Liquid Water Research Articles

X-ray absorption spectroscopy (XAS) provides critical insights into the molecular and electronic structures of complex condensed-phase systems. For example, the XAS spectrum of liquid water depends on the complex three-dimensional arrangements of water molecules and their effects on the core-to-valence electronic transitions. Consequently, a wealth of molecular and electronic information is encoded in the complex spectral patterns. To decode these structure-electronic property relationships, we simulated the XAS spectra of bulk water by combining advanced molecular dynamics (MD) simulations coupled with multiconfigurational wave function methods. Using three advanced MD approaches─ab initio MD (AIMD), RexPoN, and MB-pol─we sampled the local solvation environments and hydrogen-bond (HB) networks, which were then used to predict the XAS spectra. Based on the theory-experiment comparisons of pair distribution functions and XAS spectra, we identified the MD method that most reliably predicts the local water structure. We further revealed that the charge-transfer (CT) character observed across the entire spectral range is strongly correlated to the hydrogen-bond (HB) network. Specifically, the extent of CT and the associated excitation energy are significantly influenced by the HB structure. These findings highlight the limitations of a purely local excitation model for interpreting bulk water XAS spectra. Instead, accurate sampling of HB structures and high-level wave function theory with dynamic correlation are essential for reliable spectral interpretation. This approach provides new insights into the relationship between the electronic structure and the molecular organization of water.

Soil moisture simulations in semi-arid inland river basins remain highly uncertain due to complex land–atmosphere interactions and multiple parameterization schemes in land surface models. This study evaluated the ability of the Noah-Multiparameterization Land Surface Model (Noah-MP) to simulate soil moisture at meteorological sites representing the upstream, midstream and downstream regions of a semi-arid inland river basin with contrasting climates. A large physics-ensemble experiment (17,280 simulations per site) combining different parameterization schemes for 10 main physical processes was conducted. Natural selection, Tukey’s test and uncertainty contribution analysis were applied to identify sensitive processes and quantify their contributions to simulation uncertainty. Results indicate that Noah-MP captures soil moisture variability across the basin but with notable biases. Three physical processes—frozen soil permeability, supercooled liquid water in frozen soil and ground resistance to sublimation—were sensitive at all sites, whereas radiation transfer and surface albedo were consistently insensitive. At the upstream and midstream sites, supercooled liquid water contributed about half of the ensemble uncertainty, and at the downstream site ground resistance to sublimation contributed roughly 51%. These findings reveal which physical processes most strongly affect Noah-MP soil moisture simulations in semi-arid basins and provide guidance for improving parameterization schemes to reduce uncertainty.

The multimode Brownian model with nonlinear system-bath coupling offers a flexible framework for studying both intra- and intermolecular vibrational modes in condensed-phase molecular systems. This approach allows us to calculate linear and nonlinear spectra of molecular vibrations and to examine thermal effects-such as anharmonicity, energy relaxation, and dephasing-as reflected in the spectral peak profiles. In this study, we present computer software based on classical hierarchical Fokker-Planck equations applied to three vibrational modes of a molecular liquid. The primary objective of developing this code was to simulate the two-dimensional correlation spectrum of the intramolecular modes of liquid water [Hoshino and Tanimura, J. Chem. Phys. 162, 044105 (2025)]. The code has been further refined to optimize grid selection and numerical integration routines for graphics processing units. As a demonstration, we apply this setup to simulate three interacting modes representing intermolecular vibrations in water and calculate the resulting two-dimensional terahertz-Raman signals. The code and example routines are available in the supplementary material.

Insights into environmentally friendly solvent pretreatment of lignocellulosic biomass: Strategies, mechanisms, and future perspectives.

Aerosol light scattering enhancement and liquid water content in a tropical coastal atmosphere

Abstract Hailstorms can cause a lot of damage to agriculture and property. Therefore, efforts exist to mitigate hail damage by means of seeding a developing hailstorm with ice nucleating particles. Motivated by the Swiss hail mitigation campaign, we examined the impact of silver iodide (AgI) perturbations on a convective storm observed over northern Switzerland on 6 July 2019. We evaluated the effectiveness of an early seeding strategy and investigated the concept of beneficial competition, where an increased number of ice nucleating particles (INPs) leads to the formation of smaller, less damaging hailstones. We used the Consortium for Small-Scale Modeling (COSMO) Regional Weather and Climate Model to simulate this case. AgI particles were added as a prognostic variable to the hailstorm during its cumulus stage and were released in the updraft region near the cloud base with concentrations ranging from 0.2 to 2000 cm−3 in ensemble simulations. While seeding delayed the onset of precipitation, increased the graupel concentration, and reduced supercooled liquid water, especially in the upper part of the convective cloud, no systematic change in the overall hail size has been found. We did, however, observe fewer grid points with mean hail diameters larger than 30 mm in all seeding concentrations across all altitudes, corresponding to a decrease of the largest hail sizes (>30 mm) across all atmospheric levels by up to 11%.

Impacts of aerosol acidity and liquid water content on secondary inorganic aerosol pollution in East Asian megacities: Beijing and Seoul

Abstract In the Great Lakes region (GLR), lake-effect snow (LeS) events are a common occurrence, in which narrow, intense bands of convection cause snowfall downwind of the lakes. The shallow convection associated with LeS is dynamically different from deeper, synoptically driven snow, and the particle size distributions (PSDs) of the precipitation have different shapes, as well. This work considers whether or not the Thompson–Eidhammer microphysics scheme, which includes single-moment prediction of snow, is accurate in estimating the PSDs of LeS convection. The High-Resolution Rapid Refresh (HRRR) configuration of the Weather Research and Forecasting (WRF) Model is used to simulate three different LeS events in the GLR using two different microphysics schemes: the Thompson–Eidhammer “aerosol-aware” scheme and the Morrison double-moment scheme. Model-estimated PSDs are calculated and compared to observed PSDs at three locations in the region: Marquette, Michigan; Gaylord, Michigan; and Buffalo, New York. Model-predicted liquid water equivalent snowfall and snow density are also compared to observed products. It is found that parameterization performance varies depending on location, with Thompson struggling to create the correct PSD shape for Marquette. Both microphysics schemes do not perform well in predicting particles greater than 6 mm in diameter except in Buffalo, where both simulated and observed PSDs contain snow particles greater than 10 mm in diameter. Significance Statement In the Great Lakes region, lake-effect snow events can cause heavy snowfall with large accumulations over a narrow region downwind of the lakes. Current numerical weather prediction models struggle to exactly capture the large spatial variability of lake-effect snow and rely on parameterizations to model the characteristics of the snowfall. This study is the first to use a database of microphysical observations to evaluate how well a current operational forecast model is able to replicate the snow particle sizes in lake-effect snow events around the Great Lakes.

Influence of boundary layer-cloud coupling on cloud microphysics based on aircraft observations in the North China plain.

We present a nonparametric Bayesian framework to infer radial distribution functions from experimental scattering measurements with uncertainty quantification using nonstationary Gaussian processes. The Gaussian process prior mean and kernel functions are designed to mitigate well-known numerical challenges with the Fourier transform, including discrete measurement binning and detector windowing, while encoding fundamental yet minimal physical knowledge of the liquid structure. We demonstrate uncertainty propagation of the Gaussian process posterior to unmeasured quantities of interest. Experimental radial distribution functions of liquid argon and water with uncertainty quantification are provided as both a proof of principle for the method and a benchmark for molecular models.

Water scarcity is an escalating global challenge driven by population growth and resource depletion. Conventional fresh water production methods typically require access to liquid water sources, limiting their applicability in remote or arid regions. Water-from-air technologies offer a potential solution but are often hindered by high energy demands and/or climatological conditions. This study introduces clathrate-based desalination of deliquescent salt solutions as a novel approach for atmospheric water harvesting, with potassium acetate selected as the model salt. Potassium acetate deliquesces at a relative humidity as low as 23.3%, producing a concentrated saline solution (17.8 wt% at 90% RH). By exploiting the clathrate creeping phenomenon, where hydrates grow along surfaces, enabling facilitated phase separation, 84% purification of this brine was achieved. Advanced architectures, further enhancing the crucial clathrate creeping potentially lead to further improvements of the obtained results. This process demonstrates the potential of an energy-efficient alternative to existing water-from-air technologies.

ABSTRACT Fuel cell flow channel structure has obvious influence on reaction gas flow, distribution, and diffusion as well as liquid water discharge. For better understanding of how liquid water behavior changes in flow fields and for enhancing cell water management, two-phase flow in various organized channels must be visualized and observed. The flow field plates with paralleled channels, and orientational channels with wavy baffles, as well as orientational channels with rectangular baffles are designed. The side walls of their channels are replaced by transparent end plates for the purpose of observation. An experimental system is set up to observe how the flow rate of the reaction gas and temperature affected the two-phase flow change in channels with a high-speed camera laterally. The results show that higher reaction gas flow rate results in more water generation, even though droplet creation in cathode flow channels occurs more slowly. The generation time of droplets in cathode flow channels delays as temperature increase, resulting in that cell performance improves more because of gas flow rate increase. Moreover, compared with wavy baffle flow channels, the rectangular baffle is more helpful for water vapor collection and forming droplets.

A current trend in the construction industry involves the development and employment of eco-friendly, durable, and sustainable materials. Numerous admixtures, including various polymers, are used to modify the properties of cement. Nonetheless, their effectiveness and environmental impacts are still a matter of discussion. In this context, this work was focused on the application of innovative vegetable oil-based polymeric nanodispersed admixtures, synthesized following green chemistry principles, such as using water as a solvent. The synthesized bio-based latex admixtures were incorporated with 30 wt% of vegetable oil-based monomers derived from camelina, linseed, and rapeseed oils. The produced ordinary Portland cement fine-grained mortars, containing 0.1 wt% of each bio-based latex admixture, were thoroughly examined using several instrumental methods, such as isothermal calorimetry and scanning electron microscopy, to gain a comprehensive understanding of the roles of bio-based latex admixtures on the physical, mechanical, and microstructural properties of the examined specimens. It was found that the addition of bio-based latex admixtures led to changes in the hydration process, mineralogical composition, and liquid water transport. For example, the water absorption coefficient was found to be approximately 40% lower compared to cement mortars produced using a reference latex additive without the vegetable oil-based component. Moreover, cement mortars with a bio-based latex admixture containing camelina oil exhibited comparable compressive strength to those produced solely from ordinary Portland cement. Thus, the newly developed bio-based polymeric nanodispersion represents a new class of environmentally friendly admixtures that may be effectively utilized for water-loaded structures.

Abstract. Perennial firn aquifers (PFAs) are year-round bodies of liquid water within firns, which modulate meltwater runoff to crevasses, potentially impacting ice-shelf and ice-sheet stability. Recently identified in the Antarctic Peninsula, PFAs form in regions with both high surface melt and snow accumulation rates and are expected to expand due to the anticipated increase in surface melt and snowfall. Using a firn model to predict future Antarctic PFAs for multiple climatic forcings is relatively computationally expensive. To address this, we developed an XGBoost perennial firn aquifer emulator, a fast machine learning model. It was trained, using a scenario and spatial blocking evaluation approach, on PFA output of simulations from the firn densification model IMAU-FDM, which was forced by the combined regional climate model RACMO2.3p2 and the global climate model CESM2 for three emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5). The trained emulator was applied on nine additional forcings (2015–2100) from the regional climate models MAR and HIRHAM in combination with five global climate models. We show that the emulator is robust, explaining at least 89 % of the variance in PFA presence and meltwater storage. Our results indicate that, for the SSP1-2.6 and SSP2-4.5 scenarios, PFAs remain mostly restricted to the Antarctic Peninsula. For SSP5-8.5, PFAs expand to Ellsworth Land in six out of the seven simulations and to Enderby Land in East Antarctica in five out of the seven simulations. Furthermore, the emulator predicts PFAs for similar surface melt and accumulation conditions when forced with MAR or RACMO data. For HIRHAM these conditions are slightly different, due to the different relationship between temperature, accumulation and melt in HIRHAM compared with RACMO. Overall, our findings show that PFAs are likely to expand in a warmer Antarctica, irrespective of the emission scenario, increasing the risk that an ice shelf collapses due to hydrofracturing.

Pineapple biomass represents an abundant renewable source of carbon and a promising feedstock with considerable potential for the production of sustainable fuels. In the present study, the influence of liquid hot water (LHW) pretreatment on the pineapple mother plant was investigated at different controlled severities, then characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). Results show that LHW pretreatment causes structural changes, leading to lignin and hemicellulose depolymerization up to a severity factor of 2.36–3.55, whereas at severity factors in the range of 4.13–5.90, cellulose, hemicellulose, and lignin appear to repolymerize. This pretreatment resulted in a higher hydrolysis efficiency (94.92 ± 0.04%) at 50 °C for 72 h. Compared with the untreated sample, the hydrolysis rate under these conditions increased by a factor of 2.16. SEM imaging revealed significant disruption of the PMP microstructure following LHW treatment, while XRD data confirmed an increase in the crystallinity index. FTIR analysis further indicated modifications in functional group profiles, supporting the structural and compositional changes induced by pretreatment. Overall, this study demonstrates the effectiveness of LHW pretreatment in enhancing the enzymatic digestibility and modifying the physicochemical properties of PMP biomass, providing a foundation for its valorization into high value bioproducts.

Cloud liquid water content (CLWC) based on microwave radiometer data was investigated in this study. First, its consistency with radiosonde-based CLWC was established. Integrated CLWC was also checked against the liquid water path. CLWC performance in four weather types was considered: dense fog, clouds in spring, rainstorms, and typhoons. CLWC provides new insights into weather events. In particular, it could be useful for nowcasting low visibility associated with sea fog. It was also found to be inversely proportional to visibility in two cases of low visibility in Hong Kong. In springtime, low-level clouds and liquid water were found to exist extensively inside clouds. In rainstorm cases, supercooled cloud liquid water was absent during heavy rain but may exist within clouds when rain stops or light rain occurs. Similar observations were made in typhoon cases, namely during the direct impact of Typhoon Wipha on Hong Kong. Supercooled cloud liquid was present when outer rainbands of the typhoon affected Hong Kong with a smaller amount of rainfall. However, when Hong Kong was hit by a typhoon’s eyewall, rain was heavier, and supercooled liquid water was absent. These features are consistent with the radiosonde-based CLWC profiles. Radiometer-based CLWC is pseudocontinuous and provides additional insight into liquid water distribution in clouds under various weather conditions.

Abstract. Long-term data on PM2.5 chemical composition provide essential information for evaluating the effectiveness of air pollution control measures and understanding the evolving mechanisms of secondary species formation in the real atmosphere. This study presented field measurements of PM2.5 and its chemical composition at a regional background site in the Pearl River Delta (PRD) from 2007 to 2020. PM2.5 concentration declined significantly from 87.1 ± 15.5 to 34.0 ± 11.3 µg m−3 (−4.0 µg m−3 yr−1). The proportion of secondary species increased from 57 % to 73 % with the improvement in air quality. Among these species, sulfate (SO42-) showed a sharp decline, while nitrate (NO3-) exhibited a moderate decrease. Consequently, the proportion of NO3- in 2020 doubled relative to 2007. In addition, we further found that SO42- reduction (−10 % yr−1) lagged behind SO2 reduction (−13 % yr−1), while NO3- reduction (−6 % yr−1) outpaced that of NO2 (−3 % yr−1). These contrasting trends were associated with an increase in sulfur oxidation rate (SOR) and a decrease in nitrogen oxidation rate (NOR). Changes in PM2.5 chemical composition also influenced aerosol physicochemical properties, such as aerosol pH (0.04 yr−1), aerosol liquid water content (ALWC, −1.1 µg m−3 yr−1), and the light extinction coefficient (−21.44 Mm−1 yr−1). Given important roles of aerosol acidity and ALWC in the heterogeneous reactions, these changes may further inhibit the formation of secondary species in the atmosphere, particularly secondary organic aerosols.

Abstract Heterogeneity in component morphology and distribution, inherent in modern electrochemical devices, frequently limits device performance and durability. However, accurately characterizing heterogeneity is challenging as it requires high‐contrast detection of evolving multi‐material components and associated interfaces, and this often bottlenecks rational design. In this study, new insights into spatio‐operational heterogeneity are quantitatively revealed within multi‐component electrochemical systems using simultaneous neutron and X‐ray tomography (NeXT). In operando fuel cells, this technique uniquely offers independent yet simultaneous and correlated characterization of material distribution and morphology. This enables accurate contextualization of liquid water within all key component interfaces in sufficient detail to resolve previously unidentified 4D heterogeneity. First, 4D heterogeneity in membrane thickness and water content is found to depend strongly upon location and operating conditions, with membrane thickness variations up to 80 µm and membrane water content variation from dry to hydrated at 21 . Second, a direct experimental link is established between anisotropic humidification and local anisotropic swelling of the membrane. The observations lend unique insights into degradation mechanisms of the membrane and have notable implications on the practical durability of fuel cells. The proposed methodology is highly relevant to advancing multi‐material electrochemical devices (with evidence of applicability to batteries provided).

Abstract. Aerosols significantly influence Earth's radiative balance, yet considerable uncertainty exists in the underpinning mechanisms, particularly those involving clouds. Aerosol–cloud interactions (ACIs) are the most uncertain element in anthropogenic radiative forcing, hampering our ability to constrain Earth's climate sensitivity and understand future climate change. The 2014–2015 Holuhraun volcanic eruption in Iceland released sulfur dioxide (SO2) into the lower troposphere on a level comparable to continental-scale emissions. The resultant volcanic plume across an often near-pristine region of the northern North Atlantic Ocean presents an ideal opportunistic experiment to explore ACI representation within general circulation models (GCMs). We present Part 2 of a two-part AeroCom (Aerosol Comparisons between Observations and Models) Phase III inter-model comparison study that utilises satellite remote sensing observations to assess modelled cloud responses to the Holuhraun attributed volcanic aerosol within eight state-of-the-art GCMs during September and October 2014. We isolate the aerosol effect from meteorological variability and find that the GCMs – particularly their multi-model ensemble response – adeptly capture the observed cloud microphysical changes associated with the ACI first indirect effect (i.e. Twomey effect). Meanwhile, a clear divergence exists in the GCM responses of large-scale cloud properties, namely cloud liquid water content, expected from the precipitation suppression mechanism of the ACI second indirect effect (i.e. rapid adjustments). We attribute this to limitations and differences in their autoconversion schemes under high aerosol loading, specifically in sub-grid-variability representations. Finally, our multi-model ensemble estimates that Holuhraun had a global radiative forcing of −0.11 ± 0.04 Wm−2 across September and October 2014.

3D Numerical Study of the Liquid Water Distribution in Bipolar Membrane Fuel Cells