Comparison of multiple PM 2.5 exposure products for estimating health benefits of emission controls over New York State, USA
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This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify “Selection-Enriched Genomic Loci” (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity. Increasing the photosynthetic efficiency of algae during biomass production is perhaps the most critical hurdle for economically sustainable algal based biofuels. This presents unique challenges because modifications designed to increase photosynthesis often result in decreased fitness, due to production of toxic reactive oxygen species when photosynthesis is not adequately regulated. These problems are exacerbated under natural and outdoor production environments because of the complex nature of photosynthesis and the multifaceted interactions between genetic, environmental and physiological factors. Here, we demonstrate a high throughput biotechnological screening approach that simultaneously produces algal strains with highly increased autotrophic productivity and identifies genomic loci contributing to these improvements. Our results demonstrate that Chlamydomonas reinhardtii exhibits high directed evolutionary capacity readily accessed through breeding and selection.
The technique and uses of the multiple blade slurry (MBS) saw are considered. Multiple bands of steel are arranged in a frame and the frame is reciprocated with the steel bands to a workpiece, while simultaneously applying abrasive at the point of contact. The blades wear slots in the workpiece and progress through the piece resulting in several parts of wafers. The transition to MBA from diamond slicing is justified by savings resulting from minimized kerf losses, minimized subsurface damage, and improved surface quality off the saw. This allows wafering much closer to finished thickness specifications. The current state of the art MBS technology must be significantly improved if the low cost solar array (LSA) goals are to be attained. It is concluded that although MBS will never be the answer to every wafering requirement, the economical production of wafers to LSA project specifications will be achieved.
Consumer demand for sustainably produced agricultural products is increasing. One approach that can be used to evaluate and compare product sustainability is to conduct a life cycle analysis (LCA). The term LCA is broadly used to describe a suite of analytical resources and standardized methods. Life cycle analyses are a transdisciplinary tool which can and are used by all professions but work best when conducted by teams with diverse skills and backgrounds. The objective of this paper is to provide a primer on LCAs for the agricultural community and for LCA practitioners unfamiliar with agronomy. Agricultural LCAs can differ greatly because agricultural products have multiple end uses, complex socio-economic and environmental trade-offs, and can be generated using a variety of different practices, resources, and production systems. Through worldwide agricultural marketing, intricate agronomic supply chains and support systems have been developed to produce, store, and distribute agricultural products. In many situations, the production practices are not linked to the products consumers purchase. This limitation can be partially overcome by conducting an LCA, which is a systematic summation of the multiple environmental impacts associated with the production, use, and disposal of a product. However, the large number and types of analyses can make it difficult for non-practitioners and decision-makers to use and interpret LCA results. Finally, it is important for members of the agricultural community to be aware of these analyses and how they can be used and how they affect product markets.
Climate change is reshaping ecosystems, driving plants to adapt through leaf-trait plasticity that reflects strategies for growth and water use. Predicting biomass production and intrinsic water use efficiency (iWUE) remains challenging because of genetic, taxonomic, and environmental variability. Here, we used eastern cottonwood and Populus hybrids as a model system to test whether easily measurable leaf traits can serve as reliable predictors of performance, and whether adding stomatal and biochemical traits improves predictive power. Across two field sites in Mississippi, leaf mass per area (LMA), biomass production, iWUE, leaf area, and foliar nitrogen ( N %) differed significantly among taxa and sites, while other traits were conserved. Factorial analysis of mixed data (FAMD) revealed distinct clustering of taxa and sites, indicating coordinated variation among leaf and stomatal traits. Pairwise correlations highlighted fundamental trade-offs, with biomass positively related to LMA and petiole length but negatively associated with iWUE, N %, and carbon isotopic ratios (δ 13 C). Leaf temperature and leaf angle varied among taxa and were significantly correlated with LMA and petiole length, suggesting mechanisms of heat dissipation and leaf movability that link simple traits to gas exchange and productivity. Weighted multiple linear regression models explained 80%–91% of variation in biomass production and iWUE. Models using only LMA, petiole length, and stomatal metrics performed nearly as well as those incorporating N %, and δ 13 C, with complex traits adding approximately 10% explanatory power. These results demonstrate that simple morphological traits capture integrated functional trade-offs, while complex traits refine predictions. This tiered approach provides an efficient framework for selecting high-yielding, water-efficient genotypes of Populus and other hardwood species, offering practical pathways to enhance carbon uptake and iWUE under climate change.
Using the nucleon coalescence model based on kinetic freeze-out nucleons from the 3D MUSIC+UrQMD and the 2D VISHNU hybrid model with a crossover equation of state, we study the multiplicity dependence of deuteron ( d ) and triton ( t ) production from central to peripheral Au+Au collisions at s NN = 7.7, 14.5, 19.6, 27, 39, 62.4 and 200 GeV and Pb+Pb at s NN = 2.76 TeV, respectively. It is found that the ratio N t N p / N d 2 of the proton yield N p , deuteron yield N d and triton yield N t exhibits a scaling behavior in its multiplicity dependence, i.e., decreasing monotonically with increasing charged-particle multiplicity. A similar multiplicity scaling of this ratio is also found in the nucleon coalescence calculation based on kinetic freeze-out nucleons from a multiphase transport (AMPT) model. The scaling behavior of N t N p / N d 2 can be naturally explained by the interplay between the sizes of light nuclei and the nucleon emission source. We further argue that the multiplicity scaling of N t N p / N d 2 can be used to validate the production mechanism of light nuclei, and the collision energy dependence of this yield ratio can further serve as a baseline in the search for the QCD critical point in relativistic heavy-ion collisions.
The Data Assimilation Office (DAO) at Goddard Space Flight Center and the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) have produced multi-year global assimilations of historical data employing fixed analysis systems. These "reanalysis" products are ideally suited for studying short-term climatic variations. The availability of multiple reanalysis products also provides the opportunity to examine the uncertainty in the reanalysis data. The purpose of this document is to provide an updated estimate of seasonal and interannual variability based on the DAO and NCEP/NCAR reanalyses for the 15-year period 1980-1995. Intercomparisons of the seasonal means and their interannual variations are presented for a variety of prognostic and diagnostic fields. In addition, atmospheric potential predictability is re-examined employing selected DAO reanalysis variables.
Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall-triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select among a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity-duration thresholds. The average intensity, peak intensity, duration, and NOAA-Atlas return periods are compared ahead of reported landslides across the continental US and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real-time and post-processed satellite (IMERG), radar (MRMS), and gauge-based (NLDAS-2). Landslide-triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296mm with an average range of 51mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8262745mm/hr and as much as 57mm/hr. The two products more reliant upon ground-based observations (MRMS and NLDAS-2) performed better at identifying landslides according to published intensity duration storm thresholds, but all products exhibited hit-ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually-verified landslide locations. We recommend practitioners consider low-latency products like MRMS for investigating landslides, given their near-real time data availability and good performance in detecting landslides. Practitioners would be well-served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms.
The multiplicity dependence of jet production in pp collisions at the centre-of-mass energy of $\sqrt{s}$ = 13 TeV is studied for the first time. Jets are reconstructed from charged particles using the anti-$k_T$ algorithm with resolution parameters $\textit{R}$ varying from 0.2 to 0.7. The jets are measured in the pseudorapidity range |$η_{\text{jet}}$| < 0.9 – $\textit{R}$ and in the transverse momentum range 5 < $p^{ch}_{\text{T,jet}}$ < 140 GeV/c. The multiplicity intervals are categorised by the ALICE forward detector V0. The $p_T$ differential cross section of charged-particle jets are compared to leading order (LO) and next-to-leading order (NLO) perturbative quantum chromodynamics (pQCD) calculations. It is found that the data are better described by the NLO calculation, although the NLO prediction overestimates the jet cross section below 20 GeV/c. The cross section ratios for different $\textit{R}$ are also measured and compared to model calculations. These measurements provide insights into the angular dependence of jet fragmentation. The jet yield increases with increasing self-normalised charged-particle multiplicity. This increase shows only a weak dependence on jet transverse momentum and resolution parameter at the highest multiplicity. While such behaviour is qualitatively described by the present version of PYTHIA, quantitative description may require implementing new mechanisms for multi-particle production in hadronic collisions.
For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use‐specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based on autotrophic production, whereas phosphorus, dissolved organic carbon, and true color are used to classify TS based on both autotrophic and heterotrophic production. Both classification approaches aim to characterize an ecosystem's function broadly, but with varying degrees of autotrophic and heterotrophic processes considered in those characterizations. Moreover, differing classification schemes can create inconsistent interpretations of ecosystem integrity. For example, the US Clean Water Act focuses exclusively on algal threats to water quality, framed in terms of eutrophication in response to nutrient loading. This usage lacks information about non‐algal threats to water quality, such as dystrophication in response to dissolved organic carbon loading. Consequently, the TS classification schemes used to identify eutrophication and dystrophication may refer to ecosystems similarly (e.g., oligotrophic and eutrophic), yet these categories are derived from different proxies. These inconsistencies in TS classification schemes may be compounded when interdisciplinary projects employ varied TS frameworks. Even with these shortcomings, TS can still be used to distill information on complex aquatic ecosystem function into a set of generalizable expectations. The usefulness of distilling complex information into a TS index is substantial such that usage inconsistencies should be explicitly addressed and resolved. To emphasize the consequences of diverging TS classification schemes, we present three case studies for which an improved understanding of the TS concept advances freshwater research, management efforts, and interdisciplinary collaboration. To increase clarity in TS, the aquatic sciences could benefit from including information about the proxy variables, ecosystem type, as well as the spatiotemporal domains used to classify TS. As the field of aquatic sciences expands and climatic irregularity increases, we highlight the importance of re‐evaluating fundamental concepts, such as TS, to ensure their compatibility with evolving science.
Operational applications for Synthetic Aperture Radar (SAR) are under development around the world, driven by the free-and-open access of SAR C-band observations that Sentinel-1 of Copernicus has been providing since 2014. Groups like SERVIR, a joint initiative between NASA and USAID, are at the forefront of remote sensing applied uses, and have made many significant contributions to lower the barrier to access, process, and apply SAR for ecosystem services. A takeaway from the SERVIR experience in using SAR is the need to use the appropriate SAR polarimetric product. Radiometric Terrain Correction (RTC) is a key entry-level product for multiple applications that range from ecosystems to hazards. Many software packages exist to create RTC products from SLC or GRD-type Level-1 SAR data, some of which were released only recently, e.g. Interferometric SAR Computing Environment (ISCE) added an RTC module in April 2020. In addition, new versions of open source softwares are expected to address known issues from previous versions, such as Sentinel-1 Toolbox from the European Space Agency (SNAP-7). Despite the growing availability of RTC software solutions, little work has been done to identify differences between RTC products from different softwares. And to address the question, which open-source software produces the most accurate RTC product? This work evaluates Sentinel-1 RTC products created with three different softwares and approaches, including SNAP-7, ISCE-2, and a pseudo RTC product derived from GEE. The GAMMA-derived RTC product, a known optimal RTC and implemented by Alaska Satellite Facility (ASF), is used as a reference. Time series stacks over ten different sites representing varied terrain and ecosystems are evaluated. Products are evaluated for geolocation quality, absolute radiometric calibration, and for the fidelity of the radiometric terrain flattening. The results provide direct guidance and recommendations about the quality of the RTC products obtained from open source methods. This understanding is key to develop operational applications that rely on SAR Sentinel-1 data that need affordable and scalable solutions.
Prompt D meson and non-prompt J/ψ yields are studied as a function of the multiplicity of charged particles produced in inelastic proton-proton collisions at a centre-of-mass energy of √s = 7 TeV. The results are reported as a ratio between yields in a given multiplicity interval normalised to the multiplicity-integrated ones (relative yields). They are shown as a function of the multiplicity of charged particles normalised to the average value for inelastic collisions (relative charged-particle multiplicity). D 0 , D + and D *+ mesons are measured in five p T intervals from 1 GeV/c to 20 GeV/c and for |y| < 0.5 via their hadronic decays. The D-meson relative yield is found to increase with increasing charged-particle multiplicity. For events with multiplicity six times higher than the average multiplicity of inelastic collisions, a yield enhancement of a factor about 15 relative to the multiplicity-integrated yield in inelastic collisions is observed. The yield enhancement is independent of transverse momentum within the uncertainties of the measurement. The D0-meson relative yield is also measured as a function of the relative multiplicity at forward pseudo-rapidity. The non-prompt J/ψ, i.e. the B hadron, contribution to the inclusive J/ψ production is measured in the di-electron decay channel at central rapidity. It is evaluated for p T > 1.3 GeV/c and |y| < 0.9, and extrapolated to p T > 0. The fraction of non-prompt J/ψ in the inclusive J/ψ yields shows no dependence on the charged-particle multiplicity at central rapidity. Charm and beauty hadron relative yields exhibit a similar increase with increasing charged-particle multiplicity. The measurements are compared to PYTHIA 8, EPOS 3 and percolation calculations.
The primary objective of this project was to leverage the Big Area Additive Manufacturing (BAAM) process and materials into a long term, quick change tooling concept to drastically reduce product lead and development timelines and costs. Current refrigeration foam molds are complicated to manufacture involving casting several aluminum parts in an approximate shape, machining components of the molds and post fitting and shimming of the parts in an articulated fixture. The total process timeline can take over 6 months. The foaming process is slower than required for production, therefore multiple fixtures, 10 to 27, are required per refrigerator model. Molds are particular to a specific product configuration making mixed model assembly challenging for sequencing, mold changes or auto changeover features. The initial goal was to create a tool leveraging the ORNL materials and additive process to build a tool in 4 to 6 weeks or less. A secondary goal was to create common fixture cores and provide lightweight fixture sections that could be revised in a very short time to increase equipment flexibility reduce lead times, lower the barriers to first production trials, and reduce tooling costs.
This presentation discusses a NASA Stennis Space Center project in which NASA-supported satellite and aerial data is being used to aid state and federal agencies in restoring the Mississippi barrier islands. Led by the Applied Science and Technology Project Office (ASTPO), this project will produce geospatial information products from multiple NASA-supported data sources, including Landsat, ASTER, and MODIS satellite data as well as ATLAS multispectral, CAMS multispectral, AVIRIS hyperspectral, EAARL, and other aerial data. Project objectives include the development and testing of a regional sediment transport model and the monitoring of barrier island restoration efforts through remote sensing. Barrier islands provide invaluable benefits to the State of Mississippi, including buffering the mainland from storm surge impacts, providing habitats for valuable wildlife and fisheries habitat, offering accessible recreational opportunities, and preserving natural environments for educating the public about coastal ecosystems and cultural resources. Unfortunately, these highly valued natural areas are prone to damage from hurricanes. For example, Hurricane Camille in 1969 split Ship Island into East and West Ship Island. Hurricane Georges in 1998 caused additional land loss for the two Ship Islands. More recently, Hurricanes Ivan, Katrina, Rita, Gustav, and Ike impacted the Mississippi barrier islands. In particular, Hurricane Katrina caused major damage to island vegetation and landforms, killing island forest overstories, overwashing entire islands, and causing widespread erosion. In response, multiple state and federal agencies are working to restore damaged components of these barrier islands. Much of this work is being implemented through federally funded Coastal Impact Assessment and Mississippi Coastal Improvement programs. One restoration component involves the reestablishment of the island footprints to that in 1969. Our project will employ NASA remote sensing data and products to support these federally funded efforts on multiple fronts. Landsat and ASTER data is being analyzed to assess changes in barrier island land cover over the last 35 years. ASTER, SRTM, and EAARL terrain products and other NASA airborne imagery are being applied in assessing changes in barrier island geomorphology and geospatial extent. MODIS data is being examined as a tool for sediment transport modeling by supplying geospatial data that quantifies in-water sediment concentrations. MODIS satellite data is being assessed for monitoring changes in the spatial extent of individual barrier islands. Results thus far indicate that NASA data products are useful in assessing barrier island conditions and changes. This value is enhanced with additional historical geospatial data, commercial high resolution satellite data, other non-NASA aerial imagery, and field survey data. The project s products are relevant to the Gulf of Mexico Alliance priority issues, including coastal habitat conservation, restoration and coastal community resilience. Such products will be available to state and federal agencies involved with coastal restoration. Potential end-users of these products include the National Park Service, U.S. Geological Survey, U.S. Army Corps of Engineers, Environmental Protection Agency, Mississippi Department of Environmental Quality, and Mississippi Department of Marine Resources.
This work addresses the two great challenges of the spark plasma sintering (SPS) process: The sintering of complex shapes and the simultaneous production of multiple parts. A new controllable interface method is employed to concurrently consolidate two nickel gear shapes by SPS. A graphite deformable sub-mold is specifically designed for the mutual densification of both complex parts in a unique 40 mm powder deformation space. An energy efficient SPS configuration is developed to allow the sintering of a large-scale powder assembly under electric current lower than 900 A. The stability of the developed process is studied by electro-thermal-mechanical (ETM) simulation. The ETM simulation reveals that homogeneous densification conditions can be attained by inserting an alumina powder at the sample/punches interfaces, enabling the energy efficient heating and the thermal confinement of the nickel powder. Finally, the feasibility of the fabrication of the two near net shape gears with a very homogeneous microstructure is demonstrated.
A new Monte Carlo code has been written to simulate the response of the new University of California double scatter gamma ray telescope. This package of modular software routines, written in VAX FORTRAN 77 simulates the detection of 0.1 to 35 MeV gamma rays. The new telescope is flown from high altitude balloons to measure medium energy gamma radiation from astronomical sources. This paper presents (1) the basic physics methods in the code, and (2) the predicted response functions of the telescope. Gamma ray processes include Compton scattering, pair production and photoelectric absorption in plastic scintillator, NaI(Tl) and aluminum. Electron transport processes include ionization energy loss, multiple scattering, production of bremsstrahlung photons and positron annihilation.