Presence of polycyclic aromatic hydrocarbons in sediments and surface water from Shadegan wetland – Iran: A focus on source apportionment, human and ecological risk assessment and Sediment-Water Exchange

Ashayeri, Shirin Yavar; Keshavarzi, Behnam; Moore, Farid; Kersten, Michael; Yazdi, Mohammad; Lahijanzadeh, Ahmad Reza

doi:10.1016/j.ecoenv.2017.11.055

Cited by 84 publications

(37 citation statements)

References 73 publications

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“…PAHs also occur in liquid and solid fossil fuels such as coal, crude oil and refined petroleum products and can therefore also be emitted during their exploration/mining, refining, distribution and storage (Achten and Hofmann, 2009 ; Neff et al, 2005 ). PAHs that are emitted into the atmosphere can undergo long-range transport to distant and pristine ecosystems (such as high mountain areas, the Arctic and Antarctic) that are far from the point sources (Ashayeri et al, 2018 ; De Laender et al, 2011 ; Keyte et al, 2013 ; Li et al, 2020 ). Besides long-range transport, there are also biological sources that can contribute to the PAH concentrations in background soils, albeit at low concentrations (Wilcke, 2007 ).…”

Section: Introductionmentioning

confidence: 99%

Polycyclic aromatic hydrocarbons (PAHs) in soils of an industrial area in semi-arid Uzbekistan: spatial distribution, relationship with trace metals and risk assessment

Bandowe

Shukurov

Leimer

et al. 2021

Environ Geochem Health

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The concentrations, composition patterns, transport and fate of PAHs in semi-arid and arid soils such as in Central Asia are not well known. Such knowledge is required to manage the risk posed by these toxic chemicals to humans and ecosystems in these regions. To fill this knowledge gap, we determined the concentrations of 21 parent PAHs, 4,5-methylenephenanthrene, 6 alkylated PAHs, and biphenyl in soils from 11 sampling locations (0–10, 10–20 cm soil depths) along a 20-km transect downwind from the Almalyk metal mining and metallurgical industrial complex (Almalyk MMC), Uzbekistan. The concentrations of Σ29 PAHs and Σ16 US-EPA PAHs were 41–2670 ng g−1 and 29–1940 ng g−1, respectively. The highest concentration of Σ29 PAHs occurred in the immediate vicinity of the copper smelting factory of the Almalyk MMC. The concentrations in topsoil decreased substantially to a value of ≤ 200 ng g−1 (considered as background concentration) at ≥ 2 km away from the factory. Low molecular weight PAHs dominated the PAH mixtures at less contaminated sites and high molecular weight PAHs at the most contaminated site. The concentration of Σ16 US-EPA PAHs did not exceed the precautionary values set by the soil quality guidelines of, e.g., Switzerland and Germany. Similarly, the benzo[a]pyrene equivalent concentration in soils near the Almalyk MMC did not exceed the value set by the Canadian guidelines for the protection of humans from carcinogenic PAHs in soils. Consequently, the cancer risk due to exposure to PAHs in these soils can be considered as low.

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Section: Introductionmentioning

confidence: 99%

Polycyclic aromatic hydrocarbons (PAHs) in soils of an industrial area in semi-arid Uzbekistan: spatial distribution, relationship with trace metals and risk assessment

Bandowe

Shukurov

Leimer

et al. 2021

Environ Geochem Health

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“…The BaA, Chr, and BaP are commonly used to provide facts about PAHs origin and sources in environmental samples, suggesting excessive loadings of a pyrolytic source [ 40 ]. PC2 revealed 30.6% of the variance and obtained excessive loading for IcdP, BghiP, and DahA, suggesting that the compounds have been released from gas and diesel vehicle emissions [ 42 ]. Eventually, PC3 (13.4% of the variance) was determent by NaP, Ace, Acy, and Flu, recommending that the prevalence of low molecular weight PAHs signifies the petrogenic source [ 22 ].…”

Section: Resultsmentioning

confidence: 99%

Occurrence, Removal, and Mass Balance of Polycyclic Aromatic Hydrocarbons and Their Derivatives in Wastewater Treatment Plants in Northeast China

Mohammed

Zhang

Jiang

et al. 2021

Toxics

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polycyclic aromatic hydrocarbons (PAHs), 33 Methylated PAHs (Me-PAHs), and 14 nitrated PAHs (NPAHs) were measured in wastewater treatment plants (WWTPs) to study the removal efficiency of these compounds through the WWTPs, as well as their source appointment and potential risk in the effluent. The concentrations of ∑PAHs, ∑Me-PAHs, and ∑NPAHs were 2.01–8.91, 23.0–102, and 6.21–171 µg/L in the influent, and 0.17–1.37, 0.06–0.41 and 0.01–2.41 µg/L in the effluent, respectively. Simple Treat 4.0 and meta-regression methods were applied to calculate the removal efficiencies (REs) for the 63 PAHs and their derivatives in 10 WWTPs and the results were compared with the monitoring data. Overall, the ranges of REs were 55.3–95.4% predicated by the Simple Treat and 47.5–97.7% by the meta-regression. The results by diagnostic ratios and principal component analysis PCA showed that “mixed source” biomass, coal composition, and petroleum could be recognized to either petrogenic or pyrogenic sources. The risk assessment of the effluent was also evaluated, indicating that seven carcinogenic PAHs, Benzo[a]pyrene, Dibenz[a,h]anthracene, and Benzo(a)anthracene were major contributors to the toxic carcinogenic equivalents (TEQs) in the effluent of WWTPs, to which attention should be paid.

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“…Generally, PCA's key advantages are (i) its low noise sensitivity, (ii) the decreased requirements for capacity and memory, and (iii) increased efficiency given the processes taking place in a smaller dimensions (Karamizadeh et al, 2013). Other advantages of PCA include: (i) Lack of redundancy of data given the orthogonal components; (ii) Reduced complexity in images' grouping with the use of PCA; (iii) Smaller database representation since only the trainee images are stored in the form of their projections on a reduced basis; (iv) Reduction of noise since the maximum variation basis is chosen and so the small variations in the background are ignored automatically (Phillips et al, 2005;Srinivasulu Asadi et al, 2010); (v) Results cannot be weighted to account for uncertainties in the measured data; (vi) PCA models cannot properly handle missing data or values below the detection limit (both of which commonly occur in environmental measurements); and (vii) MLR analysis of the factor scores was used to quantify source contributions to samples based on pollutants (Larsen & Baker, 2003;Ashayeri et al, 2018). PCA's key disadvantages of PCA are: (i) The covariance matrix is difficult to be evaluated in an accurate manner (Phillips et al, 2005); (ii) Even the simplest invariance could not be captured by the PCA unless the training data explicitly provides this information (Li et al, 2008); and (iii) PCA is not as powerful as other statistical methods in small datasets (Karamizadeh et al, 2013).…”

Section: Comparison Of Statistical Methodsmentioning

confidence: 99%

Source identification of total petroleum hydrocarbons and polycyclic aromatic hydrocarbons in PM10 and street dust of a hot spot for petrochemical production: Asaluyeh County, Iran

Abbasi

Keshavarzi

2019

Sustainable Cities and Society

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Total petroleum hydrocarbons (TPH) and polycyclic aromatic hydrocarbons (PAHs) are important pollutants that affect public health in urban areas, especially in developing and oil-rich countries such as Iran. This assesses the relationship between TPH and PAHs in street dust and suspended dust, and investigates toxicity level in the urban environment of the most important petrochemical center in Iran. For this purpose, 21 and 48 street dust samples were collected for TPH analysis and PAH analysis, respectively, in Asaluyeh County. Moreover, seven air dust samples were taken for PAH analysis. TPH concentrations ranged between 240 and 4400 mg kg −1 , with a mean of 1371.43 mg kg −1 . The maximum ∑PAH concentration (6016.3 mg kg −1 ) was detected in a petrochemical complex while the minimum ∑PAHs content (16.93 mg kg −1 ) was measured in an urban area. The mean concentrations of total PAHs in street dust particles were 491.35 mg kg −1 in summer and 304.04 mg kg −1 in winter. The results indicated that PAH concentration in summer was higher. PAH sources were identified using both PAHs ratios and robust statistical methods such as Generalized Estimating Equations (GEE), backward GEE, logistic regression, principal components analysis (PCA) in conjunction with multiple linear regression (MLR) and positive matrix factorization (PMF). The results showed that PAH species generally originate from pyrogenic sources and about 0.08% of TPH was typically PAHs. However, petrogenic sources of PAHs in the industrial areas were 11.2 times more abundant than in urban areas. Also, backward GEE model demonstrated that TPH is more influenced by HMW PAHs, particularly indene. Estimated incremental lifetime cancer risk (ILCR) was higher than 10 -4 , showing that Asaluyeh inhabitants (especially children and indoor workers) are probably exposed to cancer risk, particularly through dermal contact and dust ingestion.

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Presence of polycyclic aromatic hydrocarbons in sediments and surface water from Shadegan wetland – Iran: A focus on source apportionment, human and ecological risk assessment and Sediment-Water Exchange

Cited by 84 publications

References 73 publications

Polycyclic aromatic hydrocarbons (PAHs) in soils of an industrial area in semi-arid Uzbekistan: spatial distribution, relationship with trace metals and risk assessment

Polycyclic aromatic hydrocarbons (PAHs) in soils of an industrial area in semi-arid Uzbekistan: spatial distribution, relationship with trace metals and risk assessment

Occurrence, Removal, and Mass Balance of Polycyclic Aromatic Hydrocarbons and Their Derivatives in Wastewater Treatment Plants in Northeast China

Source identification of total petroleum hydrocarbons and polycyclic aromatic hydrocarbons in PM10 and street dust of a hot spot for petrochemical production: Asaluyeh County, Iran

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