Four Years of Active Sampling and Measurement of Atmospheric Polycyclic Aromatic Hydrocarbons and Oxygenated Polycyclic Aromatic Hydrocarbons in Dronning Maud Land, East Antarctica.

Antarctica, protected by its strong polar vortex and sheer distance from anthropogenic activity, was always thought of as pristine. However, as more data on the occurrence of persistent organic pollutants on Antarctica emerge, the question arises of how fast the long-range atmospheric transport takes place. Therefore, polycyclic aromatic hydrocarbons (PAHs) and oxygenated (oxy-)PAHs were sampled from the atmosphere and measured during 4 austral summers from 2017 to 2021 at the Princess Elisabeth station in East Antarctica. The location is suited for this research as it is isolated from other stations and activities, and the local pollution of the station itself is limited. A high-volume sampler was used to collect the gas and particle phase (PM10) separately. Fifteen PAHs and 12 oxy-PAHs were quantified, and concentrations ranging between 6.34 and 131 pg m3 (Σ15PAHs-excluding naphthalene) and between 18.8 and 114 pg m3 (Σ13oxy-PAHs) were found. Phenanthrene, pyrene, and fluoranthene were the most abundant PAHs. The gas-particle partitioning coefficient log(Kp) was determined for 6 compounds and was found to lie between 0.5 and -2.5. Positive matrix factorization modeling was applied to the data set to determine the contribution of different sources to the observed concentrations. A 6-factor model proved a good fit to the data set and showed strong variations in the contribution of different air masses. During the sampling campaign, a number of volcanic eruptions occurred in the southern hemisphere from which the emission plume was detected. The FLEXPART dispersion model was used to confirm that the recorded signal is indeed influenced by volcanic eruptions. The data was used to derive a transport time of between 11 and 33 days from release to arrival at the measurement site on Antarctica.

Combined Phylogeographic Analyses and Epidemiologic Contact Tracing to Characterize Atypically Pathogenic Avian Influenza (H3N1) Epidemic, Belgium, 2019.

The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of a low pathogenicity avian influenza (H3N1) epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Spatiotemporal clustering, transport, and social contacts strongly correlated with the phylogeographic pattern of the epidemic. We detected only a limited association between wind direction and direction of viral lineage dispersal. Our results highlight the multifactorial nature of avian influenza epidemics and illustrate the use of genomic analyses of virus dispersal to complement epidemiologic and environmental data, improve knowledge of avian influenza epidemiologic dynamics, and enhance control strategies.

COVID-19 Crisis Reduces Free Tropospheric Ozone Across the Northern Hemisphere.

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (≈4 nmol/mol) below the 2000-2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere contributed less than one-quarter of the observed tropospheric anomaly. The observed anomaly is consistent with recent chemistry-climate model simulations, which assume emissions reductions similar to those caused by the COVID-19 crisis. COVID-19 related emissions reductions appear to be the major cause for the observed reduced free tropospheric ozone in 2020.

Eight-Year Estimates of Methane Emissions from Oil and Gas Operations in Western Canada Are Nearly Twice Those Reported in Inventories.

The provinces of Alberta and Saskatchewan account for 70% of Canada's methane emissions from the oil and gas sector. In 2018, the Government of Canada introduced methane regulations to reduce emissions from the sector by 40-45% from the 2012 levels by 2025. Complementary to inventory accounting methods, the effectiveness of regulatory practices to reduce emissions can be assessed using atmospheric measurements and inverse models. Total anthropogenic (oil and gas, agriculture, and waste) emission rates of methane from 2010 to 2017 in Alberta and Saskatchewan were derived using hourly atmospheric methane measurements over a six-month winter period from October to March. Scaling up the winter estimate to annual indicated an anthropogenic emission rate of 3.7 ± 0.7 MtCH4/year, about 60% greater than that reported in Canada's National Inventory Report (2.3 MtCH4). This discrepancy is tied primarily to the oil and gas sector emissions as the reported emissions from livestock operations (0.6 MtCH4) are well substantiated in both top-down and bottom-up estimates and waste management (0.1 MtCH4) emissions are small. The resulting estimate of 3.0 MtCH4 from the oil and gas sector is nearly twice that reported in Canada's National Inventory (1.6 MtCH4).

Heat related mortality in the two largest Belgian urban areas: A time series analysis.

BACKGROUND: Summer temperatures are expected to increase and heat waves will occur more frequently, be longer, and be more intense as a result of global warming. A growing body of evidence indicates that increasing temperature and heatwaves are associated with excess mortality and therefore global heating may become a major public health threat. However, the heat-mortality relationship has been shown to be location-specific and differences could largely be explained by the most frequent temperature. So far, in Belgium there is little known regarding the heat-mortality relationship in the different urban areas. OBJECTIVES: The objective of this study is to assess the heat-mortality relationship in the two largest urban areas in Belgium, i.e. Antwerp and Brussels for the warm seasons from 2002 until 2011 taking into account the effect of air pollution. METHODS: The threshold in temperature above which mortality increases was determined using segmented regressions for both urban areas. The relationship between daily temperature and mortality above the threshold was investigated using a generalized estimated equation with Poisson distribution to finally determine the percentage of deaths attributable to the effect of heat. RESULTS: Although only 50 km apart, the heat-mortality curves for the two urban areas are different. More specifically, an increase in mortality occurs above a maximum temperature of 25.2 °C in Antwerp and 22.8 °C in Brussels. We estimated that above these thresholds, there is an increase in mortality of 4.9% per 1 °C in Antwerp and of 3.1% in Brussels. During the study period, 1.5% of the deaths in Antwerp and 3.5% of the deaths in Brussels can be attributed to the effect of heat. The thresholds differed considerably from the most frequent temperature, particularly in Antwerp. Adjustment for air pollution attenuated the effect of temperature on mortality and this attenuation was more pronounced when adjusting for ambient ozone. CONCLUSION: Our results show a significant effect of temperature on mortality above a city-specific threshold, both in Antwerp and in Brussels. These findings are important given the ongoing global warming. Recurrent, intense and longer episodes of high temperature and expected changes in air pollutant levels will have an important impact on health in urban areas.

Comparative long-term trend analysis of daily weather conditions with daily pollen concentrations in Brussels, Belgium.

A clear rise in seasonal and annual temperatures, a gradual increase of total radiation, and a relative trend of change in seasonal precipitation have been observed for the last four decades in Brussels (Belgium). These local modifications may have a direct and indirect public health impact by altering the timing and intensity of allergenic pollen seasons. In this study, we assessed the statistical correlations (Spearman's test) between pollen concentration and meteorological conditions by using long-term daily datasets of 11 pollen types (8 trees and 3 herbaceous plants) and 10 meteorological parameters observed in Brussels between 1982 and 2015. Furthermore, we analyzed the rate of change in the annual cycle of the same selected pollen types by the Mann-Kendall test. We revealed an overall trend of increase in daily airborne tree pollen (except for the European beech tree) and an overall trend of decrease in daily airborne pollen from herbaceous plants (except for Urticaceae). These results revealed an earlier onset of the flowering period for birch, oak, ash, plane, grasses, and Urticaceae. Finally, the rates of change in pollen annual cycles were shown to be associated with the rates of change in the annual cycles of several meteorological parameters such as temperature, radiation, humidity, and rainfall.

Top-Down NOX Emissions of European Cities Based on the Downwind Plume of Modelled and Space-Borne Tropospheric NO2 Columns.

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April⁻September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R² = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R² = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.

Mortality related to cold and heat. What do we learn from dairy cattle?

Extreme temperatures are associated with increased mortality among humans. Because similar epidemiologic studies in animals may add to the existing evidence, we investigated the association between ambient temperature and the risk of mortality among dairy cattle. We used data on 87,108 dairy cow deaths in Belgium from 2006 to 2009, and we combined a case-crossover design with distributed lag non-linear models. Province-specific results were combined in a multivariate meta-analysis. Relative to the estimated minimum mortality temperature of 15.4°C (75th percentile), the pooled cumulative relative risks over lag 0-25 days were 1.26 (95% CI: 1.11, 1.42) for extreme cold (1st percentile, -3.5°C), 1.35 (95% CI: 1.19, 1.54) for moderate cold (5th percentile, -0.3°C), 1.09 (95% CI: 1.02, 1.17) for moderate heat (95th percentile, 19.7°C), and 1.26 (95% CI: 1.08; 1.48) for extreme heat (99th percentile, 22.6°C). The temporal pattern of the temperature-mortality association was similar to that observed in humans, i.e. acute effects of heat and delayed and prolonged effects of cold. Seasonal analyses suggested that most of the temperature-related mortality, including cold effects, occurred in the warm season. Our study reinforces the evidence on the plausibility of causal effects in humans.

A baseline for source localisation using the inverse modelling tool FREAR.

A global network of monitoring stations is set up that can measure tiny concentrations of airborne radioactivity as part of the verification regime of the Comprehensive Nuclear-Test-Ban Treaty. If Treaty-relevant detections are made, inverse atmospheric transport modelling is one of the methods that can be used to determine the source of the radioactivity. In order to facilitate the testing of novel developments in inverse modelling, two sets of test cases are constructed using real-world 133Xe detections associated with routine releases from a medical isotope production facility. One set consists of 24 cases with 5 days of observations in each case, and another set consists of 8 cases with 15 days of observations in each case. A series of inverse modelling techniques and several sensitivity experiments are applied to determine the (known) location of the medical isotope production facility. Metrics are proposed to quantify the quality of the source localisation. Finally, it is illustrated how the sets of test cases can be used to test novel developments in inverse modelling algorithms.

Acute changes in pulse pressure in relation to constituents of particulate air pollution in elderly persons.

An increased pulse pressure (difference between systolic and diastolic blood pressure) suggests aortic stiffening. The objective of this study was to examine the acute effects of both particulate matter (PM) mass and composition on blood pressure, among elderly persons. We carried out a panel study in persons living in elderly homes in Antwerp, Belgium. We recruited 88 non-smoking persons, 70% women with a mean age of 83 years (standard deviation: 5.2). Blood pressure was measured and a blood sample was collected on two time points, which were chosen so that there was an exposure contrast in ambient PM exposure. The elemental content of the collected indoor and outdoor PM(2.5) (particulate matter with an aerodynamic diameter <2.5 µm) mass concentration was measured. Oxygenated polycyclic aromatic hydrocarbons (oxy-PAHs) on outdoor PM(10) (particulate matter with an aerodynamic diameter <10 µm) were measured. Each interquartile range increase of 20.8 µg/m³ in 24-h mean outdoor PM(2.5) was associated with an increase in pulse pressure of 4.0 mm Hg (95% confidence interval: 1.8-6.2), in persons taking antihypertensive medication (n=57), but not in persons not using antihypertensive medication (n=31) (p for interaction: 0.02). Vanadium, iron and nickel contents of PM(2.5) were significantly associated with systolic blood pressure and pulse pressure, among persons on antihypertensive medication. Similar results were found for indoor concentrations. Of the oxy-PAHs, chrysene-5,6-dione and benzo[a]pyrene-3,6-dione were significantly associated with increases in systolic blood pressure and pulse pressure. In elderly, pulse pressure was positively associated with acute increases in outdoor and indoor air pollution, among persons taking antihypertensive medication. These results might form a mechanistic pathway linking air pollution as a trigger of cardiovascular events.

Uncertainty quantification of atmospheric transport and dispersion modelling using ensembles for CTBT verification applications.

Airborne concentrations of specific radioactive xenon isotopes (referred to as "radioxenon") are monitored globally as part of the verification regime of the Comprehensive Nuclear-Test-Ban Treaty, as these could be the signatures of a nuclear explosion. However, civilian nuclear facilities emit a regulated amount of radioxenon that can interfere with the very sensitive monitoring network. One approach to deal with this civilian background of radioxenon for Treaty verification purposes, is to explicitly simulate the expected radioxenon concentration from civilian sources at monitoring stations using atmospheric transport modelling. However, atmospheric transport modelling is prone to uncertainty, and the absence of an uncertainty quantification can limit its use for detection screening. In this paper, several ensembles are assessed that could provide an atmospheric transport modelling uncertainty quantification. These ensembles are validated with radioxenon observations, and recommendations are given for atmospheric transport modelling uncertainty quantification. Finally, the added value of an ensemble for detection screening is illustrated.

Residential green space in association with the methylation status in a CpG site within the promoter region of the placental serotonin receptor HTR2A.

Green space could influence adult cognition and childhood neurodevelopment , and is hypothesized to be partly driven by epigenetic modifications. However, it remains unknown whether some of these associations are already evident during foetal development. Similar biological signals shape the developmental processes in the foetal brain and placenta.Therefore, we hypothesize that green space can modify epigenetic processes of cognition-related pathways in placental tissue, such as DNA-methylation of the serotonin receptor HTR2A. HTR2A-methylation was determined within 327 placentas from the ENVIRONAGE (ENVIRonmental influence ON early AGEing) birth cohort using bisulphite-PCR-pyrosequencing. Total green space exposure was calculated using high-resolution land cover data derived from the Green Map of Flanders in seven buffers (50 m-3 km) and stratified into low (<3 m) and high (≥3 m) vegetation. Residential nature was calculated using the Land use Map of Flanders. We performed multivariate regression models adjusted for several a priori chosen covariables. For an IQR increment in total green space within a 1,000 m, 2,000 m and 3,000 m buffer the methylation of HTR2A increased with 1.47% (95%CI:0.17;2.78), 1.52% (95%CI:0.21;2.83) and 1.42% (95%CI:0.15;2.69), respectively. Additionally,, we found 3.00% (95%CI:1.09;4.91) and 1.98% (95%CI:0.28;3.68) higher HTR2A-methylation when comparing residences with and without the presence of nature in a 50 m and 100 m buffer, respectively. The methylation status of HTR2A in placental tissue is positively associated with maternal green space exposure. Future research is needed to understand better how these epigenetic changes are related to functional modifications in the placenta and the consequent implications for foetal development.

Modelling grass pollen levels in Belgium.

Biogenic aerosols such as airborne grass pollen affect the public health badly by putting additional distress on people already suffering from cardiovascular and respiratory diseases. In Belgium, daily airborne pollen concentrations are monitored offline at a few sites only, hampering the timely coverage of the country and short-term forecasts. Here we apply the Chemistry Transport Model SILAM to the Belgian territory to model the spatio-temporal airborne grass pollen levels near the surface based on bottom-up inventories of grass pollen emissions updated with the Copernicus land monitoring Service grassland map of 2015. Transport of aerosols in SILAM is driven by ECMWF ERA5 meteorological data. The emitted grass pollen amounts in SILAM are computed by the multiplication of the grass pollen source map with the release rate determined by the seasonal shape production curve during the grass flowering period. The onset and offset of this period follow a location-dependent prescribed calendar days. Here we optimize the grass pollen seasonal start and end in SILAM by comparing a 2008-2018 time series of daily airborne grass pollen concentrations from the Belgian aerobiological surveillance network with the simulations. The effect of the spatial distribution of grass pollen sources is quantified by constructing pollen source-receptor relations using model simulations with varying grass pollen emissions in five areas of the model domain as input. Up to 33% of the airborne grass pollen in one area was transport from others areas inside Belgium. Adjusting the start and end of the grass pollen season improved the model performance substantially by almost doubling the correlation with local observations. By introducing the temporal scaling of the inter-seasonal pollen amounts in the model, an additional R2 increase up to 22% was obtained. Further improvements can be made by including more detailed grass pollen sources and more dynamic start and end dates of the pollen season.

Long-Term Pollen Monitoring in the Benelux: Evaluation of Allergenic Pollen Levels and Temporal Variations of Pollen Seasons.

Airborne pollen is a major cause of allergic rhinitis, affecting between 10 and 30% of the population in Belgium, the Netherlands, and Luxembourg (Benelux). Allergenic pollen is produced by wind pollinating plants and released in relatively low to massive amounts. Current climate changes, in combination with increasing urbanization, are likely to affect the presence of airborne allergenic pollen with respect to exposure intensity, timing as well as duration. Detailed analysis of long-term temporal trends at supranational scale may provide more comprehensive insight into these phenomena. To this end, the Spearman correlation was used to statistically compare the temporal trends in airborne pollen concentration monitored at the aerobiological stations which gathered the longest time-series (30-44 years) in the Benelux with a focus on the allergenic pollen taxa: Alnus, Corylus, Betula, Fraxinus, Quercus, Platanus, Poaceae, and Artemisia. Most arboreal species showed an overall trend toward an increase in the annual pollen integral and peak values and an overall trend toward an earlier start and end of the pollen season, which for Betula resulted in a significant decrease in season length. For the herbaceous species (Poaceae and Artemisia), the annual pollen integral and peak values showed a decreasing trend. The season timing of Poaceae showed a trend toward earlier starts and longer seasons in all locations. In all, these results show that temporal variations in pollen levels almost always follow a common trend in the Benelux, suggesting a similar force of climate change-driven factors, especially for Betula where a clear positive correlation was found between changes in temperature and pollen release over time. However, some trends were more local-specific indicating the influence of other environmental factors, e.g., the increasing urbanization in the surroundings of these monitoring locations. The dynamics in the observed trends can impact allergic patients by increasing the severity of symptoms, upsetting the habit of timing of the season, complicating diagnosis due to overlapping pollen seasons and the emergence of new symptoms due allergens that were weak at first.

The assessment of the April 2020 chernobyl wildfires and their impact on Cs-137 levels in Belgium and The Netherlands.

In April 2020, several wildfires took place in and around the Chernobyl exclusion zone. These fires reintroduced radioactive particles deposited during the 1986 Chernobyl disaster into the atmosphere, causing concern about a possible radiation hazard. Several countries and several stations of the International Monitoring System measured increased Cs137 levels. This study presents the analyses made by RIVM and SCK CEN/RMI during the April 2020 wildfires. Furthermore, more in-depth research was performed after the wildfires. A statistical analysis of Cs137 detections is presented, comparing the April 2020 detections with historical detections. Inverse atmospheric transport modelling is applied to infer the total released Cs137 during the wildfires. Finally, it is assessed whether the Cs137 detections in Belgium and the Netherlands can be attributed to the wildfires.

Exposure to green space and pollen allergy symptom severity: A case-crossover study in Belgium.

BACKGROUND: The prevalence of pollen allergy has increased due to urbanization, climate change and air pollution. The effects of green space and air pollution on respiratory health of pollen allergy patients are complex and best studied in spatio-temporal detail. METHODS: We tracked 144 adults sensitized to Betulaceae pollen during the tree pollen season (January-May) of 2017 and 2018 and assessed their spatio-temporal exposure to green space, allergenic trees, air pollutants and birch pollen. Participants reported daily symptom severity scores. We extracted 404 case days with high symptom severity scores and matched these to 404 control days. The data were analyzed using conditional logistic regression with a 1:1 case-crossover design. RESULTS: Case days were associated with exposure to birch pollen concentration (100 grains/m3) [adjusted odds ratio 1.045 and 95% confidence interval (1.014-1.078)], O3 concentration (10 µg/m3) [1.504 (1.281-1.766)] and PM10 concentration (10 µg/m3) [1.255 (1.007-1.565)] on the day of the severe allergy event and with the cumulative exposure of one and two days before. Exposure to grass cover (10% area fraction) [0.655 (0.446-0.960)], forest cover (10% area fraction) [0.543 (0.303-0.973)] and density of Alnus (10%) [0.622 (0.411-0.942)] were protective for severe allergy, but only on the day of the severe allergy event. Increased densities of Betula trees (10%) were a risk factor [unadjusted OR: 2.014 (1.162-3.490)]. CONCLUSION: Exposure to green space may mitigate tree pollen allergy symptom severity but only when the density of allergenic trees is low. Air pollutants contribute to more severe allergy symptoms. Spatio-temporal tracking allows for a more realistic exposure assessment.

Source localisation and its uncertainty quantification after the third DPRK nuclear test.

The International Monitoring System is being set up aiming to detect violations of the Comprehensive Nuclear-Test-Ban Treaty. Suspicious radioxenon detections were made by the International Monitoring System after the third announced nuclear test conducted by the Democratic People's Republic of Korea (DPRK). In this paper, inverse atmospheric transport and dispersion modelling was applied to these detections, to determine the source location, the release term and its associated uncertainties. The DPRK nuclear test site was found to be a likely source location, though a second likely source region in East Asia was found by the inverse modelling, partly due to the radioxenon background from civilian sources. Therefore, techniques to indirectly assess the influence of the radioxenon background are suggested. In case of suspicious radioxenon detections after a man-made explosion, atmospheric transport and dispersion modelling is a powerful tool for assessing whether the explosion could have been nuclear or not.

Time resolution requirements for civilian radioxenon emission data for the CTBT verification regime.

The capability of the noble gas component of the International Monitoring System as a verification tool for the Comprehensive Nuclear-Test-Ban Treaty is deteriorated by a background of radioxenon emitted by civilian sources. One of the possible approaches to deal with this issue, is to simulate the daily radioxenon concentrations from these civilian sources at noble gas stations by using atmospheric transport models. In order to accurately quantify the contribution from these civilian sources, knowledge on the releases is required. However, such data are often not available and furthermore it is not clear what temporal resolution such data should have. In this paper, we assess which temporal resolution is required to best model the 133Xe contribution from civilian sources at noble gas stations in an operational context. We consider different sampling times of the noble gas stations and discriminate between nearby and distant sources. We find that for atmospheric transport and dispersion problems on a scale of 1000 km or more, emission data with subdaily temporal resolution is generally not necessary. However, when the source-receptor distance decreases, time-resolved emission data become more important. The required temporal resolution of emission data thus depends on the transport scale of the problem. In the context of the Comprehensive Nuclear-Test-Ban Treaty, where forty noble gas stations will monitor the whole globe, daily emission data are generally sufficient, but for certain meteorological conditions, better temporally resolved emission data are required.

International challenge to model the long-range transport of radioxenon released from medical isotope production to six Comprehensive Nuclear-Test-Ban Treaty monitoring stations.

After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) and in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.

Assessment of the announced North Korean nuclear test using long-range atmospheric transport and dispersion modelling.

On 6 January 2016, the Democratic People's Republic of Korea announced to have conducted its fourth nuclear test. Analysis of the corresponding seismic waves from the Punggye-ri nuclear test site showed indeed that an underground man-made explosion took place, although the nuclear origin of the explosion needs confirmation. Seven weeks after the announced nuclear test, radioactive xenon was observed in Japan by a noble gas measurement station of the International Monitoring System. In this paper, atmospheric transport modelling is used to show that the measured radioactive xenon is compatible with a delayed release from the Punggye-ri nuclear test site. An uncertainty quantification on the modelling results is given by using the ensemble method. The latter is important for policy makers and helps advance data fusion, where different nuclear Test-Ban-Treaty monitoring techniques are combined.