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Citizen-operated low-cost air quality sensors (LCSs) have expanded air quality monitoring through community engagement. However, still challenges related to lack of semantic standards, data quality, and interoperability hinder their integration into official air quality assessments, management, and research. Here, we introduce FILTER, a geospatially scalable framework designed to unify, correct, and enhance the reliability of crowd-sourced PM2.5 data across various LCS networks. FILTER assesses data quality through five steps: range check, constant value detection, outlier detection, spatial correlation, and spatial similarity. Using official data, we modeled PM2.5 spatial correlation and similarity (Euclidean distance) as functions of geographic distance as benchmarks for evaluating whether LCS measurements are sufficiently correlated/consistent with neighbors. Our study suggests a −10 to 10 Median Absolute Deviation threshold for outlier flagging (360 h). We find higher PM2.5 spatial correlation in DJF compared to JJA across Europe while lower PM2.5 similarity in DJF compared to JJA. We observe seasonal variability in the maximum possible distance between sensors and reference stations for in-situ (remote) PM2.5 data correction, with optimal thresholds of ∼11.5 km (DJF), ∼12.7 km (MAM), ∼20 km (JJA), and ∼17 km (SON). The values implicitly reflect the spatial representativeness of stations. ±15 km relaxation for each season remains feasible when data loss is a concern. We demonstrate and validate FILTER's effectiveness using European-scale data originating from the two community-based monitoring networks, sensor.community and PurpleAir with QC-ed/corrected output including 37,085 locations and 521,115,762 hourly timestamps. Results facilitate uptake and adoption of crowd-sourced LCS data in regulatory applications.
Elsevier
2025
We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios, using both the prescribed GHG concentrations as well as the interactive CH4 sources and sinks setup of the model, to quantify the model performance and its sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the maximum feasible reduction (MFR) emission scenarios from the ECLIPSE V6b emission database to simulate the future evolution of CH4 sources, sinks, and levels from 2015 to 2050. Results show that the prescribed GHG version underestimates the observed surface CH4 concentrations during the period between 1995 and 2023 by 1%, with the largest underestimations over the continental emission regions, while the interactive simulation underestimates the observations by 2%, with the biases largest over oceans and smaller over the continents. For the future, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day. In addition, the interactive simulation calculates slightly larger O3 and OH mixing ratios, in particular over the northern hemisphere, leading to slightly decreased CH4 lifetime in the present day. The CH4 forcing is projected to increase in both scenarios, in particular in the CLE scenario, from 0.53 W m−2 in the present day to 0.73 W m−2 in 2050. In addition, the interactive simulations estimate slightly higher tropospheric O3 forcing compared to prescribed simulations, due to slightly higher O3 mixing ratios simulated by the interactive models. While in the CLE, tropospheric O3 forcing continues to increase, the MFR scenario leads to a decrease in tropospheric O3 forcing, leading to a climate benefit. Our results highlight that in the interactive models, the response of concentrations are not necessarily linear with the changes in emissions as the chemistry is non-linear, and dependent on the oxidative capacity of the atmosphere. Therefore, it is important to have the CH4 sources and chemical sinks to be represented comprehensively in climate models.
IOP Publishing
2025
Unchanged PM2.5 levels over Europe during COVID-19 were buffered by ammonia
The coronavirus outbreak in 2020 had a devastating impact on human life, albeit a positive effect on the environment, reducing emissions of primary aerosols and trace gases and improving air quality. In this paper, we present inverse modelling estimates of ammonia emissions during the European lockdowns of 2020 based on satellite observations. Ammonia has a strong seasonal cycle and mainly originates from agriculture. We further show how changes in ammonia levels over Europe, in conjunction with decreases in traffic-related atmospheric constituents, modulated PM2.5. The key result of this study is a −9.8 % decrease in ammonia emissions in the period of 15 March–30 April 2020 (lockdown period) compared to the same period in 2016–2019, attributed to restrictions related to the global pandemic. We further calculate the delay in the evolution of the ammonia emissions in 2020 before, during, and after lockdowns, using a sophisticated comparison of the evolution of ammonia emissions during the same time periods for the reference years (2016–2019). Our analysis demonstrates a clear delay in the evolution of ammonia emissions of −77 kt, which was mainly observed in the countries that imposed the strictest travel, social, and working measures. Despite the general drop in emissions during the first half of 2020 and the delay in the evolution of the emissions during the lockdown period, satellite and ground-based observations showed that the European levels of ammonia increased. On one hand, this was due to the reductions in SO2 and NOx (precursors of the atmospheric acids with which ammonia reacts) that caused less binding and thus less chemical removal of ammonia (smaller loss – higher lifetime). On the other hand, the majority of the emissions persisted because ammonia mainly originates from agriculture, a primary production sector that was influenced very little by the lockdown restrictions. Despite the projected drop in various atmospheric aerosols and trace gases, PM2.5 levels stayed unchanged or even increased in Europe due to a number of reasons that were attributed to the complicated system. Higher water vapour during the European lockdowns favoured more sulfate production from SO2 and OH (gas phase) or O3 (aqueous phase). Ammonia first reacted with sulfuric acid, also producing sulfate. Then, the continuously accumulating free ammonia reacted with nitric acid, shifting the equilibrium reaction towards particulate nitrate. In high-free-ammonia atmospheric conditions such as those in Europe during the 2020 lockdowns, a small reduction in NOx levels drives faster oxidation toward nitrate and slower deposition of total inorganic nitrate, causing high secondary PM2.5 levels.
2025
A pooled analysis of host factors that affect nucleotide excision repair in humans
Oxford University Press
2025
VKM has assessed the positive and negative effects on biodiversity were sterile salmon to be used in Norwegian aquaculture. Triploidisation is assessed as the most effective method for sterilising fish, but it can affect the welfare and health of the fish.
Several other techniques for producing sterile salmon are being tested, but it is too early to determine whether they can be used in large-scale farming.
This is the key message in a knowledge summary VKM has prepared for the Norwegian Environment Agency.
Background
Escaped farmed salmon poses a major threat to wild salmon in Norway. hey can interbreed with wild salmon, genetically alter them, and make the populations less adaptable and more vulnerable to disease and environmental changes. A possible solution to the problem may be to use sterile salmon in farming.
To date, only triploidisation has been tested. Newly fertilised eggs are given a hydrostatic pressure shock, thereby retaining an extra set of chromosomes which render the fish sterile. This method is currently the only one tested on a large scale. Triploidisation is effective but can also pose health and welfare challenges to fish.
Methods
VKM has reviewed available scientific literature regarding methods that can be used to produce sterile salmon. VKM has assessed whether these methods work as well, or better, than triploidy and whether they are likely to have fewer negative effects on fish welfare. Assessments have also been made of whether farmed fish treated with other sterilisation methods pose a greater or lesser threat to wild salmon than traditional farmed salmon.
VKM has looked at the possibilities for further development of the triploidisation technique and has also assessed various methods currently being tested for producing sterile fish. Some of these are still at the laboratory-testing stage, while others are approaching trials with release into sea-pens. VKM has grouped the different methods based on whether they cause permanent changes in the genome (so-called "knock-out" of important genes) or whether the changes only result in temporary blocking or downregulation of gene expression (so-called "knock-down").
Results
VKM concludes that triploidisation remains the most effective method and that there are possibilities to further develop this methodology through targeted breeding and adjustments in how the fish are kept. These measures can potentially solve the challenges for fish health and welfare. Using pure triploid female lines can also reduce some of the other challenges by preventing spawning interactions in rivers and reducing disease transmission to wild salmon.
Alternative sterilisation methods, such as gene editing, vaccination, and temporary downregulation of proteins for gonad development using antisense oligomers and egg immersion, are promising but still under development.
VKM assesses that methods causing permanent changes in the genome of diploid fish have a higher inherent risk than methods that only affect gene expression.
Hope in egg-bathing
Perhaps the most promising technique for safe production of sterile salmon is to add synthetic oligonucleotides to the eggs at an early stage, thereby preventing germ cell development without causing any inheritable changes. Such oligonucleotides can be injected into the eggs or absorbed by the eggs through bathing (immersion) in a special solution.
"Especially the method involving targeted 'tools,' such as oligonucleotides that prevent germ cell development and can be added to the eggs in a water bath, seems promising," says Johanna Bodin, member of the Panel for Genetically Modified organisms and spokesperson for the report.
(...)
2025
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.
Elsevier
2025
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.
Elsevier
2025
This study critically examines the workflow for untargeted analysis of volatile organic compounds (VOCs) in ambient air, from sampling strategies to data interpretation by using GC-HRMS. While untargeted approaches are well-established in liquid chromatography (LC) due to advanced-deconvolution tools and extensive metabolomic libraries, their application in gas chromatography (GC) remains less developed, particularly for VOCs. The high structural isomerism of VOCs and the relative novelty of GC-based untargeted methodologies present unique challenges, including limited software tools and reference libraries. Air samples from suburban and rural sites in central Italy were analyzed to explore chemical diversity and address methodological gaps. This study evaluates critical decisions, such as sampling strategies, extraction techniques, and data-processing workflows, highlighting the limitations of automated deconvolution tools and the need for manual validation. Results revealed distinct source contributions, with suburban areas showing higher levels of anthropogenic compounds and rural areas dominated by biogenic emissions. This work underscores the potential of GC-HRMS untargeted analysis to advance environmental chemistry, while addressing key pitfalls and providing practical recommendations for reliable application. By bridging methodological gaps, it offers a roadmap for future studies aiming to integrate untargeted and targeted approaches in air quality research.
MDPI
2025
The apportionment of equivalent black carbon (eBC) to combustion sources from liquid fuels (mainly fossil; eBCLF) and solid fuels (mainly non-fossil; eBCSF) is commonly performed using data from Aethalometer instruments (AE approach). This study evaluates the feasibility of using AE data to determine the absorption Ångström exponents (AAEs) for liquid fuels (AAELF) and solid fuels (AAESF), which are fundamental parameters in the AE approach. AAEs were derived from Aethalometer data as the fit in a logarithmic space of the six absorption coefficients (470–950 nm) versus the corresponding wavelengths. The findings indicate that AAELF can be robustly determined as the 1st percentile (PC1) of AAE values from fits with R2 > 0.99. This R2-filtering was necessary to remove extremely low and noisy-driven AAE values commonly observed under clean atmospheric conditions (i.e., low absorption coefficients). Conversely, AAESF can be obtained from the 99th percentile (PC99) of unfiltered AAE values. To optimize the signal from solid fuel sources, winter data should be used to calculate PC99, whereas summer data should be employed for calculating PC1 to maximize the signal from liquid fuel sources. The derived PC1 (AAELF) and PC99 (AAESF) values ranged from 0.79 to 1.08, and 1.45 to 1.84, respectively. The AAESF values were further compared with those constrained using the signal at mass-to-charge 60 (m/z 60), a tracer for fresh biomass combustion, measured using aerosol chemical speciation monitor (ACSM) and aerosol mass spectrometry (AMS) instruments deployed at 16 sites. Overall, the AAESF values obtained from the two methods showed strong agreement, with a coefficient of determination (R2) of 0.78. However, uncertainties in both approaches may vary due to site-specific sources, and in certain environments, such as traffic-dominated sites, neither approach may be fully applicable.
Elsevier
2025
Permafrost is a considerable carbon reservoir harboring up to 1700 petagrams of carbon accumulated over millennia, which can be mobilized as permafrost thaws under global warming. Recent studies have highlighted that a fraction of this carbon can be transformed to atmospheric volatile organic compounds, which can affect the atmospheric oxidizing capacity and contribute to the formation of secondary organic aerosols. In this study, active layer soils from the seasonally unfrozen layer above the permafrost were collected from two distinct locations of the Greenlandic permafrost and incubated to explore their roles in the soil-atmosphere exchange of volatile organic compounds. Results show that these soils can actively function as sinks of these compounds, despite their different physiochemical properties. Upper active layer possessed relatively higher uptake capacities; factors including soil moisture, organic matter, and microbial biomass carbon were identified as the main factors correlating with the uptake rates. Additionally, uptake coefficients for several compounds were calculated for their potential use in future model development. Correlation analysis and the varying coefficients indicate that the sink was likely biotic. The development of a deeper active layer under climate change may enhance the sink capacity and reduce the net emissions of volatile organic compounds from permafrost thaw.
Springer Nature
2025