Positive Matrix Factorization Method Research Articles

Arsenic-contaminated groundwater of the Western Banat (Pannonian basin): Hydrogeochemical appraisal, pollution source apportionment, and Monte Carlo simulation of source-specific health risks.

Due to rapid urbanization and industrial growth, groundwater globally is continuously deteriorating, posing significant health risks to humans. This study employed a comprehensive methodology to analyze groundwater in the Western Banat Plain (Serbia). Using Piper and Gibbs plots, hydrogeochemistry was assessed, while the entropy-weighted water quality index (EWQI) was used to evaluate groundwater quality. Pollution sources were identified using positive matrix factorization (PMF) accompanied by Pearson correlation and hierarchical cluster analysis, while Monte Carlo simulation assessed health risks associated with groundwater consumption. Results showed that groundwater, mainly Ca-Mg-HCO3 type, is mostly suitable for drinking. Geogenic pollution, agricultural activities, and sewage were major pollution sources. Consumption of contaminated groundwater poses serious non-carcinogenic and carcinogenic health risks. Additionally, arsenic from geogenic source was found to be the main health risks contributor, considering its worryingly elevated concentration, ranging up to 364 μg/L. These findings will be valuable for decision-makers and researchers in managing groundwater vulnerability. PRACTITIONER POINTS: Groundwater is severely contaminated with As in the northern part of the study area. The predominant hydrochemical type of groundwater in the area is Ca-Mg-HCO3. The PMF method apportioned three groundwater pollution sources. Monte Carlo identified rock dissolution as the primary health risk contributor. Health risks and mortality in the study area are positively correlated.

Typical emerging contaminants in sewage treatment plant effluent, and related watersheds in the Pearl River Basin: Ecological risks and source identification

Emerging contaminants pose a potential risk to aquatic ecosystems in the Pearl River Basin, China, owing to the high population density and active industry. This study investigated samples from eight sewage treatment plants, and five surface water bodies of related watersheds. To screen the risk of emerging contaminants (ECs), and clarify their sources, this study calculated the risk quotient of detected chemical and performed source identification/apportionment using the positive matrix factorization method. In total, 149 organic pollutants were identified. Pharmaceuticals showed significant concentrations in sewage treatment plant samples (120.87 ng/L), compared with surface water samples (1.13 ng/L). The ecological risk assessment identified three chemicals with a heightened risk to aquatic organisms: fipronil sulfide, caffeine, and roxithromycin. Four principal sources of contaminants were identified: pharmaceutical wastewater, domestic sewage, medical effluent, and agricultural runoff. Pharmaceutical wastewater was the primary contributor (60.4 %), to the cumulative EC concentration and to ECs in sewage treatment plant effluent. Agricultural drainage was the main source of ECs in surface water. This study provides a strategy to obtain comprehensive information on the aquatic risks and potential sources of EC species in areas affected by artificial activities, which is of substantial importance to pollutant management and control.

Risk assessment and source identification of soil heavy metals: a case study of farmland soil along a river in the southeast of a mining area in Southwest China.

To investigate the heavy metals (HMs) contamination of surface farmland soil along the river in the southeast of a mining area in southwest China and identify the contamination sources, 54 topsoil samples were collected and the concentrations of seven elements (Zn, Ni, Pb, Cu, Hg, Cr, and Co) were determined by inductively coupled plasma optical emission spectrometry (ICP-OES) and atomic fluorescence spectrometry (AFS). The geo-accumulation index ([Formula: see text]) and comprehensive potential ecological risk index ([Formula: see text]) were used for analysis to determine the pollution degree of HMs and the risk level of the study area. Meanwhile, the Positive Matrix Factorization (PMF) model was combined with a variety of statistical methods to determine the sources of HMs. To explore the influence of the river flowing through the mining area on the concentrations of HMs in the farmland soil, 15 water samples were collected and the concentrations of the above seven elements were determined. The results showed that the concentrations of Pb, Cu, and Zn in soil all exceeded the risk screening value, and Pb in soil of some sampling sites exceeded control value of "Agricultural Land Soil Pollution Risk Control Standard".[Formula: see text] showed that Pb was heavily contaminated, while Cu and Zn were moderately contaminated. RI showed that the study area was at moderate risk. PMF and various statistical methods showed that the main source of HMs was the industrial source. In the short term, the river flowing through the mine has no significant influence on the concentration of HMs in the soil. The results provide a reference for the local government to control contamination and identify the sources of HMs.

Distribution and source identification of polycyclic aromatic hydrocarbons (PAHs) with PCA-MLR and PMF methods in the topsoil of Chengdu at SW, China

In spite of extensive studies on the features of polycyclic aromatic hydrocarbons (PAHs) as typical persistent organic pollutants (POPs) in cities, lack of understanding on the distribution and source characteristics of PAHs in big city with basin climate that can easily accelerate the pollution. Therefore, we sampled and analyzed PAHs from forty-five topsoil samples evenly distributed in Chengdu and the data shows that: (1) concentrations of ∑16PAHs in the study area ranged from 88.56 to 4448.34 ng/g, with a mean value of 739.07 ng/g, which is a lower level compared to similar cities, the distribution and proportion of LMW-PAHs show that the migration of pollution is blocked by the topography of the basin; (2) principal component analysis-multiple linear regression (PCA-MLR) and positive matrix factorization (PMF) indicated that combustion of fossil fuels and biomass is the most important source of PAHs in Chengdu; (3) the toxic equivalency factors of benzo[a]pyrene indicated a low risk of ∑16PAHs in all areas in Chengdu; (4) the inherited lifetime carcinogenic risk (ILCR) showed a relatively low level of potential risk in the region, while female inhabitants in several regions seem to suffer from higher health risks. Overall, our case study of PAHs in the topsoil at Chengdu city at SW China indicates that the PCA-MLR analysis is useful to identify the source of PAHs in the urban region with complicated pollution source.

Source apportionment of heavy metal(loid)s in sediments of a typical karst mountain drinking-water reservoir and the associated risk assessment based on chemical speciations.

As important place for water storage and supply, drinking-water reservoirs in karst mountain areas play a key role in ensuring human well-being, and its water quality safety has attracted much attention. Source apportionment and ecological risks of heavy metal(loid)s in sediments of drinking-water reservoir are important for water security, public health, and regional water resources management, especially in karst mountain areas where water resources are scarce. To expound the accumulation, potential ecological risks, and sources of heavy metal(loid)s in a drinking-water reservoir in Northwest Guizhou, China, the surface sediments were collected and analyzed based on the combined use of the geo-accumulation index (Igeo), sequential extraction (BCR), ratios of secondary phase and primary phase (RSP), risk assessment code (RAC), modified potential ecological risk index (MRI), as well as the positive matrix factorization methods. The results indicated that the accumulation of Cd in sediments was obvious, with approximately 61.9% of the samples showing moderate to high accumulation levels, followed by Pb, Cu, Ni, and Zn, whereas the As and Cr were at low levels. A large proportion of BCR-extracted acid extractable and reducible fraction were found in Cd (72.5%) and Pb (40.3%), suggesting high bioavailability. The combined results of RSP, RAC, and MRI showed that Cd was the major pollutant in sediments with high potential ecological risk, while the risk of other elements was low. Source apportionment results of heavy metal(loid)s indicated that Cd (75.76%) and Zn (23.1%) mainly originated from agricultural activities; As (69.82%), Cr (50.05%), Cu (33.47%), and Ni (31.87%) were associated with domestic sources related to residents' lives; Cu (52.36%), Ni (44.57%), Cr (34.33%), As (26.51%), Pb (24.77%), and Zn (23.80%) primarily came from natural geological sources; and Pb (47.56%), Zn (22.46%) and Cr (13.92%) might be introduced by mixed sources of traffic and domestic. The contribution ratios of the four sources were 18.41%, 36.67%, 29.48%, and 15.44%, respectively. Overall, priority control factors for pollution in relation to agricultural sources included Cd, while domestic sources are primarily associated with As. It is crucial to place special emphasis on the impacts of human activities when formulating pollution prevention and control measures. The results of this study can provide valuable reference and insights for water resources management and pollution prevention and control strategies in karst mountainous areas.

Risk Assessment and Source Apportionment of Metals on Atmospheric Particulate Matter in a Suburban Background Area of Gran Canaria (Spain).

Concentration levels of 11 heavy metals were analyzed in PM10 and PM2.5 samples from a suburban area frequently affected by Saharan dust in which is located a school. The heavy metals risk assessment was carried out by the 2011 U.S. Environmental Protection Agency method, estimating the chronic and carcinogenic hazard levels both in adults and children. The highest level of chronic hazard was reached for Cr, with values of approximately 8 (PM10, adulthood), 2 (PM10, childhood) and 1.5 (PM2.5, adult age), significantly exceeding the limit value (equal to 1). Regarding the carcinogenic risk level, it was also high for Cr, with values between 10-3 and 10-1 for both study populations and particle size. For the rest of the studied metals, no health risk levels of concern were obtained. The positive matrix factorization method was used for the estimation of heavy metal emission sources apportionment. Non-exhaust vehicle emissions were the main source of Cr emissions under PM2.5, while industrial processes were the main source for PM10. Mineral dust and marine aerosol were common emission sources for both particles sizes-with different contributions. Vehicle emissions, construction and agricultural activities were the main emission sources for PM10, and fossil fuel combustion, road dust re-suspension and ammonium sulfate were for PM2.5. The results obtained in this study support the need to continue applying mitigation measures in suburban areas which are affected by nearby anthropogenic emissions, causing the consequent emission of materials hazardous to human health.

Source apportionment and health impact assessment of atmospheric particulate matter in the city of São Carlos, Brazil

In this study, positive matrix factorization method was used for source apportionment of PM10 in the city of São Carlos from 2015 to 2018. The annual mean concentrations of PM10, 15 PAHs, 4 oxy-PAHs, 6 nitro-PAHs, 21 saccharides, and 17 ions in these samples were in the ranges 18.1 ± 6.99 to 25.0 ± 11.3 μg m−3 for PM10, 9.80 × 10−1 ± 2.06 to 2.03 ± 8.54 × 10−1 ng m−3 for ΣPAHs, 83.9 ± 35.7 to 683 ± 521 pg m−3 for Σoxy-PAHs, 1.79 × 10−2 ± 1.23 × 10−1 to 7.12 ± 4.90 ng m−3 for Σnitro-PAHs, 83.3 ± 44.7 to 142 ± 85.9 ng m−3 for Σsaccharides, and 3.80 ± 1.54 to 5.66 ± 4.52 μg m−3 for Σions. For most species, the concentrations were higher in the dry season than in the rainy. This was related not only to the low rainfall and relative humidity characteristic of the dry season but also to an increase in fire spots recorded in the region between April and September every year from 2015 to 2018. A 4-factor solution provided the best description of the dataset, with the four identified sources of PM10 being soil resuspension (28%), biogenic emissions (27%), biomass burning (27%), and vehicle exhaust together with secondary PM (18%). Although the PM10 concentrations were not above the limit established by local legislation, the epidemiological study showed that by reducing PM2.5 concentrations to the level recommended by the WHO, approximately 35 premature deaths per 100,000 population could be avoided annually. The results revealed that biomass burning continues to be one of the main anthropic sources of emissions to the atmosphere in the region, so it needs to be incorporated into the existing guidelines and policies to reduce the concentration of particulate matter to within the limits recommended by the WHO, in order to avoid premature deaths.

Parent and alkylated polycyclic aromatic hydrocarbon emissions from coal seam fire at Wuda, Inner Mongolia, China: characteristics, spatial distribution, sources, and health risk assessment.

The Wuda coalfield in Inner Mongolia is a vital coal base in China, and it is the hardest-hit area for coal fires (spontaneous combustion of coal seams and coal gangue). Using gas chromatography-mass spectrometry, this work tested the concentration and analyzed the characteristics, distribution, sources, and health risks of polycyclic aromatic compounds (PACs) in the surface soil of the Wuda District, including the coal mine, coal fire, agricultural, and background areas. The soil of coal mine and coal fire area were heavily polluted with PACs, with mean concentrations of 9107 and 3163µgkg-1, respectively, considerably higher than those in the agricultural (1232µgkg-1) and background areas (710µgkg-1). Alkyl polycyclic aromatic hydrocarbons (APAHs) were the dominant pollutants among these PACs, accounting for 60-81%. Alkyl naphthalenes and alkyl phenanthrenes are the primary pollutants in APAHs, accounting for 80-90% of the total amounts. Additionally, using the positive matrix factorization method, it can be concluded that the primary PAC sources are petrogenic sources, coal and biomass combustion, coal fires, and vehicle emissions. Finally, according to the cancer risk values of 16 PAHs, only the coal mine area showed a potential cancer risk. However, this result lacks a risk assessment of APAHs and underestimates the actual risk. The results of this study improved the understanding of PAC pollution in coal fire and surrounding areas and provided a reference for environmental and health risk investigations.

PM2.5-bound PAHs near a typical industrial park: Determining health risks associated with specific industrial sources

Source-specific potential health risk was proposed as an effective index for determining priority control sources of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) near an industrial park. However, industry-specific emission profiles were limited. In this study, 60 emission source samples from 13 industries and 139 p.m.2.5 samples near an industrial park were collected from 2020 to 2021. The PAH profiles of 12 industrial emission sources were constructed to address the difficulty of source apportionment refined to industrial categories. A diagnostic ratio method and a positive matrix factorization method (PMF) were used to qualitatively and quantitatively determine the emission sources of 16 p.m.2.5-bound PAHs. The incremental lifetime carcinogenic risk (ILCR) of PAH inhalation exposure for the local population was attributed to sources by a PMF-ILCR model. The results show that the local PAH pollution seriously exceeded (86.3% sampling days) the standard (GB3095-2012). The concentration of PAHs was 33.6 ± 32.6 ng/m3 and showed a seasonal trend of “heating season > autumn > spring”. There were five main sources of PM2.5-bound PAHs near the industrial park: heavy oil combustion (29.8%), coal and natural gas combustion (28.0%), vehicle emissions (19.9%), steel industry emissions (19.4%) and tar volatilization (2.9%). There is potential carcinogenic risk to both children (3.1 × 10−6) and adults (1.2 × 10−5). The mass contribution of each source to ambient PAHs is not equivalent to its contribution to potential health risk. The risks of PM2.5-bound PAHs almost all correspond to vehicle emissions (46.3%), heavy oil combustion (25.9%) and steel industrial sources (24.9%).

Source apportionment of polychlorinated dibenzo-p-dioxins and dibenzofurans in the sediments of an urban estuary.

Polychlorinated dibenzo-p-dioxins and dibenzofurans in the sediments of aquatic systems are a persistent global problem that poses serious health risks. Identifying the sources of dioxins in natural water systems and the extent of their contributions to observed sediment concentrations is important from a health advisory and mitigation perspective. This paper proposes novel distribution-based qualitative and quantitative methods as source apportionment techniques and alternatives to conventional source attribution methods. Using sampled data, air, runoff, industrial effluent, and industrial paper and pulp wastes were identified as four distinct dioxin contributors to concentrations found in the sediments of the test bed region: the Houston Ship Channel-San Jacinto River-Galveston Bay (HSC-SJR-GB) estuarine system that also includes 2 Superfund sites with dioxin contamination. Two qualitative methods, the Kullback-Leibler divergence (K-L divergence) and the Bhattacharya measure (BM), and a quantitative method, the L2 norm, were used to investigate the spatial and temporal sourcing patterns of dioxins in the system sediments. The results indicated a global contribution from air and runoff sources across the estuarine system and over time with more localized impacts of the Superfund sites and the industrial sources. The results using the developed methodologies were compared with the output from the more conventional positive matrix factorization (PMF) method. Statistically significant correlations were observed among source contributions from the proposed methods and the PMF method, with Spearman's ρ ranging between - 0.596 to - 0.963 and 0.652 to 0.719, demonstrating the utility of the sourcing approaches used in the study. Additionally, the proposed methods were found to be rigorous in terms of elucidating spatial and temporal changes in the sourcing of dioxin to the estuary, indicating their suitability for use for other contaminants and other estuarine systems.

Exploring the formation mechanism of fine particles in an ex-heavily polluted Northwestern city, China

Fine particle pollution is still a severe issue in the northwestern region of China where the formation mechanism of which remains ambiguous due to the limited studies there. In this study, a comprehensive study on the chemical composition and sources of PM2.5 at an ex-heavily polluted northwestern city was conducted, based on filter sampling data obtained from three consecutive winter campaigns during 2020–2022. The average PM2.5 during the three winter campaigns were 170.9 ± 66.4, 249.0 ± 75.7, and 200.9 ± 47.6 μg/m3, respectively, with the daily maximum value of PM2.5 exceeds 400 μg/m3 under stagnant meteorological conditions charactered by high relative humidity (>60 %) and low wind speed (<1 m/s). The major chemical components in PM2.5 were found to be inorganic aerosol (55.2 %) that mainly constituted by sulfate (24.2 %), and mineral dust (14.9 %); while the carbonous species contributed a minor fraction (∼13 %). In addition, (NH4)2SO4 and NH4NO3 were the dominate contributors to appearance of low visibility (<3 km) which together accounting for over 85 % of light extinction coefficient (bext) during heavy polluted period. Source appointment of fine particles was then conducted by applying the positive matrix factorization method, and the primary sources were resolved to be coal combustion (27.7 %) and biomass burning (18.6 %), followed by industrial dust (16.2 %), residential combustion (15.3 %), traffic emissions (11.9 %) and dust aerosol (10.4 %). To explore the potential formation mechanism of fine particle pollution, the chemical evolution pattern combined with gaseous pollutants and meteorological parameters were further analyzed, which refine the important role of primary emissions in the forming of high sulfate aerosol loading, while secondary formation was largely suppressed during the winter period that totally different from those reported in the developed regions of China, thus indicating more effort should be paid on the reduction of primary particles emissions in the northwestern cities than on its gaseous percussors.

Measurement report: Atmospheric new particle formation in a coastal agricultural site explained with binPMF analysis of nitrate CI-APi-TOF spectra

Abstract. The occurrence of new particle formation (NPF) events detected in a coastal agricultural site, at Qvidja, in Southwestern Finland, was investigated using the data measured with a nitrate ion-based chemical-ionization atmospheric-pressure-interface time-of-flight (CI-APi-TOF) mass spectrometer. The binned positive matrix factorization method (binPMF) was applied to the measured spectra. It resulted in eight factors describing the time series of ambient gas and cluster composition at Qvidja during spring 2019. The most interesting factors related to the observed NPF events were the two factors with the highest mass-to-charge ratios, numbered 7 and 8, both having profiles with patterns of highly oxygenated organic molecules with one nitrogen atom. It was observed that factor 7 had elevated intensities during the NPF events. A variable with an even better connection to the observed NPF events is fF7, which denotes the fraction of the total spectra within the studied mass-to-charge ratio range between 169 and 450 Th being in a form of factor 7. Values of fF7 higher than 0.50±0.05 were observed during the NPF events, of which durations also correlated with the duration of fF7 exceeding this critical value. It was also observed that factor 8 acts like a precursor for factor 7 with solar radiation and that the formation of factor 8 is associated with ozone levels.

Results of Source Apportionment by Receptor Modeling of Ulaanbaatar City

Results of an air pollution source apportionment study using the Positive Matrix Factorization method (PMF) based on sampling of air pollution from a site of Nuclear Research Center, National University of Mongolia 2004-2009 and Zuun ail site 2008-2009 presented. From the statistical analysis of the data, it was possible to allocate factors to sources associated with coal combustion, motor vehicles, road dust, and soil.

Improved positive matrix factorization for source apportionment of volatile organic compounds in vehicular emissions during the Spring Festival in Tianjin, China

Photochemical losses of volatile organic compounds (VOCs) and uncertainties in calculated factor profiles can reduce the accuracy of source apportionment by positive matrix factorization (PMF). We developed an improved PMF method (termed ICLP-PMF) that estimated the reaction-corrected (“initial”) concentrations of VOCs. Source profiles from literature provided constraints. ICLP-PMF evaluated the vehicular emission contributions to hourly speciated VOC data from December 2020 to March 2021 and estimated gasoline and diesel vehicles contributions to Tianjin's VOC concentrations around the Chinese Spring Festival (SF). The average observed and initial total VOCs (TVOCs) concentrations were 24.2 and 42.9 ppbv, respectively. Alkanes were the highest concentration VOCs while aromatics showed the largest photochemical losses during the study period. Literature gasoline and diesel profiles from representative Chinese cities were constructed and provided constraints. Source apportionment was performed using ICLP-PMF method and three other PMF approaches. Photochemical losses of alkenes and aromatic hydrocarbons induced differences between calculated factor profiles and literature profiles. Using observed concentrations and unconstrained profiles produced underestimated SF contributions (∼121% and 72% for gasoline and diesel vehicles, respectively). According to the ICLP-PMF results, the contributions of gasoline and diesel vehicles during the SF were 25.6% and 23.2%, respectively, lower than those before and after the SF. No diel diesel vehicle contribution variations were found during the SF likely due to the decline in truck activity north of the study site during the holiday period.

Source apportionment and ecological and health risk mapping of soil heavy metals based on PMF, SOM, and GIS methods in Hulan River Watershed, Northeastern China.

Heavy metals in agricultural soils not only affect the food security and soil security, but also endanger the human health through the food chain. Based on the incorporation of index analysis, positive matrix factorization (PMF), self-organizing map (SOM), and geostatistical methods, this research performed the assessment of source apportionment and ecological and health risks of soil heavy metals in Hulan River Watershed, Northeastern China. According to the Pollution Load Index (PLI), 83.08% of the soil samples were slightly or mildly polluted, and 1.54% of the soil samples were severely polluted. The ecological risk index (EI) showed that about 80.77% and 60.77% of the soil samples were beyond the low risk level for Hg and Cd, respectively. In this research, the non-carcinogenic and carcinogenic risk indices for children were higher than adult males and adult females. Four potential sources were revealed based on the PMF and SOM analysis including atmospheric deposition and industrial emission; transportation source; agricultural source; and a combination of agricultural, industrial, and natural sources. Considerable and high ecological risk from Hg existed in the area close to the coal steam-electric plant, and considerable and high ecological risk from Cd existed in the Hulan River estuary area. The eastern part of the study area experienced higher non-carcinogenic and carcinogenic risks for adults and children than the western part of the study area. The source apportionment and ecological and health risk mapping provide important role in reducing pollution sources. Zonal pollution control and soil restoration measures should be performed in the areas with high ecological and health risks.

Spatial distribution, risk estimation and source apportionment of potentially toxic metal(loid)s in resuspended megacity street dust.

The levels of potentially toxic metal(loid)s (PTMs) As, Cu, Co, Cr, Hg, Mn, Ni, Pb, and Zn in resuspended street dust (<100μm particles) from a megacity in north China were determined. The sources of PTMs in resuspended street dust were analyzed using multivariate statistical analysis and positive matrix factorization methods that combined the spatial distributions of PTMs. Average levels of Zn, As, Pb, Cu, Co, and Hg exceeded those found in local soil samples, while those of Cr, Mn, and Ni were less than their background levels found in local soil. The overall contamination of PTMs in resuspended street dust was characterized as moderately contaminated and as uncontaminated to moderately contaminated. The ecological risk associated with Hg was very high, while the ecological risks associated with Cu, Co, Cr, Mn, Ni, Pb, and Zn were low. The overall ecological risk of PTMs was defined as high, driven by Hg. The non-carcinogenic risks of PTMs to inhabitants fell within safety limits, and the carcinogenic risks of As, Co, Cr, and Ni were below receivable values. A comprehensive analysis of PTMs sources revealed that Co, Zn, Cu, and Pb were principally associated with traffic emissions, which accounted for about 38.3% of these PTMs' contents. Mn, Ni, and Cr were mainly generated by natural source, which contributed to about 41.5% of these PTMs' concentrations. Hg and As were primarily derived from coal-related industrial source, which accounted for 77.9% of Hg and 62.9% of As in resuspended street dust. This study demonstrates that coal-related industrial discharges and traffic emissions are the main anthropogenic sources of PTMs contamination in resuspended street dust in the study area.

Source identification of exhaust and non-exhaust traffic emissions through the elemental carbon fractions and Positive Matrix Factorization method

Our study implies the importance of exhaust and non-exhaust emissions in a highway road tunnel, which is crucial to assess their impacts on air quality, human health, climate and developing functional methods for controlling. The total suspended particulates (TSP) and road dust (RD) samples were collected by PUF samplers and manually sweeping, respectively. Campaigns were performed in the summer and winter of 2014 in a highway road tunnel in Bolu, Turkey. Chemical analyses were presented to characterize the contents of organic carbon (OC) fractions (OC1,2,3,4), elemental carbon (EC) fractions (EC1,2,3,4,5,6), polycyclic aromatic hydrocarbons (PAHs) and metals (Al, Ba, Ca, Cu, Mg, Mn, Pb, Sr, Cr and Fe) in the collected TSP and RD samples. Positive matrix factorization (PMF) and orthogonal (Deming) regression analysis were applied to find out the exhaust and non-exhaust vehicle emissions of metal and carbonaceous species in the tunnel. The results showed that the identified source profiles included resuspended road dust (43%), non-exhaust emissions (37%), diesel exhaust emissions (13%), and gasoline exhaust emissions (7%). The relationship between emission markers of metal species and EC carbon fractions was supported by correlation studies. Among these EC fractions, EC4 and EC2 were the most abundant fractions in aerosol and RD samples, respectively and so they highly represented the diesel and non-exhaust emissions. Besides, the EC1 fraction was the indicator of gasoline-fueled emissions. Lower EC1 and higher soot-EC contribution obtained in tunnel aerosol (AS) samples showed the dominance of diesel-fueled vehicles in the tunnel. The data represented herein would help to identify the characteristic of vehicle emissions.

Characterization and sources of trace elements in PM1 during autumn and winter in Qingdao, Northern China

Atmospheric sub-micrometer particles (PM1, particles with an aerodynamic diameter ≤ 1.0 μm) monitoring in Qingdao, a coastal city in Northern China, was conducted for two consecutive years from November 1, 2018 to January 31, 2019 (hereafter referred to as OP2018–2019) and from October 28, 2019 to January 20, 2020 (hereafter referred to as OP2019–2020). The results showed that compared with OP2018–2019, the concentrations of V, Ni, As, Pb, and Cd in PM1 in OP2019–2020 decreased by 61.9%, 31.4%, 49.2%, 25.4%, and 27.1%, respectively. For the indicators of ship emission sources, a significant reduction in V (73.3%) and Ni (22.1%) concentrations were observed after the implementation of the updated Domestic Emission Control Area (DECA 2.0) policy for ships since January 1, 2019 proposed by the Ministry of Transportation. This result demonstrated that the implementation of the DECA 2.0 policy had a significant effect on reducing ship emissions. The Field Emission Scanning Electron Microscope analysis identified the impact of ship emission sources, while the inconsistent distribution of V and Ni revealed other potential sources of Ni. The V/Ni ratios during the pre-policy and post-policy periods decreased by 40.7%. Along with the further implementation of the domestic coastal ship pollution control zone policy, V/Ni ratio should be cautiously used as a parameter for ship emission sources. The positive matrix factorization method identified five source factors: coal combustion/biomass burning (47.8%), crustal sources (21.2%), vehicle exhaust/road dust (15.1%), industrial emissions (11.1%), and ship emissions (4.9%). The contribution rates of ship emission sources before and after the DECA 2.0 policy were analyzed and found to be 5.6% and 3.4%. The potential source contribution factor analysis of As showed that the potential emission source areas were significantly reduced in OP2019–2020, which might be related to the coal fired cleanup operations conducted in Beijing-Tianjin-Hebei and surrounding areas.

Contribution of industrial and traffic emissions to ultrafine, fine, coarse particles in the vicinity of industrial areas in Japan

Atmospheric particulate matter (PM) in industrial areas is typically enriched with potentially toxic trace metals. However, measurements of ultrafine particles (PM0.1) in industrial areas, and the source apportionment of PM0.1 based on these results, are limited. Robust source apportionment studies are therefore necessary in order to identify the source of toxic emissions and to develop measures for reducing such emissions. The present study sought to clarify the contributions to PM mass of ultrafine, fine (PM2.5), and coarse particles (PM10 – PM2.5) in an urban–industrial area with multiple emission sources. We performed both online measurements of PM at a high temporal resolution and size-resolved offline measurements. Source apportionments were then performed for each particle size range by combining a positive matrix factorization method applied to organic aerosol data measured using an aerosol mass spectrometer, a twin-site study, and elemental tracer methods, and then assigning PM mass concentrations to 13 emission sources. The major contributing emission sources for PM0.1 were automobile exhaust (30%) and coal combustion, possibly related to integrated steelworks (24%), in winter, and fuel combustion (39%) and automobile exhaust (11%) in summer. Despite conducting measurements at one of the most heavily polluted traffic intersections in Japan, more than half of the anthropogenic primary emissions of PM0.1 and PM2.5 measured at the intersection were derived from sources other than automobile exhaust emissions. Since PM emissions from stationary-source flue gas has historically been less well regulated than automobile exhaust emissions, further mitigation measures need to be implemented in order to reduce atmospheric PM levels.

Characteristics and source apportionment of volatile organic compounds (VOCs) at a coastal site in Hong Kong

Volatile organic compounds (VOCs) that are emitted from biomass burning, vehicle exhaust, and industrial emissions play a vital role in the formation of ozone (O 3 ) and secondary organic aerosols (SOA). Since VOCs are the precursors of O 3 and aerosol pollution which have become the world's most emergent environmental problems, a field measurement study focused on VOCs was carried out from 27 August to 10 October 2018 in a rural coastal site in Hong Kong. During the campaign, 13 VOC species were detected continuously with proton-transfer-reaction quadrupole mass spectrometry, and their effects on photochemical air pollution were studied. Methanol was the most abundant species among the measured VOCs (average concentration, 3.73 ± 3.26 ppb), and higher concentrations of oxygenated VOCs were found than reported in previous studies of atmospheric chemistry in rural areas. Diurnal variations were observed in the concentrations of various VOC species, indicating that the VOC concentrations were influenced by photochemical reactions. The amount of O 3 formation was estimated based on the maximum incremental reactivity scale of the VOCs. The top five contributors to O 3 formation in Hong Kong (in order) were isoprene (13.46 μg/m 3 ), methyl ethyl ketone (12.74 μg/m 3 ), xylene (8.52 μg/m 3 ), acetaldehyde (8.22 μg/m 3 ), and acrolein (4.32 μg/m 3 ). Receptor model positive matrix factorization (PMF) was used to identify the dominant emission sources and evaluate their corresponding contributions to VOCs. Five major VOC sources were identified with the PMF method, including (1) industry and vehicle-related sources (8.1%), (2) biogenic emissions (5.5%), (3) biomass burning (63.7%), (4) secondary formation (9.2%), and (5) ship-related emissions (13.5%). The source apportionment results from PMF analysis show that the sampling site at the southeastern tip of Hong Kong was strongly influenced by urban plumes from the Guangdong–Hong Kong–Macao Greater Bay Area/Pearl River Delta region and by oceanic emissions. • VOCs concentrations were measured online by PTR-MS during autumn in Hong Kong. • OVOCs were the dominant species with potential for ozone formation. • The largest contributor to ambient VOCs was biomass burning during campaign. • The air pollution in Hong Kong was strongly influenced by urban plumes from GBA/PRD and by oceanic emissions.