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Magnetic resonance imaging of the calcaneus: preliminary assessment of trabecular bone-dependent regional variations in marrow relaxation time compared with dual X-ray absorptiometry

RATIONALE AND OBJECTIVES: Marrow transverse relaxation time (T2*) in magnetic resonance (MR) imaging may be related to the density and structure of the surrounding trabecular network. We investigated regional variations of T2* in the human calcaneus and compared the findings with bone mineral density (BMD), as measured by dual X-ray absorpiometry (DXA). Short- and long-term precisions were evaluated first to determine whether MR imaging would be useful for the clinical assessment of disease status and progression in osteoporosis. METHODS: Gradient-recalled echo MR images of the calcaneus were acquired at 1.5 T from six volunteers. Measurements of T2* were compared with BMD and (for one volunteer) conventional radiography. RESULTS: T2* values showed significant regional variation; they typically were shortest in the superior region of the calcaneus. There was a linear correlation between MR and DXA measurements (r = .66 for 1/T2* versus BMD). Differences in T2* attributable to variations in analysis region-of-interest placement were not significant for five of the six volunteers. Sagittal MR images had short- and long-term precision errors of 4.2% and 3.3%, respectively. For DXA, the precision was 1.3% (coefficient of variation). CONCLUSION: MR imaging may be useful for trabecular bone assessment in the calcaneus. However, given the large regional variations in bone density and structure, the choice of an ROI is likely to play a major role in the accuracy, precision, and overall clinical efficacy of T2* measurements.

Non-NASA Center↗

Determining Optimal Magnetometer Configuration on MAGIS-100

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.] (ORC↗

Determining Optimal Magnetometer Configuration on MAGIS-100

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.] (ORC↗

In-Situ Magnetic Field Reconstruction in the MAGIS-100 Experiment

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.; Ferm↗

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study (https://doi.org/10.1063/5.0018326), exploits the low-rank character of the polynomial expansion of potential energy to recover, using a small sample, vibrational frequencies (square roots of nuclear Hessian eigenvalues) constituting the reaction path. Furthermore, these frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four SN2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BOREAS RSS-10 TOMS Circumpolar One-Degree PAR Images

The Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-10 team investigated the magnitude of daily, seasonal, and yearly variations of Photosynthetically Active Radiation (PAR) from ground and satellite observations. This data set contains satellite estimates of surface-incident PAR (400-700 nm, MJ/sq m) at one-degree spatial resolution. The spatial coverage is circumpolar from latitudes of 41 to 66 degrees north. The temporal coverage is from May through September for years 1979 through 1989. Eleven-year statistics are also provided: (1) mean, (2) standard deviation, and (3) coefficient of variation for 1979-89. The PAR estimates were derived from the global gridded ultraviolet reflectivity data product (average of 360, 380 nm) from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS). Image mask data are provided for identifying the boreal forest zone, and ocean/land and snow/ice-covered areas. The data are available as binary image format data files. The PAR data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Dye, Dennis G.↗

Exploration of Fuel Property Impacts on the Combustion of Late Post Injections Using Binary Blends and High-Reactivity Ether Bioblendstocks

In this study, the impacts of fuel volatility and reactivity on combustion stability and emissions were studied in a light-duty single-cylinder research engine for a three-injection catalyst heating operation strategy with late post-injections. Here, N-heptane and blends of farnesane/2,2,4,4,6,8,8-heptamethylnonane were used to study the impacts of volatility and reactivity. The effect of increased chemical reactivity was also analysed by comparing the baseline #2 diesel operation with a pure blend of mono-ether components (CN > 100) representative of potential high cetane oxygenated bioblendstocks and a 25 vol.% blend of the mono-ether blend and #2 diesel with a cetane number (CN) of 55. At constant reactivity, little to no variation in combustion performance was observed due to differences in volatility, whereas increased reactivity improved combustion stability and efficiency at late injection timings. Fuels with higher reactivity were found to reduce engine-out hydrocarbon and carbon monoxide emissions while also achieving stable combustion at post-injection timings later than those achievable with #2 diesel fuel. The pure ether blend had the latest achievable post-injection timing of +30.5 CAD while still maintaining stable combustion (coefficient of variation of gross-indicated mean effective pressure < 5%). With post-injection timing adjusted to achieve a matched exhaust temperature of 300 °C, the ether-diesel CN 55 blend was observed to have slightly higher thermal efficiency in comparison to the baseline #2 diesel fuel. The results also indicate that cetane number may serve as a good indicator of combustion characteristics at late injection timings used for aftertreatment thermal management operation.

09 BIOMASS FUELS↗

Exploration of Fuel Property Impacts on the Combustion of Late Post Injections Using Binary Blends and High-Reactivity Ether Bioblendstocks

In this study, the impacts of fuel volatility and reactivity on com- bustion stability and emissions were studied in a light-duty single- cylinder research engine for a three-injection catalyst heating oper- ation strategy with late post-injections. N-heptane and blends of farnesane/2,2,4,4,6,8,8-heptamethylnonane were used to study the im- pacts of volatility and reactivity. The effect of increased chemical reac- tivity was also analysed by comparing the baseline #2 diesel operation with a pure blend of mono-ether components (CN > 100) representa- tive of potential high cetane oxygenated bioblendstocks and a 25 vol.% blend of the mono-ether blend and #2 diesel with a cetane number (CN) of 55. At constant reactivity, little to no variation in combustion performance was observed due to differences in volatility, whereas in- creased reactivity improved combustion stability and efficiency at late injection timings. Fuels with higher reactivity were found to reduce engine-out hydrocarbon and carbon monoxide emissions while also achieving stable combustion at post-injection timings later than those achievable with #2 diesel fuel. The pure ether blend had the latest achievable post-injection timing of +30.5 CAD while still maintaining stable combustion (coefficient of variation of gross-indicated mean ef- fective pressure < 5%). With post-injection timing adjusted to achieve a matched exhaust temperature of 300 °C, the ether-diesel CN 55 blend was observed to have slightly higher thermal efficiency in comparison to the baseline #2 diesel fuel. The results also indicate that cetane num- ber may serve as a good indicator of combustion characteristics at late injection timings used for aftertreatment thermal management opera- tion.

99 GENERAL AND MISCELLANEOUS↗

Remote Floating-Gate Field-Effect Transistor with 2-Dimensional Reduced Graphene Oxide Sensing Layer for Reliable Detection of SARS-CoV-2 Spike Proteins

Despite intensive research of nanomaterials-based field-effect transistors (FETs) as a rapid diagnostic tool, it remains to be seen for FET sensors to be used for clinical applications due to a lack of stability, reliability, reproducibility, and scalability for mass production. In this work, we propose a remote floating-gate (RFG) FET configuration to eliminate device-to-device variations of two-dimensional reduced graphene oxide (rGO) sensing surfaces and most of the instability at the solution interface. Also, critical mechanistic factors behind the electrochemical instability of rGO such as severe drift and hysteresis were identified through extensive studies on rGO–solution interfaces varied by rGO thickness, coverage, and reduction temperature. rGO surfaces in our RFGFET structure displayed a Nernstian response of 54 mV/pH (from pH 2 to 11) with a 90% yield (9 samples out of total 10), coefficient of variation (CV) < 3%, and a low drift rate of 2%, all of which were calculated from the absolute measurement values. As proof-of-concept, we demonstrated highly reliable, reproducible, and label-free detection of spike proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a saliva-relevant media with concentrations ranging from 500 fg/mL to 5 μg/mL, with an R 2 value of 0.984 and CV < 3%, and a guaranteed limit of detection at a few pg/mL. Taken together, this new platform may have an immense effect on positioning FET bioelectronics in a clinical setting for detecting SARS-CoV-2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of fuel film formation and soot emissions in a GDI engine during cold-start with Split-injection strategies

This study investigates the impact of fuel-film formation on engine-out soot emissions in a gasoline direct injection (GDI) engine under cold-start conditions. Split-injection strategies were applied by varying the number of injections, injection duration, and total fuel quantity to affect wall wetting and control the average in-cylinder equivalence ratio. A combined experimental and numerical approach was employed to analyze fuel-film deposition, combustion efficiency, and engine-out soot and unburnt hydrocarbons (UHC) emissions. In particular, fuel film distribution estimated by means of non-reacting, 3-D, computational fluid dynamics (CFD) simulations, together with experimentally measured soot data, were used to investigate fuel film formation and its role in soot generation. In the experiments, a skip-fired engine control strategy was applied to mimic the transient nature of engine cold-start operation. The results indicate that, under the same total number of injections, increasing the average in-cylinder equivalence ratio through longer injection durations improves combustion stability, as indicated by the decrease of the coefficient of variation of IMEP n (Net Indicated Mean Effective Pressure) from 6.0 % to 0.6 %. However, this strategy leads to higher soot emissions, which increased by nearly an order of magnitude, primarily due to enhanced wall-film formation. In contrast, increasing the number of injections while maintaining a constant equivalence ratio significantly impacts fuel-film deposition and, consequently, soot emissions, with a fivefold reduction of the measured engine-out soot, decreasing from 3.5 mg to 0.7 mg. A soot-film correlation was developed and achieved a high coefficient of determination (r 2 = 0.95) and was further extended to account for spark timing effects. These findings confirm the effectiveness of split-injection for avoiding wall film formation and soot emissions, and the critical role of fuel film in soot generation, supporting the hypothesis that pool fires play a crucial role in contributing to soot formation under these cold-start conditions. In conclusion, the study also indicates the value of a predictive soot-film correlation for developing cold-start emission control strategies.

Engine Cold-start↗

Variations in pharmacokinetic-pharmacodynamic target values across MICs and their potential impact on determination of susceptibility test interpretive criteria

Abstract Background An antibacterial drug’s susceptibility test interpretive criteria (STIC) are determined by integrating clinical, microbiological and pharmacokinetic-pharmacodynamic (PK-PD) data. PTA analysis plays a pivotal or supportive role in STIC determination and is heavily dependent on the PK-PD target values determined from animal PK-PD studies. Therefore, variations in PK-PD target values may impact STIC determination. Factors contributing to variation in the PK-PD target values include the number of and MICs for bacterial isolates used in animal PK-PD studies. Objectives To analyse the relationship between PK-PD target values and MICs, describe the variations in PK-PD target values of isolates and evaluate whether the proposed/target STICs were within the ranges of the MICs for isolates used in animal PK-PD studies. Methods A database was compiled for this research by screening animal PK-PD study reports submitted to the FDA from 10 new drug applications (NDAs). Results A relationship evaluation between PK-PD target values and MICs for tested isolates for seven drugs (that used AUC/MIC ratio as the PK-PD index) showed that, generally, the AUC/MIC values decreased with an increase in MIC. These target values were highly variable, with the percentage coefficient of variation ranging between 1% and 132% for isolates having the same MIC. For 16/27 (59%) drug/bacteria combinations from all 10 drugs, the proposed/target STICs were higher than the highest MIC for bacteria isolates evaluated, while 6/27 (22.5%) were lower. Conclusions This research suggests that careful considerations related to selection of bacterial isolates for animal PK-PD studies could strengthen the STIC determination process.

Waack, Ursula↗

Reliability, stability during long-term storage, and intra-individual variation of circulating levels of osteopontin, osteoprotegerin, vascular endothelial growth factor-A, and interleukin-17A

Background: Studies in many populations have reported associations between circulating cytokine levels and various physiological or pathological conditions. However, the reliability of cytokine measurements in population studies, which measure cytokines in multiple assays over a prolonged period, has not been adequately examined; nor has stability during sample storage or intra-individual variation been assessed. Methods: We assessed (1) analytical reliability in short- and long-term repeated measurements; (2) stability and analytical reliability during long-term sample storage, and (3) variability within individuals over seasons, of four cytokines—osteopontin (OPN), osteoprotegerin (OPG), vascular endothelial growth factor-A (VEGF-A), and interleukin-17A (IL-17A). Measurements in plasma or serum samples were made with commercial kits according to standard procedures. Estimation was performed by fitting a random or mixed effects linear model on the log scale. Results: In repeated assays over a short period, OPN, OPG, and VEGF-A had acceptable reliability, with intra- and inter-assay coefficients of variation (CV) less than 0.11. Reliability of IL-17A was poor, with inter- and intra-assay CV 0.85 and 0.43, respectively. During long-term storage, OPG significantly decayed (-33% per year; 95% confidence interval [-54, -3.7]), but not OPN or VEGF-A (-0.3% or -6.3% per year, respectively). Intra- and inter-assay CV over a long period were comparable to that in a short period except for a slight increase in inter-assay CV of VEGF-A. Within-individual variation was small for OPN and VEGF-A, with intra-class correlations (ICC) 0.68 and 0.83, respectively, but large for OPG (ICC 0.11). Conclusions: We conclude that OPN and VEGF-A can be reliably measured in a large population, that IL-17A is suitable only for small experiments, and that OPG should be assessed with caution due to degradation during storage and intra-individual variation. The overall results of our study illustrate the need for validation under relevant conditions when measuring circulating cytokines in population studies.

60 APPLIED LIFE SCIENCES↗

A Method for Landsat and Sentinel 2 (HLS) BRDF Normalization

The Harmonized Landsat/Sentinel-2 (HLS) project aims to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2 remote sensing satellites. These satellites’ sampling characteristics provide nearly constant observation geometry and low illumination variation through the scene. However, the illumination variation throughout the year impacts the surface reflectance by producing higher values for low solar zenith angles and lower reflectance for large zenith angles. In this work, we present a model to derive the bidirectional reflectance distribution function (BRDF) normalization and apply it to the HLS product at 30m spatial resolution. It is based on the BRDF parameters estimated from the MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (M{O,Y}D09) at 1 km spatial resolution using the VJB method (Vermote et al., 2009). Unsupervised classification (segmentation) of HLS images is used to disaggregate the BRDF parameters to the HLS spatial resolution and to build a BRDF parameters database at HLS scale. We first test the proposed BRDF normalization for different solar zenith angles over two homogeneous sites, in particular one desert and one Peruvian Amazon forest. The proposed method reduces both the correlation with the solar zenith angle and the coefficient of variation (CV) of the reflectance time series in the red and near infrared bands to 4% in forest and keeps a low CV of 3% to 4% for the deserts. Additionally, we assess the impact of the view zenith angle (VZA) in an area of the Brazilian Amazon forest close to the equator, where impact of the angular variation is stronger because it occurs in the principal plane. The directional reflectance shows a strong dependency with the VZA. The current HLS BRDF correction reduces this dependency but still shows an under-correction, especially in the near infrared, while the proposed method shows no dependency with the view angles. We also evaluate the BRDF parameters using field surface albedo measurements as a reference over seven different sites of the US surface radiation budget observing network (SURFRAD) and five sites of the Australian OzFlux network.

Belen Franch↗

Surrogate model evaluation and building energy benchmarking for commercial buildings

Building energy consumption benchmarking involves challenges associated with various energy patterns for different building types; heating, ventilating, and air-conditioning (HVAC) system types; and climates. Given significant variation in energy use patterns, accurate prediction of long-term energy use using surrogate models remains challenging. Multiple linear regression (MLR) is commonly used for building energy benchmarking because of its simple structure; however, it lacks accuracy compared to other black-box models. Although many studies have compared surrogate models and offer guidance on model selection based on metrics, they do not provide detailed analysis on improving the surrogate model accuracy. In this paper, we implement a surrogate model using polynomial ridge regression (i.e., MLR with interaction terms combined with ridge regularization) for small office and retail strip mall buildings across six HVAC system types and all climate zones, for electricity and natural gas in baseline and proposed scenarios. A simulation workflow is developed using OpenStudio TM /EnergyPlus TM to generate simulation data using measures over a wide range of efficiency inputs. Enhancements based on statistical insights are used for improving the model accuracy using filters, input transformations, and change points. Surrogate models achieved average coefficient of variation of the root mean squared error (CVRMSE) values of 2.17, 1.06, 2.05, and 3.26 for proposed electricity, proposed natural gas, baseline electricity, and baseline natural gas, respectively, with enhancements reducing CVRMSE by an average of 14.9% across all combinations. We provide model interpretation via Shapley additive explanations to determine which input variables most influence energy consumption and provide supportive arguments for enhancements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Method to derive the infrared complex refractive indices n(λ) and k(λ) for organic solids from KBr pellet absorption measurements

Obtaining the complex refractive index vectors $n($$\tilde{v})$ and $k($$\tilde{v})$ allows calculation of the (infrared) reflectance spectrum that is obtained from a solid in any of its many morphological forms. Here, we report an adaptation to the KBr pellet technique using two gravimetric dilutions to derive quantitative $n($$\tilde{v})$/$k($$\tilde{v})$ for dozens of powders with greater repeatability. The optical constants of bisphenol A and sucrose are compared to those derived by other methods, particularly for powdered materials. The variability of the $k$ values for bisphenol A was examined by 10 individual measurements, showing an average coefficient of variation for $k$ peak heights of 5.6%. Though no established standards exist, the pellet-derived $k$ peak values of bisphenol A differ by 11% and 31% from their single-angle- and ellipsometry-derived values, respectively. These values provide an initial estimate of the precision and accuracy of complex refractive indices that can be derived using this method. Limitations and advantages of the method are discussed, the salient advantage being a more rapid method to derive $n$/$k$ for those species that do not readily form crystals or specular pellets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Seasonal and Interannual Variations of Evaporation and their Relations with Precipitation, Net Radiation, and Net Carbon Accumulation for the Gediz Basin Area

A model combining the rate of carbon assimilation with water and energy balance equations has been run using satellite and ancillary data for a period of 60 months (January 1986 to December 1990). Calculations for the Gediz basin area give mean annual evaporation as 395 mm, which is composed of 45% transpiration, 42% soil evaporation and 13% interception. The coefficient of interannual variation of evaporation is found to be 6%, while that for precipitation and net radiation are, respectively, 16% and 2%, illustrating that net radiation has an important effect in modulating interannual variation of evaporation. The mean annual water use efficiency (i.e., the ratio of net carbon accumulation and total evaporation) is ca. 1 g/sq m/mm, and has a coefficient of interannual variation of 5%. A comparison of the mean water use efficiency with field observations suggests that evaporation over the area is utilized well for biomass production. The reference crop evaporation for irrigated areas has annual mean and coefficient of variation as, respectively, 1176 mm and 3%. The total evaporation during three summer months of peak evaporation (June-August) is estimated to be about 575 mm for irrigated crops like maize and cotton. Seasonal variations of the fluxes are presented.

Choudhury, Bhaskar J.↗

Variation in Global Chemical Composition of PM2.5: Emerging Results from SPARTAN

The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM (sub 2.5). Our methods infer the spatial and temporal variability of PM (sub 2.5) in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM (sub 2.5), with a collocated nephelometer sampling air continuously. SPARTAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM (sub 2.5) and columnar aerosol optical depth (AOD). We have examined the chemical composition of PM (sub 2.5) at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2-26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM (sub 2.5) constituents across all sites (relative contribution plus or minus Standard Deviation) are ammoniated sulfate (20 percent plus or minus 11 percent), crustal material (13.4 percent plus or minus 9.9 percent), equivalent black carbon (11.9 percent plus or minus 8.4 percent), ammonium nitrate (4.7 percent plus or minus 3.0 percent), sea salt (2.3 percent plus or minus 1.6 percent), trace element oxides (1.0 percent plus or minus 1.1 percent), water (7.2 percent plus or minus 3.3 percent) at 35 percent relative humidity, and residual matter (40 percent plus or minus 24 percent). Analysis of filter samples reveals that several PM (sub 2.5) chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 microns per cubic meter (Buenos Aires, Argentina) to 17 microns per cubic meter (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 microns per cubic meter (Mammoth Cave, in summer) to 6.8 microns per cubic meter (Kanpur, dry season). Equivalent black carbon ranged from 0.7 microns per cubic meter (Mammoth Cave) to over 8 microns per cubic meter (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM (sub 2.5) (r squared equals 0.76, slope equals 1.12), daily sulfate (r squared equals 0.86, slope equals 1.03), and mean fractions of all major PM (sub 2.5) components (within 6 percent). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 percent for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn to Al ratios. The expected water contribution to aerosols is calculated via the hygroscopicity parameter kappa (sub v (volume)) for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 plus or minus 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM (sub 2.5) at 35 percent relative humidity by merging with nephelometer measurements. These hourly PM (sub 2.5) estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r squared equals 0.67 (number equals 3167), compared to r squared equals 0.62 when v (volume) was not considered. SPARTAN continues to provide an open-access database of PM (sub 2.5) compositional filter information and hourly mass collected from a global federation of instruments.

Snider, Graydon↗

Restoring freshwater habitat mosaics to promote resilience of vulnerable salmon populations

Phenotypic diversity and abundance drive salmon resilience in the face of increasing environmental variability. But what happens when human activities fundamentally alter the habitat complexity that drives this diversity? And how can we restore habitats to recover both diversity and abundance to support salmon persistence in a warming climate? Here, we looked at the impact of a large watershed restoration effort on the abundance and climate resilience of the three remaining core natural spring-run Chinook Salmon populations in the California Central Valley (Butte, Mill, and Deer Creek). Butte Creek fish, which have floodplain access, had higher overall productivity and faster juvenile growth compared with Mill and Deer Creek populations, and the proportion of floodplain inundation was positively correlated with Butte Creek adult abundance two years later. While Butte Creek exhibited significant increases in abundance post-restoration (~2000%), it generally exhibited lower phenotypic diversity and only a marginal increase in population stability after restoration based on the coefficient of variation (CV). In particular, Butte Creek salmon tended to exhibit larger drops in escapement following dry years (e.g., return years 2010, 2017) compared with Mill and Deer Creek populations, presumably due to limited inundation of its downstream floodplain. The late-migrating juvenile strategy (i.e., yearling), which disproportionately supported Mill and Deer Creek populations during droughts, was uncommon among Butte Creek adults (averaging 60% of returns for Mill and Deer Creek vs. 0.3% for Butte Creek). Increased spring-run stock complex stability was found, post-restoration, when combining the three spring-run populations (i.e., lower aggregate CV). However, among-river pairwise correlations also suggested increased synchronization in population abundances post-restoration, potentially due to increasing frequency and severity of extreme climatic events (e.g., droughts and ocean warming). This study underscores the importance of restoring a connected mosaic of aquatic habitats across modified landscapes, such as cold water refugia and floodplains, to preserve multiple (across-population) life history pathways for increasing salmon stock complex stability and abundance. These landscape-scale process-based habitat restoration efforts are likely to be crucial for the successful long-term recovery of vulnerable species in a rapidly changing climate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗