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Energy Efficient Digital Networks

Digital networks are the foundation of the information services, and play an expanding and indispensable role in our lives, via the Internet, email, mobile phones, etc. However, these networks consume energy, both through the direct energy use of the network interfaces and equipment that comprise the network, and in the effect they have on the operating patterns of devices connected to the network. The purpose of this research was to investigate a variety of technology and policy issues related to the energy use caused by digital networks, and to further develop several energy-efficiency technologies targeted at networks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Delta size and plant patchiness as controls on channel network organization in experimental deltas

Understanding the feedbacks between water, sediment, and vegetation in deltas is an important part of understanding deltas as ecomorphodynamic systems. Here, we conducted a set of laboratory experiments using alfalfa (Medicago sativa) as a proxy for delta vegetation to investigate (1) the effects of plants on delta growth and channel network formation and (2) the timescales controlling delta evolution in the presence of plants. Experiments were conducted with fluctuating discharge (i.e. flood and base flow periods) and variable seeding densities. We found that when deltas were small, channels had no memory across flood cycles, as floods could completely fill the incised channel network. When deltas were large, the larger channel volume could remain underfilled to keep channel memory. Plant patches also helped to increase the number of channels and make a more distributive network. Patchiness increased over time to continually aid in bifurcation, but as vegetation cover and patch sizes increased, patches began to merge. Larger patches blocked the flow to enhance topset deposition and channel filling, even for the case of large deltas with a high channel volume. We conclude that both plant patchiness and delta size affect the development of the channel network, and we hypothesize that their influences are manifested through two competing timescales. The first timescale, T v , defines the time when the delta is large enough for channels to have memory (i.e., remain underfilled), and the second, T p , defines the time when vegetation patches merge, amplifying deposition and blocking channels. Finally, when run time is between these two timescales, the delta can develop a persistent distributary network of channels aided by bifurcation around plant patches, but once T p is reached, the channel network can again be destroyed by vegetation.

58 GEOSCIENCES↗

Examining Infrasound Propagation at High Spatial Resolution Using a Nodal Seismic Array

Infrasound—acoustic waves in the atmosphere below 20 Hz—is a useful monitoring tool. Topography and atmospheric structure strongly control infrasound propagation, and at common source–receiver distances neither of these effects can be ignored when quantitative source constraints are sought. Detailed spatial measurements of the infrasound wavefield would inform propagation models and improve source estimates. However, the “large-N” deployment strategy now well-known in seismology has not yet been realized for infrasound studies. Here, we use the 900-node seismic array from the 2014 Imaging Magma Under St. Helens (iMUSH) experiment as a proxy for a large-N infrasound network, by leveraging acoustic–seismic coupled arrivals. The active-source component of iMUSH consisted of 23 shallowly buried explosions around Mount Saint Helens volcano; these explosions produced epicentral infrasound recorded on the nodes. We find that the bulk presence of ground-coupled infrasound on the nodes is controlled by wind noise and source–receiver distance, with observed arrivals for eight explosions. Explosions with the most extensive coupling produce complex spatial waveform patterns across the array. These patterns are related to both topographic and atmospheric propagation effects, as well as spatially variable site (coupling) effects. We compare our observations to simple topographic diffraction and high-resolution wind advection models, and full-wave numerical simulations. We find strong spatial correlations between (a) coupled arrival strength and modeled topographic obstruction and (b) coupled arrival time and along-path winds. Our seismoacoustic analyses and results are applicable to other existing and future nodal seismic data sets and can expand the utility of such deployments.

58 GEOSCIENCES↗

A Cyber Threat Mitigation Approach For Wide Area Control of SVCs using Stability Monitoring

We propose a stability monitoring approach for the mitigation of cyber threats directed at the wide area control (WAC) system used for coordinated control of Flexible AC Transmission Systems (FACTS) used for power oscillation damping (POD) of active power flow on inter-area tie lines. The approach involves monitoring the modes of the active power oscillation on an inter-area tie line using the Matrix Pencil (MP) method. We use the stability characteristics of the observed modes as a proxy for the presence of destabilizing cyber threats. We monitor the system modes to determine whether any destabilizing modes appear after the WAC system engages to control the POD. If the WAC signal exacerbates the POD performance, the FACTS falls back to POD using local measurements. The proposed approach does not require an expansive system-wide view of the network. We simulate replay, control integrity, and timing attacks for a test system and present results that demonstrate the performance of the SM approach for mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Highland Lakes Water Resources: Using NASA Earth Observations to Improve Detection Systems for Harmful Algal Events in the Highland Lakes in Central Texas

Beginning in 2019, harmful algal events in Austin, Texas, caused canine deaths in the Lady Bird Lake and Lake Travis reservoirs. These reservoirs are part of the larger Highland Lakes chain, managed by the Lower Colorado River Authority (LCRA) and the City of Austin Department of Watershed Protection (CoA DWP), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable algal event conditions in central Texas, the LCRA and CoA DWP partnered with NASA DEVELOP to improve algal event early-warning systems through the application of remote sensing and machine learning. An Earth observation-based algal monitoring system will assist the responsible agencies in predicting algal conditions and communicating hazards to the public. The NASA DEVELOP team utilized Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data to produce products including chlorophyll-a concentrations, cyanobacteria detections, turbidity, and water surface temperature. Chlorophyll-a concentrations were retrieved with a pre-trained machine learning model (mixture density network) and spectral indices, while the other products were derived from spectral indices. In situ field data were used to validate and quantify uncertainties for each product. The validations show strong correlations for chlorophyll-a and water surface temperature. Time series analyses of chlorophyll-a concentrations show peaks in the severe drought years (2015 and 2016). This project's resulting products enable monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain and will ultimately support water management, decision making, and risk communication.

Kaitlynn Hietpas↗

Agent-Based Model of Combined Community- and Jail-Based Take-Home Naloxone Distribution

Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-related overdose among people with opioid use disorders. Design, Setting, and Participants This study developed the agent-based Justice-Community Circulation Model (JCCM) to model a synthetic population of individuals with and without a history of opioid use. Epidemiological data from 2014 to 2020 for Cook County, Illinois, were used to identify parameters pertinent to the synthetic population. Twenty-seven experimental scenarios were examined to capture diverse strategies of THN distribution and use. Sensitivity analysis was performed to identify critical mediating and moderating variables associated with population impact and a proxy metric for cost-effectiveness (ie, the direct costs of THN kits distributed per death averted). Data were analyzed between February 2022 and March 2024. Intervention Modeled interventions included 3 THN distribution channels: community facilities and practitioners; jail, at release; and social network or peers of persons released from jail. Main Outcomes and Measures The primary outcome was the percentage of opioid-related overdose deaths averted with THN in the modeled population relative to a baseline scenario with no intervention. Results Take-home naloxone distribution at jail release had the highest median (IQR) percentage of averted deaths at 11.70% (6.57%-15.75%). The probability of bystander presence at an opioid overdose showed the greatest proportional contribution (27.15%) to the variance in deaths averted in persons released from jail. The estimated costs of distributed THN kits were less than $\$$15 000 per averted death in all 27 scenarios. Conclusions and Relevance This study found that THN distribution at jail release is an economical and feasible approach to substantially reducing opioid-related overdose mortality. Training and preparation of proficient and willing bystanders are central factors in reaching the full potential of this intervention.

Tatara, Eric [Argonne National Laboratory (ANL), A↗

The Application of Remote Sensing and Machine Learning to Improve Early Warning Systems for Harmful Algal Events in the Highland Lake Chain, TX

Beginning in 2019, harmful algal events have caused canine deaths in both Lady Bird Lake and Lake Travis located near Austin, Texas. These two reservoirs are part of the larger Highland Lakes chain, managed by the City of Austin Department of Watershed Protection (COA DWP) and the Lower Colorado River Authority (LCRA), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable environmental conditions for algal events in central Texas, NASA DEVELOP partnered with LCRA and COA DWP to improve monitoring and early detection of algal events, utilizing satellite remote sensing and machine learning. Spatially and temporally varied chlorophyll a concentrations, cyanobacteria detections, turbidity, and water surface temperature products are used as environmental proxies. Landsat 8 Operational Land Imager (OLI) and the Sentinel-2 MultiSpectral Instrument (MSI) data were used to provide a combined revisit time of up to ~3 days and < 30 m per pixel products. Chlorophyll a concentrations were estimated using a pre-trained Mixture Density Network, and cyanobacteria detection was accomplished using the Broad Wavelength Algae Index, which can differentiate algal blooms from algal proliferations (mats). In situ data were used to validate remotely sensed measurements and quantify uncertainties. Preliminary results show a good fit between the modeled output and in situ observations, suggesting that remote sensing data can be used to retrieve biogeochemical properties and/or inherent optical properties (IOPs) of water columns in these inland human-made lakes. Uncertainties were introduced from the sensitivity to atmospheric correction, inherent mismatch between satellite and sampling data, and a relatively lower signal-to-noise ratio over water. The resulting products enable near real-time monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain, and will ultimately support water management, decision making, and risk communication.

Shuyu Chang↗

A21I-1875: Leveraging TEMPO Formaldehyde Observations to Assess Surface Air Quality

Surface ozone (O3) pollution is detrimental to human health, crop yields, and ecosystem productivity. Ground-based ozone observations are sparse and surface ozone retrievals from space are challenging. The process of producing ozone from the oxidation of volatile organic compounds (VOCs) in the presence of nitrogen oxides (NOx) results in formaldehyde (HCHO), which can be observed from satellite and by surface-based remote sensing. From limited field campaign observations, column formaldehyde has been shown to exhibit a strong relationship with surface ozone and, therefore, could be an useful proxy for detecting unmonitored regions of elevated ozone pollution. The spatiotemporal characteristics of this relationship are explored using ground-based Pandora spectrometers and airborne remote sensing data with surface ozone monitors across the United States during recent field campaigns over major cities (TRACER-AQ and STAQS). We extend our analysis to take advantage of HCHO column observations from recently launched Tropospheric Emissions: Monitoring of Pollution (TEMPO), a geostationary satellite over North America. TEMPO observations show preliminary promise in mapping regions of elevated surface ozone from space using column HCHO. We demonstrate the use of column HCHO in assessing the strength of the surface monitoring network, and in detecting the extent of regional ozone exceedances.

Prajjwal Rawat↗

Hygroscopic growth and cloud droplet activation of xanthan gum as a proxy for marine hydrogels: HYGROSCOPICITY OF XG AS MARINE HYDROGEL

Knowledge of the physical characteristics and chemical composition of marine organic aerosols is needed for the quantification of their effects on cloud microphysical processes and solar radiative transfer. Here we use xanthan gum (XG)—a bacterial biopolymer—as a proxy for marine hydrogels. Measurements were performed for pure XG particles and mixtures of XG with sodium chloride, calcium nitrate, and calcium carbonate. The aerosol hygroscopicity parameter (κ) is derived from hygroscopic growth factor measurements (κ gf ) at variable water activity (a w ) and from cloud condensation nuclei activation efficiency (κ ccn ). The Zdanovskii, Stokes, and Robinson (ZSR) hygroscopicity parameter derived for multicomponent systems (κ mix , sol) is used to compare measurements of κ gf and κ ccn . Pure XG shows close agreement of κ gf (at aw = 0.9) and κccn of 0.09 and 0.10, respectively. Adding salts to the system results in deviations of κ gf (at a w = 0.9) from κ ccn . The measured κ gf and ZSR-derived hygroscopicity parameter (κ mix , sol) values for different solutions show close agreement at aw > 0.9, while κ gf is lower in comparison to κ mix , sol at a w < 0.9. The differences between predicted κmix, sol and measured κ gf and κ ccn values are explained by the effects of hydration and presence of salt ions on the structure of the polymer networks. Results from this study imply that at supersaturations of 0.1 and 0.5%, the presence of 30% sea salt by mass can reduce the activation diameter of pure primary marine organic aerosols from 257 to 156 nm and from 87 to 53 nm, respectively.

54 ENVIRONMENTAL SCIENCES↗

An experimental and computational view of the photoionization of diol–water clusters

In the interstellar medium, diols and other prebiotic molecules adsorb onto icy mantles surrounding dust grains. Water in the ice may affect the reactivity and photoionization of these diols. Ethylene glycol (EG), 1,2-propylene glycol, and 1,3-propylene glycol clusters with water clusters were used as a proxy to study these interactions. The diol–water clusters were generated in a continuous supersonic molecular beam, photoionized by synchrotron-based vacuum ultraviolet light from the Advanced Light Source, and subsequently detected by reflectron time-of-flight mass spectrometry. The appearance energies for the detected clusters were determined from the mass spectra, collected at increasing photon energy. Clusters of both diol fragments and unfragmented diols with water were detected. The lowest energy geometry optimized conformers for the observed EG–water clusters and EG fragment–water clusters have been visualized using density functional theory (DFT), providing insight into hydrogen bonding networks and how these affect fragmentation and appearance energy. As the number of water molecules clustered around EG fragments (m/z 31 and 32) increased, the appearance energy for the cluster decreased, indicating a stabilization by water. This trend was supported by DFT calculations. Fragment clusters from 1,2-propylene glycol exhibited a similar trend, but with a smaller energy decrease, and no trend was observed from 1,3-propylene glycol. In conclusion, we discuss and suggest that the reactivity and photoionization of diols in the presence of water depend on the size of the diol, the location of the hydroxyl group, and the number of waters clustered around the diol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗