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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 415 records · Page 23

A Regional Map of Mangrove Extent for Myanmar, Thailand, and Cambodia Shows Losses of 44% By 1996

Southeast Asia is home to some of the planet’s most carbon-dense and biodiverse mangrove ecosystems. There is still much uncertainty with regards to the timing and magnitude of changes in mangrove cover over the past 50 years. While there are several regional to global maps of mangrove extent in Southeast Asia over the past two decades, data prior to the mid-1990s is limited due to the scarcity of Earth Observation data of sufficient quality and the historical limitations to publicly available EO. We present a classification of mangrove extent using Landsat 1-2 MSS Tier 2 data from 1972-1977 for three Southeast Asian countries: Myanmar, Thailand, and Cambodia. Mangrove extent land cover maps were generated using a Random Forest machine learning algorithm that effectively mapped a total of 15,420.51 km2. Accuracy assessments indicated that the classification for the mangrove and non-mangrove class had a producer’s accuracy of 79.63 % and 98.24 %a user’s accuracy of 89.58 % and 96.21 %, and an overall accuracy of 95.26 % . We found a decline of 6,830 km2 between the 1970’s and 2020, showing that44.29% of the mangrove area in these countries has been lost in the past 48 years. Most of this loss occurred between the 1970’s and 1996; rates of deforestation declined dramatically after 1996. This study also urges that these results be considered within the context of the local need for these coastal resources that helped them endure the political and financial challenges of their coastal homes.

Priscilla Baltezar↗

Comprehensive Analysis of Thirty Years of Land Change in Georgia: Forest Degradation, Land-Use Patterns, and Drivers

In this talk, we present results from a study, funded by the NASA Land-Cover and Land-Use Change program, of thirty years of environmental change in the country of Georgia. The country, a former Soviet Union Republic, has experienced more political, economic and social change in the last 30 years than most countries. But the environmental implications of these extreme events remain largely unknown – the region is understudied, no national forest inventory has been completed in 20 years, and previous research in the area conducted by the authors were not successful. The latter statement is because of forest degradation. After the collapse of the Soviet Union, much of the forestry infrastructure broke down and people resorted to chopping down individual trees. The result was in many parts of the country a reduction in forest biomass but not to the point of a change in land cover. This type of forest degradation, which was either gradual over decades or abrupt, could not be readily identified using the methods and data at our disposal at the time. In the recent study, we had full access to the Landsat archive in combination with computing power. By using monitoring methods that are based on time series analysis, we were able to capture and identify the gradual processes driven by small scale activities that are so characteristic of the post-Soviet Georgian landscape. We developed an approach (“CCDC-SMA”) that combines time series analysis and spectral mixture analysis running on Google Earth Engine for monitoring abrupt and gradual forest degradation. By using this approach, we found that forest degradation was significantly larger than the area estimate of deforestation; 3,541 ± 556 km2 (11% of the forest area in 1987) compared to 158 ± 98 km2 from 1987 to 2020. The prevailing narrative is that legal and illegal cutting of trees for fuelwood is primarily responsible for this process. Yet, since independence from the Soviet Union in 1991, the country has undergone rapid socioeconomic and institutional changes which have not been explored as drivers of forest change. To further our understanding of the underlying causes, we combined forest disturbance estimates, Georgian statistical data, and historical institutional change data to examine socioeconomic drivers of forest degradation. We found that higher winter temperature and drought were associated with higher degradation at the regional scale, while major institutional changes and drought were associated with higher forest degradation at the national level. Access to natural gas, the major energy alternative to fuelwood, had no significant association with degradation. Our results challenge the narrative that poverty and a lack of alternative energy infrastructure drive forest degradation and suggest that government policies banning household fuelwood cutting, including the new Forest Code of 2020, may not reduce forest degradation. Given these results, improved data on wood harvesting and more research on the commercial drivers of degradation and their links to economic and political reforms is needed to better inform forest policy in the region, especially given ongoing risks from climate change.

Pontus Olofsson↗

Spatially Refined Satellite Gravimetry Captures Human Signatures in Global Terrestrial Water Storage Trends

Human activities have directly altered the water cycle through water management, aquifer pumping, agricultural irrigation, and land use change. Although satellite gravimetry has transformed global hydrological research, its coarse resolution limits attribution of freshwater change to human activities at many management-relevant scales. Here we assessed global terrestrial water storage (TWS) trends from April 2002 to November 2025 using “stacked” regression of Level-1B intersatellite ranging data, which leverages temporal information and variability to dramatically improve effective spatial resolution relative to standard approaches. We combined this refined product with rigorous uncertainty analysis, autocorrelation-robust geostatistical methods, and literature assessment to evaluate TWS trend associations with land and water use, climate variability, and glacial mass loss. We identified TWS trend hotspots exhibiting significant spatial associations with anthropogenic 40 drivers, including groundwater and surface-water irrigation, rainfed agriculture, deforestation, and reservoir impoundment. Across these regions, cumulative TWS losses (3,122 Gt) substantially exceeded gains (2,432 Gt). Compared with traditional regression of monthly mascons, our approach yielded regional trend magnitudes that are on average 33% larger, revealing that global freshwater depletion, particularly from groundwater pumping, is considerably more acute than previously estimated. Multivariate regression models show that humans account for a significant share of the spatial variability in TWS trends on every non-polar continent except Australia. We detected localized TWS gains linked to rainfed agriculture, surface water irrigation, and reservoir filling that were unresolved in earlier gravimetric studies. The methodology provides a foundation for future gravity missions to independently track decadal freshwater change with unprecedented spatial fidelity.

groundwater↗

Rapid Damage eXplorer (RDX): A Probabilistic Framework for Learning Changes From Bitemporal Images

Recent decade has witnessed major changes on the Earth, for example, deforestation, varying cropping and human settlement patterns, and crippling damages due to disasters. Accurate damage assessment caused by major natural and anthropogenic disasters is becoming critical due to increases in human and economic loss. This increase in loss of life and severe damages can be attributed to the growing population, as well as human migration to the disaster prone regions of the world. Rapid assessment of these changes and dissemination of accurate information is critical for creating an effective emergency response. Change detection using high-resolution satellite images is a primary tool in assessing damages, monitoring biomass and critical infrastructures, and identifying new settlements. In this demo, we present a novel supervised probabilistic framework for identifying changes using very high-resolution multispectral, and bitemporal remote sensing images. Our demo shows that the rapid damage explorer (RDX) system is resilient to registration errors and differing sensor characteristics.

Change detection↗

Ganges Valley Aerosol Experiment (GVAX) Final Campaign Report

In general, the Indian Summer Monsoon (ISM) as well as the and the tropical monsoon climate is influenced by a wide range of factors. Under various climate change scenarios, temperatures over land and into the mid troposphere are expected to increase, intensifying the summer pressure gradient differential between land and ocean and thus strengthening the ISM. However, increasing aerosol concentration, air pollution, and deforestation result in changes to surface albedo and insolation, potentially leading to low monsoon rainfall. Clear evidence points to increasing aerosol concentrations over the Indian subcontinent with time, and several hypotheses regarding the effect on monsoons have been offered. The Ganges Valley Aerosol Experiment (GVAX) field study aimed to provide critical data to address these hypotheses and contribute to developing better parameterizations for tropical clouds, convection, and aerosol-cloud interactions. The primary science questions for the mission were as follows:

Kotamarthi, VR↗

Semi-automated Design of Artificial Intelligence Earth Science Models

Prediction and observation of water cycles involve not only patterns isolated in space and time, but rather modeling complex spatio-temporal relationships across multiple sources of data and domains. For instance, Evapotranspiration (ET) and Leaf Area Indexes (LAI) are two critical components in DOE’s Energy Exascale Earth System Model (E3SM). Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, current ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFT), which fail to capture the fine-scale variations due to change in vegetation type across the globe. Within this context and in light of the data-model integration challenges highlighted in the EESSD Strategic Plan, the new era of AI model development for geosciences calls for data-driven methods that provide domain scientists with estimations of parameters such as PFT and LAI in an efficient, interpretable, and easy-to-operate manner.

Ambrozio Dias, Philipe↗

Engineered microbes for conversion of organic compounds to medium chain length alcohols and methods of use

This disclosure provides a genetically-modified bacterium from the genus Pseudomonas that comprises an exogenous nucleic acid encoding an enoyl-CoA reductase and an exogenous nucleic acid encoding an acyl-CoA reductase that produces medium chain length alcohols. The disclosure further provides methods for producing medium chain alcohols using such genetically-modified bacterium. This disclosure provides a renewable, bio-based production platform for valuable mcl-alcohols that have a wide range of industrial applications. Current production of mcl-alcohols typically occurs through the hydrogenation of plant oils and waxes. This process leads to issues of deforestation and is largely unsustainable. Utilizing waste lignin streams as the carbon source provides a more sustainable feedstock that can be generated from plant waste like corn stover. Along with this, the use of lignin avoids competition with food resources as traditional starch and sugar feedstocks.

Guss, Adam M.↗

Water innovation and ecological transformation: entrepreneurial approaches to advancing sustainable solutions

Climate change and decades of water mismanagement have created a "three-headed" global water crisis. People have contaminated water and depleted water sources, and human activity like deforestation and agriculture has altered rainfall patterns; we face the prospect of a 40% shortfall in freshwater supply by 2030. Meanwhile, climate change, water mismanagement and biodiversity loss interact to cause more frequent and severe episodes of too much or too little water, such as storms, floods, droughts, and wildfires.

Bryan, Scott↗

Observations of the Polarized Solar Corona During the Annular Eclipse of 14 October 2023

We present results of a dual eclipse expedition to observe the solar corona from two sites during the annular solar eclipse of 14 October 2023 using a novel coronagraph designed to be accessible for amateurs and students to build and deploy. The coronagraph (CATEcor) builds on the standardized eclipse observing equipment developed for the Citizen CATE 2024 experiment. The observing sites were selected for likelihood of clear observations, for historic relevance (near the Climax site in the Colorado Rocky Mountains), and for centrality to the annular eclipse path (atop Sandia Peak above Albuquerque, New Mexico). The novel portion of CATEcor is an external occulter assembly that slips over the front of a conventional dioptric telescope, forming a shaded-truss externally occulted coronagraph. CATEcor is specifically designed to be easily constructed in a garage or “makerspace” environment. We successfully observed some bright features in the solar corona to an altitude of approximately 2.25 R during the annular phases of the eclipse. Future improvements to the design, in progress now, will reduce both stray light and image artifacts; our objective is to develop a design that can be operated successfully by amateur astronomers at sufficient altitude even without the darkened skies of a partial or annular eclipse.

Solar instrumentation↗

Electrochemically recovered struvite matches conventional fertilizers in soil nutrient supply

Phosphorus (P) is an essential macronutrient for agriculture, yet global reliance on finite phosphorite reserves raises concerns about long-term food and nutrient security. Struvite (MgNH 4 PO 4 ·6H 2 O), a mineral recovered from municipal wastewater, represents a sustainable and circular source of P, but uncertainty remains regarding its nutrient availability relative to conventional fertilizers. This study evaluated the fertilizer value and environmental safety of electrochemically recovered struvite (RecoP) in comparison with diammonium phosphate (DAP), triple superphosphate (TSP), and rock phosphate (RockP). Nutrient availability, potential contaminant concentrations, and soil P and nitrogen (N) dynamics were assessed using standardized chemical analyses and an 8-week incubation experiment across three soils with contrasting soil types. RecoP contained 14.7% citrate-soluble P, significantly greater than RockP and comparable to DAP and TSP. Across all soils, RecoP increased both readily available and moderately labile P pools (p < 0.01), matching the performance of conventional fast-release fertilizers. Despite containing approximately half the total of DAP, RecoP stimulated nitrification rates that were 2.2 times greater than the control and exceeded those of TSP, suggesting that fertilizer-derived N bioavailability, rather than total N loading, governed microbial N transformation responses. Concentrations of potentially toxic elements in RecoP were consistently well below US Environmental Protection Agency regulatory limits thresholds. Collectively, these results indicate that RecoP functions as a readily available source of both P and N, comparable to widely used conventional fertilizers, while meeting environmental safety standards. RecoP therefore represents a viable component of sustainable nutrient management strategies that support P recycling and agricultural productivity.

Kharal, Sudarshan [Ohio Univ., Athens, OH (United ↗

Dynamics and drivers of land use and land cover changes in Bangladesh

Abstract Bangladesh has undergone dramatic land use and land cover changes (LULCC) in recent years, but no quantitative analysis of LULCC drivers at the national scale exists so far. Here, we quantified the drivers of major LULCC in combination with biophysical and socioeconomic observations at the sub-district level. We used Landsat satellite data to interpret LULCC from 2000 to 2010 and employed a Global Surface Water Dataset to account for the influences of water seasonality. The results suggest that major LULCC in Bangladesh occur between agricultural land and waterbodies and between forest and shrubland. Exclusion of seasonal waterbodies can improve the accuracy of our LULCC results and driver analysis. Although the gross gain and loss of agricultural land are large on the local scale, the net change (gross gain minus gross loss) at a country scale is almost negligible. Climate dynamics and extreme events and changes in urban and rural households were driving the changes from forest to shrubland in the southeast region. The conversion from agricultural land to standing waterbodies in the southwest region was mainly driven by urban household dynamics, population growth, distance to cities and major roads, and precipitation dynamics. This study, which is the first effort accounting for water seasonality and quantifying biophysical and socioeconomic drivers of LULCC at the national scale, provides a perspective on overall LULCC and underlying drivers over a decadal time scale and national spatial scale and can serve as a scientific basis for developing land policies in Bangladesh.

54 ENVIRONMENTAL SCIENCES↗

Optimal deployment of thermal energy storage under diverse economic and climate conditions

This paper presents an investigation of the economic benefit of thermal energy storage (TES) for cooling, across a range of economic and climate conditions. Chilled water TES systems are simulated for a large office building in four distinct locations, Miami in the U.S.; Lisbon, Portugal; Shanghai, China; and Mumbai, India. Optimal system size and operating schedules are determined using the optimization model DER-CAM, such that total cost, including electricity and amortized capital costs are minimized. The economic impacts of each optimized TES system is then compared to systems sized using a simple heuristic method, which bases system size as fraction (50percent and 100percent) of total on-peak summer cooling loads. Results indicate that TES systems of all sizes can be effective in reducing annual electricity costs (5percent-15percent) and peak electricity consumption (13percent-33percent). The investigation also indentifies a number of criteria which drive TES investment, including low capital costs, electricity tariffs with high power demand charges and prolonged cooling seasons. In locations where these drivers clearly exist, the heuristically sized systems capture much of the value of optimally sized systems; between 60percent and 100percent in terms of net present value. However, in instances where these drivers are less pronounced, the heuristic tends to oversize systems, and optimization becomes crucial to ensure economically beneficial deployment of TES, increasing the net present value of heuristically sized systems by as much as 10 times in some instances.

25 ENERGY STORAGE↗

Modeling of thermal storage systems in MILP distributed energy resource models

Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO 2 emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Ultimately,results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids.

25 ENERGY STORAGE↗

A comparative energy analysis of three electrochromic glazing technologies in commercial and residential buildings

Here, we present a simulation study of three dynamic electrochromic window glazings, including a novel glazing capable of independently modulating its optical properties in both the visible and near-infrared spectrums. This capability allows this so-called “dual-band” technology to actively manage the solar heat and visible light transmitted into a building's interior, and creates the potential for heating, cooling, and lighting savings vis-à-vis competing window technologies. In this study EnergyPlus is used to simulate annual energy performance of the dual-band electrochromic (DBEC) glazing in three building types and 16 U.S. climate regions. The savings potential of DBEC windows are presented relative to a conventional electrochromic glazing; a visibly transparent, near-infrared switching electrochromic glazings; and several static alternatives, including ASHRAE 90-2010 standard compliant windows. Results indicate that the DBEC glazings are capable of outperforming alternatives in a diverse set of locations and building types, including both heating and cooling-dominated regions. Relative to code-compliant static windows, the DBEC is capable of achieving annual primary energy savings between 6 and 30 kW h/ft 2 of window area from reduced heating, cooling, and lighting demand. Relative to other advanced glazings, the savings are significantly lower, ranging from 0 to 1.2 kW h/ft 2 . Regional DBEC energy cost savings versus high performance static windows are presented to identify early potential market entries based on energy savings. Lastly, the impacts of widespread deployment of high-efficiency LED lighting on DBEC energy savings potentials are also presented.

14 SOLAR ENERGY↗