Greenhouse gas observation network design for Africa

An optimal network design was carried out to prioritise the installation or refurbishment of greenhouse gas (GHG) monitoring stations around Africa. The network was optimised to reduce the uncertainty in emissions across three of the most important GHGs: CO2, CH4, and N2O. Optimal networks were derived using incremental optimisation of the percentage uncertainty reduction achieved by a Gaussian Bayesian atmospheric inversion. The solution for CO2 was driven by seasonality in net primary productivity. The solution for N2O was driven by activity in a small number of soil flux hotspots. The optimal solution for CH4 was consistent over different seasons. All solutions for CO2 and N2O placed sites in central Africa at places such as Kisangani, Kinshasa and Bunia (Democratic Republic of Congo), Dundo and Lubango (Angola), Zoétélé (Cameroon), Am Timan (Chad), and En Nahud (Sudan). Many of these sites appeared in the CH4 solutions, but with a few sites in southern Africa as well, such as Amersfoort (South Africa). The multi-species optimal network design solutions tended to have sites more evenly spread-out, but concentrated the placement of new tall-tower stations in Africa between 10ºN and 25ºS. The uncertainty reduction achieved by the multi-species network of twelve stations reached 47.8% for CO2, 34.3% for CH4, and 32.5% for N2O. The gains in uncertainty reduction diminished as stations were added to the solution, with an expected maximum of less than 60%. A reduction in the absolute uncertainty in African GHG emissions requires these additional measurement stations, as well as additional constraint from an integrated GHG observatory and a reduction in uncertainty in the prior biogenic fluxes in tropical Africa

Volcanic Flank Collapse, Secondary Sediment Failure and Flow‐Transition:Multi‐Stage Landslide Emplacement Offshore Montserrat, Lesser Antilles

Volcanic flank collapses, especially those in island settings, have generated some of the most voluminous mass transport deposits on Earth and can trigger devastating tsunamis. Reliable tsunami hazard assessments for flank collapse‐driven tsunamis require an understanding of the complex emplacement processes involved. The seafloor sequence southeast of Montserrat (Lesser Antilles) is a key site for the study of volcanic flank collapse emplacement processes that span subaerial to submarine environments. Here, we present new 2D and 3D seismic data as well as MeBo drill core data from one of the most extensive mass transport deposits offshore Montserrat, which exemplifies multi‐phase landslide deposition from volcanic islands. The deposits reveal emplacement in multiple stages including two blocky volcanic debris avalanches, secondary seafloor failure and a late‐stage erosive density current that carved channel‐like incisions into the hummocky surface of the deposit about 15 km from the source region. The highly erosive density current potentially originated from downslope‐acceleration of fine‐grained material that was suspended in the water column earlier during the slide. Late‐stage erosive turbidity currents may be a more common process following volcanic sector collapse than has been previously recognized, exerting a potentially important control on the observed deposit morphology as well as on the runout and the overall shape of the deposit

From gradual spreading to catastrophic collapse - Reconstruction of the 1888 Ritter Island volcanic sector collapse from high-resolution 3D seismic data

Volcanic island flank collapses have the potential to trigger devastating tsunamis threatening coastal communities and infrastructure. The 1888 sector collapse of Ritter Island, Papua New Guinea (in the following called Ritter) is the most voluminous volcanic island flank collapse in historic times. The associated tsunami had run-up heights of more than 20 m on the neighboring islands and reached settlements 600 km away from its source. This event provides an opportunity to advance our understanding of volcanic landslide-tsunami hazards. Here, we present a detailed reconstruction of the 1888 Ritter sector collapse based on high-resolution 2D and 3D seismic and bathymetric data covering the failed volcanic edifice and the associated mass-movement deposits. The 3D seismic data reveal that the catastrophic collapse of Ritter occurred in two phases: (1) Ritter was first affected by deep-seated, gradual spreading over a long time period, which is manifest in pronounced compressional deformation within the volcanic edifice and the adjacent seafloor sediments. A scoria cone at the foot of Ritter acted as a buttress, influencing the displacement and deformation of the western flank of the volcano and causing shearing within the volcanic edifice. (2) During the final, catastrophic phase of the collapse, about 2.4 km³ of Ritter disintegrated almost entirely and travelled as a highly energetic mass flow, which incised the underlying sediment. The irregular topography west of Ritter is a product of both compressional deformation and erosion. A crater-like depression underlying the recent volcanic cone and eyewitness accounts suggest that an explosion may have accompanied the catastrophic collapse. Our findings demonstrate that volcanic sector collapses may transform from slow gravitational deformation to catastrophic collapse. Understanding the processes involved in such a transformation is crucial for assessing the hazard potential of other volcanoes with slowly deforming flanks such as Mt. Etna or Kilauea

A novel computer adaptive word list memory test optimized for remote assessment: Psychometric properties and associations with neurodegenerative biomarkers in older women without dementia

Introduction: This study established the psychometric properties and preliminary validity of the Stricker Learning Span (SLS), a novel computer adaptive word list memory test designed for remote assessment and optimized for smartphone use. Methods: Women enrolled in the Mayo Clinic Specialized Center of Research Excellence (SCORE) were recruited via e-mail or phone to complete two remote cognitive testing sessions. Convergent validity was assessed through correlation with previously administered in-person neuropsychological tests (n = 96, ages 55-79) and criterion validity through associations with magnetic resonance imaging measures of neurodegeneration sensitive to Alzheimer\u27s disease (n = 47). Results: SLS performance significantly correlated with the Auditory Verbal Learning Test and measures of neurodegeneration (temporal meta-regions of interest and entorhinal cortical thickness, adjusting for age and education). Test-retest reliabilities across two sessions were 0.71-0.76 (two-way mixed intraclass correlation coefficients). Discussion: The SLS is a valid and reliable self-administered memory test that shows promise for remote assessment of aging and neurodegenerative disorders

Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations

We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006-2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions.The inverse models infer total CH4 emissions of 26.8 (20.2-29.7) TgCH(4) yr(-1) (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006-2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 TgCH(4) yr(-1) (2006) to 18.8 TgCH(4) yr(-1) (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3-8.2) TgCH(4) yr(-1) from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain.Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between -40 and 20% at the aircraft profile sites in France, Hungary and Poland.</p