The Greater Toronto Area (GTA, pop. 6.4 million) is the populous city in Canada, thus accurately quantifying GHG emissions from the GTA is an important step towards meeting Canada’s commitments to reduce its Greenhouse gas emissions. Mitigation of methane (CH4) emissions is of particular importance when setting the country’s policy measures to meet the GHG reduction goal since it can be economically advantageous. In this study, a methane emission inventory with a high spatial resolution was prepared using individual facility reports gathered for each municipality in the GTA. Measurements using portable Fourier Transform Spectrometers (FTS), are then used to monitor CH4 levels in the GTA continuously. Four FTS instruments were installed in different locations in the city in line with the most frequent wind directions based on historical observations. High peak events were investigated and with measurements of tracer concentrations and wind data, the emissions from the city were estimated. At the end, we investigated how the results could be used to improve the existing emission inventory.

Efthymios Balomenos1, Panagiotis Davris1, Dimitrios Panias1, Ioannis Paspaliaris1Laboratory of Metallurgy, National Technical University of Athens, Zografos Campus, GreeceEmail: [email protected] Residue‘Bauxite Residue’ (BR) refers to the insoluble solid material, generated during the extraction of alumina (Al2O3) from Bauxite ore using the Bayer process. When bauxite ore is treated with caustic soda, the aluminium hydroxides/oxides contained within, are solubilized, with approximately 50% of the bauxite mass being transferred to the liquid phase, while the remaining solid fraction constitutes the -bauxite- residue.Active lime is usually added during digestion to control and reduce caustic soda and alumina losses from the formation of desilication products.. The solid-liquid separation after ore digestion takes place in thickeners and washers, resulting in the formation of a red-colored bauxite residue slurry (approx. 50% solids) which was previously termed ‘red mud’. Nowadays many plants use, as a final step of slurry treatment, high pressure filtration (the most efficient method of alkali recovery), in which the bauxite residue slurry is pressed to remove the maximum of remaining liquor and produce a compact filtercake with a relative humidity of 25-30%.It is estimated that for each ton of alumina produced 1.0- 1.5 tons of solid residue (on a dry basis) is generated depending on the initial bauxite ore grade and alumina extraction efficiency (Evans 2016). Bauxite residue consists of of various metal oxides of Fe, Al, Ti, Si, Ca, Na, V, Ga (depending on the initial chemical composition of the bauxite ore) along with inclusions of unwashed sodium aluminate solution.As the global demand for primary aluminium metal increases so will the BR production, currently in excess of 150 million tons per year worldwide (Power et al. 2011). This is generated at more than 100 active alumina refining plants worldwide. In addition, there are at least another 50 closed legacy sites, so the combined stockpile of bauxite residue at active and legacy sites is estimated at three thousand million tons. ( World Aluminium and the European Aluminium Association, 2015)The primary aluminium industry has always focused on discovering potential applications for BR utilization. The vast amount of research and studies on BR utilisation is justified by more than 734 patents since 1964. Possible applications can broadly be broken down into various categories, such as cement and building materials production, iron production, trace element (Ga, REE, V,etc.) recovery, use as soil amelioration, landfill capping, acid mine drainage treatment and others (Evans 2016). The recent REE crisis fueled significant research effort in recovering the REE that are found in some BRs in concentrations between 1 - 2 kg of total REE / t of BR. Given the large quantity of the annual BR production, the total amount of contained REE becomes significant and could cover part of the global REE demand (Balomenos et al., 2017a). Furthermore, while the treatment of BR for the recovery of REEs does not solve the BR deposition problem, as the volume of the waste remains practically unaffected, it does help in the economic viability of holistic processing flowsheet seeking to achieve near zero-waste through multiple processing steps (Balomenos et al., 2017b).Rare Earths in Bauxite ResidueThe bauxite ore is one of the factors that affect the concentration of REE in bauxite Residue. Bauxites are classified in three categories, lateritic bauxites (88%), karstic bauxites (11,5%) and Tikhvin type bauxites (0,5%) (Bardossy, 1982; Bárdossy and Aleva, 1990). Karstic bauxites are mainly found in Europe, Jamaica, Russia and China. The karstic bauxites contain higher concentrations of REE than the lateritic bauxites. REE are detected in bauxite ore as fluorcarbonate or phosphate minerals which are very similar to the main industrial minerals of REE (bastnaesite - monazite) (Li et al., 2013; Mouchos et al., 2017; Ochsenkühn-Petropulu 1995; Vind et al., 2018a). It has also been reported that in the Bayer process REE end up in the BR in 2:1 ratio, compared to the initial bauxite ore. (Derevyankin et al., 1981; Ochsenkühn-Petropulu et al., 1994; Wagh and Pinnock, 1987).The worldwide typical concentration of REE in BR is 800-2500 mg/kg and is related to the initial bauxite ore and the operating conditions of the Bayer process (Deady et al., 2018). Recent research shows that REE in BR can be found in secondary mineral phases produced by the Bayer process, known as the desilication product (DSP). DSP is the result of the silicon removal from the aluminate solution during the leaching of the bauxite ore, as silicon is major pollutant for the final alumina product. Presence of REE in the DSP can be attributed to REE from the bauxite ore being dissolved in the Bayer process; these REE are incorporated into the newly formed DSP mineral matrix that contains a mixture of Fe, Ti, Si, Al Ca and Na ions (Vind et al., 2018a).Scandium (Sc) often differs from the other REE behavior. Especially in lateritic bauxites and their corresponding BR, it is often correlated with iron and titanium and zircon minerals (Vind et al., 2018a) (Liu et al., 2018; Zhang et al., 2017), which for the most part are unaffected by the Bayer process. This is also confirmed by the laterite deposits in Australia and the Greek BR (Chassé et al., 2016) where the main mineral, with high concentration of Sc is goethite (Vind et al., 2018b). However, there are cases of BR ,where Sc is found to be related to larger extent to the soluble Al-bearing minerals, as is reported by Russian researchers (Suss et al., 2018).Published chemical analysis and leaching studies of bauxite residue focus on the concentration of Sc, because Sc represents 95% of REE’s financial values found in BR (case of Greek Bauxite, reported by Ochsenkühn-Petropoulou et al., 2002). Table 1 presents the Sc concentration in different Bauxite Residues worldwide as reported in literature.Table 1 Concentration of Scandium in Different Bauxite Residues

Computation of petrophysical properties on digital rock images is becoming important in geoscience. However, it is usually complicated for natural heterogeneous porous media due to the presence of multiscale pore structures. To capture the heterogeneity of rocks, we develop a method based on deep generative adversarial networks to assimilate multiscale imaging data for the generation of synthetic high-resolution digital rocks having a large field of view. The reconstructed images not only honor the geometric structures of 3-D micro-CT images but also recover fine details existing at the scale of 2-D scanning electron microscopy images. Furthermore, the consistency between the real and synthetically generated images in terms of porosity, specific surface area, two-point correlation and effective permeability reveals the validity of our proposed method. It provides an effective way to fuse multiscale digital rock images for better characterization of heterogeneous porous media and better prediction of pore-scale flow and petrophysical properties.

Over the past three decades, large tracts of tropical forests have been converted to crop and pasturelands across southern Amazonia, largely to meet the increasing worldwide demand for protein. As the world’s population continue to grow and consume more protein per capita, forest conversion to grow more crops could be a potential solution to meet such demand. However, widespread deforestation is expected to negatively affect crop productivity via multiple pathways (e.g., thermal regulation, rainfall, local moisture, pest control, among others). To quantify how deforestation affects crop productivity, we modeled the relationship between forest amount and enhanced vegetation index (EVI—a proxy for crop productivity) during the soybean planting season across southern Amazonia. Our hypothesis that forest amount causes increased crop productivity received strong support. We found that the maximum MODIS-based EVI in soybean fields increased as a function of forest amount across three spatial-scales, 0.5 km, 1 km, 2 km, 5 km, 10 km, 15 km and 20 km. However, the strength of this relationship varied across years and with precipitation, but only at the local scale (e.g., 500 meters and 1 km radius). Our results highlight the importance of considering forests to design sustainable landscapes.

For the first time, we monitored continuous 2D tidal currents at a shallow tidal junction using the fluvial acoustic tomography (FAT) system during a period of ~ 34.4 days. The horizontal distribution and spatiotemporal variation of the tidal velocities were efficiently estimated by the inverse analysis method, and the reconstructed velocity patterns agreed well with the recorded acoustic Doppler current profiler series data. Additionally, the high frequency observation interval (1-min) used provided us with the opportunity to detect the rapid processes of the transformation of tidal current patterns during flood tide at the junction. These results further demonstrate that FAT is a potent tool for continuously mapping variable 2D tidal currents at shallow tidal junctions. Furthermore, tidal harmonic analyses of the reconstructed tidal currents were performed to clarify the nonlinear spatial evolution processes of the variations in tidal energy, when tides propagated from the estuary to the tidal junction. The sub-tide species (, ) caused significant fortnightly variations in the tidal range along the tidal branches. The variations in the tidal current were dominated by semidiurnal species (D2: , , , ), followed by diurnal species (D1: , , ) and quarter-diurnal species (D4: , ). The / amplitude ratios were higher during low river discharge periods, signifying that the nonlinear tidal distortion varies with river discharge. River-tide interactions strongly affected tidal asymmetry. It is believed that this study provides further understanding of hydrological research in shallow tidal systems.

Outputs from new state-of-the-art climate models under the Coupled Model Inter-comparison Project phase 6 (CMIP6) promise improvement and enhancement of climate change projections information for Australia. Here we focus on three key aspects of CMIP6: what is new in these models, how the available CMIP6 models evaluate compared to CMIP5, and their projections of the future Australian climate compared to CMIP5 focussing on the highest emissions scenario. The CMIP6 ensemble has several new features of relevance to policy-makers and others, for example the integrated matrix of socio-economic and concentration pathways. The CMIP6 models show incremental improvements in the simulation of the climate in the Australian region, including a reduced equatorial Pacific cold-tongue bias, slightly improved rainfall teleconnections with regional climate drivers, improved representation of atmosphere and ocean extreme heat events, as well as dynamic sea level. However, important regional biases remain, evident in the excessive precipitation over the Maritime Continent and precipitation pattern biases in the nearby tropical convergence zones. Projections of temperature and rainfall from the available CMIP6 ensemble broadly agree with those from CMIP5, except for a group of CMIP6 models with higher climate sensitivity and greater warming and increase in some extremes after 2050. CMIP6 rainfall projections are similar to CMIP5, but the ensemble examined has a narrower range of rainfall change in summer in the north and winter in the south. Overall, future national projections are likely to be similar to previous versions but perhaps with some areas of improved confidence and clarity.

Upscaling flux tower measurements based on machine learning (ML) algorithms is an essential approach for large-scale net ecosystem CO2 exchange (NEE) estimation, but existing ML upscaling methods face some challenges, particularly in capturing NEE interannual variations (IAVs) that may relate to lagged effects. With the capacity of characterizing temporal memory effects, the Long Short-Term Memory (LSTM) networks are expected to help solve this problem. Here we explored the potential of LSTM for predicting NEE across various ecosystems using flux tower data over 82 sites in North America. The LSTM model with differentiated plant function types (PFTs) demonstrates the capability to explain 79.19% (R2 = 0.79) of the monthly variations in NEE within the testing set, with RMSE and MAE values of 0.89 and 0.57 g C m-2 d-1 respectively (r = 0.89, p < 0.001). Moreover, the LSTM model performed robustly in predicting cross-site variability, with 67.19% of the sites that can be predicted by both LSTM models with and without distinguished PFTs showing improved predictive ability. Most importantly, the IAV of predicted NEE highly correlated with that in flux observations (r = 0.81, p < 0.001), clearly outperforming that by the random forest model (r = -0.21, p = 0.011). Among all nine PFTs, solar-induced chlorophyll fluorescence, downward shortwave radiation, and leaf area index are the most important variables for explaining NEE variations, collectively accounting for approximately 54.01% in total. This study highlights the great potential of LSTM for improving carbon flux upscaling with multi-source remote sensing data.

The use of geophysical methods to characterize subsurface properties has significantly grown in the last decade. Although geophysics can bring relevant spatial and temporal information on subsurface processes, the quantitative interpretation and integration in models remain difficult. Indeed, standard deterministic solutions suffer from (excessive) smoothing and spatially variable resolution, whereas joint or coupled inversions remain difficult to apply in complex cases. Hermans et al. (2016) proved using cross-borehole ERT that physical properties distribution could be directly retrieved from data using Bayesian Evidential Learning (BEL). BEL uses a series of prior models to derive a direct relationship between data and forecast in a reduced dimension space. This can be challenging when the prediction becomes more complex with higher dimensions. In this contribution, we extend the work of Hermans et al. (2016) to a full 4D experiment (3D + time). We demonstrate that the shape and amplitude of the temperature plume can be retrieved, with uncertainty quantification, during a push-pull experiment using surface ERT. We analyze the robustness of the solution using a synthetic benchmark. The results indicate that the median of the posterior is very close to the true temperature distribution. The relative error increases at the edge of the temperature plume where the change of temperature is limited. This is related to the limited resolution of geophysics and the process of dimension reduction. We also investigate how discrete cosine transform can improve the dimension reduction process without altering the final prediction. Finally, we show that BEL is able to retrieve the spatio-temporal variability of the plume, while the smoothness constraint inversion fails to accurately image the corresponding contrast, largely underestimating the amplitude of the temperature change. BEL is therefore a well-suited framework for the interpretation of 4D geophysical data avoiding the drawbacks of standard deterministic solutions. Hermans, T., Oware, E., & Caers, J. (2016). Direct prediction of spatially and temporally varying physical properties from time-lapse electrical resistance data. Water Resources Research, 52, 7262-7283.

HDO and the D/H ratio are essential to understand Mars past and present climate, in particular with regard to the evolution through ages of the Martian water cycle. We present here new modeling developments of the HDO cycle with the LMD Mars GCM. The present study aims at exploring the behaviour of the D/H ratio cycle and its sensitivity to the modeling of water ice clouds and the formulation of the fractionation by condensation. Our GCM simulations are compared with observations provided by the Atmospheric Chemistry Suite (ACS) on board the ESA/Roscosmos Trace Gas Orbiter, and reveal that the model quite well reproduces the temperature and water vapor fields, which offers a good basis for representing the D/H ratio cycle. The comparison also emphasizes the importance of modelling the effect of supersaturation, resulting from the microphysical processes of water ice clouds, to correctly account for the water vapor and the D/H ratio of the middle-to-upper atmosphere. This work comes jointly with a detailed comparison of the measured D/H profiles by TGO/ACS and the model outputs, conducted in the companion paper of Rossi et al. 2022 (this issue).

A document by Amina Khatun. Click on the document to view its contents.

We examined the effect of snow-ice formation on SnowModel-LG snow depth and density products. We coupled SnowModel-LG, a modeling system adapted for snow depth and density reconstruction over sea ice, with HIGHTSI, a 1-D thermodynamic sea ice model, to create SnowModel-LG_HS. Pan-Arctic model simulations spanned from 1 August 1980 through 31 July 2022. In SnowModel-LG_HS, domain average snow depth decreased by 20%, and snow density increased by 2% when compared to SnowModel-LG, with largest differences in the Atlantic sector. Averaged across the CryoSat-2 era (2011–2022), domain average April sea ice thickness retrievals from CryoSat-2 decreased by 7.7% when snow-ice was accounted for. Evaluation of SnowModel-LG HS against snow depth, snow-ice, and sea ice thickness observations highlighted the importance of snow redistribution over deformed sea ice. The findings suggest that neglecting snow and sea ice interactions in models can lead to substantial overestimation of snow depth over level ice.

The C isotopic composition in macroalgae (δ13C) is highly variable and its prediction is very complex relative to terrestrial plants. To contribute to the knowledge on the variations and determinants of δ13C-macroalgal, we analyzed a large stock of specimens varying in taxa and morphology and inhabiting shallow marine habitats from the Gulf of California Ecoregion featured by distinctive environmental conditions. A large δ13C variability (-34.61‰ to -2.19‰) was observed, mostly explained on the life form (taxonomy, morphology and structural organization), and modulated by the interaction between habitat features and environmental conditions. The intertidal zone specimens had less negative d13C values than in subtidal zone. Except pH, environmental conditions of the seawater do not contribute to the δ13C variability. Specimens of the same taxa showed δ13C similar patterns, to increase or decrease, with latitude (21º-30°N). d13C-macroalgal provides information on the inorganic carbon source used for photosynthesis (CO2 diffusive entry vs HCO3- active uptake). Most species showed a δ13C belong into a range that indicates a mix of CO2 and HCO3- uptake; the HCO3- uptake by active transport is widespread among GCE macroalgae. About 20-34% species depending on cutoff limits for CCM presence showed at least one specimen with δ13C>-10‰, suggesting that potentially could have highly efficient CCM. Ochrophyta presented a high number of species with d13C>-10‰, suggesting widespread HCO3- use by non-diffusive mechanisms. Few species belonging to Rhodophyta relied on CO2 diffusive entry (d13C<-30‰) exclusively. δ13C provides useful information about the physiological and environmental status of macroalgae.

Fast solar wind streams are known to be dominated by Alfvenic turbulence, i.e. large amplitude magnetic field and quasi-incompressible velocity fluctuations with a correlation corresponding to waves propagating away from the Sun. At the same time the Ulysses spacecraft showed That microstreams, persistent long period (1/2-2 days) fluctuations in the radial velocity field, are ubiquitous in the fast wind. This contribution explores the possible causal relation between microstreams and Alfvenic turbulence. We carry out a parametric study of the stability of the microstream jets to Kelvin-Helmholtz (KH) instabilities: starting from the profiles of density, radial speed and magnetic field observed in the solar wind, we investigate both at what distance from the Sun KH instabilities may be triggered and the ensuing nonlinear dynamics.

Multispectral mapping data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provide a unique opportunity to characterize south polar ice deposits at higher spectral sampling, spatial resolution, or spatiotemporal coverage than previous work. This new perspective can help to constrain the nature and distribution of different mixtures of CO2 ice, H2O ice, and dust that influence the formation, evolution, and preservation of Mars climate records. We processed 1103 CRISM observations spanning southern summer of six Mars Years (MY) through a combination of k-means clustering and random forest classification. Using a set of 12 spectral endmembers directly tied to previous work with high-resolution CRISM targeted data, we made a series of temporally restricted mosaics showing surface spectral variation over time. The mosaics show the effects of the MY 28 dust storm on the removal of the seasonal CO2 ice cap that year and reveal how this process differed from the years that followed. A mosaic showing residual ice surfaces displays broad agreement with previous compositional maps while resolving new details in the distribution of H2O ice-rich material around the periphery of the bright CO2 ice cap. By showing how surface composition varies across a broad swath of the south polar region though time, the endmember set and classified mosaics produced in this work can provide critical context for future studies of the dynamic processes that shape south polar ice deposits.

Understanding rock mechanical behavior, especially the onset and nature of yield (i.e. permanent deformation), is critical to ensure safe and sustainable operations in many geological engineering applications, including ‘low-carbon’ subsurface technologies to aid decarbonization. In porous sandstones, yield corresponds to onset of either permanent dilatation or compaction accompanied by microcracking and is defined by a ‘capped’ yield surface in differential stress vs effective mean stress (Q/P) space. Previous studies showed that compactive yield in porous sandstones corresponds to the onset of grain fragmentation and pore collapse, manifested by the deviation of the porosity reduction curve from the hydrostat. However, determining the onset of yield can be ambiguous. Here, we investigate the micromechanical basis for the compactive yield behavior of porous (25%) Hollington sandstone, which is comparable to common aquifers, hydrocarbon and geothermal reservoir rocks and other sandstone formations with potentials for underground storage of fluids (e.g. carbon dioxide and hydrogen). A suite of conventional triaxial compression experiments with concomitant pore volumometry were performed to characterize the mechanical behavior of the rock. Effective mean stress vs porosity reduction data show a slow but near-linear initial deviation from the hydrostat followed by a sharp increase in the rate of compaction for most samples that underwent inelastic porosity reduction below 243 MPa effective mean stress (P*). Synthesis of mechanical with microstructural data suggests that the initial deviation from the hydrostat is related to the collapse of local large pores while the sharp increase in the rate of compaction corresponds to the onset of grain fragmentation leading to widespread pore collapse. Plotting yield stresses in Q/P space reveal a near linear cap of negative slope, albeit with considerable scatter, for stresses related to the collapse of local large pores, evolving into an elliptical cap for stresses approximately corresponding to the onset of widespread grain fragmentation. The results highlight the enhancing influence of non-hydrostatic stresses acting around large pores on the compactive yield in rocks with porosity heterogeneities.

Useful to Usable (U2U) was a 6-year USDA-funded research and extension project focused on improving the uptake of climate information by Midwestern U.S. farmers and agricultural advisors. Led by Purdue University, this interdisciplinary team from nine Midwestern universities developed five web-based decision support tools to examine production, financial, and environmental outcomes of different climate scenarios and management options. A dedicated team of Extension educators, marketing specialists, and program evaluators worked together to promote U2U products and collect, analyze, and communicate data to 1) help increase project impact and 2) to measure outcomes for accountability purposes. Since outreach began in July 2013, farmers and advisors have been reached at 165 outreach events and training sessions in ten Midwestern states and at least 6 regional webinars have been conducted. A four-round mailed and electronic marketing campaign reached an estimated 35,600 people from March 2015 – November 2016. Additionally, the team developed a variety of educational materials (user guides, fact sheets, presentations, etc.) to support U2U outreach and dissemination efforts. Throughout 2016-2017, the team evaluated the outcomes, impacts, and overall reach of the U2U project over the 6-year project duration. They conducted two large-scale surveys with farmers and agricultural advisors, conducted personal interviews with advisors in Iowa and Nebraska, gathered informal success stories from U2U team members and collaborators, and tracked website traffic using Google Analytics. This presentation will highlight the project’s evaluation design, results, and lessons learned, including evaluation of outreach and dissemination approaches and longer-term outcome/impact evaluation. Some key metrics include the likelihood of using U2U online tools, actual use of tools, use of tools to aid financial and environmental decisions, and willingness to consider climate information in the future (not limited to U2U tools).

River-influenced areas are very important coastal ecosystems, due to their influence on nutrients and the structure of planktonic and benthic communities. Many studies have focused on the interaction between river runoff, wind and river plume characteristics, by means of observations and modeling. This study aimed to improve our understanding about the circulation and seasonal pattern of river plumes in Central Chile, using the Regional Ocean Modeling System (ROMS). Results were in reasonable agreement with observations. The plumes exhibit a minimal area during summer-fall, with a northwest orientation caused by southwesterly winds and lower river discharges. A larger plume area is developed during June-September, as result of higher winter precipitations. The orientation of the plumes during winter is westward, driven by higher river discharge and wind from the northwest. An interesting feature reproduced by the model was the trend to coalesce as observed in satellite imagery.

Because of geographical condition such as precipitous terrains and steep rivers, meteorological conditions such as typhoons and torrential rains, and social condition, Japan is subject to frequent natural disasters such as flood and landslide. As a result, there is a great loss of people's lives and property due to natural disasters. In reality, there has been severe damage caused by various disaster in the past, including 1947 Typhoon Kathleen, 1959 Typhoon Vera also known Isewan Typhoon, and 2018 torrential rain. Especially, Landslides and flooding caused more than 200 deaths by torrential rain in 2018. This study introduces disaster management about middle size city in Japan. In non-structural disaster measures, one of the most important disaster management measures is hazard map. It shows not only flood and land slide hazard area but also evacuation shelter information and it can help the people to evacuate the flood and land slide disaster. In addition, information on evacuation methods, past disasters, and information collection way is also shown. And also, estimate the number of evacuees is very important, too. For the analysis, the population, the information of building land slide information and the simulation result of estimating the flood inundation area, depth, continued flooding times, overflow, bank erosion are required. Not only horizontal evacuation but also vertical evacuation is important. As a result of the estimate the number of evacuees, vacancy rate of shelters are calculated. It can help the flood evacuation plan.