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While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios.
In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs.
Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.
2022
Three-dimensional (3D) cloud structures may impact atmospheric trace gas products from ultraviolet–visible (UV–Vis) sounders. We used synthetic and observational data to identify and quantify possible cloud-related bias in NO2 tropospheric vertical column density (TVCD). The synthetic data were based on high-resolution large eddy simulations which were input to a 3D radiative transfer model. The simulated visible spectra for low-earth-orbiting and geostationary geometries were analysed with standard retrieval methods and cloud correction schemes that are employed in operational NO2 satellite products. For the observational data, the NO2 products from the TROPOspheric Monitoring Instrument (TROPOMI) were used, while the Visible Infrared Imaging Radiometer Suite (VIIRS) provided high-spatial-resolution cloud and radiance data. NO2 profile shape, cloud shadow fraction, cloud top height, cloud optical depth, and solar zenith and viewing angles were identified as the metrics being the most important in identifying 3D cloud impacts on NO2 TVCD retrievals. For a solar zenith angle less than about 40∘ the synthetic data show that the NO2 TVCD bias is typically below 10 %, while for larger solar zenith angles the NO2 TVCD is low-biased by tens of percent. The horizontal variability of NO2 and differences in TROPOMI and VIIRS overpass times make it challenging to identify a similar bias in the observational data. However, for optically thick clouds above 3000 m, a low bias appears to be present in the observational data.
2022
Do cytotoxicity and cell death cause false positive results in the in vitro comet assay?
The comet assay is used to measure DNA damage induced by chemical and physical agents. High concentrations of test agents may cause cytotoxicity or cell death, which may give rise to false positive results in the comet assay. Systematic studies on genotoxins and cytotoxins (i.e. non-genotoxic poisons) have attempted to establish a threshold of cytotoxicity or cell death by which DNA damage results measured by the comet assay could be regarded as a false positive result. Thresholds of cytotoxicity/cell death range from 20% to 50% in various publications. Curiously, a survey of the latest literature on comet assay results from cell culture studies suggests that one-third of publications did not assess cytotoxicity or cell death. We recommend that it should be mandatory to include results from at least one type of assay on cytotoxicity, cell death or cell proliferation in publications on comet assay results. A combination of cytotoxicity (or cell death) and proliferation (or colony forming efficiency assay) is preferable in actively proliferating cells because it covers more mechanisms of action. Applying a general threshold of cytotoxicity/cell death to all types of agents may not be applicable; however, 25% compared to the concurrent negative control seems to be a good starting value to avoid false positive comet assay results. Further research is needed to establish a threshold value to distinguish between true and potentially false positive genotoxic effects detected by the comet assay.
2022
2022
The alamar blue assay in the context of safety testing of nanomaterials
The Alamar Blue (AB) assay is widely used to investigate cytotoxicity, cell proliferation and cellular metabolic activity within different fields of toxicology. The use of the assay with nanomaterials (NMs) entails specific aspects including the potential interference of NMs with the test. The procedure of the AB assay applied for testing NMs is described in detail and step-by-step, from NM preparation, cell exposure, inclusion of interference controls, to the analysis and interpretation of the results. Provided that the proper procedure is followed, and relevant controls are included, the AB assay is a reliable and high throughput test to evaluate the cytotoxicity/proliferation/metabolic response of cells exposed to NMs.
Frontiers Media S.A.
2022
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
2022
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
2022
2022
2022
The way Norway is spearheading electrification in the transport sector is of global interest. In this study, we used the Norwegian Emissions from Road Vehicle Exhaust (NERVE) model, a bottom-up high-resolution traffic emission model, to calculate all emissions in Norway (2009–2020) and evaluate potential co-benefit and trade-offs of policies to target climate change mitigation, air quality and socioeconomic factors. Results for municipal data with regard to traffic growth, road network influences, vehicle composition, emissions and energy consumption are presented. Light vehicle CO2 emissions per kilometer have been reduced by 22% since 2009, mainly driven by an increasing bio-fuel mixing and battery electric vehicles (BEV) share. BEVs are mostly located in and around the main cities, areas with young vehicle fleets, and strong local incentives. Beneficiaries of BEVs incentives have been a subset of the population with strong economic indicators. The incentivized growth in the share of diesel-fuelled passenger vehicles has been turned, and together with Euro6 emission standards, light vehicle NOx emissions have been halved since peaking in 2014. BEVs represent an investment in emission reductions in years to come, and current sales set Norway up for an accelerated decline in all exhaust emissions despite the continual growth in traffic.
MDPI
2022
Mercury isotope evidence for Arctic summertime re-emission of mercury from the cryosphere
During Arctic springtime, halogen radicals oxidize atmospheric elemental mercury (Hg0), which deposits to the cryosphere. This is followed by a summertime atmospheric Hg0 peak that is thought to result mostly from terrestrial Hg inputs to the Arctic Ocean, followed by photoreduction and emission to air. The large terrestrial Hg contribution to the Arctic Ocean and global atmosphere has raised concern over the potential release of permafrost Hg, via rivers and coastal erosion, with Arctic warming. Here we investigate Hg isotope variability of Arctic atmospheric, marine, and terrestrial Hg. We observe highly characteristic Hg isotope signatures during the summertime peak that reflect re-emission of Hg deposited to the cryosphere during spring. Air mass back trajectories support a cryospheric Hg emission source but no major terrestrial source. This implies that terrestrial Hg inputs to the Arctic Ocean remain in the marine ecosystem, without substantial loss to the global atmosphere, but with possible effects on food webs.
2022
2022
2022
Elucidating nanofibre genotoxic mechanisms: An interlaboratory approach
John Wiley & Sons
2022
Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau
The Tibetan Plateau (TP) contains the largest amount of snow outside the polar regions and is the source of many major rivers in Asia. An accurate long-range (i.e. seasonal) meteorological forecast is of great importance for this region. The fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5) provides global long-range meteorological forecasts including over the TP. However, SEAS5 uses land initial conditions produced by assimilating Interactive Multisensor Snow and Ice Mapping System (IMS) snow data only below 1500 m altitude, which may affect the forecast skill of SEAS5 over mountainous regions like the TP. To investigate the impacts of snow assimilation on the forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer 2018. Significant changes occur in the springtime. Without snow assimilation, the reforecasts overestimate snow cover and snow depth while underestimating daily temperature over the TP. Compared to satellite-based estimates, precipitation reforecasts perform better in the west TP (WTP) than in the east TP (ETP). With snow assimilation, the reforecasts of snow cover, snow depth and temperature are consistently improved in the TP in the spring. However, the positive bias between the precipitation reforecasts and satellite observations worsens in the ETP. Compared to the experiment with no snow assimilation, the snow assimilation experiment significantly increases temperature and precipitation for the ETP and around the longitude 95∘ E. The higher temperature after snow assimilation, in particular the cold bias reduction after initialization, can be attributed to the effects of a more realistic, decreased snowpack, providing favourable conditions for generating more precipitation. Overall, snow assimilation can improve seasonal forecasts through the interaction between land and atmosphere.
2022
State of the Climate in 2021: The Arctic
American Meteorological Society
2022
Havforskningsinstituttet
2022