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On-site conversion of organic waste into biogas to satisfy consumer energy demand has the potential to realize energy equality and mitigate climate change reliably. However, existing methods ignore either real-time full supply or methane escape when supply and demand are mismatched. Here, we show an improved design of community biogas production and distribution system to overcome these and achieve full co-benefits in developing economies. We take five existing systems as empirical examples. Mechanisms of synergistic adjusting out-of-step biogas flow rates on both the plant-side and user-side are defined to obtain consumption-to-production ratios of close to 1, such that biogas demand of rural inhabitants can be met. Furthermore, carbon mitigation and its viability under universal prevailing climates are illustrated. Coupled with manure management optimization, Chinese national deployment of the proposed system would contribute a 3.77% reduction towards meeting its global 1.5 °C target. Additionally, fulfilling others' energy demands has considerable decarbonization potential.

Terrestrial production and export of dissolved organic and inorganic carbon (DOC and DIC) to streams depends on water flow and biogeochemical processes in and beneath soils. Yet, understanding of these processes in a rapidly changing climate is limited. Using the watershed-scale reactive-transport model BioRT-HBV and stream data from a snow-dominated catchment in the Rockies, we show deeper groundwater flow averaged about 20% of annual discharge, rising to ∼35% in drier years. DOC and DIC production and export peaked during snowmelt and wet years, driven more by hydrology than temperature. DOC was primarily produced in shallow soils (1.94 ± 1.45 gC/m2/year), stored via sorption, and flushed out during snowmelt. Some DOC was recharged to and further consumed in the deeper subsurface via respiration (−0.27 ± 0.02 gC/m2/year), therefore reducing concentrations in deeper groundwater and stream DOC concentrations at low discharge. Consequently, DOC was primarily exported from the shallow zone (1.62 ± 0.96 gC/m2/year, compared to 0.12 ± 0.02 gC/m2/year from the deeper zone). DIC was produced in both zones but at higher rates in shallow soils (1.34 ± 1.00 gC/m2/year) than in the deep subsurface (0.36 ± 0.02 gC/m2/year). Deep respiration elevated DIC concentrations in the deep zone and stream DIC concentrations at low discharge. In other words, deep respiration is responsible for the commonly-observed increasing DOC concentrations (flushing) and decreasing DIC concentrations (dilution) with increasing discharge. DIC export from the shallow zone was ~66% of annual export but can drop to ∼53% in drier years. Numerical experiments suggest lower carbon production and export in a warmer, drier future, and a higher proportion from deeper flow and respiration processes. These results underscore the often-overlooked but growing importance of deeper processes in a warming climate.

We present a new pore-scale model for multicomponent advective-diffusive transport with coupled mineral dissolution and precipitation. Both dissolution and precipitation are captured simultaneously by introducing a phase transformation vector field representing the direction and magnitude of the overall phase change. An effective viscosity model is adopted in simulating fluid flow during mineral dissolution-precipitation that can accurately capture the velocity field without introducing any empirical parameters. The proposed approach is validated against analytical solutions and interface tracking simulations in simplified structures. After validation, the proposed approach is employed in modeling realistic rocks where mineral dissolution and precipitation are dominant at different locations. We have identified three regimes for mineral dissolution-precipitation coupling: (a) compact dissolution-precipitation where dissolution is dominant near the inlet and precipitation is dominant near the outlet, (b) wormhole dissolution with clustered precipitation where dissolution generates wormholes in the main flow paths and precipitation clogs the secondary flow paths, and (c) dissolution dominant where all solid grains are gradually dissolved. In the three regimes, the proposed approach provides reliable porosity-permeability relationships that cannot be described well by traditional macroscale models. We find that the permeability can increase while the overall porosity decreases when the main flow paths are expanded by dissolution and adjacent pore spaces are clogged by precipitation.

Knowledge of the recurrence intervals of precipitation extremes is vital for infrastructure design, risk assessment, and insurance planning. However, trends and shifts in rainfall patterns globally pose challenges to the application of extreme value analysis (EVA) which relies critically on the assumption of stationarity. In this paper, we explore: (1) the suitability of nonstationary (NS) models in the presence of statistically significant trends, and (2) their potential in modeling out-of-sample data to improve frequency analysis of extreme precipitation. We analyze the benefits of using a nonstationary Generalized Extreme Value (GEV) model for annual extreme precipitation records from Southern Brazil. The location of the GEV distribution is allowed to change with time. The unknown GEV model parameters are estimated using Bayesian techniques coupled with Markov chain Monte Carlo simulation. Next, we use GAME sampling to compute the evidence (and their ratios, the so-called Bayes factors) for stationary and nonstationary models of annual maximum precipitation. Our results show that the presence of a statistically significant trend in annual maximum precipitation alone does not justify the use of a NS model. The location parameter of the GEV distribution must also be well defined, otherwise, stationary models of annual maximum precipitation receive more support by the data. These findings reiterate the importance of accounting for GEV model parameters and predictive uncertainty in frequency analysis and hypothesis testing of annual maximum precipitation data records. Furthermore, a meaningful EVA demands detailed knowledge about the origin and persistence of observed changes.

Most of the available data on diffusion in natural clayey rocks consider tracer diffusion in the absence of a salinity gradient despite the fact that such gradients are frequently found in natural and engineered subsurface environments. To assess the role of such gradients on the diffusion properties of clayey materials, through-diffusion experiments were carried out in the presence and absence of a salinity gradient using salt-diffusion and radioisotope tracer techniques. The experiments were carried out with vermiculite samples that contained equal proportions of interparticle and interlayer porosities so as to assess also the role played by the two types of porosities on the diffusion of water and ions. Data were interpreted using both a classical Fickian diffusion model and with a reactive transport code, CrunchClay that can handle multi-porosity diffusion processes in the presence of charged surfaces. By combining experimental and simulated data, we demonstrated that (i) the flux of water diffusing through vermiculite interlayer porosity was minor compared to that diffusing through the interparticle porosity, and (ii) a model considering at least three types of porous volumes (interlayer, interparticle diffuse layer, and bulk interparticle) was necessary to reproduce consistently the variations of neutral and charged species diffusion as a function of salinity gradient conditions.

Geologic features (e.g., fractures and alluvial fans) can play an important role in the locations and volumes of groundwater discharge and degree of groundwater-surface water (GW-SW) interactions. However, the role of these features in controlling GW-SW dynamics and streamflow generation processes are not well constrained. GW-SW interactions and streamflow generation processes are further complicated by variability in precipitation inputs from summer and fall monsoon rains, as well as declines in snowpack and changing melt dynamics driven by warming temperatures. Using high spatial and temporal resolution radon and water stable isotope sampling and a 1D groundwater flux model, we evaluated how groundwater contributions and GW-SW interactions varied along a stream reach impacted by fractures (fractured-zone) and downstream of the fractured hillslope (non-fractured zone) in Coal Creek, a Colorado River headwater stream affected by summer monsoons. During early summer, groundwater contributions from the fractured zone were high, but declined throughout the summer. Groundwater contributions from the non-fractured zone were constant throughout the summer and became proportionally more important later in the summer. We hypothesize that groundwater in the non-fractured zone is dominantly sourced from a high-storage alluvial fan at the base of a tributary that is connected to Coal Creek throughout the summer and provides consistent groundwater influx. Water isotope data revealed that Coal Creek responds quickly to incoming precipitation early in the summer, and summer precipitation becomes more important for streamflow generation later in the summer. We quantified the change in catchment dynamic storage and found it negatively related to stream water isotope values, and positively related to modeled groundwater discharge and the ratio of fractured zone to non-fractured zone groundwater. We interpret these relationships as declining hydrologic connectivity throughout the summer leading to late summer streamflow supported predominantly by shallow flow paths, with variable response to drying from geologic features based on their storage. As groundwater becomes more important for sustaining summer flows, quantifying local geologic controls on groundwater inputs and their response to variable moisture conditions may become critical for accurate predictions of streamflow.

Understanding connectivity between the soil and deeper bedrock groundwater is needed to accurately predict a watershed's response to perturbation, such as drought. Yet, the bedrock groundwater dynamics in mountainous environments are typically under-constrained and excluded from watershed hydrologic models. Here, we investigate the role of groundwater characterized with decadal and longer water ages on the hydrologic and mass-transport processes within a steep snow-dominated mountain hillslope in the Central Rocky Mountains (USA). We quantify subsurface and surface water mass-balance, groundwater flowpaths, and age distributions using the ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models, which are compared to hydrometric and environmental tracer observations. An ensemble of models with varied soil and hydrogeologic parameters reproduces observed groundwater levels and century-scale mean ages inferred from environmental tracers. The numerical models suggest soil water near the toe of the hillslope contains considerable (>60 % of the mass-flux) contributions from bedrock flowpaths characterized with water ages >10 years. Flowpath connectivity between the deeper bedrock and soil systems is present throughout the year, highlighting the potentially critical role of groundwater with old ages on processes such as evapotranspiration and streamflow generation. The coupled numerical model and groundwater age observations show the bedrock groundwater system influences the hillslope hydrodynamics and should be considered in mountain watershed conceptual and numerical models.

The sources and sinks of nitrous oxide, as control emissions to the atmosphere, are generally poorly constrained for most environmental systems. Initial depth-resolved analysis of nitrous oxide flux from observation wells and the proximal surface within a nitrate contaminated aquifer system revealed high subsurface production but little escape from the surface. To better understand the environmental controls of production and emission at this site, we used a combination of isotopic, geochemical, and molecular analyses to show that chemodenitrification and bacterial denitrification are major sources of nitrous oxide in this subsurface, where low DO, low pH, and high nitrate are correlated with significant nitrous oxide production. Depth-resolved metagenomes showed that consumption of nitrous oxide near the surface was correlated with an enrichment of Clade II nitrous oxide reducers, consistent with a growing appreciation of their importance in controlling release of nitrous oxide to the atmosphere. Our work also provides evidence for the reduction of nitrous oxide at a pH of 4, well below the generally accepted limit of pH 5.

Natural conversion of ferrihydrite (Fh), a widespread Fe(iii)-oxyhydroxide mineral at the Earth's surface, to thermodynamically more stable iron oxides such as goethite (Gt) and hematite (Hm) is a slow process that spans months to years. Here we examined the effects of synthesis and storage conditions on the hydration, the ratio of tetrahedral to octahedral iron sites, and the transformation of naturally aged 2-line Fh at room temperature and mildly acidic pH over an ageing period of 5 years. Fh samples synthesized and aged in either aerobic or anaerobic conditions were characterized over time by XRD, SEM, thermogravimetric analysis - mass spectroscopy (TGA-MS), and X-ray absorption spectroscopies (XANES and XMCD). The findings show that the ratio of tetrahedral to octahedral Fe(iii) sites in Fh is correlated to its extent of hydration, with fresher Fh samples exhibiting a higher ratio and more bound water. Fresh Fh aged in aerobic conditions has similar bound inorganic carbon, is more hydrated, and has less tetrahedral Fe(iii) than that aged in anaerobic conditions. Hence, for relatively fresh Fh there is a link between Fh properties and storage conditions. However, the long-term ageing characteristics, such as the transformation rate and relative phase fraction of Gt and Hm products, are not noticeably impacted by storage conditions. TGA-MS measurements coupled with O K-edge XANES spectra confirm that Fh tends to lose its hydration as it ages, as expected. Corresponding Fe L2,3-edge XMCD spectra reveal that this dehydration is coupled to a steady decrease in the ratio of tetrahedral to octahedral Fe(iii) sites. In addition to the obvious constraints these findings place on making comparisons across Fh samples of different age and environmental settings, they also highlight that Fh structure, and consequently magnetism, are linked to its bound water content.

The presence of toxic metals in tobacco smoke is well documented. However, few studies have quantified trace metals in secondhand smoke (SHS) and thirdhand smoke (THS). Their presence in indoor air can contribute to nonsmokers’ exposures and health effects. In this study, emission and deposition rates of toxic trace metals were determined, and their airborne concentration in typical indoor scenarios was predicted. PM2.5 was collected on Teflon-coated filters at various times following a smoking event in a room-sized chamber over a 43 h period. The concentration of 28 trace metals was determined by extraction and analysis using inductively coupled plasma-triple quadrupole-mass spectrometry (ICP-QQQ-MS). Emission and indoor deposition rates of cadmium, arsenic, chromium, manganese, beryllium and selenium were determined, and used to predict concentrations expected in a smokers’ home and a smoking bar. In most of the considered scenarios, average indoor concentrations of Cd, As, and Cr exceeded their corresponding cancer risk thresholds and, in some cases, also noncancer reference exposure levels, more than 3 h after smoking ended. The fraction of cadmium that remained airborne was significantly higher than those of other metal traces and that of PM2.5, suggesting an association of Cd traces with small particles.

In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high-resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station-based SWE observations are used as the prediction target. All DL models produce higher median Nash-Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

Existing simplified procedures for evaluating soil liquefaction potential or for estimating excess pore pressures during earthquakes are typically based on undrained cyclic tests performed on saturated soil samples under controlled loading and boundary conditions. Under such conditions, the effect of excess pore pressure (ue) dissipation and redistribution to neighboring soil layers cannot be accounted for. Existing simplified procedures treat liquefiable layers as isolated soil layers without any boundary conditions even if dense and loose layers are very thin, permeable, and adjacent to each other. However, redistribution is likely to increase and decrease ue in the neighboring dense and loose layers respectively. Until now, no procedure short of fully coupled numerical analysis is available to estimate the importance of redistribution. This paper presents an approximate analytical procedure for assessing the effects of ue redistribution in (1) soil layers that would have liquefied if they were undrained, and (2) soil layers that would have not liquefied even if undrained. It is found that a layer that is initially assumed liquefied under undrained conditions might not even liquefy accounting for the ue redistribution to neighboring layers. On the other hand, a layer initially assumed to not liquefy can develop significant ue and can even liquefy due to pore pressure migration from the neighboring layers. Thus, accounting for redistributed ue is important for liquefaction consequence assessment quantification, particularly in systems that span the depth of these effects like deep foundations. Migration of u toward the tip of a pile can reduce its capacity, even if the tip is embedded in a dense sand layer. On the other hand, if redistribution can result in the reduction of ue in initially assumed liquefied layers, risks associated with liquefaction might be avoided. A criterion is also developed to evaluate the thicknesses of a layer below which redistribution could prevent liquefaction even if the layer is deemed liquefied according to the existing liquefaction-triggering procedures. Finally, the proposed procedure is illustrated by application to selected shaking events of centrifuge tests involving liquefaction of layered soil profiles. The predictions from the procedure matched the centrifuge test results reasonably.

Predictive high-fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch-control, stall/vortex-induced vibrations, and aftermarket add-ons. The biggest challenge with high-fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high-performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU-enabled open-source incompressible-flow hybrid-computational fluid dynamics framework, comprising the near-body unstructured grid solver Nalu-Wind, and the off-body block-structured-grid solver AMR-Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds-averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds-averaged Navier–Stokes is used for near-body flow and large eddy simulation is used for off-body flow. Being two-way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry-resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt-scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

Correction to: Transport in Porous Media (2024) 151:55–84https://doi.org/10.1007/s11242-023-02033-0. There are three numbers in Table 2 of the original paper that were incorrect. Specfically, the value of the density of hydrogen (H2) for the DB model and the values of density and viscosity of H2 for the TOUGH2 model listed in Table 2 of the original paper were incorrect. (Table presented.) Properties of the H2-water upconing system for comparison against the DB model. Property DB model Used for TOUGH2 Gas cap thickness, total reservoir thickness, and radial extent (outer radius) of the reservoir Infinite, infinite, infinite 50 m, 100 m (with open boundary at bottom), 100 m (open boundary condition) Porosity (ϕ) 0.10 0.10 Permeability (kH) 1.0 × 10−12 m2 1.0 × 10−12 m2 Permeability (kV) 1.0 × 10−12 m2 1.0 × 10−12 m2 Relative permeability (krel) Not applicable Linear with Slr = 0.99 Distance from well to H2-water interface (d) 10 m 10 m Extraction rate of rate of H2 (Qm) − 5.5 kg s−1 − 5.5 kg s−1 Density of water 996 kg m−3 996 kg m−3 Density of H2 7.32 kg m−3 7.87 kg m−3 Viscosity of water 6.54 × 10−4 Pa s 5.11 × 10−4 Pa s Viscosity of H2 9.31 × 10−6 Pa s 9.53 × 10−6 Pa s A corrected Table 2 is shown below. The erroneous values in Table 2 were not used in any of the modeling and simulation. Accurate values for density and viscosity in the modeling and simulation come from CoolProp for the DB model and from EOS7CH for the TOUGH2 simulations.

In this Reply, we address the concerns of Knoben and Clark (2023, https://doi.org/10.1029/2022WR034294) or KC23 that “the assumptions needed to effectively use difference-based variance estimation methods are not always met by hourly streamflow records.” There should be little doubt that the assumptions of our difference-based estimator will sometimes be violated in hourly streamflow records but the results from de Oliveira and Vrugt (2022, https://doi.org/10.1029/2022wr032263) and confirmed by the findings in our Reply show that such violations are sporadic enough not to affect much the error variance estimates. Snowmelt as pointed out by KC23 (https://doi.org/10.1029/2022WR034294) may not have received sufficient attention in our paper, yet their 365-day record is simply not long enough to demonstrate bias of our discharge error variance estimates (and their dependence on flow level). This would require analysis of a much longer, multi-year, streamflow record of a snowmelt-driven watershed. The snowmelt catchment analyzed in dOV22 (https://doi.org/10.1029/2022wr032263) did not demonstrate bias in the discharge error variance estimates. We also provide additional clarification on the interpretation of the variance estimates obtained with the nonparametric estimator, and discuss the main issues in the test case presented in Knoben and Clark (2023, https://doi.org/10.1029/2022WR034294)).

Coupling of power-to-gas processes with underground gas storage could effectively allow surplus electricity to be stored for later use. Depleted hydrocarbon reservoirs could be used as stores, but practical experience of hydrogen storage in such sites is limited. Here we present data from a field trial that stored 119,353 m3 of hydrogen admixed to natural gas in a depleted hydrocarbon reservoir. After 285 days, hydrogen recovery was 84.3%, indicating the process’s technical feasibility. Additionally, we report that microbes mediated hydrogen conversion to methane. In laboratory experiments studying mesocosms that mimic real reservoirs, hydrogen and carbon dioxide were converted to methane (0.26 mmol l−1 h−1 evolution rate) reproducibly over 14 cycles in 357 days. This rate theoretically allows 114,648 m3 of methane per year to be produced in the test reservoir (equivalent to ~1.08 GWh). Our research demonstrates the efficiency of hydrogen storage and the importance of geo-methanation in depleted hydrocarbon reservoirs.

Buried water reservoirs are increasingly being built to replace open aboveground municipal water supply reservoirs in urban areas to enhance water quality and utilize their surface footprint for other purposes such as public parks or placement of solar arrays. Many of these lifeline structures are in seismically active regions and, as such, need to be designed to remain operational after severe earthquake shaking. However, evaluating their seismic response is challenging and involves accounting for the interaction of the structure with the stored fluid and the retained soil; in other words, accounting for fluid-structure-soil interaction (FSSI). This paper presents a combined experimental-numerical study on the seismic behavior of buried water reservoirs while considering FSSI. Two series of centrifuge model tests were performed at different reservoir orientations to investigate one-dimensional (1D) and two-dimensional (2D) motion effects under full, half-full, and empty reservoir conditions. Corresponding numerical models were developed whereby the structure and the soil were represented by continuum Lagrangian finite elements, while the fluid was modeled via Arbitrary Lagrangian Eulerian formulation. Soil-structure and fluid-structure interface parameters were calibrated using the experimental measurements. The simulations successfully captured the measured reservoir responses in terms of accelerations, bending moment increments, and water pressures. The study found that the common assumption of plane strain is not applicable for reservoirs because their behavior was found to be truly three-dimensional (3D) whereby stresses accumulated at the corners. Furthermore, the full reservoir resulted in the highest seismic demands in the reservoir walls and roof while the empty reservoir yielded the highest base slippage. The study demonstrates that the complex reservoir seismic response is best captured by carrying out a 3D FSSI numerical simulation.

Thermal energy storage (TES) solutions offer opportunities to reduce energy consumption, greenhouse gas emissions, and cost. Specifically, they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load, which are critical toward zero energy buildings. Thermochemical materials (TCMs) as a class of TES undergo a solid–gas reversible chemical reaction with water vapor to store and release energy with high storage capacities (600 kWh m−3) and negligible self-discharge that makes them uniquely suited as compact, stand-alone units for daily or seasonal storage. However, TCMs suffer from instabilities at the material (salt particles) and reactor level (packed beds of salt), resulting in poor multi-cycle efficiency and high-levelized cost of storage. In this study, a model is developed to predict the pulverization limit or Rcrit of various salt hydrates during thermal cycling. This is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy-efficient manufacturing process (solid-state mixing) to make the composites. The model is experimentally validated on multiple TCM salt hydrates with different water content, and effect of Rcrit on hydration and dehydration kinetics is also investigated.

Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.

Predicting the hydrological response of watersheds to climate disturbances requires a detailed understanding of the processes connecting hillslopes and streams. Using a network of soil moisture and temperature sensors, electrical resistivity tomography monitoring, and a weather station we assess the above and below-ground processes driving the hydrological response of a hillslope during snowmelt and summer monsoon. The transect covers bedrock and vegetation gradients, with a steep upper part characterized by shallow bedrock, and gentle lower part underlain by colluvium. The main vegetation cover is conifers on the upper, and grass and veratrum on the lower part. Combined with a simplified hydrological model, we show that the thin soil layer of the steep slope acts as a preferential flow path, leading to mostly shallow lateral flow, interrupted by vertical flow, mostly at tree locations, and likely facilitated by flow along fractures and roots. Vertical flow and upstream-driven groundwater dynamics are prevailing at the colluvium, presenting a very different hydrological behavior compared to the upper part. These results show that subsurface structure and features have a strong control on the hydrological response of a hillslope and that those can create considerably varying hydrological dynamics across small spatial scales.

Abstract: Floodplain lakes are widespread and ecologically important throughout tropical river systems, however data are rare that describe how temporal variations in hydrological, meteorological and optical conditions moderate stratification and mixing in these shallow lakes. Using time series measurements of meteorology and water‐column temperatures from 17 several day campaigns spanning two hydrological years in a representative Amazon floodplain lake, we calculated surface energy fluxes and thermal stratification, and applied and evaluated a 3‐dimensional hydrodynamic model. The model successfully simulated diel cycles in thermal structure characterized by buoyancy frequency, depth of the actively mixing layer, and other terms associated with the surface energy budget. Diurnal heating with strong stratification and nocturnal mixing were common; despite considerable heat loss at night, the strong stratification during the day meant that mixing only infrequently extended to the bottom at night. Simulations indicated that the diurnal thermocline up and downwelled creating lake‐wide differences in near‐surface temperatures and mixing depths. Infrequent full mixing creates conditions conducive to anoxia in these shallow lakes given their warm temperatures.

Abstract: Toxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long‐range forecasts is overly challenging, predicting imminent CBs is possible from precise monitoring data of the underlying covariates. It is, however, infeasibly costly to conduct precise monitoring on a large scale, leaving most lakes unmonitored or only partially monitored. The challenge is hence to build a predictive model that can use the incomplete, partially‐monitored data to make near‐future CB predictions. By using 30 years of monitoring data for 78 water bodies in Alberta, Canada, combined with data of watershed characteristics (including natural land cover and anthropogenic land use) and meteorological conditions, we train a Bayesian network that predicts future 2‐week CB with an area under the curve (AUC) of 0.83. The only monitoring data that the model needs to reach this level of accuracy are whether the cell count and Secchi depth are low, medium, or high, which can be estimated by advanced high‐resolution imaging technology or trained local citizens. The model is robust against missing values as in the absence of any single covariate, it performs with an AUC of at least 0.78. While taking a major step toward reduced‐cost, less data‐intensive CB forecasting, our results identify those key covariates that are worth the monitoring investment for highly accurate predictions.

Understanding the mechanisms that control seasonal groundwater recharge at local and intermediate scales is critical for understanding contaminant transport. The recharge mechanism of seasonal precipitation and irrigation, companied with legacy wastewater in porewater in alluvial aquifer were complicated due to the seasonal variation of multiple recharge sources. In this study, a long-term wastewater leakage and irrigation region along the Tanghe Wastewater Reservoir (TWR) in the alluvial plain area of North China Plain to investigate the recharge mechanism from unsaturated zone to the upper shallow groundwater affected by multiple water sources. Water chemical ions and stable isotopes of water (2H and 18O) of 30 m deep sediment profiles and groundwater boreholes were used to trace the recharge processes. The porewater stable isotopes of the sediment profiles revealed vertical recharge rates ranging from 0.63 to 1.09 m/year for the layered unsaturated zone with silt and silty clay. Due to the matrix flow through unsaturated zone, the legacy wastewater in the unsaturated zone affected the variation of groundwater quality in long term. However, fast flow (i.e., preferential or lateral flow) occurred in sand layers of alluvial aquifers lead to significant precipitation contributions (44 to 61 %) to the upper shallow groundwater (USGW) recharge, resulting in the seasonal variation of stable isotopes and water chemical ions. Affected by the fast flow with seasonal variations and matrix flow with legacy wastewater in the unsaturated zone, the δ2H and δ18O relationship of the USGW showed two types of hysteresis loops in the dual isotope space: 1) groundwater in regions affected by the TWR wastewater leakage shows narrow loops and a nearly straight line with end-members of precipitation that recharged to groundwater by fast flow, and evaporated porewater plotting along the TWR evaporation line; and 2) groundwater in irrigated farmlands with low and high irrigation amounts and intense evaporation shows stronger hysteresis with loops overlapping with shallow porewater, suggesting the impact of legacy wastewater of the unsaturated zone on groundwater. The residual pollutants in soil and the type of fast flow determine the different seasonal variation of groundwater quality. Preferential flow in alluvial aquifer regions can increase the proportion of seasonal recharge from precipitation, resulting in the rapid introduction of contaminants from surface or shallow soils into the alluvial aquifer.

This study demonstrated the performance of Fe2O3 nanorods-loaded carbon nanofiber sheet (Fe2O3/CNF) as a heterogeneous Fenton-like catalyst for simultaneous removal of various organic and inorganic contaminants without external energy input and chemical reagents. Fe2O3/CNF exhibited notable activities for spontaneous oxidative degradation and reductive transformation in ambient solution, with a synergistic effect for removing dual contaminants (organic||inorganic). The synergistic redox conversions on Fe2O3/CNF were facilitated by the in-situ generation of oxidant and reductant. The additional oxidant can be generated by the reaction of chromium species with in-situ produced H2O2 while the additional reductant can be generated by the incomplete oxidation of organic contaminants. Various spectroscopic characterizations and mechanistic analyses suggest that simultaneous redox conversions are induced by spontaneous electron transfers on Fe2O3/CNF. Furthermore, a flow-reactor equipped with Fe2O3/CNF achieved the simultaneous removal of dual contaminants, making it an effective reactive filter that operates without chemical reagents for water treatment.

Community solar, a business model where multiple customers buy output from shared solar systems, has expanded solar access among multifamily housing occupants, renters, and low-income households. Policies to enable community solar could be expanded and benefits of access augmented through targeted measures to support community solar adoption in underserved communities.

Correction to: Nature Energyhttps://doi.org/10.1038/s41560-024-01546-2, published online 3 June 2024 In the version of the article initially published, data in Fig. 5b–d were displayed incorrectly and have now been amended in the HTML and PDF versions of the article. The original and corrected figures can be seen below in Fig. 1. (Figure presented.)

The long-lived radiotoxicity of the high-level radioactive waste generated by nuclear power plants requires safe isolation from the biosphere for many hundreds of thousands of years. An international consensus has emerged that such isolation can best be provided by disposal in mined geologic repositories, a strategy that today is pursued by most countries dealing with radioactive waste. However, the need to predict the performance of such repositories over very long time periods generates large uncertainties that have to be accounted for in safety assessments. The findings from such safety assessments need to be conveyed to all stakeholders in a clear way, such that public confidence in geologic disposal solutions can be achieved. It is suggested here that close international collaboration on the technical aspects of geologic waste disposal has helped, and will continue to help, building trust and increasing confidence. This paper discusses a particular international collaboration initiative referred to as DECOVALEX, which brings together multiple teams and disciplines to collectively tackle complex experimental and modeling challenges related to geologic disposal. By describing how DECOVALEX works and by providing joint research examples, a case is made that such international collaboration contributes to knowledge transfer and confidence building in radioactive waste disposal science.

Rooftop and community solar are alternative product classes for residential solar in the United States. Community solar, where multiple households buy solar from shared systems, could make solar more accessible by reducing initial costs and removing adoption barriers for renters and multifamily building occupants. Here we test whether community solar has expanded solar access in the United States. On the basis of a sample of 11 states, we find that community solar adopters are about 6.1 times more likely to live in multifamily buildings than rooftop solar adopters, 4.4 times more likely to rent and earn 23% less annual income. We do not find that community solar expands access in terms of race. These differences are driven, roughly evenly, by inherent differences between the two solar products and by policies to promote low-income community solar adoption. The results suggest that alternative solar products can expand solar access and that policy could augment such benefits.

The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment-trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model-based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot-scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO-56 model), and (4) evaluating the performance of ERT-based ET computation. Our results showed that ERT was able to capture decimeter-scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point-based sensing, which can further our understanding of the hydraulic dynamics in the soil-plant-atmosphere continuum.

About 80 % of the precipitation at the Colorado River s headwaters is snow, and the resulting snowmeltdriven hydrograph is a crucial water source for about 40 million people. Snowmelt from alpine and subalpine snowpack contributes substantially to groundwater recharge and river flow. However, the dynamics of snowmelt progression are not well understood because observations of the highelevation snowpack are difficult due to challenging access in complex mountainous terrain as well as the cost and labor intensity of currently available methods. We present a novel approach to infer the processes and dynamics of highelevation snowmelt contributions predicated upon stable hydrogen and oxygen isotope ratios observed in streamflow. We show that deuterium-excess (d-excess) values of stream water could serve as a comparatively cost-effective proxy for a catchment-integrated signal of high-elevation snowmelt contributions to catchment runoff. We sampled stable hydrogen and oxygen isotope ratios of the precipitation, snowpack, and stream water in the East River, a headwater catchment of the Colorado River, and the stream water of larger catchments at sites on the Gunnison River and Colorado River. The d-excess of snowpack increased with elevation; the upper subalpine and alpine snowpack (> 3200 m) had substantially higher d-excess compared to lower elevations (< 3200 m) in the study area. The d-excess values of stream water reflected this because d-excess values increased as the higher-elevation snowpack contributed more to stream water generation later in the snowmelt/runoff season. End-member mixing analyses based on the d-excess data showed that the share of high-elevation snowmelt contributions within the snowmelt hydrograph was on average 44 % and generally increased during melt period progression, up to 70 %. The observed pattern was consistent during 6 years for the East River, and a similar relation was found for the larger catchments on the Gunnison and Colorado rivers. High-elevation snowpack contributions were found to be higher for years with lower snowpack and warmer spring temperatures. Thus, we conclude that the d-excess of stream water is a viable proxy to observe changes in high-elevation snowmelt contributions in catchments at various scales. Inter-catchment comparisons and temporal trends of the d-excess of stream water could therefore serve as a catchment-integrated measure to monitor if mountain systems rely on high-elevation water inputs more during snow drought compared to years of average snowpack depths.

The two-term infiltration equation (Formula presented.) is commonly used to determine the sorptivity, (Formula presented.) (Formula presented.), and product, (Formula presented.) (Formula presented.), of the dimensionless multiple (Formula presented.) and saturated soil hydraulic conductivity (Formula presented.) (Formula presented.) from cumulative vertical infiltration measurements (Formula presented.) (L) at times (Formula presented.) (T). This reduced form of the quasi-analytical power series solution of Richardson's equation of Philip enjoys a solid physical underpinning but at the expense of a limited time validity. Using simulated infiltration data, Jaiswal et al. have shown this time validity to equal about 2.5 cm of cumulative infiltration. The goals of this work are twofold. First, we investigate the extent to which cumulative infiltration measurements larger than 2.5 cm bias the estimates of (Formula presented.) and (Formula presented.). Second, we investigate the impact of epistemic errors on the inferred time validities and parameters. Partial infiltration curves up to 2.5 cm of cumulative vertical infiltration improve substantially the agreement between actual and least squares estimates of (Formula presented.) and (Formula presented.). But this only holds if the data generating infiltration process follows Richardson's equation and experimental conditions satisfy assumptions of soil homogeneity and a uniform initial water content. Otherwise, autocorrelated cumulative infiltration residuals will bias the least squares estimates of (Formula presented.) and (Formula presented.). Our findings reiterate and reinvigorate earlier conclusions of Haverkamp et al. and show that epistemic errors deteriorate the physical significance of the coefficients of infiltration functions. As a result, the parameters of infiltration functions cannot simply be used in storm water and vadose zone flow models to forecast runoff and recharge at field and landscape scales unless these predictions are accompanied by realistic uncertainty bounds. We conclude that the time validity of Philip's two-term equation is an elusive theoretical quantity with arbitrary physical meaning.

This study investigates the quasi-static bearing stress-settlement response of shallow foundations in monolithic tire derived aggregate (TDA) layers having a total thickness of 3 m using a large-scale container and loading system. Tests were performed on footings having a range of widths, embedment depths, shapes, and loading inclinations. In tests where tilting was restricted, a clear bearing capacity was not observed for settlements up to 1.2B, where B is the footing width, but in tests where tilting was permitted bearing capacity was observed between settlements of 0.2B to 0.7B. Surface settlements indicate a dragdown response of the TDA adjacent to the footing extending out to more than 3B from the footing center, while settlement plates beneath the footing indicate a zone of influence of induced settlements of 14% at a depth of 4B. While bearing capacity theories for frictional geomaterials provided a reasonable prediction of the bearing capacity of footings in TDA for most tests, the corresponding settlements may be excessive for engineering applications. Accordingly, a correlation was developed between the theoretical bearing capacity and bearing stress at a settlement of 0.1B. A test with sustained loading indicates slight creep settlements with some stress dependency with magnitudes consistent with past studies.

BackgroundPrenatal exposure to metals is hypothesized to be associated with child autism. We aim to investigate the joint and individual effects of prenatal exposure to urine metals including lead (Pb), mercury (Hg), manganese (Mn), and selenium (Se) on child Social Responsiveness Scale (SRS) scores.MethodsWe used data from 2 cohorts enriched for likelihood of autism spectrum disorder (ASD): Early Autism Risk Longitudinal Investigation (EARLI) and the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) studies. Metal concentrations were measured in urine collected during pregnancy. We used Bayesian Kernel Machine Regression and linear regression models to investigate both joint and independent associations of metals with SRS Z-scores in each cohort. We adjusted for maternal age at delivery, interpregnancy interval, maternal education, child race/ethnicity, child sex, and/or study site.ResultsThe final analytic sample consisted of 251 mother-child pairs. When Pb, Hg, Se, and Mn were at their 75th percentiles, there was a 0.03 increase (95% credible interval [CI]: -0.11, 0.17) in EARLI and 0.07 decrease (95% CI: -0.29, 0.15) in MARBLES in childhood SRS Z-scores, compared to when all 4 metals were at their 50th percentiles. In both cohorts, increasing concentrations of Pb were associated with increasing values of SRS Z-scores, fixing the other metals to their 50th percentiles. However, all the 95% credible intervals contained the null.ConclusionsThere were no clear monotonic associations between the overall prenatal metal mixture in pregnancy and childhood SRS Z-scores at 36 months. There were also no clear associations between individual metals within this mixture and childhood SRS Z-scores at 36 months. The overall effects of the metal mixture and the individual effects of each metal within this mixture on offspring SRS Z-scores might be heterogeneous across child sex and cohort. Further studies with larger sample sizes are warranted.

We report the dielectric constant of 1 M LiPF6 in EC:EMC 3:7 w/w (ethylene carbonate/ethyl methyl carbonate) in addition to neat EC:EMC 3:7 w/w. Using three Debye relaxations, the static permittivity value, or dielectric constant, is extrapolated to 18.5, which is compared to 18.7 for the neat solvent mixture. The EC solvent is found to strongly coordinate with the Li+ cations of the salt, which results in a loss of dielectric contribution to the electrolyte. However, the small amplitude and large uncertainty in relaxation frequency for EMC cloud definitive identification of the Li+ solvation shell. Importantly, the loss of the free EC permittivity contribution due to Li+ solvation is almost completely balanced by the positive contribution of the associated LiPF6 salt, demonstrating that a significant quantity of dipolar ion pairs exists in 1 M LiPF6 in EC:EMC 3:7.

This paper estimates feasible water savings for a sample of nine urban water districts in California during the height of the 2012-16 drought, just prior to the implementation of mandatory water use reductions, using household production theory and stochastic frontier analysis. Estimates of feasible savings are compared to mandated reductions and actual reductions in each district. Although the mandated reductions were generally feasible, our results show that they had asymmetric impacts across districts and tended to impose larger burdens on some disadvantaged groups.

The solid-electrolyte interphase (SEI) critically governs the performance of rechargeable batteries. An ideal SEI is expected to be electrically insulative to prevent persistently parasitic reactions between the electrode and the electrolyte and ionically conductive to facilitate Faradaic reactions of the electrode. However, the true nature of the electrical properties of the SEI remains hitherto unclear due to the lack of a direct characterization method. Here we use in situ bias transmission electron microscopy to directly measure the electrical properties of SEIs formed on copper and lithium substrates. We reveal that SEIs show a voltage-dependent differential conductance. A higher rate of differential conductance induces a thicker SEI with an intricate topographic feature, leading to an inferior Coulombic efficiency and cycling stability in Li∣∣Cu and Li∣∣LiNi0.8Mn0.1Co0.1O2 cells. Our work provides insight into the targeted design of the SEI with desired characteristics towards better battery performance.

The Mississippi Embayment aquifer is one of the largest alluvial groundwater aquifers in the United States. It is being excessively used, located along the lower Mississippi River covering approximately 202,019 km2 (78,000 square miles). Annual average groundwater depletion in the aquifer has been estimated at 5.18 billion cubic meters (Gm3) (4.2 million acre-feet) in 1981–2000. However, since 2000, annual groundwater depletion has increased abruptly to 8 Gm3 (2001–2008). In recent years, multi-state efforts have been initiated to improve the Mississippi Embayment aquifer sustainability. One management strategy of interest for preserving groundwater resources is managed aquifer recharge (MAR). In this study, we evaluate the impact of different MAR scenarios on land and water use decisions and the overall groundwater system using an economic model able to assess profitability of crop and land use decisions coupled to the Mississippi Embayment Regional Aquifer Study (MERAS) hydrogeologic model. We run the coupled model for 60 years by considering the hydrologic conditions from the MERAS model for the years 2002–2007 and repeating them 10 times. We find MAR is not economically attractive when the water cost is greater than $0.05/m3. Groundwater storage is unlikely to improve when relying solely on MAR as groundwater management strategy but rather should be implemented jointly with other groundwater conservation policies.

In 2022, the authors presented the first stage of implementing a revised climate control strategy at the National Gallery of Victoria, monitoring collection object response in collaboration with the Getty Conservation Institute using acoustic emissions (AE) monitoring. The research and education, motivating factors, and interdepartmental alignment required for adopting the Bizot Green Protocol (BGP) were discussed, as well as the experimental design and set-up of the AE system on a large Flemish altarpiece in an active gallery. This second and concluding paper presents the results of the AE monitoring study along with energy used by the HVAC system for the gallery housing the AE monitoring study, during the transition from traditional environmental parameters through to broadened parameters as defined in the BGP. The project highlights the importance of understanding individual gallery and building behaviour as well as the HVAC system in place. In the case of the gallery housing the AE study, the implementation of BGP parameters resulted in smaller environmental fluctuations than expected. That HVAC energy efficiency could be improved with a relatively low impact on the gallery environment was an unexpected but welcome outcome. This case study describes some common challenges faced when considering such a change operationally, including resourcing and communication needs. Identifying points of resistance, framing problems clearly, and identifying common goals were essential to making progress. In this case, sustainability has compelled many stakeholders into alignment and enabled a shift in institutional culture. [ABSTRACT FROM AUTHOR]

Periods of large igneous province (LIP) magmatism have shaped Earth’s biological and climatic history, causing major climatic shifts and biological reorganizations. The vegetation response to LIP-induced perturbations may affect the efficiency of the carbon-climate regulation system and the post-LIP climate evolution. Using an eco-evolutionary vegetation model, we demonstrate here that the vegetation’s climate adaptation capacity, through biological evolution and geographic dispersal, is a major determinant of the severity and longevity of LIP-induced hyperthermals and can promote the emergence of a new climatic steady state. Proxy-based temperature reconstructions of the Permian-Triassic, Triassic-Jurassic, and Paleocene-Eocene hyperthermals match the modeled trajectories of bioclimatic disturbance and recovery. We conclude that biological vegetation dynamics shape the multimillion-year Earth system response to sudden carbon degassing and global warming episodes. [ABSTRACT FROM AUTHOR]

The article discusses Harvard University's decision to cancel its Stratospheric Controlled Perturbation Experiment (SCoPEx), the first proposed outdoor stratospheric aerosol injection experiment. Topics include the challenges and tensions faced in developing a governance framework for solar geoengineering, the complexities of societal engagement and communication in such research, and the need for standardized and proactive research governance to address these issues effectively.

Automotive air conditioning (ACC) system designers faced unique challenges in satisfying customer demands for efficient and comfortable operation across a broad temperature range. The AAC system's effective or fixed temperature setting makes this possible. Many climate control models, like the state flow switching controller in MATLAB control, must handle heating and cooling due to a single Simulink/environment software and frequently contain steady-state error (SSE). The present research proposes to design an automatic temperature control scheme and fuzzy logic control (FLC) for an automotive air-conditioned (AAC) system. In addition, it employs MATLAB Simulink/environment software to model the fuzzy control technique to analyze the AAC system's response. A simulation has been set up to evaluate the suggested system performance to match a selection of user-specified reference temperatures and compressor speeds. Compared with a PID-controlled AAC system, the proposed FLC-based system reduced the undershoot to only 2.30% from 33.30% respectively, and was robust, quicker, and better at controlling temperature. • Challenges in automotive air conditioning systems for designers were addressed. • An automatic temperature control scheme was proposed via fuzzy logic control. • Improved efficiency and comfort in the AAC system was achieved. • The proposed FLC-based system reduced the undershoot to 2.30% from 33.30%. • The FLC-based was more robust, quicker, and better at controlling temperature. [ABSTRACT FROM AUTHOR]

A microbial fuel cell (MFC) is a bioelectrochemical system that generates electrical energy using electroactive micro-organisms. These micro-organisms convert chemical energy found in substances like wastewater into electrical energy while simultaneously treating the wastewater. Thus, MFCs serve a dual purpose, generating energy and enhancing wastewater treatment processes. Due to the high construction costs of MFCs, there is an ongoing search for alternative solutions to improve their efficiency and reduce production costs. This study aimed to improvement of MFC operation and minimize MFC costs by using anode material derived from by-products. Therefore, the proton exchange membrane (PEM) was abandoned, and a stainless steel cathode and a carbon anode were used. To improve the cell's efficiency, a carbon fiber anode supplemented with activated coconut carbon (ACCcfA) was utilized. Micro-organisms were provided with molasses decoction (a by-product of yeast production) to supply the necessary nutrients for optimal functioning. For comparison, an anode made solely of carbon fibers (CFA) and an anode composed of activated carbon grains without carbon fibers (ACCgA) were also tested. The results indicated that the ACCcfA system achieved the highest cell voltage, power density, and COD reduction efficiency (compared to the CFA and ACCgA electrodes). Additionally, the study demonstrated that incorporating activated coconut carbon significantly enhances the performance of the MFC when powered by a by-product of yeast production. [ABSTRACT FROM AUTHOR]

Managing waste tires presents a significant challenge globally, particularly in regions experiencing high temperatures and shortage of landfill sites. This issue is affecting countries like Kuwait, where the abundance of waste tires is a major source of environmental and safety risks, particularly during the intensely hot summer months. This extreme heat has sparked numerous fires, leading to substantial air pollution due to thick black smoke. Given the limited disposal options, recycling waste tires and finding practical applications for ground tire rubber (GTR) is essential. To address the challenge, a comprehensive laboratory testing program was conducted, using locally produced rubber aggregates as an additive to Kuwait's local surface sands. Two new variables were examined namely the size and gradation of the GTR, and the density of the compacted mixes. For this purpose, two different sizes of rubber aggregates, fine and coarse produced locally, were utilized, and the impact of relative compaction on the strength and compressibility of the mixtures was investigated by testing samples compacted to the maximum density and to 95% of the maximum density. The results suggest that combining local surface sands with rubber tire additives results in a lighter, more permeable, and compressible material, contributing significantly to sustainable waste management. With 20% rubber additive the maximum dry density decreased by nearly 20%, and the permeability increased by 1.74–3.11 times and the compression index increased by 6.15 and 3.8 times with fine and coarse rubber respectively. The angle of friction remained unchanged at 36° with the addition of coarse rubber and decreased by 3°–4° with fine rubber. The change in behavior although not an increase in the strength and stiffness, offers a range of suitable practical applications in civil engineering and environmental management, including use as a drainage layer, embankment construction on soft ground, earth fill around retaining walls, an additive in asphalt mixes, and in manufacturing compressible tiles for sports facilities. [ABSTRACT FROM AUTHOR]

Because of the hazards associated with handling mercury, most standards organizations have withdrawn the conventional mercury (displacement) method (MM) for shrinkage limit (SL) determination of fine-grained soils. Despite attempts to substantiate the wax (coating) method (WM), which is presently the only standardized MM-testing alternative, the geotechnical community remains somewhat hesitant of its adoption in routine practice. To encourage more widespread use of WM-testing, this study re-examines the level of agreement between the MM- and WM-deduced SL parameters (i.e., SLMM and SLWM, respectively). This was achieved by performing comprehensive statistical analyses on the largest and most diverse database of its kind, to date, entailing SLMM:SLWM measurements for 168 different fine-grained soils having wide ranges of plasticity characteristics (i.e., liquid limit = 31.6–362.0%, plasticity index = 8.2–318.0% and SLMM = 7.1–42.0%). Furthermore, an attempt was made to evaluate the SLWM (in lieu of the SLMM) parameter for performing preliminary soil expansivity assessments using existing SLMM-based classification approaches. It was demonstrated that the MM and WM methods do not produce identical SL values for a given fine-grained soil under similar testing conditions, with their discrepancy being systematic and hence likely arising from the differences between the materials (mercury versus wax) and methodologies involved in performing these tests. New SLWM → SLMM conversion relationships were established, allowing SLMM to be deduced as a function of SLWM with high accuracy. Hence, when inputting SLWM in SLMM-based empirical correlations to predict other geoengineering design parameters, the newly proposed conversion relationships can be employed to minimize systematic prediction errors. It was also demonstrated that plasticity-based correlations, at best, can only provide a rough approximation of SLMM. Hence, when the SL is desired, WM-testing or any other alternative method that directly and reliably measures the soil shrinkage factors should be retained. Finally, the same soil-expansivity rankings, as obtained for existing classification systems employing SLMM results, are achieved using SLWM measurements (i.e., without the need of applying SLWM → SLMM conversion equations). [ABSTRACT FROM AUTHOR]