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Modelling of the deterioration and conservation costs of polychrome painted wood in two Norwegian medieval stone churches

Grøntoft, Terje

EnvCul (https://envcul.nilu.no/) modelling was performed of condition changes of painted wooden panels and related conservation cost in indoor climate and object response scenarios in two Norwegian Medieval stone churches: Kinn (mean relative humidity = 79%) on the humid west coast, and Ringsaker (mean RH = 49%) in the drier eastern part of the country. It was found that, hypothetical, building measures in Kinn, and conservation heating measures in Ringsaker, to approach an indoor RH of about 65% in the two churches, could probably increase conservation intervals with 20–100%, and correspondingly reduce conservation costs between 10% and 50%. This is in reasonable agreement with an available report of observed conservation requirements in differently heated Norwegian churches. A situation between a linear and accelerating development of the deterioration of the painted wood on approaching a new conservation intervention gave the best correspondence to the observed values. The large modelling uncertainty was mainly due to lacking observations of the deterioration development, but also lacking understanding of the complex mechanisms and phases of the environmental dose-deterioration response of painting conservation treatments.

Elsevier

2023

Modelling of the particle number concentrations in five European cities.

Kukkonen, J.; Karl, M.; Keuken, M.P.; Denier van der Gon, H.A.C.; Denby, B.R.; Singh, V.; Douros, J.; Manders, A.; Samaras, Z.; Moussiopoulos, N.; Jonkers, S.; Aarnio, M.; Karppinen, A.; Kangas, L.; Lützenkirchen, S.; Petäjä, T.; Vouitsis, I.; Sokhi, R.S.

2016

Modelling organic contaminants in northern ecosystems across time, space and species using the integrated NEM model

Sunde Krogseth, Ingjerd; Breivik, Knut; Frantzen, Sylvia; Nilsen, Bente Merete; Eckhardt, Sabine; Nøst, Therese Haugdahl; Wania, Frank

2022

Modelling PCB-153 in northern ecosystems across time, space, and species using the nested exposure model

Krogseth, Ingjerd Sunde; Breivik, Knut; Frantzen, Sylvia; Nilsen, Bente Merete; Eckhardt, Sabine; Nøst, Therese Haugdahl; Wania, Frank

There is concern over possible effects on ecosystems and humans from exposure to persistent organic pollutants (POPs) and chemicals with similar properties. The main objective of this study was to develop, evaluate, and apply the Nested Exposure Model (NEM) designed to simulate the link between global emissions and resulting ecosystem exposure while accounting for variation in time and space. NEM, using environmental and biological data, global emissions, and physicochemical properties as input, was used to estimate PCB-153 concentrations in seawater and biota of the Norwegian marine environment from 1930 to 2020. These concentrations were compared to measured concentrations in (i) seawater, (ii) an Arctic marine food web comprising zooplankton, fish and marine mammals, and (iii) Atlantic herring (Clupea harengus) and Atlantic cod (Gadus morhua) from large baseline studies and monitoring programs. NEM reproduced PCB-153 concentrations in seawater, the Arctic food web, and Norwegian fish within a factor of 0.1–31, 0.14–3.1, and 0.09–21, respectively. The model also successfully reproduced measured trophic magnification factors for PCB-153 at Svalbard as well as geographical variations in PCB-153 burden in Atlantic cod between the Skagerrak, North Sea, Norwegian Sea, and Barents Sea, but estimated a steeper decline in PCB-153 concentration in herring and cod during the last decades than observed. Using the evaluated model with various emission scenarios showed the important contribution of European and global primary emissions for the PCB-153 load in fish from Norwegian marine offshore areas.

Royal Society of Chemistry (RSC)

2023

Modelling personal exposure to particulate matter in the Haifa Bay area. NILU PP

Fløisand, I.; Broday, D.; Mc Innes, H.; Laupsa, H.; Holländer, W.; Flickstein, B.

2006

Modelling photochemical oxidant formation, transport, deposition and exposure of terrestrial ecosystems.

Fowler, D.; Cape, J.N.; Coyle, M.; Smith, R.I.; Hjellbrekke, A.-G.; Simpson, D.; Derwent, R.G.; Johnson, C.E.

1999

Modelling PM2.5 chemical composition with CAMx in Southwest Spain. NILU PP

Milford, C.; Castell.; N.; Marrero, C.; Sánchez de la Campa, A.; Fernández-Camacho, R.; Rodríguez, S.; de la Rosa, J.D.; Stein, A.F.

2012

Modelling PNC from kerbside to urban scale. NILU F

Karl, M.; Denby, B.R.; Lützenkirchen, S.; Henzing, B.; Keuken, M.

2012

Modelling PNC from kerbside to urban scale.

Karl, M.; Denby, B.R.; Lützenkirchen, S.; Henzing, B.; Keuken, M.

2012

Modelling road dust emission abatement measures using the NORTRIP model: vehicle speed and studded tyre reduction.

Norman, M.; Sundvor, I.; Denby, B.R.; Johansson, C.; Gustafsson, M.; Blomqvist, G.; Janhäll, S.

2016

Modelling road dust emission abatement measures using the NORTRIP model: Vehicle speed and studded tyre reduction.

Norman, M.; Sundvor, I.; Denby, B.R.; Johansson, C.; Gustafsson, M.; Blomqvist, G.; Janhäll, S.

2016

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Nickel, Stefan; Schröder, Winfried; Schmalfuss, Roman; Saathoff, Maike; Harmens, Harry; Mills, Gina; Frontasyeva, Marina V.; Barandovski, Lambe; Blum, Oleg; Carballeira, Alejo; De Temmerman, Ludwig; Dunaev, Anatoly M; Ene, Antoaneta; Fagerli, Hilde; Godzik, Barbara; Ilyin, Ilia; Jonkers, Sander; Jeran, Zvonka; Lazo, Pranvera; Leblond, Sebastien; Liiv, Siiri; Mankovska, Blanka; Nunez-Olivera, Encarnacion; Piispanen, Juha; Poikolainen, Jarmo; Popescu, Ion V.; Qarri, Flora; Santamaria, Jesus Miguel; Schaap, Martijn; Skudnik, Mitja; Spiric, Zdravko; Stafilov, Trajce; Steinnes, Eiliv; Stihi, Claudia; Suchara, Ivan; Uggerud, Hilde Thelle; Zechmeister, Harald G

Springer

2018

Modelling surface ozone during the 2003 heat-wave in the UK.

Vieno, M.; Dore, A.J.; Stevenson, D.S.; Doherty, R.; Heal, M. R.; Reis, S.; Hallsworth, S.; Tarrasón, L.; Wind, P.; Fowler, D.; Simpson, D.,, Sutton, M.A.

2010

Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations

Tang, Hui; Haugvaldstad, Ove Westermoen; Stordal, Frode; Bi, Jianrong; Zwaaftink, Christine Groot; Grythe, Henrik; Wang, Bin; Rao, Zhimin; Zhang, Zhongshi; Berntsen, Terje Koren; Kaakinen, Anu

The 2021 East Asia sandstorm began from the Eastern Gobi desert steppe in Mongolia on March 14, and later spread to northern China and the Korean Peninsula. It was the biggest sandstorm to hit China in a decade, causing severe air pollution and a significant threat to human health. Capturing and predicting such extreme events is critical for society. The Lagrangian particle dispersion model FLEXPART and the associated dust emission model FLEXDUST have been recently developed and applied to simulate global dust cycles. However, how well the model captures Asian dust storm events remains to be explored. In this study, we applied FLEXPART to simulate the recent 2021 East Asia sandstorm, and evaluated its performance comparing with observation and observation-constrained reanalysis datasets, such as the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and CAMS global atmospheric composition forecasts (CAMS-F). We found that the default setting of FLEXDUST substantially underestimates the strength of dust emission and FLEXPART modelled dust concentration in this storm compared to that in MERRA-2 and CAMS-F. An improvement of the parametrization of bare soil fraction, topographical scaling, threshold friction velocity and vertical dust flux scheme based on Kok et al. (Atmospheric Chemistry and Physics, 2014, 14, 13023–13041) in FLEXDUST can reproduce the strength and spatio-temporal pattern of the dust storm comparable to MERRA-2 and CAMS-F. However, it still underestimates the observed spike of dust concentration during the dust storm event over northern China, and requires further improvement in the future. The improved FLEXDUST and FLEXPART perform better than MERRA-2 and CAMS-F in capturing the observed particle size distribution of dust aerosols, highlighting the importance of using more dust size bins and size-dependent parameterization for dust emission, and dry and wet deposition schemes for modelling the Asian dust cycle and its climatic feedbacks.

Frontiers Media S.A.

2023

Modelling the BC deposition in Arctic ice-cores by source–receptor matrix calculation for deposited mass with FLEXPART

Eckhardt, Sabine; Cassiani, Massimo; Evangeliou, Nikolaos; Sollum, Espen; McConnell, Joseph; Stohl, Andreas

2018

Modelling the behavior of cyclic volatile methyl siloxanes (cVMS) in an Arctic benthopelagic freshwater food-web.

Krogseth, I.S.; Undeman, E.; Evenset, A.; Christensen, G.N.; Whelan, M.J.; Breivik, K.; Warner, N.A.

2016

Modelling the coupled mercury-halogen-ozone cycle in the central Arctic during spring

Ahmed, Shaddy; Thomas, Jennie L.; Angot, Hélène; Dommergue, Aurélien; Archer, Stephen D.; Bariteau, Ludovic; Beck, Ivo; Benavent, Nuria; Blechschmidt, Anne-Marlene; Blomquist, Byron; Boyer, Matthew; Christensen, Jesper H.; Dahlke, Sandro; Dastoor, Ashu; Helmig, Detlev; Howard, Dean; Jacobi, Hans-Werner; Jokinen, Tuija; Lapere, Rémy; Laurila, Tiia; Quéléver, Lauriane L.J.; Richter, Andreas; Ryjkov, Andrei; Mahajan, Anoop S.; Marelle, Louis; Pfaffhuber, Katrine Aspmo; Posman, Kevin; Rinke, Annette; Saiz-Lopez, Alfonso; Schmale, Julia; Skov, Henrik; Steffen, Alexandra; Stupple, Geoff; Stutz, Jochen; Travnikov, Oleg; Zilker, Bianca

Near-surface mercury and ozone depletion events occur in the lowest part of the atmosphere during Arctic spring. Mercury depletion is the first step in a process that transforms long-lived elemental mercury to more reactive forms within the Arctic that are deposited to the cryosphere, ocean, and other surfaces, which can ultimately get integrated into the Arctic food web. Depletion of both mercury and ozone occur due to the presence of reactive halogen radicals that are released from snow, ice, and aerosols. In this work, we added a detailed description of the Arctic atmospheric mercury cycle to our recently published version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem 4.3.3) that includes Arctic bromine and chlorine chemistry and activation/recycling on snow and aerosols. The major advantage of our modelling approach is the online calculation of bromine concentrations and emission/recycling that is required to simulate the hourly and daily variability of Arctic mercury depletion. We used this model to study coupling between reactive cycling of mercury, ozone, and bromine during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) spring season in 2020 and evaluated results compared to land-based, ship-based, and remote sensing observations. The model predicts that elemental mercury oxidation is driven largely by bromine chemistry and that particulate mercury is the major form of oxidized mercury. The model predicts that the majority (74%) of oxidized mercury deposited to land-based snow is re-emitted to the atmosphere as gaseous elemental mercury, while a minor fraction (4%) of oxidized mercury that is deposited to sea ice is re-emitted during spring. Our work demonstrates that hourly differences in bromine/ozone chemistry in the atmosphere must be considered to capture the springtime Arctic mercury cycle, including its integration into the cryosphere and ocean.

2023

Modelling the descent of nitric oxide during the elevated stratopause event of january 2013.

Orsolini, Y. J.; Limpasuvan, V.; Pérot, K.; Espy, P.; Hibbins, R.; Lossow, S.; Raaholt Larsson, K.; Murtagh, D.

2017

Modelling the dispersion of particle numbers in five European cities.

Kukkonen, J.; Karl, M.; Keuken, M.P.; Denier van der Gon, H.A.C.; Denby, B.R.; Singh, V.; Douros, J.; Manders, A.; Samaras, Z.; Moussiopoulos, N.; Jonkers, S.; Aarnio, M.; Karppinen, A.; Kangas, L.; Lützenkirchen, S.; Petäjä, T.; Vouitsis, I.; Sokhi, R.S.

2016

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