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2024
Recent methane surges reveal heightened emissions from tropical inundated areas
Record breaking atmospheric methane growth rates were observed in 2020
and 2021 (15.2±0.5 and 17.8±0.5 parts per billion per year), the highest since the
early 1980s. Here we use an ensemble of atmospheric inversions informed by
surface or satellite methane observations to infer emission changes during
these two years relative to 2019. Results show global methane emissions
increased by 20.3±9.9 and 24.8±3.1 teragrams per year in 2020 and 2021,
dominated by heightened emissions from tropical and boreal inundated areas,
aligning with rising groundwater storage and regional warming. Current
process-based wetland models fail to capture the tropical emission surges
revealed by atmospheric inversions, likely due to inaccurate representation of
wetland extents and associated methane emissions. Our findings underscore
the critical role of tropical inundated areas in the recent methane emission
surges and highlight the need to integrate multiple data streams and modeling
tools for better constraining tropical wetland emissions.
2024
2024
The FAIRness of ACTRIS Data Centre
The purpose of this report is to document the status and implementation of FAIRness within ACTRIS Data centre as of March 2023, developed over the period January 2019 – March 2023.
The report is an extended version of ENVRI-FAIR deliverable D8.4 due March 2023 and available through Zenodo: ENVRI-FAIR D8.4: The FAIRness of ACTRIS | Zenodo, only including the work until autumn 2022. This present report adds more information to the implementation of the FAIR principles by ACTRIS Data Centre over the period January 2019 – March 2023. In addition to D8.4, the present report provides a comprehensive external FAIRness assessment covering the entire period 2019 - 2023, along with an evaluation of the implementation in the years 2022 and the first half of 2023. It's important to note that the project deliverable only encompasses the period from 2019 to 2021.
NILU
2024
Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial age, making CH4 the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). The oil and gas sector represents one of the major anthropogenic CH4 emitters as it is estimated to account for 22 % of global anthropogenic CH4 emissions. An airborne field campaign was conducted in April–May 2019 to study CH4 emissions from offshore gas facilities in the southern North Sea with the aim of deriving emission estimates using a top-down (measurement-led) approach. We present CH4 fluxes for six UK and five Dutch offshore platforms or platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting and fugitive or flaring and combustion) using observations of co-emitted ethane (C2H6) and CO2. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and operator-based reporting for individual Dutch facilities. In this study, we find that all the inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all the sampled Dutch installations together, we find that our estimated flux of (122.9 ± 36.8) kg h−1 deviates by a factor of 0.64 (0.33–12) from reported values (192.8 kg h−1). Comparisons with aircraft observations in two other offshore regions (the Norwegian Sea and the Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by 2 orders of magnitude. Therefore, mitigation is warranted equally across geographies.
2024
Extracellular Vesicles as Next-Generation Diagnostics and Advanced Therapy Medicinal Products
Extracellular vesicles (EVs) hold great promise for clinical application as new diagnostic and therapeutic modalities. This paper describes major GMP-based upstream and downstream manufacturing processes for EV large-scale production, also focusing on post-processing technologies such as surface bioengineering and uploading studies to yield novel EV-based diagnostics and advanced therapy medicinal products. This paper also focuses on the quality, safety, and efficacy issues of the bioengineered EV drug candidates before first-in-human studies. Because clinical trials involving extracellular vesicles are on the global rise, this paper encompasses different clinical studies registered on clinical-trial register platforms, with varying levels of advancement, highlighting the growing interest in EV-related clinical programs. Navigating the regulatory affairs of EVs poses real challenges, and obtaining marketing authorization for EV-based medicines remains complex due to the lack of specific regulatory guidelines for such novel products. This paper discusses the state-of-the-art regulatory knowledge to date on EV-based diagnostics and medicinal products, highlighting further research and global regulatory needs for the safe and reliable implementation of bioengineered EVs as diagnostic and therapeutic tools in clinical settings. Post-marketing pharmacovigilance for EV-based medicinal products is also presented, mainly addressing such topics as risk assessment and risk management.
2024
Environmental dose-response functions of silk and paper exposed in museums.
This paper reports 1 year of data of the environments and changes in the molecular weight of silk and the degree of polymerization of sensitive paper measured externally and indoors in 10 European museums, and the dose-response functions that were obtained by statistical analysis of this data. The measurements were performed in the EU FP5 project Master (EVK-CT-2002-00093). The work provides documentation of deterioration of silk by NO2 and O3, and alternatively in combination with UV radiation. The indoor deterioration of the silk was only observed in one location with high UV radiation. The indoor deterioration of sensitive paper correlated with the UV radiation, the concentrations of NO2 and O3, and in addition with an SO2 concentration of 4 µgm−3 and a formic acid concentration of 50 µgm−3 in two different locations. If the observed dose-response effects are linear to lower doses and longer exposure times, then the lifetime to intolerable deterioration of the paper and silk would be 6–7 times longer overall in the enclosures than in the galleries.
2024
2024
Environmental pollutants in the terrestrial and urban environment 2023
Samples from the urban terrestrial environment in the Oslo area were analysed for metals and a large number of organic environmental pollutants. The selected samples that were analysed were soil, earthworm, fieldfare egg, brown rat liver, roe deer liver, vegetation, honeybee, and Spanish slug. Biomagnification potential was estimated based on detected data for relevant predator-prey pairs.
NILU
2024
2024
2024
2024
A Machine Learning Approach to Retrieving Aerosol Optical Depth Using Solar Radiation Measurements
Aerosol optical depth (AOD) constitutes a key parameter of aerosols, providing vital information for quantifying the aerosol burden and air quality at global and regional levels. This study demonstrates a machine learning strategy for retrieving AOD under cloud-free conditions based on the synergy of machine learning algorithms (MLAs) and ground-based solar irradiance data. The performance of the proposed methodology was investigated by applying different components of solar irradiance. In particular, the use of direct instead of global irradiance as a model feature led to better performance. The MLA-based AODs were compared to reference AERONET retrievals, which encompassed RMSE values between 0.01 and 0.15, regardless of the underlying climate and aerosol environments. Among the MLAs, artificial neural networks outperformed the other algorithms in terms of RMSE at 54% of the measurement sites. The overall performance of MLA-based AODs against AERONET revealed a high coefficient of determination (R2 = 0.97), MAE of 0.01, and RMSE of 0.02. Compared to satellite (MODIS) and reanalysis (MERRA-2 and CAMSRA) data, the MLA-AOD retrievals revealed the highest accuracy at all stations. The ML-AOD retrievals have the potential to expand and complement the AOD information in non-existing timeframes when solar irradiances are available.
2024