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2020
Costs and benefits of implementing an Environmental Speed Limit in a Nordic city
We present a comprehensive study on the impacts and associated changes in costs resulting from the implementation of Environmental Speed Limits (ESLs), as a measure to reduce PM10 and associated health effects. We present detailed modelled emissions (i.e., CO2, NOx, PM2.5 and PM10), concentration levels (i.e., PM2.5 and PM10) and population exposure to PM2.5 and PM10 under three scenarios of ESL implementation for the Metropolitan Area of Oslo. We find that whilst emissions of NOx and CO2 do not seem to show significant changes with ESL implementation, PM10 emissions are reduced by 6–12% and annual concentration levels are reduced up to 8%, with a subsequent reduction in population exposure. The modelled data is used to carry out a detailed analysis to quantify the changes in private and social costs for the roads in Oslo where ESL are implemented today. This involves assessments related to human health, climate, fuel consumption, time losses and the incidence of traffic accidents. For a scenario using actual speed data from ESL implementation, our study shows a net benefit associated with the implementation of ESLs, whilst for a theoretical scenario with strict speed limit compliance we find a net increase in costs. This is largely due to variation in costs due to time losses between the scenarios, although uncertainties are high.
2020
2020
Microfibers (MFs) are frequently reported as the most dominant type of microplastic (MP) found in the marine water column and sediments. A major source of MFs is the use and washing of textiles. Although WWTPs can remove up to 98% of MP, estimates suggest billions of MP are still released from a single WWTP annually. Intrinsic properties (polymer type, density, size) will influence environmental degradation, settling times, and ingestion of MFs by marine organisms. Less well understood is the influence of environmental degradation on the fate of MFs. In the current study, we compare the effect of UV exposure on the degradation and fragmentation of polyester (PET), polyamide (nylon; PA), polyacrylonitrile (acrylic; PAN) and wool fibers. Degradation of MFs was conducted in seawater under environmentally relevant exposure conditions using simulated sunlight. PA, PET and wool MFs exhibited changes in surface morphology after just 2 weeks from the start of exposure, followed by fragmentation after
2020
På oppdrag fra Elkem Carbon AS, har NILU utført målinger av arsen (As) i omgivelsene til Elkem Carbon i Vågsbygd
(Kristiansand kommune). Bedriften ble pålagt av Miljødirektoratet å gjennomføre As-målinger i omgivelsesluft. PM10-prøver tatt med filterprøvetaker i boligområdet på Fiskåtangen (Konsul Wilds vei) ble analysert med hensyn på As med induktivt koblet plasma massespektrometri (ICP-MS). Rapporten dekker målinger i perioden 25. september 2019 – 28. september 2020. Årsmiddelverdien av konsentrasjonen av As ble målt til 2,38 ng/m3. Målsettingsverdien for tiltak i forurensningsforskriften på 6 ng/m3 ble overholdt med god margin. Årsmiddelverdien var marginalt lavere enn nedre vurderingsterskel på 2,4 ng/m3. Et langtransportert bidrag til de to høyeste registrerte As døgnkonsentrasjonene kan ikke utelukkes.
NILU
2020
The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO−3
leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling.
Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO−3
were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep < 1 g N m−2 yr−1 versus 65 % (range 35 %–85 %) for Ndep > 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.
2020
It is unclear whether the Eurasian snow plays a role in the tropospheric driving of sudden stratospheric warming (SSW). The major SSW event of February 2018 is analyzed using reanalysis datasets. Characterized by predominant planetary waves of zonal wave 2, the SSW developed into a vortex split via wave–mean flow interaction. In the following two weeks, the downward migration of zonal-mean zonal wind anomalies was accompanied by a significant transition to the negative phase of the North Atlantic Oscillation, leading to extensive cold extremes across Europe. Here, we demonstrate that anomalous Siberian snow accumulation could have played an important role in the 2018 SSW occurrence. In the 2017/18 winter, snow depths over Siberia were much higher than normal. A lead–lag correlation analysis shows that the positive fluctuating snow depth anomalies, leading to intensified “cold domes” over eastern Siberia (i.e., in a region where the climatological upward planetary waves maximize), precede enhanced wave-2 pulses of meridional heat fluxes (100 hPa) by 7–8 days. The snow–SSW linkage over 2003–19 is further investigated, and some common traits among three split events are found. These include a time lag of about one week between the maximum anomalies of snow depth and wave-2 pulses (100 hPa), high sea level pressure favored by anomalous snowpack, and a ridge anchoring over Siberia as precursor of the splits. The role of tropospheric ridges over Alaska and the Urals in the wave-2 enhancement and the role of Arctic sea ice loss in Siberian snow accumulation are also discussed.
2020
Estimation of the temporal profile of an atmospheric release, also called the source term, is an important problem in environmental sciences. The problem can be formalized as a linear inverse problem wherein the unknown source term is optimized to minimize the difference between the measurements and the corresponding model predictions. The problem is typically ill-posed due to low sensor coverage of a release and due to uncertainties, e.g., in measurements or atmospheric transport modeling; hence, all state-of-the-art methods are based on some form of regularization of the problem using additional information. We consider two kinds of additional information: the prior source term, also known as the first guess, and regularization parameters for the shape of the source term. While the first guess is based on information independent of the measurements, such as the physics of the potential release or previous estimations, the regularization parameters are often selected by the designers of the optimization procedure. In this paper, we provide a sensitivity study of two inverse methodologies on the choice of the prior source term and regularization parameters of the methods. The sensitivity is studied in two cases: data from the European Tracer Experiment (ETEX) using FLEXPART v8.1 and the caesium-134 and caesium-137 dataset from the Chernobyl accident using FLEXPART v10.3.
2020
2020