Found 9746 publications. Showing page 372 of 390:
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.
MDPI
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
Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
In environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori quality information about the sensor device without using complex and resource-demanding data assimilation techniques. Both ordinary kriging and the general regression neural network (GRNN) are integrated into this attention with their learnable parameters based on deep learning architectures. We evaluate this method using three static phenomena with different complexities: a case related to a simplistic phenomenon, topography over an area of 196 and to the annual hourly concentration in 2019 over the Oslo metropolitan region (1026 ). We simulate networks of 100 synthetic sensor devices with six characteristics related to measurement quality and measurement spatial resolution. Generally, outcomes are promising: we significantly improve the metrics from baseline geostatistical models. Besides, distance attention using the Nadaraya–Watson kernel provides as good metrics as the attention based on the kriging system enabling the possibility to alleviate the processing cost for fusion of sparse data. The encouraging results motivate us in keeping adapting distance attention to space-time phenomena evolving in complex and isolated areas.
Cambridge University Press
2024
The report presents interim 2023 maps for PM10 annual average, PM2.5 annual average, O3 indicator peak season average of maximum daily 8-hour means, and NO2 annual average. The maps have been produced based on the 2023 non-validated E2a (UTD) data of the AQ e-reporting database, the CAMS Ensemble Forecast modelling data and other supplementary data. Together with the concentration maps, the inter-annual differences between 5-year average 2018-2022 and 2023 are presented (using the 2018-2022 regular and the 2023 interim maps), as well as basic exposure estimates based on the interim maps.
ETC/HE
2024
Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components
Norwegian Meteorological Institute
2024
2024
Integrating Low-cost Sensor Systems and Networks to Enhance Air Quality Applications
Low-cost air quality sensor systems (LCS) are emerging technologies for policy-relevant air quality analysis, including pollution levels, source identification, and forecasting. This report discusses LCS use in networks and alongside other data sources for comprehensive air quality applications, complementing other WMO publications on LCS operating principles, calibration, performance assessment, and data communication.
The LCS’s utility lies in their ability to provide new insights into air quality that existing data sources may not offer. While LCS data must be verified, their integration with other data sources can enhance understanding and management of air quality. In areas without reference-grade monitors, LCS can identify factors affecting local air quality and guide future monitoring efforts. Combining LCS data with satellite and other air quality systems can improve data reliability and establish corroborating evidence for observed trends. LCS can extend the spatial coverage of existing monitoring networks, offering localized insights and supporting effective air quality management policies. Co-locating LCS with reference-grade monitors helps quantify measurement uncertainties and apply LCS data appropriately for forecasting, source impact analysis, and community engagement.
World Meteorological Organization
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
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.
MDPI
2024
2024
To achieve the objectives of COP28 for transitioning away from fossil fuels and phasing these out, both natural and technological solutions are essential, necessitating a step-change in how we implement social innovation. Given the significant CO2 emissions produced by the building sector, there is an urgent need for a transformative shift towards a net-zero building stock by mid-century. This transition to zero-energy and zero-emission buildings is difficult due to complex processes and substantial costs. Building integrated photovoltaics (BIPV) offers a promising solution due to the benefits of enhanced energy efficiency and electricity production. The availability of roof and façade space in offices and other types of buildings, especially in large cities, permits photovoltaic integration in both opaque and transparent surfaces. This study investigates the synergistic relationship between solar conversion technologies and nature-based components. Through a meta-analysis of peer-reviewed literature and critical assessment, effective BIPVs with greenery (BIPVGREEN) combinations suitable for various climatic zones are identified. The results highlight the multi-faceted benefits of this integration across a range of techno-economic and social criteria and underscore the feasibility of up-scaling these solutions for broader deployment. Applying a SWOT analysis approach, the internal strengths and weaknesses, as well as the external opportunities and threats for BIPVGREEN deployment, are investigated. The analysis reveals key drivers of synergistic effects and multi-benefits, while also addressing the challenges associated with optimizing performance and reducing investment costs. The strengths of BIPVGREEN in terms of energy efficiency and sustainable decarbonization, along with its potential to mitigate urban and climate temperature increases, enhance its relevance to the built environment, especially for informal settlements. The significance of prioritizing this BIPVGREEN climate mitigation action in low-income vulnerable regions and informal settlements is crucial through the minimum tax financing worldwide and citizen's engagement in architectural BIPVGREEN co-integration.
IOP Publishing
2024
2024