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The MetVed model: development and evaluation of emissions from residential wood combustion at high spatio-temporal resolution in Norway

We present here emissions estimated from a newly developed emission model for residential wood combustion (RWC) at high spatial and temporal resolution, which we name the MetVed model. The model estimates hourly emissions resolved on a 250 m grid resolution for several compounds, including particulate matter (PM), black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) in Norway for a 12-year period. The model uses novel input data and calculation methods that combine databases built with an unprecedented high level of detail and near-national coverage. The model establishes wood burning potential at the grid based on the dependencies between variables that influence emissions: i.e. outdoor temperature, number of and type and size of dwellings, type of available heating technologies, distribution of wood-based heating installations and their associated emission factors. RWC activity with a 1 h temporal profile was produced by combining heating degree day and hourly and weekday activity profiles reported by wood consumers in official statistics. This approach results in an improved characterisation of the spatio-temporal distribution of wood use, and subsequently of emissions, required for urban air quality assessments. Whereas most variables are calculated based on bottom-up approaches on a 250 m spatial grid, the MetVed model is set up to use official wood consumption at the county level and then distributes consumption to individual grids proportional to the physical traits of the residences within it. MetVed combines consumption with official emission factors that makes the emissions also upward scalable from the 250 m grid to the national level.

The MetVed spatial distribution obtained was compared at the urban scale to other existing emissions at the same scale. The annual urban emissions, developed according to different spatial proxies, were found to have differences up to an order of magnitude. The MetVed total annual PM2.5 emissions in the urban domains compare well to emissions adjusted based on concentration measurements. In addition, hourly PM2.5 concentrations estimated by an Eulerian dispersion model using MetVed emissions were compared to measurements at air quality stations. Both hourly daily profiles and the seasonality of PM2.5 show a slight overestimation of PM2.5 levels. However, a comparison with black carbon from biomass burning and benzo(a)pyrene measurements indicates higher emissions during winter than that obtained by MetVed. The accuracy of urban emissions from RWC relies on the accuracy of the wood consumption (activity data), emission factors and the spatio-temporal distribution. While there are still knowledge gaps regarding emissions, MetVed represents a vast improvement in the spatial and temporal distribution of RWC.

2019

Open fires in Greenland in summer 2017: transport, deposition and radiative effects of BC, OC and BrC emissions

Highly unusual open fires burned in western Greenland between 31 July and 21 August 2017, after a period of warm, dry and sunny weather. The fires burned on peatlands that became vulnerable to fires by permafrost thawing. We used several satellite data sets to estimate that the total area burned was about 2345 ha. Based on assumptions of typical burn depths and emission factors for peat fires, we estimate that the fires consumed a fuel amount of about 117 kt C and emitted about 23.5 t of black carbon (BC) and 731 t of organic carbon (OC), including 141 t of brown carbon (BrC). We used a Lagrangian particle dispersion model to simulate the atmospheric transport and deposition of these species. We find that the smoke plumes were often pushed towards the Greenland ice sheet by westerly winds, and thus a large fraction of the emissions (30 %) was deposited on snow- or ice-covered surfaces. The calculated deposition was small compared to the deposition from global sources, but not entirely negligible. Analysis of aerosol optical depth data from three sites in western Greenland in August 2017 showed strong influence of forest fire plumes from Canada, but little impact of the Greenland fires. Nevertheless, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar data showed that our model captured the presence and structure of the plume from the Greenland fires. The albedo changes and instantaneous surface radiative forcing in Greenland due to the fire emissions were estimated with the SNICAR model and the uvspec model from the libRadtran radiative transfer software package. We estimate that the maximum albedo change due to the BC and BrC deposition was about 0.007, too small to be measured. The average instantaneous surface radiative forcing over Greenland at noon on 31 August was 0.03–0.04 W m−2, with locally occurring maxima of 0.63–0.77 W m−2 (depending on the studied scenario). The average value is up to an order of magnitude smaller than the radiative forcing from other sources. Overall, the fires burning in Greenland in the summer of 2017 had little impact on the Greenland ice sheet, causing a small extra radiative forcing. This was due to the – in a global context – still rather small size of the fires. However, the very large fraction of the emissions deposited on the Greenland ice sheet from these fires could contribute to accelerated melting of the Greenland ice sheet if these fires become several orders of magnitude larger under future climate.

2019

The comet assay in animal models: From bugs to whales – (Part 1 Invertebrates)

The comet assay, also called single cell gel electrophoresis, is a sensitive, rapid and low-cost technique for quantifying and analysing DNA damage and repair at the level of individual cells. The assay itself can be applied on virtually any cell type derived from different organs and tissues of eukaryotic organisms. Although it is mainly used on human cells, the assay has applications also in the evaluation of DNA damage in yeast, plant and animal cells. Therefore, the purpose of this review is to give an extensive overview on the usage of the comet assay in animal models from invertebrates to vertebrates, covering both terrestrial and water biota. The comet assay is used in a variety of invertebrate species since they are regarded as interesting subjects in ecotoxicological research due to their significance in ecosystems. Hence, the first part of the review (Part 1) will discuss the application of the comet assay in invertebrates covering protozoans, platyhelminthes, planarians, cnidarians, molluscs, annelids, arthropods and echinoderms. Besides a large number of animal species, the assay is also performed on a variety of cells, which includes haemolymph, gills, digestive gland, sperm and embryo cells. The mentioned cells have been used for the evaluation of a broad spectrum of genotoxic agents both in vitro and in vivo. Moreover, the use of invertebrate models and their role from an ecotoxicological point of view will also be discussed as well as the comparison of the use of the comet assay in invertebrate and human models. Since the comet assay is still developing, its increasing potential in assessing DNA damage in animal models is crucial especially in the field of ecotoxicology and biomonitoring at the level of different species, not only humans.

2019

Impact of snow initialization in subseasonal-to-seasonal winter forecasts with the Norwegian Climate Prediction Model

Snow initialization has been previously investigated as a potential source of predictability atthe subseasonal‐to‐seasonal (S2S) timescale in winter and spring, through its local radiative,thermodynamical, and hydrological feedbacks. However, previous studies were conducted with low‐topmodels over short periods only. Furthermore, the potential role of the land surface‐stratosphere connectionupon the S2S predictability had remained unclear. To this end, we have carried out twin 30‐memberensembles of 2‐month (November and December) retrospective forecasts over the period 1985–2016, witheither realistic or degraded snow initialization. A high‐top version of the Norwegian Climate PredictionModel is used, based on the Whole Atmosphere Community Climate Model, to insure improved couplingwith the stratosphere. In a composite difference of high versus low initial Eurasian snow, the surfacetemperature is strongly impacted by the presence of snow, and wave activityfluxes into the stratosphere areenhanced at a 1‐month lag, leading to a weakened polar vortex. Focusing further on 7 years characterized bya strongly negative phase of the Arctic Oscillation, wefind a weak snow feedback contributing to themaintenance of the negative Arctic Oscillation. By comparing the twin forecasts, we extracted the predictiveskill increment due to realistic snow initialization. The prediction of snow itself is greatly improved, andthere is increased skill in surface temperature over snow‐covered land in thefirst 10 days, and localized skillincrements in the mid‐latitude transition regions on the southernflanks of the snow‐covered land areas, atlead times longer than 30 days.

2019

Årsrapport 2019

Solbakken, Christine Forsetlund (eds.)

NILU

2019

Monitoring of long-range transported air pollutants in Norway. Annual report 2018.

This report presents results from the monitoring of atmospheric composition and deposition of air pollution in 2018, and focuses on main components in air and precipitation, particulate and gaseous phase of inorganic constituents, particulate carbonaceous matter, ground level ozone and particulate matter. 2018 was a special year with elevated ozone levels during the whole summer season due to prolonged heat and drought.

NILU

2019

Contaminants in Atlantic walruses in Svalbard Part 1: Relationships between exposure, diet and pathogen prevalence

This study investigated relationships between organohalogen compound (OHC) exposure, feeding habits, and pathogen exposure in a recovering population of Atlantic walruses (Odobenus rosmarus rosmarus) from the Svalbard Archipelago, Norway. Various samples were collected from 39 free-living, apparently healthy, adult male walruses immobilised at three sampling locations during the summers of 2014 and 2015. Concentrations of lipophilic compounds (polychlorinated biphenyls, organochlorine pesticides and polybrominated diphenyl ethers) were analysed in blubber samples, and concentrations of perfluoroalkylated substances (PFASs) were determined in plasma samples. Stable isotopes of carbon and nitrogen were measured in seven tissue types and surveys for three infectious pathogens were conducted. Despite an overall decline in lipophilic compound concentrations since this population was last studied (2006), the contaminant pattern was similar, including extremely large inter-individual variation. Stable isotope ratios of carbon and nitrogen showed that the variation in OHC concentrations could not be explained by some walruses consuming higher trophic level diets, since all animals were found to feed at a similar trophic level. Antibodies against the bacteria Brucella spp. and the parasite Toxoplasma gondii were detected in 26% and 15% of the walruses, respectively. Given the absence of seal-predation, T. gondii exposure likely took place via the consumption of contaminated bivalves. The source of exposure to Brucella spp. in walruses is still unknown. Parapoxvirus DNA was detected in a single individual, representing the first documented evidence of parapoxvirus in wild walruses. Antibody prevalence was not related to contaminant exposure. Despite this, dynamic relationships between diet composition, contaminant bioaccumulation and pathogen exposure warrant continuing attention given the likelihood of climate change induced habitat and food web changes, and consequently OHC exposure, for Svalbard walruses in the coming decades.

2019

Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations

The Tibetan Plateau (TP) region, often referred to as the Third Pole, is the world's highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impact on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric reanalyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global reanalyses with satellite and in situ data. Yet, snow in reanalyses provides critical surface information for forecast systems from the medium to sub-seasonal timescales.

Here, snow depth and snow cover from four recent global reanalysis products, namely the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses, the Japanese 55-year Reanalysis (JRA-55) and the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-2), are inter-compared over the TP region. The reanalyses are evaluated against a set of 33 in situ station observations, as well as against the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in situ observations provides confidence in the station data despite the relative paucity of in situ measurement sites and the harsh operating conditions.

While several reanalyses show a systematic overestimation of the snow depth or snow cover, the reanalyses that assimilate local in situ observations or IMS snow cover are better capable of representing the shallow, transient snowpack over the TP region. The latter point is clearly demonstrated by examining the family of reanalyses from the ECMWF, of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. We further tested the sensitivity of the ERA5-Land model in offline experiments, assessing the impact of blown snow sublimation, snow cover to snow depth conversion and, more importantly, excessive snowfall. These results suggest that excessive snowfall might be the primary factor for the large overestimation of snow depth and cover in ERA5 reanalysis. Pending a solution for this common model precipitation bias over the Himalayas and the TP, future snow reanalyses that optimally combine the use of satellite snow cover and in situ snow depth observations in the assimilation and analysis cycles have the potential to improve medium-range to sub-seasonal forecasts for water resources applications.

2019

The Eulerian urban dispersion model EPISODE – Part 2: Extensions to the source dispersion and photochemistry for EPISODE–CityChem v1.2 and its application to the city of Hamburg

This paper describes the CityChem extension of the Eulerian urban dispersion model EPISODE. The development of the CityChem extension was driven by the need to apply the model in largely populated urban areas with highly complex pollution sources of particulate matter and various gaseous pollutants. The CityChem extension offers a more advanced treatment of the photochemistry in urban areas and entails specific developments within the sub-grid components for a more accurate representation of dispersion in proximity to urban emission sources. Photochemistry on the Eulerian grid is computed using a numerical chemistry solver. Photochemistry in the sub-grid components is solved with a compact reaction scheme, replacing the photo-stationary-state assumption. The simplified street canyon model (SSCM) is used in the line source sub-grid model to calculate pollutant dispersion in street canyons. The WMPP (WORM Meteorological Pre-Processor) is used in the point source sub-grid model to calculate the wind speed at plume height. The EPISODE–CityChem model integrates the CityChem extension in EPISODE, with the capability of simulating the photochemistry and dispersion of multiple reactive pollutants within urban areas. The main focus of the model is the simulation of the complex atmospheric chemistry involved in the photochemical production of ozone in urban areas. The ability of EPISODE–CityChem to reproduce the temporal variation of major regulated pollutants at air quality monitoring stations in Hamburg, Germany, was compared to that of the standard EPISODE model and the TAPM (The Air Pollution Model) air quality model using identical meteorological fields and emissions. EPISODE–CityChem performs better than EPISODE and TAPM for the prediction of hourly NO2 concentrations at the traffic stations, which is attributable to the street canyon model. Observed levels of annual mean ozone at the five urban background stations in Hamburg are captured by the model within ±15 %. A performance analysis with the FAIRMODE DELTA tool for air quality in Hamburg showed that EPISODE–CityChem fulfils the model performance objectives for NO2 (hourly), O3 (daily max. of the 8 h running mean) and PM10 (daily mean) set forth in the Air Quality Directive, qualifying the model for use in policy applications. Envisaged applications of the EPISODE–CityChem model are urban air quality studies, emission control scenarios in relation to traffic restrictions and the source attribution of sector-specific emissions to observed levels of air pollutants at urban monitoring stations.

2019

Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: A multi-cohort analysis

Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.

We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.

The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.

Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

2019

EURODELTA III exercise: An evaluation of air quality models' capacity to reproduce the carbonaceous aerosol

The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons.

2019

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