Characterizing Spatial Diversity of Passive Sampling Sites for Measuring Levels and Trends of Semivolatile Organic Chemicals

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Publikace nespadá pod Ústav výpočetní techniky, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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KALINA Jiří SCHERINGER Martin BORŮVKOVÁ Jana KUKUČKA Petr PŘIBYLOVÁ Petra SÁŇKA Ondřej MELYMUK Lisa Emily VANA Milan KLÁNOVÁ Jana

Rok publikování 2018
Druh Článek v odborném periodiku
Časopis / Zdroj ENVIRONMENTAL SCIENCE & TECHNOLOGY
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://pubs.acs.org/doi/10.1021/acs.est.8b03414
Doi http://dx.doi.org/10.1021/acs.est.8b03414
Klíčová slova POLYCYCLIC AROMATIC-HYDROCARBONS; AIR SAMPLERS; POLYCHLORINATED-BIPHENYLS; TEMPORAL TRENDS; AMBIENT AIR; POLLUTANTS; ATMOSPHERE; TOOL; REGION; PAHS
Popis Passive air sampling of semivolatile organic compounds (SVOCs) is a relatively inexpensive method that facilitates extensive campaigns with numerous sampling sites. An important question in the design of passive-sampling networks concerns the number and location of samplers. We investigate this question with the example of 17 SVOCs sampled at 14 background sites across the Czech Republic. More than 200 time series (length 5-11 years) were used to characterize SVOC levels and trends in air between 2003 and 2015. Six polychlorinated biphenyls (PCBs), 6 polyaromatic hydrocarbons (PAHs), and 5 organochlorine pesticides (OCPs) at 14 sites were assessed using data from the MONET passive sampling network. Significant decreases were found for most PCBs and OCPs whereas hexachlorobenzene (HCB) and most PAHs showed (mostly insignificant) increases. Spatial variability was rather low for PCBs and OCPs except for dichlorodiphenyltri-chloroethane (DDT) and rather high for PAHs. The variability of the SVOC levels and trends depends on characteristics of the sites including their remoteness, landscape, population, and pollution sources. The sites can be grouped in distinct clusters, which helps to identify similar and, thereby, potentially redundant sites. This information is useful when monitoring networks need to be optimized regarding the location and number of sites.
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