Fant 10282 publikasjoner. Viser side 379 av 412:
Here we provide an overview of the newly commenced project ‘ReGAME - Reliable Global Methane Emissions estimates in a changing world’, funded by Research Council of Norway from 2021-2025, where we combine new developments in atmospheric methane observations: isotopic ratios (deuterium and 13C in methane), and the Integrated Carbon Observation System (ICOS) ground-based station network with atmospheric models (the chemistry transport model OsloCTM, and inversion model FLEXINVERT) to understand how and why atmospheric methane levels are increasing. The project has a particular focus on understanding the state of Arctic methane reservoirs such as ocean seeps and high latitude wetlands. This includes plans for a new observing system aboard the ice breaking vessel RV Kronprins Haakon and ocean observations, e.g., dynamics of Seep fluxes assessed during 1 year of continuous measurements at a seep site the NorEMSO project, updated information on spatial seep distribution via echo sounding, as well as high resolution high-latitude inversion modeling of atmospheric methane with FLEXINVERT. Furthermore, we investigate the utility of including of satellite data (TROPOMI aboard the Sentinel 5P mission) together with ground-based data, in inversion modeling. The inclusion of satellite data into inversion models is quite novel and offers rewards by increasing spatial coverage compared to ground based networks alone, potentially reducing uncertainties in the model outputs, and challenges due to satellite data uncertainties, spatial/ temporal coverage, and handling large data fields
2022
2009
2021
2013
2014
2015
2021
2008
2013
This optimized protocol (including links to instruction videos) describes a comet-based in vitro DNA repair assay that is relatively simple, versatile, and inexpensive, enabling the detection of base and nucleotide excision repair activity. Protein extracts from samples are incubated with agarose-embedded substrate nucleoids (‘naked’ supercoiled DNA) containing specifically induced DNA lesions (e.g., resulting from oxidation, UVC radiation or benzo[a]pyrene-diol epoxide treatment). DNA incisions produced during the incubation reaction are quantified as strand breaks after electrophoresis, reflecting the extract’s incision activity. The method has been applied in cell culture model systems, human biomonitoring and clinical investigations, and animal studies, using isolated blood cells and various solid tissues. Once extracts and substrates are prepared, the assay can be completed within 2 d.
2020
Radiocarbon (14C) analysis of carbonaceous aerosols is used for source apportionment, separating the carbon content into fossil vs. non-fossil origin, and is particularly useful when applied to subfractions of total carbon (TC), i.e. elemental carbon (EC), organic carbon (OC), water-soluble OC (WSOC), and water-insoluble OC (WINSOC). However, this requires an unbiased physical separation of these fractions, which is difficult to achieve. Separation of EC from OC using thermal–optical analysis (TOA) can cause EC loss during the OC removal step and form artificial EC from pyrolysis of OC (i.e. so-called charring), both distorting the 14C analysis of EC. Previous work has shown that water extraction reduces charring. Here, we apply a new combination of a WSOC extraction and 14C analysis method with an optimised separation that is coupled with a novel approach of thermal-desorption modelling for compensation of EC losses. As water-soluble components promote the formation of pyrolytic carbon, water extraction was used to minimise the charring artefact of EC and the eluate subjected to chemical wet oxidation to CO2 before direct 14C analysis in a gas-accepting accelerator mass spectrometer (AMS). This approach was applied to 13 aerosol filter samples collected at the Arctic Zeppelin Observatory (Svalbard) in 2017 and 2018, covering all seasons, which bear challenges for a simplified 14C source apportionment due to their low loading and the large portion of pyrolysable species. Our approach provided a mean EC yield of 0.87±0.07 and reduced the charring to 6.5 % of the recovered EC amounts. The mean fraction modern (F14C) over all seasons was 0.85±0.17 for TC; 0.61±0.17 and 0.66±0.16 for EC before and after correction with the thermal-desorption model, respectively; and 0.81±0.20 for WSOC.
2023
2005
2022
2016
2010
prismAId is an open-source tool designed to streamline systematic literature reviews by leveraging generative AI models for information extraction. It offers an accessible, efficient, and replicable method for extracting and analyzing data from scientific literature, eliminating the need for coding expertise. Supporting various review protocols, including PRISMA 2020, prismAId is distributed across multiple platforms – Go, Python, Julia, R – and provides user-friendly binaries compatible with Windows, macOS, and Linux. The tool integrates with leading large language models (LLMs) such as OpenAI’s GPT series, Google’s Gemini, Cohere’s Command, and Anthropic’s Claude, ensuring comprehensive and up-to-date literature analysis. prismAId facilitates systematic reviews, enabling researchers to conduct thorough, fast, and reproducible analyses, thereby advancing open science initiatives.
2025
Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values) as a product of the source-receptor sensitivity (SRS) matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX) where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.
2020