Transportation Energy Pathways LDRD.

This report presents a system dynamics based model of the supply-demand interactions between the USlight-duty vehicle (LDV) fleet, its fuels, and the corresponding primary energy sources through the year2050. An important capability of our model is the ability to conduct parametric analyses. Others have reliedupon scenario-based analysis, where one discrete set of values is assigned to the input variables and used togenerate one possible realization of the future. While these scenarios can be illustrative of dominant trendsand tradeoffs under certain circumstances, changes in input values or assumptions can have a significantimpact on results, especially when output metrics are associated with projections far into the future. Thistype of uncertainty can be addressed by using a parametric study to examine a range of values for the inputvariables, offering a richer source of data to an analyst.The parametric analysis featured here focuses on a trade space exploration, with emphasis on factors thatinfluence the adoption rates of electric vehicles (EVs), the reduction of GHG emissions, and the reduction ofpetroleum consumption within the US LDV fleet. The underlying model emphasizes competition between13 different types of powertrains, including conventional internal combustion engine (ICE) vehicles, flex-fuel vehicles (FFVs), conventional hybrids(HEVs), plug-in hybrids (PHEVs), and battery electric vehicles(BEVs).We find that many factors contribute to the adoption rates of EVs. These include the pace of technologicaldevelopment for the electric powertrain, battery performance, as well as the efficiency improvements inconventional vehicles. Policy initiatives can also have a dramatic impact on the degree of EV adoption. Theconsumer effective payback period, in particular, can significantly increase the market penetration rates ifextended towards the vehicle lifetime.Widespread EV adoption can have noticeable impact on petroleum consumption and greenhouse gas(GHG) emission by the LDV fleet. However, EVs alone cannot drive compliance with the most aggressiveGHG emission reduction targets, even as the current electricity source mix shifts away from coal and towardsnatural gas. Since ICEs will comprise the majority of the LDV fleet for up to forty years, conventional vehicleefficiency improvements have the greatest potential for reductions in LDV GHG emissions over this time.These findings seem robust even if global oil prices rise to two to three times current projections. Thus,investment in improving the internal combustion engine might be the cheapest, lowest risk avenue towardsmeeting ambitious GHG emission and petroleum consumption reduction targets out to 2050.3 AcknowledgmentThe authors would like to thank Dr. Andrew Lutz, Dr. Benjamin Wu, Prof. Joan Ogden and Dr. ChristopherYang for their suggestions over the course of this project. This work was funded by the Laboratory DirectedResearch and Development program at Sandia National Laboratories.

Beyond Implications and Applications: the Story of ‘Safety by Design’

Using long-term anthropological observations at the Center for Biological and Environmental Nanotechnology in Houston, Texas, the article demonstrates in detail the creation of new objects, new venues and new modes of veridiction which have reoriented the disciplines of materials chemistry and nanotoxicology. Beginning with the confusion surrounding the meaning of ‘implications’ and ‘applications’ the article explores the creation of new venues (CBEN and its offshoot the International Council on Nanotechnology); it then demonstrates how the demands for a responsible, safe or ethical science were translated into new research and experiment in and through these venues. Finally it shows how ‘safety by design’ emerged as a way to go beyond implications and applications, even as it introduced a whole new array of controversies concerning its viability, validity and legitimacy

Estrogen and progesterone induce persistent increases in p53-dependent apoptosis and suppress mammary tumors in BALB/c-Trp53+/- mice

Introduction Treatment with estrogen and progesterone (E+P) mimics the protective effect of parity on mammary tumors in rodents and depends upon the activity of p53. The following experiments tested whether exogenous E+P primes p53 to be more responsive to DNA damage and whether these pathways confer resistance to mammary tumors in a mouse model of Li-Fraumeni syndrome. Methods Mice that differ in p53 status (Trp53+/+, Trp53+/-, Trp53-/-) were treated with E+P for 14 days and then were tested for p53-dependent responses to ionizing radiation. Responses were also examined in parous and age-matched virgins. The effects of hormonal exposures on tumor incidence were examined in BALB/c-Trp53+/- mammary tissues. Results Nuclear accumulation of p53 and apoptotic responses were increased similarly in the mammary epithelium from E+P-treated and parous mice compared with placebo and age-matched virgins. This effect was sustained for at least 7 weeks after E+P treatment and did not depend on the continued presence of ovarian hormones. Hormone stimulation also enhanced apoptotic responses to ionizing radiation in BALB/c-Trp53+/- mice but these responses were intermediate compared with Trp53+/+ and Trp-/- tissues, indicating haploinsufficiency. The appearance of spontaneous mammary tumors was delayed by parity in BALB/c-Trp53+/- mice. The majority of tumors lacked estrogen receptor (ER), but ER+ tumors were observed in both nulliparous and parous mice. However, apoptotic responses to ionizing radiation and tumor incidence did not differ among outgrowths of epithelial transplants from E+P-treated donors and nulliparous donors

Pregnancy in the mature adult mouse does not alter the proportion of mammary epithelial stem/progenitor cells

Introduction In humans, an early full-term pregnancy reduces lifetime breast cancer risk by up to 50% whereas a later pregnancy (>35 years old) can increase lifetime risk. Several mechanisms have been suggested, including changes in levels of circulating hormones, changes in the way the breast responds to these hormones, changes in gene expression programmes which may alter susceptibility to transformation and changes to mammary stem cell numbers or behaviour. Previous studies have shown that the mammary tissue isolated from both virgin and parous mice has the ability to repopulate a cleared mammary fat pad in transplant experiments. Limited dilution transplant assays have demonstrated that early pregnancy (at 5 weeks of age) reduces stem/progenitor cell numbers in the mouse mammary epithelium by twofold. However, the effects on stem/progenitor cell numbers in the mammary epithelium of a pregnancy in older animals have not yet been tested. Methods Mice were put through a full-term pregnancy at 9 weeks of age, when the mammary epithelium is mature. The total mammary epithelium was purified from parous 7-week post-lactation and age-matched virgin mice and analysed by flow cytometry and limiting dilution cleared fat pad transplants. Results There were no significant differences in the proportions of different mammary epithelial cell populations or numbers of CD24+/Low Sca-1- CD49fHigh cells (stem cell enriched basal mammary epithelial compartment). There was no significant difference in stem/progenitor cell frequency based on limiting dilution transplants between the parous and age-matched virgin epithelium. Conclusions Although differences between parous and virgin mammary epithelium at later time points post lactation or following multiple pregnancies cannot be ruled out, there are no differences in stem/progenitor cell numbers between mammary epithelium isolated from parous animals which were mated at 9 weeks old and virgin animals. However, a recent report has suggested that animals that were mated at 5 weeks old have a twofold reduction in stem/progenitor cell numbers. This is of interest given the association between early, but not late, pregnancy and breast cancer risk reduction in humans. However, a mechanistic connection between stem cell numbers and breast cancer risk remains to be established

Exposure Assessment Approaches for Engineered Nanomaterials

Products based on nanotechnology are rapidly emerging in the marketplace, sometimes with little notice to consumers of their nanotechnology pedigree. This wide variety of nanotechnology products will result (in some cases) in unintentional human exposure to purposely engineered nanoscale materials via the dermal, inhalation, ingestion, and ocular pathways. Occupational, consumer, and environmental exposure to the nanomaterials should be characterized during the entire product lifecycle—manufacture, use, and disposal. Monitoring the fate and transport of engineered nanomaterials is complicated by the lack of detection techniques and the lack of a defined set of standardized metrics to be consistently measured. New exposure metrics may be required for engineered nanomaterials, but progress is possible by building on existing tools. An exposure metric matrix could organize existing data by relating likely exposure pathways (dermal, inhalation, ocular, ingestion) with existing measurements of important characteristics of nanoscale materials (particle number, mass, size distribution, charge). Nanomaterial characteristics not commonly measured, but shown to initiate a biological response during toxicity testing, signal a need for further research, such as the pressing need to develop monitoring devices capable of measuring those aspects of engineered nanomaterials that result in biological responses in humans. Modeling the behavior of nanoparticles may require new types of exposure models that individually track particles through the environment while keeping track of the particle shape, surface area, and other surface characteristics as the nanoparticles are transformed or become reactive. Lifecycle analysis could also be used to develop conceptual models of exposure from engineered nanomaterials.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79200/1/j.1539-6924.2010.01446.x.pd

Continuum-based models and concepts for the transport of nanoparticles in saturated porous media: A state-of-the-science review

Environmental applications of nanoparticles (NP) increasingly result in widespread NP distribution within porous media where they are subject to various concurrent transport mechanisms including irreversible deposition, attachment/detachment (equilibrium or kinetic), agglomeration, physical straining, site-blocking, ripening, and size exclusion. Fundamental research in NP transport is typically conducted at small scale, and theoretical mechanistic modeling of particle transport in porous media faces challenges when considering the simultaneous effects of transport mechanisms. Continuum modeling approaches, in contrast, are scalable across various scales ranging from column experiments to aquifer. They have also been able to successfully describe the simultaneous occurrence of various transport mechanisms of NP in porous media such as blocking/straining or agglomeration/deposition/detachment. However, the diversity of model equations developed by different authors and the lack of effective approaches for their validation present obstacles to the successful robust application of these models for describing or predicting NP transport phenomena. This review aims to describe consistently all the important NP transport mechanisms along with their representative mathematical continuum models as found in the current scientific literature. Detailed characterizations of each transport phenomenon in regards to their manifestation in the column experiment outcomes, i.e., breakthrough curve (BTC) and residual concentration profile (RCP), are presented to facilitate future interpretations of BTCs and RCPs. The review highlights two NP transport mechanisms, agglomeration and size exclusion, which are potentially of great importance in controlling the fate and transport of NP in the subsurface media yet have been widely neglected in many existing modeling studies. A critical limitation of the continuum modeling approach is the number of parameters used upon application to larger scales and when a series of transport mechanisms are involved. We investigate the use of simplifying assumptions, such as the equilibrium assumption, in modeling the attachment/detachment mechanisms within a continuum modelling framework. While acknowledging criticisms about the use of this assumption for NP deposition on a mechanistic (process) basis, we found that its use as a description of dynamic deposition behavior in a continuum model yields broadly similar results to those arising from a kinetic model. Furthermore, we show that in two dimensional (2-D) continuum models the modeling efficiency based on the Akaike information criterion (AIC) is enhanced for equilibrium vs kinetic with no significant reduction in model performance. This is because fewer parameters are needed for the equilibrium model compared to the kinetic model. Two major transport regimes are identified in the transport of NP within porous media. The first regime is characterized by higher particle-surface attachment affinity than particle-particle attachment affinity, and operative transport mechanisms of physicochemical filtration, blocking, and physical retention. The second regime is characterized by the domination of particle-particle attachment tendency over particle-surface affinity. In this regime although physicochemical filtration as well as straining may still be operative, ripening is predominant together with agglomeration and further subsequent retention. In both regimes careful assessment of NP fate and transport is necessary since certain combinations of concurrent transport phenomena leading to large migration distances are possible in either case

Heteroaggregation of nanoparticles with biocolloids and geocolloids

The application of nanoparticles has raised concern over the safety of these materials to human health and the ecosystem. After release into an aquatic environment, nanoparticles are likely to experience heteroaggregation with biocolloids, geocolloids, natural organic matter (NOM) and other types of nanoparticles. Heteroaggregation is of vital importance for determining the fate and transport of nanoparticles in aqueous phase and sediments. In this article, we review the typical cases of heteroaggregation between nanoparticles and biocolloids and/or geocolloids, mechanisms, modeling, and important indicators used to determine heteroaggregation in aqueous phase. The major mechanisms of heteroaggregation include electric force, bridging, hydrogen bonding, and chemical bonding. The modeling of heteroaggregation typically considers DLVO, X-DLVO, and fractal dimension. The major indicators for studying heteroaggregation of nanoparticles include surface charge measurements, size measurements, observation of morphology of particles and aggregates, and heteroaggregation rate determination. In the end, we summarize the research challenges and perspective for the heteroaggregation of nanoparticles, such as the determination of αhetero values and heteroaggregation rates; more accurate analytical methods instead of DLS for heteroaggregation measurements; sensitive analytical techniques to measure low concentrations of nanoparticles in heteroaggregation systems; appropriate characterization of NOM at the molecular level to understand the structures and fractionation of NOM; effects of different types, concentrations, and fractions of NOM on the heteroaggregation of nanoparticles; the quantitative adsorption and desorption of NOM onto the surface of nanoparticles and heteroaggregates; and a better understanding of the fundamental mechanisms and modeling of heteroaggregation in natural water which is a complex system containing NOM, nanoparticles, biocolloids and geocolloids

Feasibility, economics, and environmental impact of producing 90 billion gallons of ethanol per year by 2030

This paper addresses a national interest in investigating the potential of displacing a large fraction of U.S. gasoline use by 2030 with ethanol. This study assesses the feasibility, implications, limitations, and enablers of producing 90 billion gallons ethanol per year by 2030. We developed a dynamic supply chain model, the Biofuels Deployment Model (BDM), and conducted sensitivity analyses to determine the parameters that most affect the feasibility, cost-competitiveness, and greenhouse gas impact of large-scale ethanol production. Though we found no theoretical barriers to achieving the stated goal, we identified a number of practical obstacles that need to be addressed. In particular, investment in cellulosic ethanol production needs long-term protection against oil and feedstock price volatility. Capital costs are significant, and investment risk needs to be managed. Technology improvements, particularly in cellulosic conversion yields, are critical and must be sustained over a number of years. Finally, large-scale development of energy crops is necessary