Changing the direction of environmental investment in Australia: Learnings from implementing INFFER

Investment in natural resource management (NRM) by regional organisations in Australia has been widely criticised for failing to achieve substantial environmental outcomes. The Investment Framework for Environmental Resources (INFFER) is a tool for developing and prioritising projects to address environmental issues such as water quality, biodiversity decline, environmental pest impacts and land degradation. INFFER is an asset-based, targeted, and outcome-focussed approach to environmental investment, and as such is a very different and more rigorous approach to prioritising possible environmental projects than used previously by most catchment management organisations (CMOs) in Australia. From 2008 to 2010 INFFER has been trialled with CMOs. Evaluation and benchmarking data obtained at 2-day INFFER training sessions with seven CMOs in three eastern Australia states are reported. Before commencing to use INFFER, CMO staff are generally confident about the current decision-making processes for environmental investment used within their organisation. In some cases, this initial perception challenges their acceptance of a new approach to investment decisionmaking. Key issues when implementing INFFER include concerns about changing the direction of CMO investment, concerns about compatibility with funder requirements, and various issues associated with specific aspects of the Framework. Perceived complexity of INFFER, existing institutional arrangements, and the legacy of past institutional arrangements remain serious barriers to the adoption of methods to improve environmental outcomes from NRM investment. Despite these difficulties INFFER is being used by a number of CMOs. However, it is likely that widespread adoption of INFFER, or indeed any other transparent and robust process, will only occur with greater requirement from governments for environmental decision making by regional NRM bodies that is more focused on outcomes and cost-effectiveness.NRM investment planning, NRM investment prioritisation, regional catchment management organisations, NRM policy, environmental planning, environmental prioritisation, environmental policy, Environmental Economics and Policy, Research and Development/Tech Change/Emerging Technologies, Q50, Q58,

Nano-sized Mo- and Nb-doped TiO2 as anode materials for high energy and high power hybrid Li-ion capacitors

Nano-sized Mo-doped titania (Mo0.1Ti0.9O2) and Nb-doped titania (Nb0.25Ti0.75O2) were directly synthesized via a continuous hydrothermal flow synthesis process. Materials characterization was conducted using physical techniques such as transmission electron microscopy, powder x-ray diffraction, x-ray photoelectron spectroscopy, Brunauer–Emmett–Teller specific surface area measurements and energy dispersive x-ray spectroscopy. Hybrid Li-ion supercapacitors were made with either a Mo-doped or Nb-doped TiO2 negative electrode material and an activated carbon (AC) positive electrode. Cells were evaluated using electrochemical testing (cyclic voltammetry, constant charge discharge cycling). The hybrid Li-ion capacitors showed good energy densities at moderate power densities. When cycled in the potential window 0.5–3.0 V, the Mo0.1Ti0.9O2/AC hybrid supercapacitor showed the highest energy densities of 51 Wh kg−1 at a power of 180 W kg−1 with energy densities rapidly declining with increasing applied specific current. In comparison, the Nb0.25Ti0.75O2/AC hybrid supercapacitor maintained its energy density of 45 Wh kg−1 at 180 W kg−1 better, showing 36 Wh g−1 at 3200 W kg−1, which is a very promising mix of high energy and power densities. Reducing the voltage window to the range 1.0–3.0 V led to an increase in power density, with the Mo0.1Ti0.9O2/AC hybrid supercapacitor giving energy densities of 12 Wh kg−1 and 2.5 Wh kg−1 at power densities of 6700 W kg−1 and 14 000 W kg−1, respectively

A Bayesian Neural Network Approach for Tropospheric Temperature Retrievals from a Lidar Instrument

We have constructed a Bayesian neural network able of retrieving tropospheric temperature profiles from rotational Raman-scatter measurements of nitrogen and oxygen and applied it to measurements taken by the RAman Lidar for Meteorological Observations (RALMO) in Payerne, Switzerland. We give a detailed description of using a Bayesian method to retrieve temperature profiles including estimates of the uncertainty due to the network weights and the statistical uncertainty of the measurements. We trained our model using lidar measurements under different atmospheric conditions, and we tested our model using measurements not used for training the network. The computed temperature profiles extend over the altitude range of 0.7 km to 6 km. The mean bias estimate of our temperatures relative to the MeteoSwiss standard processing algorithm does not exceed 0.05 K at altitudes below 4.5 km, and does not exceed 0.08 K in an altitude range of 4.5 km to 6 km. This agreement shows that the neural network estimated temperature profiles are in excellent agreement with the standard algorithm. The method is robust and is able to estimate the temperature profiles with high accuracy for both clear and cloudy conditions. Moreover, the trained model can provide the statistical and model uncertainties of the estimated temperature profiles. Thus, the present study is a proof of concept that the trained NNs are able to generate temperature profiles along with a full-budget uncertainty. We present case studies showcasing the Bayesian neural network estimations for day and night measurements, as well as in clear and cloudy conditions. We have concluded that the proposed Bayesian neural network is an appropriate method for the statistical retrieval of temperature profiles

Clostridium difficile: a healthcare associated infection of unknown significance in adults in sub-Saharan Africa

Background: Clostridium difficile infection (CDI) causes a high burden of disease in high-resource healthcare systems, with significant morbidity, mortality and financial implications. CDI is a healthcare-associated infection for which the primary risk factor is antibiotic usage and it is the leading cause of bacterial diarrhoea in HIV infected patients in USA. Little is known about the disease burden of CDI in sub-Saharan Africa, where HIV and healthcare associated infection have a higher prevalence and antibiotic usage is less restricted. Aim: To review published literature on CDI in sub-Saharan Africa, highlighting areas for future research. Methods: English language publications since 1995 were identified from online databases (PubMed, Medline, Google Scholar, SCOPUS) and personal collections of articles, using combinations of keywords to include C. difficile, Africa and HIV. Results: Ten relevant studies were identified. There is considerable variation in methodology to assess for carriage of toxigenic C. difficile and its associations. Eight studies report carriage of toxigenic C. difficile. Three (of four) studies found an association with antibiotic usage. One (of four) studies showed an association with HIV infection. One study showed no association with degree of immunosuppression in HIV. Two (of three) studies showed an association between carriage of toxigenic C. difficile and diarrhoeal illness. Conclusion: Whilst the carriage of toxigenic C. difficile is well described in sub-Saharan Africa, the impact of CDI in the Region remains poorly l understood and warrants high quality research

Extratropical transition of tropical cyclones in a multiresolution ensemble of atmosphere-only and fully coupled global Climate Models

Tropical cyclones undergo extratropical transition (ET) in every ocean basin. Projected changes in ET frequency under climate change are uncertain and differ between basins, so multimodel studies are required to establish confidence. We used a feature-tracking algorithm to identify tropical cyclones and performed cyclone phase-space analysis to identify ET in an ensemble of atmosphere-only and fully coupled global model simulations, run at various resolutions under historical (1950–2014) and future (2015–50) forcing. Historical simulations were evaluated against five reanalyses for 1979–2018. Considering ET globally, ensemble-mean biases in track and genesis densities are reduced in the North Atlantic and western North Pacific when horizontal resolution is increased from ∼100 to ∼25 km. At high resolution, multi-reanalysis-mean climatological ET frequencies across most ocean basins as well as basins’ seasonal cycles are reproduced better than in low-resolution models. Skill in simulating historical ET interannual variability in the North Atlantic and western North Pacific is ∼0.3, which is lower than for all tropical cyclones. Models project an increase in ET frequency in the North Atlantic and a decrease in the western North Pacific. We explain these opposing responses by secular change in ET seasonality and an increase in lower-tropospheric, pre-ET warm-core strength, both of which are largely unique to the North Atlantic. Multimodel consensus about climate change responses is clearer for frequency metrics than for intensity metrics. These results help clarify the role of model resolution in simulating ET and help quantify uncertainty surrounding ET in a warming climate.All authors received financial support from the PRIMAVERA project (European Commission Horizon2020 Grant Agreement 641727) with data access via JASMIN (https://jasmin.ac.uk) supported by IS-ENES3 (Grant Agreement 824084). AJB also received support from National Environmental Research Council (NERC) national capability grant for the North Atlantic Climate System: Integrated study (ACSIS) program (Grants NE/N018001/1, NE/N018044/1, NE/N018028/1, and NE/N018052/1). KL received funding from the German Federal Ministry of Education and Research (BMBF) through JPI Climate/JPI Oceans NextG-Climate Science-ROADMAP (FKZ: 01LP2002A). The authors are grateful to the editor and to three anonymous reviewers, whose recommendations improved this paper. AJB, PLV, RJH, and MJR conceived the study. Simulations were performed by MJR, ET, KL, CDR, and LT. Output data were managed by JS. MJR performed the cyclone tracking. BV computed the Eady growth rate. AJB undertook cyclone phase-space analysis and all other data analyses, figure preparation, and wrote the manuscript. All authors provided input in interpreting results and approved the final manuscript. The authors declare no competing interests.Peer Reviewed"Article signat per 13 autors/es: Alexander J. Baker, Malcolm J. Roberts, Pier Luigi Vidale, Kevin I. Hodges, Jon Seddon, Benoît Vannière, Rein J. Haarsma, Reinhard Schiemann, Dimitris Kapetanakis, Etienne Tourigny, Katja Lohmann, Christopher D. Roberts, and Laurent Terray"Postprint (published version

Uncovering the natural variability of araucariacean exudates from ex situ and in situ tree populations in New Caledonia using FTIR spectroscopy

Background Understanding the natural variability of plant resins is crucial for evaluating the chemical information stored in ambers that may support inferring palaeoenvironmental conditions. However, even among extant resin-producing plants, the variation of resinous exudates within and between tree genera and species is still poorly understood. Methods We analysed plant exudates from across the Araucariaceae in New Caledonia using Fourier-transform infrared spectroscopy in attenuated total reflection mode (FTIR-ATR). Both, wild (in situ) and arboretum grown (ex situ) populations were used to uncover the effects of intergeneric, inter- and intraspecific variation of the araucariacean plants on the resin chemistry. Results We show that even resins from the same species in the same habitat do have natural (intraspecific) chemical variation. Some of the variation can result from the degree of resin polymerisation, but this is not the only source of variation. Wild sourced resins have greater natural intraspecific chemical variation than the arboretum sourced ones. Interspecific and intergeneric differences were not easy to distinguish in the resins sampled. This has strong implications for the evaluation of the chemical information from worldwide ambers: multiple samples should be analysed to give a more accurate picture of the natural chemical variation present and how this may or may not overlap with the chemistries of other resin types. Additionally we discovered that the Araucariacean species can produce up to three distinct types of exudate (gum, resin, and gum resin). This is the first time that gum resins have been identified and characterized with FTIR-ATR. We also provide a guide on how to distinguish the exudate types when using FTIR-ATR.Peer reviewe

Imaging of crystalline and amorphous surface regions using time-of-flight secondary-ion mass spectrometry (ToF-SIMS): application to pharmaceutical materials

The structure of a material, in particular the extremes of crystalline and amorphous forms, significantly impacts material performance in numerous sectors such as semiconductors, energy storage, and pharmaceutical products, which are investigated in this paper. To characterize the spatial distribution for crystalline−amorphous forms at the uppermost molecular surface layer, we performed time-of-flight secondary-ion mass spectroscopy (ToF-SIMS) measurements for quench-cooled amorphous and recrystallized samples of the drugs indomethacin, felodipine, and acetaminophen. Polarized light microscopy was used to localize crystallinity induced in the samples under controlled conditions. Principal component analysis was used to identify the subtle changes in the ToF-SIMS spectra indicative of the amorphous and crystalline forms for each drug. The indicators of amorphous and crystalline surfaces were common in type across the three drugs, and could be explained in general terms of crystal packing and intermolecular bonding, leading to intramolecular chain scission in the formation of secondary ions. Less intramolecular scission occurred in the amorphous form, resulting in a greater intensity of molecular and dimer secondary ions. To test the generality of amorphous−crystalline differentiation using ToF-SIMS, a different recrystallization method was investigated where acetaminophen single crystals were recrystallized from supersaturated solutions. The findings indicated that the ability to assign the crystalline/amorphous state of the sample using ToF-SIMS was insensitive to the recrystallization method. This demonstrates ToF-SIMS capabilities of detecting and mapping ordered crystalline and disordered amorphous molecular materials forms at micron spatial resolution in the uppermost surface of a material