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At least 1,315 records · Page 73

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗

Importance of lateral flux and its percolation depth on organic carbon export in Arctic tundra soil: Implications from a soil leaching experiment

Temperature rise in the Arctic is causing deepening of active layers and resulting in the mobilization of deep permafrost dissolved organic matter (DOM). However, the mechanisms of DOM mobilization from Arctic soils, especially upper soil horizons which are drained most frequently through a year, are poorly understood. Here, we conducted a short-term leaching experiment on surface and deep organic active layer soils, from the Yukon River basin, to examine the effects of DOM transport on bulk and molecular characteristics. We report our data showed a net release of DOM from surface soils equal to an average of 5% of soil carbon. Conversely, deep soils percolated with surface leachates retained up to 27% of bulk DOM-while releasing fluorescent components (up to 107%), indicating selective release of aromatic components (e.g. lignin, tannin), while retaining non-chromophoric components, as supported by spectrofluorometric and ultra high resolution mass spectroscopic techniques. Our findings highlight the importance of the lateral flux of DOM on ecosystem carbon balance as well as processing of DOM transport through organic active layer soils en route to rivers and streams. This work also suggests the potential role of leachate export as an important mechanism of C losses from Arctic soils, in comparison with the more traditional pathway from soil to atmosphere in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗

An in-depth understanding of biomass recalcitrance using natural poplar variants as the feedstock

Here, in an effort to better understand the biomass recalcitrance, six natural poplar variants were selected as feedstocks based on previous sugar release analysis. Compositional analysis and physicochemical characterizations of these poplars were performed and the correlations between these physicochemical properties and enzymatic hydrolysis yield were investigated. Gel permeation chromatography (GPC) and 13 C solid state NMR were used to determine the degree of polymerization (DP) and crystallinity index (CrI) of cellulose, and the results along with the sugar release study indicated that cellulose DP likely played a more important role in enzymatic hydrolysis. Simons’ stain revealed that the accessible surface area of substrate significantly varied among these variants from 17.3 to 33.2 mg g$–1\atop{biomass}$ as reflected by dye adsorption, and cellulose accessibility was shown as one of the major factors governing substrates digestibility. HSQC and 31 P NMR analysis detailed the structural features of poplar lignin variants. Overall, cellulose relevant factors appeared to have a stronger correlation with glucose release, if any, than lignin structural features. Lignin structural features, such as a phenolic hydroxyl group and the ratio of syringyl and guaiacyl (S/G), were found to have a more convincing impact on xylose release. Low lignin content, low cellulose DP, and high cellulose accessibility generally favor enzymatic hydrolysis; however, recalcitrance cannot be simply judged on any single substrate factor.

09 BIOMASS FUELS↗

An in-depth field validation of “DUSST”: A novel low-maintenance soiling measurement device

This study presents indoor and field validation results for two versions of the “DUSST” optical soiling sensor, intended to be a low-cost and low-maintenance device for measuring photovoltaic soiling losses. Indoor testing covers irradiance calibration and temperature dependencies, which are necessary to achieve high accuracy, low uncertainty field measurements. Field testing includes an array of different environments including Saudi Arabia, California, Utah, and Colorado. DUSST versions include a configuration with a 530-nm light emitting diode (LED) (discussed in previous work) and a unit with seven white LEDs and a polycarbonate collimating optic. The new design increases light intensity fivefold and demonstrates a single linear calibration coefficient is effective to measure soiling losses as high as 75%. Field data from Utah and California demonstrate that daily soiling loss measurements and soiling rate calculations closely match both reference cell and full-size module measurements of soiling losses and soiling rates. Corrective methods employed on the Utah DUSST sensor suggest that it is possible to achieve measurement errors as low as ±0.1% at two standard deviations. Field data from both Colorado and Saudi Arabia demonstrate that LED lens soiling can occur and that further design optimizations are needed. The lesson learned from all the field deployment locations suggests directions for future design improvements.

14 SOLAR ENERGY↗

In-Depth Proteome Profiling of the Hippocampus of LDLR Knockout Mice Reveals Alternation in Synaptic Signaling Pathway

The low-density lipoprotein receptor (LDLR) is a major apolipoprotein receptor that regulates cholesterol homeostasis. LDLR deficiency is associated with cognitive impairment by the induction of synaptopathy in the hippocampus. Despite the close relationship between LDLR and neurodegenerative disorders, proteomics research for protein profiling in the LDLR knockout (KO) model remains insufficient. Therefore, understanding LDLR KO-mediated differential protein expression within the hippocampus is crucial for elucidating a role of LDLR in neurodegenerative disorders. In this study, we conducted first-time proteomic profiling of hippocampus tissue from LDLR KO mice using tandem mass tag (TMT)-based MS analysis. LDLR deficiency induces changes in proteins associated with the transport of diverse molecules, and activity of kinase and catalyst within the hippocampus. Additionally, significant alterations in the expression of components in the major synaptic pathways were found. Furthermore, these synaptic effects were verified using a data-independent acquisition (DIA)-based proteomic method. In conclusion, our data will serve as a valuable resource for further studies to discover the molecular function of LDLR in neurodegenerative disorders.

60 APPLIED LIFE SCIENCES↗

In-depth understanding of molecular mechanisms of aldehyde toxicity to engineer robust Saccharomyces cerevisiae

Aldehydes are ubiquitous electrophilic compounds that ferment microorganisms including Saccharomyces cerevisiae encounter during the fermentation processes to produce food, fuels, chemicals, and pharmaceuticals. Aldehydes pose severe toxicity to the growth and metabolism of the S. cerevisiae through a variety of toxic molecular mechanisms, predominantly via damaging macromolecules and hampering the production of targeted compounds. Compounds with aldehyde functional groups are far more toxic to S. cerevisiae than all other functional classes, and toxic potency depends on physicochemical characteristics of aldehydes. The yeast synthetic biology community established a design–build–test–learn framework to develop S. cerevisiae cell factories to valorize the sustainable and renewable biomass, including the lignin-derived substrates. However, thermochemically pretreated biomass-derived substrate streams contain diverse aldehydes (e.g., glycolaldehyde and furfural), and biological conversions routes of lignocellulosic compounds consist of toxic aldehyde intermediates (e.g., formaldehyde and methylglyoxal), and some of the high-value targeted products have aldehyde functional group (e.g., vanillin and benzaldehyde). Numerous studies comprehensively characterized both single and additive effects of aldehyde toxicity via systems biology investigations, and novel molecular approaches have been discovered to overcome the aldehyde toxicity. Based on those novel approaches, researchers successfully developed synthetic yeast cell factories to convert lignocellulosic substrates to valuable products, including aldehyde compounds. Here, we highlight the salient relationship of physicochemical charac- teristics and molecular toxicity of aldehydes, the molecular detoxification and macromolecules protection mechanisms of aldehydes, and the advances of engineering robust S. cerevisiae against complex mixtures of aldehyde inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

Spatially Quasi-Periodic Water Waves of Infinite Depth

Abstract We formulate the two-dimensional gravity-capillary water wave equations in a spatially quasi-periodic setting and present a numerical study of solutions of the initial value problem. We propose a Fourier pseudo-spectral discretization of the equations of motion in which one-dimensional quasi-periodic functions are represented by two-dimensional periodic functions on a torus. We adopt a conformal mapping formulation and employ a quasi-periodic version of the Hilbert transform to determine the normal velocity of the free surface. Two methods of time-stepping the initial value problem are proposed, an explicit Runge–Kutta (ERK) method and an exponential time-differencing (ETD) scheme. The ETD approach makes use of the small-scale decomposition to eliminate stiffness due to surface tension. We perform a convergence study to compare the accuracy and efficiency of the methods on a traveling wave test problem. We also present an example of a periodic wave profile containing vertical tangent lines that is set in motion with a quasi-periodic velocity potential. As time evolves, each wave peak evolves differently, and only some of them overturn. Beyond water waves, we argue that spatial quasi-periodicity is a natural setting to study the dynamics of linear and nonlinear waves, offering a third option to the usual modeling assumption that solutions either evolve on a periodic domain or decay at infinity.

Wilkening, Jon (ORCID:0000000327827596)↗

Estimation of Crystal Lattice Deformations with Depth of Proton-Exchanged Optical Waveguides on Lithium Niobate Single Crystal Substrates

A method for determining the crystal phase and estimating the crystal lattice deformations in H{sub x}Li{sub 1-x}NbO{sub 3} proton-exchanged optical waveguides from an analysis of the Raman light scattering spectra measured with high spatial resolution (the so-called method of micro-RS spectroscopy) is suggested.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗