Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

From 28 November to 23 December 2009, 24-h?PM_2.5 samples were collected simultaneously at six sites in Guangzhou. Concentrations of 18 polycyclic aromatic hydrocarbons (PAHs) together with certain molecular tracers for vehicular emissions (i.e., hopanes and elemental carbon), coal combustion (i.e., picene), and biomass burning (i.e., levoglucosan) were determined. Positive matrix factorization (PMF) receptor model combined with tracer data was applied to explore the source contributions to PAHs. Three sources were identified by both inspecting the dominant tracer(s) in each factor and comparing source profiles derived from PMF with determined profiles in Guangzhou or in the Pearl River Delta region. The three sources identified were vehicular emissions (VE), biomass burning (BB), and coal combustion (CC), accounting for 11?±?2 %, 31?±?4 %, and 58?±?4 % of the total PAHs, respectively. CC replaced VE to become the most important source of PAHs in Guangzhou, reflecting the effective control of VE in recent years. The three sources had different contributions to PAHs with different ring sizes, with higher BB contributions (75?±?3 %) to four-ring PAHs such as pyrene and higher CC contributions (57?±?4 %) to six-ring PAHs such as benzo[ghi]perylene. Temporal variations of VE and CC contributions were probably caused by the change of weather conditions, while temporal variations of BB contributions were additionally influenced by the fluctuation of BB emissions. Source contributions also showed some spatial variations, probably due to the source emission variations near the sampling sites.     

Concentrations and source apportionment of PM10 and associated elemental and ionic species in a lignite-burning power generation area of southern Greece

Ambient concentrations of PM₁₀ and associated elemental and ionic species were measured over the cold and the warm months of 2010 at an urban and two rural sites located in the lignite-fired power generation area of Megalopolis in Peloponnese, southern Greece. The PM₁₀ concentrations at the urban site (44.2?±?33.6 μg m^?3) were significantly higher than those at the rural sites (23.7?±?20.4 and 22.7?±?26.9 μg m^?3). Source apportionment of PM₁₀ and associated components was accomplished by an advanced computational procedure, the robotic chemical mass balance model (RCMB), using chemical profiles for a variety of local fugitive dust sources (power plant fly ash, flue gas desulfurization wet ash, feeding lignite, infertile material from the opencast mines, paved and unpaved road dusts, soil), which were resuspended and sampled through a PM₁₀ inlet onto filters and then chemically analyzed, as well as of other common sources such as vehicular traffic, residential oil combustion, biomass burning, uncontrolled waste burning, marine aerosol, and secondary aerosol formation. Geological dusts (road/soil dust) were found to be major PM₁₀ contributors in both the cold and warm periods of the year, with average annual contribution of 32.6 % at the urban site vs. 22.0 and 29.0 % at the rural sites. Secondary aerosol also appeared to be a significant source, contributing 22.1 % at the urban site in comparison to 30.6 and 28.7 % at the rural sites. At all sites, the contribution of biomass burning was most significant in winter (28.2 % at the urban site vs. 14.6 and 24.6 % at the rural sites), whereas vehicular exhaust contribution appeared to be important mostly in the summer (21.9 % at the urban site vs. 11.5 and 10.5 % at the rural sites). The highest contribution of fly ash (33.2 %) was found at the rural site located to the north of the power plants during wintertime, when winds are favorable. In the warm period, the highest contribution of fly ash was found at the rural site located to the south of the power plants, although it was less important (7.2 %). Moderate contributions of fly ash were found at the urban site (5.4 and 2.7 % in the cold and the warm period, respectively). Finally, the mine field was identified as a minor PM₁₀ source, occasionally contributing with lignite dust and/or deposited wet ash dust under dry summer conditions, with the summertime contributions ranging between 3.1 and 11.0 % among the three sites. The non-parametric bootstrapped potential source contribution function analysis was further applied to localize the regions of sources apportioned by the RCMB. For the majority of sources, source regions appeared as being located within short distances from the sampling sites (within the Peloponnesse Peninsula). More distant Greek areas of the NNE sector also appeared to be source regions for traffic emissions and secondary calcium sulfate dust.     

Polycyclic aromatic hydrocarbon contamination in an urban area assessed by Quercus ilex leaves and soil

We investigated the PAH contamination of Naples urban area, densely populated and with high traffic flow, by analyses of environmental matrices: soil and Quercus ilex leaves. Being some PAHs demonstrated to have hazardous effects on human health, the accumulation of carcinogenic and toxic PAHs (expressed as B(a)Peq) was evaluated in the leaves and soil. The main sources of the PAHs were discriminated by the diagnostic ratios in the two matrices. The urban area appeared heavily contaminated by PAHs, showing in soil and leaves total PAH concentrations also fivefold higher than those from the remote area. The soil mainly accumulated heavy PAHs, whereas leaves the lightest ones. Median values of carcinogenic PAH concentrations were higher in soil (440 ng g^?1 d.w.) and leaves (340 ng g^?1 d.w.) from the urban than the remote area (60 and 70 ng g^?1 d.w., respectively, for soil and leaves). Also, median B(a)Peq concentrations were higher both in soil and leaves from the urban (137 and 63 ng g^?1 d.w., respectively) than those from the remote area (19 and 49 ng g^?1 d.w., respectively). Different from the soils, the diagnostic ratios found for the leaves discerned PAH sources in the remote and urban areas, highlighting a great contribution of vehicular traffic emission as main PAH source in the urban area.     

PAH air pollution at a Portuguese urban area: carcinogenic risks and sources identification

This study aimed to characterize air pollution and the associated carcinogenic risks of polycyclic aromatic hydrocarbon (PAHs) at an urban site, to identify possible emission sources of PAHs using several statistical methodologies, and to analyze the influence of other air pollutants and meteorological variables on PAH concentrations.The air quality and meteorological data were collected in Oporto, the second largest city of Portugal. Eighteen PAHs (the 16 PAHs considered by United States Environment Protection Agency (USEPA) as priority pollutants, dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were collected daily for 24 h in air (gas phase and in particles) during 40 consecutive days in November and December 2008 by constant low-flow samplers and using polytetrafluoroethylene (PTFE) membrane filters for particulate (PM₁₀ and PM_2.5 bound) PAHs and pre-cleaned polyurethane foam plugs for gaseous compounds. The other monitored air pollutants were SO₂, PM₁₀, NO₂, CO, and O₃; the meteorological variables were temperature, relative humidity, wind speed, total precipitation, and solar radiation. Benzo[a]pyrene reached a mean concentration of 2.02 ng?m^?3, surpassing the EU annual limit value. The target carcinogenic risks were equal than the health-based guideline level set by USEPA (10^?6) at the studied site, with the cancer risks of eight PAHs reaching senior levels of 9.98?×?10^?7 in PM₁₀ and 1.06?×?10^?6 in air. The applied statistical methods, correlation matrix, cluster analysis, and principal component analysis, were in agreement in the grouping of the PAHs. The groups were formed according to their chemical structure (number of rings), phase distribution, and emission sources. PAH diagnostic ratios were also calculated to evaluate the main emission sources. Diesel vehicular emissions were the major source of PAHs at the studied site. Besides that source, emissions from residential heating and oil refinery were identified to contribute to PAH levels at the respective area. Additionally, principal component regression indicated that SO₂, NO₂, PM₁₀, CO, and solar radiation had positive correlation with PAHs concentrations, while O₃, temperature, relative humidity, and wind speed were negatively correlated.     

Source diagnostics of polycyclic aromatic hydrocarbons in urban road runoff, dust, rain and canopy throughfall

Diagnostic ratios and multivariate analysis were utilized to apportion polycyclic aromatic hydrocarbon (PAH) sources for road runoff, road dust, rain and canopy throughfall based on samples collected in an urban area of Beijing, China. Three sampling sites representing vehicle lane, bicycle lane and branch road were selected. For road runoff and road dust, vehicular emission and coal combustion were identified as major sources, and the source contributions varied among the sampling sites. For rain, three principal components were apportioned representing coal/oil combustion (54%), vehicular emission (34%) and coking (12%). For canopy throughfall, vehicular emission (56%), coal combustion (30%) and oil combustion (14%) were identified as major sources. Overall, the PAH's source for road runoff mainly reflected that for road dust. Despite site-specific sources, the findings at the study area provided a general picture of PAHs sources for the road runoff system in urban area of Beijing.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

Source apportionment of PAHs and n-alkanes in respirable particles in Tehran,Iran by wind sector and vertical profile

The vertical concentration profiles and source contributions of polycyclic aromatic hydrocarbons (PAHs) and n-alkanes in respirable particle samples (PM₄) collected at 10, 100, 200 and 300-m altitude from the Milad Tower of Tehran, Iran during fall and winter were investigated. The average concentrations of total PAHs and total n-alkanes were 16.7 and 591 ng/m³, respectively. The positive matrix factorization (PMF) model was applied to the chemical composition and wind data to apportion the contributing sources. The five PAH source factors identified were: ‘diesel’ (56.3 % of total PAHs on average), ‘gasoline’ (15.5 %), ‘wood combustion, and incineration’ (13 %), ‘industry’ (9.2 %), and ‘road soil particle’ (6.0 %). The four n-alkane source factors identified were: ‘petrogenic’ (65 % of total n-alkanes on average), ‘mixture of petrogenic and biomass burning’ (15 %), ‘mixture of biogenic and fossil fuel’ (11.5 %), and ‘biogenic’ (8.5 %). Source contributions by wind sector were also estimated based on the wind sector factor loadings from PMF analysis. Directional dependence of sources was investigated using the conditional probability function (CPF) and directional relative strength (DRS) methods. The calm wind period was found to contribute to 4.4 % of total PAHs and 5.0 % of total n-alkanes on average. Highest average concentrations of PAHs and n-alkanes were found in the 10 and 100 m samples, reflecting the importance of contributions from local sources. Higher average concentrations in the 300 m samples compared to those in the 200 m samples may indicate contributions from long-range transport. The vertical profiles of source factors indicate the gasoline and road soil particle-associated PAHs, and the mixture from biogenic and fossil fuel source-associated n-alkanes were mostly from local emissions. The smaller average contribution of diesel-associated PAHs in the lower altitude samples also indicates that the restriction of diesel-fueled vehicle use in the central area of Tehran has been effective in reducing the PAHs concentration.     

Spatial distribution,potential risk assessment,and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in sediments of Lake Chaohu,China

Twenty-nine sediment samples were collected from Lake Chaohu, a shallow eutrophic lake in Eastern China, and were analyzed for 15 priority polycyclic aromatic hydrocarbons (PAHs) to determine the spatial distribution and exposure risks of PAHs. Three receptor models, the principal component analysis-multiple linear regression (PCA-MLR) model, the positive matrix factorization (PMF) model, and the Unmix model, were used in combination with the PAHs diagnostic ratios to investigate the potential source apportionment of PAHs. A clear gradient in the spatial distribution and the potential toxicity of PAHs was observed from west to east in the sediments of Lake Chaohu. ∑₁₅PAH concentrations and the TEQ were in the range of 80.82-30 365.01 ng g^?1 d.w. and 40.77-614.03, respectively. The highest values of the aforementioned variables were attributed to urban–industrial pollution sources in the west lake region, and the levels decreased away from the river inlets. The three different models yielded excellent correlation coefficients between the predicted and measured levels of the 15 PAH compounds. Similarly, source apportionment results were derived from the three receptor models and the PAH diagnostic ratios, suggesting that the highest contribution to the PAHs was from coal combustion and wood combustion, followed by vehicular emissions. The PMF model yielded the following contributions to the PAHs from gasoline combustion, diesel combustion, unburned petroleum emissions, and wood combustion: 34.49, 24.61, 16.11, 13.01, and 11.78 %, respectively. The PMF model produced more detailed source apportionment results for the PAHs than the PCA-MLR and Unmix models.     

Risk assessment of inhalation exposure to polycyclic aromatic hydrocarbons in school children

Polycyclic aromatic hydrocarbons (PAHs) associated with the inhalable fraction of particulate matter were determined for 1 year (2009–2010) at a school site located in proximity of industrial and heavy traffic roads in Delhi, India. PM₁₀ (aerodynamic diameter ≤10 μm) levels were ～11.6 times the World Health Organization standard. Vehicular (59.5 %) and coal combustion (40.5 %) sources accounted for the high levels of PAHs (range 38.1–217.3 ng m^?3) with four- and five-ring PAHs having ～80 % contribution. Total PAHs were dominated by carcinogenic species (～75 %) and B[a]P equivalent concentrations indicated highest exposure risks during winter. Extremely high daily inhalation exposure of PAHs was observed during winter (439.43 ng day^?1) followed by monsoon (232.59 ng day^?1) and summer (171.08 ng day^?1). Daily inhalation exposure of PAHs to school children during a day exhibited the trend school hours?>?commuting to school?>?resting period in all the seasons. Vehicular source contributions to daily PAH levels were significantly correlated (r?=?0.94, p?<?0.001) with the daily inhalation exposure level of school children. A conservative estimate of ～11 excess cancer cases in children during childhood due to inhalation exposure of PAHs has been made for Delhi.     

Identification and source apportionment of polycyclic aromatic hydrocarbons in ambient air particulate matter of Riyadh, Saudi Arabia

In an effort to assess the occurrence and sources of polycyclic aromatic hydrocarbons (PAHs) in the ambient air of Riyadh, Saudi Arabia, PM₁₀ samples were collected during December 2010. Diagnostic PAH concentration ratios were used as a tool to identify and characterize the PAH sources. The results reflect high PM₁₀ and PAH concentrations (particulate matter (PM)?=?270–1,270 μg/m³). The corresponding average PAH concentrations were in the range of 18?±?8 to 1,003?±?597 ng/m³ and the total concentrations (total PAHs (TPAHs) of 17 compounds) varied from 1,383 to 13,470 ng/m³ with an average of 5,871?±?2,830 ng/m³. The detection and quantification limits were 1–3 and 1–10 ng/ml, respectively, with a recovery range of 42–80 %. The ratio of the sum of the concentrations of the nine major non-alkylated compounds to the total (CPAHs/TPAHs) was 0.87?±?0.10, and other ratios were determined to apportion the PM sources. The PAHs found are characteristic for emissions from traffic with diesel being a predominant source.     

Potential source apportionment of polycyclic aromatic hydrocarbons in surface sediments from the middle and lower reaches of the Yellow River,China

In this work, principal component analysis/multiple linear regression (PCA/MLR), positive matrix factorization (PMF), and UNMIX model were employed to apportion potential sources of polycyclic aromatic hydrocarbons (PAHs) in surface sediments from middle and lower reaches of the Yellow River, based on the measured PAHs concentrations in sediments collected from 22 sites in November 2005. The results suggested that pyrogenic sources were major sources of PAHs. Further analysis indicated that source contributions of PAHs compared well among PCA/MLR, PMF, and UNMIX. Vehicles contributed 25.1–36.7 %, coal 34.0–41.6 %, and biomass burning and coke oven 29.2–33.2 % of the total PAHs, respectively. Coal combustion and traffic-related pollution contributed approximately 70 % of anthropogenic PAHs to sediments, which demonstrated that energy consumption was a predominant factor of PAH pollution in middle and lower reaches of the Yellow River. In addition, the distributions of contribution for each identified source category were studied, which showed similar distributed patterns for each source category among the sampling sites.     

Temporal variation of volatile organic compounds and their major emission sources in Seoul, Korea

This study examines the characteristics of volatile organic compounds (VOCs) and their major emission sources at the Bulgwang site in Seoul, Korea. The annual levels of VOCs (96.2–121.1 ppb C) have shown a decreasing trend from 2004 to 2008. The most abundant component in Seoul was toluene, which accounted for over 23.5 % of the total VOCs on the parts per billion on a carbon basis, and the portions of alkanes with two to six carbons constituted the largest major lumped group, ranging from 40.1 to 48.4 % (45.3?±?3.7 %) of the total VOCs. Major components of the solvent (toluene, m/p-xylene, o-xylene, and ethylbenzene) showed high in daytime and summer and low in nighttime and winter due mainly to the variation of the ambient temperature. The species mostly emitted from gasoline vapor (i/n-butane, i/n-pentane, n-hexane, and 2-methylpentane) and vehicular exhaust (ethylene, acetylene, and benzene) showed bimodal peaks in the diurnal variation around the commuting hours because of the high traffic volume. For the 14 out of 15 highest concentration species, the weekend effect was only evident on Sundays because of the stepwise implementation of the 5-day work-week system. Principal components analysis (PCA) was applied in order to identify the sources of the 15 highest concentration VOCs and, as a result, three principal components such as gasoline vapor (48.9 %), vehicular exhaust (17.9 %), and evaporation of solvents (9.8 %) were obtained to explain a total of 76.6 % of the data variance. Most influential contributing sources at the sampling site were traffic-related ones although the use of solvent was the dominant emission source based on the official emission inventory.     

Characterization and concentrations of polycyclic aromatic hydrocarbons in emissions from different heating systems in Damascus,Syria

Traffic has long been recognized as the major contributor to polycyclic aromatic hydrocarbon (PAH) emissions to the urban atmosphere. Stationary combustion sources, including residential space heating systems, are also a major contributor to PAH emissions. The aim of this study was to determine the profile and concentration of PAHs in stack flue gas emissions from different kinds of space heaters in order to increase the understanding of the scale of the PAH pollution problem caused by this source. This study set out to first assess the characteristics of PAHs and their corresponding benzo[a]pyrene equivalent emissions from a few types of domestic heaters and central heating systems to the urban atmosphere. The study, enabled for the first time, the characterization of PAHs in stationary combustion sources in the city of Damascus, Syria. Nine different types of heating systems were selected with respect to age, design, and type of fuel burned. The concentrations of 15 individual PAH compounds in the stack flue gas were determined in the extracts of the collected samples using high-performance liquid chromatography system (HPLC) equipped with ultraviolet–visible and fluorescence detectors. In general, older domestic wood stoves caused considerably higher PAH emissions than modern domestic heaters burning diesel oil. The average concentration of ΣPAH (sum of 15 compounds) in emissions from all types of studied heating systems ranged between 43?±?0.4 and 316?±?1.4 μg/m³. Values of total benzo[a]pyrene equivalent ranged between 0.61 and 15.41 μg/m³.     

Identification of sources affecting fog formation using receptor modeling approaches and inventory estimates of sectoral emissions

Positive matrix factorization (PMF) was used to identify factors affecting fog formation in Kanpur during the ISRO-GBP land campaign-II (LC-II) in December 2004. PMF predicted factors were validated by contrasting the emission strength of sources in the foggy and clear periods, using a combination of potential source contribution function (PSCF) analysis and quantitative emission inventory information. A time series aerosol chemical data set of 29 days and 12 species was decomposed to identify 4-factors: Secondary species, Biomass burning, Dust and Sea salt. PMF predicted particle mass with a satisfactory goodness-of-fit (slope of 0.83 ± 0.17 and R² of 0.8), and strong species within 11–12% relative standard deviation. Mean contributions of anthropogenic factors were significantly higher during the foggy period for secondary species (2.9 ± 0.3) and biomass burning (1.2 ± 0.09) compared to the clear period. Local sources contributing to aerosols that mediated fog events at Kanpur, based on emissions in a 200 km × 200 km area around Kanpur city were thermal power plants and transportation (SO₂) and biofuel combustion (BC and OM). Regional scale sources influencing emissions during the foggy period, in probable source regions identified by PSCF included thermal power plants, transportation, brick kilns and biofuel combustion. While biofuel combustion and transportation are distributed area sources, individual point sources include coal-fired thermal power plants located in Aligarh, Delhi, Ghaziabad, Jhansi, Kanpur, Rae Bareli and Rupnagar and brick kilns located in Allahabad, Agra, Farrukhabad, Ghaziabad, Kanpur, Ludhiana, Lucknow and Rae Bareli. Additionally, in the foggy period, large areas of probable source regions lay outside India, implying the significance of aerosol incursion from outside India.     

Source,distribution, and health risk assessment of polycyclic aromatic hydrocarbons in urban street dust from Tianjin,China

To better assess and understand potential health risk of urban residents exposed to urban street dust, the total concentration, sources, and distribution of 16 polycyclic aromatic hydrocarbons (PAHs) in 87 urban street dust samples from Tianjin as a Chinese megacity that has undergone rapid urbanization were investigated. In the meantime, potential sources of PAHs were identified using the principal component analysis (PCA), and the risk of residents’ exposure to PAHs via urban street dust was calculated using the Incremental Lifetime Cancer Risk (ILCR) model. The results showed that the total PAHs (∑PAHs) in urban street dust from Tianjin ranged from 538 μg kg^?1 to 34.3 mg kg^?1, averaging 7.99 mg kg^?1. According to PCA, the two to three- and four to six-ring PAHs contributed 10.3 and 89.7 % of ∑PAHs, respectively. The ratio of the sum of major combustion specific compounds (ΣCOMB)?/?∑PAHs varied from 0.57 to 0.79, averaging 0.64. The ratio of Ant/(Ant?+?Phe) varied from 0.05 to 0.41, averaging 0.10; Fla/(Fla?+?Pyr) from 0.40 to 0.68, averaging 0.60; BaA/(BaA?+?Chry) from 0.29 to 0.51, averaging 0.38; and IcdP/(IcdP?+?BghiP) from 0.07 to 0.37, averaging 0.22. The biomass combustion, coal combustion, and traffic emission were the main sources of PAHs in urban street dust with the similar proportion. According to the ILCR model, the total cancer risk for children and adults was up to 2.55?×?10^?5 and 9.33?×?10^?5, respectively.     

Source apportionment and location by selective wind sampling and Positive Matrix Factorization

In order to determine the pollution sources in a suburban area and identify the main direction of their origin, PM_2.5 was collected with samplers coupled with a wind select sensor and then subjected to Positive Matrix Factorization (PMF) analysis. In each sample, soluble ions, organic carbon, elemental carbon, levoglucosan, metals, and Polycyclic Aromatic Hydrocarbons (PAHs) were determined. PMF results identified six main sources affecting the area: natural gas home appliances, motor vehicles, regional transport, biomass combustion, manufacturing activities, and secondary aerosol. The connection of factor temporal trends with other parameters (i.e., temperature, PM_2.5 concentration, and photochemical processes) confirms factor attributions. PMF analysis indicated that the main source of PM_2.5 in the area is secondary aerosol. This should be mainly due to regional contributions, owing to both the secondary nature of the source itself and the higher concentration registered in inland air masses. The motor vehicle emission source contribution is also important. This source likely has a prevalent local origin. The most toxic determined components, i.e., PAHs, Cd, Pb, and Ni, are mainly due to vehicular traffic. Even if this is not the main source in the study area, it is the one of greatest concern. The application of PMF analysis to PM_2.5 collected with this new sampling technique made it possible to obtain more detailed results on the sources affecting the area compared to a classical PMF analysis.     

Characterization, sources, and potential risk assessment of PAHs in surface sediments from nearshore and farther shore zones of the Yangtze estuary, China

The assessment of polycyclic aromatic hydrocarbons (PAHs) contamination in surface sediments from the Yangtze estuary which is a representative area affected by anthropogenic activity (rapid industrialization, high-population density, and construction of dams upstream) in the world was systematically conducted. Fifty-one samples were analyzed by high-performance liquid chromatography (HPLC). The ??PAHs in all sediments varied from 76.9 to 2,936.8?ng?g^?1. Compared with other estuaries in the world, the PAH levels in the Yangtze estuary are low to moderate. Phenanthrene, acenaphthylene, fluoranthene, and pyrene were relatively abundant. The ??PAH levels and composition varied obviously in different estuarine zones due to different sources. The highest ??PAHs concentration was observed in the nearshore of Chongming Island. The PAH composition showed that four to six ring PAHs were mainly found in the nearshore areas, while two to three ring PAHs were in the farther shore zones. The PAHs in the Yangtze estuary were derived primarily from combustion sources. A mixture of petroleum combustion and biomass combustion mainly from coal combustion and vehicle emission was the main source of PAHs from the nearshore areas, while the spill, volatilization, or combustion of petroleum from shipping process and shoreside discharge were important for PAHs in the farther shore areas. The result of potential ecotoxicological risk assessment based on sediment quality guidelines indicated low PAH ecological risk in the Yangtze estuary. The study could provide foundation for the protection of water quality of the Yangtze estuary by inducing main sources input.     

Studies on polycyclic aromatic hydrocarbons in two sediment cores from the huaxi reservoir,china: Assessment of levels,sources, and ecological risk

This study investigated the levels, sources and ecological risks of 16 polycyclic aromatic hydrocarbons (PAHs) in two sediment cores that were collected along the Huaxi Reservoir. The spatial distributions and residue levels of the 16 priority PAHs in the sediments from the Huaxi Reservoir were analyzed for their potential ecological risk, source apportionment and contribution to the total PAH residue. The concentration level of the total PAHs (TPAHs) was in the range 1805 ng·g^?1 to 20023 ng·g^?1 based on dry weight, and the content of PAHs in the Huaxi Reservoir exhibited a gradual upward trend. The PAH congener ratios fluoranthene/(fluoranthene + pyrene) and indeno[1, 2, 3-cd]pyrene/(indeno[1, 2, 3-cd]pyrene + benzo[g, h, i]perylene) were used to identify the source. The main source of the low molecular weight PAHs was wood and coal combustion, whereas the high molecular weight PAHs were primarily from petroleum combustion sources. The results of an ecological risk assessment demonstrated that ACE poses a potential ecological risk, while FLU, NAP, ANT, BaP, DBA, PHEN and PYR can have serious ecological risks.     

Atmospheric concentrations,gaseous–particulate distribution,and carcinogenic potential of polycyclic aromatic hydrocarbons in Assiut,Egypt

The concentrations of 15 priority PAHs were determined in the atmospheric gaseous and particulate phases from nine sites across Assiut City, Egypt. While naphthalene, acenaphthene, and fluorene were the most abundant in the gaseous phase with average concentrations of 377, 184, and 181 ng/m³, benzo[b]fluoranthene, chrysene, and benzo[g,h,i]perylene showed the highest levels in the particulate phase with average concentrations of 76, 6, and 52 ng/m³. The average total atmospheric concentration of target PAHs (1,590 ng/m³) indicates that Assiut is one of the highest PAH-contaminated areas in the world. Statistical analysis revealed a significant difference between the levels of PAHs in the atmosphere of urban and suburban sites (P?=?0.029 and 0.043 for gaseous and particulate phases, respectively). Investigation of diagnostic PAH concentration ratios revealed vehicular combustion and traffic exhaust emissions as the major sources of PAHs with a higher contribution of gasoline rather than diesel vehicles in the sampled areas. Benzo[a]pyrene has the highest contribution (average?=?32, 4 % for gaseous and particulate phases) to the total carcinogenic activity (TCA) of atmospheric PAHs. While particulate phase PAHs have higher contribution to the TCA, gaseous phase PAHs present at higher concentrations in the atmosphere are more capable of undergoing atmospheric reactions to form more toxic derivatives.     

Source apportionment of polycyclic aromatic hydrocarbons in surface sediments of the Bohai Sea, China

A total of 112 surface sediment samples covering virtually the entire Bohai Sea were analyzed for polycyclic aromatic hydrocarbons (PAHs), in order to provide the extensive information of recent occurrence levels, distribution, possible sources, and potential biological risk of these compounds in this area. Surface sediment samples were collected from the Bohai Sea using a stainless steel grab sampler. Sixteen PAHs were determined by a Finnigan TRACE DSQ gas chromatography/mass spectrometry. Diagnostic ratios, cluster analysis, and principal component analysis (PCA) with multivariate linear regression (MLR) were performed to identify and quantitatively apportion the major sources of sedimentary PAHs in the Bohai Sea. Concentrations of total PAHs in the Bohai Sea ranged widely from 97.2 to 300.7 ng/g (mean, 175.7?±?37.3 ng/g). High concentrations of PAHs were found in the vicinity of Luan River Estuary-Qinhuangdao Harbor, Cao River Estuary-Bohai Sea Center, and north of the Yellow River Estuary. The three-ring PAHs were most abundant, accounting for about 37?±?5 % of total PAHs. The four-ring and five-ring PAHs were the next dominant ones comprising approximately 29?±?7and 23?±?3 % of total PAHs, respectively. Concentrations of acenaphthylene, acenaphthene, and dibenz[a,h]anthracene are higher than Canadian interim marine sediment quality guideline values at most of the sites in the study area. Contamination levels of PAHs in the Bohai Sea were low in comparison with other coastal sediments in China and developed countries. The distribution pattern of PAHs and source identification implied that PAH contamination in the Bohai Sea mainly originates from petrogenic and pyrogenic sources. Further PCA/MLR analysis suggested that the contributions of spilled oil products (petrogenic), coal combustion, and traffic-related pollution were 39, 38, and 23 %, respectively. Pyrogenic sources (coal combustion and traffic-related pollution) contributed 61 % of anthropogenic PAHs to sediments, which indicates that energy consumption could be a dominant factor in PAH pollution in this area. Acenaphthylene, acenaphthene, and dibenz[a,h]anthracene are the three main species of PAHs with more ecotoxicological concern in the Bohai Sea.