Norwegian Institute for Air Research

<strong class="journal-contentHeaderColor">Abstract.</strong> During summer 2023, Greece experienced one of its most severe wildfire seasons in recent decades, with widespread fires across Evros, Rodopi, Attica, the Peloponnese, and several islands. This study investigates the aerosol optical and microphysical properties, as well as the impact on ground-level ultraviolet-B (UVB) radiation over Athens, focusing on two major wildfire episodes (18&ndash;21 July and 22&ndash;25 August). A synergistic approach was deployed, combining satellite imagery (MODIS), FLEXPART simulations, ground-based remote sensing, and in situ aerosol and radiation measurements. Elevated aerosol optical depths (AOD) up to 1.2, high fine-mode fractions (&gt; 0.85), and &Aring;ngstr&ouml;m exponents above 1.5 indicated a strong dominance of fine biomass burning aerosols. The Single scattering albedo (SSA) ranged from 0.85 to 0.98, showing enhanced absorption during biomass burning periods and weaker absorption when smoke was mixed with dust. At 320 nm, dust presence resulted in stronger absorption, with SSA below 0.8 for pure dust cases compared to smoke mixtures. Particle linear depolarization ratios (PLDR), varied between 0.03 and 0.20, with higher values (~0.10&ndash;0.20) reflecting the presence of non-spherical dust particles, and lower values (~0.03&ndash;0.08) indicating spherical smoke particles. Ground-level UVB irradiance decreased by up to 50 % during peak smoke episodes, highlighting strong aerosol radiative impacts. Concurrently, PM₁₀ and PM_2.5 concentrations increased to 94 and 49 &micro;g m^-3, respectively, while organic aerosols peaked at 22.77 &micro;g m^-3, consistent with intense fire activity. FLEXPART simulations confirmed long-range transport of smoke from active fire regions, with additional contributions from regional pollution and Saharan dust.

Abstract. Fire is a global phenomenon and a key Earth system process. Extreme fire events have increased in recent years, and fire frequency and intensity are projected to rise across most regions and biomes, posing substantial challenges for ecosystems, the carbon cycle, and society. The Fire Model Intercomparison Project (FireMIP), launched in 2014, has contributed to advancing global fire modeling in Dynamic Global Vegetation Models (DGVMs) and improving understanding of fire's local drivers and local impacts on vegetation and land carbon budgets through land offline (i.e., uncoupled from the atmosphere) simulations. We now bring FireMIP into Coupled Model Intercomparison Project Phase 7 (CMIP7) to: (1) evaluate fire simulations in state-of-the-art fully coupled Earth system models (ESMs); (2) assess fire regime changes in the past, present, and future, and identify their primary natural and anthropogenic forcings and causal pathways within the Earth system, including the associated uncertainties; and (3) quantify the impacts of fires and fire changes on climate, ecosystems, and society across Earth system components, regions, and timescales, and elucidate the underlying mechanisms. FireMIP in CMIP7 will advance the fire and fire-related modeling in fully coupled ESMs, and provide a quantitative, detailed, and process-based understanding of fire's role in the Earth system by using models that incorporate critical climate feedbacks and multi-model, multi-initial-condition, and CMIP7 multi-scenario ensembles. This paper presents the motivation, scientific questions, experimental design and its rationale, model inputs and outputs, and the analysis framework for FireMIP in CMIP7, providing guidance for Earth system modeling teams conducting simulations and informing communities studying fire, climate change, and climate solutions.

<strong class="journal-contentHeaderColor">Abstract.</strong> This study assesses trends in the total ozone column (TOC) and the atmospheric factors influencing ozone variability at three Antarctic stations (Marambio, Troll/Trollhaugen, and Concordia) from 2007 to 2023. Ground-based TOC measurements were used, supplemented by satellite observations from the Ozone Monitoring Instrument on NASA's Aura satellite. TOC trends were derived using a multiple linear regression model provided by the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) project. The selected LOTUS model was able to explain 94&ndash;97 % of the TOC variability at all three stations. The regression analysis showed that ozone variability at these stations is mainly driven by the lower stratospheric temperature, eddy heat flux, and the Quasi-Biennial Oscillation. A statistically significant increasing trend was found at the Marambio station (3.43 DU/decade), while statistically insignificant trends were detected at the other two stations. Using MERRA-2 reanalyses, the LOTUS model was applied to each grid point in the 40&ndash;90&deg; S region, which effectively illustrates the spatial distribution of the impacts of individual predictors. It was found that warmer conditions in the Antarctic stratosphere in September 2019 caused TOC to be up to 100 DU higher than normal, especially over East Antarctica. The results improve understanding of regional TOC trends and how the Antarctic ozone layer responds to changes in ozone-depleting substances.

BackgroundMost studies on the prevalence of oral mucosal lesions (OMLs), including those from Norway, focus on patient populations. This study aimed to estimate the overall prevalence of OMLs and its types across different age groups and to examine their association with selected risk factors in a general adult population of Norway.MethodsThis cross-sectional study included a random sample of 4,909 individuals aged 19 years and older who completed questionnaires and underwent a standardized clinical examination for OMLs in the HUNT Oral Health Survey (2017–2019). The classification of OMLs was based on the World Health Organization and NHANES III guidelines. Odds Ratio (OR) with 95% confidence intervals (CI) were calculated using multivariable logistic regression to assess associations between OMLs and potential risk factors, adjusting for relevant confounders.ResultsThe overall prevalence of OMLs was 7.5%, with a higher proportion observed in individuals aged 60 and older. The most prevalent oral lesions were exophytic lesions (3.1%) and white lesions (1.5%). Notably, individuals with a low/middle level of education had higher odds of having an OMLs than those with a higher level of education (OR, 1.27, 95% CI: 1.00-1.61) in the fully adjusted model. Exploratory analyses of lesion types found a positive association between smoking status and white lesions (OR, 1.77, 95% CI:1.05–2.97), as well as between a history of cancer and red-blue lesions (OR, 2.17, 95% CI, 1.14–4.11).ConclusionIn this population-based study, 7.5% of Norwegian adults had one or more OMLs, with higher prevalence in participants aged 60 years and older. Further research is needed to confirm these findings in similar populations.

<strong class="journal-contentHeaderColor">Abstract.</strong> The winter 2023/24 exhibited remarkable stratospheric dynamics with multiple sudden stratospheric warmings (SSWs). Based on the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) polar-cap averaged 10 hPa zonal wind, three major SSWs are identified &ndash; an extremely rare occurrence in a single winter. Two of three SSWs were short-lived, lasting under 7 days. In this study, we give an overview of the three SSWs that occurred in winter 2023/24 and focus on the impact of tropospheric forcing on their duration. Blocking high-pressure systems are shown to modulate wave activity flux into the stratosphere through interactions with tropospheric planetary waves, depending on their location. The rapid termination of the first SSW (14&ndash;19 January 2024) is linked to a developing high-pressure system over the North Pacific. The second SSW (16&ndash;22 February 2024) terminated quickly due to more contributing factors, one of which was a high-pressure system developed over the Far East. The third SSW (3&ndash;28 March 2024) was a long-duration canonical event extending to levels below 100 hPa. In contrast to two short-lived SSWs in winter 2023/24, the tropospheric forcing was sustained around the SSW onset in March 2024, allowing a long event to develop. We also note that conditions for these SSWs were particularly favorable due to external factors, including an Easterly Quasi-Biennial Oscillation (QBO), the presence of El Ni&ntilde;o conditions of the ENSO cycle, and the proximity to the solar maximum.

<strong class="journal-contentHeaderColor">Abstract.</strong> Airborne microplastics are a recently identified atmospheric aerosol species with potential air quality and climate impacts, yet they are not currently represented in global climate models. Here, we describe the addition of microplastics to the aerosol scheme of the UK Earth System Model (UKESM1.1): the Global Model of Aerosol Processes (GLOMAP). Microplastics are included as both fragments and fibres across a range of aerosol size modes, enabling interaction with existing aerosol processes such as ageing and wet and dry deposition. Simulated microplastics have higher concentrations over land, but can be transported into remote regions including Antarctica despite no assumed emissions from these regions. Lifetimes range between ~17 days to ~1 hour, with smaller, soluble microplastics having longer lifetimes. Microplastics are well-mixed throughout the troposphere, and the smallest particles are simulated to reach the lower stratosphere in small numbers. Dry deposition is the dominant microplastic removal pathway, but greater wet deposition occurs for smaller soluble microplastic, due to interactions with clouds. Although microplastics currently contribute a minor fraction of the total aerosol burden, their concentration is expected to increase in future if plastic production continues to increase, and as existing plastic waste in the environment degrades to form new microplastic. Incorporating microplastics into UKESM1.1 is a key step toward quantifying their current atmospheric impact and offers a framework for simulating future emission scenarios for an assessment of their long term impacts on air quality and climate.

Abstract. Airborne microplastics are a recently identified atmospheric aerosol species with potential air quality and climate impacts, yet they are not currently represented in global climate models. Here, we describe the addition of microplastics to the aerosol scheme of the UK Earth System Model (UKESM1.1): the Global Model of Aerosol Processes (GLOMAP). Microplastics are included as both fragments and fibres across a range of aerosol size modes, enabling interaction with existing aerosol processes such as ageing and wet and dry deposition. Simulated microplastics have higher concentrations over land, but can be transported into remote regions including Antarctica despite no assumed emissions from these regions. Lifetimes range between ~17 days to ~1 hour, with smaller, soluble microplastics having longer lifetimes. Microplastics are well-mixed throughout the troposphere, and the smallest particles are simulated to reach the lower stratosphere in small numbers. Dry deposition is the dominant microplastic removal pathway, but greater wet deposition occurs for smaller soluble microplastic, due to interactions with clouds. Although microplastics currently contribute a minor fraction of the total aerosol burden, their concentration is expected to increase in future if plastic production continues to increase, and as existing plastic waste in the environment degrades to form new microplastic. Incorporating microplastics into UKESM1.1 is a key step toward quantifying their current atmospheric impact and offers a framework for simulating future emission scenarios for an assessment of their long term impacts on air quality and climate.

Nitrous Oxide (N&amp;#8322;O) is a long-lived and highly potent greenhouse gas, recognized as the third most significant contributor to radiative forcing, with a substantial proportion of its emissions originating from a large area source, agricultural soils, due to the application of mineral fertilizer and livestock manure. As part of the Horizon Europe project EYE-CLIMA, we performed atmospheric inversions to improve the estimates of N2O fluxes across Europe at two spatial resolution scales. The first inversion, spanning the period from 2005 to 2023, was performed at a resolution of 0.5&amp;#176; &amp;#215; 0.5&amp;#176;. The second inversion, covering the period from 2018 to 2023, was carried out at a higher resolution of 0.2&amp;#176; &amp;#215; 0.2&amp;#176;. The method integrates the Community Inversion Framework (CIF) with the Lagrangian particle dispersion model, FLEXPART v11 (CIF-FLEXPART), to estimate N2O emissions using ground-based measurements of atmospheric N2O concentrations. Comprehensive prior N2O flux estimates were generated by incorporating monthly data from key source categories, including agriculture, other anthropogenic activities such as combustion, industry or waste treatment, biomass burning, natural soils, and ocean fluxes. For consistency, observed atmospheric concentrations of N2O were sourced from a newly harmonized dataset for Europe, compiled collaboratively by EYE-CLIMA and the Horizon Europe projects AVENGERS and PARIS.Following the inversion, the modelled concentrations showed improved agreement with observations, capturing the seasonal cycle and increasing trend from 2005 onward. Statistical analyses revealed high correlations between modelled and observed concentrations at most stations. The N2O emissions from the inversion differ from the prior estimates in intensity and spatial distribution with increased emissions in regions of specifically high agricultural activity and reductions in other areas. Monthly flux variations exhibited a consistent seasonal cycle, with peak emissions occurring in early summer (May&amp;#8211;June) and lower emissions during winter months. Across all years, total posterior emissions were lower than the prior estimates. While the phase of the seasonal cycle remained consistent from year to year, interannual variability in the amplitude was observed.

Over the last decade, low-cost sensors (LCSs) have improved air quality monitoring by enabling widespread, community-driven data collection, particularly in regions with limited resources. Although these LCSs have increased public engagement and enriched datasets for understanding pollution dynamics, challenges related to data quality, standardization, and interoperability have hindered their full integration into regulatory frameworks and large-scale environmental monitoring (Barkjohn et al., 2024; Carotenuto et al., 2023). The lack of consistent Quality Control (QC) processes and correction methodologies limits the reliability of LCS-derived data for applications such as public health assessments, modeling, and policymaking.To address these issues, we introduce FILTER (Framework for Improving Low-cost Technology Effectiveness and Reliability), a scalable, multi-level QC, and correction framework designed to improve the reliability of PM2.5 data from citizen-operated LCS networks. FILTER employs spatial &amp;#8220;correlation&amp;#8221; and &amp;#8220;similarity&amp;#8221; QC tests, allowing for in-situ correction of LCS data in different environments. The FILTER framework&amp;#8217;s effectiveness is validated using large-scale European data from the sensor.community and PurpleAir networks, two of Europe&amp;#8217;s largest citizen-driven air quality networks, covering the period 2018 &amp;#8211; 2023. The final dataset, including 521,115,762 hourly PM2.5 measurements from 37,085 locations, was categorized into &amp;#8220;high quality,&amp;#8221; &amp;#8220;good quality,&amp;#8221; and &amp;#8220;other quality&amp;#8221; groups. At the raw data stage, applying QC steps through the spatial similarity level results in a ~50.3% decrease in median RMSE (from 7.61 to 3.78 &amp;#181;g m&amp;#8315;&amp;#179;) across 483 LCSs. For corrected data, applying the same QC steps reduces the median RMSE by ~49.5% (from 7.59 to 3.83 &amp;#181;g m&amp;#8315;&amp;#179;) across 456 LCSs. These enhancements enable LCS data to be more effectively integrated into scientific research, regulatory datasets, and policy development.FILTER demonstrates several key advantages: independence from sensor-specific designs, geospatial scalability, adaptability to real-time processing, and applicability to other pollutants with spatial patterns similar to PM2.5. However, its utility is constrained for pollutants like NO&amp;#8322;, which exhibit hyper-local variability, or scenarios requiring sub-hour temporal resolution. FILTER also demonstrates the potential of on-site calibration techniques that do not require co-location to generate accurate data from LCS networks. This is particularly important for developing large LCS networks that can contribute to both science and policy, especially in light of the new European Air Quality Directive.&amp;#160;ReferencesBarkjohn, K. K., Clements, A., Mocka, C., Barrette, C., Bittner, A., Champion, W., et al. (2024). Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data. ACS ES&amp;amp;T Air.&amp;#160;Carotenuto, F., Bisignano, A., Brilli, L., Gualtieri, G., &amp;amp; Giovannini, L. (2023). Low&amp;#8208;cost air quality monitoring networks for long&amp;#8208;term field campaigns: A review. Meteorological Applications, 30(6), e2161.&amp;#160;We acknowledge funding for CitiObs project from the European Union&amp;#8217;s Horizon Europe research and innovation programme under grant agreement No.101086421. We also acknowledge the contributions of sensor.community (https://sensor.community/en/, accessed October 2024) and PurpleAir (https://www2.purpleair.com/, accessed October 2024) sensor networks where the original sensor data come from, as well as the citizens who provided the low-cost sensor data.