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.

Acid mine drainage biogeochemistry at Iron Mountain, California

Abstract: The Richmond Mine at Iron Mountain, Shasta County, California, USA provides an excellent opportunity to study the chemical and biological controls on acid mine drainage (AMD) generation in situ, and to identify key factors controlling solution chemistry. Here we integrate four years of field-based geochemical data with 16S rRNA gene clone libraries and rRNA probe-based studies of microbial population structure, cultivation-based metabolic experiments, arsenopyrite surface colonization experiments, and results of intermediate sulfur species kinetics experiments to describe the Richmond Mine AMD system. Extremely acidic effluent (pH between 0.5 and 0.9) resulting from oxidation of approximately 1 × 105 to 2 × 105 moles pyrite/day contains up to 24 g/1 Fe, several g/1 Zn and hundreds of mg/l Cu. Geochemical conditions change markedly over time, and are reflected in changes in microbial populations. Molecular analyses of 232 small subunit ribosomal RNA (16S rRNA) gene sequences from six sites during a sampling time when lower temperature ( 0.8) conditions predominated show the dominance of Fe-oxidizing prokaryotes such as Ferroplasma and Leptospirillum in the primary drainage communities. Leptospirillum group III accounts for the majority of Leptospirillum sequences, which we attribute to anomalous physical and geochemical regimes at that time. A couple of sites peripheral to the main drainage, "Red Pool" and a pyrite "Slump," were even higher in pH (>1) and the community compositions reflected this change in geochemical conditions. Several novel lineages were identified within the archaeal Thermoplasmatales order associated with the pyrite slump, and the Red Pool (pH 1.4) contained the only population of Acidithiobacillus. Relatively small populations of Sulfobacillus spp. and Acidithiobacillus caldus may metabolize elemental sulfur as an intermediate species in the oxidation of pyritic sulfide to sulfate. Experiments show that elemental sulfur which forms on pyrite surfaces is resistant to most oxidants; its solublization by unattached cells may indicate involvement of a microbially derived electron shuttle. The detachment of thiosulfate (S2O32-) as a leaving group in pyrite oxidation should result in the formation and persistence of tetrathionate in low pH ferric iron-rich AMD solutions. However, tetrathionate is not observed. Although a S2O32--like species may form as a surface-bound intermediate, data suggest that Fe3+ oxidizes the majority of sulfur to sulfate on the surface of pyrite. This may explain why microorganisms that can utilize intermediate sulfur species are scarce compared to Fe-oxidizing taxa at the Richmond Mine site.

On model selection criteria in multimodel analysis

Abstract: [1] Hydrologic systems are open and complex, rendering them prone to multiple conceptualizations and mathematical descriptions. There has been a growing tendency to postulate several alternative hydrologic models for a site and use model selection criteria to (1) rank these models, (2) eliminate some of them, and/or (3) weigh and average predictions and statistics generated by multiple models. This has led to some debate among hydrogeologists about the merits and demerits of common model selection (also known as model discrimination or information) criteria such as AIC, AICc, BIC, and KIC and some lack of clarity about the proper interpretation and mathematical representation of each criterion. We examine the model selection literature to find that (1) all published rigorous derivations of AIC and AICc require that the (true) model having generated the observational data be in the set of candidate models; (2) though BIC and KIC were originally derived by assuming that such a model is in the set, BIC has been rederived by Cavanaugh and Neath (1999) without the need for such an assumption; and (3) KIC reduces to BIC as the number of observations becomes large relative to the number of adjustable model parameters, implying that it likewise does not require the existence of a true model in the set of alternatives. We explain why KIC is the only criterion accounting validly for the likelihood of prior parameter estimates, elucidate the unique role that the Fisher information matrix plays in KIC, and demonstrate through an example that it imbues KIC with desirable model selection properties not shared by AIC, AICc, or BIC. Our example appears to provide the first comprehensive test of how AIC, AICc, BIC, and KIC weigh and rank alternative models in light of the models' predictive performance under cross validation with real hydrologic data.

High-Concentration Ether Electrolytes for Stable High-Voltage Lithium Metal Batteries

Abstract: High-voltage (>4.3 V) rechargeable lithium (Li) metal batteries (LMBs) face huge obstacles due to the high reactivity of Li metal with traditional electrolytes. Despite their good stability with Li metal, conventional ether-based electrolytes are typically used only in <4.0 V LMBs because of their limited oxidation stability. Here we report high-concentration ether electrolytes that can induce the formation of a unique cathode electrolyte interphase via the synergy between the salt and the ether solvent, which effectively stabilizes the catalytically active cathodes and preserves their structural integrity under high voltages. Eventually, LMBs can retain 92% capacity after 500 cycles at 4.3 V with very limited Li consumption. More importantly, such ether electrolytes enable stable battery cycling not only under voltages as high as 4.5 V but also on highly demanding Ni-rich layered cathodes. These findings significantly expand knowledge of ether electrolytes and provide new perspectives of electrolyte desi...

Extracellular Polymeric Substances from Shewanella sp. HRCR-1 Biofilms: Characterization by Infrared Spectroscopy and Proteomics

Abstract: The composition of extracellular polymeric substances (EPS) from Shewanella sp. HRCR-1 biofilms was investigated using infrared spectroscopy and proteomics to provide insight into potential ecophysiological functions and redox activity of the EPS. Both bound and loosely associated EPS were extracted from Shewanella sp. HRCR-1 biofilms prepared using a hollow-fibre membrane biofilm reactor. Fourier transform infrared spectra revealed the presence of proteins, polysaccharides, nucleic acids, membrane lipids and fatty acids in the EPS fractions. Using a global proteomic approach, a total of 58 extracellular and outer membrane proteins were identified in the EPS. These included homologues of multiple Shewanella oneidensis MR-1 proteins that potentially contribute to key physiological biofilm processes, such as biofilm-promoting protein BpfA, surface-associated serine protease, nucleotidases (CpdB and UshA), an extracellular lipase, and oligopeptidases (PtrB and a M13 family oligopeptidase lipoprotein). In addition, 20 redox proteins were found in extracted EPS. Among the detected redox proteins were the homologues of two S. oneidensis MR-1 c-type cytochromes, MtrC and OmcA, which have been implicated in extracellular electron transfer. Given their detection in the EPS of Shewanella sp. HRCR-1 biofilms, c-type cytochromes may contribute to the possible redox activity of the biofilm matrix and play important roles in extracellular electron transfer reactions.

Toward understanding of differences in current cloud retrievals of ARM ground-based measurements

Abstract: Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.