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It is of considerable interest to identify chemicals which may represent a hazard and risk to environmental and human health in remote areas. The OECD POV and LRTP Screening Tool (“The Tool”) for assessing chemicals for persistence (P) and long-range transport potential (LRTP) has been extensively used for combined P and LRTP assessments in various regulatory contexts, including the Stockholm Convention (SC) on Persistent Organic Pollutants (POPs). The approach in The Tool plots either the Characteristic Travel Distance (CTD, in km), a transport-oriented metric, or the Transfer Efficiency (TE, in %), which calculates the transfer from the atmosphere to surface compartments in a remote region, against overall persistence (POV). For a chemical to elicit adverse effects in remote areas, it not only needs to be transported and transferred to remote environmental surface media, it also needs to accumulate in these media. The current version of The Tool does not have a metric to quantify this process. We screened a list of >12 000 high production volume chemicals (HPVs) for the potential to be dispersed, transferred, and accumulate in surface media in remote regions using the three corresponding LRTP metrics of the emission fractions approach (EFA; ϕ1, ϕ2, ϕ3), as implemented in a modified version of The Tool. Comparing the outcome of an assessment based on CTD/TE and POV with the EFA, we find that the latter classifies a larger number of HPVs as having the potential for accumulation in remote regions than is classified as POP-like by the existing approach. In particular, the EFA identifies chemicals capable of accumulating in remote regions without fulfilling the criterion for POV. The remote accumulation fraction of the EFA is the LRTP assessment metric most suited for the risk assessment stage in Annex E of the SC. Using simpler metrics (such as half-life criteria, POV, and LRTP–POV combinations) in a hazard-based assessment according to Annex D is problematic as it may prematurely screen out many of the chemicals with potential for adverse effects as a result of long-range transport.
2023
Updated trends for atmospheric mercury in the Arctic: 1995–2018
The Arctic region forms a unique environment with specific physical, chemical, and biological processes affecting mercury (Hg) cycles and limited anthropogenic Hg sources. However, historic global emissions and long range atmospheric transport has led to elevated Hg in Arctic wildlife and waterways. Continuous atmospheric Hg measurements, spanning 20 years, and increased monitoring sites has allowed a more comprehensive understanding of how Arctic atmospheric mercury is changing over time. Time-series trend analysis of TGM (Total Gaseous Mercury) in air was performed from 10 circumpolar air monitoring stations, comprising of high-Arctic, and sub-Arctic sites. GOM (gaseous oxidised mercury) and PHg (particulate bound mercury) measurements were also available at 2 high-Arctic sites. Seasonal mean TGM for sub-Arctic sites were lowest during fall ranging from 1.1 ng m−3 Hyytiälä to 1.3 ng m−3, Little Fox Lake. Mean TGM concentrations at high-Arctic sites showed the greatest variability, with highest daily means in spring ranging between 4.2 ng m−3 at Amderma and 2.4 ng m−3 at Zeppelin, largely driven by local chemistry. Annual TGM trend analysis was negative for 8 of the 10 sites. High-Arctic seasonal TGM trends saw smallest decline during summer. Fall trends ranged from −0.8% to −2.6% yr−1. Across the sub-Arctic sites spring showed the largest significant decreases, ranging between −7.7% to −0.36% yr−1, while fall generally had no significant trends. High-Arctic speciation of GOM and PHg at Alert and Zeppelin showed that the timing and composition of atmospheric mercury deposition events are shifting. Alert GOM trends are increasing throughout the year, while PHg trends decreased or not significant. Zeppelin saw the opposite, moving towards increasing PHg and decreasing GOM. Atmospheric mercury trends over the last 20 years indicate that Hg concentrations are decreasing across the Arctic, though not uniformly. This is potentially driven by environmental change, such as plant productivity and sea ice dynamics.
2022
Trends in Air Pollution in Europe, 2000–2019
This paper encompasses an assessment of air pollution trends in rural environments in Europe over the 2000–2019 period, benefiting from extensive long-term observational data from the EMEP monitoring network and EMEP MSC-W model computations. The trends in pollutant concentrations align with the decreasing emission patterns observed throughout Europe. Annual average concentrations of sulfur dioxide, particulate sulfate, and sulfur wet deposition have shown consistent declines of 3-4% annually since 2000. Similarly, oxidized nitrogen species have markedly decreased across Europe, with an annual reduction of 1.5-2% in nitrogen dioxide concentrations, total nitrate in the air, and oxidized nitrogen deposition. Notably, emission reductions and model predictions appear to slightly surpass the observed declines in sulfur and oxidized nitrogen, indicating a potential overestimation of reported emission reductions. Ammonia emissions have decreased less compared to other pollutants since 2000. Significant reductions in particulate ammonium have however, been achieved due to the impact of reductions in SOx and NOx emissions. For ground level ozone, both the observed and modelled peak levels in summer show declining trends, although the observed decline is smaller than modelled. There have been substantial annual reductions of 1.8% and 2.4% in the concentrations of PM10 and PM2.5, respectively. Elemental carbon has seen a reduction of approximately 4.5% per year since 2000. A similar reduction for organic carbon is only seen in winter when primary anthropogenic sources dominate. The observed improvements in European air quality emphasize the importance of comprehensive legislations to mitigate emissions.
2024
Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
In environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori quality information about the sensor device without using complex and resource-demanding data assimilation techniques. Both ordinary kriging and the general regression neural network (GRNN) are integrated into this attention with their learnable parameters based on deep learning architectures. We evaluate this method using three static phenomena with different complexities: a case related to a simplistic phenomenon, topography over an area of 196 and to the annual hourly concentration in 2019 over the Oslo metropolitan region (1026 ). We simulate networks of 100 synthetic sensor devices with six characteristics related to measurement quality and measurement spatial resolution. Generally, outcomes are promising: we significantly improve the metrics from baseline geostatistical models. Besides, distance attention using the Nadaraya–Watson kernel provides as good metrics as the attention based on the kriging system enabling the possibility to alleviate the processing cost for fusion of sparse data. The encouraging results motivate us in keeping adapting distance attention to space-time phenomena evolving in complex and isolated areas.
2024
Life starts with plastic: High occurrence of plastic pieces in fledglings of northern fulmars
Plastic pollution threatens many organisms around the world. In particular, the northern fulmar, Fulmarus glacialis, is known to ingest high quantities of plastics. Since data are sparse in the Eurasian Arctic, we investigated plastic burdens in the stomachs of fulmar fledglings from Kongsfjorden, Svalbard. Fifteen birds were collected and only particles larger than 1 mm were extracted, characterised and analysed with Fourier Transform InfraRed spectroscopy. All birds ingested plastic. In total, 683 plastic particles were found, with an average of 46 ± 40 SD items per bird. The most common shape, colour and polymer were hard fragment, white, and polyethylene, respectively. Microplastics ( 5 mm). This study confirms high numbers of ingested plastics in fulmar fledglings from Svalbard and suggests that fulmar fledglings may be suitable for temporal monitoring of plastic pollution, avoiding potential biases caused by age composition or breeding state.
2024
Altitude-temporal behaviour of atmospheric ozone, temperature and wind velocity observed at Svalbard
2018
The way Norway is spearheading electrification in the transport sector is of global interest. In this study, we used the Norwegian Emissions from Road Vehicle Exhaust (NERVE) model, a bottom-up high-resolution traffic emission model, to calculate all emissions in Norway (2009–2020) and evaluate potential co-benefit and trade-offs of policies to target climate change mitigation, air quality and socioeconomic factors. Results for municipal data with regard to traffic growth, road network influences, vehicle composition, emissions and energy consumption are presented. Light vehicle CO2 emissions per kilometer have been reduced by 22% since 2009, mainly driven by an increasing bio-fuel mixing and battery electric vehicles (BEV) share. BEVs are mostly located in and around the main cities, areas with young vehicle fleets, and strong local incentives. Beneficiaries of BEVs incentives have been a subset of the population with strong economic indicators. The incentivized growth in the share of diesel-fuelled passenger vehicles has been turned, and together with Euro6 emission standards, light vehicle NOx emissions have been halved since peaking in 2014. BEVs represent an investment in emission reductions in years to come, and current sales set Norway up for an accelerated decline in all exhaust emissions despite the continual growth in traffic.
2022
There is little information to decision support in air traffic management in case of nuclear releases into the atmosphere. In this paper, the dose estimation due to both, external exposure (i.e. cloud immersion, deposition inside and outside the aircraft), and due to internal exposure (i.e, inhalation of radionuclides inside the aircraft) to passengers and crew is calculated for a worst-case emergency scenario. The doses are calculated for different radionuclides and activities. Calculations are mainly considered according to International Commission on Radiological Protection (ICRP) recommendations and Monte Carlo simulations. In addition, a discussion on potential detectors installed inside the aircraft for monitoring the aerosol concentration and the ambient dose equivalent rate, H*(10), for during-flight monitoring and early warning is provided together with the evaluation of a response of a generic detector. The results show that the probability that a catastrophic nuclear accident would produce significant radiological doses to the passengers and crew of an aircraft is very low. In the worst-case scenarios studied, the maximum estimated effective dose was about 1 mSv during take-off or landing operations, which is the recommended yearly threshold for the public. However, in order to follow the ALARA (As Low As Reasonably Achievable) criteria and to avoid aircraft contamination, the installation of radiological detectors is considered. This would, on one hand help the pilot or corresponding decision maker to decide about the potential change of the route and, on the other, allow for gathering of 4D data for future studies.
2019
The influence of photochemistry on outdoor to indoor NO2 in some European museums
This paper reports 1 year of monthly average NO2 indoor to outdoor (I/O) concentrations measured in 10 European museums, and a simple steady-state box model that explains the annual variation. The measurements were performed in the EU FP5 project Master (EVK-CT-2002-00093). The work provides extensive documentation of the annual variation of NO2 I/O concentration ratios, with ratios above unity in the summer, in situations with no indoor emissions of NO2. The modelling included the most relevant production and removal processes of NO2 and showed that the outdoor photolysis was the probable main explanation of the annual trends in the NO2 I/O concentration ratios.
2022
2018
Using life cycle assessment to inform municipal climate mitigation planning
Local governments can play a key role in reducing emissions associated with local energy use. 17 Polish municipalities provided data on energy use and CO2 emissions for 2015. Life Cycle Assessment (LCA) was used to calculate lifecycle impact indicators for greenhouse gases, particulate matter, acidification and eutrophication associated with the annual energy demand in each municipality. Results showed that impacts from energy use increase almost proportionally with total energy used in the participating municipalities due to the heavy reliance on fossil fuels. Analysis of two municipalities of similar size showed that impacts can be attributed to different usage sectors. For one municipality, energy plans should focus on reducing emissions from private transport and associated fuel use. For the other, energy plans should focus on reducing energy demand from residential buildings. This means that a ‘one-size-fits-all’ energy plan, which may be developed at a national level, would not fit all municipalities. The application of LCA allows for identifying and informing energy planning with impact reduction potential for multiple environmental pressures. Analysis of the provided energy use and CO2 data showed large uncertainties in CO2 emission intensities and allowing for sufficient time and guidance in the energy and emissions accounting is recommended.
2019
2020
Atmospheric inversions have been used for the past two decades to derive large-scale constraints on the sources and sinks of CO2 into the atmosphere. The development of dense in situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM (European atmospheric transport inversion comparison) project is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006–2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale.
The project participants were provided with a common database of in situ-observed CO2 concentrations (including the observation sites that are now part of the ICOS network) and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach, and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties.
This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (−0.21±0.2
Pg C yr−1). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for sub-regions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country-scale flux estimates appears achievable in the near future.
2020
2019
Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface...
2022
2018
Global occurrence, chemical properties, and ecological impacts of e-wastes (IUPAC Technical Report)
The waste stream of obsolete electronic equipment grows exponentially, creating a worldwide pollution and resource problem. Electrical and electronic waste (e-waste) comprises a heterogeneous mix of glass, plastics (including flame retardants and other additives), metals (including rare Earth elements), and metalloids. The e-waste issue is complex and multi-faceted. In examining the different aspects of e-waste, informal recycling in developing countries has been identified as a primary concern, due to widespread illegal shipments; weak environmental, as well as health and safety, regulations; lack of technology; and inadequate waste treatment structure. For example, Nigeria, Ghana, India, Pakistan, and China have all been identified as hotspots for the disposal of e-waste. This article presents a critical examination on the chemical nature of e-waste and the resulting environmental impacts on, for example, microbial biodiversity, flora, and fauna in e-waste recycling sites around the world. It highlights the different types of risk assessment approaches required when evaluating the ecological impact of e-waste. Additionally, it presents examples of chemistry playing a role in potential solutions. The information presented here will be informative to relevant stakeholders seeking to devise integrated management strategies to tackle this global environmental concern.
2020
2021
Global greenhouse gas reconciliation 2022
n this study, we provide an update on the methodology and data used by Deng et al. (2022) to compare the national greenhouse gas inventories (NGHGIs) and atmospheric inversion model ensembles contributed by international research teams coordinated by the Global Carbon Project. The comparison framework uses transparent processing of the net ecosystem exchange fluxes of carbon dioxide (CO2) from inversions to provide estimates of terrestrial carbon stock changes over managed land that can be used to evaluate NGHGIs. For methane (CH4), and nitrous oxide (N2O), we separate anthropogenic emissions from natural sources based directly on the inversion results to make them compatible with NGHGIs. Our global harmonized NGHGI database was updated with inventory data until February 2023 by compiling data from periodical United Nations Framework Convention on Climate Change (UNFCCC) inventories by Annex I countries and sporadic and less detailed emissions reports by non-Annex I countries given by national communications and biennial update reports. For the inversion data, we used an ensemble of 22 global inversions produced for the most recent assessments of the global budgets of CO2, CH4, and N2O coordinated by the Global Carbon Project with ancillary data. The CO2 inversion ensemble in this study goes through 2021, building on our previous report from 1990 to 2019, and includes three new satellite inversions compared to the previous study and an improved managed-land mask. As a result, although significant differences exist between the CO2 inversion estimates, both satellite and in situ inversions over managed lands indicate that Russia and Canada had a larger land carbon sink in recent years than reported in their NGHGIs, while the NGHGIs reported a significant upward trend of carbon sink in Russia but a downward trend in Canada. For CH4 and N2O, the results of the new inversion ensembles are extended to 2020. Rapid increases in anthropogenic CH4 emissions were observed in developing countries, with varying levels of agreement between NGHGIs and inversion results, while developed countries showed a slowly declining or stable trend in emissions. Much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites, coordinated into a global constellation, is expected in the coming years. The methodology proposed here to compare inversion results with NGHGIs can be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objectives of their pledges. The dataset constructed for this study is publicly available at https://doi.org/10.5281/zenodo.13887128 (Deng et al., 2024).
2025
Road traffic externalities are an important consequence of land-use and transport interactions and may be especially induced by their inefficient combinations. In this study, we integrate land-use, transport and emission modelling tools (the LUTEm framework) to assess how suburban expansion vs. inward densification scenarios influence journey parameters, road network performance and traffic emissions. Case-study simulations for Warsaw (Poland) underscore the negative consequences of suburban sprawl development, which are hardly mitigated by additional land-use or transport interventions, such as rebalancing of population-workplace distribution or road capacity reductions. On the other side, compact city development lowers global traffic congestion and emissions, but can also raise the risks of traffic externalities in central city area unless complemented with further interventions such as improved public transport attractiveness. This study aims to enrich the understanding of how integrating the land-use development and transport interventions can ultimately influence travel parameters and reduce urban road traffic externalities.
2025
Poor Indoor Environmental Quality (IEQ) in schools significantly impacts students’ well-being, learning capabilities, and health. Perceived dissatisfaction rates (PD%) among students often remain high, even when indoor environmental variables appear well-controlled. This study aims to predict perceived dissatisfaction rates (PD%) across multi-domain environmental factors—thermal, acoustic, visual, and indoor air quality (IAQ)—using machine learning (ML) models. The research integrates sensor-based environmental measurements, outdoor weather data, building parameters, and 1437 student survey responses collected from three classrooms in a Norwegian school across multiple seasons. Statistical tests were used to pre-select relevant input variables, followed by the development and evaluation of multiple ML algorithms. Among the tested ML models, Random Forest (RF) demonstrated the highest predictive accuracy for PD%, outperforming multi-linear regression (MLR) and decision trees (DT), with R² values up to 0.91 for overall IEQ dissatisfaction (PDIEQ%). SHAP analysis revealed key predictors: CO₂ levels, VOCs, humidity, temperature, solar radiation, and room window orientation. IAQ, thermal comfort, and acoustic environment were the most influential factors affecting students' perceived well-being. Despite limitations as implementation in building level scale, the study demonstrates the feasibility of deploying predictive ML models under real-world constraints for improving IEQ monitoring system. The findings support practical strategies for adaptive indoor environmental management, particularly in educational settings, and provide a replicable framework for future research. Future research can expand to other climates, buildings, measurements, occupant levels, and ML training optimization.
2025
Long-term monitoring of regulated organic chemicals, such as legacy persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAHs), in ambient air provides valuable information about the compounds' environmental fate as well as temporal and spatial trends. This is the foundation to evaluate the effectiveness of national and international regulations for priority pollutants. Extracts of high-volume air samples, collected on glass fibre filters (GFF for particle phase) and polyurethane foam plugs (PUF for gaseous phase), for targeted analyses of legacy POPs are commonly cleaned by treatment with concentrated sulfuric acid, resulting in extracts clean from most interfering compounds and matrices that are suitable for multi-quantitative trace analysis. Such standardised methods, however, severely restrict the number of analytes for quantification and are not applicable when targeting new and emerging compounds as some may be less stable under acid treatment. Recently developed suspect and non-target screening analytical strategies (SUS and NTS, respectively) are shown to be effective evaluation tools aimed at identifying a high number of compounds of emerging concern. These strategies, combining highly sophisticated analytical technology with extensive data interpretation and statistics, are already widely accepted in environmental sciences for investigations of various environmental matrices, but their application to air samples is still very limited. In order to apply SUS and NTS for the identification of organic contaminants in air samples, an adapted and more wide-scope sample clean-up method is needed compared to the traditional method, which uses concentrated sulfuric acid. Analysis of raw air sample extracts without clean-up would generate extensive contamination of the analytical system, especially with PUF matrix-based compounds, and thus highly interfered mass spectra and detection limits which are unacceptable high for trace analysis in air samples.
In this study, a novel wide-scope sample clean-up method for high-volume air samples has been developed and applied to real high-volume air samples, which facilitates simultaneous target, suspect and non-target analyses. The scope and efficiency of the method were quantitatively evaluated with organic compounds covering a wide range of polarities (logP 2–11), including legacy POPs, brominated flame retardants (BFRs), chlorinated pesticides and currently used pesticides (CUPs). In addition, data reduction and selection strategies for SUS and NTS were developed for comprehensive two-dimensional gas chromatography separation with low-resolution time-of-flight mass spectrometric detection (GC × GC-LRMS) data and applied to real high-volume air samples. Combination of the newly developed clean-up procedure and data treatment strategy enabled the prioritisation of over 600 compounds of interest in the particle phase (on GFF) and over 850 compounds in the gas phase (on PUF) out of over 25 000 chemical features detected in the raw dataset. Of these, 50 individual compounds were identified and confirmed with reference standards, 80 compounds were identified with a probable structure, and 774 compounds were assigned to various compound classes. In the dataset available here, 11 hitherto unknown halogenated compounds were detected. These unknown compounds were not yet listed in the available mass spectral libraries.
2021