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The role of SVOCs in the initial film formation and soiling of unvarnished paintings

Grøntoft, Terje; Cutajar, Jan Dariusz

In recent years increased research efforts and environmental improvements have been directed towards the preventive conservation of the monumental, unvarnished oil paintings on canvas (1909–1916) by Edvard Munch (1863–1944) housed in the University of Oslo Aula. Surface soiling of the paintings has been a documented issue since their display, and the modern-day effect of air-borne particulates and gases on the painting surfaces remains hitherto undocumented. For the first time in the Aula, this study has measured the in-situ time-dependent mass deposit of air pollution onto vertical surfaces over the period of one year (2021–2022). Concomitant measurements of the concentrations of ozone (O3) and nitrogen dioxide (NO2) were also taken, to complement periodic data from 2020. The mass deposit was measured through incremental weight changes of Teflon membrane filters, and quartz filters for analysis of elemental/organic carbon (EC/OC), whilst the gaseous pollutants were measured using passive gas samplers. Indoor-to-outdoor ratios (I/O) for O3 were noted to be higher than those suggested by earlier data, whereas NO2 I/O ratios were found to be lower, indicating a stronger oxidising atmosphere in the Aula. Just over half of the deposited mass on the quartz filters was found to be OC, with no EC detected. Surprisingly, an overall decrease in the mass deposit from three to twelve months was measured on the Teflon membrane filters. It was hypothesised, based on models reported in the literature, that the source of the OC on the filters was mainly gaseous, semi-volatile organic compounds (SVOCs), which were present in an adsorption/desorption equilibrium that was dependent on possible SVOC emission episodes, relative humidity levels, gaseous oxidative reactions and the particulate matter deposit. A simple mathematical model is proposed to rationalise the observed mass deposits on the filters, together with a discussion of uncertainties affecting the measurements. The hypothesis preliminarily indicates the possible and previously unconsidered role of SVOCs on the initial film formation of soiling layers on the Aula paintings, and could bear implications for their monitoring in the preventive care of unvarnished oil paintings on canvas.

2023

Ozone measurements 2021

Hjellbrekke, Anne-Gunn; Solberg, Sverre

NILU

2023

VOC measurements 2021

Solberg, Sverre; Claude, Anja; Reimann, Stefan; Walker, Sam-Erik

NILU

2023

Comparative Analysis of Deep Learning and Statistical Models for Air Pollutants Prediction in Urban Areas

Naz, Fareena; McCann, Conor; Fadim, Muhammad; Cao, Tuan-Vu; Hunter, Ruth; Nguyen, Trung Viet; Nguyen, Long D.; Duong, Trung Q.

Rapid growth in urbanization and industrialization leads to an increase in air pollution and poor air quality. Because of its adverse effects on the natural environment and human health, it’s been declared a “silent public health emergency”. To deal with this global challenge, accurate prediction of air pollution is important for stakeholders to take required actions. In recent years, deep learning-based forecasting models show promise for more effective and efficient forecasting of air quality than other approaches. In this study, we made a comparative analysis of various deep learning-based single-step forecasting models such as long short term memory (LSTM), gated recurrent unit (GRU), and a statistical model to predict five air pollutants namely Nitrogen Dioxide (NO 2 ), Ozone (O 3 ), Sulphur Dioxide (SO 2 ), and Particulate Matter (PM2.5, and PM10). For empirical evaluation, we used a publicly available dataset collected in Northern Ireland, using an air quality monitoring station situated in Belfast city centre. It measures the concentration of air pollutants. The performance of forecasting models is evaluated based on three performance metrics: (a) root mean square error (RMSE), (b) mean absolute error (MAE) and (c) R-squared ( R2 ). The result shows that deep learning models consistently achieved the least RMSE compared to the statistical models with a value of 0.59. In addition, the deep learning model is also found to have the highest R2 score of 0.856.

2023

Equilibrium Climate after Spectral and Bolometric Irradiance Reduction in Grand Solar Minimum Simulations

Tartaglione, Nazario; Toniazzo, Thomas; Otterå, Odd Helge; Orsolini, Yvan Joseph Georges Emile G.

In this study, we use the Whole Atmosphere Community Climate Model, forced by present-day atmospheric composition and coupled to a Slab Ocean Model, to simulate the state of the climate under grand solar minimum forcing scenarios. Idealized experiments prescribe time-invariant solar irradiance reductions that are either uniform (percentage-wise) across the total solar radiation spectrum (TOTC) or spectrally localized in the ultraviolet (UV) band (SCUV). We compare the equilibrium condition of these experiments with the equilibrium condition of a control simulation, forced by perpetual solar maximum conditions. In SCUV, we observe large stratospheric cooling due to ozone reduction. In both the Northern Hemisphere (NH) and the Southern Hemisphere (SH), this is accompanied by a weakening of the polar night jet during the cold season. In TOTC, dynamically induced polar stratospheric cooling is observed in the transition seasons over the NH, without any ozone deficit. The global temperature cooling values, compared with the control climate, are 0.55±0.03 K in TOTC and 0.39±0.03 K in SCUV. The reductions in total meridional heat transport outside of the subtropics are similar in the two experiments, especially in the SH. Despite substantial differences in stratospheric forcing, similarities exist between the two experiments, such as cloudiness; meridional heating transport in the SH; and strong cooling in the NH during wintertime, although this cooling affects two different regions, namely, North America in TOTC and the Euro–Asian continent in SCUV.

2023

Microplastic to be measured at EMEP sites in the frame of MAGIC project

Evangeliou, Nikolaos; Yttri, Karl Espen; Herzke, Dorte; Cassiani, Massimo; Eckhardt, Sabine; Kylling, Arve; Wisthaler, Armin; Stohl, Andreas; Tichy, Ondrej; Revell, Laura E.

2023

ACTRIS Data Centre: Recent implementation and future developments

Myhre, Cathrine Lund; Fiebig, Markus; Rud, Richard Olav; Mona, Lucia; Dema, Claudio; Pascal, Nicolas; Henry, Patrice; Picquet-Varrault, Bénédicte; Brissebrat, Guillaume; Boonne, Cathy; O’Connor, Ewan; Tukiainen, Simo

2023

Renere luft i Longyearbyen

Grythe, Henrik (intervjuobjekt); Krüger, Louise (journalist)

2023

Low-Cost Particulate Matter Sensors for Monitoring Residential Wood Burning

Hassani, Amirhossein; Schneider, Philipp; Vogt, Matthias; Castell, Nuria

Conventional monitoring systems for air quality, such as reference stations, provide reliable pollution data in urban settings but only at relatively low spatial density. This study explores the potential of low-cost sensor systems (LCSs) deployed at homes of residents to enhance the monitoring of urban air pollution caused by residential wood burning. We established a network of 28 Airly (Airly-GSM-1, SP. Z o.o., Poland) LCSs in Kristiansand, Norway, over two winters (2021–2022). To assess performance, a gravimetric Kleinfiltergerät measured the fine particle mass concentration (PM2.5) in the garden of one participant’s house for 4 weeks. Results showed a sensor-to-reference correlation equal to 0.86 for raw PM2.5 measurements at daily resolution (bias/RMSE: 9.45/11.65 μg m–3). High-resolution air quality maps at a 100 m resolution were produced by combining the output of an air quality model (uEMEP) using data assimilation techniques with the network data that were corrected and calibrated by using a proposed five-step network data processing scheme. Leave-one-out cross-validation demonstrated that data assimilation reduced the model’s RMSE, MAE, and bias by 44–56, 38–48, and 41–52%, respectively.

2023

Retrieval of Aerosol Optical Properties via an All-Sky Imager and Machine Learning: Uncertainty in Direct Normal Irradiance Estimations

Logothetis, Stavros-Andreas; Giannaklis, Christos-Panagiotis; Salamalikis, Vasileios; Tzoumanikas, Panagiotis; Raptis, Panagiotis-Ioannis; Amiridis, Vassilis; Eleftheratos, Kostas; Kazantzidis, Andreas

Quality-assured aerosol optical properties (AOP) with high spatiotemporal resolution are vital for the accurate estimation of direct aerosol radiative forcing and solar irradiance under clear skies. In this study, the sky information from an all-sky imager (ASI) is used with machine learning (ML) synergy to estimate aerosol optical depth (AOD) and the Ångström Exponent (AE). The retrieved AODs (AE) revealed good accuracy, with a dispersion error lower than 0.07 (0.15). The retrieved ML AOPs are used to estimate the DNI by applying radiative transfer modeling. The estimated ML DNI calculations revealed adequate accuracy to reproduce reference measurements with relatively low uncertainties.

2023

Gigant-skogbranner kan ses fra verdensrommet – røykpartikler har nådd Norge

Evangeliou, Nikolaos (intervjuobjekt); Berger, Nina Dayana (journalist)

2023

Svovelskya kom – slik gjekk det

Tørseth, Kjetil (intervjuobjekt); Baas, Jarand Aga (journalist)

2023

Summarizing the research of the MADEIRA project - Middle atmosphere dynamics: exploiting infrasound using a multidisciplinary approach at high latitudes

Näsholm, Sven Peter; Amezcua, Javier; Assink, Jelle D.; Belova, Evgenia; Blixt, Mårten; Brissaud, Quentin; Eggen, Mari Dahl; Espy, Patrick Joseph; Hibbins, Robert Edward; Kero, Johan; Kværna, Tormod; Pichon, Alexis Le; Orsolini, Yvan Joseph Georges Emile G.; Rodriguez, Ismael Vera; Turquet, Antoine Leo; Vorobeva, Ekaterina

2023

Røykpartikler fra Canada har nådd Sørlandet

Tørseth, Kjetil; Evangeliou, Nikolaos (intervjuobjekter); Skår, Kari Løberg; Bjøranger, Ada Drevdal (journalister)

2023

Skogens helsetilstand i Norge. Resultater fra skogskadeovervåkingen i 2022

Timmermann, Volkmar; Børja, Isabella; Clarke, Nicholas; Gohli, Jostein; Hietala, Ari Mikko; Jepsen, Jane Uhd; Krokene, Paal; Lislegård, Harald Haga; Nagy, Nina Elisabeth; Nyeggen, Hans; Solberg, Sverre; Solheim, Halvor; Solvin, Thomas Mørtvedt; Svensson, Arvid; Tollefsrud, Mari Mette; Vindstad, Ole Petter Laksforsmo; Økland, Bjørn; Aas, Wenche

Skogens helsetilstand påvirkes i stor grad av klima og værforhold, enten direkte ved tørke, frost og vind, eller indirekte ved at klimaet påvirker omfanget av soppsykdommer og insektangrep. Klimaendringene og den forventede økningen i klimarelaterte skogskader gir store utfordringer for forvaltningen av framtidas skogressurser. Det samme gjør invaderende skadegjørere, både allerede etablerte arter og nye som kan komme til Norge i nær framtid. I denne rapporten presenteres resultater fra skogskadeovervåkingen i Norge i 2022 og trender over tid for følgende temaer:
(i) Landsrepresentativ skogovervåking;
(ii) Intensiv skogovervåking;
(iii) Overvåking av bjørkemålere i Troms og Finnmark;
(iv) Barkbilleovervåkingen;
(v) Furuvednematode;
(vi) Askeskuddsyke;
(vii) Andre spesielle skogskader i 2022.

NIBIO

2023

Deposition of sulfur and nitrogen in Norway 2017-2021

Blake, Lewis R.; Aas, Wenche; Denby, Bruce; Hjellbrekke, Anne-Gunn; Mu, Qing; Simpson, David; Ytre-Eide, Martin; Fagerli, Hilde

Norwegian Meteorological Institute

2023

Measuring DNA modifications with the comet assay: a compendium of protocols

Collins, Andrew; Møller, Peter; Gajski, Goran; Vodenková, Soňa; Abdulwahed, Abdulhadi; Anderson, Diana; Bankoglu, Ezgi Eyluel; Bonassi, Stefano; Boutet-Robinet, Elisa; Brunborg, Gunnar; Chao, Christy; Cooke, Marcus S.; Costa, Carla; Costa, Solange; Dhawan, Alok; Lapuente, Joaquin de; Bo, Cristian Del; Dubus, Julien; Dusinska, Maria; Duthie, Susan J.; Yamani, Naouale El; Engelward, Bevin; Gaivão, Isabel; Giovannelli, Lisa; Godschalk, Roger; Guilherme, Sofia; Gutzkow, Kristine Bjerve; Habas, Khaled; Hernández, Alba; Herrero, Oscar; Isidori, Marina; Jha, Awadhesh N.; Knasmüller, Siegfried; Kooter, Ingeborg M.; Koppen, Gudrun; Kruszewski, Marcin; Ladeira, Carina; Laffon, Blanca; Larramendy, Marcelo; Hégarat, Ludovic Le; Lewies, Angelique; Lewinska, Anna; Liwszyc, Guillermo E.; Cerain, Adela López de; Manjanatha, Mugimane; Marcos, Ricard; Milic, Mirta; Andrade, Vanessa Moraes de; Moretti, Massimo; Muruzabal, Damian; Novak, Matjaž; Oliveira, Rui; Olsen, Ann-Karin Hardie; Owiti, Norah; Pacheco, Mário; Pandey, Alok K.; Pfuhler, Stefan; Pourrut, Bertrand; Reisinger, Kerstin; Rojas, Emilio; Rundén-Pran, Elise; Sanz-Serrano, Julen; Shaposhnikov, Sergey; Sipinen, Ville Erling; Smeets, Karen; Stopper, Helga; Teixeira, João Paulo; Valdiglesias, Vanessa; Valverde, Mahara; Acker, Frederique van; Schooten, Frederik-Jan van; Vasquez, Marie; Wentzel, Johannes F.; Wnuk, Maciej; Wouters, Annelies; Žegura, Bojana; Zikmund, Tomas; Langie, Sabine A. S.; Azqueta, Amaya

2023

Støv – hva er det og hvordan måler vi det?

Weydahl, Torleif; Hak, Claudia

2023

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