Characterizing weather-related biophysical and financial risks in algal biofuel production
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Energy & Fuels↗
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Investigating capacity credit sensitivity to reliability metrics and computational methodologies
Assigning capacity value to renewable energy sources (RES) is a challenge faced in planning their integration with the grid. The difficulties stem from the natural characteristics of variability and intermittency of wind and solar sources. The capacity credit (CC) analysis evaluates the system’s actual power output compared with a constant capacity generator, i.e., conventional generator and determines an effective capacity to use for planning and operation. Herein this paper presents different factors that could affect the CC of a system. Two methods are proposed to determine the CC, namely equivalent firm capacity (EFC) and effective load carrying capability (ELCC). Since these methods are based on satisfying reliability criteria, daily loss of load expectation (LOLE), hourly loss of load (LOLH), and expected energy not served (EENS) have been employed as indices. To obtain the CC value, both methods apply two techniques: traditional and optimization. Genetic algorithm (GA) is the optimization approach used in this paper. Then, this work compares the two techniques and shows the superior performance of the optimization approach. Two hybrid systems, stand-alone (SA) and grid-connected (GC) modes, are proposed and used as case studies. The hybrid systems consist of photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS). In this work, three different scenarios are used to compare capacity credit: system as a whole, only wind, and no batteries. Finally, sensitivity analysis is carried out to examine the impact of varying the wind speed, solar irradiation, and load. It is demonstrated that the choice of reliability index plays an important role in determining the capacity credit and it is shown that EENS is a more comprehensive and consistent index of reliability.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Effects of water recirculation on microalgae assemblage and corresponding sustainability of the photobioreactor cultivation system
An algae photobioreactor (APB) was used to determine the effect of water recirculation on the growth of algal assemblage. CO 2 in the flue gas from a power plant was the carbon source. Boiler water was used as the source water. The results showed that microalgae cultivation under recirculation conditions was stable over a period of four months. Biomass productivities during the 1st through 4th months of recirculation (0.26, 0.23, 0.20, and 0.18 g L –1 d –1 , respectively) were not significantly different than freshwater (0.22 g L –1 d –1 ). Furthermore, the relationship between eukaryotic and bacterial domains in the assemblage remained consistent throughout the four months of recirculation (80.7, 87.1, 83.1, and 82.1%, respectively, and 19.2, 12.8, 16.9, and 17.8%, respectively). This was not significantly different than the abundance of each domain in the control freshwater cultivation (83.7% eukaryotic and 16.2% bacterial). A 1 m 3 photobioreactor was then envisioned for a mass, energy, and exergy analysis to evaluate the water recirculation on sustainability of the culture system. The mass balance analysis concluded that 98% reduction in water usage, 25% reduction in nitrogen, and 12.5% reduction in phosphorus could be achieved during cultivation operating under recirculation for one year, while maintaining biomass productivity of 1.2 kg wet algal biomass and sequestration of 0.4 kg CO 2 per day. Furthermore, the exergy balance analysis concluded that without considering solar irradiation, the culture with water recirculation greatly enhanced the rational exergy efficiency, which represents a more sustainable cultivation system for CO 2 capture and utilization.
59 BASIC BIOLOGICAL SCIENCES↗
Formation and transformation of manganese(III) intermediates in the photochemical generation of manganese(IV) oxide minerals
As important natural oxidants and adsorbents, manganese (Mn) oxide minerals affect the speciation, bioavailability and fate of pollutants and nutrient elements. It was found that birnessite-type Mn(IV) oxide minerals can be formed in the presence of NO 3 – and solar irradiation. However, the photochemical formation and transformation processes from Mn 2+ to Mn(IV) oxide minerals remain unclear. In this work, the Mn(IV) oxide minerals were confirmed to be photochemically formed mainly due to the disproportionation of Mn(III) intermediates generated from the oxidation of Mn 2+ in the presence of NO 3 – under UV light irradiation. The oxidation rate of Mn 2+ to Mn(IV) oxide minerals decreased with increasing initial Mn 2+ concentration due to the lower disproportionation rate. The increase in NO 3 – concentration, pH and temperature promoted Mn 2+ photochemical oxidation. The photochemical formation rate of Mn(IV) oxide minerals increased with increasing ligand concentrations at low ligand concentrations. Ligands affected the formation of Mn(IV) oxide minerals by promoting the formation and reducing the reactivity of Mn(III) intermediates. Altogether, this work reveals the important role of Mn(III) intermediates in the formation of natural Mn oxide minerals.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Second-generation downscaled earth system model data using generative machine learning
The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Enhancing building resilience in cold climates: Integrating heat pump technologies with renewable energy
As electrification advances and Cold Climate Heat Pump technology progresses, ensuring grid stability becomes increasingly critical for effective heating in cold climates. However, natural disasters, especially during winter, pose significant threats to grid stability, impacting the reliability of air-source heat pumps. Despite these challenges, the integration of renewable energy sources and storage solutions in heating systems has not been extensively studied within the context of resilience. Here, this paper delves into the literature on renewable-powered heat pumps to assess their potential in enhancing building resilience in U.S. cold climate zones, which are particularly susceptible to extreme weather and grid disruptions. By leveraging renewable sources—solar, geothermal, and water—in conjunction with heat pump technology and supported by thermal or battery storage, this approach aims to provide a dependable solution for maintaining indoor heating during grid failures. Our analysis begins with a review of various renewable energy sources suitable for heat pumps, followed by an exploration of their application in cold climate regions across the U.S., and discussions on potential integration strategies with heat pump systems. This study highlights the advantages and suitability of solar irradiance and geothermal resources, emphasizing the importance of tailored, site-specific assessments to maximize energy efficiency and resilience. Additionally, it outlines the economic and environmental considerations necessary for implementing such systems and identifies potential challenges and areas for future research to facilitate the broader integration of renewable energy in heating solutions for enhanced resilience.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Post-extreme-event restoration using linear topological constraints and DER scheduling to enhance distribution system resilience
In this paper, a post-extreme-event restoration (PEER) algorithm is proposed to improve distribution system resilience. Linear topological constraints are proposed to ensure radial topology after N-k contingencies, possibly in multiple islands. The approach is made comprehensive by considering dispatchable distributed energy resources (DERs), non-dispatchable DERs, and demand responses, as well as on-load tap changers (OLTCs) and shunt capacitors. The goal is to minimize the accumulative expense caused by load reduction payment or penalty, as well as DER operation cost. As a result, the overall system will survive longer with higher resilience during an extreme event. To verify the effectiveness of the PEER algorithm, we proposed a resilience evaluation algorithm using Monte Carlo simulation (MCS) with reduced scenarios. This is based on a probabilistic model for generating random scenarios which consider the uncertainty of line faults and solar irradiance. Combined with the proposed PEER algorithm, this reduced-scenario MCS can evaluate the expected energy not served (EENS) which is an essential index for distribution system resilience. Case studies of the IEEE 33-bus and 123-bus test systems validate the proposed algorithm in reducing EENS.
24 POWER TRANSMISSION AND DISTRIBUTION↗
ZnO/CuO nanostructures anchored over Ni/Cu tubular films via pulse electrodeposition for photocatalytic and antibacterial applications
In this work, we report the fabrication of Ni and Cu tubular substrates and the synthesis of ZnO/CuO nanocomposite on them through the process of pulse electrodeposition. The systematic variation in CuO incorporation in the ZnO matrix and the processing technique were noticed to affect the structural, optical, photocatalytic, and anti-bacterial properties, which are well in accordance with the Field Emission-Scanning Electron Microscope, X-ray Diffraction, Fourier transform Infrared Spectroscopy and UV-Differential reflectance spectroscopy results. The remediation capabilities of the photocatalytic substrates were assessed through the degradation of methylene blue (MB) dye under solar irradiation. Optimized CuO incorporation within the ZnO nanorods resulted in the degradation of a 20 ppm of MB dye solution within 40 min and a higher concentration of 50 ppm within 95 min. The Ni and Cu electroformed tubes as substrates provided not only a reusable supporting frame but also a large surface-area for the growth of ZnO/CuO nanocomposite. The current study also dealt with the anti-bacterial efficacy of the above-mentioned substrates against E.coli. Hence, the Ni and Cu tubular thin film substrates with nanorods of ZnO/CuO composite were explored for the removal of organic as well as biological contaminants from waste water.
36 MATERIALS SCIENCE↗
Aerosol iron speciation and seasonal variation of iron oxidation state over the western Antarctic Peninsula
The iron (Fe) speciation and oxidation state have been considered critical factors affecting Fe solubility in the atmosphere and bioavailability in the surface ocean. In this study, elemental composition and Fe speciation in aerosol samples collected at the Palmer Station in the West Antarctic Peninsula were determined using synchrotron-based X-ray fluorescence (XRF) and X-ray Absorption Near-Edge Structure (XANES) spectroscopy. The elemental composition of coarse-mode (>1 mu m) Fe-containing particles suggests that the region's crustal emission is the primary source of aerosol Fe. The Fe minerals in these aerosol particles were predominantly hematite and biotite, but minor fractions of pyrite and ilmenite were observed as well. The Fe oxidation state showed an evident seasonal variation. Further, the Fe(II) content accounted for 71% of the total Fe in the austral summer, while this fraction dropped to 60% in the austral winter. Multivariate linear models involving meteorological parameters suggested that the wind speed, relative humidity, and solar irradiance were the factors that significantly controlled the percentage of Fe(II) in the austral summer. On the contrary, no relationship was found between these factors and the Fe(II) percentage in the austral winter, suggesting that atmospheric photoreduction and regional dust emission were limited. Moreover, the snow depth was significantly (p < 0.05) correlated with the aerosol Fe concentration, confirming the limiting effect of snow/ice cover on the regional dust emission. Given that the Antarctic Peninsula has experienced rapid warming during recent decades, the ice-free areas in the Antarctic Peninsula may act as potential dust sources.
54 ENVIRONMENTAL SCIENCES↗
Benchmark probabilistic solar forecasts: Characteristics and recommendations
We illustrate and compare commonly used benchmark, or reference, methods for probabilistic solar forecasting that researchers use to measure the performance of their proposed techniques. A thorough review of the literature indicates wide variation in the benchmarks implemented in probabilistic solar forecast studies. To promote consistent and sensible methodological comparisons, we implement and compare ten variants from six common benchmark classes at two temporal scales: intra-hourly forecasts and hourly resolution forecasts. Using open-source Surface Radiation Budget Network (SURFRAD) data from 2018, these benchmark methods are compared using proper probabilistic metrics and common diagnostic tools. Practical implementation issues, such as the impact of missing data and applicability for operational forecasting, are also discussed. Furthermore, we make recommendations for practitioners on the appropriate selection of benchmark methods to properly showcase state-of-the-art improvements in forecast reliability and sharpness. All code and open-source data are available on Github for reproducibility and for other researchers to apply the same benchmark methods to their own data.
14 SOLAR ENERGY↗
Establishing the Role of Operating Potential and Mass Transfer in Multicarbon Product Generation for Photoelectrochemical CO 2 Reduction Cells Using a Cu Catalyst
There is increasing interest in the possibility of photoelectrochemical (PEC) reduction of CO 2 to C 2+ products; however, the criteria for maximizing PEC solar-to-C 2+ (STC 2+ ) rates are not well understood. We report here a continuum-scale model of PEC CO 2 reduction (CO 2 R) on Cu in 0.1 M CsHCO 3 and use it to optimize the design and operating conditions for generating C 2+ products. Furthermore, we demonstrate that the potential-dependent product distribution of CO 2 R on Cu requires operating near the potential that maximizes C 2+ generation rates ($V$ id ), unlike PEC water splitting, which desires operation at the maximum photocurrent density. Because of this requirement, the criterion for a high STC 2+ rate includes high-photocurrent semiconductors with photovoltages near $V$ id and low series resistance. The STC 2+ rate in these systems is enhanced by optimal CO 2 transport and exhibits low sensitivity to dirunal solar irradiance variations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests
Abstract Dry deposition is the second largest tropospheric ozone (O 3 ) sink and occurs through stomatal and nonstomatal pathways. Current O 3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O 3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O 3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O 3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O 3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O 3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O 3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O 3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O 3 fluxes; and (c) the CTM big‐leaf treatment overestimates O 3 ‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O 3 predictions.
Vermeuel, Michael P. [Department of Soil, Water, a↗
Variations of organic functional chemistry in carbonaceous matter from the asteroid 162173 Ryugu
Abstract Primordial carbon delivered to the early earth by asteroids and meteorites provided a diverse source of extraterrestrial organics from pre-existing simple organic compounds, complex solar-irradiated macromolecules, and macromolecules from extended hydrothermal processing. Surface regolith collected by the Hayabusa2 spacecraft from the carbon-rich asteroid 162173 Ryugu present a unique opportunity to untangle the sources and processing history of carbonaceous matter. Here we show carbonaceous grains in Ryugu can be classified into three main populations defined by spectral shape: Highly aromatic (HA), Alkyl-Aromatic (AA), and IOM-like (IL). These carbon populations may be related to primordial chemistry, since C and N isotopic compositions vary between the three groups. Diffuse carbon is occasionally dominated by molecular carbonate preferentially associated with coarse-grained phyllosilicate minerals. Compared to related carbonaceous meteorites, the greater diversity of organic functional chemistry in Ryugu indicate the pristine condition of these asteroid samples.
Science & Technology - Other Topics↗
Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves
We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001–2020), future mid-term (2041–2060), and future long-term (2081–2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 “Resilient Cooling for Buildings”, are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.
54 ENVIRONMENTAL SCIENCES↗
Production of hydrogen peroxide in an intra-meander hyporheic zone at East River, Colorado.
The traditionally held assumption that photo-dependent processes are the predominant source of H 2 O 2 in natural waters has been recently questioned by an increasing body of evidence showing the ubiquitiousness of H 2 O 2 in dark water bodies and in groundwater. In this study, we conducted field measurement of H 2 O 2 in an intra-meander hyporheic zone and in surface water at East River, CO. On-site detection using a sensitive chemiluminescence method suggests H 2 O 2 concentrations in groundwater ranging from 6 nM (at the most reduced region) to ~ 80 nM (in a locally oxygen-rich area) along the intra-meander transect with a maxima of 186 nM detected in the surface water in an early afternoon, lagging the maximum solar irradiance by ~1.5 h. Our results suggest that the dark profile of H 2 O 2 in the hyporheic zone is closely correlated to local redox gradients, indicating that interactions between various redox sensitive elements could play an essential role. Due to its transient nature, the widespread presence of H 2 O 2 in the hyporheic zone indicates the existence of a sustained balance between H 2 O 2 production and consumption, which potentially involves a relatively rapid succession of various biogeochemically important processes (such as organic matter turnover, metal cycling and contaminant mobilization). More importantly, this study confirmed the occurrence of reactive oxygen species at a subsurface redox transition zone and further support our understanding of redox boundaries on reactive oxygen species generation and as key locations of biogeochemical activity.
63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
Air separation via two-step solar thermochemical cycles based on SrFeO 3-δ and (Ba,La) 0.15 Sr 0.85 FeO 3-δ perovskite reduction/oxidation reactions to produce N 2 : rate limiting mechanism(s) determination
Two-step solar thermochemical cycles based on reversible reactions of SrFeO 3–δ and (Ba,La) 0.15 Sr 0.85 FeO 3–δ perovskites were considered for air separation. The cycle steps encompass (1) the thermal reduction of SrFeO 3–δ or (Ba,La) 0.15 Sr 0.85 FeO 3–δ perovskites driven by concentrated solar irradiation and (2) oxidation in air to remove O 2 and produce N 2 . Rate limiting mechanisms were examined for both reactions using a combination of isothermal and non-isothermal thermogravimetry for temperature-swings between 673 and 1373 K, heating rates of 10, 20, and 50 K min –1 , and O 2 pressure-swings between 20% O 2 /Ar and 100% Ar at atmospheric pressure. Evolved O 2 and associated lag due to transport behavior were measured with gas chromatography and used with measured sample temperatures to predict equilibrium compositions from a compound energy formalism thermodynamic model. Measured and predicted chemical equilibrium changes in deviation from stoichiometry were compared. Rapid chemical kinetics were observed as the samples equilibrated rapidly for all conditions, indicative that heat and mass transfer were the rate limiting mechanisms. Furthermore, the effects of bulk diffusion (or gas diffusion through the bed or pellet) were examined using pelletized and loose powdered samples and determined to have no discernable impact.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Guest Editorial: Advanced Data-Analytics for Power System Operation, Control, and Enhanced Situational Awareness
Along with the smart grid development, modern power systems are entering a ‘data-intensive’ era. A vast volume of data from power grids is being collected through advanced sensing and communication technologies, such as smart metering data, phasor measurement data, as well as meteorological data (e.g., wind speed and solar irradiance) related to renewable power generation. Such data contains comprehensive information about the power system covering equipment's health status, power grid's static and dynamic characteristics, renewable power generation, customers’ electricity usage pattern, etc. Therefore, advanced data-analytics techniques are needed to convert such data to knowledge for practical applications. In line with the trend of widespread data-driven applications in power systems, this Special Issue aims to present state-of-the-art research works on advanced data-analytics for power system's operation, control, and situational awareness. There are in total twenty-six papers accepted for publication in this Special Issue through careful peer reviews and revisions. Under the overarching theme of data-driven applications in power systems, the selected papers are broadly categorised into five topics. The summary of every topic is given below. You are, however, strongly encouraged to read the full paper if interested.
Xu, Yan↗
Probabilistic Prediction of Geomagnetic Storms and the K p index
Geomagnetic activity is often described using summary indices to summarize the likelihood of space weather impacts, as well as when parameterizing space weather models. The geomagnetic index K p in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministic K p predictions using a variety of methods – including empirically-derived functions, physics-based models, and neural networks – but do not provide uncertainty estimates associated with the forecast. This paper provides a sample methodology to generate a 3-hour-ahead K p prediction with uncertainty bounds and from this provide a probabilistic geomagnetic storm forecast. Specifically, we have used a two-layered architecture to separately predict storm (K p ≥ 5 – ) and non-storm cases. As solar wind-driven models are limited in their ability to predict the onset of transient-driven activity we also introduce a model variant using solar X-ray flux to assess whether simple models including proxies for solar activity can improve the predictions of geomagnetic storm activity with lead times longer than the L1-to-Earth propagation time. By comparing the performance of these models we show that including operationally-available information about solar irradiance enhances the ability of predictive models to capture the onset of geomagnetic storms and that this can be achieved while also enabling probabilistic forecasts.
79 ASTRONOMY AND ASTROPHYSICS↗