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Green synthesis of gold nanoparticles (AuNPs) using microorganisms has been generally studied aiming for high-yield production and morphologies appropriated for various applications, such as bioremediation, (bio)sensors, and (bio)catalysis. Numerous approaches showed the individual effect of factors influencing the synthesis of AuNPs with limited analysis of the governing factors enhancing the production and desired quality of the precipitates. This study proposes a fractional-factorial design to investigate the simultaneous influence of seven environmental factors (cell concentration, temperature, anoxic/oxic conditions, pH, gold concentration, electron donor type, and bacterial species) on the recovery yield and synthesis of targeted AuNPs. Various sizes and morphologies of the AuNPs were obtained by varying the environmental factors studied. The factors with significant effects (i.e., 0.2 mM Au and pH 5) were selected according to statistical analysis for optimal removal of 88.2 ± 3.5% of gold and with the production of valuable 50 nm AuNPs, which are known for their enhanced sensitivity. Implications of the cytochrome-C on the bacterial mechanisms and the provision of electron donors via an electrochemical system are further discussed. This study helps develop gold recovery and nanoparticle synthesis methods, focusing on the determining factor(s) for efficient, low-cost, green synthesis of valuable materials.

Negotiated solutions among contrasting land use interests in the nexus of water, energy, food and ecosystems require cooperation between actors with different viewpoints and backgrounds. We suggest aerial imagery and videos, captured by drones, to be "boundary objects ", easily interpretable landscape representations that might create a common understanding across stakeholders through their universal interpretability. We collected drone imagery and videos from different angles of a wide range of landscapes in Zambia, showing agricultural areas, forests, wetlands and water infrastructure. Then, we took the imagery back to the field to probe the perceptions of multiple stakeholders, including staff from both governmental and non-governmental organizations, hydropower operators, small-and large-scale farmers. In focus group discussions, we assessed the interpretability of oblique images, taken at an angle by a video drone, compared to nadir (vertical) imagery from Google Earth and from a high-end mapping drone. We show that oblique images produced better identification results across all groups of stakeholders, but especially from small-scale farmers, suggesting this type of imagery is helpful to empower people who lack previous experience in interpreting nadir images. Overall, the appreciation of the aesthetic value and the perceived professional benefits of drone imagery are high, but technical and legal barriers impede a wider adoption of the technology. While we highlight ethical concerns and technical limitations, we suggest that conservationists and environmental planners could benefit from a critical use of affordable video drones so as to produce intuitive landscape representations useful for more effective multi-stakeholder collaborations. Landscape and Urban Planning, 228 ISSN:0169-2046 ISSN:1872-6062

Atmospheric mercury (Hg) observations in the lower free troposphere (LFT) can give important insights into Hg redox chemistry and can help constrain Hg background concentrations on a regional level. Relatively continuous sampling of LFT air, inaccessible to most ground-based stations, can be achieved at highaltitude observatories. However, such high-altitude observatories are rare, especially in the Southern Hemisphere (SH), and atmospheric Hg in the SH LFT is unconstrained. To fill this gap, we continuously measured gaseous elemental mercury (GEM; hourly) and reactive mercury (RM; integrated over ∼ 6-14 d) for 9 months at Maïdo mountain observatory (2160 m a.s.l.) on remote Réunion Island (21.1 • S, 55.5 • E) in the tropical Indian Ocean. GEM exhibits a marked diurnal variation characterized by a midday peak (mean: 0.95 ng m −3 ; SD: 0.08 ng m −3) and a nighttime low (mean: 0.78 ng m −3 ; SD: 0.11 ng m −3). We find that this diurnal variation is likely driven by the interplay of important GEM photo-reemission from the islands' vegetated surfaces (i.e. vegetation + soil) during daylight hours (8-22 ng m −2 h −1), boundary layer influences during the day, and predominant LFT influences at night. We estimate GEM in the LFT based on nighttime observations in particularly dry air masses and find a notable seasonal variation, with LFT GEM being lowest from December to March (mean 0.66 ng m −3 ; SD: 0.07 ng m −3) and highest from September to November (mean: 0.79 ng m −3 ; SD: 0.09 ng m −3). Such a clear GEM seasonality contrasts with the weak seasonal variation reported for the SH marine boundary layer but is in line with modeling results, highlighting the added value of continuous Hg observations in the LFT. Maïdo RM is 10.6 pg m −3 (SD: 5.9 pg m −3) on average, but RM in the cloud-free LFT might be about twice as high, International audience

Despite the wealth of existing climate forecast data, only a small part is effectively exploited for sectoral applications. A major cause of this is the lack of integrated tools that allow the translation of data into useful and skillful climate information. This barrier is addressed through the development of an R package. Climate Services Toolbox (CSTools) is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts for seasonal to multi-annual scales. The package contains process-based, state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. Due to the modular design of the toolbox in individual functions, the users can develop their own post-processing chain of functions, as shown in the use cases presented in this paper, including the analysis of an extreme wind speed event, the generation of seasonal forecasts of snow depth based on the SNOWPACK model, and the post-processing of temperature and precipitation data to be used as input in impact models. "Article signat per 19 autors/es: Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté , Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie" This research has been supported by the Horizon 2020 (S2S4E; grant no. 776787), EUCP (grant no. 776613), ERA4CS (grant no. 690462), and the Ministerio de Ciencia e Innovación (grant no. FPI PRE2019-088646). Peer Reviewed

The aim of this paper is to study the effect of strain rate on the compressive behavior of the highly cross-linked RTM6 epoxy resin used in advanced aerospace composites. Dynamic compression tests were performed using a split Hopkinson pressure bar, along with reference quasi-static compression tests, to cover a strain rate range from 0.001 to 1035 s−1. Special attention was paid to the optimization of the test methodologies in order to obtain material data free of bias related to the use of different load introduction techniques and sample geometries over the considered strain rate range. In addition, the use of full-field 3D deformation measurements allowed the validation of traditional test and material assumptions. A novel self-alignment tool was developed to enable perfect interfacial contact during compression loading. The 3D digital image correlation technique was used to measure the instantaneous deformation of the sample during compression at different strain rates. Results showed a pronounced strain rate sensitivity of the RTM6 epoxy in compression. The peak yield strength increased with increasing strain rate, while the elastic modulus and Poisson’s ratio in compression were independent of the strain rate. The barreling of the sample in compression, quantified by the barreling ratio, showed an increase during the progression of the compression tests. However, the barreling ratio significantly decreased with the increasing strain rate. Finally, it was shown that neglecting the significant volume change in the yield stages gave rise to a non-negligible underestimation of the strength of the material.

Soil maps can usefully serve in data scarce regions, for example for yield (gap) assessments using a crop simulation model. The soil property estimates’ contribution to inaccuracy and uncertainty can be functionally evaluated by comparing model results using the estimates as input against independent observations. We conducted a functional evaluation of digital maps of soil hydraulic properties of the Zambezi River Basin using a crop growth model AquaCrop. AquaCrop was run, alimented with local meteorological data, and with soil hydraulic properties derived from the digital maps of digital soil mapping (DSM) techniques, as opposed to estimations from the widely used Saxton and Rawls pedotransfer functions. The two simulated time series of canopy cover (CC) (AquaCrop-CC-DSM and AquaCrop-CC-Saxton), which were compared against canopy cover data derived from the remotely sensed Leaf Area Index (LAI) from the MODIS archive (MODIS-CC). A pairwise comparison of the time series resulted in a root mean squared error (RMSE) of 0.07 and a co-efficient of determination (R2) of 0.93 for AquaCrop-CC-DSM versus MODIS-CC, and an RMSE of 0.08 and R2 of 0.88 for AquaCrop-CC-Saxton versus MODIS-CC. In dry years, the AquaCrop-CC-DSM deviated less from the MODIS-CC than the AquaCrop-CC-Saxton (p < 0.001), although this difference was not significant in wet years. The functional evaluation showed that soil hydraulic property estimates based on digital soil mapping outperformed those based on Saxton and Rawls when used for simulating crop growth in dry years in the Zambezi River Basin. This study also shows the value of conducting a functional evaluation of estimated (static) soil hydraulic properties in terms of dynamic model output. ispartof: Land vol:11 issue:5 status: Published online