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Source apportionment of black carbon in Oslo (Norway) and Vinca (Serbia)

Platt, Stephen Matthew; Yttri, Karl Espen; Hak, Claudia; Jovasevic-Stojanovic, Milena

2023

Global fields of the methane isotopic ratio constrained with observations

Zwaaftink, Christine Groot; Thompson, Rona Louise; Tsuruta, Aki; Röckmann, Thomas; Levin, Ingeborg; Platt, Stephen Matthew

2023

European air quality maps for 2020. PM10, PM2.5, Ozone, NO2, NOx and Benzo(a)pyrene spatial estimates and their uncertainties.

Horálek, Jan; Vlasakova, Leona; Schreiberova, Marketa; Markova, Jana; Schneider, Philipp; Kurfürst, Pavel; Tognet, Frédéric; Schovánková, Jana; Vlcek, Ondrej; Damaskova, Dasa

The report provides the annual update of the European air quality concentration maps and population exposure estimates for human health related indicators of pollutants PM10 (annual average, 90.4 percentile of daily means), PM2.5 (annual average), ozone (93.2 percentile of maximum daily 8-hour means, SOMO35, SOMO10), NO2 (annual average) and benzo(a)pyrene (annual average), and vegetation related ozone indicators (AOT40 for vegetation and for forests) for the year 2020. The report contains also Phytotoxic ozone dose (POD) for wheat, potato and tomato maps and NOx annual average map for 2020. The benzo(a)pyrene map is presented for the first time in this regular mapping report. The trends in exposure estimates in the period 2005–2020 are summarized. The analysis for 2020 is based on the interpolation of the annual statistics of the 2020 observational data reported by the EEA member and cooperating countries and other voluntary reporting countries and stored in the Air Quality e-reporting database, complemented, when needed, with measurements from additional sources. The mapping method is the Regression – Interpolation – Merging Mapping (RIMM). It combines monitoring data, chemical transport model results and other supplementary data using linear regression model followed by kriging of its residuals (residual kriging). The paper presents the mapping results and gives an uncertainty analysis of the interpolated maps. It also presents concentration change in 2020 in comparison to the five-year average 2015-2019 using the difference maps.

ETC/HE

2023

Initial comparison of recent years satellite and CAMS aerosol data over Svalbard

Stebel, Kerstin; Hansen, Georg H.; Kylling, Arve; Schneider, Philipp

2023

Mobile monitoring of urban ultrafine particles in Novi Sad, Serbia

Davidović, Miloš D.; Kleut, Duška N.; Vito, Saverio De; Bartonova, Alena; Jovasevic-Stojanovic, Milena

2023

Interim European air quality maps for 2021. PM10, NO2 and ozone spatial estimates based on non-validated UTD data.

Horálek, Jan; Vlasakova, Leona; Schreiberova, Marketa; Schneider, Philipp; Damaskova, Dasa

This report presents European interim air quality maps for 2021, which are based on the non-validated up-to-date (UTD) measurement data and the CAMS Ensemble Forecast modelling results, together with other supplementary data. It contains maps of PM10 and NO2 annual averages and ozone indicator SOMO35.

ETC/HE

2023

Long-term Comparison of NOAA and AGAGE Non-CO2 Trace Gas Observations at Common Sites

Hall, Brad D.; Krummel, Paul B.; Muhle, Jens; Weiss, Ray F.; Montzka, Stephen A.; Vimont, Isaac J.; Dutton, Geoffrey S.; Harth, Christina M.; O'Doherty, Simon; Young, Dickon; nance, Jon David; Loh, Zoe M; Lan, Xin; Langenfelds, Ray; Salameh, Peter K.; Prinn, Ronald G.; Mitrevski, Blagoj; Lunder, Chris Rene

2023

Potential sources and transport of atmospheric microplastics in the Northern Atlantic Ocean

Evangeliou, Nikolaos; Gossmann, Isabel; Herzke, Dorte; Held, Andreas; Schulz, Janina; Nikiforov, Vladimir; Eckhardt, Sabine; Gerdts, Gunnar; Wurl, Oliver; Scholz-Böttcher, Barbara

2023

Establishment of killer whale (Orcinus orca) primary fibroblast cell cultures and their transcriptomic responses to pollutant exposure

Bjørneset, J.; Blévin, P.; Bjørnstad, P.M.; Dalmo, R.A.; Goksøyr, A.; Harju, M.; Limonta, G.; Panti, C.; Rikardsen, A.H.; Sundaram, A.Y.M.; Yadetie, F.; Routti, H.

Populations of killer whale (Orcinus orca) contain some of the most polluted animals on Earth. Yet, the knowledge on effects of chemical pollutants is limited in this species. Cell cultures and in vitro exposure experiments are pertinent tools to study effects of pollutants in free-ranging marine mammals. To investigate transcriptional responses to pollutants in killer whale cells, we collected skin biopsies of killer whales from the Northern Norwegian fjords and successfully established primary fibroblast cell cultures from the dermis of 4 out of 5 of them. Cells from the individual with the highest cell yield were exposed to three different concentrations of a mixture of persistent organic pollutants (POPs) that reflects the composition of the 10 most abundant POPs found in Norwegian killer whales (p,p’-DDE, trans-nonachlor, PCB52, 99, 101, 118, 138, 153, 180, 187). Transcriptional responses of 13 selected target genes were studied using digital droplet PCR, and whole transcriptome responses were investigated utilizing RNA sequencing. Among the target genes analysed, CYP1A1 was significantly downregulated in the cells exposed to medium (11.6 µM) and high (116 µM) concentrations of the pollutant mixture, while seven genes involved in endocrine functions showed a non-significant tendency to be upregulated at the highest exposure concentration. Bioinformatic analyses of RNA-seq data indicated that 13 and 43 genes were differentially expressed in the cells exposed to low and high concentrations of the mixture, respectively, in comparison to solvent control. Subsequent pathway and functional analyses of the differentially expressed genes indicated that the enriched pathways were mainly related to lipid metabolism, myogenesis and glucocorticoid receptor regulation. The current study results support previous correlative studies and provide cause-effect relationships, which is highly relevant for chemical and environmental management.

2023

Moisture Transport into the Arctic in a past and future climate

Eckhardt, Sabine; Svendby, Tove Marit; Cassiani, Massimo; Oliviè, Dirk Jan Leo

2023

Constraining black carbon emissions from wildfires and anthropogenic sources at contrasting Canadian sites

Lynch, Jada; Huang, Lin; Zhang, Wendy; Eckhardt, Sabine; Evangeliou, Nikolaos; Chang, Rachel

2023

Målinger av SO2 i omgivelsene til Elkem Carbon og REC Solar. Januar 2022 – desember 2022.

Hak, Claudia; Stensrød, Anna Maria Røyset; Andresen, Erik

På oppdrag fra Elkem Carbon AS har NILU utført målinger av SO2 i omgivelsene til Elkem Carbon og REC Solar i Vågsbygd (Kristiansand kommune). Elkem Carbon har i sin tillatelse fra Miljødirektoratet krav om å gjennomføre kontinuerlig måling av SO2 i omgivelsesluft. Målingene ble utført med SO2-monitor i boligområdet på Fiskåtangen (Konsul Wilds vei). I tillegg har Elkem Carbon AS valgt å måle med passive SO2-prøvetakere ved 3 steder rundt bedriftene. Rapporten dekker målinger i perioden 1. januar – 31. desember 2022. Norske grenseverdier for luftkvalitet (SO2) ble overholdt ved Konsul Wilds vei for alle midlingsperioder krevet i forurensningsforskriften (årsmiddel, vintermiddel, døgnmiddel og timemiddel). De mest belastede stedene i måleperioden var Konsul Wilds vei nordøst og Fiskåveien rett sør for bedriftene. To døgnmidler var over 125 µg/m3 (grenseverdi, 3 tillatt), 4 døgnmidler var over øvre vurderingsterskel (75 µg/m3) og 11 døgnmidler var over nedre vurderingsterskel (50 µg/m3).

NILU

2023

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

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