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Methane at Svalbard and over the European Arctic Ocean
Methane (CH<sub>4</sub>) is a powerful greenhouse gas. Its atmospheric mixing ratios have been increasing since 2005. Therefore, quantification of CH<sub>4</sub> sources is essential for effective climate change mitigation. Here we report observations of the CH<sub>4</sub> mixing ratios measured at the Zeppelin Observatory (Svalbard) in the Arctic and aboard the research vessel (RV) Helmer Hanssen over the Arctic Ocean from June 2014 to December 2016, as well as the long-term CH<sub>4</sub> trend measured at the Zeppelin Observatory from 2001 to 2017. We investigated areas over the European Arctic Ocean to identify possible hotspot regions emitting CH<sub>4</sub> from the ocean to the atmosphere, and used state-of-the-art modelling (FLEXPART) combined with updated emission inventories to identify CH<sub>4</sub> sources. Furthermore, we collected air samples in the region as well as samples of gas hydrates, obtained from the sea floor, which we analysed using a new technique whereby hydrate gases are sampled directly into evacuated canisters. Using this new methodology, we evaluated the suitability of ethane and isotopic signatures (δ<sup>13</sup>C in CH<sub>4</sub>) as tracers for ocean-to-atmosphere CH<sub>4</sub> emission. We found that the average methane / light hydrocarbon (ethane and propane) ratio is an order of magnitude higher for the same sediment samples using our new methodology compared to previously reported values, 2379.95 vs. 460.06, respectively. Meanwhile, we show that the mean atmospheric CH<sub>4</sub> mixing ratio in the Arctic increased by 5.9±0.38 parts per billion by volume (ppb) per year (yr<sup>−1</sup>) from 2001 to 2017 and ∼8 pbb yr<sup>−1</sup> since 2008, similar to the global trend of ∼ 7–8 ppb yr<sup>−1</sup>. Most large excursions from the baseline CH<sub>4</sub> mixing ratio over the European Arctic Ocean are due to long-range transport from land-based sources, lending confidence to the present inventories for high-latitude CH<sub>4</sub> emissions. However, we also identify a potential hotspot region with ocean–atmosphere CH<sub>4</sub> flux north of Svalbard (80.4∘ N, 12.8∘ E) of up to 26 nmol m<sup>−2</sup>s<sup>−1</sup> from a large mixing ratio increase at the location of 30 ppb. Since this flux is consistent with previous constraints (both spatially and temporally), there is no evidence that the area of interest north of Svalbard is unique in the context of the wider Arctic. Rather, because the meteorology at the time of the observation was unique in the context of the measurement time series, we obtained over the short course of the episode measurements highly sensitive to emissions over an active seep site, without sensitivity to land-based emissions.
2018
A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation method, which relaxes model fields to observed values. Such fields are of interest to a variety of applications, such as inverse modelling, satellite retrievals, radiative forcing models and estimating global growth rates of greenhouse gases. Here, we apply this method to methane using 6 million model particles filling the global model domain. For each particle, methane mass tendencies due to emissions (based on several inventories) and loss by reaction with OH, Cl and O(1D), as well as observation data nudging were calculated. Model particles were transported by mean, turbulent and convective transport driven by 1∘×1∘ ERA-Interim meteorology. Nudging is applied at 79 surface stations, which are mostly included in the World Data Centre for Greenhouse Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) in Siberia. For simulations of 1 year (2013), we perform a sensitivity analysis to show how nudging settings affect modelled concentration fields. These are evaluated with a set of independent surface observations and with vertical profiles in North America from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional Observations in SIBeria (YAK-AEROSIB) and the National Institute for Environmental Studies (NIES). FLEXPART CTM results are also compared to simulations from the global Eulerian chemistry Transport Model version 5 (TM5) based on optimized fluxes. Results show that nudging strongly improves modelled methane near the surface, not only at the nudging locations but also at independent stations. Mean bias at all surface locations could be reduced from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART CTM, including nudging, appears better able to capture methane molar mixing ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb in TM5 simulations. The vertical profiles indicate that nudging affects model methane at high altitudes, yet leads to little improvement in the model results there. Averaged from 19 aircraft profile locations in North America and Siberia, root mean square error (RMSE) changes only from 16.3 to 15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to 8.2 ppb. The performance for vertical profiles is thereby similar to TM5 simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and RMSE of 15.9 ppb. With this rather simple model setup, we thus provide three-dimensional methane fields suitable for use as boundary conditions in regional inverse modelling as a priori information for satellite retrievals and for more accurate estimation of mean mixing ratios and growth rates. The method is also applicable to other long-lived trace gases.
2018
Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
Black carbon (BC) aerosols perturb climate and impoverish air quality/human health—affecting ∼1.5 billion people in South Asia. However, the lack of source-diagnostic observations of BC is hindering the evaluation of uncertain bottom-up emission inventories (EIs) and thereby also models/policies. Here, we present dual-isotope-based (Δ14C/δ13C) fingerprinting of wintertime BC at two receptor sites of the continental outflow. Our results show a remarkable similarity in contributions of biomass and fossil combustion, both from the site capturing the highly populated highly polluted Indo-Gangetic Plain footprint (IGP; Δ14C-fbiomass = 50 ± 3%) and the second site in the N. Indian Ocean representing a wider South Asian footprint (52 ± 6%). Yet, both sites reflect distinct δ13C-fingerprints, indicating a distinguishable contribution of C4-biomass burning from peninsular India (PI). Tailored-model-predicted season-averaged BC concentrations (700 ± 440 ng m–3) match observations (740 ± 250 ng m–3), however, unveiling a systematically increasing model-observation bias (+19% to −53%) through winter. Inclusion of BC from open burning alone does not reconcile predictions (fbiomass = 44 ± 8%) with observations. Direct source-segregated comparison reveals regional offsets in anthropogenic emission fluxes in EIs, overestimated fossil-BC in the IGP, and underestimated biomass-BC in PI, which contributes to the model-observation bias. This ground-truthing pinpoints uncertainties in BC emission sources, which benefit both climate/air-quality modeling and mitigation policies in South Asia.
2020
2018
Modelled sources of airborne microplastics collected at a remote Southern Hemisphere site
Airborne microplastics have emerged in recent years as ubiquitous atmospheric pollutants. However, data from the Southern Hemisphere, and remote regions in particular, are sparse. Here, we report airborne microplastic deposition fluxes measured during a five-week sampling campaign at a remote site in the foothills of the Southern Alps of New Zealand. Samples were collected over 24-hour periods for the first week and for 7-day periods thereafter. On average, atmospheric microplastic (MP) deposition fluxes were six times larger during the 24-hour sampling periods (150 MP m−2 day−1) than during the 7-day sampling periods (26 MP m−2 day−1), highlighting the importance of sampling frequency and deposition collector design to limit particle resuspension. Previous studies, many of which used weekly sampling frequencies or longer, may have substantially underestimated atmospheric microplastic deposition fluxes, depending on the study design. To identify likely sources of deposited microplastics, we performed simulations with a global dispersion model coupled with an emissions inventory of airborne microplastics. Modelled deposition fluxes are in good agreement with observations, highlighting the potential for this method in tracing sources of deposited microplastics globally. Modelling indicates that sea-spray was the dominant source when microplastics underwent long-range atmospheric transport, with a small contribution from road dust.
2024
10-year satellite-constrained fluxes of ammonia improve performance of chemistry transport models
In recent years, ammonia emissions have been continuously increasing, being almost 4 times higher than in the 20th century. Although an important species, as its use as a fertilizer sustains human living, ammonia has major consequences for both humans and the environment because of its reactive gas-phase chemistry that makes it easily convertible to particles. Despite its pronounced importance, ammonia emissions are highly uncertain in most emission inventories. However, the great development of satellite remote sensing nowadays provides the opportunity for more targeted research on constraining ammonia emissions. Here, we used satellite measurements to calculate global ammonia emissions over the period 2008–2017. Then, the calculated ammonia emissions were fed to a chemistry transport model, and ammonia concentrations were simulated for the period 2008–2017.
The simulated concentrations of ammonia were compared with ground measurements from Europe, North America and Southeastern Asia, as well as with satellite measurements. The satellite-constrained ammonia emissions represent global concentrations more accurately than state-of-the-art emissions. Calculated fluxes in the North China Plain were seen to be more increased after 2015, which is not due to emission changes but due to changes in sulfate emissions that resulted in less ammonia neutralization and hence in larger atmospheric loads. Emissions over Europe were also twice as much as those in traditional datasets with dominant sources being industrial and agricultural applications. Four hot-spot regions of high ammonia emissions were seen in North America, which are characterized by high agricultural activity, such as animal breeding, animal farms and agricultural practices. South America is dominated by ammonia emissions from biomass burning, which causes a strong seasonality. In Southeastern Asia, ammonia emissions from fertilizer plants in China, Pakistan, India and Indonesia are the most important, while a strong seasonality was observed with a spring and late summer peak due to rice and wheat cultivation. Measurements of ammonia surface concentrations were better reproduced with satellite-constrained emissions, such as measurements from CrIS (Cross-track Infrared Sounder).
2021
Procellariiform seabirds like northern fulmars (Fulmarus glacialis) are prone to ingest and accumulate floating plastic pieces. In the North Sea region, there is a long tradition to use beached fulmars as biomonitors for marine plastic pollution. Monitoring data revealed consistently lower plastic burdens in adult fulmars compared to younger age classes. Those findings were hypothesized to partly result from parental transfer of plastic to chicks. However, no prior study has examined this mechanism in fulmars by comparing plastic burdens in fledglings and older fulmars shortly after the chick-rearing period. Therefore, we investigated plastic ingestion in 39 fulmars from Kongsfjorden (Svalbard), including 21 fledglings and 18 older fulmars (adults/older immatures). We found that fledglings (50–60 days old) had significantly more plastic than older fulmars. While plastic was found in all fledglings, two older fulmars contained no and several older individuals barely any plastic. These findings supported that fulmar chicks from Svalbard get fed high quantities of plastic by their parents. Adverse effects of plastic on fulmars were indicated by one fragment that perforated the stomach and possibly one thread perforating the intestine. Negative correlations between plastic mass and body fat in fledglings and older fulmars were not significant.
2023
Air quality mitigation in European cities: Status and challenges ahead
Cities are currently at the core of air quality (AQ) improvement. The present work provides an overview of AQ management strategies and outcomes in 10 European cities (Antwerp, Berlin, Dublin, Madrid, Malmö, Milan, Paris, Plovdiv, Prague, Vienna) in 2018, and their evolution since 2013 (same cities, plus Ploiesti and Vilnius), based on first-hand input from AQ managers. The status of AQ mitigation in 2018, and its evolution since 2013, were assessed. While results evidenced that the majority of mitigation strategies targeted road traffic, emerging sources such as inland shipping, construction/demolition and recreational wood burning were identified. Several cities had in 2018 the ambition to continue decreasing air pollution concentrations to meet WHO guidelines, an ambition which had not yet been identified in 2013. Specific needs identified by all of the cities assessed were tools to quantify the effectiveness of mitigation strategies and for cost-benefit analysis, as well as specific and up to date technical guidance on real-world road vehicle emissions. The cities also requested guidance to identify mitigation measures promoting co-benefits, e.g., in terms of AQ, climate change, and noise. Support from administrations at local-regional-national-EU scales, and especially involving local policy-makers early on in the air quality management process, was considered essential. This work provides insight into the drivers of successful/unsuccessful AQ policies as well as on the challenges faced during their implementation. We identify knowledge gaps and provide input to the research and policy-making communities as to specific needs of cities.
2020
The who, why and where of Norway's CO
We present emissions from Norway’s tourist travel by the available transport modes, i.e., aviation, maritime (ferries and cruises) and land-based transport (road and railways). Our study includes detailed information on both domestic and international tourist travel within, from and to Norway. We have coupled statistics from several large surveys with detailed emission data to allow us to separate the purpose of the travel (holiday or business).
Total transport emissions for tourists in 2018 were estimated to be 8 530 kt, equivalent to 19% of the reported Norwegian national emissions. Of these emissions, international tourists visiting Norway were responsible for 3 273 kt , whereas travel by Norwegians accounted for 4 875 kt , most of which occur outside Norway’s reporting obligations. Aviation and maritime transport were found to be the largest emission sources, responsible for 71% and 21% of total emissions, respectively. The reduction due to the COVID-19 pandemic was approximately 60% in 2020, and was sustained throughout the year.
Our study shows that officially reported emissions, as limited to the countries territory, are not suitable for accurate evaluation of transport emissions related to tourism. A consumer or tourist-based calculation gives a marked redistribution of emission responsibility. Our results indicate that emissions from Norwegian residents travelling abroad are 1 602 kt higher than those from tourists coming to Norway. This is driven by frequent trips to popular tourist destinations such as Spain, Thailand, Turkey and Greece. Globally consumer based calculations would shift the responsibility of emissions by tourists to the large wealthy nations, with the most international tourists. The understanding of emission distributed by population group or market support in addition the developing of marketing strategies to attract low emission tourist markets and create awareness among the nations with higher shares of international tourist.
2021
Per and polyfluoroalkyl substances (PFASs) are found in Antarctic wildlife, with high levels in the avian top predator south polar skua (Catharacta maccormicki). As increasing PFAS concentrations were found in the south polar skua during the breeding season in Antarctica, we hypothesised that available prey during the breeding period contributes significantly to the PFAS contamination in skuas. To test this, we compared PFAS in south polar skuas and their main prey from two breeding sites on opposite sides of the Antarctic continent: Antarctic petrel (Thalassoica antarctica) stomach content, eggs, chicks, and adults from Svarthamaren in Dronning Maud Land and Adélie penguin chicks (Pygoscelis adeliae) from Dumont d’Urville in Adélie Land. Of the 22 PFAS analysed, seven were present in the majority of samples, except petrel stomach content [only perfluoroundecanoate (PFUnA) present] and Adélie penguins (only four compounds present), with increasing concentrations from the prey to the skuas. The biomagnification factors (BMFs) were higher at Dumont d’Urville than Svarthamaren. When adjusted to reflect one trophic level difference, the BMFs at Svarthamaren remained the same, whereas the ones at Dumont d’Urville doubled. At both the colonies, the skua PFAS pattern was dominated by perfluorooctanesulfonic acid (PFOS), followed by PFUnA, but differed with the presence of branched PFOS and perfluorotetradecanoate (PFTeA) and lack of perfluorononanoate (PFNA) and perfluorodecanoate (PFDA) at Dumont d’Urville. At Svarthamaren, the pattern in the prey was comparable to the skuas, but with a higher relative contribution of PFTeA in prey. At Dumont d’Urville, the pattern in the prey differed from the skuas, with the domination of PFUnA and the general lack of PFOS in prey. Even though the PFAS levels are low in Antarctic year-round resident prey, the three lines of evidence (pattern, BMF difference, and BMF adjusted to one trophic level) suggest that the Antarctic petrel are the significant source of PFAS in the Svarthamaren skuas, whereas the skuas in Dumont d’Urville have other important sources to PFAS than Adélie penguin, either in the continent or external on the inter-breeding foraging grounds far from Antarctica.
2022
We present here emissions estimated from a newly developed emission model for residential wood combustion (RWC) at high spatial and temporal resolution, which we name the MetVed model. The model estimates hourly emissions resolved on a 250 m grid resolution for several compounds, including particulate matter (PM), black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) in Norway for a 12-year period. The model uses novel input data and calculation methods that combine databases built with an unprecedented high level of detail and near-national coverage. The model establishes wood burning potential at the grid based on the dependencies between variables that influence emissions: i.e. outdoor temperature, number of and type and size of dwellings, type of available heating technologies, distribution of wood-based heating installations and their associated emission factors. RWC activity with a 1 h temporal profile was produced by combining heating degree day and hourly and weekday activity profiles reported by wood consumers in official statistics. This approach results in an improved characterisation of the spatio-temporal distribution of wood use, and subsequently of emissions, required for urban air quality assessments. Whereas most variables are calculated based on bottom-up approaches on a 250 m spatial grid, the MetVed model is set up to use official wood consumption at the county level and then distributes consumption to individual grids proportional to the physical traits of the residences within it. MetVed combines consumption with official emission factors that makes the emissions also upward scalable from the 250 m grid to the national level.
The MetVed spatial distribution obtained was compared at the urban scale to other existing emissions at the same scale. The annual urban emissions, developed according to different spatial proxies, were found to have differences up to an order of magnitude. The MetVed total annual PM2.5 emissions in the urban domains compare well to emissions adjusted based on concentration measurements. In addition, hourly PM2.5 concentrations estimated by an Eulerian dispersion model using MetVed emissions were compared to measurements at air quality stations. Both hourly daily profiles and the seasonality of PM2.5 show a slight overestimation of PM2.5 levels. However, a comparison with black carbon from biomass burning and benzo(a)pyrene measurements indicates higher emissions during winter than that obtained by MetVed. The accuracy of urban emissions from RWC relies on the accuracy of the wood consumption (activity data), emission factors and the spatio-temporal distribution. While there are still knowledge gaps regarding emissions, MetVed represents a vast improvement in the spatial and temporal distribution of RWC.
2019
Method for retrieval of aerosol optical depth from multichannel irradiance measurements
We present, to the best of our knowledge, a new method for retrieval of aerosol optical depth from multichannel irradiance measurements. A radiative transfer model is used to simulate measurements to create the new aerosol optical depth retrieval method. A description of the algorithm, simulations, proof of principle, merits, possible future developments and implementations is provided. As a demonstration, measurements in the New York City area are simulated based on the specific channel configuration of an existing multichannel irradiance instrument. Verification of the method with irradiance measurement data is also provided.
2023
Personalized approaches are required for stroke management due to the variability in symptoms, triggers, and patient characteristics. An innovative stroke recommendation system that integrates automatic predictive analysis with semantic knowledge to provide personalized recommendations for stroke management is proposed by this paper. Stroke exacerbation are predicted and the recommendations are enhanced by the system, which leverages automatic Tree-based Pipeline Optimization Tool (TPOT) and semantic knowledge represented in an OWL Ontology (StrokeOnto). Digital sovereignty is addressed by ensuring the secure and autonomous control over patient data, supporting data sovereignty and compliance with jurisdictional data privacy laws. Furthermore, classifications are explained with Local Interpretable Model-Agnostic Explanations (LIME) to identify feature importance. Tailored interventions based on individual patient profiles are provided by this conceptual model, aiming to improve stroke management. The proposed model has been verified using public stroke dataset, and the same dataset has been utilized to support ontology development and verification. In TPOT, the best Variance Threshold + DecisionTree Classifier pipeline has outperformed other supervised machine learning models with an accuracy of 95.2%, for the used datasets. The Variance Threshold method reduces feature dimensionality with variance below a specified threshold of 0.1 to enhance predictive accuracy. To implement and evaluate the proposed model in clinical settings, further development and validation with more diverse and robust datasets are required.
2025
The Troll Observing Network (TONe): plugging observation holes in Dronning Maud Land, Antarctica
Understanding how Antarctica is changing and how these changes influence the rest of the Earth is fundamental to the future robustness of human society. Strengthening our understanding of these changes and their implications requires dedicated, sustained and coordinated observations of key Antarctic indicators. The Troll Observing Network (TONe), now under development, is Norway’s contribution to the global need for sustained, coordinated, complementary and societally relevant observations from Antarctica. When fully implemented within the coming three years, TONe will be a state-of-the-art, multi-platform, multi-disciplinary observing network in data-sparse Dronning Maud Land. A critical part of the network is a data management system that will ensure broad, free access to all TONe data to the international research community.
2024
Extreme precipitation events in Norway in all seasons are often linked to atmospheric rivers (AR). We show that during the period 1979–2018 78.5% of the daily extreme precipitation events in Southwestern Norway are linked to ARs, this percentage decreasing to 59% in the more northern coastal regions and ~40% in the inland regions. The association of extreme precipitation with AR occurs most often in fall for the coastal areas and in summer inland. All Norwegian regions experience stronger winds and 1–2°C increase of the temperature at 850 hPa during AR events compared to the climatology, the extreme precipitation largely contributing to the wet climatology (only considering rainy days) in Norway but also in Denmark and Sweden when the rest of Europe is dry. A cyclone is found nearby the AR landfall point in 70% of the cases. When the cyclone is located over the British Isles, as it is typically the case when ARs reach Southeastern Norway, it is associated with cyclonic Rossby wave breaking whereas when the ARs reach more northern regions, anticyclonic wave breaking occurs over Northern Europe. Cyclone-centered composites show that the mean sea level pressure is not significantly different between the eight Norwegian regions, that baroclinic interaction can still take place although the cyclone is close to its decay phase and that the maximum precipitation occurs ahead of the AR. Lagrangian air parcel tracking shows that moisture uptake mainly occurs over the North Atlantic for the coastal regions with an additional source over Europe for the more eastern and inland regions.
2021
Top-down approaches, such as atmospheric inversions, are a promising tool for evaluating emission estimates based on activity-data. In particular, there is a need to examine carbon budgets at subnational scales (e.g. state/province), since this is where the climate mitigation policies occur. In this study, the subnational scale anthropogenic CO2 emissions are estimated using a high-resolution global CO2 inverse model. The approach is distinctive with the use of continuous atmospheric measurements from regional/urban networks along with background monitoring data for the period 2015–2019 in global inversion. The measurements from several urban areas of the U.S., Europe and Japan, together with recent high-resolution emission inventories and data-driven flux datasets were utilized to estimate the fossil emissions across the urban areas of the world. By jointly optimizing fossil fuel and natural fluxes, the model is able to contribute additional information to the evaluation of province–scale emissions, provided that sufficient regional network observations are available. The fossil CO2 emission estimates over the U.S. states such as Indiana, Massachusetts, Connecticut, New York, Virginia and Maryland were found to have a reasonable agreement with the Environmental Protection Agency (EPA) inventory, and the model corrects the emissions substantially towards the EPA estimates for California and Indiana. The emission estimates over the United Kingdom, France and Germany are comparable with the regional inventory TNO–CAMS. We evaluated model estimates using independent aircraft observations, while comparison with the CarbonTracker model fluxes confirms ability to represent the biospheric fluxes. This study highlights the potential of the newly developed inverse modeling system to utilize the atmospheric data collected from the regional networks and other observation platforms for further enhancing the ability to perform top-down carbon budget assessment at subnational scales and support the monitoring and mitigation of greenhouse gas emissions.
2023
Public Perception of Urban Air Quality Using Volunteered Geographic Information Services
Investigating perceived air quality (AQ) in urban areas is a rather new topic of interest. Papers presenting results from studies on perception of AQ have thus far focused on the individual characteristics leading to a certain AQ perception or have compared personal perception with on-site measurements. Here we present a novel approach, namely applying volunteered geographic information (VGI) technologies in urban AQ monitoring. We present two smartphone applications that have been developed and applied in two EU projects (FP7 CITI-SENSE and H2020 hackAIR) to obtain citizens’ perception of AQ. We focus on observations reported through the smartphone apps for the greater Oslo area in Norway. In order to evaluate whether the reports on perceived AQ contain information about the actual spatial patterns of AQ, we carried out a comparison of the perception data against the output from the high-resolution urban AQ model EPISODE. The results indicate an association between modelled annual average pollutant concentrations and the provided perception reports. This demonstrates that the spatial patterns of perceived AQ are not entirely random but follow to some extent what would be expected due to proximity of emission sources and transport. This information shows that VGI about citizens’ perception of AQ has the potential to identify areas with low environmental quality for urban development.
2020
Roadmap for action for advancing aggregate exposure to chemicals in the EU
The European Food Safety Authority (EFSA) has a goal to efficiently conduct aggregate exposure assessments (AEAs) for chemicals using both exposure models and human biomonitoring (HBM) data by 2030. To achieve EFSA's vision, a roadmap for action for advancing aggregate exposure (AE) in the EU was developed. This roadmap was created by performing a series of engagement and data collection activities to map the currently available methods, data, and tools for assessing AE of chemicals, against the needs and priorities of EFSA. This allowed for the creation of a AEA framework, identification of data and knowledge gaps in our current capabilities, and identification of the challenges and blockers that would hinder efforts to fill the gaps. The roadmap identifies interdependent working areas (WAs) where additional research and development are required to achieve EFSA's goal. It also proposes future collaboration opportunities and recommends several project proposals to meet EFSA's goals. Eight proposal projects supported by SWOT analysis are presented for EFSA's consideration. The project proposals inform high-level recommendations for multi-annual and multi-partner projects. Recommendations to improve stakeholder engagement and communication of EFSA's work on AEA were gathered by surveying stakeholders on specific actions to improve EFSA's communication on AE, including webinars, virtual training, social media channels, and newsletters.
2024
Intrusion Detection Systems (IDS) are critical in safeguarding network infrastructures against malicious attacks. Traditional IDSs often struggle with knowledge representation, real-time detection, and accuracy, especially when dealing with high-throughput data. This paper proposes a novel IDS framework that leverages machine learning models, streaming data, and semantic knowledge representation to enhance intrusion detection accuracy and scalability. Additionally, the study incorporates the concept of Digital Sovereignty, ensuring that data control, security, and privacy are maintained according to national and regional regulations. The proposed system integrates Apache Kafka for real-time data processing, an automatic machine learning pipeline (e.g., Tree-based Pipeline Optimization Tool (TPOT)) for classifying network traffic, and OWL-based semantic reasoning for advanced threat detection. The proposed system, evaluated on NSL-KDD and CIC-IDS-2017 datasets, demonstrated qualitative outcomes such as local compliance, reduced data storage needs due to real-time processing, and improved adaptability to local data laws. Experimental results reveal significant improvements in detection accuracy, processing efficiency, and Sovereignty alignment.
2025
2021
Aerosol particles are major short-lived climate forcers, because of their ability to interact with incoming solar radiation. Therefore, addressing mean levels and sources of Arctic aerosols is of high importance in the battle against climate change, due to the Arctic amplification. In the Eastern Arctic, from Finland to Alaska, only one monitoring station exists (HMO Tiksi) and the levels of the Arctic aerosols are usually recorded by sporadic campaigns, while other stations exist in Canada, Finland and Europe. From April 2015 to December 2016, the research station "Ice Base Cape Baranova" (79°16.82'N, 101°37.05'E), located on the Bolshevik island was established in the Siberian high Arctic. Samples were analyzed for equivalent Black Carbon (eBC), Organic Carbon (OC), Elemental Carbon (EC), water-soluble ions, and elements. To identify the spatial origin of the sources, the Potential Source Contributions Function (PSCF) was used in combination with FLEXPART emission sensitivities. OC is the most dominant PM compound in the Ice Cape Baranova station and mostly originates from gas flaring and other industrial regions at lower latitudes, as well as from biomass burning during summertime. Sulfate concentrations were affected by anthropogenic sources in the cold seasons and by natural sources in the warm ones showing distinct seasonal patterns. K+ and Mg2+ originate from sea-salt in winter and from forest fires in summer. The interannual variability of eBC was in good agreement with the general Arctic seasonal trends and was mainly affected by gas flaring, low latitude industrial sources and from biomass burning emissions. Cl− depletion was very low, while Na+ and Cl− originated from the locally formed sea spray.
2020
Air pollution is an important cause of adverse health effects, even in the Nordic countries, which have relatively good air quality. Modelling-based air quality assessment of the health impacts relies on reliable model estimates of ambient air pollution concentrations, which furthermore rely on good-quality spatially resolved emission data. While quantitative emission estimates are the cornerstone of good emission data, description of the spatial distribution of the emissions is especially important for local air quality modelling at high resolution. In this paper we present a new air pollution emission inventory for the Nordic countries with high-resolution spatial allocation (1 km × 1 km) covering the years 1990, 1995, 2000, 2005, 2010, 2012, and 2014. The inventory is available at https://doi.org/10.5281/zenodo.10571094 (Paunu et al., 2023). To study the impact of applying national data and methods to the spatial distribution of the emissions, we compared road transport and machinery and off-road sectors to CAMS-REGv4.2, which used a consistent spatial distribution method throughout Europe for each sector. Road transport is a sector with well-established proxies for spatial distribution, while for the machinery and off-road sector, the choice of proxies is not as straightforward as it includes a variety of different type of vehicles and machines operating in various environments. We found that CAMS-REGv4.2 was able to produce similar spatial patterns to our Nordic inventory for the selected sectors. However, the resolution of our Nordic inventory allows for more detailed impact assessment than CAMS-REGv4.2, which had a resolution of 0.1° × 0.05° (longitude–latitude, roughly 5.5 km × 3.5–6.5 km in the Nordic countries). The EMEP/EEA Guidebook chapter on spatial mapping of emissions has recommendations for the sectoral proxies. Based on our analysis we argue that the guidebook should have separate recommendations for proxies for several sub-categories of the machinery and off-road sectors, instead of including them within broader sectors. We suggest that land use data are the best starting point for proxies for many of the subsectors, and they can be combined with other suitable data to enhance the spatial distribution. For road transport, measured traffic flow data should be utilized where possible, to support modelled data in the proxies.
2024
Forecasting the Exceedances of PM2.5 in an Urban Area
Particular matter (PM) constitutes one of the major air pollutants. Human exposure to fine PM (PM with a median diameter less than or equal to 2.5 μm, PM2.5) has many negative and diverse outcomes for human health, such as respiratory mortality, lung cancer, etc. Accurate air-quality forecasting on a regional scale enables local agencies to design and apply appropriate policies (e.g., meet specific emissions limitations) to tackle the problem of air pollution. Under this framework, low-cost sensors have recently emerged as a valuable tool, facilitating the spatiotemporal monitoring of air pollution on a local scale. In this study, we present a deep learning approach (long short-term memory, LSTM) to forecast the intra-day air pollution exceedances across urban and suburban areas. The PM2.5 data used in this study were collected from 12 well-calibrated low-cost sensors (Purple Air) located in the greater area of the Municipality of Thermi in Thessaloniki, Greece. The LSTM-based methodology implements PM2.5 data as well as auxiliary data, meteorological variables from the Copernicus Atmosphere Monitoring Service (CAMS), which is operated by ECMWF, and time variables related to local emissions to enhance the air pollution forecasting performance. The accuracy of the model forecasts reported adequate results, revealing a correlation coefficient between the measured PM2.5 and the LSTM forecast data ranging between 0.67 and 0.94 for all time horizons, with a decreasing trend as the time horizon increases. Regarding air pollution exceedances, the LSTM forecasting system can correctly capture more than 70.0% of the air pollution exceedance events in the study region. The latter findings highlight the model’s capabilities to correctly detect possible WHO threshold exceedances and provide valuable information regarding local air quality.
2024
Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. ...
2023