Pacific Northwest National Laboratory

About: Pacific Northwest National Laboratory is a facility organization based out in Richland, Washington, United States. It is known for research contribution in the topics: Catalysis & Aerosol. The organization has 11581 authors who have published 27934 publications receiving 1120489 citations. The organization is also known as: PNL & PNNL.

Climate model response from the Geoengineering Model Intercomparison Project (GeoMIP)

Abstract: Solar geoengineering - deliberate reduction in the amount of solar radiation retained by the Earth - has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2 mm day-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels. Key Points Temperature reduction from uniform geoengineering is not uniform Geoengineering cannot offset both temperature and hydrology changes NPP increases mostly due to CO2 fertilization ©2013. American Geophysical Union. All Rights Reserved.

Effect of Genetic Diagnosis on Patients with Previously Undiagnosed Disease

Abstract: Background Many patients remain without a diagnosis despite extensive medical evaluation. The Undiagnosed Diseases Network (UDN) was established to apply a multidisciplinary model in the evaluation of the most challenging cases and to identify the biologic characteristics of newly discovered diseases. The UDN, which is funded by the National Institutes of Health, was formed in 2014 as a network of seven clinical sites, two sequencing cores, and a coordinating center. Later, a central biorepository, a metabolomics core, and a model organisms screening center were added. Methods We evaluated patients who were referred to the UDN over a period of 20 months. The patients were required to have an undiagnosed condition despite thorough evaluation by a health care provider. We determined the rate of diagnosis among patients who subsequently had a complete evaluation, and we observed the effect of diagnosis on medical care. Results A total of 1519 patients (53% female) were referred to the UDN, of whom 6...

Acetate Availability and its Influence on Sustainable Bioremediation of Uranium-Contaminated Groundwater

Abstract: Field biostimulation experiments at the U.S. Department of Energy's Integrated Field Research Challenge (IFRC) site in Rifle, Colorado, have demonstrated that uranium concentrations in groundwater can be decreased to levels below the U.S. Environmental Protection Agency's (EPA) drinking water standard (0.126 μM). During successive summer experiments – referred to as “Winchester” (2007) and “Big Rusty” (2008) - acetate was added to the aquifer to stimulate the activity of indigenous dissimilatory metal-reducing bacteria capable of reductively immobilizing uranium. The two experiments differed in the length of injection (31 vs. 110 days), the maximum concentration of acetate (5 vs. 30 mM), and the extent to which iron reduction (“Winchester”) or sulfate reduction (“Big Rusty”) was the predominant metabolic process. In both cases, rapid removal of U(VI) from groundwater occurred at calcium concentrations (6 mM) and carbonate alkalinities (8 meq/L) where Ca-UO2-CO3 ternary complexes constitute >90% of uranyl ...

Online Detection of Stealthy False Data Injection Attacks in Power System State Estimation

Abstract: State estimation is one of the fundamental functions in modern power grid operations that provide operators with situational awareness and is used by several applications like contingency analysis and power markets. Several research in the recent past have highlighted the vulnerability of state estimators to stealthy false data injection attacks that bypass bad data detection mechanisms. They primarily focused on identifying stealthy attack vectors and characterizing their impacts on state estimates. Existing mitigation measures either focus on masking the effect of attacks through redundant measurements or prevent attacks by increasing the cyber security of associated sensors and communication channels. The solutions based on these offline approaches make specific assumptions about the nature of attacks and of the system, which are often restrictive and grossly inadequate to deal with dynamically evolving cyber threats and changing system configurations. In this paper, we propose an online anomaly detection algorithm that utilizes load forecasts, generation schedules, and synchrophasor data to detect measurement anomalies. We provide some insight into the factors that affect the performance of the proposed algorithm. We also describe an empirical method to obtain the minimum attack magnitudes and the detection thresholds for meeting specified false positive and true positive rates. Finally, we evaluated the performance of the proposed algorithm using the IEEE 14 bus power system model for several measures (false positive, false negative, and thresholds). We observed that the best performance of the proposed algorithm relies on finding the right balance between the minimum attack magnitude and detection thresholds. We also observed that the minimum attack magnitudes and detection thresholds could be further improved through the use of a combination of more accurate forecasts and PMU measurements.