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At least 109 records · Page 6

Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs

The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.

Cybersecurity↗

A Functional All-Hazard Approach to Critical Infrastructure Dependency Analysis

The critical infrastructures protection landscape is a vast and varied pattern of independent, but interconnected infrastructure systems that are essential to the function of our modern society. The U.S. policy on critical infrastructure protection has been continually evolving since the “President’s Commission on Critical Infrastructure Protection” was published in 1997. In response to these policies, federal, state, and local governments, along with research institutions, have invested a substantial amount of time and effort into identifying and analyzing critical infrastructure, their functions, and dependencies/interdependencies to better understand their vulnerabilities. To date, the ability to assess vulnerabilities, resiliency, and priorities for protecting interdependent critical infrastructure systems from an all-hazards perspective remains a difficult problem. In this paper we introduce the All-Hazards Analysis (AHA) methodology, which provides an integrated functional basis across infrastructure systems, through the implementation of a common language and a scalable level of decomposition to effectively evaluate the resilience of interconnected infrastructure systems. AHA models infrastructure systems as directed multidimensional graphs, which enable the evaluation of cross-sector interdependencies prior to, during, and after disruptive events. Finally, and by design, AHA enables the cross linking of data taxonomies to enable more effective data sharing, such as the National Critical Functions (NCF) and Infrastructure Data Taxonomy (IDT).

02 PETROLEUM↗

Cyber-Informed Engineering Case Study of an Integrated Hydrogen Generation Plant

Strategies for securing digital instrumentation and control (I&C) systems within the nuclear industry are provided by multiple standards and guidance documents. However, since selection and use of security controls outlined in these documents are frequently only considered during or after installation, there are often limitations on their use, such as technological constraints related to design or operation. Furthermore, alternative controls intended to provide the same or similar security countermeasure as the primary control may also be infeasible at these stages, leaving the I&C system vulnerable to cyber-attacks. The limitations associated with ‘bolting on’ security controls late in the systems engineering lifecycle can be reduced by integrating Cyber-Informed Engineering (CIE) into the process. This paper evaluates the use of CIE during the high-level design stage of a hydrogen generation project where heat and electricity are provided by a nuclear power plant. Applying CIE to this project highlighted potential cyber vulnerabilities of the initial design, leading to recommendations for process flow and I&C system design modifications to reduce, and at times eliminate, the risk from both deliberate and unintentional cyber incidents.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Real-Time Testbed for Smart Inverter Cyber Security Studies

Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.

97 MATHEMATICS AND COMPUTING↗

The Impacts of Developing a Port Network for Floating Offshore Wind Energy on the West Coast of the United States

Floating offshore wind is a pre-commercial industry with the potential for significant market growth on the U.S. West Coast in the near future; however, significant investment in port infrastructure will be required to enable the industry to progress from demonstration projects to efficient and cost effective commercial deployment. Developing a system of ports that can enable commercial-scale floating wind development on the West Coast of the United States will require significant levels of funding and coordination between governments, industry, ports, and local communities. A critical first step to strategically planning these resources is understanding the number of ports (and associated investment) that would be required to support different phases of offshore wind projects, including manufacturing, installation, and operation. But simply tallying up these costs is not sufficient to understand how a robust network of ports could impact local communities, the environment, workforce development, the offshore wind industry, and the West Coast region as a whole. In this report, the authors present analyses and perspectives related to port development in California, Oregon, and Washington. We describe the requirements for floating offshore wind ports that conduct manufacturing, installation, and/or service activities, and estimate the investment and time frames required to construct these ports at suitable locations in West Coast states. We develop indicators for the vulnerability and workforce accessibility of coastal communities and consider the potential risks and benefits associated with port development in these locations. We model how the proximity of an offshore wind project to installation and operations ports can impact the levelized cost of energy of the project, and then consider how these costs could be affected by local or foreign supply chains. We build upon these analyses to develop scenarios with increasing levels of offshore wind deployment and port assets on the West Coast and show how these ports could enable deployment goals to be achieved. Finally, we draw upon outreach with key floating wind stakeholders to summarize five key challenges that will need to be overcome to develop a comprehensive port network, and present potential approaches that could help to address these obstacles.

17 WIND ENERGY↗

How Quantum Sensing Will Help Solve GPS Denial in Warfare

The U.S. military’s ability to posture, deter, and prevail in future conflicts may rest on the quantum sensing position, navigation, and timing (PNT) capabilities that are currently being developed. Heavy reliance on GPS signals for PNT has become a critical vulnerability for the U.S. military. Meanwhile, the conflict in Ukraine has demonstrated that GPS denial and electronic warfare (EW) is now a key component of modern combat and satellite-guided munitions are reportedly being rendered ineffective. The Department of Defense (DOD) is focusing on upgrading GPS to use stronger, military-specific signals, which will still be vulnerable to EW and anti-satellite capabilities. A more diverse and resilient alternate-PNT strategy is needed to ensure mission success.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Aprendizaje vertical

In the teaching and learning events of our life, there are characters who play key roles. Teachers, mentors, relatives, novels, songs, newspaper columns, often help us understand the questions in our heads. However, we often reject them because they are messages or attitudes from older people and the generation gap does not allow us to understand them well. The times of covid-19 have us locked up at home. They alert us that precisely “elderly people” are a vulnerable group. Also, we have been asked to take care of grandparents. If we are lucky enough to have an internet connection, it seems that we can learn anything we want with just one click. This could lead us to explore only what we find attractive, easy and comfortable. With this testimony, I invite you to acknowledge on the role of the elderly in the learning of entire generations. I call for openness towards diverse voices and for the understanding that we all play a role in moving towards a more mature society.

99 GENERAL AND MISCELLANEOUS↗

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗

A distributed voltage inference framework for cyber-physical attacks detection and localization in active distribution grids

The transition to active distribution grids with real-time monitoring and control depends on the proliferation of advanced communication networks and devices. This paradigm shift towards a cyber-physical architecture also introduces new vulnerabilities for adversaries to exploit and launch sophisticated cyber-physical attacks targeting grid observability. Current research highlights the challenges in distinguishing attacks on voltage phasor or nodal injection measurements and isolating multi-source attack locations in a multiphase distribution grid. The attack detection and localization methods in literature face accuracy issues, applications across diverse attack scenarios, or scalability limits. Here, to bridge these gaps, this paper proposes a distributed Voltage Inference framework for real-time detection and localization of cyber-physical attacks, addressing scalability, adaptability, and accuracy challenges in state-of-the-art methods. The proposed methodology leverages the distributed nature of the Voltage Inference framework through a two-step process of prediction and correction, together with a tractable graph partitioning approach, providing a reliable solution to identify compromised measurement sources and facilitate isolation. Extensive testing on IEEE 13 and 123-node distribution feeders underscores the algorithm’s efficacy, enhancing the security and resilience of active distribution grids against evolving cyber threats. Additionally, Hardware-in-the-Loop (HIL) implementation validates the proposed strategy’s practical applicability in real-world scenarios.

active distribution grids↗

Modeling nuclear waste disposal in crystalline rocks at the Forsmark and Olkiluoto repository sites – Evaluation of potential thermal–mechanical damage to repository excavations

We conduct coupled thermo-hydro-mechanical modeling of a KBS-3V repository design in crystalline rocks, using data and conditions from the Forsmark in Olkiluoto repository sites in Sweden and Finland. The study focuses on repository performance related to the impact of thermal and hydraulic evolution on the potential for thermal–mechanical damage to underground repository excavations. For the designs and conditions considered at the Forsmark and Olkiluoto repository sites, the simulations show a peak temperature well under the adopted performance target of a 100°C maximum temperature, whereas there is still a high potential for thermal–mechanical damage to the KBS-3V waste deposition holes. The thermal–mechanical damage is much more likely if rock permeability is so low that it delays saturation and swelling of bentonite-clay-based backfill beyond the time for the thermal–mechanical peak, which occurs 50 to 100 years after nuclear waste deposition. We also found that sidewalls of the KBS-3V emplacement tunnels are vulnerable to tensile fracturing due to the combined effect of thermal stressing and backfill swelling. The study highlights a strong interaction between bentonite-based backfill and host rock through capillary suction along with induced rock desaturation. A careful design and selection of the bentonite-clay-based backfill materials for KBS-3V tunnels and deposition holes can facilitate a timely saturation and backfill swelling that in turn can minimize thermal–mechanical damage.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Oak Ridge National Laboratory Pilot Demonstration of an Attestation and Anomaly Detection Framework using Distributed Ledger Technology for Power Grid Infrastructure

This report summarizes the design and pilot demonstration of a framework called Grid Guard that was created to provide increased data and device trustworthiness to electric grid devices by leveraging distributed ledger technology (DLT), specifically blockchain. Grid Guard contains a combination of core cryptographic methods such as the secure hash algorithm (SHA), and asymmetric cryptography, private permissioned blockchain, baselining configuration data, consensus algorithm (Raft) and the Hyperledger Fabric (HLF) framework. The system implements a low energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems such as substations, control centers and metering infrastructures. Blockchain is a distributed database structured that provides a practically unalterable (immutable) timeline of stored transactions. By relying on hashing and the Raft consensus algorithm, if an entity tries to illegitimately alter a record at one instance of the database the other ledger nodes are not altered. They work to cross-reference each other and easily locate any incorrectly added data and remove it. The bulk raw data is stored in an off-chain storage (outside of the blockchain ledger) and a hash of this baseline data is stored in the Blockchain ledger via hashing windows of time-series and configuration data, after aggregation and filtering. The bulk off-chain data repository is then considered to be trust-anchored using the hashes stored in the blockchain. To secure the electric grid testbed devices and data, device configuration baselines were compared to those baselines that had been previously stored in the ledger. Statistical baselines for device configurations, network communication patterns, and high-speed sensor data are calculated and then stored off-chain and hashes stored in the ledger. Measurements such as three-phase voltage and current, frequency, breaker status, protection scheme settings, network configuration settings (and other device configuration artifacts) and network traffic features (packet interarrival times) are compared every minute or other selected time windows. During phase 1 of the Grid Guard DLT project different DLT technologies were studies, and an assessment was performed on DLT technology vulnerabilities, uses, and key characteristics. DLT consensus protocols were studies (e.g., RAFT, named after Reliable, Replicated, Redundant, And Fault-Tolerant). Also, cryptography, public, private and permissioned or permissionless systems were assessed. Grid Guard implements a permissioned private DLT. Consensus algorithm selection and choice of DLT implementation depended heavily on the use-case. For this use-case, parameters were selected to measure performance and existing tools for assessment. Benchmarking was performed theoretically and practically. During phase 2 hashed transactions/blocks were inserted into the ledger every second. During phase 2 of the Grid Guard DLT project, a prototype framework was developed and demonstrated for attestation of critical substation devices and data using precision timing systems that use PTP and IRIG-B protocols) on a testbed of operational devices that emulated a distribution substation, control center, and power metering infrastructure using real Operational Technology (OT). The testbed includes OT devices such as protective relays, human machine interfaces (HMI), and power meters. To determine when to collect and compare system and network baselines, an initial examination of an anomaly detection capability to identify malicious manipulation of data streams was conducted. The resulting anomaly detection was demonstrated in a set of experiments and leveraged to trigger device artifact attestation checks. Attestation checks occur against device configuration baselines when compared with the immutable blockchain-stored baselines, which provided a cryptographically supported means by which to store baselines. The electrical substation-grid testbed was created to test the Grid Guard framework. The testbed emulates the operations of a portion of a power grid and SCADA systems as closely as possible. The testbed integrates real protocols, mainly IEC 61850 standard protocols, such as the Sampled Value (SV) and the GOOSE protocols. The testbed also supports DNP3 and other layer 2 and layer 3 protocols such as Telnet, SSH, SFTP/FTP and other proprietary protocols needed to connect to industrial control system equipment. The testbed emulates real power conditions using the OpalRT hardware-in-the-loop (HIL) device which can create fault situations that cannot be easily tested on real systems. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that electrical utilities commonly use.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using the Principals of Electrochemistry to Understand and Overcome the Complicated Degradation Mechanisms of Silicon Anodes in Lithium-Ion Batteries [Slides]

Battery technology is the most significant problem facing widespread market adoption of battery electric vehicles (BEVs). The low energy density of state-of-the-art lithium-ion electrode materials leaves BEV owners and prospective buyers with lower ranges than a comparable internal combustion engine (ICE) vehicle, and vulnerable to a nascent fast charging network. Silicon has the potential to increase the anode energy density by nearly ten times compared to the incumbent material (graphite) and make BEVs a more competitive transportation option. However, lithiated silicon is extremely reactive towards components of the electrolyte and forms a heterogeneous, complicated, and dynamic solid at its surface known as the solid electrolyte interphase (SEI). Ideally, the SEI would passivate the silicon surface, but continuous chemical degradation persists even when the battery is not operating. This reactivity reduces silicon anode lifetimes well below the necessary standards for BEVs. The NREL-led Silicon Consortium Project is dedicated to understanding and solving these mechanisms of degradation. Here, I will discuss an electrochemical method that provides deep insights into the silicon interface during battery operation. I will link these observations to fundamental electrochemical principals and how they translate into actionable strategies that extend the lifetime of silicon anodes.

25 ENERGY STORAGE↗

Towards generic memory forensic framework for programmable logic controllers

A Programmable Logic Controller (PLC) is a microprocessor-based controller that is used to automate physical processes in critical infrastructure and various other industries and manufacturing sectors. Initially, PLCs were completely isolated from the Internet, and cyber security was not incorporated at the time of development. The introduction of industry 4.0 and the evolution of ICS systems to communicate over public IP addresses from the Internet enhanced productivity and efficiency, but Internet connectivity exposed the systems and their vulnerabilities, which led to an increase in cyber attacks. When a system is sabotaged/compromised, security analysts need to get to the root cause of the attack as quickly as possible to recover the system. To do so, memory forensic analysis is critical to provide a unique insight into the run-time memory activities and extract a reliable source of evidence. In this paper, we analyze the memory structure of the Schneider Electric Modicon M221 PLC. To build a memory profile, we reverse engineer the communication protocol and conduct differential analysis to gain knowledge about the structure of the memory and the low-level representation of control logic instructions. We then identify dynamic and static memory regions by modifying different project fields and conducting differential analysis, which allows us to identify boundaries of critical memory structures and extract important forensic artifacts that can be found in the memory. The Python implementation of the memory profile can help reduce the time and effort required for manual analysis in case of cyber incident or system failure.

97 MATHEMATICS AND COMPUTING↗

Alerga: Alert Aggregation and Reasoning in GOOSE Simulation Pipeline

IEC 61850 specifies the Generic Object Oriented Substation Event (GOOSE) protocol as one option for low latency communication of substation-related events. Due to its strict timing requirements, GOOSE lacks any form of encryption or authentication and has only minimal integrity guarantees. These absences render the protocol vulnerable to a variety of communication anomalies, including adversarial action. In particular, an adversary with access to the substation network can launch man in the middle (MITM) attacks. We propose Alerga, a set of tools to allow operators to mitigate some of the risks of the protocol while retaining its strengths. To that end, we have developed first a GOOSE simulation pipeline including data generation, anomaly detection, alert handling, causal reasoning and data visualization components. The simulator is designed to be modular, allowing operators to swap components to better fit their network capabilities. The volume of alert traffic on a substation network threatens operators with alert fatigue. In order to combat this, we secondly present a novel form of alert aggregation and processing, offering operators a condensed view of any threats to the system. Thirdly, to facilitate the handling of these threats, our causal reasoning system traces the alerts back to their most likely cause, generating an initial hypothesis for operators to investigate.

alert aggregation↗

Supporting Cyber Security of Power Distribution Systems by Detecting Differences Between Real-time Micro-Synchrophasor Measurements and Cyber-Reported SCADA (Final Report)

As modern power grids tend towards greater levels of automation and communication, the challenges of identifying and mitigating vulnerabilities to cyber-attacks are ones that are increasingly demanding attention. Today’s power system has evolved to form the foundational bedrock of modern society, and an attack on this infrastructure could prove disastrous. In this project we were tasked to investigate the use of distribution synchrophasors as an independent isolated sensor network with which we can corroborate, or flag potentially spoofed,Supervisory Control And Data Acquisition (SCADA) data. We adapted an approach to marry the underlying physical properties of power systems with the network communications used by power systems in order to offer insights unattainable by either data stream isolation. While the concept of intrusion detection systems (IDS) is well understood for monitoring network traffic and traditional IT computing systems, the approach discussed in this report is motivated by several key notions: first, current SCADA communications alone presents an incomplete view of the grid. Second, the power grid, and the equipment controlling it, is grounded by laws of physics. Given this, we leverage high-frequency physical grid measurements to understand the physical condition of the grid, and combine this with SCADA. While high-frequency physical grid measurements and SCADA communication over Internet Protocol (IP) networks are fundamentally disparate information sources, when collectively examined through appropriate lenses, they offer a much more nuanced depiction of the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Digital Tools for the Preventive Conservation of Built Heritage: The Church of Santa Ana in Seville

Historic Building Information Modelling (HBIM) plays a pivotal role in heritage conservation endeavours, offering a robust framework for digitally documenting existing structures and supporting conservation practices. However, HBIM’s efficacy hinges upon the implementation of case-specific approaches to address the requirements and resources of each individual asset and context. This paper defines a flexible and generalisable workflow that encompasses various aspects (i.e., documentation, surveying, vulnerability assessment) to support risk-informed decision making in heritage management tailored to the peculiar conservation needs of the structure. This methodology includes an initial investigation covering historical data collection, metric and condition surveys and non-destructive testing. The second stage includes Finite Element Method (FEM) modelling and structural analysis. All data generated and processed are managed in a multi-purpose HBIM model. The methodology is tested on a relevant case study, namely, the church of Santa Ana in Seville, chosen for its historical significance, intricacy and susceptibility to seismic action. The defined level of detail of the HBIM model is sufficient to inform the structural analysis, being balanced by a more accurate representation of the alterations, through linked orthophotos and a comprehensive list of alphanumerical parameters. This ensures an adequate level of information, optimising the trade-off between model complexity, investigation time requirements, computational burden and reliability in the decision-making process. Field testing and FEM analysis provide valuable insight into the main sources of vulnerability in the building, including the connection between the tower and nave and the slenderness of the columns.

Chaves, Estefanía↗

Satellite-based Investigation of Power-Line Vegetation Encroachment in the US (SILVANUS)

Rapid wide-area assessments of vegetation encroachment on transmission and distribution line rights-of-way (ROW) is a highly desirable capability for understanding risks to the power grid during severe weather and wildfire events. Conventional assessments are time-consuming and expensive due to the need for in-situ inspections and the use of aerial assets. Performing conventional assessments on a wide area would require immense resources and time that might not be available within the horizon of an expected adverse event. Developing a capability to accurately assess vegetation encroachment into ROWs will enable faster analysis of potential grid vulnerabilities in NAERM. This project sought to develop a prototype capability for rapid ROW vegetation encroachment assessments by using Puerto Rico as a test case. Puerto Rico is a heavily forested island territory frequently impacted by tropical cyclones that threaten the electric grid by downing trees across transmission and distribution lines. Multispectral satellite imagery (MSI) enable very high resolution (i.e., 0.5 - 2 meter) assessment of vegetation conditions at scale and with revisit times appropriate for regular monitoring (e.g., weekly to quarterly, depending on cloud cover) of the entire island. Synthetic aperture radar (SAR) data from satellites was also investigated as solution to the cloud-cover issue as they are active sensors that emit and receive a microwave signal rather than relying on solar illumination, and are therefore unaffected by cloud cover and can collect data during day or night. Finally, MSI-derived digital surface models (DSMs) map the height of objects relative to sea level, and were assessed for their ability to estimate the height of forest canopies relative to coincident transmission lines. The results of the mapping investigation are described in this report.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Global projections of heat exposure of older adults

The global population is aging at the same time as heat exposures are increasing due to climate change. Age structure, and its biological and socio-economic drivers, determine populations’ vulnerability to high temperatures. Here we combine age-stratified demographic projections with downscaled temperature projections to mid-century and find that chronic exposure to heat doubles across all warming scenarios. Moreover, >23% of the global population aged 69+ will inhabit climates whose 95th percentile of daily maximum temperature exceeds the critical threshold of 37.5 °C, compared with 14% today, exposing an additional 177–246 million older adults to dangerous acute heat. Effects are most severe in Asia and Africa, which also have the lowest adaptive capacity. Our results facilitate regional heat risk assessments and inform public health decision-making.

60 APPLIED LIFE SCIENCES↗