scholarly journals Application of Binary Diagnostic Ratios of Polycyclic Aromatic Hydrocarbons for Identification of Tsunami 2004 Backwash Sediments in Khao Lak, Thailand

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Siwatt Pongpiachan
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Marine Sediments ◽  
Aromatic Hydrocarbons ◽  
Organic Molecules ◽  
Three Dimensional ◽  
Diagnostic Ratios ◽  
Tsunami Deposit ◽  
Tsunami Deposits ◽  
Sedimentary Characteristics ◽  
Polycyclic Aromatic

Identification of Tsunami deposits has long been a controversial issue among geologists. Although there are many identification criteria based on the sedimentary characteristics of unequivocal Tsunami deposits, the concept still remains ambiguous. Apart from relying on some conventional geological, sedimentological, and geoscientific records, geologists need some alternative “proxies” to identify the existence of Tsunami backwash in core sediments. Polycyclic aromatic hydrocarbons (PAHs) are a class of very stable organic molecules, which can usually be presented as complex mixtures of several hundred congeners; one can assume that the “Tsunami backwash deposits” possess different fingerprints of PAHs apart from those of “typical marine sediments.” In this study, three-dimensional plots of PAH binary ratios successfully identify the Tsunami backwash deposits in comparison with those of global marine sediments. The applications of binary ratios of PAHs coupled with HCA are the basis for developing site-specific Tsunami deposit identification criteria that can be applied in paleotsunami deposits investigations.

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

Toxics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 76
Author(s):  
Rashid Mohammed ◽  
Zi-Feng Zhang ◽  
Chao Jiang ◽  
Ying-Hua Hu ◽  
Li-Yan Liu ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Wastewater Treatment Plants ◽  
Principal Component ◽  
Diagnostic Ratios ◽  
Regression Methods ◽  
Polycyclic Aromatic ◽  
Meta Regression ◽  
Coal Composition

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 toxics equivalency concentrations (TEQs) in the effluent of WWTPs, to which attention should be paid.

scholarly journals The General (α,3)-Path Connectivity Indices of Polycyclic Aromatic Hydrocarbons

2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Haiying Wang ◽  
Chuantao Li
Keyword(s):  
Applied Sciences ◽  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Molecular Graph ◽  
Three Dimensional ◽  
3D Qsar ◽  
Medical Sciences ◽  
Connectivity Indices ◽  
Polycyclic Aromatic ◽  
Extremal Values

The general (α,t)-path connectivity index of a molecular graph originates from many practical problems such as three-dimensional quantitative structure-activity (3D QSAR) and molecular chirality. It is defined as Rtα(G)=∑Pt=vi1vi2⋯vit+1⊆G[d(vi1)d(vi2)⋯d(vit+1)]α, where the summation is taken over all possible paths of length t of G and we do not distinguish between the paths vi1vi2⋯vit+1 and vit+1⋯vi2vi1. In this paper, we focus on the structures of Polycyclic Aromatic Hydrocarbons (PAHn), which play a role in organic materials and medical sciences. We try to compute the exact general (α,3)-path connectivity indices of this family of hydrocarbon structures. Furthermore, we exactly derive the monotonicity and the extremal values of R3α(PAHn) for any real number α. These valuable results could produce strong guiding significance to these applied sciences.

Ultrasonic micellar extraction of polycyclic aromatic hydrocarbons from marine sediments

Talanta ◽  
2001 ◽  
Vol 54 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Verónica Pino ◽  
Juan H. Ayala ◽  
Ana M. Afonso ◽  
Venerando González
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Marine Sediments ◽  
Aromatic Hydrocarbons ◽  
Micellar Extraction ◽  
Polycyclic Aromatic

scholarly journals Polycyclic Aromatic Hydrocarbons in PM2.5 and PM2.5–10 in Urumqi, China: Temporal Variations, Health Risk, and Sources

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 412 ◽  
Author(s):  
Suwubinuer Rekefu ◽  
Dilinuer Talifu ◽  
Bo Gao ◽  
Yusan Turap ◽  
Mailikezhati Maihemuti ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Coal Combustion ◽  
Temporal Variations ◽  
Diagnostic Ratios ◽  
Positive Matrix ◽  
Increasing Trend ◽  
Polycyclic Aromatic ◽  
The Mean

PM2.5 and PM2.5–10 samples were simultaneously collected in Urumqi from January to December 2011, and 14 priority polycyclic aromatic hydrocarbons (PAHs) were determined. The mean concentrations of total PAHs in PM2.5 and PM2.5–10 were 20.90~844.22 ng m−3 and 19.65~176.5 ng m−3 respectively, with the highest in winter and the lowest in summer. Above 80% of PAHs were enriched in PM2.5, which showed remarkable seasonal variations compared to coarse particles. High molecular weight (HMW) PAHs were predominant in PM2.5 (46.61~85.13%), whereas the proportions of lower molecular weight (LMW) and HMW PAHs in PM2.5–10 showed a decreasing and an increasing trend, respectively, from spring to winter. The estimated concentrations of benzo[a]pyrene equivalent carcinogenic potency (BaPeq) in PM2.5 (10.49~84.52 ng m−3) were higher than that of in PM2.5–10 (1.15~13.33 ng m−3) except in summer. The estimated value of inhalation cancer risk in PM2.5 and PM2.5–10 were 1.63 × 10−4~7.35 × 10−3 and 9.94 × 10−5~1.16 × 10−3, respectively, far exceeding the health-based guideline level of 10−4. Diagnostic ratios and positive matrix factorization results demonstrated that PAHs in PM2.5 and PM2.5–10 were from similar sources, such as coal combustion, biomass burning, coking, and petroleum combustion, respectively. Coal combustion was the most important source for PAHs both in PM2.5 and PM2.5–10, accounting for 54.20% and 50.29%, respectively.

scholarly journals Variability of polycyclic aromatic hydrocarbons and their oxidative derivatives in wintertime Beijing, China

2019 ◽  
Vol 19 (13) ◽  
pp. 8741-8758 ◽  
Author(s):  
Atallah Elzein ◽  
Rachel E. Dunmore ◽  
Martyn W. Ward ◽  
Jacqueline F. Hamilton ◽  
Alastair C. Lewis
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Gas Phase ◽  
Aromatic Hydrocarbons ◽  
Total Concentration ◽  
Diagnostic Ratios ◽  
Strong Positive Correlation ◽  
Night Time ◽  
Naphthalic Anhydride ◽  
Positive Correlation ◽  
Polycyclic Aromatic

Abstract. Ambient particulate matter (PM) can contain a mix of different toxic species derived from a wide variety of sources. This study quantifies the diurnal variation and nocturnal abundance of 16 polycyclic aromatic hydrocarbons (PAHs), 10 oxygenated PAHs (OPAHs) and 9 nitrated PAHs (NPAHs) in ambient PM in central Beijing during winter. Target compounds were identified and quantified using gas chromatography–time-of-flight mass spectrometry (GC-Q-ToF-MS). The total concentration of PAHs varied between 18 and 297 ng m−3 over 3 h daytime filter samples and from 23 to 165 ng m−3 in 15 h night-time samples. The total concentrations of PAHs over 24 h varied between 37 and 180 ng m−3 (mean: 97±43 ng m−3). The total daytime concentrations during high particulate loading conditions for PAHs, OPAHs and NPAHs were 224, 54 and 2.3 ng m−3, respectively. The most abundant PAHs were fluoranthene (33 ng m−3), chrysene (27 ng m−3), pyrene (27 ng m−3), benzo[a]pyrene (27 ng m−3), benzo[b]fluoranthene (25 ng m−3), benzo[a]anthracene (20 ng m−3) and phenanthrene (18 ng m−3). The most abundant OPAHs were 9,10-anthraquinone (18 ng m−3), 1,8-naphthalic anhydride (14 ng m−3) and 9-fluorenone (12 ng m−3), and the three most abundant NPAHs were 9-nitroanthracene (0.84 ng m−3), 3-nitrofluoranthene (0.78 ng m−3) and 3-nitrodibenzofuran (0.45 ng m−3). ∑PAHs and ∑OPAHs showed a strong positive correlation with the gas-phase abundance of NO, CO, SO2 and HONO, indicating that PAHs and OPAHs can be associated with both local and regional emissions. Diagnostic ratios suggested emissions from traffic road and coal combustion were the predominant sources of PAHs in Beijing and also revealed the main source of NPAHs to be secondary photochemical formation rather than primary emissions. PM2.5 and NPAHs showed a strong correlation with gas-phase HONO. 9-Nitroanthracene appeared to undergo a photodegradation during the daytime and showed a strong positive correlation with ambient HONO (R=0.90, P < 0.001). The lifetime excess lung cancer risk for those species that have available toxicological data (16 PAHs, 1 OPAH and 6 NPAHs) was calculated to be in the range 10−5 to 10−3 (risk per million people ranges from 26 to 2053 cases per year).

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