Long-term Deployment Research Articles

Summarizing long-term changes in daily echogram patterns observed by moored echosounders in the U.S. Ocean Observatories Initiative network

Long-term deployments of autonomous echosounders deliver rich data embedded with information about mid-trophic level organisms of the marine food web. As a remote sensing tool, moored echosounders have played an important role in observing temporal changes of animal distributions in the water column over large temporal scales, ranging from months, seasons to years. Taking advantage of the power of matrix decomposition techniques in exploiting regularity in the data to automatically discover low-dimensional structures in large data sets, we apply Principal Component Pursuit (PCP) and temporally smooth Nonnegative Matrix Factorization (tsNMF) in a time-windowed fashion to analyze data from a network of moored, upward-looking echosounders deployed by the U.S. Ocean Observatories Initiative (OOI) from 2015 to 2018. We show that these echosounder time series are low-rank in nature and can be reproduced by a time-varying linear combination (activation) of a small number of distinct daily movement patterns (components). The components and the associated activation jointly provide a compact representation that is suitable for visualization and systematic analysis of mid-trophic animal activities in response to environmental changes, such as those from seasonal changes and extreme weather events.

Aquatic Eddy Covariance: The Method and Its Contributions to Defining Oxygen and Carbon Fluxes in Marine Environments

Aquatic eddy covariance (AEC) is increasingly being used to study benthic oxygen (O2) flux dynamics, organic carbon cycling, and ecosystem health in marine and freshwater environments. Because it is a noninvasive technique, has a high temporal resolution (∼15 min), and integrates over a large area of the seafloor (typically 10-100 m2), it has provided new insights on the functioning of aquatic ecosystems under naturally varying in situ conditions and has given us more accurate assessments of their metabolism. In this review, we summarize biogeochemical, ecological, and biological insightsgained from AEC studies of marine ecosystems. A general finding for all substrates is that benthic O2 exchange is far more dynamic than earlier recognized, and thus accurate mean values can only be obtained from measurements that integrate over all timescales that affect the local O2 exchange. Finally, we highlight new developments of the technique, including measurements of air-water gas exchange and long-term deployments.

The effect of device density on encounters by a mobile urban carnivore: Implications for managing peri-urban wild dogs

A variety of devices are often placed in the landscape to count, catch, kill, or otherwise manage wild species. It is important to understand the interactions between such devices and the species of interest to achieve and improve the efficiency of research and management objectives. Canid pest ejectors (CPEs; hereafter ejectors) are a device recently made available for use in Australia for the control of wild dogs (Canis familiaris) and European foxes (Vulpes vulpes), but there is limited data to inform best practice deployment for their safe and effective use in peri-urban environments. Data from eleven GPS collared wild dogs in peri-urban north-eastern Australia were used to quantify and compare encounters with three different densities (spacings of every 200 m, 500 m or intersections only) of modelled ejector locations placed in each respective animal’s home-range. Survival analyses was conducted on each modelled ejector to determine the effect of the three road-based deployment spacings and the effect of sex and season on the initial encounter by wild dogs. Ejector survivability (i.e. encounter) was significantly different between seasons for individual wild dogs, and between male and females, with ejectors placed within female home-ranges found to have significantly less survivorship than those in male home-ranges. Ejectors spaced at closer intervals (200 m) had a greater percentage of days with wild dog encounters. Placing ejectors at intersections provided the highest probability of wild dog encounter, with the average ejector at this location 1.5 times more likely to be encountered than those at the alternative spacings (200 m and 500 m). Our results show that achieving the most appropriate ejector placement depends on whether maximum interactions or maximum efficiency is desired, which are important considerations in the short- or long-term deployment of ejectors for the management of wild dogs. These findings assist the development of guidelines for the optimal and efficient placement of ejectors to ensure their safe and effective use in peri-urban environments. They also have additional relevance for other applications of device placement to survey or manage mobile species in peri-urban areas.

Power projection of Middle East states in the Horn of Africa: linking security burdens with capabilities

ABSTRACT The reported militarization of the Horn of Africa by Middle Eastern states has generated great interest among scholars and analysts alike. Their analyses and articles about the projections of power from the Middle East to the Horn of Africa are exaggerated, however, because they underappreciate the extant and enduring security burdens of the states in question and overestimate their national power capabilities. This is largely due to common misperceptions and faulty measures of military power. The question that this article answers is therefore not whether states such as Turkey or the United Arab Emirates (UAE) could redeploy limited military resources extra-regionally, but why would they and for how long? Using empirical data from interviews, defence statistics and data from recent deployments of the UAE and Turkey, we show how these key players are inhibited from prospective, long-term, and sustained deployments extra-territorially. This is supported by our analysis of the two states’ power capabilities (latent and actual) and their security burdens that constrain and limit options for the use of military tools abroad in the pursuit of foreign policy aims. This has led both Turkey and the UAE to engage in various forms of remote warfare involving local partners, allied militias, and mercenaries.

Survey of IoT for Developing Countries: Performance Analysis of LoRaWAN and Cellular NB-IoT Networks

Recently, Internet of Things (IoT) deployments have shown their potential for aiding the realisation of the Sustainable Development Goals (SDGs). Concerns regarding how the IoT can specifically drive SDGs 6, 11 and 9 in developing countries have been raised with respect to the challenges of deploying licensed and unlicensed low-power wide area network (LPWAN) IoT technologies and their opportunities for IoT consumers and service providers. With IoT infrastructure and protocols being ubiquitous and each being proposed for different SDGs, we review and compare the various performance characteristics of LoRaWAN and NB-IoT networks. From the performance analysis of our networks, NB-IoT, one of the standardised promising cellular IoT solutions for developing countries, is more expensive and less energy-efficient than LoRaWAN. Utilising the same user equipment (UE), NB-IoT consumed an excess of 2 mAh of power for joining the network and 1.7 mAh more for a 44-byte uplink message compared to LoRaWAN. However, NB-IoT has the advantage of reliably and securely delivering higher network connection capacity in IoT use cases, leveraging existing cellular infrastructure. With a maximum throughput of 264 bps at 837 ms measured latency, NB-IoT outperformed LoRaWAN and proved robust for machine-type communications. These findings will help IoT consumers and service providers understand the performance differences and deployment challenges of NB-IoT and LoRaWAN and establish new research directions to tackle IoT issues in developing countries. With Nigeria as a case study, for consumers and organisations at a crossroads in their long-term deployment decisions, the proposed LPWAN integrated architecture is an example of the deployment opportunities for consumer and industrial IoT applications in developing countries.

Enhanced Spatial–Temporal Map-Based Video Analytic Platform and Its Local- Versus Cloud-Based Deployment with Regional 511 Camera Network

This paper explores the cloud- versus server-based deployment scenarios of an enhanced computer vision platform for potential deployment on low-resolution 511 traffic video streams. An existing computer vision algorithm based on a spatial–temporal map and designed for high-angle traffic video like that of NGSIM (Next Generation SIMulation) is enhanced for roadside CCTV traffic camera angles. Because of the lower visual angle, determining the directions, splitting vehicles from occlusions, and identifying lane changes become difficult. A motion-flow-based direction determination method, a bisection occlusion detection and splitting algorithm, and a lane-change tracking method are proposed. The model evaluation is conducted by using videos from multiple cameras from the New Jersey Department of Transportation’s 511 traffic video surveillance system. The results show promising performance in both accuracy and computational efficiency for potential large-scale cloud deployment. The cost analysis reveals that at the current pricing model of cloud computing, the cloud-based deployment is more convenient and cost-effective for an on-demand network assessment. In contrast, the dedicated-server-based deployment is more economical for long-term traffic detection deployment.

Characterizing the Aging of Alphasense NO2 Sensors in Long-Term Field Deployments

Low-cost NO2 sensors have been widely deployed for atmospheric sampling. While their initial performance has been characterized, few studies have examined their long-term degradation. This study focused on the performance of Alphasense low-cost NO2 sensors (NO2-B42F and NO2-B43F) over 4 years (2016-2020). A total of 29 NO2 sensors from 10 batches were collocated 78 times at two sites with reference instruments. Raw signals from "functional" NO2 sensors correlated linearly with reference NO2 concentrations. After long-term deployment, sensor raw signals started to deviate from reference NO2 concentrations due to sensor aging, an accumulated effect after sensor unpacking. Several sensors eventually became "non-functional" as sensor raw signals showed no correlation with reference NO2 concentrations. Sensor aging and non-functionality may be primarily caused by expiration of the ozone (O3) scrubber built into these sensors so that sensors responded to both ambient NO2 and O3. The influence of O3 on sensor response is quantified through the permutation importance method. Most of the sensors are non-functional after approximately 200-400 days of deployment, and no sensor was functional after 400 days of deployment. This result agrees well with the estimated lifetime of the built-in ozone scrubbers considering the ambient ozone concentration in the Pittsburgh area where these sensors were deployed. To ensure reliable data quality in long-term field deployments, we recommend collocating NO2 sensors with reference instruments regularly after 200-400 days of deployment to identify and replace non-functional sensors in a timely manner.

Underwater dual-magnification imaging for automated lake plankton monitoring

The Dual Scripps Plankton Camera (DSPC) is a new approach for automated in-situ monitoring of phyto- and zooplankton communities based on a dual magnification dark-field imaging microscope. Here, we present the DSPC and its associated image processing while evaluating its capabilities in i) detecting and characterizing plankton species of different size and taxonomic categories and ii) measuring their abundance in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scaled with measurements derived by microscopy. In the field, a DSPC installed permanently at 3 m depth in Lake Greifensee (Switzerland) delivered images of plankton individuals, colonies, and heterospecific aggregates at hourly timescales without disrupting natural arrangements of interacting organisms, their microenvironment or their behavior. The DSPC was able to track the dynamics of taxa, mostly at the genus level, in the size range between ∼10 μm to ∼ 1 cm, covering many components of the planktonic food web (including parasites and potentially toxic cyanobacteria). Comparing data from the field-deployed DSPC to traditional sampling and microscopy revealed a general overall agreement in estimates of plankton diversity and abundances. The most significant disagreements between traditional methods and the DSPC resided in the measurements of zooplankton community properties. Our data suggest that the DSPC is better equipped to study the dynamics and demography of heterogeneously distributed organisms such as zooplankton, because high temporal resolution and continuous sampling offer more information and less variability in taxa detection and quantification than traditional sampling. Time series collected by the DSPC depicted ecological succession patterns, algal bloom dynamics and diel fluctuations with a temporal frequency and morphological resolution that was never observed by traditional methods. Access to high frequency, reproducible and real-time data of a large spectrum of the planktonic ecosystem expands our understanding of both applied and fundamental plankton ecology. We conclude the DSPC is robust for both research and water quality monitoring and suitable for stable long-term deployments.

Examining wind energy deployment pathways in complex macro-economic and political settings using a fuzzy cognitive map-based method

Long-term sustainable wind energy deployment faces an array of challenges due to various complex interconnected impediment factors. These inherent endogenous and exogenous uncertainties preclude obtaining an accurate future trend, which in turn complicates the design of the good policy. This study employs Fuzzy Cognitive Maps (FCMs) to semi-quantitatively explore the scenarios of wind energy deployment in Iran. The FCM-based framework was built using participatory workshops and a subsequent questionnaire survey to identify 26 influential factors shaping the dynamics of the system. The developed scenarios originated from the latest narratives of real-world geopolitical variations. The findings demonstrated that the sector is governed by six major groupings of factors predominated by economic and political concepts with strong interconnections between them. Five key concepts, including two economic, one legal, and two political, were ascertained that contribute to the stability of the system. Of the four scenarios, only one optimistic trajectory expects an acceleration in the deployment. Another scenario projects that there will not be any considerable change between the future scheme and the current state of development. However, the other scenarios envisage a substantially slower growth than the current trend.

Field evaluation of a low-uptake VOC passive sampler suitable for long-term deployments

Passive samplers have proven to be effective for continuous monitoring of volatile organic compounds (VOCs) in ambient air in remote, urban and industrial environments. Thermal desorption tubes fitted with endcaps that facilitate passive uptake through diffusion are now routinely used for monitoring fugitive benzene emissions from refineries and petrochemical facilities across North America (EPA Method 325A/B). However, deployment periods of 14 days are typically employed to minimize the risk of poor retention, requiring 26 deployments per year to return an annual average concentration for comparison with chronic exposure health-based standards. Here, we explore extending the deployment duration of these passive samplers to one, two and three months by limiting VOC uptake rates using an alternative diffusive endcap featuring a smaller cross-sectional area. Field testing was performed beside a major highway during two separate three-month campaigns. Uptake rates for benzene, toluene, ethylbenzene and xylenes (BTEX) were observed to remain linear for deployments of up to three months when using the low-uptake endcaps. Application of the low-uptake endcaps and the uptake rates determined here will enable annual average concentrations of BTEX to be calculated using only four tube deployments per year. The cost savings associated with this decreased deployment frequency will facilitate increased spatial resolution during future exposure assessment studies. The stability of selected air toxics within the tubes was also assessed and the results suggest that while aromatic VOCs are stable for storage times of at least 70 days, chloroform and trichloroethylene begin to degrade within two weeks of sampling.

Hard-to-Abate Sectors: The role of industrial carbon capture and storage (CCS) in emission mitigation

Carbon capture and storage (CCS) technology is an important option in the portfolio of emission mitigation solutions in scenarios that lead to deep reductions in greenhouse gas (GHG) emissions. We focus on CCS application in hard-to-abate sectors (cement industry, iron and steel, chemicals) and introduce industrial CCS options into the MIT Economic Projection and Policy Analysis (EPPA) model, a global multi-region multi-sector energy-economic model that provides a basis for the analysis of long-term energy deployment. We use the EPPA model to explore the potential for industrial CCS in different parts of the world, under the assumptions that CCS is the only mitigation option for deep GHG emission reductions in industry and that negative emission options are not available for other sectors of the economy. We evaluate CCS deployment in a scenario that limits the increase in average global surface temperature to 2 °C above preindustrial levels. When industrial CCS is not available, global costs of reaching the target are higher by 12% in 2075 and 71% in 2100 relative to the cost of achieving the policy with CCS. Overall, industrial CCS enables continued growth in the use of energy-intensive goods along with large reductions in global and sectoral emissions. We find that in scenarios with stringent climate policy, CCS in the industry sector is a key mitigation option, and our approach provides a path to projecting the deployment of industrial CCS across industries and regions.

BoSL FAL pump: A small, low-cost, easily constructed, 3D-printed peristaltic pump for sampling of waters

Water sampling is an essential undertaking for water utilities and agencies to protect and enhance our natural resources. The high variability in water quality, however, often necessitates a spatially distributed sampling program which is impeded by high-cost and large sampling devices. This paper presents the BoSL FAL Pump - a low-cost, easily constructed, 3D-printed peristaltic pump which can be made from commonly available components and is sized to suit even the most space constrained installations. The pump is 38 mm in height and 28 mm in diameter, its components cost $19 AUD and the construction time is just 12 min (excluding 3D printing times). The pump is driven by a direct current motor which is commonly available, cheap and allows for flexibility in the energy supply (5–12 V). Optionally, the pump has a Hall effect sensor and magnet to detect rotation rates and pumping volumes to improve the accuracy of pumping rates/volumes. The pump can be easily controlled by commonly available microcontrollers, as demonstrated by this paper which implements the ATmega328P on the Arduino Uno R3. This paper validates the pump for long-term deployments at flow rates of up to 13 mL per minute in 0.14 mL volume increments at accuracy levels of greater than 99%. The pump itself is scalable, allowing for a wider range of pumping rates when, for example, large volume samples are required for pathogen and micropollutant detection.

Effects of seasonal biofouling on diffusion coefficients through filter membranes with different hydrophilicities in natural waters

Biofouling is a major issue for the diffusive gradients in thin films (DGT) passive samplers during long-term deployment. Although biofilms have a negative effect on DGT samplers, the effects of seasonal biofilms on the flux of targets through different membranes are poorly understood. Herein, we evaluated the relationship between the biofilm growth and diffusion coefficients' decline rate through two membranes with different hydrophilicities during the four seasons in natural waters. Cu2+ and tetracycline were selected as the model metal and organic contaminant, respectively. Rapid biofilm growth on the membrane surface was observed, and the fouling growth rate increased in the order: winter < spring < autumn < summer. Biofouling had a negative effect on the diffusion coefficients of Cu2+ and tetracycline. Generally, the decreasing tendency of diffusion coefficients agreed with the increasing tendency of the fouling growth rate. Biofilms in a lag phase with little bacterial colonies had insignificant effect on the diffusion coefficients. After 30 days, the decline ratios of diffusion coefficients were in the range of 38.14%–53.05%, 69.63%–83.19%, 51.57–68.42%, and 19.43–35.84%, respectively, during the spring, summer, autumn and winter. The flux through the membrane with higher hydrophilicity was greater. Both the hydrophilicity of membrane and structure of target analytes had important effects on the diffusion coefficients through biofouled membranes. Owing to similar physical and chemical characteristics, there was insignificant difference in diffusion coefficients decline trend between the Yalu River water and Hunhe River water in the summer.

Coastal upwelling along the west coast of Sabah and its impact on coastal aquaculture management

The aquaculture industry in Malaysia is currently growing at nearly 9 percent per year and is generating more than 250,000 tons of production per annum. However, little commercial scale aquaculture is present along the west coast of the state of Sabah. Few if any studies have been conducted to investigate aquaculture site suitability along the west coast of Sabah and the wider west coast of Borneo from an environmental or coastal management perspective. To determine the site suitability for marine aquaculture and other coastal resource users there needs to be an improved understanding of the physical, chemical, and biological characteristics of the coastal environment. One year of data collection including the long-term deployment of Conductivity, Temperature and Depth (CTD) sensors, and bi-monthly water column and seabed sediment sampling was undertaken to provide an indication if the coastal waters between Kota Belud and Kudat are suitable for marine aquaculture purposes. The site provided an analogy for much of the west coast of Borneo, especially the west coast of Sabah, due to similar oceanographic drivers in the region. Results indicated that during the NE monsoon period there is dramatic decrease in water temperature due to the upwelling of cold dense nutrient rich water onto the west coast of Sabah's continental shelf from deeper offshore areas of the South China Sea. This large change in temperature will likely rule out the potential commercial marine grow out of such species as Asian Seabass and perhaps Tropical Spiny Lobsters. Other species such as Cobia, Grouper and Snapper which have a wider tolerance for temperature change will likely be suitable but at times will be stressed due to magnitude of the observed changes. Such observations have ramifications in regard to site suitability for future resource consent applications for open ocean and coastal aquaculture along the west coast of Borneo. In summary the study highlights how physical processes can impact on resource use and development in a coastal setting.

An Implementation of a Multi-Hop Underwater Wireless Sensor Network using Bowtie Antenna

Water quality is a growing area of research, with more and more focus in the UK and globally on environmental issues and water quality. Current methods of monitoring environmental data such as air quality have continued to develop, spurred on by the growth of the Internet of Things. However, water quality monitoring mainly still depends on manual sample collection. This research presents the first implementation of a multi-hop underwater radio frequency sensor network using bowtie antennas combined with the 433 MHz frequency and a controlled flooding routing approach. The experimental work was conducted in the water reservoir and demonstrates the potential of multi-hop routing in underwater sensor networks to extend range to 19 meters as well as improvements on communication distances from 7 meters previously to 17 meters using radio frequency communications in an underwater environment. Simulated results show that the experimental platform used could enable the long-term deployment of an underwater wireless sensor network that used RF for periods of over a year with support for a 100 sensor node network broadcasting twice daily remaining active for 418 days or a 100 sensor node network broadcasting hourly remaining active for 406 days before any node deaths.

Research on China’s technology lists for addressing climate change

The compilation of technology lists addressing climate change has a guiding effect on promoting technological research and development, demonstration, and popularization. It is also crucial for China to strengthen ecological civilization construction, achieve the carbon emission peak and carbon neutrality target, and enhance global climate governance capabilities. This study first proposes the existing classification outline of the technology promotion lists, technology demand lists, and future technology lists. Then, different methodologies are integrated on the basis of the existing outline of four technology lists: China’s existing technological promotion list for addressing climate change, China’s demand list for climate change mitigation technology, China’s key technology list for addressing climate change, and China’s future technology list for addressing climate change. What’s more, core technologies are analyzed in the aspects of technology maturity, carbon reduction cost, carbon reduction potential, economic benefits, social influence, uncertainty, etc. The results show that: key industries and sectors in China already have relatively mature mitigation/adaptation technologies to support the achievement of climate change targets. The multi-sectoral system of promoting climate-friendly technologies has been established, which has played an active role in tackling climate change. Currently, climate technology needs are concentrated in the traditional technology and equipment upgrading, renewable energy technology, and management decision-making support technology. The key technologies are concentrated in 3 major areas and 12 technological directions that urgently need a breakthrough. For carbon emmission peak and nentrality, carbon depth reduction and zero carbon emissions and geoengineering technology (CDR and SRM) have played an important role in forming the structure of global emissions and achieving carbon neutrality in the future. Thus, the uncertainty assessment for the comprehensive technology cost-effectiveness, technology integration direction, technical maturity, ethics and ecological impacts is supportive to the national technology strategy. Finally, the presented study proposes several policy implications for medium- and long-term technology deployment, improving technology conversion rate, promoting the research and development of core technologies, and forming a technology list collaborative update and release mechanism.

Polymer multilayer film with excellent UV-resistance &amp; high transmittance and its application for glass-free photovoltaic modules

The choice of polymer material as photovoltaic (PV) module front cover is important to realize high optical transparency and high UV-resistance. We have successfully designed and prepared a polymer multilayer film (PMF) with UV-resistance & High transmittance which could provide a low-cost, simple but effective way to address the weight issue of PV modules. Compared with conventional PV glass which has transmissivity greater than 90% at 400–1200 nm, the PMF we designed has equivalent transmissivity between 410 and 1200 nm and high reflectance (R>90%) at 320–400 nm.The glass-free and semi-flexible crystalline silicon PV module has a power generation efficiency of 20.37% and the efficiency of the control group with glass as a cover layer is 20.67%. The weight of our designed module can be greatly reduced by 85%. The photo aging experiment shows that the PMF has an excellent UV-resistance which makes it suitable for long-term outdoor deployment. The materials and multiple co-extrusion processes necessary to fabricate such films are suitable for large-scale manufacturing. This research provides valuable contributions in the future preparations and applications for PMF. • The weight of our designed module can be reduced by 85.8%. • The polymer multilayer film shows excellent UV-resistance and high optical transparency. • The materials and multiple co-extrusion processes are suitable for large-scale manufacturing.

Engineering application of power generation technology for adding and reducing silt in multi-sediment reservoir

The uncoordinated relationship between water and sand is a major technical problem that has not been completely eradicated or resolved in the construction of water conservancy and hydropower in the world. In response to the problem of sedimentation, scientific research, design and operation units have carried out research and application of key technologies for the addition of sediment-laden reservoirs to reduce siltation and power generation. The research results have been successfully applied to the Liujiaxia Tao River Mouth Desilting Tunnel and Machine Expansion Project. The Liujiaxia Reservoir has successfully solved the sediment discharge and silt reduction, increased the effective storage capacity of the reservoir, improved the power generation efficiency of the reservoir, improved the water quality of the reservoir, and provided support for the long-term spatial deployment of water resources.

Bridge mode shape identification using moving vehicles at traffic speeds through non‐parametric sparse matrix completion

Advances in smart infrastructure produces a natural demand of system identification techniques for structural health and performance monitoring that can be scaled to regions and large asset inventories. Conventional approaches require sensors to be installed, often in long-term deployments, on the monitored infrastructure systems, which is a costly undertaking when thousands of systems (e.g., bridges) need to be monitored. This paper presents a novel mode shape identification method for bridges that uses data collected from moving vehicles as input—a paradigm that can overcome limitations associated with conventional approaches. The method consists of two steps. First, the data collected from moving measurement points are mapped to virtual fixed points to generate a sparse matrix. Then, a “soft-imputing” technique is employed to fill the sparse matrix. Finally, a singular value decomposition is applied to extract the mode shapes of the bridge. Experiments with synthetic, yet realistic, data are conducted to verify the method. The sensitivity of the proposed approach to different factors, including the number of vehicles, car speed, road roughness, and measurement errors, are also investigated. The results show that the proposed method is capable of identifying the mode shapes of the bridge accurately.

Implementing Radical Innovation in Renewable Energy Experience Curves

Cost reductions in nascent forms of Renewable Energy Technology (RET) are essential for them to contribute to the energy mix. Policy intervention can facilitate this cost reduction; however, this may require a significant investment from the public sector. These cost reductions fall into two broad categories: (1) incremental cost reductions through continual improvements to existing technologies, and (2) radical innovation where technologies that significantly differ from the incumbents are developed. This study presents a modelling methodology to integrate radical innovation in RET experience curve and learning investment analysis, using wave energy as an example nascent RET. This aims to quantify the potential effects of radical innovation on the learning investment, allowing the value of successful innovation to be better analysed. The study highlights the value offered by radical innovations in long-term deployment scenarios for wave energy. This suggests that high-risk R&amp;D efforts in nascent RET sectors, even with low success rates, could still present significant expected value in offsetting future revenue support.