Found 10000 publications. Showing page 342 of 400:
Equal abundance of summertime natural and wintertime anthropogenic Arctic organic aerosols
Aerosols play an important yet uncertain role in modulating the radiation balance of the sensitive Arctic atmosphere. Organic aerosol is one of the most abundant, yet least understood, fractions of the Arctic aerosol mass. Here we use data from eight observatories that represent the entire Arctic to reveal the annual cycles in anthropogenic and biogenic sources of organic aerosol. We show that during winter, the organic aerosol in the Arctic is dominated by anthropogenic emissions, mainly from Eurasia, which consist of both direct combustion emissions and long-range transported, aged pollution. In summer, the decreasing anthropogenic pollution is replaced by natural emissions. These include marine secondary, biogenic secondary and primary biological emissions, which have the potential to be important to Arctic climate by modifying the cloud condensation nuclei properties and acting as ice-nucleating particles. Their source strength or atmospheric processing is sensitive to nutrient availability, solar radiation, temperature and snow cover. Our results provide a comprehensive understanding of the current pan-Arctic organic aerosol, which can be used to support modelling efforts that aim to quantify the climate impacts of emissions in this sensitive region.
2022
2022
Machine learning-based stocks and flows modeling of road infrastructure
This paper introduces a new method to account for the stocks and flows of road infrastructure at the national level based on material flow accounting (MFA). The proposed method closes some of the current shortcomings in road infrastructures that were identified through MFA: (1) the insufficient implementation of prospective analysis, (2) heavy use of archetypes as a way to represent road infrastructure, (3) inadequate attention to the inclusion of dissipative flows, and (4) limited coverage of the uncertainties. The proposed dynamic bottom-up MFA method was tested on the Norwegian road network to estimate and predict the material stocks and flows between 1980 and 2050. Here, a supervised machine learning model was introduced to estimate the road infrastructure instead of archetypical mapping of different roads. The dissipation of materials from the road infrastructure based on tire–pavement interaction was incorporated. Moreover, this study utilizes iterative classified and regression trees, lifetime distributions, randomized material intensities, and sensitivity analyses to quantify the uncertainties.
2022
2022
Pharmacokinetics of PEGylated Gold Nanoparticles: In Vitro—In Vivo Correlation
Data suitable for assembling a physiologically-based pharmacokinetic (PBPK) model for nanoparticles (NPs) remain relatively scarce. Therefore, there is a trend in extrapolating the results of in vitro and in silico studies to in vivo nanoparticle hazard and risk assessment. To evaluate the reliability of such approach, a pharmacokinetic study was performed using the same polyethylene glycol-coated gold nanoparticles (PEG-AuNPs) in vitro and in vivo. As in vitro models, human cell lines TH1, A549, Hep G2, and 16HBE were employed. The in vivo PEG-AuNP biodistribution was assessed in rats. The internalization and exclusion of PEG-AuNPs in vitro were modeled as first-order rate processes with the partition coefficient describing the equilibrium distribution. The pharmacokinetic parameters were obtained by fitting the model to the in vitro data and subsequently used for PBPK simulation in vivo. Notable differences were observed in the internalized amount of Au in individual cell lines compared to the corresponding tissues in vivo, with the highest found for renal TH1 cells and kidneys. The main reason for these discrepancies is the absence of natural barriers in the in vitro conditions. Therefore, caution should be exercised when extrapolating in vitro data to predict the in vivo NP burden and response to exposure.
2022
Acquired drug resistance and metastasis in breast cancer (BC) are coupled with epigenetic deregulation of gene expression. Epigenetic drugs, aiming to reverse these aberrant transcriptional patterns and sensitize cancer cells to other therapies, provide a new treatment strategy for drug-resistant tumors. Here we investigated the ability of DNA methyltransferase (DNMT) inhibitor decitabine (DAC) to increase the sensitivity of BC cells to anthracycline antibiotic doxorubicin (DOX). Three cell lines representing different molecular BC subtypes, JIMT-1, MDA-MB-231 and T-47D, were used to evaluate the synergy of sequential DAC + DOX treatment in vitro. The cytotoxicity, genotoxicity, apoptosis, and migration capacity were tested in 2D and 3D cultures. Moreover, genome-wide DNA methylation and transcriptomic analyses were employed to understand the differences underlying DAC responsiveness. The ability of DAC to sensitize trastuzumab-resistant HER2-positive JIMT-1 cells to DOX was examined in vivo in an orthotopic xenograft mouse model. DAC and DOX synergistic effect was identified in all tested cell lines, with JIMT-1 cells being most sensitive to DAC. Based on the whole-genome data, we assume that the aggressive behavior of JIMT-1 cells can be related to the enrichment of epithelial-to-mesenchymal transition and stemness-associated pathways in this cell line. The four-week DAC + DOX sequential administration significantly reduced the tumor growth, DNMT1 expression, and global DNA methylation in xenograft tissues. The efficacy of combination therapy was comparable to effect of pegylated liposomal DOX, used exclusively for the treatment of metastatic BC. This work demonstrates the potential of epigenetic drugs to modulate cancer cells' sensitivity to other forms of anticancer therapy.
2022
The modified Target Diagram (MTD) was developed to evaluate the performance of low-cost sensors (LCS) for air quality monitoring in comparison with reference methods by reporting relative expanded uncertainty and its contributors. An MTD provides several pieces of information, including compliance with regulation, sources of error and how to diminish them, completeness and validity of LCS calibration etc. It allows the user to examine the effect of selecting different regression types and residual fitting on the LCS measurement uncertainty. The ordinary least squared regression with fitted residuals and dynamic between reference analyser uncertainty rather than constant ones yielded more realistic LCS measurement uncertainty compared to other options. The MTD is a fast visual tool to extract several pieces of information on evaluation of any candidate method against reference method.
2022
The Arctic is warming two to three times faster than the global average, and the role of aerosols is not well constrained. Aerosol number concentrations can be very low in remote environments, rendering local cloud radiative properties highly sensitive to available aerosol. The composition and sources of the climate-relevant aerosols, affecting Arctic cloud formation and altering their microphysics, remain largely elusive due to a lack of harmonized concurrent multi-component, multi-site, and multi-season observations. Here, we present a dataset on the overall chemical composition and seasonal variability of the Arctic total particulate matter (with a size cut at 10 μm, PM10, or without any size cut) at eight observatories representing all Arctic sectors. Our holistic observational approach includes the Russian Arctic, a significant emission source area with less dedicated aerosol monitoring, and extends beyond the more traditionally studied summer period and black carbon/sulfate or fine-mode pollutants. The major airborne Arctic PM components in terms of dry mass are sea salt, secondary (non-sea-salt, nss) sulfate, and organic aerosol (OA), with minor contributions from elemental carbon (EC) and ammonium. We observe substantial spatiotemporal variability in component ratios, such as EC/OA, ammonium/nss-sulfate and OA/nss-sulfate, and fractional contributions to PM. When combined with component-specific back-trajectory analysis to identify marine or terrestrial origins, as well as the companion study by Moschos et al 2022 Nat. Geosci. focusing on OA, the composition analysis provides policy-guiding observational insights into sector-based differences in natural and anthropogenic Arctic aerosol sources. In this regard, we first reveal major source regions of inner-Arctic sea salt, biogenic sulfate, and natural organics, and highlight an underappreciated wintertime source of primary carbonaceous aerosols (EC and OA) in West Siberia, potentially associated with the oil and gas sector. The presented dataset can assist in reducing uncertainties in modelling pan-Arctic aerosol-climate interactions, as the major contributors to yearly aerosol mass can be constrained. These models can then be used to predict the future evolution of individual inner-Arctic atmospheric PM components in light of current and emerging pollution mitigation measures and improved region-specific emission inventories.
2022
The influence of photochemistry on outdoor to indoor NO2 in some European museums
This paper reports 1 year of monthly average NO2 indoor to outdoor (I/O) concentrations measured in 10 European museums, and a simple steady-state box model that explains the annual variation. The measurements were performed in the EU FP5 project Master (EVK-CT-2002-00093). The work provides extensive documentation of the annual variation of NO2 I/O concentration ratios, with ratios above unity in the summer, in situations with no indoor emissions of NO2. The modelling included the most relevant production and removal processes of NO2 and showed that the outdoor photolysis was the probable main explanation of the annual trends in the NO2 I/O concentration ratios.
2022
Human adaptation to climate change is the outcome of long-term decisions continuously made and revised by local communities. Adaptation choices can be represented by economic investment models in which the often large upfront cost of adaptation is offset by the future benefits of avoiding losses due to future natural hazards. In this context, we investigate the role that expectations of future natural hazards have on adaptation in the Colorado River basin of the USA. We apply an innovative approach that quantifies the impacts of changes in concurrent climate extremes, with a focus on flooding events. By including the expectation of future natural hazards in adaptation models, we examine how public policies can focus on this component to support local community adaptation efforts. Findings indicate that considering the concurrent distribution of several variables makes quantification and prediction of extremes easier, more realistic, and consequently improves our capability to model human systems adaptation. Hazard expectation is a leading force in adaptation. Even without assuming increases in exposure, the Colorado River basin is expected to face harsh increases in damage from flooding events unless local communities are able to incorporate climate change and expected increases in extremes in their adaptation planning and decision making.
2022
This report aims to support the on-going revision of the Ambient Air Quality Directives by providing a series of recommendations on the reciprocal exchange of information and reporting of ambient air quality (e-reporting) following the Commission Implementing Decision (2011/850/EU). It builds on the experience and understanding from the EEA and technical experts at its European Topic Centre for Human Health and the Environment (ETC HE) working with implementing provisions for reporting (IPR) and identifies areas for further efficiency gains in e-reporting, in particular concerning the H-K dataflows.
ETC/HE
2022
Environmental contaminants in freshwater food webs, 2021
This report presents monitoring data from freshwater food webs and abiotic samples from Lake Mjøsa and Femunden within the
Milfersk programme. Studies and monitoring of legacy and emerging contaminants have been carried out through this programme
for several years, focusing on the pelagic food web. This is the first report in the monitoring program focusing on a benthic food
chain (Chironomids, ruffe, roach and perch) in addition to inputs to Lake Mjøsa by analysis of lake sediments, surface waters,
stormwater, effluent and sludge from a wastewater treatment plant (WWTP). The analytical programme includes the determination
of a total of ̴ 260 single components.
Norsk institutt for vannforskning (NIVA)
2022
Atmospheric Supply of Nitrogen, Copper, HCB, BDE-99, SCCP and PFOS to the Baltic Sea in 2020.
Norwegian Meteorological Institute
2022
Microplastics in Norwegian coastal areas, rivers, lakes and air (MIKRONOR1)
Norsk institutt for vannforskning
2022
Frontiers Media S.A.
2022
Environmental Contaminants in an Urban Fjord, 2021
This report presents data from the first year of a new 5-year period of the Urban Fjord programme. The programme started in 2013 and has since been altered/advanced. In 2021 the programme covers sampling and analyses of stormwater, river water, effluent from a wastewater treatment plant (inputs to the fjord), fjord sediment, blue mussel, cod and (river) trout, all from the Inner Oslofjord area. A total of 260 single compounds/isomers were analysed and frequent detection was found of benzothiazoles in abiotic aqueous phases, UV-compounds in most matrices, metals in all matrices, PBDEs in biota, chlorinated paraffins in all matrices and PCBs in biota and abiotic particle phases. Four
Norsk institutt for vannforskning (NIVA)
2022
Microplastics in Norwegian coastal areas, rivers, lakes and air (MIKRONOR1)
The Norwegian Environment Agency (Miljødirektoratet, NEA) tasked the Norwegian Institute for Water Research (NIVA) to initiate Norway’s National microplastic monitoring program. The program “Microplastics in Norwegian coastal areas, rivers, lakes and air (MIKRONOR)”, was designed to target the multitude of environments in the Norwegian coastal, freshwater and terrestrial ecosystems. The primary aim is to provide information on levels and types of microplastics in aquatic environments as well as in air and build on the baseline data already generated for a number of these environments on previous assignments by NEA.
This report contains the first results of coastal sites, open marine waters, lakes, rivers and air including high-volume water samples (freshwater and marine, n=48), Ferrybox samples (marine, n=20), blue mussels (marine, n=71), vertical plankton net samples (marine, n=29) and 24 air samples (precipitation n= 12 and active air sampling n = 12).
Norsk institutt for vannforskning (NIVA)
2022
2022
2022