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At least 109 records · Page 6

Impact Assessment of Biomass Burning on Air Quality in Southeast and East Asia During BASE-ASIA

A synergy of numerical simulation, ground-based measurement and satellite observation was applied to evaluate the impact of biomass burning originating from Southeast Asia (SE Asia) within the framework of NASA's 2006 Biomass burning Aerosols in Southeast Asia: Smoke Impact Assessment (BASE-ASIA). Biomass burning emissions in the spring of 2006 peaked in MarcheApril when most intense biomass burning occurred in Myanmar, northern Thailand, Laos, and parts of Vietnam and Cambodia. Model performances were reasonably validated by comparing to both satellite and ground-based observations despite overestimation or underestimation occurring in specific regions due to high uncertainties of biomass burning emission. Chemical tracers of particulate K(+), OC concentrations, and OC/EC ratios showed distinct regional characteristics, suggesting biomass burning and local emission dominated the aerosol chemistry. CMAQ modeled aerosol chemical components were underestimated at most circumstances and the converted AOD values from CMAQ were biased low at about a factor of 2, probably due to the underestimation of biomass emissions. Scenario simulation indicated that the impact of biomass burning to the downwind regions spread over a large area via the Asian spring monsoon, which included Southern China, South China Sea, and Taiwan Strait. Comparison of AERONET aerosol optical properties with simulation at multi-sites clearly demonstrated the biomass burning impact via longrange transport. In the source region, the contribution from biomass burning to AOD was estimated to be over 56%. While in the downwind regions, the contribution was still significant within the range of 26%-62%.

biomass burning↗

Optical Evaluation of Digital Micromirror Devices (DMDs) with UV-Grade Fused Silica, Sapphire, and Magnesium Fluoride Windows and Longterm Reflectance of Bare Devices

Digital micromirror devices (DMDs) are commercial micro-electromechanical systems, consisting of millions of mirrors which can be individually addressed and tilted into one of two states (+/-12deg). These devices were developed to create binary patterns in video projectors, in the visible range. Commercially available DMDs are hermetically sealed and extremely reliable. Recently, DMDs have been identified as an alternative to microshutter arrays for space-based multi-object spectrometers (MOS). Specifically, the MOS at the heart of the proposed Galactic Evolution Spectroscopic Explorer (GESE) uses the DMD as a reprogrammable slit mask. Unfortunately, the protective borosilicate windows limit the use of DMDs in the UV and IR regimes, where the glass has insufficient throughput. In this work, we present our efforts to replace standard DMD windows with custom windows made from UV-grade fused silica, low-absorption optical sapphire (LAOS) and magnesium fluoride (MgF2). We present transmission measurements of the antireflection coated windows and the reflectance of bare (window removed) DMDs. Furthermore, we investigated the long-term stability of the DMD reflectance and experiments for coating DMD active area with a layer of pure aluminum (Al) to boost reflectance performance in the UV spectral range (200−400 nm).

reflectance↗

Optical Evaluation of DMDs with UV-Grade FS, Sapphire, MgF2 Windows and Reflectance of Bare Devices

Digital Micro-mirror Devices (DMDs) have been identified as an alternative to microshutter arrays for space-based multi-object spectrometers (MOS). Specifically, the MOS at the heart of a proposed Galactic Evolution Spectroscopic Explorer (GESE) that uses the DMD as a reprogrammable slit mask. Unfortunately, the protective borosilicate windows limit the use of DMDs in the UV and IR regimes, where the glass has insufficient throughput. In this work, we present our efforts to replace standard DMD windows with custom windows made from UV-grade fused silica, Low Absorption Optical Sapphire (LAOS) and magnesium fluoride. We present reflectance measurements of the antireflection coated windows and a reflectance study of the DMDs active area (window removed). Furthermore, we investigated the long-term stability of the DMD reflectance and recoating device with fresh Al coatings.

Quijada, Manuel A.↗

Ground and Satellite Based Observation Datasets for the Lower Mekong River Basin

In ‘Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability’ [1] hydrological fluxes, meteorological variables, land cover land use maps, and soil characteristics and parameters data were compiled and processed for the Lower Mekong River Basin. In this work, daily streamflow time series data at nine gauges located at five different countries in the Mekong region (Thailand, Laos People׳s Democratic Republic (PDR), Myanmar, Cambodia, and Viet Nam) is presented. Satellite-based daily precipitation and air temperature (minimum & maximum) data is processed and provided over the entire basin as part of the dataset provided in this work. Moreover, land cover land use raster data that contains 18 classes that cover agriculture, urban, range and forests land cover land use classes for the basin is offered. In addition, a soil data that contains physical and chemical characteristics needed by physically based hydrological models to simulate the cycling of water and air is also provided.

Streamflow↗

Diagnosing Challenges and Setting Priorities for Sustainable Water Resource Management Under Climate Change

Managing transboundary river basins requires balancing tradeoffs of sustainable water use and coping with climate uncertainty. We demonstrate an integrated approach to exploring these issues through the lens of a social-ecological system, combining remote and in-situ earth observations, hydrologic and climate models, and social surveys. Specifically, we examine how climate change and dam development could impact the Se Kong, Se San and Sre Pok rivers in the Mekong region. We find that climate change will lead to increased precipitation, necessitating a shift in dam operations, from maintaining low flows to reducing flood hazards. We also find that existing water governance systems in Laos, Vietnam, and Cambodia are ill-prepared to address the problem. We conclude that the solution space for addressing these complex issues will be highly constrained unless major deficiencies in transboundary water governance, strategic planning, financial capacity, information sharing, and law enforcement are remedied in the next decades.

Ibrahim Nourein Mohammed↗

Rainfall-induced Landslide Inventories for Lower Mekong Based on Planet Imagery and a Semi-Automatic Mapping Method

Fatal landslides occur every year during the rainy season (June–November) in the Lower Mekong Region (LMR). There is an urgent need to develop a landslide early warning system in the LMR. In collaboration with the Asian Disasters Preparedness Center and NASA’s SERVIR Programme, we are regionalizing the global Landslide Hazard Assessment System for Situational Awareness model for the LMR (LHASA-Mekong). A robust set of landslide inventories are needed to effectively train the machine learning-based LHASA-Mekong model. In this study, the Semi-Automatic Landslide Detection (SALaD) system was modified by incorporating a change detection module (SALaD-CD) to produce rainfall event-based landslide inventories using pre- and post-imagery from RapidEye and PlanetScope for various locations in the LMR that were identified based on media and government reports. These rainfall-induced landslides are published as initiation points for ease of use. In total, we created 22 inventories: 2 in Laos, 4 in Myanmar, 1 in Thailand and 15 in Vietnam. These inventories are being used to train the LHASA-Mekong model and quantify the effects of Land use/Land cover change on landslide susceptibility. These open data will be a valuable resource for advancing landslide studies in this region.

Pukar Amatya↗

Columnar Aerosol Types and Compositions Over Peninsular Southeast Asia Based on Long-Term AERONET Data

Aerosol chemical components such as black carbon (BC) and brown carbon (BrC) regulate aerosol optical properties, which in turn drive the atmospheric radiative forcing estimations due to aerosols. In this study, we used the long-term measurements from AERONET (Aerosol Robotic Network) to better understand the aerosol types and composition with respect to their seasonal and spatial variabilities in peninsular Southeast Asia (PSEA, here defined as Vietnam, Cambodia, Thailand, Laos, and Myanmar). Two methods (i.e., aerosol type cluster and aerosol component retrieval) were applied to determine the aerosol type and chemical composition during the biomass-burning (BB) season. AERONET sites in northern PSEA showed a higher AOD (aerosol optical depth) compared to that of southern PSEA. Differences in land use pattern, geographic location, and weather regime caused much of the aerosol variability over PSEA. Lower single-scattering albedo (SSA) and higher fine-mode fraction (FMF) values were observed in February and March, suggesting the predominance of BB type aerosols with finer and stronger absorbing particles during the dry season. However, we also found that the peak BB month (i.e., March) in northern PSEA may not coincide with the lowest SSA once dust particles have mixed with the other aerosols. Furthermore, we investigated two severe BB events in March of 2014 and 2015, revealing a significant BrC fraction during BB event days. On high AOD days, although the BC fraction was high, the BrC fraction remained low due to lack of aerosol aging. This study highlights the dominance of carbonaceous aerosols in the PSEA atmosphere during the BB season, while also revealing that transported dust particles and BrC aerosol aging may introduce uncertainties into the aerosol radiative forcing calculation.

Sheng-Hsiang Wang↗

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗

Enabling Floating Solar (FPV) Deployment: Policy and Operational Considerations

Floating solar photovoltaics, or "floating PV", offer an opportunity for scaling up the deployment of renewable energy on inland and offshore bodies of water. Floating PV presents the opportunity to: increase clean energy generation to help meet growing demand; lessen the potential for land-use conflicts; help existing hydropower systems optimize their operation; and adapt to increasing temperatures and drought events by reducing the rate of evapotranspiration of waterways. There is significant promise for floating PV deployment in several Southeast Asian countries, especially those rich in hydropower resources, such as Laos and Thailand, but deployment remains limited. This slide deck presents an overview of NREL's research on (1) the policy, economic, environmental, and cultural barriers that currently exist, (2) recently completed modeling exercise on the potential operational benefits of pairing floating PV and hydropower, (3) international best practices that can be adopted to Southeast Asia, and (4) plans for high-resolution floating PV technical potential assessment.

Asia Clean Energy Forum↗

Exploring Renewable Energy Opportunities in Select Southeast Asian Countries: A Geospatial Analysis of the Levelized Cost of Energy of Utility-Scale Wind and Solar Photovoltaics

The costs of renewable energy-based electricity generation have fallen precipitously in recent years to levels that are increasingly competitive with traditional generation such as fossil fuel-based generation. As these costs become increasingly competitive, private developers, policymakers, and energy system planners are searching for opportunities to harness high-quality renewable energy resources. Developing economies are setting ambitious targets and exploring how cost-effective, grid-connected renewable energy options can help power economic growth and meet growing electricity demands. This includes the member states of the Association of Southeast Asian Nations (ASEAN) that are determined to reach a target of 23% of renewable energy in the region's total primary energy supply by 2025. A critical gap to identifying opportunities and scaling up renewable energy is the lack of quality data and analyses to support decisions on the investment and deployment of renewables - including wind and solar photovoltaics (PV). This work supports decision making by providing high-quality data and spatial analysis of the cost of utility-scale wind and solar PV generation in select countries of Southeast Asia - specifically, the ASEAN member states. Generation costs are expressed as the levelized cost of energy (LCOE) - a commonly used metric that represents the net present value of the unit cost of electricity during the lifetime of a particular electricity generation technology. This is the first spatial estimate of LCOE for these technologies within the ASEAN member states - providing insights into the roles that renewable energy resource quality and other factors may play in generation costs.

14 SOLAR ENERGY↗

Revealing the Structural Evolution of Green Rust Synthesized in Ionic Liquids by In Situ Molecular Imaging

Abstract Ionic liquids are green solvents that have wide applications in material synthesis, catalysis, and separation. A model switchable ionic liquid (SWIL) consisting of 1,8‐diazabicycloundec‐7‐ene (DBU) and 1‐hexanol with carbon dioxide (CO 2 ) as the trigger gas is chosen to synthesize nanocrystalline green rust. Under anoxic conditions, by adding iron (II) acetate (Fe(C 2 H 3 O 2 ) 2 ) and methanol to the degassed SWIL, a nanoparticulate green rust with carbonate (nano‐GR) is synthesized. More importantly, the molecular structural change of the ionic liquid resulting in green rust crystallines is first characterized using in situ liquid using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) coupled with the system for analysis at the liquid vacuum interface (SALVI), a vacuum compatible microfluidic reactor in this work. Dimers and ionic clusters consisting ferric and ferrous ions are identified in liquid ToF‐SIMS spectra. Spectral principal component analysis is used to confirm that these ion pairs including dimers and cluster ions are different from nonionic liquids. The results show that liquid ToF‐SIMS can be a useful tool to study complex liquids at the molecular level providing insights into predicative synthesis of nanomaterials using environmentally friendly green solvents and giving unique visualization of the evolving material interface due to nucleation.

Shen, Yanjie↗

Simultaneous optimization of simulated moving bed adsorption and distillation for 2,3‐butanediol recovery

Abstract A combined simulated moving bed (SMB) and distillation separation scheme is developed to recover 2,3‐butanediol (BDO) from a dilute fermentation broth. The scheme was integrated into a lignocellulosic biorefinery that produces hydrocarbon fuels from corn stover with BDO as an intermediate. BDO recovery is one of the most challenging processes in this biorefinery; and given the high associated energy duties, direct distillation is considered cost‐prohibitive. An alternative separation is SMB adsorption in nanoporous materials, which can reject 90% of the water and reduce subsequent distillation costs. Rigorous models were used to optimize the SMB and distillation simultaneously. The separation can be added to the biorefinery while keeping the projected minimum fuel selling price (MFSP) below $0.66 USD (US dollars) per liter gasoline‐equivalent ($2.50/GGE, gallon gasoline equivalent). Finally, sensitivity analyses were conducted to assess the effects of cost and lifetime of the adsorbent, titer concentration, and BDO purity.

09 BIOMASS FUELS↗

Countermeasures for Preventing and Treating Opioid Overdose

The only medication available currently to prevent and treat opioid overdose (naloxone) was approved by the US Food and Drug Administration (FDA) nearly 50 years ago. Due to its pharmacokinetic and pharmacodynamic properties, naloxone has limited utility under some conditions and would not be effective to counteract mass casualties involving large-scale deployment of weaponized synthetic opioids. To address shortcomings of current medical countermeasures for opioid toxicity, a trans-agency scientific meeting was convened by the US National Institute of Allergy and Infectious Diseases/National Institutes of Health (NIAID/NIH) on August 6 and 7, 2019, to explore emerging alternative approaches for treating opioid overdose in the event of weaponization of synthetic opioids. The meeting was initiated by the Chemical Countermeasures Research Program (CCRP), was organized by NIAID, and was a collaboration with the National Institute on Drug Abuse/NIH (NIDA/NIH), the FDA, the Defense Threat Reduction Agency (DTRA), and the Biomedical Advanced Research and Development Authority (BARDA). This paper provides an overview of several presentations at that meeting that discussed emerging new approaches for treating opioid overdose, including the following: (1) intranasal nalmefene, a competitive, reversible opioid receptor antagonist with a longer duration of action than naloxone; (2) methocinnamox, a novel opioid receptor antagonist; (3) covalent naloxone nanoparticles; (4) serotonin (5-HT)1A receptor agonists; (5) fentanyl-binding cyclodextrin scaffolds; (6) detoxifying biomimetic “nanosponge” decoy receptors; and (7) antibody-based strategies. These approaches could also be applied to treat opioid use disorder.

59 BASIC BIOLOGICAL SCIENCES↗

Magnetic-Confinement Fusion—Plasma Theory: Tokamak Magnetohydrodynamic Equilibrium and Stability

Magnetohydrodynamics (MHD) provides a useful model to describe the crucial plasma macroscopic equilibrium and stability behaviors in toroidal tokamak devices by considering the plasma as a conducting fluid interacting with a surrounding confining electromagnetic field. MHD is the most basic plasma model, incorporating most large-scale phenomena, including plasma equilibrium and all major instabilities. MHD equations are obtained by taking moments of the Boltzmann equations for different plasma species. They provide a set of comprehensive physics constrains to compute and optimize the equilibrium plasma shape and pressure and current profiles that are critical to its stability and performance. In the ideal case, the equations have special properties that lead to efficient numerical calculation schemes, the most important of which is the ideal MHD energy principle for linear stability against small departures from equilibrium. In a tokamak plasma, equilibrium pressure is mostly destabilizing for MHD modes, whereas equilibrium current is also often a major driving force. Plasma resistivity creates new freedom for a MHD instability to grow, but there are also cases where the plasma resistivity plays a stabilizing role. Equilibrium toroidal flow and/or flow shear can affect MHD instabilities. Principal MHD instabilities include the internal kink mode, sawtooth, fishbone, external kink, resistive wall mode, resistive interchange, tearing and neoclassical tearing modes (NTMs), locked modes, toroidal Alfven eigenmodes (TAEs), and edge localized modes (ELMs). Fast-growing MHD instabilities can lead to an abrupt plasma disruption and termination that can potentially damage the device plasma facing components (PFCs) and in-vessel structures. Furthermore, an important MHD application is to develop robust techniques to mitigate and control MHD instabilities.

Dispersive pellet injection↗