-temporal patterns for inhalation health risks of particle-bound metals in three main city clusters, inland area and coastal area in the region from December 2014 through July 2016. Results showed that the carcinogenic risk of particle-bound metals for adults (4.13 × 10-5) was higher than that for children (9.53 × 10-6) in the PRD region. The highest and significant non-carcinogenic risk was found in the northwest city cluster. Industrial emission (63.3%) were the dominant contributors to the cancer risk, while the main contributors to the non-cancer risk were the vehicle emission source (33.2%) in the dry season and industrial emission (30.8%) in the wet season. Our results provide important evidence for spatial source-specific health risks with temporal characteristics of particle-bound metals in most densely populated areas in the southern China, and suggest that reduction of industrial and vehicle emissions could facilitate more cost-effective PM2.5 control measures to improve human health.

Toxic metals in outdoor/indoor airborne PM2.5 in port city of Northern, China: Characteristics, sources, and personal exposure risk assessment

Outdoor and indoor PM_2.5 samples were simultaneously collected over four seasons (2017-2018) in Caofeidian, China, and analyzed for 15 elements to investigate the characteristics, sources, and health risks of PM_2.5-bound metals. Source-specific PM_2.5-bound metals were analyzed using positive matrix factorization, combined with the conditional probability function and potential source contribution function model. The health risks were evaluated using the health risk assessment model, which included the exposure parameters of indoor and outdoor activities of Chinese residents. The annual median of PM_2.5 concentrations (89.68 μg/m³) and total metals (2.67 μg/m³) from the outdoor samples significantly surpassed that of the indoor samples (51.56 μg/m³) and total metals (1.51 μg/m³) (P < 0.05). In addition, the indoor/outdoor concentration ratios indicated that most indoor metals mainly originated from outdoor emission sources. In the annual analysis of PM_2.5-bound metal sources, this study identified five metal sources: coal combustion, resuspended dust, traffic emissions, fuel combustion sources, and industrial sources, among which industry sources (36.6%) contributed the most. The non-carcinogenic risks of metals for adults (2.81) and children (2.80) all exceed the acceptable non-carcinogenic risk level (1). The non-carcinogenic risk of Mn (1.46 for children, 1.48 for adults) was a key factor in the total non-carcinogenic risk. The total carcinogenic risk of metals for children (3.75 × 10^-5) was above the acceptable level (1.0 × 10^-6) but within the tolerant limit (1.0 × 10^-4), and that for adults (1.48 × 10^-4) was above the tolerant limit. The lifetime carcinogenic risk of Cr⁶⁺ had the highest proportion of the total carcinogenic risk for children (87.5%) and adults (87.8%). Our results revealed that both adults and children suffered carcinogenic and non-carcinogenic risks from the PM_2.5-bound metals in Caofeidian. The corresponding emission control measures of metals in atmosphere should be considered.

High-time-resolution PM2.5 source apportionment based on multi-model with organic tracers in Beijing during haze episodes

Fine particulate matter (PM_2.5) is a prominent atmospheric pollutant that poses serious adverse effects on air quality and human health. PM_2.5 source apportionment based on receptor model suggests that Beijing is polluted by mixed emission sources, but the model is limited by a lack of organic tracers and an inability to distinguish between contributions from local and regional transport. In this study, positive matrix factorization (PMF) model with organic tracers was employed to analyze refined PM_2.5 pollution sources at 1-h time resolution, and the contribution of regional transport was quantified using Particulate source apportionment technology (PSAT) in the Comprehensive Air Quality Model with Extensions (CAMx). The results identified nine source types using PMF model based on offline data for PM_2.5 concentrations, organic carbon, elemental carbon, water-soluble ions, trace elements and organic species. Gasoline and diesel exhausts were distinguished by adding polycyclic aromatic hydrocarbons (PAHs), C19-C24 n-alkanes as key organic tracers. In addition, levoglucosan and hexadecanoic acid are important additions for identifying biomass burning and cooking, respectively. Furthermore, the contribution of specific sources and source regions, from the formation to dissipation of two typical haze episodes (EP1 and EP2) in Beijing, was quantitatively analyzed. EP1 was primarily caused by local emissions with an average contribution rate of 67.5%, characterized by secondary source, gasoline and diesel exhausts, as well as industrial source. EP2 was dominated by secondary source from regional transport contributing approximately 50%. Short-range transport from Baoding (9.1%) and Langfang (5.8%) in Hebei Province was the largest external contributor, and long-range transport contributed 20% of the PM_2.5 concentration. This study suggests that combining receptor model-based source apportionment with air quality model has practical significance for understanding the causes of haze episodes, setting city-specific emission reduction measures and improving air quality in the Beijing-Tianjin-Hebei (BTH) region.

Airborne particulate matter in Tehran's ambient air

In recent decades, particulate matter (PM) concentrations in Tehran have exceeded the World Health Organization's (WHO) guideline on most days. In this study, a search protocol was defined by identifying the keywords, to carry out a systematic review of the concentrations and composition of PM in Tehran's ambient air. For this purpose, searches were done in Scopus, PubMed, and Web of Science in 2019. Among the founded articles (197 in Scopus, 61 in PubMed, and 153 in Web of Science). The results show that in Tehran, the annual average PM10 exceeded the WHO guidelines and for more than 50.0% of the days, the PM2.5 concentration was more than WHO 24-h guidance value. The PM concentration in Tehran has two seasonal peaks due to poorer dispersion and suspension from dry land, respectively. Tehran has two daily PM peaks due to traffic and changes in boundary-layer heights; one just after midnight and the other during morning rush hour. Indoor concentrations of PM10 and PM2.5 in Tehran were 10.6 and 21.8 times higher than the corresponding values in ambient air. Tehran represents a unique case of problems of controlling PM because of its geographical setting, emission sources, and land use. This review provided a comprehensive assessment for decision makers to assist them in making appropriate policy decisions to improve the air quality. Considering factors such as diversity of resources, temporal and spatial variations, and urban location is essential in developing control plans. Also future studies should focus more on PM reduction plans.

Heavy metal pollution of road dust in a city and its highly polluted suburb; quantitative source apportionment and source-specific ecological and health risk assessment

Sources of heavy metals (As, Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn) in the road dust of Bandar Abbas city, Iran, and its west suburb were apportioned and the related source-specific ecological and health risks were assessed. The level of heavy metal pollution and the related ecological risk for suburban road dust (suburban RD) were far higher than those of urban RD. Accordingly, probabilistic health risk assessment showed no significant health risk in urban region but significant health risk in the suburb, especially for As with cancer risk above 10^-4. Source apportionment using positive matrix factorization (PMF) identified lithogenic source (45.9%) and traffic emission (47.6%) as the main sources of heavy metals in urban and suburban regions, respectively. However, the industrial/construction activities showed the main contribution in ecological risk in both regions. On the other hand, the health risks in urban and suburban regions were mainly attributed to lithogenic source (49.7% for non-cancer risk and 36.8% of cancer risk) and traffic emission (69.4% of non-cancer risk and 46.6% of cancer risk), respectively. The sensitivity analysis showed that the Pb and As originated from traffic emission had the most impact on the non-cancer and cancer risks, respectively, in the suburb. Therefore, this study highlighted the concern about traffic emission as a critical heavy metal source in the road dust of Bandar Abbas suburb.