Found 10359 publications. Showing page 384 of 415:
This study investigates the efficacy of supramolecular solvent (SUPRAS) in extracting a diverse spectrum of organic contaminants from indoor dust. Initially, seven distinct SUPRAS were assessed across nine categories of contaminants to identify the most effective one. A SUPRAS comprising Milli-Q water, tetrahydrofuran, and hexanol in a 70:20:10 ratio, respectively, demonstrated the best extraction performance and was employed for testing a wider array of organic contaminants. Furthermore, we applied the selected SUPRAS for the extraction of organic compounds from the NIST Standard Reference Material (SRM) 2585. In parallel, we performed the extraction of NIST SRM 2585 with conventional extraction methods using hexane:acetone (1:1) for non-polar contaminants and methanol (100%) extraction for polar contaminants. Analysis from two independent laboratories (in Norway and the Czech Republic) demonstrated the viability of SUPRAS for the simultaneous extraction of twelve groups of organic contaminants with a broad range of physico-chemical properties including plastic additives, pesticides, and combustion by-products. However, caution is advised when employing SUPRAS for highly polar contaminants like current-use pesticides or volatile substances like naphthalene.
2024
2024
This report summaries the outcome of a workshop focused on standardizing monitoring strategies for Chemicals of Emerging Concern (CECs), including PFAS, flame retardants, chlorinated paraffins, siloxanes, and microplastics. Key recommendations include harmonised sampling methods, expanding the monitoring programs, conducting measurement campaigns, and enhancing analysis techniques.
NILU
2024
2024
Air quality and transport behaviour: sensors, field, and survey data from Warsaw, Poland
The present study describes the data sets produced in Warsaw, Poland with the aim of developing tools and methods for the implementation of human-centred and data-driven solutions to the enhancement of sustainable mobility transition. This study focuses on school commutes and alternatives to private cars for children drop off and pick up from primary schools. The dataset enables the complex analysis of interactions between determinants of transport mode choice, revealed choices, and air quality impact. We draw on four data collection methods, namely, (i) air quality and noise sensors’ measurements, (ii) in-person observations of transport behaviours, (iii) travel diaries, and (iv) social surveys. Moreover, all trip data from travel diaries are complemented with the calculated attributes of alternative travel modes. The data produced in the project can be also combined with publicly available information on air quality, public transport schedules, and traffic flows. The present data sets help to open new venues for interdisciplinary analyses of sustainable mobility transition effectiveness and efficiency.
2024
Chemicals of emerging concern (CECs) in coastal waters: Environmental impact & Management strategies
2024
2024
Active vegetation fires in south-eastern (SE) Europe resulted in a notable increase in the number concentration of aerosols and cloud condensation nuclei (CCN) particles at two high latitude locations—the SMEAR IV station in Kuopio, Finland, and the Zeppelin Observatory in Svalbard, high Arctic. During the fire episode aerosol hygroscopicity κ slightly increased at SMEAR IV and at the Zeppelin Observatory κ decreased. Despite increased κ in high CCN conditions at SMEAR IV, the aerosol activation diameter increased due to the decreased supersaturation with an increase in aerosol loading. In addition, at SMEAR IV during the fire episode, in situ measured cloud droplet number concentration (CDNC) increased by a factor of ∼7 as compared to non-fire periods which was in good agreement with the satellite observations (MODIS, Terra). Results from this study show the importance of SE European fires for cloud properties and radiative forcing in high latitudes.
2024
Background
Prioritisation of chemical pollutants is a major challenge for environmental managers and decision-makers alike, which is essential to help focus the limited resources available for monitoring and mitigation actions on the most relevant chemicals. This study extends the original NORMAN prioritisation scheme beyond target chemicals, presenting the integration of semi-quantitative data from retrospective suspect screening and expansion of existing exposure and risk indicators. The scheme utilises data retrieved automatically from the NORMAN Database System (NDS), including candidate substances for prioritisation, target and suspect screening data, ecotoxicological effect data, physico-chemical data and other properties. Two complementary workflows using target and suspect screening monitoring data are applied to first group the substances into six action categories and then rank the substances using exposure, hazard and risk indicators. The results from the ‘target’ and ‘suspect screening’ workflows can then be combined as multiple lines of evidence to support decision-making on regulatory and research actions.
Results
As a proof-of-concept, the new scheme was applied to a combined dataset of target and suspect screening data. To this end, > 65,000 substances on the NDS, of which 2579 substances supported by target wastewater monitoring data, were retrospectively screened in 84 effluent wastewater samples, totalling > 11 million data points. The final prioritisation results identified 677 substances as high priority for further actions, 7455 as medium priority and 326 with potentially lower priority for actions. Among the remaining substances, ca. 37,000 substances should be considered of medium priority with uncertainty, while it was not possible to conclude for 19,000 substances due to insufficient information from target monitoring and uncertainty in the identification from suspect screening. A high degree of agreement was observed between the categories assigned via target analysis and suspect screening-based prioritisation. Suspect screening was a valuable complementary approach to target analysis, helping to prioritise thousands of substances that are insufficiently investigated in current monitoring programmes.
Conclusions
This updated prioritisation workflow responds to the increasing use of suspect screening techniques. It can be adapted to different environmental compartments and can support regulatory obligations, including the identification of specific pollutants in river basins and the marine environments, as well as the confirmation of environmental occurrence levels predicted by modelling tools.
2024
Monitoring of environmental contaminants in freshwater food webs (MILFERSK), 2023
This report presents data from the third year of a 5-year period of the MILFERSK program. In 2023 the monitoring program reports on the sampling and analyses of the pelagic food chain in Lake Mjøsa, with the following sample types: zooplankton, Mysis, E. smelt, vendace, and brown trout, in addition to brown trout from Lake Femunden. A total of 205 single compounds/isomers were determined, and frequent detections were found of specific PFAS, PBDEs, Hg and siloxanes through the food chain with biomagnifying properties. Some contaminants, such as octocrylene is found in higher concentrations in the lower trophic levels. A slight downwards trend is observed from 2014 – 2023 for PFOS in Lake Mjøsa. We also observe a lower length adjusted mercury concentration for brown trout in Lake Mjøsa for the period 2014 to 2023, compared to the 9 years prior (2006 – 2014).
Norsk institutt for vannforskning (NIVA)
2024
The FAIR principles as a key enabler to operationalize safe and sustainable by design approaches
Safe and sustainable development of chemicals, (advanced) materials, and products is at the heart of achieving a healthy future environment in line with the European Green Deal and the Chemicals Strategy for Sustainability. Recently, the Joint Research Center (JRC) of the European Commission (EC) developed the safe and sustainable by design (SSbD) framework for definition of criteria and evaluation procedure proposed to be established in Research and Innovation (R&I) activities. The framework aims to support the design of chemicals, materials and products that provide desirable functions (or services), while simultaneously minimizing the risk for harmful impacts to human health and the environment. While many industrial sectors already consider such aspects during R&I, the framework aims to harmonize safety and sustainability assessment across diverse sectors and innovation strategies to meet the mentioned overarching policy goals. A cornerstone to successfully implement and operationalize the SSbD framework lies in the availability of high-quality data and tools, and their interoperability, aspects which also play a key role in ensuring transparency and thereby trust in the assessment outcomes. Availability of data and tools depend on their machine-actionability in terms of findability, accessibility, interoperability, and reusability, in line with the FAIR principles. The principles were developed in order to harmonize digitalization across all data domains, supporting unanticipated data-driven “seamless” integration of information and generation of new knowledge. Here we discuss the essentiality of FAIR data and tools to operationalize SSbD providing views and examples of activities within the European Partnership for the Assessment of Risks from Chemicals (PARC). The discussion covers five areas previously brought up in relation to the SSbD framework, and which are highly dependent on implementation of the FAIR principles; (i) digitalization to leverage innovation towards a green transition; (ii) existing data sources and their interoperability; (iii) navigating SSbD with data from new scientific developments (iv) transparency and trust through automated assessment of data quality and uncertainty; and (v) “seamless” integration of SSbD tools.
2024
Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present-day greenhouse gas (GHG) budgets. We compare bottom-up (data-driven upscaling and process-based models) and top-down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom-up approaches estimate higher land-to-atmosphere fluxes for all GHGs. Both bottom-up and top-down approaches show a sink of CO2 in natural ecosystems (bottom-up: −29 (−709, 455), top-down: −587 (−862, −312) Tg CO2-C yr−1) and sources of CH4 (bottom-up: 38 (22, 53), top-down: 15 (11, 18) Tg CH4-C yr−1) and N2O (bottom-up: 0.7 (0.1, 1.3), top-down: 0.09 (−0.19, 0.37) Tg N2O-N yr−1). The combined global warming potential of all three gases (GWP-100) cannot be distinguished from neutral. Over shorter timescales (GWP-20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process-based models and the compilation of process-model ensembles for CH4 and N2O. Discrepancies between bottom-up and top-down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well-distributed in situ GHG measurements and improved resolution in upscaling techniques.
2024
We investigate the concentration fluctuations of passive scalar plumes emitted from small, localised (point-like) steady sources in a neutrally stratified turbulent boundary layer over a rough wall. The study utilises high-resolution large-eddy simulations for sources of varying sizes and heights. The numerical results, which show good agreement with wind-tunnel studies, are used to estimate statistical indicators of the concentration field, including spectra and moments up to the fourth order. These allow us to elucidate the mechanisms responsible for the production, transport and dissipation of concentration fluctuations, with a focus on the very near field, where the skewness is found to have negative values – an aspect not previously highlighted. The gamma probability density function is confirmed to be a robust model for the one-point concentration at sufficiently large distances from the source. However, for ground-level releases in a well-defined area around the plume centreline, the Gaussian distribution is found to be a better statistical model. As recently demonstrated by laboratory results, for elevated releases, the peak and shape of the pre-multiplied scalar spectra are confirmed to be independent of the crosswind location for a given downwind distance. Using a stochastic model and theoretical arguments, we demonstrate that this is due to the concentration spectra being directly shaped by the transverse and vertical velocity components governing the meandering of the plume. Finally, we investigate the intermittency factor, i.e. the probability of non-zero concentration, and analyse its variability depending on the thresholds adopted for its definition.
2024
NILU og Transportøkonomisk institutt (TØI) har på oppdrag fra Miljødirektoratet videreutviklet modellen NERVE («Norwegian Emissions from Road Vehicle Exhaust») for beregning av klimagassutslipp fra veitrafikken i norske kommuner. NERVE-modellen anvender de mest detaljerte datasettene for bilpark, utslippsfaktorer, trafikk og veier for spesifikke lokale forhold. Datasettene er kombinert i en datastruktur som gjør at resultat kan aggregeres på et lite eller et stort geografisk område. NERVE kan således betegnes som en «bottom-up»-utslippsmodell, fordi den er bygget opp «nedenfra» fra detaljerte datakilder. Denne rapporten presenterer metodikken og antagelsene bak beregningene med NERVE, og sammenligner resultat aggregert på nasjonalt nivå med annen tilgjengelig nasjonal statistikk.
NILU
2024
2024