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Lack of mutagenicity of TiO2 nanoparticles in vitro despite cellular and nuclear uptake
The potential genotoxicity of titanium dioxide (TiO2) nanoparticles (NPs) is a conflictive topic because both positive and negative findings have been reported. To add clarity, we have carried out a study with two cell lines (V79–4 and A549) to evaluate the effects of TiO2 NPs (NM-101), with a diameter ranging from 15 to 60 nm, at concentrations 1–75 μg/cm2. Using two different dispersion procedures, cell uptake was determined by Transmission Electron Microscopy (TEM). Mutagenicity was evaluated using the Hprt gene mutation test, while genotoxicity was determined with the comet assay, detecting both DNA breaks and oxidized DNA bases (with formamidopyrimidine glycosylase - Fpg). Cell internalization, as determined by TEM, shows TiO2 NM-101 in cytoplasmic vesicles, as well as close to and inside the nucleus. Such internalization did not depend on the state of agglomeration, nor the dispersion used. In spite of such internalization, no cytotoxicity was detected in V79–4 cells (relative growth activity and plating efficiency assays) or in A549 cells (AlamarBlue assay) after exposure lasting for 24 h. However, a significant decrease in the relative growth activity was detected at longer exposure times (48 and 72 h) and at the highest concentration 75 µg/cm2. When the modified enzyme-linked alkaline comet assay was performed on A549 cells, although no significant induction of DNA damage was detected, a positive concentration-effects relationship was observed (Spearman’s correlation = 0.9, p 0.0001). Furthermore, no significant increase of DNA oxidized purine bases was observed. When the frequency of Hprt gene mutants was determined in V79–4 cells, no increase was observed in the exposed cells, relative to the unexposed cultures. Our general conclusion is that, under our experimental conditions, TiO2 NM-101 exposure does not exert mutagenic effects despite the evidence of NP uptake by V79–4 cells.
2022
2022
2022
FAIRMODE Guidance Document on Modelling Quality Objectives and Benchmarking. Version 3.3.
The development of the procedure for air quality model benchmarking in the context of the Air Quality Directive 2008/50/EC (AQD) has been an on-going activity in the context of the FAIRMODE community, chaired by the JRC. A central part of the studies was the definition of proper modelling quality indicators and criteria to be fulfilled in order to allow sufficient level of quality for a given model application under the AQD. The focus initially on applications related to air quality assessment has gradually been expanded to other applications, such as forecasting and planning. The main purpose of this Guidance Document is to explain and summarise the current concepts of the modelling quality objective methodology, elaborated in various papers and documents in the FAIRMODE community, addressing model applications for air quality assessment and forecast. Other goals of the Document are linked to presentation and explanation of templates for harmonised reporting of modelling results. Giving an overview of still open issues in the implementation of the presented methodology, the document aims at triggering further research and discussions. A core set of statistical indicators is defined using pairs of measurement-modelled data. The core set is the basis for the definition of a modelling quality indicator (MQI) and additional modelling performance indicators (MPI), which take into account the measurement uncertainty. The MQI describes the discrepancy between measurements and modelling results (linked to RMSE), normalised by measurement uncertainty and a scaling factor. The modelling quality objective (MQO) requires MQI to be less than or equal to 1. With an arbitrary selection of the scaling factor of 2, the fulfilment of the MQO means that the allowed deviation between modelled and measured concentrations is twice the measurement uncertainty. Expressions for the MQI calculation based on time series and yearly data are introduced. MPI refer to aspects of correlation, bias and standard deviation, applied to both the spatial and temporal dimensions. Similarly to the MQO for the MQI, modelling performance criteria (MPC) are defined for the MPI; they are necessary, but not sufficient criteria to determine whether the MQO is fulfilled. The MQO is required to be fulfilled at 90% of the stations, a criterion which is implicitly taken into account in the derivation of the MQI. The associated modelling uncertainty is formulated, showing that in case of MQO fulfilment the modelling uncertainty must not exceed 1.75 times the measurement one (with the scaling factor fixed to 2). A reporting template is presented and explained for hourly and yearly average data. In both cases there is a diagram and a table with summary statistics. In a separate section open issues are discussed and an overview of related publications and tools is provided. Finally, a chapter on modelling quality objectives for forecast models is introduced. In Annex 1, we discuss the measurement uncertainty which is expressed in terms of concentration and its associated uncertainty. The methodology for estimating the measurement uncertainty is overviewed and the parameters for its calculation for PM, NO2 and O3 are provided. An expression for the associated modelling uncertainty is also given. This aim of this document is to support modelling groups, local, regional and national authorities in their modelling application, in the context of air quality policy.
Publications Office for the European Union
2022
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
2022
Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface...
2022
The miniaturized enzyme-modified comet assay for genotoxicity testing of nanomaterials
The in vitro comet assay is a widely applied method for investigating genotoxicity of chemicals including engineered nanomaterials (NMs). A big challenge in hazard assessment of NMs is possible interference between the NMs and reagents or read-out of the test assay, leading to a risk of biased results. Here, we describe both the standard alkaline version of the in vitro comet assay with 12 mini-gels per slide for detection of DNA strand breaks and the enzyme-modified version that allows detection of oxidized DNA bases by applying lesion-specific endonucleases (e.g., formamidopyrimidine DNA glycosylase or endonuclease III). We highlight critical points that need to be taken into consideration when assessing the genotoxicity of NMs, as well as basic methodological considerations, such as the importance of carrying out physicochemical characterization of the NMs and investigating uptake and cytotoxicity. Also, experimental design—including treatment conditions, cell number, cell culture, format and volume of medium on the plate—is crucial and can have an impact on the results, especially when testing NMs. Toxicity of NMs depends upon physicochemical properties that change depending on the environment. To facilitate testing of numerous NMs with distinct modifications, the higher throughput miniaturized version of the comet assay is essential.
Frontiers Media S.A.
2022
High-Resolution Emissions from Wood Burning in Norway—The Effect of Cabin Emissions
Emissions from wood burning for heating in secondary homes or cabins is an important part in the development of high-resolution emissions in specific areas. Norway is used as case study as 20% of the national wood consumption for heating occurs in cabins. Our study first shows a method to estimate emissions from cabins based on traffic data to derive cabin occupancy, which combined with heating need allows for the spatial and temporal distribution of emissions. The combination of residential (RWC) and cabin wood combustion (CWC) emissions shows large spatial and temporal differences, and a temporally “cabin population” can in areas be orders of magnitude larger than the registered population. While RWC emissions have been steadily reduced, CWC have kept relatively constant or even increased, which results in an increase in the cabin share to total heating emissions up to 25–35%. When comparing with regional emission inventories, our study shows that the gradient between rural and urban areas is not well-represented in regional inventories, which resembles a population-based distribution and does not allocate emissions in cabin municipalities. CWC emissions may become an increasing environmental concern as higher densification trends in mountain areas are observed.
MDPI
2022
2022
The EmSite model for high resolution emissions from machinery in construction sites
The report describes the EmSite model developed to estimate exhaust and non-exhaust emissions from non-road mobile machinery (NRMM) used in building and construction. The model is based on a complete national database of the exact location of construction and building activity, machine registries and variables that affect emissions (ground conditions, meteorology, type of ground material). EmSite model allows us to determine, i) the location, area and time of construction projects at fine resolution; ii) energy demand for NRMM; and iii) fuel consumption, air pollutants and GHGs emissions. For exhaust emissions, specific dynamic emission factors for NRMMs were developed. For non-exhaust emissions, an approach based on the Tier 1 (EMEP/EEA Guidebook, 2019) was chosen. EmSite allows for bottom-up estimates for NRMM employed in construction, and the results are comparable with official air pollutant and GHGs emissions.
NILU
2022
Screening Programme 2020, Part 1 and 2: Plastic Additives and REACH Compounds
I screening 2020 gjennomført av Norsk institutt for vannforskning (NIVA) og NILU-Norsk institutt for luftforskning i fellesskap ble det satt søkelys på forekomst og mulige miljøproblemer av 160 kjemikalier. Forbindelser som er valgt ut til Screening 2020 inkluderer tilsetningsstoffer til plast og nylig registrerte stoffer i REACH registeret.
Norsk institutt for vannforskning
2022
Mercury in air and soil on an urban-rural transect in East Africa
There are large knowledge gaps concerning concentrations, sources, emissions, and spatial trends of mercury (Hg) in the atmosphere in developing regions of the Southern Hemisphere, particularly in urban areas. Filling these gaps is a prerequisite for assessing the effectiveness of international regulation and for enabling a better understanding of the global transport of Hg in the environment. Here we use a passive sampling technique to study the spatial distribution of gaseous elemental Hg (Hg(0), GEM) and assess emission sources in and around Dar es Salaam, Tanzania's largest city. Included in the study were the city's main municipal waste dumpsite and an e-waste processing facility as potential sources of GEM. To complement the GEM data and for a better overview of the Hg contamination status of Dar es Salaam, soil samples were collected from the same locations where passive air samplers were deployed and analysed for total Hg. Overall, GEM concentrations ranged between <0.86 and 5.34 ng m−3, indicating significant local sources within the urban area. The municipal waste dumpsite and e-waste site had GEM concentrations elevated above the background, at 2.41 and 1.77 ng m−3, respectively. Hg concentrations in soil in the region (range 0.0067 to 0.098 mg kg−1) were low compared to those of other urban areas and were not correlated with atmospheric GEM concentrations. This study demonstrates that GEM is a significant environmental issue in the urban region of Dar es Salaam. Further studies from urban areas in the Global South are needed to better identify sources of GEM.
Royal Society of Chemistry (RSC)
2022
Potential environmental impact of bromoform from Asparagopsis farming in Australia
To mitigate the rumen enteric methane (CH4) produced by ruminant livestock, Asparagopsis taxiformis is proposed as an additive to ruminant feed. During the cultivation of Asparagopsis taxiformis in the sea or in terrestrially based systems, this macroalgae, like most seaweeds and phytoplankton, produces a large amount of bromoform (CHBr3), which contributes to ozone depletion once released into the atmosphere. In this study, we focus on the impact of CHBr3 on the stratospheric ozone layer resulting from potential emissions from proposed Asparagopsis cultivation in Australia. The impact is assessed by weighting the emissions of CHBr3 with its ozone depletion potential (ODP), which is traditionally defined for long-lived halocarbons but has also been applied to very short-lived substances (VSLSs). An annual yield of ∼3.5 × 104 Mg dry weight is required to meet the needs of 50 % of the beef feedlot and dairy cattle in Australia. Our study shows that the intensity and impact of CHBr3 emissions vary, depending on location and cultivation scenarios. Of the proposed locations, tropical farms near the Darwin region are associated with the largest CHBr3 ODP values. However, farming of Asparagopsis using either ocean or terrestrial cultivation systems at any of the proposed locations does not have the potential to significantly impact the ozone layer. Even if all Asparagopsis farming were performed in Darwin, the CHBr3 emitted into the atmosphere would amount to less than 0.02 % of the global ODP-weighted emissions. The impact of remaining farming scenarios is also relatively small even if the intended annual yield in Darwin is scaled by a factor of 30 to meet the global requirements, which will increase the global ODP-weighted emissions up to ∼0.5 %.
2022
Condensable primary organic aerosol (CPOA) emissions are a class of organic compounds that are vapour phase at stack conditions, but which can undergo both condensation and evaporation processes as the stack air is cooled and diluted upon discharge into ambient air. Emission factors may misrepresent, and even miss, the amount of particulate matter (PM) or gas that actually enters the atmosphere, depending on the emission measurement techniques used. In the current emission reporting to EMEP/CLRTAP there is no clear definition of whether condensable organics are included or not, and, if included, to what extent.
In this study, new residential combustion emission estimates have been made for the years 2005-2019 (called TNO Ref2_v2.1) in a consistent manner, with improved estimation of fuel consumption (in particular wood) and emission factors, as well as an updated split of fuel use over different appliances and technologies. For these two elements, data were taken primarily from the Eurostat fuel statistics and the IIASA GAINS model. Three scenarios have been defined: a “typical” case, which is our best estimate, an alternative “ideal” case which excludes the impact of “bad combustion”, and a “high EF” scenario in which higher emission factors are assumed than in the typical scenario. Total emissions in the typical scenario are around 40% higher than in the ideal case (in 2019), whereas resulting emissions in the “high EF” scenario are around 90% higher than in the typical scenario.
The Ref2_v2.1 inventory was used in a series of modelling studies which aimed to assess the importance of condensable organics for current air quality, for trends over time (2010–2019), and for source-receptor calculations.
Including condensables in a consistent way for all countries gave model results (concentrations, trends and bias) in better agreement with observations for OC and PM2.5 than when using the EMEP emissions which have condensables for some countries but not others. However, the model results were sensitive to the choice of Ref2_v2.1 scenario, and also to the assumptions concerning volatility of the CPOA emissions, and assumptions about extra intermediate-volatility volatile organic compounds (IVOC) associated with such emissions.
No single setup performed best for each site. There are many factors that can contribute to such mixed results (activity data, emissions factors, assumed combustion conditions, large and small scale spatial distributions issues in emissions, dispersion and CPOA/IVOC assumptions in the modelling), and much further work (and with other observational data-sets) will be needed to disentangle the reasons for model-measurement discrepancies, and to draw conclusions on how realistic the new emissions are.
Assumptions about volatility seem to be important for both the country-to-itself contribution, and for impacts of each country on others. In the few cases investigated so far, assuming inert CPOA provides results which generally lie within the range of the more complex VBS scenarios. Given the many uncertainties associated with the emissions and the modelling of POA and SOA, these results indicates that the inert CPOA assumptions provide a reasonable first approach for handling POA emissions, which can hopefully be improved once our understanding of the sources and processing of these compounds improves.
The new emission data-base, combined with increasing availability of measurements of organic and other components, should provide the best available basis for future improvements in both the emission inventories and model formulations. Much analysis and further tests remain, both with the other model setups, and ideally with alternative secondary organic aerosol schemes to get a better idea of the sensitivity of the results to the various assumptions concerning both emissions and atmospheric processing of POA.
Nordic Council of Ministers
2022
2022
Air pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited accuracy of the PM detector, the measurement data are refined using a two-stage procedure that involves elimination of the non-physical signal spikes followed by a non-linear correction of the responses using a multiplicative surrogate model. The correction layer is derived from the sparse and non-uniform calibration data, i.e., a combination of the measurements from the PM monitoring station and the sensor obtained in the same location over a specified (relatively short) interval. The device and the method have been both demonstrated based on the data obtained during three measurement campaigns. The proposed correction scheme improves the fidelity of PM measurements by around two orders of magnitude w.r.t. the responses for which the post-processing has not been considered. Performance of the proposed surrogate-assisted technique has been favorably compared against the benchmark approaches from the literature.
2022
2022