Addressing the advantages and limitations of using Aethalometer data to determine the optimal absorption Ångström exponents (AAEs) values for eBC source apportionment

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.publishedVersio

CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials

The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced in vitro models, in silico approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems. Significant progress has been made in generating atomistic and quantum-mechanical descriptors for various NMs, evaluating their interactions with biological systems (from small molecules or metabolites, to proteins, cells, organisms, animals, humans and ecosystems), and in developing predictive models for NMs risk assessment. The CompSafeNano project has also focused on implementing and further standardising data reporting templates and enhancing data management practices, ensuring adherence to the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Despite challenges, such as limited regulatory acceptance of New Approach Methodologies (NAMs) currently, which has implications for predictive nanosafety assessment, CompSafeNano has successfully developed tools and models that are integral to the safety evaluation of NMs, and that enable the extensive datasets on NMs safety to be utilised for the re-design of NMs that are inherently safer, including through prediction of the acquired biomolecule coronas which provide the biological or environmental identities to NMs, promoting their sustainable use in diverse applications. Future efforts will concentrate on further refining these models, expanding the NanoPharos Database, and working with regulatory stakeholders thereby fostering the widespread adoption of SbD practices across the nanotechnology sector. CompSafeNano's integrative approach, multidisciplinary collaboration and extensive stakeholder engagement, position the project as a critical driver of innovation in NMs SbD methodologies and in the development and implementation of computational nanosafety.publishedVersio

A pooled analysis of host factors that affect nucleotide excision repair in humans

Nucleotide excision repair (NER) is crucial for repairing bulky lesions and crosslinks in DNA caused by exogenous and endogenous genotoxins. The number of studies that have considered DNA repair as a biomarker is limited, and therefore one of the primary objectives of the European COST Action hCOMET (CA15132) was to assemble and analyse a pooled database of studies with data on NER activity. The database comprised 738 individuals, gathered from 5 laboratories that ran population studies using the comet-based in vitro DNA repair assay. NER activity data in peripheral blood mononuclear cells were normalized and correlated with various host-related factors, including sex, age, body mass index (BMI), and smoking habits. This multifaceted analysis uncovered significantly higher NER activity in female participants compared to males (1.08 ± 0.74 vs. 0.92 ± 0.71; P = .002). Higher NER activity was seen in older subjects (>30 years), and the effect of age was most pronounced in the oldest females, particularly those over 70 years (P = .001). Females with a normal BMI (<25 kg/m2) exhibited the highest levels of NER, whereas the lowest NER was observed in overweight males (BMI ≥ 25 kg/m2). No independent effect of smoking was found. After stratification by sex and BMI, higher NER was observed in smoking males (P = .017). The biological implication of higher or lower repair capacity remains unclear; the inclusion of DNA repair as a biomarker in molecular epidemiological trials should elucidate the link between health and disease status.publishedVersio

Uptake of chemicals from tire wear particles into aquatic organisms - search for biomarkers of exposure in blue mussels

Little is known about the exposure of aquatic biota to tire and road wear particles (TRWP) washed away from roads. Mussels were exposed for 7 days to model TRWP (m-TRWP), produced by milling tire tread particles with pure sand, and analyzed for 21 tire-related compounds by liquid chromatography-high resolution-mass spectrometry (LC-HRMS). Upon exposure to 0.5 g/L of m-TRWP, 15 compounds were determined from 944 μg/kg wet weight (diphenylguanidine, DPG) over 18 μg/kg for an oxidation product of N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6-PPDQ) to 0.6 μg/kg (4-hydroxydiphenyl amine). Transfer into mussels was highest for PTPD, DTPD and 6-PPDQ and orders of magnitude lower for 6-PPD. During 7 days depuration the concentration of all determined chemicals decreased to remaining concentrations between ~50 % (PTPD, DTPD) and 6 % (6-PPD). Suspect and non-target screening found 37 additional transformation products (TPs) of tire additives, many of which did not decrease in concentration during depuration, among them ten likely TPs of DPG, two of 6-PPD and PTPD and two of 1,2-dihydro-2,2,4-trimethylquinoline. A wide variety of chemicals is taken up by mussels upon exposure to m-TRWP and a wide range of TPs is formed, enabling the differentiation of biomarkers of exposure to TRWP and biomarkers of exposure to tire-associated chemicals.publishedVersio

Metals, PCB, PAH and dioxins in the Russian-Norwegian border areas. Moss survey 2008, 2015, 2020

I 2008 samlet Svanhovd Miljøsenter inn mose ved lokaliteter i grenseområdene mot Russland som NILU analyserte for 11 metaller, PCB, PAH og dioksiner. Formålet var å undersøke om det var andre kilder til forurensning i grenseområdene enn gruvedrift og smelteverksindustri. Prøvetaking og analyse ble gjentatt av NILU i 2015 og 2020, men kun for 60 (2015) og 56 (2020) metaller. For spormetallene Ni, Cu, Co og As er det et klart mønster med forhøyede konsentrasjoner nedstrøms Nikel og Zapolyarnyj. Organiske miljøgifter viser lave konsentrasjoner.publishedVersio

Critical Insights into Untargeted GC-HRMS Analysis: Exploring Volatile Organic Compounds in Italian Ambient Air

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.publishedVersio

Using a citizen science approach to assess nanoplastics pollution in remote high-altitude glaciers

Nanoplastics are suspected to pollute every environment on Earth, including very remote areas reached via atmospheric transport. We approached the challenge of measuring environmental nanoplastics by combining high-sensitivity TD-PTR-MS (thermal desorption-proton transfer reaction-mass spectrometry) with trained mountaineers sampling high-altitude glaciers (“citizen science”). Particles < 1 μm were analysed for common polymers (polyethylene, polyethylene terephthalate, polypropylene, polyvinyl chloride, polystyrene and tire wear particles), revealing nanoplastic concentrations ranging 2–80 ng mL− 1 at five of 14 sites. The dominant polymer types found in this study were tire wear, polystyrene and polyethylene particles (41%, 28% and 12%, respectively). Lagrangian dispersion modelling was used to reconstruct possible sources of micro- and nanoplastic emissions for those observations, which appear to lie largely to the west of the Alps. France, Spain and Switzerland have the highest contributions to the modelled emissions. The citizen science approach was found to be feasible providing strict quality control measures are in place, and is an effective way to be able to collect data from remote and inaccessible regions across the world.publishedVersio

UV-degradation is a key driver of the fate and impacts of marine plastics. How can laboratory experiments be designed to effectively inform risk assessment?

Marine plastic litter is subject to different abiotic and biotic forces that lead to its degradation, the main driver being UV-induced photodegradation. Since UV-exposure leads to both physical and chemical degradation of plastic, leading to a release of micro- and nanoplastics as well as leaching of chemicals and degradation products – it is expected to have radical impacts on plastics fate and effects in the marine environment. The number of laboratory studies investigating the mechanisms of plastic UV-degradation in seawater has increased significantly in the past 10 years, but are the exposures designed in a manner that allow observations to be extrapolated to environmental fate? Most studies to date focus on quantifying plastic fragmentation and surface changes, but is this relevant for impact assessments? Here, we provide a review of the current scientific literature on UV-degradation of plastic under marine conditions. Plastic fragmentation processes and surface changes as well as implications of UV-degradation of plastics on additive leaching and the toxicity of UV-weathered versus non-weathered plastics are highlighted. Furthermore, experimental set-ups are critically inspected and recommendations for future studies are issued.publishedVersio

New Approach Methods (NAMs) for genotoxicity assessment of nano- and advanced materials; Advantages and challenges

Genotoxicity assessment is essential for ensuring chemical safety and mitigating risks to human health and the environment. Traditional methods, reliant on animal models, are time-consuming, costly, and raise ethical concerns. New Approach Methods (NAMs) offer innovative, cost-effective, and ethical alternatives, playing a pivotal role in both traditional and next-generation risk assessment (NGRA) by minimizing the need for animal testing, particularly in genotoxicity evaluations. However, the development of NAMs often overlooks the particular physicochemical properties of nanomaterials (NMs), which significantly influence their toxicological behaviour and can interfere with genotoxicity evaluation. This underscores an urgent need for the standardization and adaptation of NAMs to address nano- and advanced material-specific genotoxicity challenges. In this review, we summarize the challenges associated with genotoxicity testing of NMs and highlight the suitability of existing in vitro and in silico NAMs for NMs and advanced materials, enabling genotoxicity testing across various exposure routes and organ systems. Despite considerable progress, regulatory validation remains constrained by the absence of approved test guidelines and standardized protocols. To achieve regulatory acceptance, it is crucial to adapt NAMs to NM-specific exposure scenarios, refine test systems to better mimic human biology, develop tailored in vitro protocols, and ensure thorough characterisation of NMs both in pristine form and dispersed in culture medium. Collaborative efforts among scientists, regulators, industry, and advocacy groups are vital to improving the reliability and regulatory acceptance of NAMs. By addressing these challenges, NAMs have the potential to revolutionize genotoxicity risk assessment, advancing it towards a more sustainable, efficient and ethical framework.publishedVersio

Air Quality and Healthy Ageing: Predictive Modelling of Pollutants using CNN Quantum-LSTM

The concept of healthy ageing is emerging and becoming a norm to achieve a high quality of life, reducing healthcare costs and promoting longevity. Rapid growth in global population and urbanisation requires substantial efforts to ensure healthy and supportive environments to improve the quality of life, closely aligned with the principles of healthy ageing. Access to fundamental resources which include quality healthcare services, clean air, green and blue spaces plays a pivotal role in achieving this goal. Air quality, in particular, is a critical factor in achieving healthy ageing targets. However, it necessitates a global effort to develop and implement policies aimed at reducing air pollution, which has severe implications for human health including cognitive impairment and neurodegenerative diseases, while promoting healthier environments such as high quality green and blue spaces for all age groups. Such actions inevitably depend on the current status of air pollution and better predictive models to mitigate the harmful impact of emissions on planetary health and public health. In this work, we proposed a hybrid model referred as AirVCQnet, which combines the variational mode decomposition (VMD) method with a convolutional neural network (CNN) and a quantum long short-term memory (QLSTM) network for the prediction of air pollutants. The performance of the proposed model is analysed on five key pollutants including fine Particulate Matter PM2.5, Nitrogen Dioxide (NO2), Ozone (O3), PM10, and Sulphur Dioxide (SO2), sourced from air quality monitoring station in Northern Ireland, UK. The effectiveness of the proposed model is evaluated by comparing its performance with its equivalent classical counterpart using root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2). The results demonstrate the superiority of the proposed model, achieving a performance gain of up to 14% and validating its robustness, efficiency and reliability by leveraging t.publishedVersio