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Sarah Albertin, Slimane Bekki, Joël Savarino. (2021). Nitrogen isotopes (δ15N) and oxygen isotope anomalies (Δ17O, δ18O) in atmospheric nitrogen dioxide : a new perspective for isotopic constraints on oxidation and aerosols formation processes.
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Brice Temime Roussel, Meeta Cesler-Maloney, Benjamin Chazeau, Amna Ijaz, Natalie Brett, Katharine Law, Slimane Bekki, Jingqiu Mao, Damien Ketcherside, Vanessa Selimovic, Lu Hu, William R. Simpson, Barbara D'Anna. (2022). Concentrations and Sources of VOCs during wintertime urban pollution at Fairbanks, Alaska (Vol. 2022).
Abstract: Fairbanks, Alaska is an urban area that has multiple local emission sources including power plants, domestic heating, and mobile sources, leading to severe wintertime pollution events during cold stable episodes where strong temperature inversions limit pollutant dispersion. In order to evaluate the individual contribution of these sources on Volatile Organic Compounds (VOCs) concentrations, ground-based measurements were carried out at high temporal resolution (2 minutes) using on-line instrumentation (Proton Transfer Reaction Time of Flight Mass Spectrometer: PTR-ToF-MS) during the winter 2022 in downtown Fairbanks as part of the Alaskan Layered Pollution and Chemical Analysis (ALPACA) 2022 field experiment. These measurements are recorded in the urban business district, which probably enhances the traffic component compared to domestic heating. From the detailed analysis of the mass spectra acquired in the 0-500 amu range, more than 330 ions were found of interest for further investigation. Source apportionment analysis was performed using Positive Matrix Factorization (PMF) resolved with the multilinear engine (ME-2) approach. Based on their mass spectral profiles, diurnal cycles and correlation with external collocated measurements (gaseous pollutants: CO, CO2, NOx, SO2, ozone, and specific particulate matter markers), the factors identified could be related to mobile sources (gasoline-like and diesel-like traffic), to heating (residential, diesel-like heating in addition to a couple of specific biomass burning, and to non-combustion sources attributed to secondary processes. This study contributes to the Air Pollution in the Arctic: Climate, Environment and Societies – Alaskan Layered Pollution And Chemical Analysis (PACES-ALPACA) initiative. The French contribution is part of the CASPA (Climate-relevant Aerosol Sources and Processes in the Arctic)/IPEV project.
Programme: 1215
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Eleftherios Ioannidis. (2022). Local and remote sources of Arctic air pollution // Sources locales et éloignées de pollution atmosphérique dans l'Arctique.
Abstract: La région arctique se réchauffe plus rapidement que toute autre région de la planète en raison de l’effet des gaz à effet de serre, notamment le CO2, et des forçeurs climatiques à courte durée de vie d’origine anthropique, comme le carbone suie (BC). Au cours des 20 à 30 dernières années, les émissions anthropiques lointain au-dessus des régions de latitude moyenne ont diminué. Les émissions anthropiques dans l’Arctique y contribuent également et pourraient augmenter à l’avenir et influencer davantage la pollution atmosphérique et le climat de l’Arctique. Les émissions naturelles, telles que les aérosols d’origine marine, pourraient également augmenter en raison du changement climatique en cours. Cependant, les processus et les sources qui influencent les aérosols et les gaz traces dans l’Arctique sont mal quantifiés, surtout en hiver. Dans cette thèse, des simulations quasi-hémisphériques et régionales sont réalisées à l’aide du modèle Weather Research Forecast, couplé à la chimie (WRF-Chem). Le modèle est utilisé pour étudier la composition atmosphérique sur la région Arctique et lors de deux campagnes de terrain, l’une au nord de l’Alaska à Barrow, Utqiagvik en janvier et février 2014 et la seconde à Fairbanks, au centre de l’Alaska en novembre et décembre 2019 lors de la campagne française pré-ALPACA (Alaskan Layered Pollution And Chemical Analysis). Tout d’abord, les aérosols inorganiques et les aérosols de sel marin (SSA) modélisés sont évalués sur des sites arctiques pendant l’hiver. Ensuite, le modèle est amélioré en ce qui concerne les traitements des SSA, après évaluation par rapport aux données de la campagne de Barrow, et leur contribution à la charge totale d’aérosols dans la région arctique est quantifiée. Une série d’analyses de sensibilité est effectuée sur le nord de l’Alaska, révélant des incertitudes du modèle dans les processus influençant les SSA dans l’Arctique, tels que la présence de glace de mer et de chenaux ouverts. Ensuite, une analyse de sensibilité est effectuée pour étudier les processus et les sources qui influencent le BC hivernale dans l’ensemble de l’Arctique et au nord de l’Alaska, en se concentrant sur les traitements de dépôt et les émissions régionales. Des variations de la sensibilité du modèle aux dépôts humides et secs sont constatées dans tout l’Arctique et pourraient expliquer les biais du modèle. Dans le nord de l’Alaska, les émissions régionales provenant de l’extraction pétrolière contribuent de manière importante au BC observée. Les résultats du modèle sont également sensibles aux schémas de paramétrisation de la couche limite. Troisièmement, la version améliorée du modèle est utilisée pour étudier la contribution des sources régionales et locales à la pollution atmosphérique dans la région de Fairbanks pendant l’hiver 2019. En utilisant des émissions actualisées, le modèle donne de meilleurs résultats pour l’hiver 2019 que pour l’hiver 2014, lorsqu’on le compare aux observations effectuées sur des sites de fond en Alaska. Les sous-estimations des aérosols modélisés de BC et de sulfate s’expliquent en partie par le manque d’émissions anthropiques locales et régionales. Dans le cas du sulfate , des mécanismes supplémentaires de formation d’aérosols secondaires dans des conditions sombres/froides doivent également être pris en compte.
Keywords: 551.5113 577.278 Aérosols marins Arctic air pollution Arctique Chimie de l'atmosphère -- Modèles mathématiques Effets du réchauffement de la Terre Local sources Pollution atmosphérique Pollution atmosphérique -- Arctique Sources locales WRF-Chem
Programme: 1215
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Julia Maillard. (2022). Boundary layer processes impacting the surface energy balance in the Arctic // Processus de la couche limite Arctique et impact sur le bilan d'énergie en surface.
Abstract: L'Arctique se réchauffe deux à trois fois plus vite que le reste de la Terre, et c'est donc une zone d'étude cruciale des sciences de l'atmosphère. Cette thèse a pour but d'étudier deux caractéristiques de la couche limite de l'Arctique (les nuages et les inversions de température en surface) et de déterminer leur impact sur le bilan d'énergie de surface en combinant observations et modélisation. Tout d'abord, une nouvelle statistique des caractéristiques nuageuses au-dessus de la banquise a été dérivée d'un ensemble de 1777 profils lidar obtenus au cours de la campagne Ice, Atmosphere, Ocean Observation Systems (IAOOS). Lors de cette campagne, les nuages étaient présents plus de 85% du temps de mai à octobre et l'épaisseur (optique et géométrique) des couches de nuages individuelles était maximale en octobre. Le forçage radiatif total des nuages en été a été était négatif pour les nuages optiquement minces, mais positif pour les nuages optiquement épais. Deuxièmement, l'impact des vitesses de vent sur le développement des inversions de température en surface en Arctique continental a été étudié. L'analyse des mesures de la campagne pré-ALPACA, qui a eu lieu à Fairbanks, Alaska, en hiver 2019, a montré qu'une circulation locale se renforce en conditions anticycloniques. Cet écoulement inhibe le développement de fortes inversions de température en alimentant la turbulence, même lorsque le refroidissement radiatif est très fort. La modélisation des inversions de température en conditions de ciel clair en lien avec la vitesse du vent a ensuite été étudiée, plus particulièrement en zones de couvert forestier. Un modèle analytique à deux couches de la couche de surface végétalisée a été développé. Ce modèle prévoit une diminution plus lente du gradient de température en fonction de la vitesse du vent par rapport à un modèle à une seul couche, et il est cohérent avec les observations menées à un site du réseau Ameriflux près de Fairbanks. En revanche, deux schémas de couche de surface de WRF se sont avérés imposer des limites excessives à la turbulence.
Keywords: 551.51 Arctic Arctique Arctique -- Climat Boundary-layer Clouds Couche limite Couche limite (météorologie) Inversions de température Modélisation Nuages Nuages -- Arctique Observations Physique de l'atmosphère Température atmosphérique -- Arctique -- Modèles mathématiques
Programme: 1215
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Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, David W. Tarasick. (2023). Arctic tropospheric ozone: assessment of current knowledge and model performance (Vol. 23).
Abstract: As the third most important greenhouse gas (GHG) after carbon dioxide (CO2) and methane (CH4), tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of ±50 % depending on the model and the altitude. The MMM performs best, within ±8 % for most locations and seasons. However, nearly all models overestimate O3 near the tropopause (∼300 hPa or ∼8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx, and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O3.
Programme: 1215
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Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, Tahya Weiss-Gibbons. (2022). Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study (Vol. 22).
Abstract: While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO42-), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.
Programme: 1215
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Knut von Salzen, Cynthia H. Whaley, Susan C. Anenberg, Rita Van Dingenen, Zbigniew Klimont, Mark G. Flanner, Rashed Mahmood, Stephen R. Arnold, Stephen Beagley, Rong-You Chien, Jesper H. Christensen, Sabine Eckhardt, Annica M. L. Ekman, Nikolaos Evangeliou, Greg Faluvegi, Joshua S. Fu, Michael Gauss, Wanmin Gong, Jens L. Hjorth, Ulas Im, Srinath Krishnan, Kaarle Kupiainen, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Ville-Veikko Paunu, Yiran Peng, David Plummer, Luca Pozzoli, Shilpa Rao, Jean-Christophe Raut, Maria Sand, Julia Schmale, Michael Sigmond, Manu A. Thomas, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Minqi Wang, Barbara Winter. (2022). Clean air policies are key for successfully mitigating Arctic warming (Vol. 3).
Abstract: A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050.
Keywords: Atmospheric chemistry Climate-change mitigation
Programme: 1255
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Eleftherios Ioannidis, Kathy S. Law, Jean-Christophe Raut, Louis Marelle, Tatsuo Onishi, Rachel M. Kirpes, Lucia M. Upchurch, Thomas Tuch, Alfred Wiedensohler, Andreas Massling, Henrik Skov, Patricia K. Quinn, Kerri A. Pratt. (2023). Modelling wintertime sea-spray aerosols under Arctic haze conditions (Vol. 23).
Abstract: Anthropogenic and natural emissions contribute to enhanced concentrations of aerosols in the Arctic winter and early spring, with most attention being paid to anthropogenic aerosols that contribute to so-called Arctic haze. Less-well-studied wintertime sea-spray aerosols (SSAs) under Arctic haze conditions are the focus of this study, since they can make an important contribution to wintertime Arctic aerosol abundances. Analysis of field campaign data shows evidence for enhanced local sources of SSAs, including marine organics at Utqiaġvik (formerly known as Barrow) in northern Alaska, United States, during winter 2014. Models tend to underestimate sub-micron SSAs and overestimate super-micron SSAs in the Arctic during winter, including the base version of the Weather Research Forecast coupled with Chemistry (WRF-Chem) model used here, which includes a widely used SSA source function based on Gong et al. (1997). Quasi-hemispheric simulations for winter 2014 including updated wind speed and sea-surface temperature (SST) SSA emission dependencies and sources of marine sea-salt organics and sea-salt sulfate lead to significantly improved model performance compared to observations at remote Arctic sites, notably for coarse-mode sodium and chloride, which are reduced. The improved model also simulates more realistic contributions of SSAs to inorganic aerosols at different sites, ranging from 20 %–93 % in the observations. Two-thirds of the improved model performance is from the inclusion of the dependence on SSTs. The simulation of nitrate aerosols is also improved due to less heterogeneous uptake of nitric acid on SSAs in the coarse mode and related increases in fine-mode nitrate. This highlights the importance of interactions between natural SSAs and inorganic anthropogenic aerosols that contribute to Arctic haze. Simulation of organic aerosols and the fraction of sea-salt sulfate are also improved compared to observations. However, the model underestimates episodes with elevated observed concentrations of SSA components and sub-micron non-sea-salt sulfate at some Arctic sites, notably at Utqiaġvik. Possible reasons are explored in higher-resolution runs over northern Alaska for periods corresponding to the Utqiaġvik field campaign in January and February 2014. The addition of a local source of sea-salt marine organics, based on the campaign data, increases modelled organic aerosols over northern Alaska. However, comparison with previous available data suggests that local natural sources from open leads, as well as local anthropogenic sources, are underestimated in the model. Missing local anthropogenic sources may also explain the low modelled (sub-micron) non-sea-salt sulfate at Utqiaġvik. The introduction of a higher wind speed dependence for sub-micron SSA emissions, also based on Arctic data, reduces biases in modelled sub-micron SSAs, while sea-ice fractions, including open leads, are shown to be an important factor controlling modelled super-micron, rather than sub-micron, SSAs over the north coast of Alaska. The regional results presented here show that modelled SSAs are more sensitive to wind speed dependence but that realistic modelling of sea-ice distributions is needed for the simulation of local SSAs, including marine organics. This study supports findings from the Utqiaġvik field campaign that open leads are the primary source of fresh and aged SSAs, including marine organic aerosols, during wintertime at Utqiaġvik; these findings do not suggest an influence from blowing snow and frost flowers. To improve model simulations of Arctic wintertime aerosols, new field data on processes that influence wintertime SSA production, in particular for fine-mode aerosols, are needed as is improved understanding about possible local anthropogenic sources.
Programme: 1215
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Meeta Cesler-Maloney, William R. Simpson, Tate Miles, Jingqiu Mao, Kathy S. Law, Tjarda J. Roberts. (2022). Differences in Ozone and Particulate Matter Between Ground Level and 20 m Aloft are Frequent During Wintertime Surface-Based Temperature Inversions in Fairbanks, Alaska (Vol. 127).
Abstract: During winter in Fairbanks, Alaska, fine particulate matter (PM2.5) accumulates to large concentrations at breathing level; yet little is known about atmospheric composition aloft. To investigate vertical differences of pollutants, we measured PM2.5 and ozone (O3) at 3 and 20 m above ground level (AGL) in Fairbanks during winter (November 2019–March 2020). We measured temperature and PM2.5 at 3, 6, 9, and 11 m AGL on a tower to quantify surface-based temperature inversions (SBIs) and near-surface PM2.5 gradients. We defined SBIs as data with an 11 m minus 3 m temperature difference greater than 0.5°C. We observed the largest differences in PM2.5 and O3 when SBIs were present. During SBIs, PM2.5 accumulated to large concentrations at 3 m but to a lesser extent at 20 m, demonstrating reduced vertical mixing. During SBIs, the median PM2.5 concentration was 4.8 μg m−3 lower at 20 m than at 3 m. When PM2.5 concentrations were large at 3 m, O3 was often completely chemically removed (titrated) but was still present at 20 m. During SBIs, the O3 mixing ratio was more than 2 nmol mol−1 larger at 20 m than at 3 m in 48% of the data. Results show that during SBIs, pollution in Fairbanks is mixed to altitudes below 20 m AGL and that the oxidation regime of the atmosphere changes from 3 to 20 m AGL as large differences in O3 mixing ratios were measured during SBIs.
Keywords: Alaska inversion ozone PM2.5 pollution vertical
Programme: 1215
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Thierry Boulinier. (2023). Avian influenza spread and seabird movements between colonies (Vol. 38). Bachelor's thesis, , .
Keywords: colonial breeding foraging HPAI H5N1 migration movement ecology prospecting spatial disease dynamics
Programme: 333,1151
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