Economic Feasibility of Commercial Algae Oil Production in the United States

A Monte Carlo simulation model was constructed to analyze the economic feasibility of growing algae as a renewable fuel source. Increasing growth rates, pond water depth, oil content, and facility size are important for ensuring the economic viability of a commercial algae facility.algae, renewable, fuel, feedstock, microalgae, Agribusiness, Agricultural and Food Policy, Crop Production/Industries, Production Economics, Resource /Energy Economics and Policy, Risk and Uncertainty,

Analyzing Carbon Dioxide and Methane Emissions in California Using Airborne Measurements and Model Simulations

Greenhouse gas (GHG) concentrations have increased over the past decades and are linked to global temperature increases and climate change. These changes in climate have been suggested to have varying effects, and uncertain consequences, on agriculture, water supply, weather, sea-level rise, the economy, and energy. To counteract the trend of increasing atmospheric concentrations of GHGs, the state of California has passed the California Global Warming Act of 2006 (AB-32). This requires that by the year 2020, GHG (e.g., carbon dioxide (CO2) and methane (CH4)) emissions will be reduced to 1990 levels. To quantify GHG fluxes, emission inventories are routinely compiled for the State of California (e.g., CH4 emissions from the California Greenhouse Gas Emissions Measurement (CALGEM) Project). The major sources of CO2 and CH4 in the state of California are: transportation, electricity production, oil and gas extraction, cement plants, agriculture, landfills/waste, livestock, and wetlands. However, uncertainties remain in these emission inventories because many factors contributing to these processes are poorly quantified. To alleviate these uncertainties, a synergistic approach of applying air-borne measurements and chemical transport modeling (CTM) efforts to provide a method of quantifying local and regional GHG emissions will be performed during this study. Additionally, in order to further understand the temporal and spatial distributions of GHG fluxes in California and the impact these species have on regional climate, CTM simulations of daily variations and seasonality of total column CO2 and CH4 will be analyzed. To assess the magnitude and spatial variation of GHG emissions and to identify local hot spots, airborne measurements of CH4 and CO2 were made by the Alpha Jet Atmospheric eXperiment (AJAX) over the San Francisco Bay Area (SFBA) and San Joaquin Valley (SJV) in January and February 2013 during the Discover-AQ-CA study. High mixing ratios of GHGs were observed in-flight with a high degree of spatial variability. To provide an additional method to quantify GHG emissions, and analyze AJAX measurement data, the GEOS-Chem CTM is used to simulate SFBA/SJV GHG measurements. A nested-grid version of GEOS-Chem will be applied and utilizes varying emission inventories and model parameterizations to simulate GHG fluxes/emissions. The model considers CO2 fluxes from fossil fuel use, biomass/biofuel burning, terrestrial and oceanic biosphere exchanges, shipping and aviation, and production from the oxidation of carbon monoxide, CH4, and non-methane volatile organic carbons. The major sources of CH4 simulated in GEOS-Chem are domesticated animals, rice fields, natural gas leakage, natural gas venting/flaring (oil production), coal mining, wetlands, and biomass burning. Preliminary results from the comparison between available observations (e.g., AJAX and CALGEM CH4 emission maps) and GEOS-Chem results will be presented, along with a discussion of CO2 and CH4 source apportionment and the use of the GEOS-Chem-adjoint to perform inverse GHG modeling

Measuring equilibrium properties in aging systems

We corroborate the idea of a close connection between replica symmetry breaking and aging in the linear response function for a large class of finite-dimensional systems with short-range interactions. In these system, characterized by a continuity condition with respect to weak random perturbations of the Hamiltonian, the ``fluctuation dissipation ratio'' in off-equilibrium dynamics should be equal to the static cumulative distribution function of the overlaps. This allows for an experimental measurement of the equilibrium order parameter function.Comment: 5 pages, LaTeX. The paper has been completely rewritten and shortene

Solvent effects on catalytic activity and selectivity in amine-catalyzed D-fructose isomerization

Rational catalyst design and optimal solvent selection are key to advancing biorefining. Here, we explored the organocatalytic isomerization of D-fructose to a valuable rare monosaccharide, D-allulose, as a function of solvent. The isomerization of D-fructose to D-allulose competes with its isomerization to D-glucose and sugar degradation. In both water and DMF, the catalytic activity of amines towards D-fructose is correlated with their basicity. Solvents impact the selectivity significantly by altering the tautomeric distribution of D-fructose. Our results suggest that the furanose tautomer of D-fructose is isomerized to D-allulose, and the fractional abundance of this tautomer increases as follows: water < MeOH < DMF ≈ DMSO. Reaction rates are also higher in aprotic than in protic solvents. The best D-allulose yield, 14 %, was obtained in DMF with 1,5,7-triazabicyclo[4.4.0]dec-5-ene (TBD) as the catalyst. The reaction kinetics and mechanism were explored using operando NMR spectroscopy

Observation of CH4 and other Non-CO2 Green House Gas Emissions from California

In 2006, California passed the landmark assembly bill AB-32 to reduce California's emissions of greenhouse gases (GHGs) that contribute to global climate change. AB-32 commits California to reduce total GHG emissions to 1990 levels by 2020, a reduction of 25 percent from current levels. To verify that GHG emission reductions are actually taking place, it will be necessary to measure emissions. We describe atmospheric inverse model estimates of GHG emissions obtained from the California Greenhouse Gas Emissions Measurement (CALGEM) project. In collaboration with NOAA, we are measuring the dominant long-lived GHGs at two tall-towers in central California. Here, we present estimates of CH{sub 4} emissions obtained by statistical comparison of measured and predicted atmospheric mixing ratios. The predicted mixing ratios are calculated using spatially resolved a priori CH{sub 4} emissions and surface footprints, that provide a proportional relationship between the surface emissions and the mixing ratio signal at tower locations. The footprints are computed using the Weather Research and Forecast (WRF) coupled to the Stochastic Time-Inverted Lagrangian Transport (STILT) model. Integral to the inverse estimates, we perform a quantitative analysis of errors in atmospheric transport and other factors to provide quantitative uncertainties in estimated emissions. Regressions of modeled and measured mixing ratios suggest that total CH{sub 4} emissions are within 25% of the inventory estimates. A Bayesian source sector analysis obtains posterior scaling factors for CH{sub 4} emissions, indicating that emissions from several of the sources (e.g., landfills, natural gas use, petroleum production, crops, and wetlands) are roughly consistent with inventory estimates, but livestock emissions are significantly higher than the inventory. A Bayesian 'region' analysis is used to identify spatial variations in CH{sub 4} emissions from 13 sub-regions within California. Although, only regions near the tower are significantly constrained by the tower measurements, CH{sub 4} emissions from the south Central Valley appear to be underestimated in a manner consistent with the under-prediction of livestock emissions. Finally, we describe a pseudo-experiment using predicted CH{sub 4} signals to explore the uncertainty reductions that might be obtained if additional measurements were made by a future network of tall-tower stations spread over California. These results show that it should be possible to provide high-accuracy estimates of surface CH{sub 4} emissions for multiple regions as a means to verify future emissions reductions

Inverse Estimation of an Annual Cycle of California's Nitrous Oxide Emissions

Nitrous oxide (N_2O) is a potent long‐lived greenhouse gas (GHG) and the strongest current emissions of global anthropogenic stratospheric ozone depletion weighted by its ozone depletion potential. In California, N_2O is the third largest contributor to the state's anthropogenic GHG emission inventory, though no study has quantified its statewide annual emissions through top‐down inverse modeling. Here we present the first annual (2013–2014) statewide top‐down estimates of anthropogenic N_2O emissions. Utilizing continuous N_2O observations from six sites across California in a hierarchical Bayesian inversion, we estimate that annual anthropogenic emissions are 1.5–2.5 times (at 95% confidence) the state inventory (41 Gg N_2O in 2014). Without mitigation, this estimate represents 4–7% of total GHG emissions assuming that other reported GHG emissions are reasonably correct. This suggests that control of N_2O could be an important component in meeting California's emission reduction goals of 40% and 80% below 1990 levels of the total GHG emissions (in CO_2 equivalent) by 2030 and 2050, respectively. Our seasonality analysis suggests that emissions are similar across seasons within posterior uncertainties. Future work is needed to provide source attribution for subregions and further characterization of seasonal variability

Use of Japanese Encephalitis Vaccine in US Travel Medicine Practices in Global TravEpiNet

Few data regarding the use of Japanese encephalitis (JE) vaccine in clinical practice are available. We identified 711 travelers at higher risk and 7,578 travelers at lower risk for JE who were seen at US Global TravEpiNet sites from September of 2009 to August of 2012. Higher-risk travelers were younger than lower-risk travelers (median age = 29 years versus 40 years, P < 0.001). Over 70% of higher-risk travelers neither received JE vaccine during the clinic visit nor had been previously vaccinated. In the majority of these instances, clinicians determined that the JE vaccine was not indicated for the higher-risk traveler, which contradicts current recommendations of the Advisory Committee on Immunization Practices. Better understanding is needed of the clinical decision-making regarding JE vaccine in US travel medicine practices

Elevated HbA1c levels and the accumulation of differentiated T cells in CMV+ individuals

Aims/hypothesis Biological ageing of the immune system, or immunosenescence, predicts poor health and increased mortality. A hallmark of immunosenescence is the accumulation of differentiated cytotoxic T cells (CD27−CD45RA+/−; or dCTLs), partially driven by infection with the cytomegalovirus (CMV). Immune impairments reminiscent of immunosenescence are also observed in hyperglycaemia, and in vitro studies have illustrated mechanisms by which elevated glucose can lead to increased dCTLs. This study explored associations between glucose dysregulation and markers of immunosenescence in CMV+ and CMV− individuals. Methods A cross-sectional sample of participants from an occupational cohort study (n = 1,103, mean age 40 years, 88% male) were assessed for HbA1c and fasting glucose levels, diabetes, cardiovascular risk factors (e.g. lipids), numbers of circulating effector memory (EM; CD27−CD45RA−) and CD45RA re-expressing effector memory (EMRA; CD27−CD45RA+) T cells, and CMV infection status. Self-report and physical examination assessed anthropometric, sociodemographic and lifestyle factors. Results Among CMV+ individuals (n = 400), elevated HbA1c was associated with increased numbers of EM (B = 2.75, p \u3c 0.01) and EMRA (B = 2.90, p \u3c 0.01) T cells, which was robust to adjustment for age, sex, sociodemographic variables and lifestyle factors. Elevated EM T cells were also positively associated with total cholesterol (B = 0.04, p \u3c 0.05) after applying similar adjustments. No associations were observed in CMV− individuals. Conclusions/interpretation The present study identified consistent associations of unfavourable glucose and lipid profiles with accumulation of dCTLs in CMV+ individuals. These results provide evidence that the impact of metabolic risk factors on immunity and health can be co-determined by infectious factors, and provide a novel pathway linking metabolic risk factors with accelerated immunosenescence. Electronic supplementary material The online version of this article (doi:10.1007/s00125-015-3731-4) contains peer-reviewed but unedited supplementary material, which is available to authorised users