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Disproportionation of superoxide to peroxide and O2 generates the highly reactive singlet O2, which needs to be avoided for highly reversible metal–O2 batteries.

A questionnaire survey was carried out in four European countries to gather end-user's perceptions of using plants from phytotechnologies in combustion and anaerobic digestion (AD). Nine actors of the wood energy sector from France, Germany, and Sweden, and eleven AD platform operators from France, Germany, and Austria were interviewed. Questions related to installation, input materials, performed analyses, phytostabilization, and phytoextraction were asked. Although the majority of respondents did not know phytotechnologies, results suggested that plant biomass from phytomanaged areas could be used in AD and combustion, under certain conditions. As a potential benefit, phytomanaged plants would not compete with plants grown on agricultural lands, contaminated lands being not suitable for agriculture production. Main limitations would be related to additional controls in process' inputs and end-products and installations that might generate additional costs. In most cases, the price of phytotechnologies biomass was mentioned as a driver to potentially use plants from metal-contaminated soils. Plants used in phytostabilization or phytoexclusion were thought to be less risky and, consequently, benefited from a better theoretical acceptance than those issued from phytoextraction. Results were discussed according to national regulations. One issue was related to the regulatory gap concerning the status of the plant biomass produced on contaminated land.

Centaurus A (Cen A) is the nearest radio galaxy discovered as a very-high-energy (VHE; 100 GeV–100 TeV) γ-ray source by the High Energy Stereoscopic System (H.E.S.S.). It is a faint VHE γ-ray emitter, though its VHE flux exceeds both the extrapolation from early Fermi-LAT observations as well as expectations from a (misaligned) single-zone synchrotron-self Compton (SSC) description. The latter satisfactorily reproduces the emission from Cen A at lower energies up to a few GeV. New observations with H.E.S.S., comparable in exposure time to those previously reported, were performed and eight years of Fermi-LAT data were accumulated to clarify the spectral characteristics of the γ-ray emission from the core of Cen A. The results allow us for the first time to achieve the goal of constructing a representative, contemporaneous γ-ray core spectrum of Cen A over almost five orders of magnitude in energy. Advanced analysis methods, including the template fitting method, allow detection in the VHE range of the core with a statistical significance of 12σ on the basis of 213 hours of total exposure time. The spectrum in the energy range of 250 GeV–6 TeV is compatible with a power-law function with a photon index Γ = 2.52 ± 0.13stat ± 0.20sys. An updated Fermi-LAT analysis provides evidence for spectral hardening by ΔΓ ≃ 0.4 ± 0.1 at γ-ray energies above 2.8+1.0−0.6 GeV at a level of 4.0σ. The fact that the spectrum hardens at GeV energies and extends into the VHE regime disfavour a single-zone SSC interpretation for the overall spectral energy distribution (SED) of the core and is suggestive of a new γ-ray emitting component connecting the high-energy emission above the break energy to the one observed at VHE energies. The absence of significant variability at both GeV and TeV energies does not yet allow disentanglement of the physical nature of this component, though a jet-related origin is possible and a simple two-zone SED model fit is provided to this end.

Abstract. Bookkeeping models are used to estimate land-use and land-cover change (LULCC) carbon fluxes (ELULCC). The uncertainty of bookkeeping models partly arises from data used to define response curves (usually from local data) and their representativeness for application to large regions. Here, we compare biomass recovery curves derived from a recent synthesis of secondary forest plots in Latin America by Poorter et al. (2016) with the curves used previously in bookkeeping models from Houghton (1999) and Hansis et al. (2015). We find that the two latter models overestimate the long-term (100 years) vegetation carbon density of secondary forest by about 25 %. We also use idealized LULCC scenarios combined with these three different response curves to demonstrate the importance of considering gross forest area changes instead of net forest area changes for estimating regional ELULCC. In the illustrative case of a net gain in forest area composed of a large gross loss and a large gross gain occurring during a single year, the initial gross loss has an important legacy effect on ELULCC so that the system can be a net source of CO2 to the atmosphere long after the initial forest area change. We show the existence of critical values of the ratio of gross area change over net area change (γAnetAgross), above which cumulative ELULCC is a net CO2 source rather than a sink for a given time horizon after the initial perturbation. These theoretical critical ratio values derived from simulations of a bookkeeping model are compared with observations from the 30 m resolution Landsat Thematic Mapper data of gross and net forest area change in the Amazon. This allows us to diagnose areas in which current forest gains with a large land turnover will still result in LULCC carbon emissions in 20, 50 and 100 years.

AbstractGlobal impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.