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Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

Abstract. Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).

Micro- and nanoscale patterned monolayers of plasmonic nanoparticles were fabricated by combining concepts from colloidal chemistry, self-assembly, and subtractive soft lithography. Leveraging chemical interactions between the capping ligands of pre-synthesized gold colloids and a polydimethylsiloxane stamp, we demonstrated patterning gold nanoparticles over centimeter-scale areas with a variety of micro- and nanoscale geometries, including islands, lines, and chiral structures (e.g., square spirals). By successfully achieving nanoscale manipulation over a wide range of substrates and patterns, we establish a powerful and straightforward strategy, nanoparticle chemical lift-off lithography (NP-CLL), for the economical and scalable fabrication of functional plasmonic materials with colloidal nanoparticles as building blocks, offering a transformative solution for designing next-generation plasmonic technologies.

Microbial electrochemical technologies (METs) constitute the core of a number of emerging technologies with a high potential for treating urban wastewater due to a fascinating reaction mechanism—the electron transfer between bacteria and electrodes to transform metabolism into electrical current. In the current work, we focus on the model electroactive microorganism Geobacter sulfurreducens to explore both the design of new start-up procedures and electrochemical operations. Our chemostat-grown plug and play cells, were able to reduce the start-up period by 20-fold while enhancing chemical oxygen demand (COD) removal by more than 6-fold during this period. Moreover, a filter-press based bioreactor was successfully tested for both acetate-supplemented synthetic wastewater and real urban wastewater. This proof-of-concept pre-pilot treatment included a microbial electrolysis cell (MEC) followed in time by a microbial fuel cell (MFC) to finally generate electrical current of ca. 20 A·m−2 with a power of 10 W·m−2 while removing 42 g COD day−1·m−2. The effective removal of acetate suggests a potential use of this modular technology for treating acetogenic wastewater where Geobacter sulfurreducens outcompetes other organisms.

AbstractThis paper presents the experimental plans and designs as well as examples of predictive modeling of a pilot-scale CO2 injection experiment at the Heletz site (Israel). The overall objective of the experiment is to find optimal ways to characterize CO2 -relevant in-situ medium properties, including field-scale residual and dissolution trapping, to explore ways of characterizing heterogeneity through joint analysis of different types of data, and to detect leakage. The experiment will involve two wells, an injection well and a monitoring well. Prior to the actual CO2 injection, hydraulic, thermal and tracer tests will be carried out for standard site characterization. The actual CO2 injection experiments will include (i) a single well injection-withdrawal experiment, with the main objective to estimate in-situ residual trapping and (ii) a two-well injection-withdrawal test with injection of CO2 in a dipole mode (injection of CO2 in one well with simultaneous withdrawal of water in the monitoring well), with the objective to understand the CO2 transport in heterogeneous geology as well as the associated dissolution and residual trapping. Tracers will be introduced in both experiments to further aid in detecting the development of the phase composition during CO2 transport. Geophysical monitoring will also be implemented. By means of modeling, different experimental sequences and injection/withdrawal patterns have been analyzed, as have parameter uncertainties. The objectives have been to (i) evaluate key aspects of the experimental design, (ii) to identify key parameters affecting the fate of the CO2 and (iii) to evaluate the relationships between measurable quantities and parameters of interest.

AbstractA better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.