Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
Sammendrag
Rovebekken drenerer mye av Sandefjord lufthavn. Det ble påvist en lav konsentrasjoner av glykol i en ukeblandprøve fra Rovebekken i mars 2022 (0,21 mg PG/l). I de 36 andre ukeblandprøvene ble det ikke påvist glykol. Ved fiskeundersøkelsen i juli 2022 ble det registrert lav tetthet av årsyngel (2 fisk/100 m2) på den øvre stasjonen (R 3-4), rett nedstrøms flyplassen, men normal tetthet på stasjonene videre nedstrøms i bekken. Oppsummert har overvåkingen gjennom 2022 vist tilfredsstillende vannkvalitet i Rovebekken, med god oksygenstatus og kun en påvisning av glykol i lav konsentrasjon. Resultatene viste at kravene i utslippstillatelsen har blitt overholdt.
Forfattere
Trond MæhlumSammendrag
Renseanlegg behandler sigevannet fra Bølstad avfallsdeponi i en luftet lagune etterfulgt av sedimentering og filtrering før utslipp til Bølstadbekken. Miljøovervåkningsprogrammet er tilpasset gjeldende sigevannsveileder (TA-2077/2005) og Statsforvalterens krav til dokumentasjon og utslippskontroll (2006). Rapporten beskriver analysedata fra utslippskontroll og driftserfaringer fra 2022. Midlere vannføring i 2022 er beregnet til 65 mP 3 P/døgn i gjennomsnitt, totalt 23 626 mP 3 P som er lavere enn normalt på grunn av relativt lite nedbør og høy temperatur i 2022. Sigevannet fra Bølstad har generelt lave konsentrasjoner, typisk for mange norske deponier i etterdriftsfasen. Krav til årlig middel-konsentrasjon (mg/liter) tilfredsstilles for alle parametere. Årlig utslippsmengde (kg/år) for ammonium-N, tot-N, jern, fosfor og KOF tilfredsstilles. Renseeffekt (%) tilfredsstilles med god margin både for jern og ammonium-N. Nivåene for tungmetallkonsentrasjoner ligger lavt og generelt under terskelverdier. Innholdet av undersøkte organiske miljøgifter er lavt, men det er påvist PFAS forbindelser, også etter rensing. Det er ikke påvist giftighet i utslippsvannet. Overvåkningen av overvannet fra miljøstasjonen/ avsluttet deponi, som i dag ledes direkte til Bølstadbekken, er forurenset. Dette kan skyldes avrenning fra arealer med lagring av park/ hageavfall og rankekompostering med jordproduksjon. Miljøstasjonen som har åpne konteinere med sortert avfall kan også bidra med forurenset avrenning. Avbøtende tiltak bør vurderes. Grunnvannet fra en fjellbrønn i utkanten av deponiet, som benyttes på miljøstasjonen til vasking av utstyr, er påvirket av sigevann. NIBIO anbefaler at driftsoppfølging og miljøovervåkingsprogrammet videreføres i 2023.
Forfattere
Trond MæhlumSammendrag
Rapporten oppsummer resultater fra miljøovervåking av Spillhaug avfallsdeponi for driftsåret 2022. Data vurderes mot rensekrav og tidligere undersøkelser. Deponiet er etablert i et tidligere sandtak uten bunntetting. Vannet strømmer 2-300 m gjennom sand avgrenset av fjell før sigevannsforurenset grunnvann pumpes til et behandlingsanlegg. Renseparken omfatter brønner med pumpe, luftebasseng og tre tilplantede våtmarksbasseng. Grunnvannsmagasinet inngår som en del av rensesystemet for sigevann. Sigevannsmengde gjennom renseparken er i 2022 målt til 25 916 m3 som er på nivå med tidligere år i forhold til årsnedbøren (583 mm). Beregnet ut fra endring i vannkvalitet fra deponiet og til resipienten Sandbekken, har rensegraden vært: 99% for jern, 87% for KOF, 86% for nitrogen (tot-N) og 94% for ammonium nitrogen. Nivået av miljøgifter i utløpet av renseanlegget er lavt, og konsentrasjoner av tungmetaller er hovedsakelig under terskelverdier som anses å være skadelige. Sandbekken, som mottar renset vann og diffus innlekking via grunnvann og overvann påvirkes av sigevann med økte konsentrasjoner av konduktivitet og nitrogen, men kun liten endring for de andre analyserte parameterne. Årlig utslipp av PFAS forbindelser er ca 3 gram. Overvåkningen gir grunnlag for å fastslå at renseanlegget virker tilfredsstillende. Det er derfor ikke foreslått spesielle tiltak for å bedre rensingen i 2023. NIBIO foreslår at driftsoppfølging og overvåkning ligger på samme nivå som 2022, med kontroll av anleggets prosesser i ulike trinn for å dokumentere anleggets funksjon, utslipp og påvirkning av resipient.
Sammendrag
Active canopy sensors (ACSs) are great tools for diagnosing crop nitrogen (N) status and grain yield prediction to support precision N management strategies. Different commercial ACSs are available and their performances in crop N status diagnosis and recommendation may vary. The objective of this study was to determine the potential to minimize the differences of two commonly used ACSs (GreenSeeker and Crop Circle ACS-430) in maize (Zea mays L.) N status diagnosis and recommendation with multi-source data fusion and machine learning. The regression model was based on simple regression or machine learning regression including ancillary information of soil properties, weather conditions, and crop management information. Results of simple regression models indicated that Crop Circle ACS-430 with red-edge based vegetation indices performed better than GreenSeeker in estimating N nutrition index (NNI) (R2 = 0.63 vs. 0.50–0.51) and predicting grain yield (R2 = 0.56–0.57 vs. 0.49). The random forest regression (RFR) models using vegetation indices and ancillary data greatly improved the prediction of NNI (R2 = 0.81–0.82) and grain yield (R2 = 0.87–0.89), regardless of the sensor type or the vegetation index used. Using RFR models, moderate degree of accuracy in N status diagnosis was achieved based on either GreenSeeker or Crop Circle ACS-430. In comparison, using simple regression models based on spectral data only, the accuracy was significantly lower. When these two ACSs were used independently, they performed similarly in N fertilizer recommendation (R2 = 0.57–0.60). Hybrid RFR models were established using vegetation indices from both ACSs and ancillary data, which could be used to diagnose maize N status (moderate accuracy) and make side-dress N recommendations (R2 = 0.62–0.67) using any of the two ACSs. It is concluded that the use of multi-source data fusion with machine learning model could improve the accuracy of ACS-based N status diagnosis and recommendation and minimize the performance differences of different active sensors. The results of this research indicated the potential to develop machine learning models using multi-sensor and multi-source data fusion for more universal applications.
Forfattere
Silvano Fares Teodoro Georgiadis Arne Sæbø Ben Somers Koenraad Van Meerbeek Eva Beele Roberto Tognetti Giuseppe E. Scarascia-MugnozzaSammendrag
In this chapter, we analyse the current state of the art on how green infrastructures mitigate and adapt to climate changes and pollution, how they may improve urban air quality, increase green mobility, and can promote other important ecosystem benefits as water cycle regulation and supply. Relevant case studies will be also described, as gaps and future perspectives will be analyzed towards reaching the full potential of urban forests and other green spaces, for Biocities in Europe and beyond.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Marleen Pallandt Bernhard Ahrens Marion Schrumpf Holger Lange Sönke Zaehle Markus ReichsteinSammendrag
Soil organic carbon (SOC) is the largest terrestrial carbon pool, but it is still uncertain how it will respond to climate change. Especially the fate of SOC due to concurrent changes in soil temperature and moisture is uncertain. It is generally accepted that microbially driven SOC decomposition will increase with warming, provided that sufficient soil moisture, and hence enough C substrate, is available for microbial decomposition. We use a mechanistic, microbially explicit SOC decomposition model, the Jena Soil Model (JSM), and focus on the depolymerization of litter and microbial residues by microbes. These model processes are sensitive to temperature and soil moisture content and follow reverse Michaelis-Menten kinetics. Microbial decomposition rate V of the substrate [S] is limited by the microbial biomass [B]: V = Vmax * [S] * [B]/(kMB + [B]). The maximum reaction velocity, Vmax, is temperature sensitive and follows an Arrhenius function. Also, a positive correlation between temperature and kMB-values of different enzymes has been empirically shown, with Q10 values ranging from 0.71-2.80 (Allison et al., 2018). Q10 kMB-values for microbial depolymerization of microbial residues would be low compared to those of a (lignified) litter pool. An increase in kMB leads to a lower reaction velocity (V) and V becomes less temperature sensitive at low substrate concentrations. In this work we focus on the following questions: “how do temperature and soil moisture changes affect modelled heterotrophic respiration through the Michaelis-Menten term? Is there a temperature compensation effect on modelled decomposition rate because of the counteracting temperature sensitivities of Vmax and kMB?” We model these interactions under a mean warming experiment (+3.5 °K) as well as three soil moisture experiments: constant soil moisture, a drought, and a wetting scenario.
Sammendrag
Recent decades have seen increased temperatures and precipitation in the Nordic countries with long-term projections for reduced frost duration and depth. The consequence of these trends has been a gradual shift of delivery volumes to the frost-free season, requiring more agile management to exploit suitable weather conditions. Bearing capacity and trafficability are dependent on soil moisture state and in this context two satellite missions offer potenially useful information on soil moisture levels; NASA’s SMAP (Soil Moisture Active Passive) and ESA’s Sentinel-1. The goal of this pilot study was to quantify the performance of such satellite-based soil moisture variables for modeling forest road bearing capacity (e-module) during the frost-free season. The study was based on post-transport registrations of 103 forest road segments on the coastal and interior side of the Scandinavian mountain range. The analysis focused on roads of three types of surface deposits. Weekly SMAP soil moisture values better explained the variation in road e-module than soil water index (SWI) derived from Sentinel-1. Soil Water Index (SWI), however, reflected the weather conditions typical for operations on the respective surface deposit types. Regression analysis using (i) SMAP-based soil dryness index and (ii) its interaction with surface deposit types, together with (iii) the ratio between a combined SMAP_SWI dryness index and segment-specific depth to water (DTW) explained over 70% of the variation in road e-module. The results indicate a future potential to monitor road trafficability over large supply areas on a weekly level, given further refinement of study methods and variables for improved prediction.
Sammendrag
In cold climates, the use of de-icing chemicals in the winter can lead to groundwater contamination, especially when used in large quantities, such as at airports. Oslo Airport, Gardermoen, is situated on Norway’s largest rain-fed aquifer. Potassium formate is used to remove ice from runways and propylene glycol from airplanes; the organic parts are degradable. Most of the wells to monitor the spread of de-icing chemicals in the underlying aquifer have well screens near the groundwater level, while the runways and the source of de-icing chemicals are near the groundwater divides, where vertical flow is expected. The objective of this study is to demonstrate the importance of layers and time-varying recharge on the spreading of contaminant plumes in an aquifer near a groundwater divide. This is done with numerical modelling. The model results show increased vertical transport of the added tracer in the presence of horizontal layers, both continuous and discontinuous, in the aquifer. With certain distributions of hydraulic conductivity, Ks, we demonstrate that deeper monitoring wells are required. With the scenarios modelled here, time-varying recharge has a weaker effect on plume distribution. Measured concentrations of potassium and total organic carbon show the cyclic effect of seasonally varying recharge of contaminants, and an asymptotic accumulation of concentration over time, that is consistent with the model runs. In conclusion, groundwater monitoring systems near a groundwater divide should include multi-level samplers to ensure control of the vertical plume movement.
Sammendrag
With a view to integration into the European Union, the efficiency and competitiveness of the Kosovo’ different sectors (including agriculture) must be improved. This paper assesses the technical efficiency (TE) of horticultural farms through Data Envelopment Analysis (DEA) applying output orientation. It was founded that the TE of these farms is positively affected by their size, with large-size farms presenting overall higher technical efficiency. The research findings indicate that the degree of agricultural education does not have a significant impact on TE, whereas public assistance through subsidies and grants has a substantial and negative impact on TE, as confirmed by statistical analysis.