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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.

The United States’ greenhouse gas (GHG) emissions reduction goals, along with targets set by the International Maritime Organization, create an opportunity for battery electric shipping. In this study, we model life-cycle costs and GHG emissions from shipping electrification, leveraging ship activity datasets from across the United States in 2021. We estimate that retrofitting 6,323 domestic ships under 1,000 gross tonnage to battery electric vessels would reduce US domestic shipping GHG emissions by up to 73% by 2035 from 2022 levels. By 2035, electrifying up to 85% of these ships could become cost effective versus internal combustion engine ships if they cover 99% of annual trips and charge from a deeply decarbonized grid. We find that charging demands from electrifying these ships could be concentrated at just 20 of 150 major ports nationwide. This study demonstrates that retrofitting to battery electric vessels has economic potential and could significantly accelerate GHG emission reductions.

Co- and Ni-free disordered rocksalt cathodes utilize oxygen redox to increase the energy density of lithium-ion batteries, but it is challenging to achieve good cycle life at high voltages >4.5 V (versus Li/Li+). Here we report a family of Li-excess Mn-rich cathodes that integrates rocksalt- and polyanion-type structures. Following design rules for cation filling and ordering, we demonstrate the bulk incorporation of polyanion groups into the rocksalt lattice. This integration bridges the two primary families of lithium-ion battery cathodes—layered/spinel and phosphate oxides—dramatically enhancing the cycling stability of disordered rocksalt cathodes with 4.8 V upper cut-off voltage. The cathode exhibits high gravimetric energy densities above 1,100 Wh kg−1 and >70% retention over 100 cycles. This study opens up a broad compositional space for developing battery cathodes using earth-abundant elements such as Mn and Fe.

ABSTRACT: Disinfection byproducts (DBPs), residual compounds formed from the chemical disinfection of drinking water, can cause a host of damaging public health and environmental impacts. This study evaluates the landscape of regulations designed to reduce the occurrence and/or impact of DBPs, focusing on regulations issued by the US states. Drawing on a systematic search of state administrative codes and agency websites, we first identify the presence, absence, and layering of DBP-related regulations. We then evaluate the number and types of policy tools – the specific approaches required by each regulation, such as monitoring requirements, economic incentives, and required treatment technologies – to identify how DBPs are being managed and how states cluster with relatively more and less robust regulatory frameworks. Finally, we evaluate the relationship between the regulatory approach and the frequency of drinking water quality violations for DBP compounds. While most states have at least one DBP-specific regulation, these vary substantially in their comprehensiveness. The most-used policy tools (monitoring, compliance schedules, and reporting) directly reflect federal regulations; few states have adopted innovative tools such as collaboration or financial incentives. We observe no relationship between regulatory efforts and water quality violations, suggesting that current policy implementation may not adequately address the complex risk of DBPs.

A viscoplastic model for representing plastic silts and clays in geotechnical static slope stability applications is presented. The PM4SiltR model builds on the stress ratio-controlled, critical state-based, bounding surface plasticity model PM4Silt and is coded as a dynamic link library for use in the finite difference program FLAC 8.1. PM4SiltR incorporates strain rate-dependent shear strength, stress relaxation, and creep using a consistency approach combined with an internal strain rate and auto-decay process. The model does not include a cap, and as such cannot simulate strain rate-dependent consolidation under increasing overburden stress. Six parameters control the viscous response for PM4SiltR, while the parameters controlling the nonviscous components of the response are the same as for PM4Silt. Single element simulations are presented to illustrate the influence of viscoplasticity on the constitutive response in direct simple shear loading and undrained creep. Single element responses are shown to be consistent with observed experimental results. Simulations of a hypothetical tailings dam constructed using the upstream method are performed to illustrate use of PM4SiltR at field scale. Results of field-scale simulations show PM4SiltR can model undrained creep and progressive failure leading to delayed slope instability after relatively minor changes in loading conditions at field scale.

Abstract: Precipitation and temperature extremes from daily data indexed using the CLIMDEX methodology were calculated over the Central American region. The data comprises the coarsened versions of the Climate Hazards and Infrared Precipitation with stations (CHIRPs) and the corresponding data set for temperature (CHIRTs) from the year 1981 to 2020 and 1983 to 2016, respectively. The objective is to detect trend patterns in extremes in recent periods, use novel statistical techniques for assessing the trend significance and study the monthly and annual trends for each of the indices. Trends of extreme temperature indices show more consistent, robust and widespread significant results according with the observed warming of the region. Significant extreme precipitation indices trends are more localized, and therefore harder to analyse, but it seems that one robust result from several indices is the trend toward more intense extreme precipitation events in Costa Rica. The findings of this work suggest possible impacts in human and environmental systems across the region.

The over 15 million metric tonnes of carbon black produced annually emit carbon dioxide in the range of 29–79 million metric tonnes each year. With the renaissance of carbon black in many new renewable energy applications as well as the growing transportation sector, where carbon black is used as a rubber reinforcement agent in car tires, the carbon black market is expected to grow by 66% over the next 9 years. As such, it is important to better understand energy intensity and carbon dioxide emissions of carbon black production. In this work, the furnace black process is studied in detail using process models to provide insights into mass and energy balances, economics, and potential pathways for lowering the environmental impact of carbon black production. Current state-of-the-art carbon black facilities typically flare the tail gas of the carbon black reactor. While low in heating value, this tail gas contains considerable amounts of energy and flaring this tail gas leads to low overall efficiency (39.6%). The efficiency of the furnace black process can be improved if the tail gas is used to produce electricity. However, the high capital investment cost and increased operating costs make it difficult to operate electricity generation from the tail gas economically. Steam co-generation (together with electricity generation) on the other hand is shown to substantially improve energy efficiency as well as economics, provided that steam users are nearby. Steam co-generation can be achieved via back-pressure steam turbines so that the low-pressure exhaust steam (∼2 bar/120 °C) can be used locally for heating or drying purposes. Furthermore, the potential of utilizing hydrogen to reduce carbon dioxide emissions is investigated. Using hydrogen as fuel for the carbon black reactor instead of natural gas is shown to reduce the carbon dioxide footprint by 19%. However, current prices of hydrogen lead to a steep increase in the levelized cost of carbon black (47%).

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.

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.

Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases. [ABSTRACT FROM AUTHOR]

Wet tropical forests play an important role in the global carbon (C) cycle, but given current rates of land‐use change, nitrogen (N) and phosphorus (P) limitation could reduce productivity in regenerating forests in this biome. Whereas the strong controls of climate and parent material over forest recovery are well known, the influence of vegetation can be difficult to determine. We addressed species‐specific differences in plant traits and their relationships to ecosystem properties and processes, relevant to N and P supply to regenerating vegetation in experimental plantations in a single site in lowland wet forest in Costa Rica. Single‐tree species were planted in a randomized block design, such that climate, soil (an Oxisol), and land‐use history were similar for all species. In years 15–25 of the experiment, we measured traits regarding N and P acquisition and use in four native, broad‐leaved, evergreen tree species, including differential effects on soil pH, in conjunction with biomass and soil stocks and fluxes of N and P. Carbon biomass stocks increased significantly with increasing soil pH (p = 0.0184, previously reported) as did biomass P stocks (p = 0.0011). Despite large soil N pools, biomass P stocks were weakly dependent on traits associated with N acquisition and use (N2 fixation and leaf C:N, p < 0.09). Mass‐balance budgets indicated that soil organic matter (SOM) could supply the N and P accumulated in biomass via the process of SOM mineralization. Secondary soil P pools were weakly correlated with biomass C and P stocks (R = 0.47, p = 0.08) and were large enough to have supplied sufficient P in these rapidly growing plantations, suggesting that alteration of soil pH provided a mechanism for liberation of soil P occluded in organo‐mineral soil complexes and thus supply P for plant uptake. These results highlight the importance of considering species' effect on soil pH for restoration projects in highly weathered soils. This study demonstrates mechanisms by which individual species can alter P availability, and thus productivity and C cycling in regenerating humid tropical forests, and the importance of including traits into global models of element cycling. [ABSTRACT FROM AUTHOR]

In the majority of nations, environmental sustainability is an integral aspect of government policies, highlighting the criticality of equipping upcoming engineers with the necessary environmental awareness and skills to tackle this complex challenge. Higher education institutions assume a pivotal role in fulfilling this mission as their engineering programs aspire to generate graduates who possess the necessary competencies to effectively operate as "sustainable" engineers. Novel pedagogical methodologies, such as service learning, are currently being utilized to foster the cultivation of sustainable development values. Service-Learning represents a highly congruent approach to achieving Sustainable Development Goal (SDG) 4, insofar as it seamlessly integrates educational curricula with relevant community issues. As a result, it effectively contributes to the advancement of education for a sustainable future. This investigation sought to assess the impact of service learning projects developed in a rural school community on the boosting of social skills and environmental values among engineering students. The empirical evidence suggests that Service-Learning initiatives centered on environmental issues are efficacious in promoting the acquisition of social and environmental values among students. This, in turn, results in a positive transformation of their skill sets. Significantly, a substantial proportion of environmental engineering students who previously demonstrated a low awareness of these skills acknowledged their acquisition upon completion of the Service-Learning projects. Moreover, no less than 75% of the participants endorsed the attainment of each of the 11 competencies evaluated. [ABSTRACT FROM AUTHOR]

Focusing on 'Geographies of Knowledge', this Commentary explores interactions between knowledge about climate change and the evolving multi‐level governance of climate. Three vignettes illustrate the complexity of this relationship. The first shows how expert advice, combined with other factors, persuaded the UK government to adopt an ambitious, long‐term emissions reduction target in the early 2000s. The second considers the '2°C target' (latterly 1.5°C) to limit rises in global mean temperature, variously seen as essential, unachievable or symbolic. The third turns to geoengineering and its governance. All three demonstrate the significance of epistemic, political and discursive factors, as these intertwine and play out across different sites, scales and levels of governance. Focusing on 'Geographies of Knowledge', this Commentary explores interactions between knowledge about climate change and the evolving multi‐level governance of climate. [ABSTRACT FROM AUTHOR]

Rock hardness and abrasivity are among the most crucial properties that can significantly impact the interaction between rocks and mechanical tools in different parts of geoengineering projects. Accurate estimation of these properties is essential for a better understanding and optimization of geoengineering operations. Hence, the main aim of this study was to develop different machine learning (ML) models based on the geochemical measurements for predicting rock hardness and abrasivity. To do this, 159 rock samples were collected from a gold mine, and portable X-ray fluorescence spectrometry (pXRF), Leeb rebound hardness (LRH), and Cerchar abrasivity index (CAI) tests were performed on the collected rock samples. Three different ML algorithms, including random forest regressor (RFR), support vector regression, and gradient boosting regressor, were applied to develop predictive models for LRH and CAI separately. Considering the fact that the geochemical data are of the compositional type, two scenarios were followed: developing predictive models based on the original data obtained from the pXRF and the centered log-ratio (Clr) transformed data, resulting in the development of six predictive models for LRH and CAI. The performance assessment of the developed predictive models showed that RFR models outperformed the other two ML algorithms in predicting LRH and CAI. In addition, the developed models based on the original data demonstrated a better performance in both cases of LRH and CAI than the trained model based on Clr data. The result indicates that integrated pXRF measurements and RFR technique have strong potential to be used for practical and efficient rock materials characterization during exploration and extraction processes. [ABSTRACT FROM AUTHOR]

A study published in Environmental Science & Technology and Environmental Toxicology and Chemistry examined the effects of low levels of water contamination on fish behavior, growth, and survival. The research team, led by Cheryl Murphy from Michigan State University, found that even fish populations that had evolved tolerance to contaminants still showed gene expression changes and altered behavior when exposed to pollutants. The study highlights the importance of understanding how contaminants impact fish populations and the need for ecological risk assessments to protect aquatic ecosystems. Additionally, the US EPA awarded research funding to five universities for innovative technologies addressing environmental and public health challenges, such as PFAS removal and stormwater remediation. [Extracted from the article]

According to reports from the scientific, public health and medical communities around the world, the quality of ambient and indoor air has a significant impact on the health of the population. Maintaining adequate indoor air quality in accordance with the standards set by the European Union and the WHO guarantees a reduction in the risk of many diseases and improved work capacity. It is extremely important to assess the air quality in schools. This is because during adolescence, the body undergoes significant development, making it particularly susceptible to harmful factors. The purpose of this study was to assess the indoor air quality based on physical, chemical and particulate pollutants present in the air in classrooms at an elementary school. The measurement was carried out using an IAQmeter, designed and manufactured by employees of the Faculty of Environmental Engineering at Lublin University of Technology, which allows continuous measurement and recording of temperature, humidity, CO2, SO2, NO2, VOCs (volatile organic compounds), formaldehyde, PM 2.5, and PM 10. The study was conducted for grades IIII, where students go out only at break and continue in the same room throughout the day. In addition, the factors that can affect the concentration of pollutants, such as ventilation or prolonged opening of doors, were monitored. Sensors were placed in the classroom and in the corridor nearby classroom. The study showed that while spending time at school, students are exposed to a number of factors that can affect their well-being and health, which is best illustrated by the CO2 concentrations. The results of the study show that for more than 90% of the time spent at school, children are in indoor environments where the carbon dioxide concentrations exceed 1000 ppm. It was also shown that the indoor environment in corridors is of lower quality than the environment in classrooms. The designed device enabled rapid measurement, recording a wide range of pollutants. [ABSTRACT FROM AUTHOR]

This study addresses a gap in municipal leachate (MUPL) treatment by introducing a pioneering application of artificial intelligence (AI) in the electrocoagulation/electroflocculation (EC/EF) process utilizing iron electrodes. The overarching aim is to demonstrate the efficacy of AI, particularly a multi-layer perceptron (MLP)-based feed-forward artificial neural network (ANN) incorporating the Levenberg-Marquardt (LMb) algorithm, in predicting and optimizing EC/EF outcomes for turbidity (TDY) removal. The research methodology involved experimentation and robust ANN data modeling. The significance of this work emerges from the successful integration of AI, showcasing its potential in advancing wastewater, demonstrated through a strong positive correlation (0.994) between the ANN model predictions and experimental outcomes. The study achieves a remarkable 99.4% TDY removal at an electrolysis time of 10 min and contributes valuable insights into the critical parameters influencing the EC/EF process. Results from the ANN modeling exhibit high predictive accuracy, supported by elevated R-squared values and minimal mean square error. Statistical analyses underscore the significance of key process parameters, highlighting the influential roles of current intensity and settling time. The study emphasized the favourable impact of maintaining an acidic pH range, as it reduced electrostatic repulsion between particles, facilitating pollutant agglomeration, and identified electrolysis time as a key factor in enhancing treatment efficiency, supported by a strong positive correlation between electrolysis time and TDY reduction. Energy cost savings were realized by not requiring temperature elevation. Achieving a 99.4% TDY removal translates to substantial reductions in other pollutants present in the MUPL, thereby elevating water quality and ensuring compliance. [ABSTRACT FROM AUTHOR]

This article focuses on the challenges of modeling energy supply systems for buildings, encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings. Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material, such as for thermal upgrades, which consequently incurs additional economic costs. It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions, considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in buildings. In addition, it explores the methods and mechanisms for modeling the operating modes of electric boilers used to collectively improve energy efficiency and indoor climatic conditions. Using the developed mathematical models, the study examines the dynamic states of building energy supply systems and provides recommendations for improving their efficiency. These dynamic models are executed in software environments such as MATLAB/Simscape and Python, where the component detailing schemes for various types of controllers are demonstrated. Additionally, controllers based on reinforcement learning (RL) displayed more adaptive load level management. These RL-based controllers can lower instantaneous power usage by up to 35%, reduce absolute deviations from a comfortable temperature nearly by half, and cut down energy consumption by approximately 1% while maintaining comfort. When the energy source produces a constant energy amount, the RL-based heat controller more effectively maintains the temperature within the set range, preventing overheating. In conclusion, the introduced energy-dynamic building model and its software implementation offer a versatile tool for researchers, enabling the simulation of various energy supply systems to achieve optimal energy efficiency and indoor climate control in buildings. [ABSTRACT FROM AUTHOR]

Soils support a highly diverse community of plant pathogens, which are highly responsive to global change. Climate and livestock grazing are the main global changes in grasslands, yet, how long-term grazing alone, and in interaction with climate, influence the distribution of soil-borne plant pathogens remain virtually unknown. Here, we present the first long-term regional-scale experimental investigation on the impacts of livestock grazing on soil-borne fungal plant pathogens and their association with plant community across 10 experimental sites spanning a climate gradient in the steppe in Northern China. Our results showed that long-term grazing effects on the diversity and proportion of soil-borne fungal plant pathogens are strongly controlled by temperature, with grazing increasing pathogen richness and proportions largely in cooler grasslands. We further show that long-term grazing supported stronger connections between soil-borne fungal pathogens and plant communities. Our work demonstrates that climate controls the effects of grazing on plant pathogens, which is critical to understand and manage grasslands in a changing world. Long-term effects of grazing on soil-borne fungal plant pathogens are strongly controlled by temperature, posing greater potential threats to plant pathogen infections in cooler grasslands. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach using Clustered Artificial Neural Networks (CLANN) to address the challenge of developing predictive models for multimodal dataset with extreme parameter values. The CLANN method strategically decomposes the dataset, derived from Finite Element Analysis (FEA), into clusters, each representing distinct diffusion behaviors, and applies specialized neural networks within these clusters. The CLANN model was rigorously evaluated and demonstrated superior accuracy and consistency compared to traditional methods such as the Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy expert systems. While these conventional models struggled to capture the full range of diffusion dynamics, particularly under extreme conditions, CLANN consistently provided predictions that closely aligned with the actual FEA data across all scenarios. The versatility of the CLANN approach extends beyond its application to soil contamination. Its ability to handle complex, multimodal datasets suggests that this methodology can be generalized to a wide range of scientific and engineering problems characterized by similar data structures. This makes CLANN not only a powerful tool for geotechnical engineers but also a promising framework for broader applications where traditional models fall short. The findings of this study pave the way for more accurate, reliable, and adaptable predictive modeling in diverse domains, enhancing our ability to manage and mitigate environmental and engineering challenges. [ABSTRACT FROM AUTHOR]

AbstractThe efficient removal of pollutants from aqueous systems remains a significant challenge in environmental science and engineering, particularly when dealing with hazardous dyes commonly found in industrial wastewater. Our research described in this paper investigated the adsorption of the dye, Eriochrome Black T (EBT), a synthetic azo dye widely used in various industries, onto charged macrospheres based on polyglycidyl methacrylate-graft-polyvinyl chloride (P1). The macrospheres were prepared using the synthesized graft copolymer P1 by the phase inversion method and functionalized by quaternary hydrazine to introduce charged groups on the surface of these macrospheres, enhancing their affinity for the anionic EBT dye. The effects of initial dye concentration, contact time and temperature on the adsorption process were evaluated. Furthermore, adsorption isotherms and kinetic models were applied to elucidate the mechanism of this adsorption process. The results demonstrated that the experimental data of the adsorption process was well-fitted by the Langmuir model isotherm and the charged macrospheres exhibited excellent adsorption capacity for EBT. In the thermodynamic study the adsorption process was found to be exothermic and spontaneous at room temperature. Besides, the kinetics study revealed that the adsorption process was better described by the pseudo-second-order model (R2= 0.992) than the pseudo-first-order model (R2= 0.963), suggesting that chemisorption was the adsorption process. The mechanism of this adsorption was mainly based on electrostatic interactions and hydrogen bonding between the adsorbent and the adsorbate. [ABSTRACT FROM AUTHOR]

Terrestrial processes influence the atmosphere by controlling land‐to‐atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model version 2 under preindustrial conditions. We find that an observationally‐informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (σ = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagate to the entire Earth system, and provides insights into where and how land process uncertainty influences climate. Plain Language Summary: Land processes can affect climate by controlling the transfer of energy and water from the land to the atmosphere. Previous research has shown that uncertainty surrounding land processes (e.g., photosynthesis and the movement of water through soils) can drive uncertainty in land‐to‐atmosphere fluxes. However, it remains unclear how much that land uncertainty can impact climate. Here, we quantify how climate is sensitive to assumptions about land processes by varying 18 land model parameters to create an ensemble of 36 possible worlds in a global climate model. Land temperature ranges by 2.2°C across this ensemble, mostly due to changes in how much water is evaporated from the land surface. Changing land parameters also drives regionally variable changes in mean precipitation. This study highlights a large and underappreciated impact of land processes in determining the mean climate state, and provides insights into how climate is influenced by land process uncertainty. Key Points: Land processes substantially impact the climatological mean state terrestrial temperature and precipitationLand parameters influence climate predominantly through changing evapotranspiration rather than through other mechanismsWarming driven by land processes activates different atmospheric feedbacks than radiatively‐driven warming [ABSTRACT FROM AUTHOR]

The manufacturing process for membrane electrode assemblies (MEAs), from coating to stack assembly, is typically performed under climate-controlled conditions due to the hygroscopic properties of catalyst-coated membranes (CCMs). Large climate-controlled areas in the assembly line not only increase the energy consumption but also limit the scalability of the production line. In this study, experiments were conducted to analyze the effects of ambient humidity on the mechanical properties of a CCM. The hygroscopic swelling behavior of a commercial CCM with an ePTFE-reinforced membrane was also characterized. Using the finite element method, a 3D numerical model covering the entire MEA assembly process was developed, allowing for a numerical investigation of different climate control strategies. The influence of ambient humidity on the dimensional changes in the CCM, which leads to significant stress on the CCM due to mechanical constraints and thus to deformation of the MEA product, was simulated and validated experimentally using optical measurements. Finally, the critical steps during MEA assembly were identified, and a recommendation for the optimal humidity range for climate control was derived. [ABSTRACT FROM AUTHOR]

Superfine cement is widely used in building reinforcement and repair, special concrete manufacturing, and environmental protection engineering due to its high toughness, high durability, good bonding strength, and environmental friendliness. However, there are some problems in superfine cement slurry, such as high bleeding rate, prolonged setting time, and consolidated body volume retraction. In this article, on the premise of using the excellent injectability of superfine cement slurry, the fluidity, setting time, reinforcement strength, and volume expansion rate of novel expansive superfine cement slurries with varying proportions were analyzed by adding expansion agent UEA, naphthalene-based water reducer FDN-C, and triisopropanolamine accelerating agent TIPA. The results show that under most mix ratios, the bleeding rate and fluidity of the novel superfine cement slurry initially increase and decrease with rising water-reducing agent dosage. The initial setting time generally decreases with accelerating agent dosage, reaching a minimum value of 506 min, representing a 33.68% reduction compared to the benchmark group (traditional superfine cement). Under normal conditions, the compressive strength of the net slurry consolidation body is positively correlated with expansion agent dosage, achieving maximum strengths of 8.11 MPa at three days and 6.93 MPa at 28 days; these values are respectively higher by 6.7 MPa and 2.6 MPa compared to those in the benchmark group. On the seventh day, the volume expansion rate of the traditional superfine cement solidified sand body ranges from −0.19% to −0.1%, while that for the corresponding body formed from the novel superfine cement is between 0.41% and 1.33%, representing a difference of 0.6–1.43%. After the on-site treatment of water and sand-gushing strata, the core monitor rate of the inspection hole exceeds 70%. The permeability coefficient of the stratum decreases to a range between 1.47 × 10−6 and 8.14 × 10−6 cm/s, resulting in nearly a thousandfold increase in stratum impermeability compared to its original state. Hence, the findings of this research hold practical importance for the future application of such materials in the development of stratum reinforcement or building repair. [ABSTRACT FROM AUTHOR]

Due to the ubiquity of textiles in the lives, electronic textiles (E‐textiles) have emerged as a future technology capable of addressing a myriad of challenges from mixed reality interfaces, on‐garment climate control, patient diagnostics, and interactive athletic wear. However, providing sufficient electrical power in a textile form factor has remained elusive. To address this issue, different approaches are discussed, starting with supercapacitors' advantages and limitations and material choices for textile‐based supercapacitors before discussing proper data analysis and design considerations of textile‐based energy storage to power wearable electronics. [ABSTRACT FROM AUTHOR]

[Display omitted] With the rapid development of the global economy and the continuous consumption of fossil resources, sustainable and biodegradable natural biomass has garnered extensive attention as a promising substitute for synthetic polymers. Due to their hierarchical and nanoscale structures, natural biopolymers exhibit remarkable mechanical properties, along with excellent innate biocompatibility and biodegradability, demonstrating significant potential in various application scenarios. Among these biopolymers, proteins and polysaccharides are the most commonly studied due to their low cost, abundance, and ease of use. However, the direct processing/conversion of proteins and polysaccharides into their final products has been a long-standing challenge due to their natural morphology and compositions. In this review, we emphasize the importance of processing natural biopolymers into high-value-added products through sustainable and cost-effective methods. We begin with the extraction of four types of natural biopolymers: cellulose, chitosan, eggshell membrane, and silk fibroin. The processing and post-functionalization strategies for these natural biopolymers are then highlighted. Alongside their unique structures, the versatile potential applications of these processable natural biopolymers in biomedical engineering, biosensors, environmental engineering, and energy applications are illustrated. Finally, we provide a summary and future outlook on processable natural biopolymers, underscoring the significance of converting natural biopolymers into valuable biomaterial platforms. [ABSTRACT FROM AUTHOR]

Aerosols are microscopic liquid or solid particles that enter the atmosphere through natural and man-made processes. Time series trends and correlations of aerosol optical depth and cloud parameters over Addis Ababa have become the subject of scientific research because of the importance of clouds in controlling climate. In this study, we have examined the temporal variations (time series analysis) in aerosol particles over Addis Ababa and the impact of these variations on various optical properties of clouds using Moderate Resolution Imaging Spectroradiometer (MODIS) data from January 2003 to December 2018. The maximum aerosol optical depth (AOD) was found during the summer period, with minimum values in winter. During summer, the air temperature is high, which leads to abundant atmospheric water vapor, facilitating the hygroscopic growth of aerosols. We then analyzed the relationships between AOD and other cloud parameters, namely, water vapor (WV), cloud fraction (CF), cloud top temperature (CTT), and cloud top pressure (CTP), to provide a better understanding of aerosol–cloud interactions. The correlation between AOD and CF and WV was positive for Addis Ababa, while there was a negative correlation with CTT and CTP. [ABSTRACT FROM AUTHOR]

The rapid expansion of industrialization has resulted in the release of multiple ecological contaminants in gaseous, liquid, and solid forms, which pose significant environmental risks to many different ecosystems. The efficient and cost‐effective removal of these environmental pollutants has attracted global attention. This growing concern has prompted the synthesis and optimization of nanomaterials and their application as potential pollutant removal. In this context, MXene is considered an outstanding photocatalytic candidate due to its unique physicochemical and mechanical properties, which include high specific surface area, physiological compatibility, and robust electrodynamics. This review highlights recent advances in shaping titanium carbide (Ti3C2Tx) MXenes, emphasizing the importance of termination groups to boost photoactivity and product selectivity, with a primary focus on engineering aspects. First, a broad overview of Ti3C2Tx MXene is provided, delving into its catalytic properties and the formation of surface termination groups to establish a comprehensive understanding of its fundamental catalytic structure. Subsequently, the effects of engineering the morphology of Ti3C2Tx MXene into different structures, such as two‐dimensional (2D) accordion‐like forms, monolayers, hierarchies, quantum dots, and nanotubes. Finally, a concise overview of the removal of different environmental pollutants is presented, and the forthcoming challenges, along with their prospective outlooks, are delineated. [ABSTRACT FROM AUTHOR]

With buildings representing a substantial portion of global energy consumption, exploring alternatives to traditional fossil fuel-based heating and cooling systems is critical. Thermoelectricity offers a promising solution by converting temperature differentials into electrical voltage or vice versa, enabling efficient indoor thermal regulation. This paper presents a comprehensive investigation into the integration of thermoelectric wall systems for sustainable building climate control through numerical simulations and experimental analyses. Numerical simulations using computational fluid dynamics (CFD) techniques were conducted to model fluid flow and heat transfer within the thermoelectric wall systems under various operating conditions. These simulations provided insights into the system's thermal behavior, which were validated through experimental setups designed to measure temperature differentials, airflow rates, and power consumption. The results showed that power consumption is directly correlated with electrical current, ranging from 0.19 W to 77.4 W as the current increased from 0.1 A to 2 A. Additionally, the heat absorbed by the system increased significantly with electrical current, by 706–1044%, depending on the air velocity. The thermal energy released from the hot side of the thermoelectric modules also rose substantially, ranging from 9850 to 5285% with increasing electrical current, and from 275 to 51% with higher air velocities. Moreover, increasing air velocity led to a 6.78–9.37% reduction in power consumption for currents between 0.1 A and 2 A. The coefficient of performance (COP) analysis revealed that optimizing both electrical current and air velocity is essential for maximizing system efficiency. While fan power consumption reduces COP at higher air velocities, neglecting fan power consumption results in COP improvements ranging from 6.5 × 10⁻⁴ to 49.0%. These findings highlight the potential of thermoelectric wall systems to enhance indoor comfort and energy efficiency in buildings. [ABSTRACT FROM AUTHOR]

Marine phytoplankton are fundamental to Earth's ecology and biogeochemistry. Our understanding of the large-scale dynamics of phytoplankton biomass has greatly benefited from, and is largely based on, satellite ocean color observations from which chlorophyll-a (Chla), a commonly used proxy for carbon biomass, can be estimated. However, ocean color satellites only measure a small portion of the surface ocean, meaning that subsurface phytoplankton biomass is not directly monitored. Chla is also an imperfect proxy for carbon biomass because cellular physiology drives large variations in their ratio. The global network of Biogeochemical (BGC)-Argo floats now makes it possible to complement satellite observations by addressing both these issues at once. In our study, we use ~100,000 water-column profiles from BGC-Argo to describe Earth's phytoplankton carbon biomass and its spatiotemporal variability. We estimate the global stock of open ocean phytoplankton biomass at ~314 Tg C, half of which is present at depths not accessible through satellite detection. We also compare the seasonal cycles of carbon biomass stocks and surface Chla visible from space and find that surface Chla does not accurately identify the timing of the peak annual biomass in two-thirds of the ocean. Our study is a demonstration of global-scale, depth-resolved monitoring of Earth's phytoplankton, which will be crucial for understanding future climate-related changes and the effects of geoengineering interventions if implemented. [ABSTRACT FROM AUTHOR]

Renowned for its organic richness, unconventional shale presents both unique challenges and opportunities for hydrocarbon extraction and various geo-engineering applications, owing to its complex storage, flow, and stimulation properties. It is essential, from a multidisciplinary perspective, to characterize the rock physics response and construct rock physics model for unconventional shale reservoirs. A maturity-constrained rock physics modeling method for shales, in conjunction with geochemical analyses, is proposed, employing the stepwise homogenization method to quantify the scale-dependent elastic and anisotropic behavior of laminated shales. Considering the complex pore structure of shale, combined with the microscale effects of fluid transport, various forces, and microfracture features, the multiphase fluid flow behavior can be accurately characterized. Then, from the perspective of fracturing performance, it is necessary to develop a new fracability evaluation model for unconventional shale reservoirs. This model integrates fracture mechanics theory, the elastic and mechanical properties of rocks, fracturing operations, reservoir geological characteristics, and in-situ stress to thoroughly evaluate fracability. Unconventional petrophysicists must move beyond traditional hydrocarbon evaluation to embrace interdisciplinary approaches, which requires comprehensive understanding and characterization of the storage, flow, and stimulation capacities, thereby optimizing development strategies and maximize resource utilization. [ABSTRACT FROM AUTHOR]

Stress tolerance is a vital attribute for all living beings to cope with environmental adversities. IrrE (also named PprI) from Deinococcus radiodurans enhances resistance to extreme radiation stress by functioning as a global regulator, mediating the transcription of genes involved in deoxyribonucleic acid (DNA) damage response (DDR). The expression of IrrE augmented the resilience of various species to heat, radiation, oxidation, osmotic stresses and inhibitors, encompassing bacterial, fungal, plant, and mammalian cells. Moreover, IrrE was employed in a global regulator engineering strategy to broaden its applications in stress tolerance. The regulatory impacts of heterologously expressed IrrE have been investigated at the molecular and systems level, including the regulation of genes, proteins, modules, or pathways involved in DNA repair, detoxification proteins, protective molecules, native regulators and other aspects. In this review, we discuss the regulatory role and mechanism of IrrE in the antiradiation response of D. radiodurans. Furthermore, the applications and regulatory effects of heterologous expression of IrrE to enhance abiotic stress tolerance are summarized in particular. [ABSTRACT FROM AUTHOR]

Under in-situ conditions, natural hydraulic fractures (NHF) can occur in permeable rock structures as a result of a rapid decrease of pore water accompanied by a local pressure regression. Obviously, these phenomena are of great interest for the geo-engineering community, as for instance in the framework of mining technologies. Compared to induced hydraulic fractures, NHF do not evolve under an increasing pore pressure resulting from pressing a fracking fluid in the underground but occur and evolve under local pore-pressure reductions resulting in tensile stresses in the rock material. The present contribution concerns the question under what quantitative circumstances NHF emerge and evolve. By this means, the novelty of this article results from the combination of numerical investigations based on the Theory of Porous Media with a tailored experimental protocol applied to saturated porous sandstone cylinders. The numerical investigations include both pre-existing and evolving fractures described by use of an embedded phase-field fracture model. Based on this procedure, representative mechanical and hydraulic loading scenarios are simulated that are in line with experimental investigations on low-permeable sandstone cylinders accomplished in the Porous Media Lab of the University of Stuttgart. The values of two parameters, the hydraulic conductivity of the sandstone and the critical energy release rate of the fracture model, have turned out essential for the occurrence of tensile fractures in the sandstone cores, where the latter is quantitatively estimated by a comparison of experimental and numerical results. This parameter can be taken as reference for further studies of in-situ NHF phenomena and experimental results. [ABSTRACT FROM AUTHOR]

This paper presents a study of the hydraulic response of an infinite unsaturated slope exposed to a perturbation of the ordinary seasonal climatic cycle. The ground flow is modelled via a simplified one-dimensional finite difference scheme by decomposing the two-dimensional slope seepage into antisymmetric and symmetric parts. The numerical scheme incorporates two distinct hysteretic and non-hysteretic soil water retention laws, whose parameters have been selected after a preliminary sensitivity analysis. Results indicate that, in the hysteretic case, the "memory" of the perturbation takes a long time to fade, and the ordinary soil saturation cycle is only restored after several years of normal weather. Instead, in the non-hysteretic case, the recovery of the ordinary saturation regime is almost immediate after the perturbation. In contrast with the markedly different predictions of degree of saturation, both hysteretic and non-hysteretic slope models predict virtually identical evolutions of negative pore water pressures, with an almost immediate restoration of the ordinary cycle after the perturbation. [ABSTRACT FROM AUTHOR]

Ecotones are the transition zones between ecosystems and can exhibit steep gradients in ecosystem properties controlling flows of energy and organisms between them. Ecotones are understood to be sensitive to climate and environmental changes, but the potential for spatiotemporal dynamics of ecotones to act as indicators of such changes is limited by methodological and logistical constraints. Here, we use a novel combination of satellite remote sensing and analyses of spatial synchrony to identify the tropical dry forest–rainforest ecotone in Area de Conservación Guanacaste, Costa Rica. We further examine how climate and topography influence the spatiotemporal dynamics of the ecotone, showing that ecotone is most prevalent at mid‐elevations where the topography leads to moisture accumulation and that climatic moisture availability influences up and downslope interannual variation in ecotone location. We found some evidence for long‐term (22 year) trends toward upslope or downslope ecotone shifts, but stronger evidence that regional climate mediates topographic controls on ecotone properties. Our findings suggest the ecotone boundary on the dry forest side may be less resilient to future precipitation reductions and that if drought frequency increases, ecotone reductions are more likely to occur along the dry forest boundary. [ABSTRACT FROM AUTHOR]

The present study uses the Jiweishan landslide in Wulong District, Chongqing City, China, as an example to design a numerical simulation technique to examine two environmental consequences: corrosion deterioration and underground mining. A shear strength prediction model for the corrosion rate of the structural plane was thus proposed by mimicking the time-dependent weakening characteristics of structural planes by using strength reduction. The discrete element simulation method was applied to reproduce the complete process of dangerous rock body movement and slope instability under the effects of these two factors to clarify the influence of environmental and engineering effects on slope deformation behaviour. This was intended to clarify the overburden movement process, fracture evolution law, and rock formation subsidence characteristics of karst mountains affected by mining from the perspective of geomechanics, and the results showed that the deformation evolution process of the Jiweishan landslide can be divided into two stages: the slow chronic deformation caused by long-term corrosion deterioration and the more severe acute deformation caused by short-term underground mining. The overburden movement and fracture evolution seen under corrosion deterioration and underground mining thus represent a progressive evolutionary process with full spatial and temporal continuity. Corrosion is a long-term synchronous process that creates the transformation of numerous structural planes around a dangerous rock body. Underground mining, in contrast, is typically a short-term trigger factor that can nevertheless easily cause significant differential adjustment of the movement characteristics of different parts of a dangerous rock body that result in distinct spatial differentiations of dangerous rock body movement. Further, the subsidence deformation characteristics of the rock formation plane mainly depend on the spatial position and scale of the goaf created by such mining. Analysing the stress characteristics of the relevant inclined rock strata helps clarify the control mechanism of a mountain's spatial structure's adaptive adjustment. The simulation results in this case were also compared with the results of centrifuge tests and physical model tests to verify the rationality of the simulation scheme, and the conclusions thus remove provide an important reference for the study of landslide development processes and instability mechanisms under multi-factor coupling conditions. [ABSTRACT FROM AUTHOR]

The social progress, economic growth, and meteoric urbanization prompt the exploitation of available resources triggering the contagion of the biological and physical elements of the atmosphere irrationally causing global environmental pollution. Environmental contamination monitoring is a dire necessity. Although a number of technologies find mention in the literature for environmental remediation, however, environmental catalysis is an advanced steadily growing technique for pollution abatement. In this dimension, ceramic materials have turned heads due to their wide‐scale application areas. Hitherto, research is being done on advanced ceramics to fabricate novel modules for energy storage applications, in designing green buildings, pollution rheostats, and environmental engineering. This article deals with the abatement of environmental contaminants by adopting various methodologies such as aerobic and anaerobic biological treatments, adsorption, chemical oxidation, membrane separation, photocatalysis, ozonation using the ceramic as precursor materials. The ceramic membranes are cost‐effective, ecofriendly, efficacious, and green approach to obliterate toxins and harmful gases released in environment. Even though, limited literature is available on the abolition of harmful contaminants from air and soil using ceramic materials, an attempt has been made to present currently available data with best of our knowledge. This article will sensitize researchers to refabricate novel materials for environment sustainability. [ABSTRACT FROM AUTHOR]

Evaporative cooling systems have gained increasing attention as an energy-efficient solution for climate control in hot and dry regions. This review aims to assess the effectiveness of the most recent advancements in evaporative cooling technologies for building applications in hot and dry climates. The review focuses on global literature, with an emphasis on building applications. The findings of this review indicate that evaporative cooling systems with hybrid configurations, particularly multi-stage systems, can achieve cooling efficiencies of up to 95%. These systems are highly energy-efficient, with energy consumption ranging from 0.3 to 1.2 kW/t, with hybrid and multi-stage designs showing the best performance. Direct and indirect evaporative cooling systems also perform well, with cooling effectiveness ranging from 60% to 85%. Their reliance on water, rather than harmful refrigerants, results in minimal environmental impact, making them an eco-friendly alternative to traditional cooling methods. The coefficient of performance (COP) for these systems is favorable, with hybrid and multi-stage designs reaching COP values as high as 35, indicating substantial cooling output relative to energy input. In addition, the performance of evaporative cooling systems is highly influenced by their design parameters and operating conditions. Advanced designs that incorporate multi-stage cooling and effective water management tend to provide enhanced cooling capacity and energy efficiency. Therefore, evaporative cooling systems are an excellent option for sustainable building practices, contributing significantly to energy savings and reduced environmental impact. [ABSTRACT FROM AUTHOR]

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This study investigates the enhancement of mechanical and thermal properties of carbon fiber reinforced epoxy composites by incorporating zinc oxide (ZnO) nanofillers. The composites were developed by adding 3–15 g of ZnO nanoparticles into the epoxy matrix and were evaluated through experimental testing. The results showed significant improvements in mechanical performance, with the maximum tensile strength of 112.49 MPa and flexural strength of 114.82 MPa at the 15 g ZnO concentration. SEM analysis revealed a reduction in void content and improved fiber-matrix adhesion, enhancing load transfer. Thermal conductivity is 13.47 W/mK, while the coefficient of linear thermal expansion is 9.29 × 10−5/°C, indicating superior thermal stability. TGA analysis demonstrated a shift in decomposition temperature from 310 to 375 °C, confirming enhanced thermal stability. These results highlight the positive influence of ZnO nanofillers on both the mechanical and thermal properties of carbon fiber reinforced epoxy composites, making them more suitable for advanced structural applications.Article highlights: Alkaline treatment technique is employed to enhance the fibre properties. ZnO filler improved the thermal stability at degradation temperatures. Proposed composite is suited for structural applications. [ABSTRACT FROM AUTHOR]

Climate change control requires more land to increase ecosystem carbon sequestration. With the high-intensity development of mineral resources in past decades, massive mining areas have been generated worldwide. However, few studies have evaluated the carbon sequestration of these mining areas. In this study, we analyzed the net ecosystem productivity (NEP) changes and calculated the NEP losses in global terrestrial mining areas. We adopted the random forest model to evaluate the NEP recovery potential and its driving factors. The key findings are that (1) the NEP of global mining areas exhibited a relatively obvious decreasing trend from 2000 to 2020, with an overall reduction of 29.1% and a maximum decline of 35.7%. By 2020, the NEP loss in mining areas was 11.9 g C m−2 year−1, and the total loss reached 576.9 Gg C year−1. (2) Global mining areas demonstrate significant NEP recovery potential, with an average of 12.0 g C m−2 year−1. Notably, Oceania and South America have significantly higher recovery potentials, with average mine site NEP recovery potentials of 15.9 g C m−2 year−1 and 16.1 g C m−2 year−1. In contrast, European mines have considerably lower recovery potentials of less than 10 g C m−2 year−1. In Asia, North America and Africa, the NEP recovery potential varies widely from mine to mine, but generally meets the global average. (3) The annual precipitation, population density, organic soil carbon, and average slope are important drivers of NEP recovery in mining areas and exhibit positive correlations with the NEP recovery potential. In contrast, mine area and minimum temperature exhibit a negative correlation. The dependency curves of the three drivers, standardized precipitation evapotranspiration index, average elevation, and annual maximum temperature, are U-shaped, indicating that the recovery potential was poorer in the tropical and frigid zones with less precipitation. The results of this study provide a scientific basis for ecological restoration and sustainable development of mining areas worldwide. [ABSTRACT FROM AUTHOR]