Sensitivity of atmospheric CO2 and climate to explosive volcanic eruptions

Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric aerosol optical depth changes. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initial weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields a small additional radiative forcing that amplifies the cooling and perturbs the Earth System on longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different magnitudes of stratospheric aerosol optical depth changes and from global warming simulations show that the carbon cycle-climate sensitivity γ, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the magnitude and temporal evolution of the perturbation, and time scale of interest. On decadal time scales, modeled γ is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario.

Metabolism of sulphonated anthraquinones in rhubarb, maize and celery: the role of cytochromes P450 and peroxidases

Sulphonated anthraquinones are precursors of many synthetic dyes and pigments, recalcitrant to biodegradation, and thus contaminating many industrial effluents and rivers. In the development of a phytotreatment to remove sulphonated aromatic compounds, rhubarb (Rheum rhaponticum), a plant producing natural anthraquinones, as well as maize (Zea mays) and celery (Apium graveolens), plants not producing anthraquinones, were tested for their ability to metabolise these xenobiotics. Plants were cultivated under hydroponic conditions, with or without sulphonated anthraquinones, and were harvested at different times. Either microsomal or cytosolic fractions were prepared. The monooxygenase activity of cytochromes P450 towards several sulphonated anthraquinones was tested using a new method based on the fluorimetric detection of oxygen consumed during cytochromes P450-catalysed reactions. The activity of cytosolic peroxidases was measured by spectrophotometry, using guaiacol as a substrate. Results indicated that the activity of cytochromes P450 and peroxidases significantly increased in rhubarb plants cultivated in the presence of sulphonated anthraquinones. A higher activity of cytochromes P450 was also detected in maize and celery exposed to the pollutants. In these two plants, a peroxidase activity was also detected, but without a clear difference between the control plants and the plants exposed to the organic contaminants. This research demonstrated the existence in rhubarb, maize and celery of biochemical mechanisms involved in the metabolism and detoxification of sulphonated anthraquinones. Taken together, results confirmed that rhubarb might be the most appropriate plant for the phytotreatment of these organic pollutants.

Heuristic decomposition and LP-based scheduling in make-and-pack production

In this paper, we are concerned about the short-term scheduling of industrial make-and-pack production processes. The planning problem consists in minimizing the production makespan while meeting given end-product demands. Sequence-dependent changeover times, multi-purpose storage units with finite capacities, quarantine times, batch splitting, partial equipment connectivity, material transfer times, and a large number of operations contribute to the complexity of the problem. Known MILP formulations cover all technological constraints of such production processes, but only small problem instances can be solved in reasonable CPU times. In this paper, we develop a heuristic in order to tackle large instances. Under this heuristic, groups of batches are scheduled iteratively using a novel MILP formulation; the assignment of the batches to the groups and the scheduling sequence of the groups are determined using a priority rule. We demonstrate the applicability by means of a real-world production process.