The AVOID programme’s new simulations of the global benefits of stringent climate change mitigation

Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions

Serpentinite with and without brucite: A reaction pathway analysis of a natural serpentinite in the Josephine ophiolite, California

A partially serpentinized peridotite from the Josephine ophiolite has been studied in detail in order to characterize the chemical processes of its serpentinization. The original rock was harzburgite, and its olivine and orthopyroxene are partially replaced by veins and patches of lizardite serpentine and magnetite; brucite and talc are completely absent from the serpentinite, regardless of whether the precursor mineral was olivine or pyroxene. Petrographic and mineral-chemical data suggest at least two phases of serpentinization. Incipient serpentinization produced lizardite and magnetite veinlets, from preferential dissolution of orthopyroxene, and/or infiltration of a silica-rich fluid. No talc or brucite was produced, which suggests this serpentinization happened in a chemically open system. Later serpentinization was from a fluid closer to Fe-Mg-Si chemical equilibrium with the harzburgite, which should in theory favor formation of a brucite-bearing serpentinite. Brucite is absent from late serpentine veins, but they have some porosity which could represent former brucite that was dissolved out or was reacted out after serpentinization. Isocon modeling suggests that Si, Fe, and K were added during serpentinization and that Ca was lost; i.e., the serpentinization was not isochemical (except for H2O). Results of petrographic observations, thermodynamic modeling, and mass balance calculations were used to constrain the reactions for global serpentinization of the studied sample. These reactions indicate that water with a concentration of H2 up to two times that of deep sea vent fluids may have been produced during the serpentinization of the Josephine peridotite, which could then have been a potential host for significant biomass

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less tim