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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Functional and structural basis of E. coli enolase inhibition by SF2312: a mimic of the carbanion intermediate

Many years ago, the natural secondary metabolite SF2312, produced by the actinomycete Micromonospora, was reported to display broad spectrum antibacterial properties against both Gram-positive and Gram-negative bacteria. Recent studies have revealed that SF2312, a natural phosphonic acid, functions as a potent inhibitor of human enolase. The mechanism of SF2312 inhibition of bacterial enolase and its role in bacterial growth and reproduction, however, have remained elusive. In this work, we detail a structural analysis of E. coli enolase bound to both SF2312 and its oxidized imide-form. Our studies support a model in which SF2312 acts as an analog of a high energy intermediate formed during the catalytic process. Biochemical, biophysical, computational and kinetic characterization of these compounds confirm that altering features characteristic of a putative carbanion (enolate) intermediate significantly reduces the potency of enzyme inhibition. When SF2312 is combined with fosfomycin in the presence of glucose-6 phosphate, significant synergy is observed. This suggests the two agents could be used as a potent combination, targeting distinct cellular mechanism for the treatment of bacterial infections. Together, our studies rationalize the structure-activity relationships for these phosphonates and validate enolase as a promising target for antibiotic discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Interactions between urban heat islands and heat waves

Heat waves (HWs) are among the most damaging climate extremes to human society. Climate models consistently project that HW frequency, severity, and duration will increase markedly over this century. For urban residents, the urban heat island (UHI) effect further exacerbates the heat stress resulting from HWs. Here we use a climate model to investigate the interactions between the UHI and HWs in 50 cities in the United States under current climate and future warming scenarios. We examine UHI 2m (defined as urban-rural difference in 2m-height air temperature) and UHI s (defined as urban-rural difference in radiative surface temperature). Our results show significant sensitivity of the interaction between UHI and HWs to local background climate and warming scenarios. Sensitivity also differs between daytime and nighttime. During daytime, cities in the temperate climate region show significant synergistic effects between UHI and HWs in current climate, with an average of 0.4 K higher UHI 2m or 2.8 K higher UHI s during HWs than during normal days. These synergistic effects, however, diminish in future warmer climates. In contrast, the daytime synergistic effects for cities in dry regions are insignificant in the current climate, but emerge in future climates. At night, the synergistic effects are similar across climate regions in the current climate, and are stronger in future climate scenarios. We use a biophysical factorization method to disentangle the mechanisms behind the interactions between UHI and HWs that explain the spatial-temporal patterns of the interactions. Results show that the difference in the increase of urban versus rural evaporation and enhanced anthropogenic heat emissions (air conditioning energy use) during HWs are key contributors to the synergistic effects during daytime. The contrast in water availability between urban and rural land plays an important role in determining the contribution of evaporation. At night, the enhanced release of stored and anthropogenic heat during HWs are the primary contributors to the synergistic effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CO 2 fertilization of crops offsets yield losses due to future surface ozone damage and climate change

Tropospheric ozone (O 3 ) is harmful to plant productivity and negatively impacts crop yields. O3 concentrations are projected to decrease globally in the optimistic Representative Concentration Pathway of 2.6 W m –2 (RCP2.6) but increase globally following the high-emission scenario under the RCP8.5, with substantial implications for global food security. The damaging effect of O 3 on future crop yield is affected by CO 2 fertilization and climate change, and their interactions for RCP scenarios have yet to be quantified. In this study, we used the Joint UK Land Environment Simulator modified to include crops (JULES-crop) to quantify the impacts, and relative importance of present-day and future O3, CO 2 concentration and meteorology on crop production at the regional scale until 2100 following RCP2.6 and RCP8.5 scenarios. We focus on eight major crop-producing regions that cover the production of wheat, soybean, maize, and rice. Our results show that CO 2 alone has the largest effect on regional yields, followed by climate and O 3 . However, the CO 2 fertilization effect is offset by the negative impact of tropospheric O 3 in regions with high O 3 concentrations, such as South Asia and China. Simulated crop yields in 2050 were compared with Food and Agriculture Organisation (FAO) statistics to investigate the differences between a socioeconomic and a biophysical process-based approach. Results showed that FAO estimates are closer to our JULES-crop RCP8.5 scenario. This study demonstrates that air pollution could be the biggest threat to future food production and highlights an urgent policy need to mitigate the threat of climate change and O 3 pollution on food security.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Janus: A Python Package for Agent-Based Modeling of Land Use and Land Cover Change

Janus is an open source Python package for agent-based modeling (ABM) of land use and land cover change (LULCC). Many ABMs of LULCC have been created across platforms, some of which are not ideal for large scale, high resolution scenarios. This model provides a simple object-oriented framework for creating ABMs specific to LULCC. The organizational philosophy of the modeling framework is to create software objects (agents) that are associated with specific and contextual attributes which are isolated from where those agents exist in the spatial setting of the model, yet provide clear linkages between the agent, their environment, and other agents in the simulation. In this way, the framework allows for assembly of LULCC ABMs with low (programmatic) overhead, making the models extensible and providing clear mechanisms for integrating them with process-oriented biophysical models. Provided with Janus is a suite of geospatial data preprocessing tools that can use arbitrary land cover products as an input. Crop choice decisions are based on potential crop prices, these can be created synthetically, or drawn from integrated human-Earth systems models such as the GCAM. Janus is publicly accessible through GitHub and provides an example dataset for testing.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

Imhoff, Marc L.↗
NASA NTRS2010

Irrigation Requirement Estimation Using Vegetation Indices and Inverse Biophysical Modeling

We explore an inverse biophysical modeling process forced by satellite and climatological data to quantify irrigation requirements in semi-arid agricultural areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation and climate, and non-equilibrium, water added through irrigation. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation. The amount of water required over and above precipitation is considered as an irrigation requirement. For July, results show that spray irrigation resulted in an additional amount of water of 1.3 mm per occurrence with a frequency of 24.6 hours. In contrast, the drip irrigation required only 0.6 mm every 45.6 hours or 46% of that simulated by the spray irrigation. The modeled estimates account for 87% of the total reported irrigation water use, when soil salinity is not important and 66% in saline lands.

Bounoua, Lahouari↗
NASA NTRS2014

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve substantially the climate, crop, and economic simulation tools that are used to characterize the agricultural sector, to assess future world food security under changing climate conditions, and to enhance adaptation capacity both globally and regionally. To understand better and improve the modeled crop responses, AgMIP has conducted detailed crop model intercomparisons at closely observed field sites for wheat (Asseng et al., 2013), rice (Li et al., in review), maize (Bassu et al., 2014), and sugarcane (Singels et al., 2013). A coordinated modeling exercise was one of the original motivations for AgMIP, and C3MP provides rapid estimation of crop responses to CO2, water, and temperature (CTW) changes, adding dimension and insight into the crop model intercomparisons, while facilitating interactions within the global community of modelers. C3MP also contributes a fast-track, multi-model climate sensitivity assessment for the AgMIP climate and crop modeling teams on Research Track 2 (Fig. 1), which seeks to understand the impact of projected climatic changes on crop production and food security (Rosenzweig et al., 2013; Ruane et al., 2014).

agriculture↗
DOE OSTI2021

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗
DOE OSTI2019

Development and Verification of a Numerical Library for Solving Global Terrestrial Multiphysics Problems

Abstract Current generation Land Surface Models (LSMs) routinely simulate many nonlinear multiphysics processes. The complexity of future generation LSMs is expected to increase as critical new biophysical and biogeochemical processes are incorporated. Current generation LSMs have several shortcomings including the lack of robust numerical methods to solve discretized equations, monolithic software design that hinders testing of a process representation in isolation from other components, and absence of a flexible coupling framework to solve tightly coupled multiphysics problems. While the LSMs community vigorously evaluates the accuracy of the conceptual model to represent reality (validation), the accuracy of the numerical implementation of the conceptual model (verification) is seldom examined. Method of Manufactured Solutions is a technique for verifying complex codes when analytical solutions are unavailable. In this work, we present a stand‐alone, open source numerical library for solving global terrestrial multiphysics processes that includes a flexible coupling framework. Robust numerical solution for linear and nonlinear equations is provided via the Portable, Extensible Toolkit for Scientific Computation library. We verify the numerical library using Method of Manufactured Solutions for a range of problems comprising single and multiphysics steady state problems that are applied in one or multiple physical domains. This work provides an example of incorporating code verification as an integral part of Land Surface Model development activities.

58 GEOSCIENCES↗
NASA NTRS1993

How do plant cell walls extend?

This article briefly summarizes recent work that identifies the biophysical and biochemical processes that give rise to the extension of plant cell walls. I begin with the biophysical notion of stress relaxation of the wall and follow with recent studies of wall enzymes thought to catalyze wall extension and relaxation. Readers should refer to detailed reviews for more comprehensive discussion of earlier literature (Taiz, 1984; Carpita and Gibeaut, 1993; Cosgrove, 1993).

Review, Tutorial↗
DOE OSTI2025

Mining Thermophile Photosynthesis Genes: A Synthetic Operon Expressing Chloroflexota Species Reaction Center Genes in Rhodobacter sphaeroides

Photosynthesis is the foundation of the vast majority of life systems, and is therefore the most important bioenergetic process on earth. The greatest diversity of photosynthetic systems is found in microorganisms. However, our understanding of the biophysical and biochemical processes that transduce light into chemical energy is derived from a relatively small subset of proteins from microbes that are amenable to cultivation, in contrast to the huge number of predicted proteins that catalyze the initial photochemical reactions deposited in databases, such as from metagenomics. We describe the use of a Rhodobacter sphaeroides laboratory strain for the expression of heterologous photosynthesis genes to demonstrate the feasibility of mining this resource, focusing on hot spring Chloroflexota gene sequences. Using a synthetic operon of genes, we produced a photochemically active complex of reaction center proteins in our biological system. We also present bioinformatic analyses of anoxygenic type II reaction center sequences from metagenomic samples collected from hot (42–90 °C) springs available through the JGI IMG database, to generate a resource of diverse sequences that are potentially adapted to photosynthesis at such temperatures. These data provide a view into the natural diversity of anoxygenic photosynthesis, through a lens focused on high-temperature environments. The approach we took to express such genes can be applied for potential biotechnology purposes as well as for studies of fundamental catalytic properties of these heretofore inaccessible protein complexes.

Chloroflexota↗
DOE OSTI2019

Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models

Abstract. Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models. EcoPAD (v1.0) is a web-based software system that automates data transfer and processing from sensor networks to ecological forecasting through data management, model simulation, data assimilation, forecasting, and visualization. It facilitates interactive data–model integration from which the model is recursively improved through updated data while data are systematically refined under the guidance of model. EcoPAD (v1.0) relies on data from observations, process-oriented models, DA techniques, and the web-based workflow. We applied EcoPAD (v1.0) to the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in northern Minnesota. The EcoPAD-SPRUCE realizes fully automated data transfer, feeds meteorological data to drive model simulations, assimilates both manually measured and automated sensor data into the Terrestrial ECOsystem (TECO) model, and recursively forecasts the responses of various biophysical and biogeochemical processes to five temperature and two CO 2 treatments in near-real time (weekly). Forecasting with EcoPAD-SPRUCE has revealed that mismatches in forecasting carbon pool dynamics are more related to model (e.g., model structure, parameter, and initial value) than forcing variables, opposite to forecasting flux variables. EcoPAD-SPRUCE quantified acclimations of methane production in response to warming treatments through shifted posterior distributions of the CH 4 :CO 2 ratio and the temperature sensitivity ( Q 10 ) of methane production towards lower values. Different case studies indicated that realistic forecasting of carbon dynamics relies on appropriate model structure, correct parameterization, and accurate external forcing. Moreover, EcoPAD-SPRUCE stimulated active feedbacks between experimenters and modelers to identify model components to be improved and additional measurements to be taken. It has become an interactive model–experiment (ModEx) system and opens a novel avenue for interactive dialogue between modelers and experimenters. Altogether, EcoPAD (v1.0) acts to integrate multiple sources of information and knowledge to best inform ecological forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Biocompatible surface functionalization architecture for a diamond quantum sensor

Significance Diamond-based quantum sensing enables nanoscale measurements of biological systems with unprecedented sensitivity. Potential applications of this emerging technology range from the investigation of fundamental biological processes to the development of next-generation medical diagnostics devices. One of the main challenges faced by bioquantum sensing is the need to interface quantum sensors with biological target systems. Specifically, such an interface needs to maintain the highly fragile quantum states of our sensor and at the same time be able to fish intact biomolecules out of solution and immobilize them on our quantum sensor surface. Our work overcomes these challenges by combining tools from quantum engineering, single-molecule biophysics, and material processing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Global Market and Economic Welfare Implications of Changes in Agricultural Yields Due to Climate Change

The economic welfare effects of climate change on global agriculture will be mediated by several complex biophysical and economic processes. For a given emissions scenario, these include: (1) the response of the climate system to anthropogenic forcing, (2) the response of crop yields to climate system and carbon dioxide changes, given baseline improvements in crop yields, (3) the response of agricultural markets to crop yield changes, and (4) the economic welfare implications of such market responses. In this paper, we use information about the first two processes from available climate-crop model comparison studies to analyze implications for the third and fourth processes. Applying the range of crop yield changes in a Global Integrated Assessment Model (GCAM) highlights several important economic relationships. First, we find a consistent relationship between global cropland area and yield change that is approximately orthogonal to the relationship between regional cropland area and yield change. Second, we find that the change in economic welfare, expressed as total surplus change per unit economic output, peaks during the 21st century. Third, we find that, at the global level, changes in yield affect both producer surplus and consumer surplus. Specifically, surplus changes to producers and consumers are always opposite in sign, although which economic actors gain or lose varies with the sign of yield change for any given commodity. Taken together, these results contribute to a growing body of research on climate-induced changes on agriculture by highlighting several economic relationships that are robust to differences in the underlying biophysical responses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

biogeochemistry↗
DOE OSTI2021

Leaf 13 C data constrain the uncertainty of the carbon dynamics of temperate forest ecosystems

Stable carbon isotope discrimination occurred in plant biophysical and biogeochemical processes can help understand plant physiology and soil biogeochemistry with respect to carbon cycling. Here, we incorporated the photosynthetic carbon isotope discrimination into a process-based land surface model (iTEM) to test if stable carbon isotope composition (δ 13 C) can impose additional constraint on model parameters. Sequential data assimilation was implemented at six eddy covariance flux tower sites using carbon flux observations including gross primary productivity (GPP) and net ecosystem exchange (NEE) with and without considering foliar δ 13 C (δ 13 C f ) measurement constraints, respectively. Our model-data fusion showed that δ 13 C f can provide useful constraint on photosynthetic (V cmax25 , the maximum rate of carboxylation at 25°C) and stomatal (g1, the slope of stomatal function) parameters as well as the posterior carbon fluxes. When including δ 13 C f measurement, g1 spatially varies among the six sites and is significantly correlated with annual precipitation. We incorporated the statistical relationship between g1 and annual precipitation into iTEM, which is then used to quantify the regional carbon dynamic in temperate forest ecosystems of the Northern Hemisphere. Compared with the simulation only conditioned on carbon flux observations, regional carbon flux estimations performed slightly better against the FLUXCOM products and the uncertainties of modeled carbon fluxes were reduced by 27%. Our study demonstrated that δ 13 C f data constrains carbon flux uncertainties across space.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

How much of the world’s land has been urbanized, really? A hierarchical framework for evading confusion

Urbanization has transformed the world’s landscapes, resulting in a series of ecological and environmental problems. To assess urbanization impacts and improve sustainability, one of the first questions that we must address is: how much of the world’s land has been urbanized? Unfortunately, the estimates of the global urban land reported in the literature vary widely from less than 1% to 3% primarily because different definitions of urban land were used. To evade confusion, here we propose a hierarchical framework for representing and communicating the spatial extent of the world’s urbanized land at the global, regional, and more local levels. The hierarchical framework consists of three spatially nested definitions: “urban area” that is delineated by administrative boundaries, “built-up area” that is dominated by artificial surfaces, and “impervious surface area” that is devoid of life. These are really three different measures of urbanization. In 2010, the global urban land was close to 3%, the global built-up area was 0.65%, and the global impervious surface area was 0.45%, of the word’s total land area (excluding Antarctica and Greenland). We argue that this hierarchy of urban land measures, in particular the ratios between them, can also facilitate better understanding the biophysical and socioeconomic processes and impacts of urbanization.

Urbanization Global urban land Urban area Built-up↗