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The purpose of this project is to dig deeper into the data material already generated in the Suspect screening in Nordic countries: Point sources in city areas (TemaNord: 2017:561) to further optimize the benefits of the major work that has already been done. Samples (effluent, sediment, and biota) from all of the Nordic countries were carefully selected, sampled and analysed by a consortium of some of the Nordic region’s most experienced scientific groups in analyses of emerging environmental contaminants. But where perhaps the full potential of the generated data is still to be realized. This project will try to further identify and describe the substances already detected, to be able to better understand what substances we in modern Nordic societies release into the sea via our wastewater.

Comprehensive two-dimensional (2D) gas chromatography (GC×GC) coupled to mass spectrometry (MS, GC×GC-MS), which enhances selectivity compared to GC-MS analysis, can be used for non-directed analysis (non-target screening) of environmental samples. Additional tools that aid in identifying unknown compounds are needed to handle the large amount of data generated. These tools include retention indices for characterizing relative retention of compounds and prediction of such. In this study, two quantitative structure–retention relationship (QSRR) approaches for prediction of retention times (1tR and 2tR) and indices (linear retention indices (LRIs) and a new polyethylene glycol–based retention index (PEG-2I)) in GC × GC were explored, and their predictive power compared. In the first method, molecular descriptors combined with partial least squares (PLS) analysis were used to predict times and indices. In the second method, the commercial software package ChromGenius (ACD/Labs), based on a “federation of local models,” was employed. Overall, the PLS approach exhibited better accuracy than the ChromGenius approach. Although average errors for the LRI prediction via ChromGenius were slightly lower, PLS was superior in all other cases. The average deviations between the predicted and the experimental value were 5% and 3% for the 1tR and LRI, and 5% and 12% for the 2tR and PEG-2I, respectively. These results are comparable to or better than those reported in previous studies. Finally, the developed model was successfully applied to an independent dataset and led to the discovery of 12 wrongly assigned compounds. The results of the present work represent the first-ever prediction of the PEG-2I. Graphical abstractᅟ Electronic supplementary material The online version of this article (10.1007/s00216-018-1415-x) contains supplementary material, which is available to authorized users.

Nondestructive sample cleanup and comprehensive two-dimensional gas chromatography (GC×GC) high-resolution mass spectrometry (HRMS) analysis generated a massive amount of data that could be used for nontarget screening purposes. We present a data reduction and prioritization strategy that involves time-trend analysis of nontarget data. Sewage sludge collected between 2005 and 2015 in Stockholm (Sweden) was retrieved from an environmental specimen bank, extracted, and analyzed by GC×GC-HRMS. After data alignment features with high blank levels, artifacts and low detection frequency were removed. Features that appeared in four to six out of ten years were reprocessed to fill in gaps. The total number of compounds was reduced by more than 97% from almost 60 000 to almost 1500. The remaining compounds were analyzed for monotonic (log-linear) and nonmonotonic (smoother) time trends. In total, 192 compounds with log-linear trends and 120 compounds with nonmonotonic trends were obtained, respectively. Most compounds described by a log-linear trend exhibited decreasing trends and were traffic-related. Compounds with increasing trends included UV-filters, alkyl-phenols, and flavor and fragrances, which often could be linked to trade statistics. We have shown that nontarget screening and stepwise reduction of data provides a simple way of revealing significant changes in emissions of chemicals in society.

To investigate the wide range of pollutants occurring in sewage sludge, an analytical method for comprehensive non-target screening is needed. To the best of our knowledge, no procedures currently exist for the full screening of organic contaminants in sewage sludge, which is the ultimate goal of this project. We developed non-discriminating sample preparation methods for gas chromatography-mass spectrometry (GC-MS) analysis. Pressurized liquid extraction (PLE) was used for extraction, with in-line (silica gel selective PLE, SPLE) or off-line clean-up (gel permeation chromatography, GPC). This combination allowed the analysis of non-polar compounds of all sizes and small semi-polar and non-polar compounds. The results show that the combination of SPLE and PLE with GPC is suitable for analysis of established as well as new contaminants. Both methods were validated for 99 compounds with different properties. For all GC suitable analytes, either one of the methods produced acceptable recoveries (64 to 136%). As a test, the two methods were used for non-target screening of Swedish sewage sludge. A tiered approach was used to tentatively identify the sludge contaminants. In total, 1865 and 1593 compounds were found of which 321 and 192 compounds were tentatively identified for the PLE and SPLE method, respectively. For a comprehensive coverage of contaminants, the two methods should be used together, with the PLE method covering a wider polarity range and the SPLE method a wider size range. In addition, polar substances will require liquid chromatography-mass spectrometry analysis, the method for which will be developed soon. Electronic supplementary material The online version of this article (doi:10.1007/s00216-017-0429-0) contains supplementary material, which is available to authorized users.

Building-related health effects are frequently observed. Several factors have been listed as possible causes including temperature, humidity, light conditions, presence of particulate matter, and microorganisms or volatile organic compounds. To be able to link exposure to specific volatile organic compounds to building-related health effects, powerful and comprehensive analytical methods are required. For this purpose, we developed an active air sampling method that utilizes dual-bed tubes loaded with TENAX-TA and Carboxen-1000 adsorbents to sample two parallel air samples of 4 L each. For the comprehensive volatile organic compounds analysis, an automated thermal desorption comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry method was developed and used. It allowed targeted analysis of approximately 90 known volatile organic compounds with relative standard deviations below 25% for the vast majority of target volatile organic compounds. It also allowed semiquantification (no matching standards) of numerous nontarget air contaminants using the same data set. The nontarget analysis workflow included peak finding, background elimination, feature alignment, detection frequency filtering, and tentative identification. Application of the workflow to air samples from 68 indoor environments at a large hospital complex resulted in a comprehensive volatile organic compound characterization, including 178 single compounds and 13 hydrocarbon groups.

Building related health effects or symptoms (BRS), known also as sick-building syndrome (SBS), are a phenomenon that is not well understood. In this study, air samples from 51 rooms associated with BRS and 34 control rooms were collected on multi-sorbent tubes and analyzed by a non-target approach using comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry techniques. The large amount of data gathered was analyzed using multivariate statistics (principle component analysis (PCA) and partial least squares (PLS)). This new analysis approach revealed that in rooms where people experienced BRS, petrochemicals and chemicals emitted from plastics were abundant, whereas in rooms where people did not experience BRS, flavor and fragrance compounds were abundant. Among the petrochemicals benzene and 2-butoxyethanol were found in higher levels in rooms where people experienced BRS. The levels of limonene were sometimes in the range of reported odor thresholds, and similarly 3-carene and beta-myrcene were found in higher concentrations in indoor air of rooms where people did not experience BRS. It cannot be ruled out that these compounds may have influenced the perceived air quality. However, the overall variability in air concentrations was large and it was not possible to accurately predict if the air in a particular room could cause BRS or not.

Regional climate change scenarios predict increased temperature and precipitation in the northern Baltic Sea, leading to a greater runoff of fresh water and terrestrial dissolved organic carbon (DOC) within the second part of the 21st century. As a result, the current north to south gradient in temperature and salinity is likely to be shifted further toward the south. To examine if such climate change effects would cause alterations in the environmental fate of organic pollutants, spatial variations of DOC quality and sorption behavior toward organic contaminants were examined using multiple analytical methods. The results showed declining contents of aromatic functional groups in DOC along a north to south gradient. Similarly, the sorption of a diverse set of organic contaminants to DOC also showed spatial differences. The sorption behavior of these contaminants was modeled using poly parameter linear energy relationships. The resulting molecular descriptors indicated clear differences in the sorption properties of DOC sampled in northern and southern parts of the Baltic Sea, which imply that more organic contaminants are sorbed to DOC in the northern part. The extent of this sorption process determines whether individual contaminants will partition to biota via direct uptake or through sorption to DOC, which serves as food source for bacteria-based food-webs.