Fant 10020 publikasjoner. Viser side 372 av 401:
2016
2007
An assessment of the contribution of air pollution to the weathering of limestone heritage in Malta
Malta is known for its limestone megalithic temples of which many are inscribed on the UNESCO World Heritage List. A variation of this limestone was historically, and until very few years ago, a primary building material in Malta. The temples are subject to various environmental influences which until recently have led to several collapses due in part to serious stone surface and infill loss. As a protection measure, open-sided shelters have been built over three of these temples. This work assesses the degrading influence of air pollution (nitrogen dioxide, ozone, particle matter, sulfur dioxide, and acidity in rain) on the temples, in combination and comparison with the influence of other environmental factors (relative humidity, temperature, precipitation, moisture, sea salt, wind) and in this respect evaluates the potential protective effect of the shelters. The variation in air pollution weathering of limestone exposed outdoor in Malta was calculated by exposure–response functions from the ICP-materials programme and compared with measured values, and its contribution to the deterioration of the temples was evaluated. The difference between urban and rural locations in Malta, in the first year of atmospheric chemical weathering of limestone due to air pollution, was found to be about one micrometer loss of stone surface. This is probably less than the annual variations due to the influence of natural climatic factors, and small compared to the present annual variations in continental Europe. The deposition of sea salt and presence of salts on and in the limestone megaliths and changes in salt-crystallization events due to relative humidity fluctuations, inside and outside the shelters, will account for more of the variations in the first year of weathering of Globigerina limestone than variations in air pollution. The deterioration will also be related to temperature (including condensation events), wind parameters and rainfall, as well as ground water replenished from areas beyond the shelter.
2020
2008
2001
2010
2023
2015
2008
2009
2006
2017
An AI-Enhanced Systematic Review of Climate Adaptation Costs: Approaches and Advancements, 2010–2021
This study addresses the critical global challenge of climate adaptation by assessing the inadequacies in current methodologies for estimating adaptation costs. Broad assessments reveal a significant investment shortfall in adaptation strategies, highlighting the necessity for precise cost analysis to guide effective policy-making. By employing the PRISMA 2020 protocol and enhancing it with the prismAId tool, this review systematically analyzes the recent evolution of cost assessment methodologies using state-of-the-art generative AI. The AI-enhanced approach facilitates rapid and replicable research extensions. The analysis reveals a significant geographical and sectoral disparity in research on climate adaptation costs, with notable underrepresentation of crucial areas and sectors that are most vulnerable to climate impacts. The study also highlights a predominant reliance on secondary data and a lack of comprehensive uncertainty quantification in economic assessments, suggesting an urgent need for methodological enhancements. It concludes that extending analyses beyond merely verifying that benefits exceed costs is crucial for supporting effective climate adaptation. By assessing the profitability of adaptation investments, it becomes possible to prioritize these investments not only against similar interventions but also across the broader spectrum of public spending.
2024
2018
2017
2021
An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry
Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.
2022
2007
Ammonia emission estimates using CrIS satellite observations over Europe
Over the past century, ammonia (NH3) emissions have increased with the growth of livestock and fertilizer usage. The abundant NH3 emissions lead to secondary fine particulate matter (PM2.5) pollution, climate change, and a reduction in biodiversity, and they affect human health. Up-to-date and spatially and temporally resolved information on NH3 emissions is essential to better quantify their impact. In this study we applied the existing Daily Emissions Constrained by Satellite Observations (DECSO) algorithm to NH3 observations from the Cross-track Infrared Sounder (CrIS) to estimate NH3 emissions. Because NH3 in the atmosphere is influenced by nitrogen oxides (NOx), we implemented DECSO to estimate NOx and NH3 emissions simultaneously. The emissions are derived over Europe for 2020 on a spatial resolution of 0.2°×0.2° using daily observations from both CrIS and the TROPOspheric Monitoring Instrument (TROPOMI; on the Sentinel-5 Precursor (S5P) satellite). Due to the limited number of daily satellite observations of NH3, monthly emissions of NH3 are reported. The total NH3 emissions derived from observations are about 8 Tg yr−1, with a precision of about 5 %–17 % per grid cell per year over the European domain (35–55° N, 10° W–30° E). The comparison of the satellite-derived NH3 emissions from DECSO with independent bottom-up inventories and in situ observations indicates a consistency in terms of magnitude on the country totals, with the results also being comparable regarding the temporal and spatial distributions. The validation of DECSO over Europe implies that we can use DECSO to quickly derive fairly accurate monthly emissions of NH3 over regions with limited local information on NH3 emissions.
2024
Amines worst case studies. Worst case studies on amine emissions from CO2 capture plants (Task 6). NILU OR
2008
2008