Graduate Recital:Shelly L. Monier, Flute Patricia Foltz, Piano

Kemp Recital Hall Tuesday Evening April 7, 2004 7:30p.m

Uncertainty in Future Agro-Climate Projections in the United States and Benefits of Greenhouse Gas Mitigation

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios, climate sensitivity, and natural variability. By end of century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations—although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Finally, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.This work was partially funded by the US Environmental Protection Agency’s Climate Change Division, under Cooperative Agreement #XA-83600001, by the US Department of Energy, Office of Biological and Environmental Research, under grant DE-FG02-94ER61937, and by the National Science Foundation Macrosystems Biology Program Grant #EF1137306. The Joint Program on the Science and Policy of Global Change is funded by a number of federal agencies and a consortium of 40 industrial and foundation sponsors. (For the complete list see http://globalchange.mit.edu/sponsors/current.html). This research used the Evergreen computing cluster at the Pacific Northwest National Laboratory. Evergreen is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-76RL01830

Optimization of Drinking Water and Sewer Hydraulic Management: Coupling of a Genetic Algorithm and Two Network Hydraulic Tools

AbstractVeolia has developed an optimization platform for the operation of sewer networks (POSTEVENT) and drinking water networks (OPTIM’HYDRO). This platform couples a genetic algorithm NSGA-II with hydraulic network simulation tools (INFOWORKS CS and EPANET). The challenge is to optimize the design and operation of networks according to given objectives and constraints, by changing asset control parameters. This article deals with optimization challenges raised and developed off-line support tools. It ends with a case study on a French drinking water network consisting in upscale set points for pumping stations to optimize the procurement management of water and reduce the energy costs

Chemical composition of A and F dwarfs members of the Hyades open cluster

Aims: Abundances of 15 chemical elements have been derived for 28 F and 16 A stars members of the Hyades open cluster in order to set constraints on self-consistent evolutionary models that include radiative and turbulent diffusion. Methods: A spectral synthesis, iterative procedure was applied to derive the abundances from selected high-quality lines in high-resolution, high-signal-to-noise spectra obtained with SOPHIE and AURELIE at the Observatoire de Haute Provence. Results: The abundance patterns found for A and F stars in the Hyades resemble those observed in Coma Berenices and Pleiades clusters. In graphs representing the abundances versus the effective temperature, A stars often display much more scattered abundances around their mean values than the coolest F stars do. Large star-to-star variations are detected in the Hyades A dwarfs in their abundances of C, Na, Sc, Fe, Ni, Sr, Y, and Zr, which we interpret as evidence of transport processes competing with radiative diffusion. In A and Am stars, the abundances of Cr, Ni, Sr, Y, and Zr are found to be correlated with that of Fe as in the Pleiades and in Coma Berenices. The ratios C/Fe and O/Fe are found to be anticorrelated with Fe/H as in Coma Berenices. All Am stars in the Hyades are deficient in C and O and overabundant in elements heavier than Fe but not all are deficient in Ca and/or Sc. The F stars have solar abundances for almost all elements except for Si. The overall shape of the abundance pattern of the slow rotator HD 30210 cannot be entirely reproduced by models including radiative diffusion and different amounts of turbulent diffusion. Conclusions: While part of the discrepancies between derived and predicted abundances could come from non-LTE effects, including competing processes such as rotational mixing and/or mass loss seems necessary in order to improve the agreement between the observed and predicted abundance patterns

Bench-scale studies of natural attenuation, biostimulation, and bioaugmentation for remediation of groundwater contaminated with benzene and toluene in the Piceance Basin, CO

The US EPA requires direct evidence of contaminant removal before bioremediation or natural attenuation can be used for site remediation. Microcosm studies are commonly used to provide this line of evidence; however, molecular biology tools may provide a better approach for biological forensic analysis of contaminated sites. DNA biomarker technology and laboratory scale microcosms were used to assess the feasibility of natural attenuation, biostimulation, and bioaugmentation for the remediation of a benzene and toluene (B/T) contaminated aquifer. Detection and subsequent increase of target aerobic catabolic and phylogenetic gene biomarkers corroborated aerobic B/T degradation observed in laboratory scale microcosms. Anaerobic biomarker and microcosm studies failed to produce evidence of anaerobic B/T biodegradation potential. Biostimulation (nitrate and sulfate addition) and bioaugmentation with a known anaerobic benzene degrading culture both failed to stimulate B/T removal. However, the addition of benzoate slightly stimulated the removal of benzene under anaerobic conditions. Collectively these results suggest this petroleum hydrocarbon aquifer is not strictly anaerobic and has the potential for natural attenuation processes under aerobic conditions. This research demonstrated the value of using DNA biomarkers as a tool for biological and abiotic forensic site investigations

Estimating the potential of U.S. urban infrastructure albedo enhancement as climate mitigation in the face of climate variability

The climate mitigation potential of U.S. urban infrastructure albedo enhancement is explored using multidecadal regional climate simulations. Increasing albedo from 0.2 to 0.4 results in summer daytime surface temperature decreases of 1.5°C, substantial reductions in health-related heat (50% decrease in days with danger heat advisory) and decreases in energy demand for air conditioning (15% decrease in cooling degree days) over the U.S. urban areas. No significant impact is found outside urban areas. Most regional modeling studies rely on short simulations; here, we use multidecadal simulations to extract the forced signal from the noise of climate variability. Achieving a ±0.5°C margin of error for the projected impacts of urban albedo enhancement at a 95% confidence level entails using at least 5 simulation years. Finally, single-year higher-resolution simulations, requiring the same computing power as the multidecadal coarser-resolution simulations, add little value other than confirming the overall magnitude of our estimates.This work was supported by the Concrete Sustainability Hub at MIT, with sponsorship provided by the Portland Cement Association and the RMC Research & Education Foundation, and by the US Department of Energy, Office of Biological and Environmental Research, under grant DE-FG02-94ER61937. The MIT Joint Program on the Science and Policy of Global Change is funded by a number of federal agencies and a consortium of 40 industrial and foundation sponsors. For a complete list of sponsors, see http://globalchange.mit.edu