The NILU – Norwegian Institute for Air Research (Norwegian: NILU – Norsk Institutt for luftforskning) or NILU is one of the leading specialized scientific laboratories in Europe researching issues related to air pollution, climate change and health. It is an independent nonprofit institution, established in 1969, staffed by scientists, engineers and technicians with specialized expertise for working on air pollution problems. The staff do more than two hundred projects annually for research councils, industries, international banks and local, national and international authorities and organizations. Its first director was Brynjulf Ottar.
The European Union (EU) net-zero emission target for 2050 requires large-scale deployment of carbon capture and storage (CCS). Amine-based CO2 capture (CC) is the most mature CC technology but may lead to the spread of nitrosamines (NSAs) and nitramines (NAs) in the nearby surroundings. These are carcinogenic compounds that can persist in water resources. Hence, EU's ambition towards carbon neutrality might pose risk of drinking water contamination as well as ecosystem and agricultural crops pollution. We compiled a dataset of planned CCS projects in the Franco-Danish corridor, Europe's future CCS hub, where most capacity will be located by 2030, with at least 40% based on amine technology. Spatial analysis indicates that up to 10.2 million inhabitants, large Natura 2000 reserves, and extensive crop areas may be impacted by NA and NSA deposition, often in regions already under severe water stress. Biogeochemical modelling shows that surface waters with short residence times are highly sensitive to deposition rates, whereas groundwater concentrations depend strongly on the interplay between NA and NSA half-lives and travel times, creating greater uncertainty in aquifers, especially small systems with limited dilution. In both cases, MEA is the most environmentally friendly when emission abatement measures are limited to water wash, compared to piperazine and other emerging solvents. Main findings highlight the need for regional-scale modelling and harmonized regulation to safeguard drinking water, ecosystems, and food security as CCS deployment expands.
Potato plants are highly vulnerable to numerous diseases that can substantially affect both yield and quality. Conventional approaches for detecting these diseases are often labor-intensive, slow, and prone to inaccuracies, particularly under variable environmental conditions. This study presents a hybrid deep learning architecture, termed potato leaf diseases DenseNet (PLDNet), which integrates a DenseNet-based convolutional neural network with a Transformer-based attention module to accurately classify potato leaf diseases. Furthermore, an adaptive parametric activation function, referred to as Adaptive Flatten p-Mish (AFpM), is proposed to enhance the model’s learning flexibility and representational capacity. When evaluated on the PlantVillage and Mendeley datasets, PLDNet attains classification accuracies of 99.54% and 87.50%, respectively, surpassing contemporary state-of-the-art models and activation techniques. The proposed framework exhibits strong generalization performance and offers a scalable, efficient approach for automated plant disease identification. To highlight the novelty, the proposed AFpM activation function introduces a learnable parameter enabling adaptive nonlinearity, improving over Mish, Swish, and PFpM activation functions through dynamic gradient control. AFpM improves accuracy by 2.52% on Mendeley dataset, and 1.93% on PlantVillage dataset compared to PFpM, and by more than 3% compared to Swish and Mish.
Plastic pollution monitoring programs use a wide array of methods, protocols, and analytical approaches, making it difficult for researchers and practitioners to determine which techniques to apply, where, and how. This lack of harmonisation across environmental compartments and plastic size classes has led to inconsistent data and limited comparability across studies. To address this, a systematic review of monitoring methods from 1960 to 2021 was conducted, encompassing both peer-reviewed and grey literature. Techniques were categorised into Reproducible Analytical Pipelines (RAPs), each comprising six core steps: survey design, sample collection, sample preparation, analytical detection, quantification, and data reporting. Each RAP was assessed using Technological Readiness Levels (TRLs) to evaluate maturity and suitability for standardised monitoring. The review revealed that while robust and repeatable methods exist, they are inconsistently applied. At the time of this review, atmospheric plastics was underrepresented, highlighting a critical gap in monitoring efforts. The findings underscore the urgent need for a global, objective framework to guide the selection and implementation of plastic pollution monitoring methodologies. This paper lays the foundation for such a framework by presenting a methodology to identify mature, reproducible methods and prioritise areas for further development. Future work should focus on harmonising protocols across compartments and size classes, improving transparency in data reporting, and building consensus around standardised practices to enable global comparability and policy relevance.
In the summer of 2019, the Arctic region registered exceptionally high aerosol optical depth (AOD) values over Svalbard, linked to intense biomass burning (BB) and volcanic activity across the Northern Hemisphere. This study presents a comprehensive, multi-instrumental analysis of the aerosol conditions in and around Ny-Ålesund (Spitsbergen, Norway), combining data from ground-based sun-photometry, in-situ observations, active remote sensing (ground-based and on satellite), and atmospheric dispersion modelling (FLEXPART). Despite high AOD was observed during all the period, three different aerosol events are identified in the atmospheric column (6–10 July, 25–28 July, and 6–17 August). In contrast, in-situ surface stations only recorded significant aerosol load during 5–9 July, 30 August, and 12 September, suggesting that most of the aerosol particles remained above the boundary layer. Lidar and photometric observations revealed the presence of spherical, weakly absorbing Accumulation-mode particles (with effective radii between 0.1 and 0.2 µm) in both the troposphere and stratosphere, with persistent layers extending above 10 km. Simulations carried out with FLEXPART correlate well with the measurements, attributing the observed aerosol events to multiple sources, including Siberian and North American wildfires, the Raikoke (Russia) volcanic eruption, and anthropogenic pollution. While the simulations show a contribution from volcanic aerosols, the contribution from biomass-burning aerosols in the upper troposphere and lower stratosphere were likely more significant under the atmospheric conditions of summer 2019. Overall, the aerosol radiative impact during this long-lasting event was substantial, with a mean reduction in direct solar radiation of approximately −74 W m−2 during July and August. This work shows how the use of dispersion modelling together with multiple observation sources allows to achieve a more complete description of the atmospheric aerosol events and contributes to a better understanding of the overall picture.
Hydrofluoroolefins (HFOs) are important synthetic compounds replacing other halocarbons in phase-down from usage (e.g., as refrigerants, propellants, foam blowing). Little is known about their atmospheric abundance, distribution and trends, nor about their emissons. Here, we report atmospheric observations of the widely used HFO-1234yf (2,3,3,3-tetrafluoroprop-1-ene), and HFO-1234ze(E) (E-1,3,3,3-tetrafluoroprop-1-ene), and the hydrochlorofluoroolefin (HCFO) HCFO-1233zd(E) (E-1-chloro-3,3,3-trifluoroprop-1-ene) observed as part of the Advanced Global Atmospheric Gases Experiment (AGAGE) network. Over the observational period 2011–2025, pollution events have grown in magnitude and frequency at sites which are influenced by regional emissions, while remote stations show first appearances of these substances. By 2024/2025 winter peak mole fractions in background northern hemisphere air have reached ∼ 0.25 ppt (picomol mol−1, parts-per-trillion in dry air) for HFO-1234yf and HFO-1234ze(E) and ∼ 0.45 ppt for HCFO-1233zd(E). Using European observations and the inverse modeling frameworks InTEM, ELRIS, and RHIME we determine emission trends and regional distributions. For Northwest Europe, emissions of HFO-1234yf increased steadily and rapidly from <0.1 Gg yr−1 in 2014 to 1.50 [1.23–1.74, range of 16–84 percentile] Gg yr−1 by 2023, presumably due to its introduction in mobile air conditioning and stationary refrigeration. HFO-1234ze(E) emissions were low during 2014–2017, followed by a rapid increase in 2018/2019, potentially due its introduction as an aerosol propellant, after which they increased more slowly to 0.96 [0.82–1.13] Gg yr−1 by 2023. HCFO-1233zd(E) emissions are derived from 2017 onward, showing a steady increase from 0.15 [0.07–0.23] to 1.04 [0.93–1.15] Gg yr−1 in 2023.
