Polycyclic aromatic hydrocarbons in particulate matter emitted from coke oven battery

Kozielska, Barbara; Konieczyński, Jan

doi:10.1016/j.fuel.2014.12.069

Cited by 20 publications

(15 citation statements)

References 43 publications

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“…The residual doubts were removed by computing the values of diagnostic ratios (proportions of particular PAH concentrations [8,20,[22][23][24][25][26]), which matched the values of such ratios for PAHs from coal combustion and coking ( Table 2).…”

Section: Resultsmentioning

confidence: 99%

PAH Concentrations Inside a Wood Processing Plant and the Indoor Effects of Outdoor Industrial Emissions

Rogula-Kopiec

Rogula–Kozłowska

Kozielska³

et al. 2015

Pol. J. Environ. Stud.

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Section: Resultsmentioning

confidence: 99%

PAH Concentrations Inside a Wood Processing Plant and the Indoor Effects of Outdoor Industrial Emissions

Rogula-Kopiec

Rogula–Kozłowska

Kozielska³

et al. 2015

Pol. J. Environ. Stud.

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“…PM from anthropogenic sources include particles from so-called municipal emissions (mainly soot, organic matter, and inorganic salts resulting from the combustion of coal and biomass in domestic furnaces, local coal-fired boiler plants, or heat plants [20,[60][61][62]) and from industrial emissions (mainly fine particles enriched in heavy metals or persistent organic pollutants [63][64][65][66][67][68]). In addition, particles of salt, sand (coarse PM), or a mixture of both are released into the urban atmosphere, especially during the winter season [9,25,35,40,69].…”

Section: Introductionmentioning

confidence: 99%

Particulate Matter from the Road Surface Abrasion as a Problem of Non-Exhaust Emission Control

2018

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Along with house heating and industry, emissions from road traffic (exhaust and tire, brake, car body or road surface abrasions) are one of the primary sources of particulate matter (PM) in the atmosphere in urban areas. Though numerous regulations and vehicle-control mechanisms have led to a significant decline of PM emissions from vehicle exhaust gases, other sources of PM remain related to road and car abrasion are responsible for non-exhaust emissions. Quantifying these emissions is a hard problem in both laboratory and field conditions. First, we must recognize the physicochemical properties of the PM that is emitted by various non-exhaust sources. In this paper, we underline the problem of information accessibility with regards to the properties and qualities of PM from non-exhaust sources. We also indicate why scarce information is available in order to find the possible solution to this ongoing issue.

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“…PAHs occur due to incomplete combustion of organic matter, such as wood, coal or oil. In addition to natural sources of PAHs in the environment, like forest fires [30,31] and volcanic eruptions [32], there are numerous anthropogenic sources, such as coke oven emissions [33,34], combustion of fossil fuels [35] and vehicle exhausts [36]. Furthermore, benzo(a)pyrene and fluoranthene are detected in many different products.…”

Section: Data and Data Set Characteristicsmentioning

confidence: 99%

Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances

Babitsch

Sundermann

2020

Environ Sci Eur

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Background: Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results: The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions: The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe.

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Polycyclic aromatic hydrocarbons in particulate matter emitted from coke oven battery

Cited by 20 publications

References 43 publications

PAH Concentrations Inside a Wood Processing Plant and the Indoor Effects of Outdoor Industrial Emissions

PAH Concentrations Inside a Wood Processing Plant and the Indoor Effects of Outdoor Industrial Emissions

Particulate Matter from the Road Surface Abrasion as a Problem of Non-Exhaust Emission Control

Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances

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