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Per and polyfluoroalkyl substances (PFASs) are found in Antarctic wildlife, with high levels in the avian top predator south polar skua (Catharacta maccormicki). As increasing PFAS concentrations were found in the south polar skua during the breeding season in Antarctica, we hypothesised that available prey during the breeding period contributes significantly to the PFAS contamination in skuas. To test this, we compared PFAS in south polar skuas and their main prey from two breeding sites on opposite sides of the Antarctic continent: Antarctic petrel (Thalassoica antarctica) stomach content, eggs, chicks, and adults from Svarthamaren in Dronning Maud Land and Adélie penguin chicks (Pygoscelis adeliae) from Dumont d’Urville in Adélie Land. Of the 22 PFAS analysed, seven were present in the majority of samples, except petrel stomach content [only perfluoroundecanoate (PFUnA) present] and Adélie penguins (only four compounds present), with increasing concentrations from the prey to the skuas. The biomagnification factors (BMFs) were higher at Dumont d’Urville than Svarthamaren. When adjusted to reflect one trophic level difference, the BMFs at Svarthamaren remained the same, whereas the ones at Dumont d’Urville doubled. At both the colonies, the skua PFAS pattern was dominated by perfluorooctanesulfonic acid (PFOS), followed by PFUnA, but differed with the presence of branched PFOS and perfluorotetradecanoate (PFTeA) and lack of perfluorononanoate (PFNA) and perfluorodecanoate (PFDA) at Dumont d’Urville. At Svarthamaren, the pattern in the prey was comparable to the skuas, but with a higher relative contribution of PFTeA in prey. At Dumont d’Urville, the pattern in the prey differed from the skuas, with the domination of PFUnA and the general lack of PFOS in prey. Even though the PFAS levels are low in Antarctic year-round resident prey, the three lines of evidence (pattern, BMF difference, and BMF adjusted to one trophic level) suggest that the Antarctic petrel are the significant source of PFAS in the Svarthamaren skuas, whereas the skuas in Dumont d’Urville have other important sources to PFAS than Adélie penguin, either in the continent or external on the inter-breeding foraging grounds far from Antarctica.
Frontiers Media S.A.
2022
The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian continental shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t yr−1 (with a mean of 211 t yr−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes only 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representativity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritising targeted emission mitigation solutions. Future surveys of individual facilities would benefit from knowledge of facility operational status over time. Field-specific aggregated emissions (and uncertainty statistics), as presented here for the Norwegian Sea, can be meaningfully estimated from intensive aircraft surveys. However, field-specific estimates cannot be reliably extrapolated to other production fields without their own tailored surveys, which would need to capture a range of facility designs, oil and gas production volumes, and facility ages. For year-on-year comparison to annually updated inventories and regulatory emission reporting, analogous annual surveys would be needed for meaningful top-down validation. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of airborne measurement approaches to validate bottom-up accounting.
2022
Evaluation and Global-Scale Observation of Nitrous Oxide from IASI on Metop-A
Nitrous oxide (N2O) is a greenhouse gas difficult to estimate by satellite because of its weak spectral signature in the infra-red band and its low variability in the troposphere. Nevertheless, this study presents the evaluation of new tropospheric N2O observations from the Infrared Atmospheric Sounder Interferometer (IASI) on Metop-A using the Toulouse N2O Retrieval Version 2.0 tool. This tool is based on the Radiative Transfer for Tiros Operational Vertical sounder (RTTOV) model version 12.3 coupled to the Levenberg-Marquardt optimal estimation method enabling the simultaneous retrieval of methane, water vapour, temperature profiles together with surface temperature and emissivity within the 1240–1350 cm−1 window. In this study, we focused on the upper troposphere (300 hPa) where the sensitivity of IASI is significant. The IASI N2O data has been evaluated using aircraft N2O observations from the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO) campaigns in 2009, 2010, and 2011 and from the National Oceanic and Atmospheric Administration’s (NOAA) Global Greenhouse Gas Reference Network (GGGRN) in 2011. In addition, we evaluated the IASI N2O using ground-based N2O measurements from 9 stations belonging to the Network for the Detection of Atmospheric Composition Change (NDACC). We found a total random error of ∼2 ppbv (0.6%) for one single retrieval at 300 hPa. Under favorable conditions, this error is also found in the vertical level pressure range 300–500 hPa. It decreases rapidly to ∼0.4 ppbv (0.1%) when we average on a 1° × 1° box. In addition, independent observations allows the estimation of bias with the IASI TN2OR v2.0 N2O. The bias between IASI and aircraft N2O data at 300 hPa is ∼1.0 ppbv (∼0.3%). We found an estimated random error of ∼2.3 ppbv (∼0.75%). This study also shows relatively high correlations between IASI data and aircraft in situ profiles but more varying correlations over the year 2011 depending on the location between IASI and NDACC remote sensing data. Finally, we present daily, monthly, and seasonal IASI N2O horizontal distributions in the upper troposphere as well as cross sections for different seasons that exhibit maxima in the Tropical band especially over Africa and South America.
MDPI
2022
Optical properties of surface aerosols at Dome C, Antarctica, in 2007–2013 and their potential source areas are presented. Scattering coefficients (σsp) were calculated from measured particle number size distributions with a Mie code and from filter samples using mass scattering efficiencies. Absorption coefficients (σap) were determined with a three-wavelength Particle Soot Absorption Photometer (PSAP) and corrected for scattering by using two different algorithms. The scattering coefficients were also compared with σsp measured with a nephelometer at the South Pole Station (SPO). The minimum σap was observed in the austral autumn and the maximum in the austral spring, similar to other Antarctic sites. The darkest aerosol, i.e., the lowest single-scattering albedo ωo≈0.91, was observed in September and October and the highest ωo≈0.99 in February and March. The uncertainty of the absorption Ångström exponent αap is high. The lowest αap monthly medians were observed in March and the highest in August–October. The equivalent black carbon (eBC) mass concentrations were compared with eBC measured at three other Antarctic sites: the SPO and two coastal sites, Neumayer and Syowa. The maximum monthly median eBC concentrations are almost the same ( ng m−3) at all these sites in October–November. This suggests that there is no significant difference in eBC concentrations between the coastal and plateau sites. The seasonal cycle of the eBC mass fraction exhibits a minimum f(eBC) ≈0.1 % in February–March and a maximum ∼4 %–5 % in August–October. Source areas were calculated using 50 d FLEXPART footprints. The highest eBC concentrations and the lowest ωo were associated with air masses coming from South America, Australia and Africa. Vertical simulations that take BC particle removal processes into account show that there would be essentially no BC particles arriving at Dome C from north of latitude 10∘ S at altitudes
2022
2022
Ecologically unequal exchange arises if more developed economies ('core') shift the environmental burden of their consumption and capital accumulation to less developed economies ('periphery'/'semi-core'). Here we demonstrate that human populations in core regions can benefit from the use of products containing toxic chemicals while transferring to the periphery the risk of human and ecological exposure to emissions associated with manufacturing and waste disposal. We use a global scale substance flow analysis approach to quantify the emissions of polybrominated diphenyl ethers (PBDEs), a group of flame retardants added to consumer products, that are embodied in the trade of chemicals, products and wastes between seven world regions over the 2000–2020 time period. We find that core regions have off-loaded PBDE emissions, mostly associated with the disposal of electrical and electronic waste (e-waste), to semi-core and peripheral regions in mainland China and the Global South. In core regions this results in small emissions that mostly occur during the product use phase, whereas in peripheral regions emissions are much higher and dominated by end of life disposal. The transfer of toxic chemical emissions between core and periphery can be quantified and should be accounted for when appraising the costs and benefits of global trade relationships.
2022
The historical (1835–2020) deposition of major air pollutants (SO2, NOx, O3 and PM2.5) indoors, as represented by the monumental Edvard Munch paintings (c. 220 m2) installed in 1916 in the Oslo University Aula in Norway, were approximated from the outdoor air concentrations, indoor to outdoor concentration ratios and dry deposition velocities. The annual deposition of the pollutants to the paintings was found to have been 4–25 times lower than has been reported to buildings outdoors in the urban background in the centre of Oslo. It reflected the outdoor deposition but varied less, from 0.3 to 1.2 g m−2 a−1. The accumulated deposition since 1916, and then not considering the regularly performed cleaning of the paintings, was found to have been 43 ± 13 g m−2, and 110 ± 40 g m−2 in a similar situation since 1835. The ozone deposition, and the PM2.5 deposition before the 1960s, were a relatively larger part of the accumulated total indoor (to the paintings) than reported outdoor deposition. About 18 and 33 times more O3 than NOx and PM2.5 deposition was estimated to the paintings in 2020, as compared to the about similar reported outdoor dry deposition of O3 and NOx. The deposition of PM2.5 to the paintings was probably reduced with about 62% (50–80%) after installation of mechanical filtration in 1975 and was estimated to be 0.011 (± 0.006) g m−2 in 2020.
BioMed Central (BMC)
2022
The global monitoring plan of the Minamata Convention on Mercury was established to generate long-term data necessary for evaluating the effectiveness of regulatory measures at a global scale. After 25 years of monitoring (since 1995), Mace Head is one of the atmospheric monitoring stations with the longest mercury record and has produced sufficient data for the analysis of temporal trends of total gaseous mercury (TGM) in Europe and the North Atlantic. Using concentration-weighted trajectories for atmospheric mercury measured at Mace Head as well as another five locations in Europe, Amderma, Andøya, Villum, Waldhof and Zeppelin, we identify the regional probabilistic source contribution factor and its changes for the period of 1996 to 2019. Temporal trends indicate that concentrations of mercury in the atmosphere in Europe and the North Atlantic have declined significantly over the past 25 years at a non-monotonic rate averaging 0.03 . Concentrations of TGM at remote marine sites were shown to be affected by continental long-range transport, and evaluation of reanalysis back trajectories displays a significant decrease in TGM in continental air masses from Europe in the last 2 decades. In addition, using the relationship between mercury and other atmospheric trace gases that could serve as a source signature, we perform factorization regression analysis, based on positive rotatable factorization to solve probabilistic mass functions. We reconstructed atmospheric mercury concentration and assessed the contribution of the major natural and anthropogenic sources. The results reveal that the observed downward trend in the atmospheric mercury is mainly associated with a factor with a high load of long-lived anthropogenic species.
2022
The greenhouse gases (GHG) emissions in the European Union (EU) are mainly caused by human activity from five sectors—power, industry, transport, buildings, and agriculture. To tackle all these challenges, the EU actions and policies have been encouraging initiatives focusing on a holistic approach but these initiatives are not enough coordinated and connected to reach the much needed impact. To strengthen the important role of regions in climate actions, and stimulate wide stakeholders’ engagement including citizens, a conceptual framework for enabling rapid and far-reaching climate actions through multi-sectoral regional adaptation pathways is hereby developed. The target audience for this framework is composed by regional policy makers, developers and fellow scientists. The scale of the framework emphasizes the regional function as an important meeting point and delivery arena for European and national climate strategies and objectives both at urban and rural level. The framework is based on transformative and no-regret measures, prioritizing the Key Community Systems (KCS) that most urgently need to be protected from climate impacts and risks.
Frontiers Media S.A.
2022
What caused a record high PM10 episode in northern Europe in October 2020?
In early October 2020, northern Europe experienced an episode with poor air quality due to high concentrations of particulate matter (PM). At several sites in Norway, recorded weekly values exceeded historical maximum PM10 concentrations from the past 4 to 10 years. Daily mean PM10 values at Norwegian sites were up to 97 µg m−3 and had a median value of 59 µg m−3. We analysed this severe pollution episode caused by long-range atmospheric transport based on surface and remote sensing observations and transport model simulations to understand its causes. Samples from three sites in mainland Norway and the Arctic remote station Zeppelin (Svalbard) showed strong contributions from mineral dust to PM10 (23 %–36 % as a minimum and 31 %–45 % as a maximum) and biomass burning (8 %–16 % to 19 %–21 %). Atmospheric transport simulations indicate that Central Asia was the main source region for mineral dust observed in this episode. The biomass burning fraction can be attributed to forest fires in Ukraine and southern Russia, but we cannot exclude other sources contributing, like fires elsewhere, because the model underestimates observed concentrations. The combined use of remote sensing, surface measurements, and transport modelling proved effective in describing the episode and distinguishing its causes.
2022
From 2015 to 2021, we optimized mass cultivation of diatoms in our own developed vertical column airlift photobioreactors using natural and artificial light (LEDs). The project took place at the ferrosilicon producer Finnfjord AS in North Norway as a joint venture with UiT—The Arctic University of Norway. Small (0.1–6–14 m3) reactors were used for initial experiments and to produce inoculum cultures while upscaling experiments took place in a 300 m3 reactor. We here argue that species cultivated in reactors should be large since biovolume specific self-shadowing of light can be lower for large vs. small cells. The highest production, 1.28 cm3 L−1 biovolume (0.09–0.31 g DW day−1), was obtained with continuous culture at ca. 19% light utilization efficiency and 34% CO2 uptake. We cultivated 4–6 months without microbial contamination or biofouling, and this we argue was due to a natural antifouling (anti-biofilm) agent in the algae. In terms of protein quality all essential amino acids were present, and the composition and digestibility of the fatty acids were as required for feed ingredients. Lipid content was ca. 20% of ash-free DW with high EPA levels, and omega-3 and amino acid content increased when factory fume was added. The content of heavy metals in algae cultivated with fume was well within the accepted safety limits. Organic pollutants (e.g., dioxins and PCBs) were below the limits required by the European Union food safety regulations, and bioprospecting revealed several promising findings.
MDPI
2022
Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data, and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering.
In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC (Monte Carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres). The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMFs) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos.
Two cloud setups are considered: the first includes simple box clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical of central Europe such as shallow cumulus, convective cloud cells, cirrus and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically.
Along with the dataset, the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analysed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %.
The dataset is available for the scientific community to assess the behaviour of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.
2022
Atmospheric composition in the European Arctic and 30 years of the Zeppelin Observatory, Ny-Ålesund
The Zeppelin Observatory (78.90∘ N, 11.88∘ E) is located on Zeppelin Mountain at 472 m a.s.l. on Spitsbergen, the largest island of the Svalbard archipelago. Established in 1989, the observatory is part of Ny-Ålesund Research Station and an important atmospheric measurement site, one of only a few in the high Arctic, and a part of several European and global monitoring programmes and research infrastructures, notably the European Monitoring and Evaluation Programme (EMEP); the Arctic Monitoring and Assessment Programme (AMAP); the Global Atmosphere Watch (GAW); the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS); the Advanced Global Atmospheric Gases Experiment (AGAGE) network; and the Integrated Carbon Observation System (ICOS). The observatory is jointly operated by the Norwegian Polar Institute (NPI), Stockholm University, and the Norwegian Institute for Air Research (NILU). Here we detail the establishment of the Zeppelin Observatory including historical measurements of atmospheric composition in the European Arctic leading to its construction. We present a history of the measurements at the observatory and review the current state of the European Arctic atmosphere, including results from trends in greenhouse gases, chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs), other traces gases, persistent organic pollutants (POPs) and heavy metals, aerosols and Arctic haze, and atmospheric transport phenomena, and provide an outline of future research directions.
2022
We combine observations from Western USA and inverse modelling to constrain global atmospheric emissions of microplastics (MPs) and microfibers (MFs). The latter are used further to model their global atmospheric dynamics. Global annual MP emissions were calculated as 9.6 ± 3.6 Tg and MF emissions as 6.5 ± 2.9 Tg. Global average monthly MP concentrations were 47 ng m-3 and 33 ng m-3 for MFs, at maximum. The largest deposition of agricultural MPs occurred close to the world’s largest agricultural regions. Road MPs mostly deposited in the East Coast of USA, Central Europe, and Southeastern Asia; MPs resuspended with mineral dust near Sahara and Middle East. Only 1.8% of the emitted mass of oceanic MPs was transferred to land, and 1.4% of land MPs to ocean; the rest were deposited in the same environment. Previous studies reported that 0.74–1.9 Tg y-1 of land-based atmospheric MPs/MFs (
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
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
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.
John Wiley & Sons
2022
Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines
Wind turbines are one of the primary sources of renewable energy, which leads to a sustainable and efficient energy solution. It does not release any carbon emissions to pollute our planet. The wind farms monitoring and power generation prediction is a complex problem due to the unpredictability of wind speed. Consequently, it limits the decision power of the management team to plan the energy consumption in an effective way. Our proposed model solves this challenge by utilizing a 5G-Next Generation-Radio Access Network (5G-NG-RAN) assisted cloud-based digital twins’ framework to virtually monitor wind turbines and form a predictive model to forecast wind speed and predict the generated power. The developed model is based on Microsoft Azure digital twins infrastructure as a 5-dimensional digital twins platform. The predictive modeling is based on a deep learning approach, temporal convolution network (TCN) followed by a non-parametric k-nearest neighbor (kNN) regression. Predictive modeling has two components. First, it processes the univariate time series data of wind to predict its speed. Secondly, it estimates the power generation for each quarter of the year ranges from one week to a whole month (i.e., medium-term prediction) To evaluate the framework the experiments are performed on onshore wind turbines publicly available datasets. The obtained results confirm the applicability of the proposed framework. Furthermore, the comparative analysis with the existing classical prediction models shows that our designed approach obtained better results. The model can assist the management team to monitor the wind farms remotely as well as estimate the power generation in advance.
IEEE (Institute of Electrical and Electronics Engineers)
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.
MDPI
2022
Earth system and environmental impact studies need high quality and up-to-date estimates of atmospheric deposition. This study demonstrates the methodological benefits of multimodel ensemble and measurement-model fusion mapping approaches for atmospheric deposition focusing on 2010, a year for which several studies were conducted. Global model-only deposition assessment can be further improved by integrating new model-measurement techniques, including expanded capabilities of satellite observations of atmospheric composition. We identify research and implementation priorities for timely estimates of deposition globally as implemented by the World Meteorological Organization.
2022
Electrification of residential heating and investment in building energy efficiency are central pillars of many national strategies to reduce carbon emissions from the built environment sector. Ireland has a strong dependence on oil use for central heating and a substantial share of homes still using solid fuels. The current national strategy calls for the retrofitting of 400,000 home heating systems with heat pumps by 2030, principally replacing oil fired heating systems. Displacing natural gas, oil and solid fuel boilers with heat pumps will have a favourable impact on climate outcomes. However, the impact on air pollutant outcomes is far more favourable when solid fuels are replaced, and the positive impact on ambient air quality is much enhanced where concentrated clusters of solid-fuel use are targeted. This research spatially analyses emissions and air pollutant concentration outcomes for both targeted and non-targeted deployments of heat pumps and shows that a focused deployment of just 3% of the national heat pump target on solid-fuel homes could offer similar progress on climate goals but with a substantial impact in terms of reducing air pollution hot spots. For the Irish residential heating season (October–March), the targeted solid fuel scenario delivers average PM2.5 concentration decreases of 20–34%. This paper shows that these targeted communities are often in areas of relative deprivation, and as such, direct support for fabric retrofitting and heat pump technology installation offers the potential to simultaneously advance climate, air and just transition policy ambitions.
Elsevier
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.
MDPI
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.
Elsevier
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.
Elsevier
2022