Out of Sight, Out of Mind: An Analysis of Immigration Detention Practices in Canada and Germany

International criticisms from human rights activists on a variety of matters related to Canada and Germany’s immigration detention frameworks illuminate the need for an examination of human rights impacts. This thesis explores the legal framework that allows for immigration detention and hopes to draw attention to and shed light on problems in the immigration detention frameworks identified in the literature. Through a qualitative comparative legal content analysis of laws and policies in the two countries, insight can be gained into the similarities and differences between the two countries to ultimately provide information about, and possible solutions to, the challenges faced by policymakers in this domain. Various laws and policies that govern immigration detention in both countries will be analyzed and compared in this thesis, in order to identify key themes and answer the following research questions: 1) How does each country regulate immigration detention? (a) In what circumstances is detention lawful in each country? What makes a detention unlawful in each country? b) How does each country address the key human rights concerns identified in the literature review (namely, racial discrimination, mental health, and child detentions)? (c) What can be learned from each country to better address the human rights impacts of immigration detention? By comparing Canada and Germany, light can be shed on potential human rights issues in the immigration detention frameworks and the domestic policy reform debates in both countries can be enriched. Faculty Supervisor: Dr. Tamara O’Doherty, School of Criminology, Simon Fraser Universit

Black carbon ageing in the Canadian Centre for Climate modelling and analysis atmospheric general circulation model

International audienceBlack carbon (BC) particles in the atmosphere have important impacts on climate. The amount of BC in the atmosphere must be carefully quantified to allow evaluation of the climate effects of this type of aerosol. In this study, we present the treatment of BC aerosol in the developmental version of the 4th generation Canadian Centre for Climate modelling and analysis (CCCma) atmospheric general circulation model (AGCM). The focus of this work is on the conversion of insoluble BC to soluble/mixed BC by physical and chemical ageing. Physical processes include the condensation of sulphuric and nitric acid onto the BC aerosol, and coagulation with more soluble aerosols such as sulphates and nitrates. Chemical processes that may age the BC aerosol include the oxidation of organic coatings by ozone. Four separate parameterizations of the ageing process are compared to a control simulation that assumes no ageing occurs. These simulations use 1) an exponential decay with a fixed 24h half-life, 2) a condensation and coagulation scheme, 3) an oxidative scheme, and 4) a linear combination of the latter two ageing treatments. Global BC burdens are 2.15, 0.15, 0.11, 0.21, and 0.11TgC for the control run, and four ageing schemes, respectively. The BC lifetimes are 98.1, 6.6, 5.0, 9.5, and 4.9 days, respectively. The sensitivity of modelled BC burdens, and concentrations to the factor of two uncertainty in the emissions inventory is shown to be greater than the sensitivity to the parameterization used to represent the BC ageing, except for the oxidation based parameterization. A computationally efficient parameterization that represents the processes of condensation, coagulation, and oxidation is shown to simulate BC ageing well in the CCCma AGCM. As opposed to the globally fixed ageing time scale, this treatment of BC ageing is responsive to varying atmospheric composition

Simulation of mineral dust aerosol with Piecewise Log-normal Approximation (PLA) in CanAM4-PAM

A new size-resolved dust scheme based on the numerical method of piecewise log-normal approximation (PLA) was developed and implemented in the fourth generation of the Canadian Atmospheric Global Climate Model with the PLA Aerosol Model (CanAM4-PAM). The total simulated annual global dust emission is 2500 Tg yr<sup>−1</sup>, and the dust mass load is 19.3 Tg for year 2000. Both are consistent with estimates from other models. Results from simulations are compared with multiple surface measurements near and away from dust source regions, validating the generation, transport and deposition of dust in the model. Most discrepancies between model results and surface measurements are due to unresolved aerosol processes. Biases in long-range transport are also contributing. Radiative properties of dust aerosol are derived from approximated parameters in two size modes using Mie theory. The simulated aerosol optical depth (AOD) is compared with satellite and surface remote sensing measurements and shows general agreement in terms of the dust distribution around sources. The model yields a dust AOD of 0.042 and dust aerosol direct radiative forcing (ADRF) of −1.24 W m<sup>−2</sup> respectively, which show good consistency with model estimates from other studies

Parameterization of sea-salt optical properties and physics of the associated radiative forcing

The optical properties of sea-salt aerosol have been parameterized at shortwave and longwave wavelengths. The optical properties were parameterized in a simple functional form in terms of the ambient relative humidity based on Mie optical property calculations. The proposed parameterization is tested relative to Mie calculations and is found to be accurate to within a few percent. In the parameterization, the effects of the size distribution on the optical properties are accounted for in terms of effective radius of the sea-salt size distribution. This parameterization differs from previous works by being formulated directly with the wet sea-salt size distribution and, to our knowledge, this is the first published sea-salt parameterization to provide a parameterization for both shortwave and longwave wavelengths. <br><br> We have used this parameterization in a set of idealized 1-D radiative transfer calculations to investigate the sensitivity of various attributes of sea-salt forcing, including the dependency on sea-salt column loading, effective variance, solar angle, and surface albedo. From these sensitivity tests, it is found that sea-salt forcings for both shortwave and longwave spectra are linearly related to the sea-salt loading for realistic values of loadings. The radiative forcing results illustrate that the shortwave forcing is an order of magnitude greater than the longwave forcing results and opposite in sign, for various loadings. Forcing sensitivity studies show that the influence of effective variance for sea-salt is minor; therefore, only one value of effective variance is used in the parameterization. The dependence of sea-salt forcing with solar zenith angle illustrates an interesting result that sea-salt can generate a positive top-of-the-atmosphere result (i.e. warming) when the solar zenith angle is relatively small (i.e. <30°). Finally, it is found that the surface albedo significantly affects the shortwave radiative forcing, with the forcing diminishing to zero as the surface albedo tends to unity

Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study

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 SO), 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.Assessments from the Russian ship-based campaign were performed with the support of RFBR project no. 20-55-12001 and according to the development program of the Interdisciplinary Scientific and Educational School of M.V. Lomonosov Moscow State University “Future Planet and Global Environmental Change”. Development of the methodology for aethalometric data treatment was supported by RSF project no. 19-77-30004. The BC observations on R/V Mirai were supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (Arctic Challenge for Sustainability (ArCS) project). Contributions by SMHI were funded by the Swedish Environmental Protection Agency under contract NV-03174-20 and the Swedish Climate and Clean Air Research program (SCAC) as well as partly by the Swedish National Space Board (NORD-SLCP, grant agreement ID: 94/16) and the EU Horizon 2020 project Integrated Arctic Observing System (INTAROS, grant agreement ID: 727890). Work on ACE-FTS analysis was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). Julia Schmale received funding from the Swiss National Science Foundation (project no. 200021_188478). Duncan Watson-Parris received funding from NERC projects NE/P013406/1 (A-CURE) and NE/S005390/1 (ACRUISE) as well as funding from the European Union's Horizon 2020 research and innovation program iMIRACLI under Marie Skłodowska-Curie grant agreement no. 860100. LATMOS has been supported by the EU iCUPE (Integrating and Comprehensive Understanding on Polar Environments) project (grant agreement no. 689443) under the European Network for Observing our Changing Planet (ERA-Planet), as well as access to IDRIS HPC resources (GENCI allocation A009017141) and the IPSL mesoscale computing center (CICLAD: Calcul Intensif pour le CLimat, l’Atmosphère et la Dynamique) for model simulations. Naga Oshima was supported by the Japan Society for the Promotion of Science KAKENHI (grant nos. JP18H03363, JP18H05292, and JP21H03582), the Environment Research and Technology Development Fund (grant nos. JPMEERF20202003 and JPMEERF20205001) of the Environmental Restoration and Conservation Agency of Japan, the Arctic Challenge for Sustainability II (ArCS II) under program grant no. JPMXD1420318865, and a grant for the Global Environmental Research Coordination System from the Ministry of the Environment, Japan (MLIT1753). The research with GISS-E2.1 has been supported by the Aarhus University Interdisciplinary Centre for Climate Change (iClimate) OH fund (no. 2020-0162731), the FREYA project funded by the Nordic Council of Ministers (grant agreement nos. MST-227-00036 and MFVM-2019-13476), and the EVAM-SLCF funded by the Danish Environmental Agency (grant agreement no. MST-112-00298). Jesper Christensen (for DEHM model) received funding from the Danish Environmental Protection Agency (DANCEA funds for Environmental Support to the Arctic Region project; grant no. 2019-7975). Maria Sand has been supported by the Research Council of Norway (grant 315195, ACCEPT).Peer Reviewed"Article signat per més de 50 autors/es: 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, and Tahya Weiss-Gibbons "Postprint (published version

Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models

This study quantifies black carbon (BC) processes in three global climate models and one chemistry transport model, with focus on the seasonality of BC transport, emissions, wet and dry deposition in the Arctic. In the models, transport of BC to the Arctic from lower latitudes is the major BC source for this region. Arctic emissions are very small. All models simulated a similar annual cycle of BC transport from lower latitudes to the Arctic, with maximum transport occurring in July. Substantial differences were found in simulated BC burdens and vertical distributions, with Canadian Atmospheric Global Climate Model (CanAM) (Norwegian Earth System Model, NorESM) producing the strongest (weakest) seasonal cycle. CanAM also has the shortest annual mean residence time for BC in the Arctic followed by Swedish Meteorological and Hydrological Institute Multiscale Atmospheric Transport and Chemistry model, Community Earth System Model, and NorESM. Overall, considerable differences in wet deposition efficiencies in the models exist and are a leading cause of differences in simulated BC burdens. Results from model sensitivity experiments indicate that convective scavenging outside the Arctic reduces the mean altitude of BC residing in the Arctic, making it more susceptible to scavenging by stratiform (layer) clouds in the Arctic. Consequently, scavenging of BC in convective clouds outside the Arctic acts to substantially increase the overall efficiency of BC wet deposition in the Arctic, which leads to low BC burdens and a more pronounced seasonal cycle compared to simulations without convective BC scavenging. In contrast, the simulated seasonality of BC concentrations in the upper troposphere is only weakly influenced by wet deposition in stratiform clouds, whereas lower tropospheric concentrations are highly sensitive.Key PointsSeasonal variations of black carbon (BC) mass budgets in the Arctic are simulatedGood agreement in simulated annual mean transport of BC to the Arctic in modelsConvective wet removal is important for differences in modeled BC concentrationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/133539/1/jgrd53064-sup-0001-SI.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133539/2/jgrd53064.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133539/3/jgrd53064_am.pd

Sensitivity of Arctic sulfate aerosol and clouds to changes in future surface seawater dimethylsulfide concentrations

Dimethylsulfide (DMS), outgassed from ocean waters, plays an important role in the climate system, as it oxidizes to methane sulfonic acid (MSA) and sulfur dioxide (SO2), which can lead to the formation of sulfate aerosol. Newly formed sulfate aerosol resulting from DMS oxidation may grow by condensation of gases, in-cloud oxidation, and coagulation to sizes where they may act as cloud condensation nuclei (CCN) and influence cloud properties. Under future global warming conditions, sea ice in the Arctic region is expected to decline significantly, which may lead to increased emissions of DMS from the open ocean and changes in cloud regimes. In this study we evaluate impacts of DMS on Arctic sulfate aerosol budget, changes in cloud droplet number concentration (CDNC), and cloud radiative forcing in the Arctic region under current and future sea ice conditions using an atmospheric global climate model. Given that future DMS concentrations are highly uncertain, several simulations with different surface seawater DMS concentrations and spatial distributions in the Arctic were performed in order to determine the sensitivity of sulfate aerosol budgets, CDNC, and cloud radiative forcing to Arctic surface seawater DMS concentrations. For any given amount and distribution of Arctic surface seawater DMS, similar amounts of sulfate are produced by oxidation of DMS in 2000 and 2050 despite large increases in DMS emission in the latter period due to sea ice retreat in the simulations. This relatively low sensitivity of sulfate burden is related to enhanced sulfate wet removal by precipitation in 2050. However simulated aerosol nucleation rates are higher in 2050, which results in an overall increase in CDNC and substantially more negative cloud radiative forcing. Thus potential future reductions in sea ice extent may cause cloud albedos to increase, resulting in a negative climate feedback on radiative forcing in the Arctic associated with ocean DMS emissions.</p

Modelling the relationship between liquid water content and cloud droplet number concentration observed in low clouds in the summer Arctic and its radiative effects

Low clouds persist in the summer Arctic with important consequences for the radiation budget. In this study, we simulate the linear relationship between liquid water content (LWC) and cloud droplet number concentration (CDNC) observed during an aircraft campaign based out of Resolute Bay, Canada, conducted as part of the Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments study in July 2014. Using a single-column model, we find that autoconversion can explain the observed linear relationship between LWC and CDNC. Of the three autoconversion schemes we examined, the scheme using continuous drizzle (Khairoutdinov and Kogan, 2000) appears to best reproduce the observed linearity in the tenuous cloud regime (Mauritsen et al., 2011), while a scheme with a threshold for rain (Liu and Daum, 2004) best reproduces the linearity at higher CDNC. An offline version of the radiative transfer model used in the Canadian Atmospheric Model version 4.3 is used to compare the radiative effects of the modelled and observed clouds. We find that there is no significant difference in the upward longwave cloud radiative effect at the top of the atmosphere from the three autoconversion schemes (p=0.05) but that all three schemes differ at p=0.05 from the calculations based on observations. In contrast, the downward longwave and shortwave cloud radiative effect at the surface for the Wood (2005b) and Khairoutdinov and Kogan (2000) schemes do not differ significantly (p=0.05) from the observation-based radiative calculations, while the Liu and Daum (2004) scheme differs significantly from the observation-based calculation for the downward shortwave but not the downward longwave fluxes.This research has been supported by the Natural Sciences and Engineering Research Council of Canada (Discovery Grants RGPIN-2014-05173 and RGPIN 155649) and the Marine Environmental Observation, Prediction and Response Network (MEOPAR), which is a federally funded Networks of Centres of Excellence (NCE) (EC1-RC-DAL).Peer ReviewedPostprint (published version

Arctic air pollution: Challenges and opportunities for the next decade

The Arctic is a sentinel of global change. This region is influenced by multiple physical and socio-economic drivers and feedbacks, impacting both the natural and human environment. Air pollution is one such driver that impacts Arctic climate change, ecosystems and health but significant uncertainties still surround quantification of these effects. Arctic air pollution includes harmful trace gases (e.g. tropospheric ozone) and particles (e.g. black carbon, sulphate) and toxic substances (e.g. polycyclic aromatic hydrocarbons) that can be transported to the Arctic from emission sources located far outside the region, or emitted within the Arctic from activities including shipping, power production, and other industrial activities. This paper qualitatively summarizes the complex science issues motivating the creation of a new international initiative, PACES (air Pollution in the Arctic: Climate, Environment and Societies). Approaches for coordinated, international and interdisciplinary research on this topic are described with the goal to improve predictive capability via new understanding about sources, processes, feedbacks and impacts of Arctic air pollution. Overarching research actions are outlined, in which we describe our recommendations for 1) the development of trans-disciplinary approaches combining social and economic research with investigation of the chemical and physical aspects of Arctic air pollution; 2) increasing the quality and quantity of observations in the Arctic using long-term monitoring and intensive field studies, both at the surface and throughout the troposphere; and 3) developing improved predictive capability across a range of spatial and temporal scales