Science-Driven Network Requirements for ESnet

The Energy Sciences Network (ESnet) is the primary providerof network connectivity for the US Department of Energy Office ofScience, the single largest supporter of basic research in the physicalsciences in the United States. In support of the Office of Scienceprograms, ESnet regularly updates and refreshes its understanding of thenetworking requirements of the instruments, facilities and scientiststhat it serves. This focus has helped ESnet to be a highly successfulenabler of scientific discovery for over 20 years. In August, 2002 theDOE Office of Science organized a workshop to characterize the networkingrequirements for Office of Science programs. Networking and middlewarerequirements were solicited from a representative group of scienceprograms. The workshop was summarized in two documents the workshop finalreport and a set of appendixes. This document updates the networkingrequirements for ESnet as put forward by the science programs listed inthe 2002 workshop report. In addition, three new programs have beenadded. Theinformation was gathered through interviews with knowledgeablescientists in each particular program or field

Methods for spatial extrapolation of methane measurements in constructing regional estimates from sample populations

Reporting initiatives for methane emissions from oil and gas operations are broadly shifting towards measurement-informed inventories. Measurement campaigns typically measure a subpopulation of facilities, and these measurements are extrapolated to a larger region or basin. Methane emissions from oil and gas systems are inherently variable and intermittent, which makes it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work proposes a framework using a case study of an operator in the Green River Basin that assesses selection of sample populations, extrapolation of measurements to a larger region, and methods for estimating the error associated with extrapolation. This work also identifies a new metric, the capture ratio, which has a strong correlation with extrapolation error (Spearman’s correlation coefficient = -0.75). The strength of this correlation between the capture ratio, which takes into account the skewness of source-level emissions, and extrapolation error suggests that understanding the distributions of source-level emissions distributions is necessary when identifying sample populations and extrapolating measurements. The results from this work can be broadly applied to inform the selection and extrapolation of site measurements when developing methane emission inventories

Methods for Spatial Extrapolation of Methane Measurements in Constructing Regional Estimates from Sample Populations

Methane emission estimates for oil and gas facilities are typically based on estimates at a subpopulation of facilities, and these emission estimates are then extrapolated to a larger region or basin. Basin-level emission estimates are then frequently compared with basin-level observations. Methane emissions from oil and gas systems are inherently variable and intermittent, which make it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work develops a framework for extrapolation of emission estimates using the case study of an operator in the Green River Basin. This work also identifies a new metric, the capture ratio, which quantifies the extent to which sources are represented in the sample population, based on the skewness of emissions for each source. There is a strong correlation between the capture ratio and extrapolation error, which suggests that understanding source-level emissions distributions can mitigate error when sample populations are selected and extrapolating measurements. The framework and results from this work can inform the selection and extrapolation of site measurements when developing methane emission inventories and establishing uncertainty bounds to assess whether inventory estimates are consistent with independent large spatial-scale observations

An Evaluation of Economic Models to Provide Policy Advice in Response to the BSE Crisis in Canada

"The days following the discovery of BSE in Canada were characterized by considerable uncertainty for both policy makers and industry stakeholders. This paper develops eight criteria for economic systems models that would provide information on the impacts of border closures and the effects of programs designed to alleviate some of the financial strain on industry stakeholders. The eight criteria provide a framework to evaluate two economic models used extensively by policy makers in Canada to provide policy guidance in addition to a survey of published economics literature related to the Canadian beef industry prior to the discovery of the BSE case in May 2003. The results suggest a need to improve the combination of knowledge and modeling skills and techniques before another tragedy strikes the agricultural industry in Canada." Copyright 2007 Canadian Agricultural Economics Society.