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Advancing hydrogen production: A comprehensive review of wastewater reforming techniques, feedstocks, and opportunities

Wastewater is produced across nearly all human activities and requires treatment to safeguard human health and the natural environment. Treatment of wastewater often requires a large amount of thermal energy, resulting in wasted heat after the treatment process. Because hydrocarbon reforming needs both water and heat, the integration of wastewater treatment with hydrocarbon reforming, a process that produces synthesis gas rich in hydrogen, offers an excellent opportunity to utilize this waste heat and the impurities in wastewater to produce valuable hydrogen gas, to minimize waste from industrial processes, and to integrate water treatment with the hydrogen economy. Yet, no comprehensive literature review has been conducted to examine the integration of reforming and wastewater. To address this lack, we summarize the variety of catalytic reforming techniques available in the open literature and review the current literature on wastewater reforming with these techniques. Subsequently, we conduct a review of common types of wastewater contaminants and their possible effects on reforming catalyst performance and life. Lastly, three underexamined wastewater sources are identified, namely, oilfield wastewater, geothermal water, and mining and mineral processing wastewater, and their potential for future study as a reforming feedstock is examined.

08 HYDROGEN↗

A comprehensive analysis of the crop effect on the urban-rural differences in land surface phenology

The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultural managements (e.g., timing of sowing and harvesting), leading to biased conclusions derived from the urban-rural LSP differences. To demonstrate this problem, we investigated the crop influence on the phenological response to a warmer environment resulting from the UHI effect. We partitioned cities in the United States into cultivated and non-cultivated categories according to the proportion of crops in rural areas. We then built continuous buffer zones starting from the urban boundary to explore the urban-rural LSP differences considering the UHI effect on them. In this work, the results suggest crop inclusion is likely to lead to >14 days of urban-rural differences at both the start of the season (SOS) and the end of the season (EOS) between cultivated and non-cultivated cities. The temperature sensitivity (ST) of SOS is overestimated by approximately 2.7 days/°C, whereas the EOS is underestimated by 3.6 days/°C. Removing crop-dominated pixels (i.e., above 50 %) can minimize the influence of crop planting/harvesting on LSP and derive reliable results. We, therefore, suggest explicit consideration of crop impacts in future studies of phenological differences between urban and rural areas and the UHI effect on LSP in urban domains, as presented by this comprehensive study.

54 ENVIRONMENTAL SCIENCES↗

Acoustics at the nanoscale (nanoacoustics): A comprehensive literature review. Part I: Materials, devices and selected applications

We report in the past decade, acoustics at the nanoscale (i.e., nanoacoustics) has evolved rapidly with continuous and substantial expansion of capabilities and refinement of techniques. Motivated by research innovations in the last decade, for the first time, recent advancements of acoustics-associated nanomaterials/nanostructures and nanodevices for different applications are outlined in this comprehensive review, which is written in two parts. As part I of this two-part review, firstly, active and passive nanomaterials and nanostructures for acoustics are presented. Following that, representative applications of nanoacoustics including material property characterization, nanomaterial/nanostructure manipulation, and sensing, are discussed in detail. Finally, a summary is presented with point of views on the current challenges and potential solutions in this burgeoning field.

42 ENGINEERING↗

Acoustics at the nanoscale (nanoacoustics): A comprehensive literature review. Part II: Nanoacoustics for biomedical imaging and therapy

We report in the past decade, acoustics at the nanoscale (i.e., nanoacoustics) has evolved rapidly with continuous and substantial expansion of capabilities and refinement of techniques. Motivated by research innovations in the last decade, for the first time, recent advancements of acoustics-associated nanomaterials/nanostructures and nanodevices for different applications are outlined in this comprehensive review, which is written in two parts. As part II of this two-part review, this paper concentrates on nanoacoustics in biomedical imaging and therapy applications, including molecular ultrasound imaging, photoacoustic imaging, ultrasound-mediated drug delivery and therapy, and photoacoustic drug delivery and therapy. Firstly, the recent developments of nanosized ultrasound and photoacoustic contrast agents as well as their various imaging applications are examined. Secondly, different types of nanomaterials/nanostructures as nanocarriers for ultrasound and photoacoustic therapies are discussed. Finally, a discussion of challenges and future research directions are provided for nanoacoustics in medical imaging and therapy.

47 OTHER INSTRUMENTATION↗

Comprehensive energy balance analysis of photon-enhanced thermionic power generation considering concentrated solar absorption distribution

The present article reports a comprehensive energy balance analysis of a photon-enhanced thermionic emission (PETE) device when it is used for concentrated solar power (CSP) generation. To this end, we consider a realistic PETE device composed of a boron-doped silicon emitter on glass and a phosphorus-doped diamond collector on tungsten separated by the interelectrode vacuum gap. Here, depth-dependent spectral solar absorption and its photovoltaic and photothermal energy conversion processes are rigorously calculated to predict the PETE power output and energy conversion efficiency. Our calculation predicts that when optimized, the power output of the considered PETE device can reach 1.6 W/cm 2 with the energy conversion efficiency of ~ 18% for 100× solar concentration, which is substantially lower than those predicted in previous works under ideal conditions. In addition, the photon-enhancement ratio is lower than 10 and decreases with the increasing solar concentration due to the photothermal heating of the emitter assembly, suggesting that PETE should be more suitable for lowto- medium CSP below ~ 100× concentration. These observations signify the importance of a rigorous energy balance analysis based on spectral and spatial solar absorption distribution for the accurate prediction of PETE power generation.

14 SOLAR ENERGY↗

Comprehensive analysis of differentially expressed mRNA and circRNA in Ankylosing spondylitis patients’ platelets

Highlights: • 4996 mRNAs and 2942 circRNAs were identified differentially expressed in platelets of AS patients. • Several platelet-derived immune mediators were upregulated to regulate the interaction between platelets and immune cells. • Two downregulated circRNA were identified, and the corresponding circRNA-miRNA-mRNA regulatory network was constructed. • mRNAs and circRNAs found herein could be used as diagnostic biomarkers or new therapeutic targets. Ankylosing spondylitis (AS) is a chronic inflammatory disease significantly decreasing the quality of life. Platelets play an important and active role in the development of AS. Accumulating evidence demonstrated platelets contain diverse RNA repository inherited from megakaryocytes or microvesicles. Platelet RNAs are dynamically affected by pathological conditions and could be used as diagnostic or prognostic biomarkers. However, the role of the platelet RNAs in AS is elusive. In this study, we compared mRNA and circRNA profiles in platelets between AS patients and healthy controls using RNA sequencing and bioinformatic analysis, and found 4996 mRNAs and 2942 circRNAs were differently expressed. The significantly over-expressed mRNAs in AS patients are involved in platelet activity, gap junction, focal adhesion, rap1 and toll and Imd signaling pathway. The previous identified platelet-derived immune mediators such as P2Y1, P2Y12, PF4, GPIbα, CD40L, ICAM2, CCL5 (RANTES), TGF-β (TGF-β1 and TGF-β2) and PDGF (PDGFB and PDGFA) are also included in these over expressed mRNAs, implying these factors may trigger inflammatory cascades and promote the development of AS. Additionally, we found two down-regulated circRNA (circPTPN22 and circFCHSD2) from the intersection analyses of platelets and spinal ligament tissues of AS patients. The circRNA-miRNA-mRNA regulatory network of these two circRNAs was constructed, and the target mRNAs were enriched in Th17 cell differentiation, inflammatory bowel disease, cell adhesion molecules, cytokine-cytokine receptor interaction, Jak-STAT and Wnt signaling pathway, all these pathways participate in the bone remodeling and pro/anti-inflammatory immune regulation in AS. Then, qRT-PCR was performed to validate the expression of selected key mRNAs and circRNAs and the results demonstrated that the expression levels of P2Y12, GPIbα, circPTPN22 and circFCHSD2 were consistent with the sequencing analysis. In addition, the high expression of five predicted miRNAs interacting with circPTPN22 and circFCHSD2 were also detected in AS by qRT-PCR. Taken together, our study presents a comprehensive overview of mRNAs and circRNAs in platelets in AS patients and offers new insight into the mechanisms of platelet involving in the pathogenesis of AS. The mRNAs and circRNAs identified in this study may serve as candidates for diagnosis and targeted treatment of AS.

60 APPLIED LIFE SCIENCES↗

N -Arylimide Molecular Balances: A Comprehensive Platform for Studying Aromatic Interactions in Solution

Noncovalent interactions of aromatic surfaces play a key role in many biological processes and in determining the properties and utility of synthetic materials, sensors, and catalysts. However, the study of aromatic interactions has been challenging because these interactions are usually very weak and their trends are modulated by many factors such as structural, electronic, steric, and solvent effects. Recently, N-arylimide molecular balances have emerged as highly versatile and effective platforms for studying aromatic interactions in solution. These molecular balances can accurately measure weak noncovalent interactions in solution via their influence on the folded–unfolded conformational equilibrium. The structure (i.e., size, shape, π-conjugation, and substitution) and nature (i.e., element, charge, and polarity) of the π-surfaces and interacting groups can be readily varied, enabling the study of a wide range of aromatic interactions. These include aromatic stacking, heterocyclic aromatic stacking, and alkyl–π, chalcogen–π, silver–π, halogen–π, substituent–π, and solvent–π interactions. The ability to measure a diverse array of aromatic interactions within a single model system provides a unique perspective and insights as the interaction energies, stability trends, and solvent effects for different types of interactions can be directly compared. Some broad conclusions that have emerged from this comprehensive analysis include: (1) The strongest aromatic interactions involve groups with positive charges such as pyridinium and metal ions which interact with the electrostatically negative π-face of the aromatic surface via cation–π or metal–π interactions. Attractive electrostatic interactions can also form between aromatic surfaces and groups with partial positive charges. (2) Electrostatic interactions involving aromatic surfaces can be switched from repulsive to attractive using electron-withdrawing substituents or heterocycles. These electrostatic trends appear to span many types of aromatic interactions involving a polar group interacting with a π-surface such as halogen–π, chalcogen–π, and carbonyl–π. (3) Nonpolar groups form weak but measurable stabilizing interactions with aromatic surfaces in organic solvents due to favorable dispersion and/or solvophobic effects. Furthermore, a good predictor of the interaction strength is provided by the change in solvent-accessible surface area. (4) Solvent effects modulate the aromatic interactions in the forms of solvophobic effects and competitive solvation, which can be modeled using solvent cohesion density and specific solvent–solute interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bench-Scale Apparatus for Rapid, Simultaneous, Comprehensive Vapor–Liquid Equilibrium and Kinetic Property Measurements to Advance CO 2 Capture Solvent Technology

We present here, the design, fabrication, and testing of a new "pressure, volume, temperature (PVT)" apparatus that enables rapid standardized testing for viscosity, vapor–liquid equilibria, and kinetics for water-lean carbon capture solvents. This unit is the first of its kind where equilibrium data are collected during operation as a PTx (pressure–temperature–composition) cell while kinetic data are collected simultaneously with an internal mini wetted-wall contactor (WWC) using controlled adjustments of CO 2 injections to allow for measurements of gas flux (in and out of the liquid). Additionally, in situ measurements of viscosity data are also continuously collected while a solvent is in circulation during gas absorption. This cell empowers comprehensive testing of critical CO 2 capture solvent properties in a single measurement, ensuring all data are collected at the same temperature, pressure, and CO 2 loading. This apparatus also expedites screening of materials since less than 50 mL of sample is needed as compared to 2–3 L needed to get similar data from a conventional WWC. In conclusion, we describe here the methodology of data collected on this new PVT cell, nicknamed “Gary” in honor of Professor Gary Rochelle, for multiple water-lean amine solvents, which we compare to data collected from conventional instrumentation for amine testing.

Zheng, Richard [STARS Technology Corporation, Rich↗

Complex and Unusual Excited-State Relaxation Dynamics of 9,9′-Bifluorenylidene Revealed by Comprehensive Time-Resolved Spectroscopy and MRSF-TDDFT Calculations

Design of novel photochemical molecular motors often requires molecular building blocks that exhibit rather unusual photoactivity, for which conventional analyses of spectroscopic data can lead to conflicting interpretations. We here systematically investigated the excited-state relaxation dynamics of one such molecule, 9,9′-bifluorenylidene (BF), through comprehensive and complementary integration of ultrafast transient absorption (TA) and femtosecond stimulated Raman (FSRS) spectroscopies and first-principles mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT). TA and FSRS identified two sequentially formed transients following photoexcitation. The decay kinetics of the two intermediates differ in response to excitation wavelengths and the viscosity/polarity of solvents. MRSF-TDDFT calculations reveal a direct, barrierless internal-conversion pathway from the bright Franck−Condon state to a dark S1 minimum, where the excited-state population is transiently trapped, accounting for the first transient species observed in spectroscopic experiments. Further tracking down along the PES with MRSF-TDDFT mapped out two nonradiative relaxation pathways via conical intersections that connect the dark S 1 state to three configurations in the ground-state manifolds, within which a ring structure with a C8−C8′ bond and the vibrationally excited ground-state BF were identified from spectroscopic and kinetic data. The complexity of relaxation kinetics was attributed to the flexible torsional and twisting motions about the C9−C9′ bridge bond enabled by the diradical character of the S 1 state. These findings clarify unusual photoactive relaxation dynamics stemming from a novel correlation between structural flexibility and shifting electronic characteristics, and they demonstrate the importance of integrating spectroscopic and advanced electronic structure calculation studies for judicious clarification of complex, competing relaxation pathways of excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package

Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher-order products including an approximation of volume-weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self-describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase-changes at high temporal resolution. Bulk precipitation characteristics from a multi-site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high-quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.

54 ENVIRONMENTAL SCIENCES↗

Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models

Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.

54 ENVIRONMENTAL SCIENCES↗

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the multiscale modeling framework (MMF), which embeds a kilometer-resolution cloud-resolving model (CRM) within each atmospheric column of a host climate model to replace traditional convection and cloud parameterizations. Machine learning offers a unique opportunity to make MMF more accessible by emulating the embedded CRM and reducing its substantial computational cost. Although many studies have demonstrated proof-of-concept success of achieving stable hybrid simulations, it remains a challenge to achieve near operational-level success with real geography and comprehensive variable emulation that includes, for example, explicit cloud condensate coupling. In this study, we present a stable hybrid model capable of integrating for at least 5 years with near operational-level complexity, including coarse-grid geography, seasonality, explicit cloud condensate and wind predictions, and land coupling. Our model demonstrates skillful online performance, achieving a 5-year zonal mean tropospheric temperature bias within 2 K, water vapor bias within 1 g/kg, and a precipitation root mean square error of 0.96 mm/day. Key factors contributing to our online performance include an expressive U-Net architecture and physical thermodynamic constraints for microphysics. With microphysical constraints mitigating unrealistic cloud formation, our work is the first to demonstrate realistic multi-year cloud condensate climatology under the MMF framework. Despite these advances, online diagnostics reveal persistent biases in certain regions, highlighting the need for innovative strategies to further optimize online performance.

Hu, Zeyuan [NVIDIA Corporation, Santa Clara, CA (U↗

An all optical approach for comprehensive in-operando analysis of radiative and nonradiative recombination processes in GaAs double heterostructures

We demonstrate an all optical approach that can surprisingly offer the possibility of yielding much more information than one would expect, pertinent to the carrier recombination dynamics via both radiative and nonradiative processes when only one dominant deep defect level is present in a semiconductor material. By applying a band-defect state coupling model that explicitly treats the inter-band radiative recombination and Shockley–Read–Hall (SRH) recombination via the deep defect states on an equal footing for any defect center occupation fraction, and analyzing photoluminescence (PL) as a function of excitation density over a wide range of the excitation density (e.g., 5–6 orders in magnitude), in conjunction with Raman measurements of the LO-phonon plasmon (LOPP) coupled mode, nearly all of the key parameters relevant to the recombination processes can be obtained. They include internal quantum efficiency (IQE), minority and majority carrier density, inter-band radiative recombination rate (W r ), minority carrier nonradiative recombination rate (W nr ), defect center occupation fraction (f), defect center density (N t ), and minority and majority carrier capture cross-sections (σ t and σ tM ). While some of this information is thought to be obtainable optically, such as IQE and the W r /W nr ratio, most of the other parameters are generally considered to be attainable only through electrical techniques, such as current-voltage (I-V) characteristics and deep level transient spectroscopy (DLTS). Following a procedure developed herein, this approach has been successfully applied to three GaAs double-heterostructures that exhibit two distinctly different nonradiative recombination characteristics. The method greatly enhances the usefulness of the simple PL technique to an unprecedented level, facilitating comprehensive material and device characterization without the need for any device processing.

14 SOLAR ENERGY↗

Comprehensive deletion landscape of CRISPR-Cas9 identifies minimal RNA-guided DNA-binding modules

Proteins evolve through the modular rearrangement of elements known as domains. Extant, multidomain proteins are hypothesized to be the result of domain accretion, but there has been limited experimental validation of this idea. Here, we introduce a technique for genetic minimization by iterative size-exclusion and recombination (MISER) for comprehensively making all possible deletions of a protein. Using MISER, we generate a deletion landscape for the CRISPR protein Cas9. We find that the catalytically-dead Streptococcus pyogenes Cas9 can tolerate large single deletions in the REC2, REC3, HNH, and RuvC domains, while still functioning in vitro and in vivo, and that these deletions can be stacked together to engineer minimal, DNA-binding effector proteins. In total, our results demonstrate that extant proteins retain significant modularity from the accretion process and, as genetic size is a major limitation for viral delivery systems, establish a general technique to improve genome editing and gene therapy-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part II: comprehensive ternary design and validation

Abstract Here the discovery of refractory multi-principal element alloys (MPEAs) with high-temperature strength and stability is pursued within a constrained and application-relevant design space. A comprehensive approach is developed and applied to explore all 165 ternary systems in the Al-Ce-Fe-Hf-Mo-Nb-Ta-Ti-V-W-Zr family. A subset of ternary systems that contain large areas in composition–temperature space with high strength and robust BCC phase stability is found. Twelve sets of high-performing alloys are identified, each set optimized for one combination of phase constraint, optimization target, and temperature range. Preliminary mechanical tests support the viability of the method. This work highlights the importance of considering phase stability, exploring non-equiatomic regions of composition space, and applying application-relevant constraints. Parts I and II provide three down-selection techniques for identifying high-performing BCC refractory MPEAs, design guidelines, and many candidates predicted to have BCC phase stability and strengths 2–3 times higher than any reported to date.

36 MATERIALS SCIENCE↗

QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures—comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-/trans- and conformational isomers)—as well as 100 non-equilibrium structural variations thereof to reach a total of ≈4.2 million molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly-converged dataset of quantum-mechanically computed physicochemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing in silico design of molecules with targeted properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A comprehensive spectral assay library to quantify the Halobacterium salinarum NRC-1 proteome by DIA/SWATH-MS

Data-Independent Acquisition (DIA) is a mass spectrometry-based method to reliably identify and reproducibly quantify large fractions of a target proteome. The peptide-centric data analysis strategy employed in DIA requires a priori generated spectral assay libraries. Such assay libraries allow to extract quantitative data in a targeted approach and have been generated for human, mouse, zebrafish, E. coli and few other organisms. However, a spectral assay library for the extreme halophilic archaeon Halobacterium salinarum NRC-1, a model organism that contributed to several notable discoveries, is not publicly available yet. Here, we report a comprehensive spectral assay library to measure 2,563 of 2,646 annotated H. salinarum NRC-1 proteins. We demonstrate the utility of this library by measuring global protein abundances over time under standard growth conditions. The H. salinarum NRC-1 library includes 21,074 distinct peptides representing 97% of the predicted proteome and provides a new, valuable resource to confidently measure and quantify any protein of this archaeon. Data and spectral assay libraries are available via ProteomeXchange (PXD042770, PXD042774) and SWATHAtlas (SAL00312-SAL00319).

59 BASIC BIOLOGICAL SCIENCES↗

CHUWD-H v1.0: a comprehensive historical hourly weather database for U.S. urban energy system modeling

Reliable and continuous meteorological data are crucial for modeling the responses of energy systems and their components to weather and climate conditions, particularly in densely populated urban areas. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies, posing great challenges for detailed urban energy system modeling and cross-city comparison under realistic weather conditions. Here we introduce the Historical Comprehensive Hourly Urban Weather Database (CHUWD-H) v1.0, a 23-year (1998-2020) gap-free and quality-controlled hourly weather dataset covering 550 weather station locations across all urban areas in the contiguous United States. CHUWD-H v1.0 synthesizes hourly weather observations from stations with outputs from a physics-based solar radiation model and a reanalysis dataset through a multi-step gap filling approach. A 10-fold Monte Carlo cross-validation suggests that the accuracy of this gap filling approach surpasses that of conventional gap filling methods. Designed primarily for urban energy system modeling, CHUWD-H v1.0 should also support historical urban meteorological and climate studies, including the validation and evaluation of urban climate modeling.

54 ENVIRONMENTAL SCIENCES↗