Effect of high temperature heat treatments on the quality factor of a large-grain superconducting radio-frequency niobium cavity

Large-grain Nb has become a viable alternative to fine-grain Nb for the fabrication of superconducting radio-frequency cavities. In this contribution we report the results from a heat treatment study of a large-grain 1.5 GHz single-cell cavity made of "medium purity" Nb. The baseline surface preparation prior to heat treatment consisted of standard buffered chemical polishing. The heat treatment in the range 800 - 1400 C was done in a newly designed vacuum induction furnace. Q0 values of the order of 2x1010 at 2.0 K and peak surface magnetic field (Bp) of 90 mT were achieved reproducibly. A Q0-value of (5+-1)1010 at 2.0 K and Bp = 90 mT was obtained after heat treatment at 1400 C. This is the highest value ever reported at this temperature, frequency and field. Samples heat treated with the cavity at 1400 C were analyzed by secondary ion mass spectrometry, secondary electron microscopy, energy dispersive X-ray, point contact tunneling and X-ray diffraction and revealed a complex surface composition which includes titanium oxide, increased carbon and nitrogen content but reduced hydrogen concentration compared to a non heat-treated sample

Effect of High Temperature Heat Treatments on the Quality Factor of a Large-grain Superconducting Radio-frequency Niobium Cavity

Large-grain Nb has become a viable alternative to fine-grain Nb for the fabrication of superconducting radio-frequency cavities. In this contribution we report the results from a heat treatment study of a large-grain 1.5 GHz single-cell cavity made of “medium purity” Nb. The baseline surface preparation prior to heat treatment consisted of standard buffered chemical polishing. The heat treatment in the range 800–1400°C was done in a newly designed vacuum induction furnace. Q0 values of the order of 2×1010 at 2.0 K and peak surface magnetic field (Bp) of 90 mT were achieved reproducibly. A Q0 value of (5±1)×1010 at 2.0 K and Bp=90  mT was obtained after heat treatment at 1400°C. This is the highest value ever reported at this temperature, frequency, and field. Samples heat treated with the cavity at 1400°C were analyzed by secondary ion mass spectrometry, x-ray photoelectron spectroscopy, energy dispersive x ray, point-contact tunneling, and x-ray diffraction, and revealed a complex surface composition which includes titanium oxide, increased carbon, and nitrogen content but reduced hydrogen concentration compared to a non-heat-treated sample

Amazon rainforests green-up with sunlight in dry season

Metabolism and phenology of Amazon rainforests significantly influence global dynamics of climate, carbon and water, but remain poorly understood. We analyzed Amazon vegetation phenology at multiple scales with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements from 2000 to 2005. MODIS Enhanced Vegetation Index (EVI, an index of canopy photosynthetic capacity) increased by 25% with sunlight during the dry season across Amazon forests, opposite to ecosystem model predictions that water limitation should cause dry season declines in forest canopy photosynthesis. In contrast to intact forests, areas converted to pasture showed dry-season declines in EVI-derived photosynthetic capacity, presumably because removal of deep-rooted forest trees reduced access to deep soil water. Local canopy photosynthesis measured from eddy flux towers in both a rainforest and forest conversion site confirm our interpretation of satellite data, and suggest that basin-wide carbon fluxes can be constrained by integrating remote sensing and local flux measurements

Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data

Monitoring and understanding climate-induced changes in the boreal and arctic vegetation is critical to aid in prognosticating their future. Weused a 33 year (1982-2014) long record of satellite observations to robustly assess changes in metrics of growing season (onset: SOS, end: EOS and length: LOS) and seasonal total gross primary productivity. Particular attention was paid to evaluating the accuracy of these metrics by comparing them to multiple independent direct and indirect growing season and productivity measures. These comparisons reveal that the derived metrics capture the spatio-temporal variations and trends with acceptable significance level (generally p < 0.05). We find that LOS has lengthened by 2.60 d dec(-1) (p < 0.05) due to an earlier onset of SOS (-1.61 d dec(-1), p < 0.05) and a delayed EOS (0.67 d dec(-1), p < 0.1) at the circumpolar scale over the past three decades. Relatively greater rates of changes in growing season were observed in Eurasia (EA) and in boreal regions than in North America (NA) and the arctic regions. However, this tendency of earlier SOS and delayed EOS was prominent only during the earlier part of the data record (1982-1999). During the later part (2000-2014), this tendency was reversed, i.e. delayed SOS and earlier EOS. As for seasonal total productivity, we find that 42.0% of northern vegetation shows a statistically significant (p < 0.1) greening trend over the last three decades. This greening translates to a 20.9% gain in productivity since 1982. In contrast, only 2.5% of northern vegetation shows browning, or a 1.2% loss of productivity. These trends in productivity were continuous through the period of record, unlike changes in growing season metrics. Similarly, we find relatively greater increasing rates of productivity in EA and in arctic regions than in NA and the boreal regions. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation during last three decades

Decadal variations in NDVI and food production in India

In this study we use long-term satellite, climate, and crop observations to document the spatial distribution of the recent stagnation in food grain production affecting the water-limited tropics (WLT), a region where 1.5 billion people live and depend on local agriculture that is constrained by chronic water shortages. Overall, our analysis shows that the recent stagnation in food production is corroborated by satellite data. The growth rate annually integrated vegetation greenness, a measure of crop growth, has declined significantly (p &lt; 0.10) in 23% of the WLT cropland area during the last decade, while statistically significant increases in the growth rates account for less than 2%. In most countries, the decade-long declines appear to be primarily due to unsustainable crop management practices rather than climate alone. One quarter of the statistically significant declines are observed in India, which with the world’s largest population of food-insecure people and largest WLT croplands, is a leading example of the observed declines. Here we show geographically matching patterns of enhanced crop production and irrigation expansion with groundwater that have leveled off in the past decade. We estimate that, in the absence of irrigation, the enhancement in dry-season food grain production in India, during 1982–2002, would have required an increase in annual rainfall of at least 30% over almost half of the cropland area. This suggests that the past expansion of use of irrigation has not been sustainable. We expect that improved surface and groundwater management practices will be required to reverse the recent food grain production declines

Sulfur-mediated electron shuttling during bacterial iron reduction

Microbial reduction of ferric iron [Fe(III)] is an important biogeochemical process in anoxic aquifers. Depending on groundwater pH, dissimilatory metal-reducing bacteria can also respire alternative electron acceptors to survive, including elemental sulfur (S0). To understand the interplay of Fe/S cycling under alkaline conditions, we combined thermodynamic geochemical modeling with bioreactor experiments using Shewanella oneidensis MR-1. Under these conditions, S. oneidensis can enzymatically reduce S0 but not goethite (α-FeOOH). The HS– produced subsequently reduces goethite abiotically. Because of the prevalence of alkaline conditions in many aquifers, Fe(III) reduction may thus proceed via S0-mediated electron-shuttling pathways

Diminished temperature and vegetation seasonality over northern high latitudes

Global temperature is increasing, especially over northern lands (>50° N), owing to positive feedbacks1. As this increase is most pronounced in winter, temperature seasonality (ST)—conventionally defined as the difference between summer and winter temperatures—is diminishing over time2, a phenomenon that is analogous to its equatorward decline at an annual scale. The initiation, termination and performance of vegetation photosynthetic activity are tied to threshold temperatures3. Trends in the timing of these thresholds and cumulative temperatures above them may alter vegetation productivity, or modify vegetation seasonality (SV), over time. The relationship between ST and SV is critically examined here with newly improved ground and satellite data sets. The observed diminishment of ST and SV is equivalent to 4° and 7° (5° and 6°) latitudinal shift equatorward during the past 30 years in the Arctic (boreal) region. Analysis of simulations from 17 state-of-the-art climate models4 indicates an additional STdiminishment equivalent to a 20° equatorward shift could occur this century. How SV will change in response to such large projected ST declines and the impact this will have on ecosystem services5 are not well understood. Hence the need for continued monitoring6 of northern lands as their seasonal temperature profiles evolve to resemble thosefurther south.Lopullinen vertaisarvioitu käsikirjoitu

Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022

Leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) are critical biophysical parameters for the characterization of terrestrial ecosystems. Long-term global LAI/FPAR products, such as the moderate resolution imaging spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS), provide the fundamental dataset for accessing vegetation dynamics and studying climate change. However, existing global LAI/FPAR products suffer from several limitations, including spatial–temporal inconsistencies and accuracy issues. Considering these limitations, this study develops a sensor-independent (SI) LAI/FPAR climate data record (CDR) based on Terra-MODIS/Aqua-MODIS/VIIRS LAI/FPAR standard products. The SI LAI/FPAR CDR covers the period from 2000 to 2022, at spatial resolutions of 500 m/5 km/0.05∘, 8 d/bimonthly temporal frequencies and available in sinusoidal and WGS1984 projections. The methodology includes (i) comprehensive analyses of sensor-specific quality assessment variables to select high-quality retrievals, (ii) application of the spatial–temporal tensor (ST-tensor) completion model to extrapolate LAI and FPAR beyond areas with high-quality retrievals, (iii) generation of SI LAI/FPAR CDR in various projections and various spatial and temporal resolutions, and (iv) evaluation of the CDR by direct comparisons with ground data and indirectly through reproducing results of LAI/FPAR trends documented in the literature. This paper provides a comprehensive analysis of each step involved in the generation of the SI LAI/FPAR CDR, as well as evaluation of the ST-tensor completion model. Comparisons of SI LAI (FPAR) CDR with ground truth data suggest an RMSE of 0.84 LAI (0.15 FPAR) units with R2 of 0.72 (0.79), which outperform the standard Terra/Aqua/VIIRS LAI (FPAR) products. The SI LAI/FPAR CDR is characterized by a low time series stability (TSS) value, suggesting a more stable and less noisy dataset than sensor-dependent counterparts. Furthermore, the mean absolute error (MAE) of the CDR is also lower, suggesting that SI LAI/FPAR CDR is comparable in accuracy to high-quality retrievals. LAI/FPAR trend analyses based on the SI LAI/FPAR CDR agree with previous studies, which indirectly provides enhanced capabilities to utilize this CDR for studying vegetation dynamics and climate change. Overall, the integration of multiple satellite data sources and the use of advanced gap filling modeling techniques improve the accuracy of the SI LAI/FPAR CDR, ensuring the reliability of long-term vegetation studies, global carbon cycle modeling, and land policy development for informed decision-making and sustainable environmental management. The SI LAI/FPAR CDR is open access and available under a Creative Commons Attribution 4.0 License at https://doi.org/10.5281/zenodo.8076540 (Pu et al., 2023a).</p