Compound climate events transform electrical power shortfall risk in the Pacific Northwest

Meteorological drivers of resource adequacy failures in current and high renewable Western U.S. power systems

Power system resource adequacy (RA), or its ability to continually balance energy supply and demand, underpins human and economic health. How meteorology affects RA and RA failures, particularly with increasing penetrations of renewables, is poorly understood. We characterize large-scale circulation patterns that drive RA failures in the Western U.S. at increasing wind and solar penetrations by integrating power system and synoptic meteorology methods. At up to 60% renewable penetration and across analyzed weather years, three high pressure patterns drive nearly all RA failures. The highest pressure anomaly is the dominant driver, accounting for 20-100% of risk hours and 43-100% of cumulative risk at 60% renewable penetration. The three high pressure patterns exhibit positive surface temperature anomalies, mixed surface solar radiation anomalies, and negative wind speed anomalies across our region, which collectively increase demand and decrease supply. Our characterized meteorological drivers align with meteorology during the California 2020 rolling blackouts, indicating continued vulnerability of power systems to these impactful weather patterns as renewables grow.

A Stunt of Sustainability: Artificial Humic Substances Can Generate and Stabilize Single Fe0 Species on Mineral Surfaces

Iron species are omnipresent in fertile soils and contribute to biological and geological redox processes. Here, we show by advanced electron microscopy techniques that an important, but previously not considered iron species, single atom Fe0 stabilized on clay mineral surfaces, is contained in soils when humic substances are present. As the concentration of neutral iron atoms is highest under frost logged soil conditions, their formation can be attributed to the action of a then reductive microbiome. The Fe0 /Fe2+ couple is with -0.04 V standard potential highly suited for natural environmental remediation and detoxification, and its occurrence can help to explain the sustained auto-detoxification of black soils.

High-Performance Co-production of Electricity and Light Olefins Enabled by Exsolved NiFe Alloy Nanoparticles from a Double-Perovskite Oxide Anode in Solid Oxide-Ion-Conducting Fuel Cells

Light olefins (LOs) such as ethylene and propylene are critical feedstocks for many vital chemicals that support our economy and daily life. LOs are currently mass produced via steam cracking of hydrocarbons, which is highly energy intensive and carbon polluting. Efficient, low-emission, and LO-selective conversion technologies are highly desirable. Electrochemical oxidative dehydrogenation of alkanes in oxide-ion-conducting solid oxide fuel cell (SOFC) reactors has been reported in recent years as a promising approach to produce LOs with high efficiency and yield while generating electricity. We report here an electrocatalyst that excels in the co-production. The efficient catalyst is NiFe alloy nanoparticles (NPs) exsolved from a Pr- and Ni-doped double perovskite Sr2Fe1.5Mo0.5O6 (Pr0.8Sr1.2Ni0.2Fe1.3Mo0.5O6-δ, PSNFM) matrix during SOFC operation. We show evidence that Ni is first exsolved, which triggers the following Fe-exsolution, forming the NiFe NP alloy. At the same time as the NiFe exsolution, abundant oxygen vacancies are created at the NiFe/PSNFM interface, which promotes the oxygen mobility for oxidative dehydrogenation of propane (ODHP), coking resistance, and power generation. At 750 °C, the SOFC reactor with the PSNFM catalyst reaches a propane conversion of 71.40% and LO yield of 70.91% under a current density of 0.3 A cm-2 without coking. This level of performance is unmatchable by the current thermal catalytic reactors, demonstrating the great potential of electrochemical reactors for direct hydrocarbon conversion into value-added products.

Drought impacts on the electricity system, emissions, and air quality in the western United States

The western United States has experienced severe drought in recent decades, and climate models project increased drought risk in the future. This increased drying could have important implications for the region's interconnected, hydropower-dependent electricity systems. Using power-plant level generation and emissions data from 2001 to 2021, we quantify the impacts of drought on the operation of fossil fuel plants and the associated impacts on greenhouse gas (GHG) emissions, air quality, and human health. We find that under extreme drought, electricity generation from individual fossil fuel plants can increase up to 65% relative to average conditions, mainly due to the need to substitute for reduced hydropower. Over 54% of this drought-induced generation is transboundary, with drought in one electricity region leading to net imports of electricity and thus increased pollutant emissions from power plants in other regions. These drought-induced emission increases have detectable impacts on local air quality, as measured by proximate pollution monitors. We estimate that the monetized costs of excess mortality and GHG emissions from drought-induced fossil generation are 1.2 to 2.5x the reported direct economic costs from lost hydro production and increased demand. Combining climate model estimates of future drying with stylized energy-transition scenarios suggests that these drought-induced impacts are likely to remain large even under aggressive renewables expansion, suggesting that more ambitious and targeted measures are needed to mitigate the emissions and health burden from the electricity sector during drought.

Developing a novel framework to re-examine half a century of compound drought and heatwave events in mainland China

Compound drought and heatwave events (CDHEs) are more devastating than single drought or heatwave events and have gained widespread attention. However, previous studies have not investigated the impacts of the precipitation attenuation effect (PAE) (i.e., the effect of previous precipitation on the dryness and wetness of the current system is attenuated) and event merging (EM) (i.e., merging two CDHEs with short intervals into a single event). Moreover, few studies have assessed short-term CDHEs within monthly scales and their variation characteristics under different background temperatures. Here we propose a novel framework for assessing CDHEs on a daily scale and considering the PAE and EM. We applied this framework to mainland China and investigated the spatiotemporal variation of the CDHE indicators (spatial extent (CDHE_spa), frequency (CDHE_fre), duration (CHHE_dur), and severity (CDHE_sev)) from 1968 to 2019. The results suggested that ignoring the PAE and EM led to significant changes in the spatial distribution and magnitude of the CDHE indicators. Daily-scale assessments allowed for monitoring the detailed evolution of CDHEs and facilitated the timely development of mitigation measures. Mainland China experienced frequent CDHEs from 1968 to 2019 (except for the southwestern part of Northwest China (NWC) and the western part of Southwest China (SWC)), whereas, hotspot areas of CDHE_dur and CDHE_sev had a patchy distribution in different geographical subregions. The CDHE indicators were higher in the warmer 1994-2019 period than in the colder 1968-1993 period, but the rate of increase of the indicators was lower or there was a downward trend. Overall, CDHEs in mainland China have been in a state of remarkable continuous strengthening over the past half a century. This study provides a new quantitative analysis approach for CDHEs.

Distance measurements between 5 nanometer diamonds - single particle magnetic resonance or optical super-resolution imaging?

5 nanometer sized detonation nanodiamonds (DNDs) are studied as potential single-particle labels for distance measurements in biomolecules. Nitrogen-vacancy (NV) defects in the crystal lattice can be addressed through their fluorescence and optically-detected magnetic resonance (ODMR) of a single particle can be recorded. To achieve single-particle distance measurements, we propose two complementary approaches based on spin-spin coupling or optical super-resolution imaging. As a first approach, we try to measure the mutual magnetic dipole-dipole coupling between two NV centers in close DNDs using a pulse ODMR sequence (DEER). The electron spin coherence time, a key parameter to reach long distance DEER measurements, was prolonged using dynamical decoupling reaching T _2,DD ≈ 20 μs, extending the Hahn echo decay time T ₂ by one order of magnitude. Nevertheless, an inter-particle NV-NV dipole coupling could not be measured. As a second approach, we successfully localize the NV centers in DNDs using STORM super-resolution imaging, achieving a localization precision of down to 15 nm, enabling optical nanometer-scale single-particle distance measurements.

Designed Synthesis of Compartmented Bienzyme Biocatalysts Based on Core-Shell Zeolitic Imidazole Framework Nanostructures

For complex cascade biocatalysis, multienzyme compartmentalization helps to optimize substrate transport channels and promote the orderly and tunable progress of step reactions. Herein, a simple and general synthesis strategy is proposed for the construction of a multienzyme biocatalyst by compartmentalizing glucose oxidase and horseradish peroxidase (GOx and HRP) within core-shell zeolite imidazole frameworks (ZIF)-8@ZIF-8 nanostructures. Owing to the combined effects of biomimetic mineralization and the fine regulation of the ZIF-8 growth process, the uniform shell encloses the seed (core) surface by epitaxial growth, and the bienzyme system is accurately localized in a controlled manner. The versatility of this strategy is also reflected in ZIF-67. Meanwhile, with the ability to covalently bind divalent metal ions, lithocholic acid (LCA) is used as a competitive ligand to improve the pore structure of the ZIF from a single micropore to a hierarchical micro/mesopore network, which greatly increases mass transfer efficiency. Furthermore, the multienzyme cascade reaction is exemplified by the oxidation of o-phenylenediamine (OPD). The findings show that the bienzyme assembly strategy significantly affects the biocatalytic efficiency mainly by influencing the utilization efficiency of the intermediate (Hydrogen peroxide, H₂ O₂ ) between the step reactions. This study sheds new light on facile synthetic routes to constructing in vitro multienzyme biocatalysts.

Consideration of compound drivers and impacts in the disaster risk reduction cycle

Consideration of compound drivers and impacts are often missing from applications within the Disaster Risk Reduction (DRR) cycle, leading to poorer understanding of risk and benefits of actions. The need to include compound considerations is known, but lack of guidance is prohibiting practitioners from including these considerations. This article makes a step toward practitioner guidance by providing examples where consideration of compound drivers, hazards, and impacts may affect different application domains within disaster risk management. We discern five DRR categories and provide illustrative examples of studies that highlight the role of "compound thinking" in early warning, emergency response, infrastructure management, long-term planning, and capacity building. We conclude with a number of common elements that may contribute to the development of practical guidelines to develop appropriate applications for risk management.

Memory-aware end-to-end learning of channel distortions in optical coherent communications

We implement a new variant of the end-to-end learning approach for the performance improvement of an optical coherent-detection communication system. The proposed solution enables learning the joint probabilistic and geometric shaping of symbol sequences by using auxiliary channel model based on the perturbation theory and the refined symbol probabilities training procedure. Due to its structure, the auxiliary channel model based on the first order perturbation theory expansions allows us performing an efficient parallelizable model application, while, simultaneously, producing a remarkably accurate channel approximation. The learnt multi-symbol joint probabilistic and geometric shaping demonstrates a considerable bit-wise mutual information gain of 0.47 bits/2D-symbol over the conventional Maxwell-Boltzmann shaping for a single-channel 64 GBd transmission through the 170 km single-mode fiber link.

The Impact of Climate Change on Mental Health and Emotional Wellbeing: A Narrative Review of Current Evidence, and its Implications

Converging global evidence highlights the dire consequences of climate change for human mental health and wellbeing. This paper summarises literature across relevant disciplines to provide a comprehensive narrative review of the multiple pathways through which climate change interacts with mental health and wellbeing. Climate change acts as a risk amplifier by disrupting the conditions known to support good mental health, including socioeconomic, cultural and environmental conditions, and living and working conditions. The disruptive influence of rising global temperatures and extreme weather events, such as experiencing a heatwave or water insecurity, compounds existing stressors experienced by individuals and communities. This has deleterious effects on people's mental health and is particularly acute for those groups already disadvantaged within and across countries. Awareness and experiences of escalating climate threats and climate inaction can generate understandable psychological distress; though strong emotional responses can also motivate climate action. We highlight opportunities to support individuals and communities to cope with and act on climate change. Consideration of the multiple and interconnected pathways of climate impacts and their influence on mental health determinants must inform evidence-based interventions. Appropriate action that centres climate justice can reduce the current and future mental health burden, while simultaneously improving the conditions that nurture wellbeing and equality. The presented evidence adds further weight to the need for decisive climate action by decision makers across all scales.

Tubular chitosan hydrogels with a tuneable lamellar structure programmed by electrical signals

The discovery of facile methods to create complex lamellar structures in hydrogels, which mimic the exquisite structures in nature, remains a great challenge. In this work, an ordered lamellar structured hydrogel from the stimuli-responsive amino-polysaccharide chitosan is fabricated by an electro-assembly process, during which the diffusion of OH^- and the electrophoresis of the chitosan chains play important roles. Importantly, a complex ordered/disordered structure of chitosan hydrogel can be regulated with high fidelity by programming the input electrical signals.

Featuring few essential Raman spectroscopic signatures between heterogeneous cells

Here we demonstrate it is instructive to quantify cell Raman spectroscopy by sparse regularization. To be able to extract the specific spectral differences in a heterogeneous cell system with great spectroscopic similarities derived from many common biomolecular components, the maximum information entropy probability was proposed and exemplified by identifying normal lymphocytes from leukemia cells. The essential spectroscopic features were observed to locate at three Raman peaks whose spectral signatures were commensurate. The applicability of the extracted features was acknowledged by that the predicted identification accuracy of up to 93% was still achieved when only two peaks were loaded into decision tree model, which may provide the possibility of a clinically rapid hematological malignancy detection.

A highly efficient three-solvent methodology for separating colloidal nanoparticles

This study has established a three-solvent methodology for separating nanomaterials, such as monometallic nanoparticles, miscible and immiscible nanoalloys. After systematically investigating the separation methods in two-solvent and three-solvent systems, a three-solvent theoretical model has been proposed to thoroughly reveal the centrifugation mechanism of colloidal particles. PVP plays an important role in the formation of emulsion droplets as the key factor for separation. Based on the three-solvent model, a novel solvent system has been discovered, with low-toxicity solvents and high separation efficiency. This study can open a new path for the separation of colloidal particles in both research and industrial fields and further promote the development of functional nanomaterials in greener pathways.

Population exposure to compound extreme events in India under different emission and population scenarios

It is well understood that India is largely exposed to different climate extremes including floods, droughts, heat waves, among others. However, the exposure of co-occurrence of these events is still unknown. The present analysis, first study of its kind, provides the projected changeability of five different compound extremes under three different emission scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5). These changes are combined with population projection under SSP2, SSP3, and SSP5 scenarios to examine the total exposure in terms of number of persons exposed during 2021-2060 (T1) and 2061-2100 (T2). Here, the outputs from thirteen GCMs are used under CMIP6 experiment. The findings from the study show that all the compound extremes are expected to increase in future under all the emission scenarios being greater in case of SSP5-8.5. The population exposure is highest (2.51- to 4.96-fold as compared to historical) under SSP3-7.0 scenario (2021-2100 i.e., T1 and T2) in case of coincident heat waves and droughts compound extreme. The total exposure in Central Northeast India is projected to be the highest while Hilly Regions are likely to have the lowest exposure in future. The increase in the exposure is mainly contributed from climate change, population growth and their interaction depending on different kinds of compound extremes. The findings would help in devising sustainable policy strategies to climate mitigation and adaptation.

Reconstruction of bimetal CoFe0.13-MOF to enhance the catalytic performance in the oxygen evolution reaction

Oxygen evolution reaction (OER) is a key process in electrochemical energy conversion systems. This paper found that the solvothermal reconstruction could resume the original morphology and generate more oxygen vacancies on the surface of oxyhydroxide. The reconstructed electrocatalyst (re-CoFe_0.13O_xH_y) presents promising long-term stability (>85 h) under 1 M KOH condition without replacing the electrolyte.

Plasmonic-perovskite solar cells, light emitters, and sensors

The field of plasmonics explores the interaction between light and metallic micro/nanostructures and films. The collective oscillation of free electrons on metallic surfaces enables subwavelength optical confinement and enhanced light-matter interactions. In optoelectronics, perovskite materials are particularly attractive due to their excellent absorption, emission, and carrier transport properties, which lead to the improved performance of solar cells, light-emitting diodes (LEDs), lasers, photodetectors, and sensors. When perovskite materials are coupled with plasmonic structures, the device performance significantly improves owing to strong near-field and far-field optical enhancements, as well as the plasmoelectric effect. Here, we review recent theoretical and experimental works on plasmonic perovskite solar cells, light emitters, and sensors. The underlying physical mechanisms, design routes, device performances, and optimization strategies are summarized. This review also lays out challenges and future directions for the plasmonic perovskite research field toward next-generation optoelectronic technologies.

Climate-Induced Tradeoffs in Planning and Operating Costs of a Regional Electricity System

Electricity grid planners design the system to supply electricity to end-users reliably and affordably. Climate change threatens both objectives through potentially compounding supply- and demand-side climate-induced impacts. Uncertainty surrounds each of these future potential impacts. Given long planning horizons, system planners must weigh investment costs against operational costs under this uncertainty. Here, we developed a comprehensive and coherent integrated modeling framework combining physically based models with cost-minimizing optimization models in the power system. We applied this modeling framework to analyze potential tradeoffs in planning and operating costs in the power grid due to climate change in the Southeast U.S. in 2050. We find that planning decisions that do not account for climate-induced impacts would result in a substantial increase in social costs associated with loss of load. These social costs are a result of under-investment in new capacity and capacity deratings of thermal generators when we included climate change impacts in the operation stage. These results highlight the importance of including climate change effects in the planning process.

Exploring the Grid Value of Offshore Wind Energy in Oregon

The significant offshore wind energy potential of Oregon faces several challenges, including a power grid which was not developed for the purpose of transmitting energy from the ocean. The grid impacts of the energy resource are considered through the lenses of (i) resource complementarity with Variable Renewable Energy resources; (ii) correlations with load profiles from the four balancing authorities with territory in Oregon; and (iii) spatial value to regional and coastal grids as represented through a production cost model of the Western Interconnection. The capacity implications of the interactions between offshore wind and the historical east-to-west power flows of the region are discussed. The existing system is shown to accommodate more than two gigawatts of offshore wind interconnections with minimal curtailment. Through three gigawatts of interconnection, transmission flows indicate a reduction of coastal and statewide energy imports as well as minimal statewide energy exports.

Laser-driven growth of structurally defined transition metal oxide nanocrystals on carbon nitride photoelectrodes in milliseconds

Fabrication of hybrid photoelectrodes on a subsecond timescale with low energy consumption and possessing high photocurrent densities remains a centerpiece for successful implementation of photoelectrocatalytic synthesis of fuels and value-added chemicals. Here, we introduce a laser-driven technology to print sensitizers with desired morphologies and layer thickness onto different substrates, such as glass, carbon, or carbon nitride (CN). The specially designed process uses a thin polymer reactor impregnated with transition metal salts, confining the growth of transition metal oxide (TMO) nanostructures on the interface in milliseconds, while their morphology can be tuned by the laser. Multiple nano-p-n junctions at the interface increase the electron/hole lifetime by efficient charge trapping. A hybrid copper oxide/CN photoanode with optimal architecture reaches 10 times higher photocurrents than the pristine CN photoanode. This technology provides a modular approach to build a library of TMO-based composite films, enabling the creation of materials for diverse applications.

Effects of Climate Change on Capacity Expansion Decisions of an Electricity Generation Fleet in the Southeast U.S

The electric power sector in the United States faces many challenges related to climate change. On the demand side, climate change could shift demand patterns due to increased air temperatures. On the supply side, climate change could lead to deratings of thermal units due to changes in air temperature, water temperature, and water availability. Past studies have typically analyzed these risks separately. Here, we developed an integrated, multimodel framework to analyze how compounding risks of climate-change impacts on demand and supply affect long-term planning decisions in the power system. In the southeast U.S., we found that compounding climate-change impacts could result in a 35% increase in installed capacity by 2050 relative to the reference case. Participation of renewables, particularly solar, in the fleet increased, driven mostly by the expected increase in summertime peak demand. Such capacity requirements would increase investment costs by approximately 31 billion (USD 2015) over the next 30 years, compared to the reference case. These changes in investment decisions align with carbon emission mitigation strategies, highlighting how adaptation and mitigation strategies can converge.

Analysis and Classification of Hepatitis Infections Using Raman Spectroscopy and Multiscale Convolutional Neural Networks

Hepatitis infections represent a major health concern worldwide. Numerous computer-aided approaches have been devised for the early detection of hepatitis. In this study, we propose a method for the analysis and classification of cases of hepatitis-B virus ( HBV), hepatitis-C virus (HCV), and healthy subjects using Raman spectroscopy and a multiscale convolutional neural network (MSCNN). In particular, serum samples of HBV-infected patients (435 cases), HCV-infected patients (374 cases), and healthy persons (499 cases) are analyzed via Raman spectroscopy. The differences between Raman peaks in the measured serum spectra indicate specific biomolecular differences among the three classes. The dimensionality of the spectral data is reduced through principal component analysis. Subsequently, features are extracted, and then feature normalization is applied. Next, the extracted features are used to train different classifiers, namely MSCNN, a single-scale convolutional neural network, and other traditional classifiers. Among these classifiers, the MSCNN model achieved the best outcomes with a precision of 98.89%, sensitivity of 97.44%, specificity of 94.54%, and accuracy of 94.92%. Overall, the results demonstrate that Raman spectral analysis and MSCNN can be effectively utilized for rapid screening of hepatitis B and C cases.

Drought and climate change impacts on cooling water shortages and electricity prices in Great Britain

The risks of cooling water shortages to thermo-electric power plants are increasingly studied as an important climate risk to the energy sector. Whilst electricity transmission networks reduce the risks during disruptions, more costly plants must provide alternative supplies. Here, we investigate the electricity price impacts of cooling water shortages on Britain’s power supplies using a probabilistic spatial risk model of regional climate, hydrological droughts and cooling water shortages, coupled with an economic model of electricity supply, demand and prices. We find that on extreme days (p99), almost 50% (7GW_e) of freshwater thermal capacity is unavailable. Annualized cumulative costs on electricity prices range from £29–66m.yr^-1 GBP2018, whilst in 20% of cases from £66-95m.yr^-1. With climate change, the median annualized impact exceeds £100m.yr^-1. The single year impacts of a 1-in-25 year event exceed >£200m, indicating the additional investments justifiable to mitigate the 1^st-order economic risks of cooling water shortage during droughts.

The impacts of power plant water shortage during drought on electricity prices are understudied. Here the authors show that on extreme days, almost 50% (7 GWe) of the freshwater thermal capacity is unavailable in the Great Britain and annualized cumulative costs on electricity prices are in the range of £29-95m per year.

Rapidly self-healing, magnetically controllable, stretchable, smart, moldable nanoparticle composite gel

Attributed to a combination of healing properties, a magnetic gel shows rapid self-healing, magnetically controllable, stretchable, smart and moldable properties.

Climate-Water Adaptation for Future US Electricity Infrastructure

Future climate-water conditions are anticipated to increase electricity demand, reduce transmission capacity, and limit power production. Yet, typical electricity capacity expansion planning does not consider climate-water constraints. We project four alternative U.S. power system configurations using an iterative modeling and data exchange platform that integrates climate-driven hydrological, thermal power plant, and capacity expansion models. Through a comparison with traditional modeling approaches, we show that this novel approach provides greater confidence in electricity capacity projections by incorporating feasibility checks that adjust infrastructure development to reach grid reliability thresholds under climate-water constraints. Initial projections without climate-water impacts on electricity generation show future power systems become less vulnerable, independent of climate-water adaptation, as economic drivers increase renewable and natural gas-based capacity, while water-intensive coal and nuclear plants retire. However, power systems may face reliability challenges without climate-water adaptation, revealing the significance of incorporating climate-water impacts into power system planning. Climate-adjusted (Iterative approach) projections require a 5.3-12.0% increase in national-level capacity, relative to Initial projections, leading to an additional $125-143 billion (5.0-7.0%) in infrastructure costs. Variable renewable and natural gas technologies account for nearly all the additional capacity and, together with regional trade-offs in electricity generation, enhance grid performance to reach reliability thresholds. These adaptation transitions also lower water use and emissions, contributing to climate change mitigation, and highlight the trade-offs and impacts of both near and long-term electricity generation planning decisions.

Catalase-linked immunosorbent pressure assay for portable quantitative analysis

In this study, catalase-linked immunosorbent pressure assay with a gas-generation reaction was established for quantitative detection of disease biomarker C-reactive protein (CRP) by a portable pressuremeter. The pressure-based detection system recognizes, transduces, and amplifies the target signal to a convenient target-correlated pressure signal reading in a closed chamber. Biotin molecules were modified on the surface of catalase in order to incorporate catalase into the pressure immunoassay by the streptavidin-biotin interaction. To improve the assay performance, the modification ratios of biotin molecules to catalase, and the concentrations of capture and detection antibodies were further optimized. The catalase-linked immunosorbent pressure assay allows portable and quantitation analysis of CRP with a limit of detection of 1.8 nM, which can satisfy the clinical needs for determining the risk of cardiovascular disease. The catalase-linked immunosorbent pressure assay also shows superior specificity and good accuracy. Compared to the previously reported assay catalyzed by PtNP nanozyme, catalase is not easily deactivated during storage and operation. With the merits of enzymatic efficiency, biocompatibility, low non-specific adsorption and facile modification, catalase can be reasonably used for reproducible, stable, simple quantitative detection of disease markers using a portable pressure-based assay in resource-limited settings.