The quantification of nanoplastic retention in soils and release mechanisms mediated by soil colloids remains challenging. This study used palladium-labeled nanoplastics (Pd-NPs) in column experiments to investigate their retention and potential long-term release, focusing on interactions with soil colloids. Pd-NPs were primarily immobilized through low energy barriers related to charge heterogeneity or nanoscale roughness, but also influenced by blocking, ripening, charge reversal, and cation bridging. These interactions limited particle release under steady-state conditions or flow interruptions. However, transient changes in solution chemistry (e.g., increased pH and reduced ionic strength, IS) lowered energy barriers to detachment on some convex nanoscale roughness locations, facilitating remobilization of reversibly retained Pd-NPs. Cation exchange and IS reduction further promoted particle release (5.2%-30.7%) by decreasing charge heterogeneity and weakening cation bridging. Approximately 75.9% of the released Pd-NPs were mainly associated with soil colloids in the 0.1-2 μm range under reduced IS conditions via cotransport or heteroaggregation, and the detachment of these soil colloids was the dominant mechanism of their long-term release. In contrast, 68.7% of the released Pd-NPs under increased pH occurred independently of soil colloid release. Additionally, Pd-NPs bound to stable solid surfaces in deep primary minima were irreversibly retained (≤63.8%), preventing detachment. This study highlights the importance of understanding the interaction between Pd-NPs and soil colloids for accurate assessment of long-term environmental risks, particularly groundwater contamination.

Humic acid (HA), a critical component of soil organic colloids and a key player in the carbon cycle, exhibits complex transport behaviors in porous media under varying chemical and hydrodynamic conditions. This study systematically investigates the deposition and release mechanisms of HA colloids in saturated quartz sand using column experiments combined with theoretical modeling. Specifically, HA colloidal suspensions were prepared by dissolving HA powder in CaCl2 solution, and experiments were conducted under controlled ionic strengths (IS: 0.2, 0.01, and 0.001 M), flow velocities (1 x 10(-)(4) m s(-1) and 2 x 10(-)(4) m s(-1)), and media particle sizes (240 and 328 mu m). Results demonstrated that HA colloid deposition was enhanced under higher IS, smaller media size, and lower flow velocity. Notably, a sequential cation exchange process (i.e., replacing Ca2+ with Na+ prior to IS reduction via deionized water injection) induced a substantial release of HA colloids, surpassing the release observed with IS reduction alone. Furthermore, by integrating extended Derjaguin-Landau-Verwey-Overbeek theoretical calculations and a two-site kinetic model with experimental data, we provided new mechanistic insights into HA colloid interactions in porous media. These findings advance the understanding of HA transport in calcareous soils and provide a theoretical framework for predicting contaminant or colloid mobility in subsurface environments.

Quantifying interfacial interaction energy between the 30nm hollow nanoparticles and fractal surfaces is the prerequisite for quantitatively understanding and evaluating the environmental risks of hollow nanoparticles and their associated pollutants. Although some studies have investigated the interaction energy between hollow nanoparticles and a planar surface, the influence of different fractal dimension D or fractal roughness G on the interaction energies of hollow nanoparticles with different interior fluids under different ionic strengths is unclear. In this study, the attachment and detachment of the 30nm hollow nanoparticles from fractal surfaces were evaluated through computing the extended Derjaguin-Landau-Verwey-Overbeek (extended-DLVO) interaction energies with the three-dimensional space based on surface element integration (SEI). The results indicated that for hollow nanoparticles filled with water, the primary minimum decreased slightly with all fractal surfaces, while it reduced significantly between hollow nanoparticles filled with air and fractal surfaces at 1mM. Interestingly, the maximum energy barrier for hollow nanoparticles increased significantly, especially for hollow nanoparticles filled with air at the 200mM ionic strength or with fractal surfaces with largest D value or smallest G value. Compared with solid nanoparticles, the attachment efficiency in the primary minimum decreased slightly at the ionic strength from 1 to 100mM for both hollow nanoparticles, and reduced significantly at 200mM, especially for nanoparticles filled with air. The reduced attachment efficiency in primary minimum decreased with the increasing fractal dimension D and decreasing fractal roughness G. Although values of secondary energy minimum for solid nanoparticles were small at both valleys and peaks at 200mM, it further decreased for hollow nanoparticles with different interior fluids. The findings in the present study have important implications for the design and use of hollow nanoparticles in soil remediation and colloid assembly.

On September 5, 2022, a magnitude Ms6.8 earthquake occurred in Luding County, Sichuan Province. This earthquake occurred at the key part of the southeast-clockwise extrusion of material on the eastern margin of the Tibetan Plateau, the Y-shaped confluence of the Xianshuihe, Longmenshan and Anninghe fault zones. In this study, the three-dimensional dynamic crustal density changes in the earthquake area are obtained by the typical gravity change data from 2019 to 2022 before the earthquake and gravity inversion by growing bodies. The results indicate that gravity changes presented an obvious four-quadrant and gradient belt distribution in the Luding area before the earthquake. The three-dimensional density horizontal slices show that small density changes occurred at the epicenter in the mid-to-upper crust between 2019.9 - 2020.9 and 2019.9 - 2021.9. At the same time, the surrounding areas exhibited a positive and negative quadrant distribution. These observations indicate that the source region was likely in a stable locked state, with locking in shear forces oriented in the NW and NE directions. From 2021.9 to 2022.8, the epicentral region showed negative density changes, indicating that the source region was in the expansion stage, approaching a near-seismic state. The three-dimensional density vertical slices reveal a southeastward migration of positive and negative densities near the epicenter and on the western of the Xianshuihe Fault Zone, indicating that the material is flowing out to the southeast. The observed local negative density changes at the epicenter along the Longmenshan Fault Zone are likely associated with the NE-oriented extensional stress shown by the seismic source mechanism. The above results can provide a basis for interpreting pre-earthquake gravity and density changes, thereby contributing to the advancement of earthquake precursor theory.

This study systematically examines the roles of positive goethite on the retention and release of negative plastic nanoparticles (PSNPs) with different surface functional groups (Blank, -COOH, and -NH2). It provides the first evidence for the dual roles of goethite coatings on colloid transport; e.g., increased transport caused by surface morphology modification or decreased transport due to increased surface roughness and charge heterogeneity. Although previous work has shown that goethite-coated sand increases the retention of negative colloids, this work demonstrates that collector surface roughness can also reduce the retention of PSNPs due to increased interaction energy profiles. Nonmonotonic retention of all the different functionalized PSNPs was observed in goethite-coated rough sand, and the magnitude of variations was contingent on the PSNP functionalization, the solution ionic strength (IS), and the goethite coating. The release of PSNPs with IS decrease (phase I) and pH increase (phase II) varied significantly due to differences in energy barriers to detachment, e.g., release in phase I was inhibited in both goethite-coated sands, whereas release in phase II was enhanced in coated smooth sand but completely inhibited in rough sand. The findings of this study provide innovative insight into transport mechanisms for colloidal and colloid-associated contaminants.

Assessing heavy metal pollution and understanding the driving factors are crucial for monitoring and managing soil pollution. This study developed two modified assessment methods (NIPIt and NECI) based on soil type-specific background values and pollution indices, and combined them with the receptor model to evaluate pollution status. Additionally, a structural equation model was used to analyze the driving factors of soil heavy metal pollution. Results showed that the average NIPIt and NECI were 1.48 and 0.92, respectively, indicating a low pollution risk level. In some areas, Cd and Hg were the primary heavy metals contributing to pollution risk, with their highest average concentrations exceeding soil type-specific background values by 2.06 and 2.04 times, respectively. Additionally, in black soils, meadow soils, and chernozems, heavy metals primarily originated from natural sources, accounting for 48.92%, 45.98%, and 45.58%, respectively. In aeolian soils, agricultural sources were predominant, contributing 43.38%. Soil pH and organic matter were key soil properties affecting NECI and NIPIt, with direct effects of 0.36 and -0.19, respectively. This study aims to provide new methods and insights for the comprehensive assessment and driving factors analysis of soil heavy metal pollution, with the goal of enhancing pollution monitoring and reducing risk.

Heavy metals released from metallic sulfidic tailings pose significant environmental threats by contaminating surface and groundwater in mining areas. Sustainable rehabilitation methods are essential to remove or stabilize these metals, improving the quality of acid mine drainage and minimizing pollution. This study examines the adsorption capacity of zinc ions (Zn2+) by different iron-silicate mineral groups under natural weathering and bacteria-regulated weathered conditions. Batch experiments revealed that all tested mineral groups exhibit limited adsorption Zn2+ on iron-silicate surfaces, with adsorption behavior aligning with Langmuir and Freundlich isotherm models. Among the mineral groups, pristine iron-muscovite (2.58 mg/g) and iron-chlorite (4.52 mg/g) demonstrated the highest Zn2+adsorption capacity, primarily due to favorable ion exchange properties and surface characteristics. Acidic conditions induced by pyrite oxidation and the experimental growth medium slightly reduced Zn2+ adsorption in samples without microbial inoculation. In contrast, the addition of Acidithiobacillus species modestly enhanced Zn2+ adsorption, likely through microbial alteration of silicate surface properties and the formation of secondary iron-silicate aggregates with high adsorption potential. The dominant adsorption mechanisms included electrostatic attractions, surface complexation and coprecipitation. It is recommended to elevate pH levels and thus enhance metal ion adsorption through the incorporation of alkaline additives such as zeolites or bauxite residue to optimize Zn2+ immobilization in sulfidic tailings. This study highlights the importance of both microbial and clay mineral selection in designing effective strategies for stabilizing Zn2+ in metallic sulfidic tailings.

Soil organic carbon (SOC) is important for agricultural production and from an environmental perspective. This research determined the chemical composition of SOC and studied factors related to its distribution for various crops and peat-swamp forests in the tropical region. In total, 21 topsoil samples were collected from areas of paddy rice, sugarcane, cassava, pineapple, oil palm, para rubber, and peat-swamp forest in Thailand. Four groups of SOC chemical composition were investigated (carbonyl C, aromatic C, O-alkyl C, and alkyl C) using solid-state C-13 nuclear magnetic resonance spectroscopy (NMR). The dominant peak of the NMR spectra indicated that SOC originated from a variety of lignin compound units. The results revealed the dominant SOC chemical component was O-alkyl C (36.57-50.90%), followed by alkyl C (22.32-32.60%), aromatic C (16.65-23.41%), and carbonyl C (7.99-10.95%), respectively. Most of the SOC chemical components were derived from plant debris, particularly biodegraded lignin compounds. There were slightly differences between the distributions of the SOC functional groups in each vegetation type, perhaps partially as a result of the specific management activities for each crop, including tillage. Furthermore, alkyl C was related to some soil properties (silt and clay fractions), while O-alkyl C was related to available P in the soil. The hydrophobicity index, aromaticity index, and degree of humification were in the ranges 0.69-1.12, 0.17-0.23, and 0.46-0.92, respectively. These findings provided SOC chemical composition data of several economic crops to further support soil management for crop production and carbon stock preservation in tropical soils.

Cultivated land is the most important natural resource for human survival and development. The quality of cultivated land is closely related to grain output, and whether it can guarantee stable food supply is directly related to national food security. Cultivated land quality evaluation is an effective tool for understanding and mastering cultivated land quality. However, few studies have applied bibliometrics to quantitatively and systematically analyze this field. We used VOSviewer 1.6.19 and CiteSpace 6.3.1 software to visually analyze and construct 2478 documents related to cultivated land quality evaluation retrieved from the Web of Science core collection database from 2000 to 2023. Results show that cultivated land quality evaluation is still a popular research field. The collaboration ability among authors is weak and the distribution of institutions and countries publishing in this field is very uneven. In addition, the relevant research has been published in a variety of journals such as agriculture, environment, ecology, and computer technology. The research content is becoming more and more interdisciplinary. Keywords such as “Soil quality”, “Swat”, “Remote sensing”, “Heavy metals” and “Ecosystem services” have become hot topics in this field. In the future, it is necessary to further deepen the connotation of cultivated land quality, develop a long time series dynamic model of cultivated land quality evaluation and monitoring, and enhance the transformation of research results into practical applications.

Source apportionment and risk assessment of soil heavy metals (HMs) are essential for pollution control. However, inherent limitations in receptor models hinder accurate source apportionment, impacting outcomes of source-oriented risk assessment. A hybrid model was employed by combining two receptor models, absolute principal component score/multiple linear regression (APCS/MLR) and positive matrix factorization (PMF) models. Four primary pollution sources were identified, followed by an assessment of source-oriented environmental and human health risks in the Huangshui River Basin. Results revealed that Cr, Cd, and Ni average concentrations surpassed their background by 3.1, 2.1, and 1.9 times, respectively. Additionally, 54.29%, 13.34%, and 18.09% of Igeo values for Cr, Cd, and Ni were classified as “moderately contamination” or higher. Natural sources significantly influence Cu (90.2%) and As (71.4%). Cr (63.4%) and Ni (77.9%) mainly originated from agriculture and industry, respectively. Transportation sources emerged as the primary contributors to Pb (59.6%), Zn (48.6%), and Cd (47.2%). The environmental risk level in this study area remained acceptable. Ecological risk was mainly attributed to industrial activities (46.6%) and transportation (37.6%), with Cd being the predominant metal responsible for this risk. Although the noncarcinogenic risk was negligible for all populations, the carcinogenic risk demands attention, particularly concerning children. Industrial sources (67.0%) and Ni were identified as the main contributors to the carcinogenic risk. This study represents an attempt to develop a hybrid model, providing an effective approach to combine models for the accurate apportionment of pollution sources and the reduction of risks.

While the facilitated transport of heavy metals by colloids such as clay particles has been widely recognized, the influence of heavy metals on transport of the colloids has received much less attention. This study conducted saturated column experiments to systematically examine influence of multivalent heavy metal cations on transport of natural clay colloids and fullerene nC(60) nanoparticles in glass bead porous media. Results showed that the presence of Cd2+ in the solution can cause more deposition of clay colloids in glass beads compared to Ca2+ at a given ionic strength (IS), and the subsequent release by IS reduction was less, demonstrating that the presence of Cd2+ increased the irreversibility of attachment. When the glass beads were initially adsorbed with Ca2+ and Cd2+, the release of clay colloids was significantly reduced due to strong cation bridge between the clay colloids and collector surfaces via the heavy metal cations. The release of clay colloids was significantly increased upon reduction of solution IS if the Na+ was used to exchange for the Ca2+ or Cd2+ before the IS reduction. Additional experiments showed that the nC(60) nanoparticles that were deposited in the presence of Fe3+ and Cu2+ cannot be released by reduction of solution IS. However, the nanoparticle release occurred when the Ca2+ was used to exchange for the Fe3+ and Cu2+ Our work was the first to reveal the influence of heavy metal cations on the irreversibility of colloid attachment, and the findings have important implication to fabrication of functional nanomaterials for stabilization of heavy metals in soil and development of mathematic models for accurate prediction of cotransport of heavy metals and colloids in subsurface environments.

The rapid aggregation and subsequent deposition of nanoscale zero-valent iron (nZVI) cause extremely low mobility in porous media. This study fabricated novel hollow mesoporous silica (HMS) supported nZVIs (HMS-nZVIs) by decorating spherical nZVI on HMS surfaces in a monolayer and examined the stability and transport of the HMS-nZVIs in porous media. Results show that the stability of the HMS-nZVIs was similar to that of HMSs, which was much greater than that of nZVIs due to increased electrostatic repulsion. The HMS-nZVIs showed greater mobility in porous media even than HMSs. This is because while decorating of nZVIs on the HMS surfaces reduced repulsive energy barrier, the nZVIs reduced the primary minimum depth and accordingly the adhesive force, causing less deposition of the HMS-nZVIs on the collector surfaces compared to HMSs. Increasing the loading concentration of nZVIs led to the aggregation of nZVIs on HMS surfaces, which increased the sizes of HMS-nZVIs and the retention of HMS-nZVIs in porous media through straining. The great mobility of the HMS-nZVIs revealed by this study shows the potential of using hollow particles as vehicles for delivery of nZVIs for in situ soil and groundwater remediation.

Source identification and risk assessment of heavy metals in soil are essential for preventing and controlling pollution, which is particularly important for the fragile plateau ecotones. However, precise identification was hindered by the large spatial heterogeneity using a single receptor model. Therefore, the absolute principal component score/multiple linear regression (APCS/MLR) and positive matrix factorization (PMF) receptor models were combined, and by employing auxiliary methods such as redundancy analysis, correlation analysis, and spatial analysis, the source of soil heavy metals in the plateau ecotone (Huangshui River Basin) were accurately identified. Furthermore, the environment and health risks were assessed using risk assessment models. Results showed that the mean concentrations of Cr, Cd, and Ni were 3.1, 2.1, and 1.9 times higher than their background values, and the Ganhe industrial park area was identified as the hot-spot area for Zn, Pb, and Cd. Combining receptor models and multiple statistical methods to source identification indicated that Cr was predominantly contributed by agricultural sources, Ni was primarily derived from industrial sources, Pb, Zn, and Cd were mainly originated from transport sources, while As, Cu, Hg, and Co were mainly from natural sources. The environmental risk level in this study area remained acceptable, and Cd was the major metal causing the risk. While the noncarcinogenic risk was negligible for all populations, the carcinogenic risk demanded attention, particularly concerning children, as it reached an unacceptable level. Ni emerged as the principal heavy metal contributing to the carcinogenic risk, with Cr chiefly responsible for the potential noncarcinogenic risk. This study has significant implications for addressing soil heavy metals pollution, safeguarding the ecological environment, and promoting human health in the delicate plateau ecotones.

Detecting heavy metals using proximal soil sensors is increasingly important as soil pollution is a global environmental problem. Researchers commonly use portable X-ray fluorescence (PXRF) and visible-near infrared (VNIR) sensors in polluted areas. However, a single sensor tends to perform poorly in soil with low heavy metal content， while sensor data fusion might provide robust perfomance.This study collected the PXRF and VNIR spectra of 273 soil samples from cultivated land in Lishu County, Northeast China. We investigated multiple data fusion methods to integrate PXRF and VNIR spectra to improve the estimation of five heavy metals in soil, combining machine learning models. The data-level fusion directly combined PXRF and VNIR; the feature-level fusion integrated the feature bands of PXRF and VNIR selected by the Boruta algorithm; the decision-level fusion involved outer product analysis fusion (OPA), OPA fusion based on feature bands (Boruta-OPA) and Granger-Ramanathan averaging (GRA). The results showed that PXRF and VNIR provided successful estimations of the Cr, Pb, As with residual prediction deviation (RPD) > 1.4. The extent to which the three data fusion techniques improved the prediction of heavy metals were ranked as decision-level > feature-level > data-level. Cr and As were best estimated in Boruta-OPA fusion with RPD = 1.99, 1.90, concordance correlation coefficient (CCC) = 0.85,0.85, and root mean square error (RMSE) = 7.93, 1.39 mg/kg, respectively. Pb was best predicted in the feature-level fusion with RPD = 1.90, CCC = 0.84, and RMSE = 2.76 mg/kg. The Cd and Hg concentrations could not be estimated due to very low content (RPD < 1.4). We recommend the Boruta-OPA as a universally effective spectral fusion method for soil heavy metals estimation.

Digital soil mapping of soil organic matter (SOM) is necessary because of its importance for carbon sequestration, soil health, and food security. However, large-scale digital soil mapping of SOM remains a challenge to improve accuracy and provide more local information. To address this knowledge gap, a strategy that incorporates remote and proximal sensing data into an ensemble model for the digital soil mapping is proposed. In this study, moderate resolution imaging spectroradiometer, portable X-ray fluorescence, and visible near-infrared spectroscopy data from 402 soil samples were used to map the SOM at a resolution of 90 m, model the SOM with random forest, cubist, and ensemble models, and evaluate its environmental factors in the northeastern and northern Chinese plains, a typical agricultural plain (approximately 66,000,000 ha). The digital maps of the SOM were derived along with their uncertainties. The results show that the visible near-infrared and portable X-ray fluorescence data play an important role in the SOM distribution. Inclusion of these data in the model, improved the R-p(2) by 6.25-35.42 %, and reduced the root mean square error of the prediction by 0.30-1.54 g kg(-1). The ensemble model, which included remote and proximal sensing variables, outperformed the results of previous studies with a root mean square error of 6.68 g kg 1 and provided more detailed information. Thus, this study confirmed the effectiveness of the proposed strategy. The SOM product obtained by this strategy was able to accurately control soil management, and the structural equation model showed that human activities exerted a direct influence on SOM comparable to the overall effect of natural factors on SOM. The contribution of straw mulching to human activities was great with path coefficient >0.50. This suggests that land management, especially straw mulching, should be improved in this area. In summary, this study proposed a novel strategy for accurately and efficiently obtaining SOM products for agricultural decision-making, terrestrial carbon cycling, and carbon stock estimation. Future advancements will focus on more accurate and detailed global SOM maps or carbon storage by integrating multiple models with remote sensing data and proximal sensing data from available soil spectral libraries.

Hardpan-based profiles naturally formed under semi-arid climatic conditions have substantial potential in rehabilitating sulfidic tailings, resulting from their aggregation microstructure regulated by Fe-Si cements. Nevertheless, eco-engineered approaches for accelerating the formation of complex cementation structure remain unclear. The present study aims to investigate the microbial functions of extremophiles on mineral dissolution, oxidation, and aggregation (cementation) through a microcosm experiment containing pyrites and polysilicates, of which are dominant components in typical sulfidic tailings. Microspectroscopic analysis revealed that pyrite was rapidly dissolved and massive microbial corrosion pits were displayed on pyrite surfaces. Synchrotron-based X-ray absorption spectroscopy demonstrated that approximately 30 % pyrites were oxidized to jarosite-like (ca. 14 %) and ferrihydrite-like minerals (ca. 16 %) in talc group, leading to the formation of secondary Fe precipitates. The Si ions co-dissolved from polysilicates may be embedded into secondary Fe precipitates, while these clustered Fe-Si precipitates displayed distinct morphology (e.g., "circular" shaped in the talc group, "fine-grained" shaped in the chlorite group, and "donut" shaped in the muscovite group). Moreover, the precipitates could join together and act as cementing agents aggregating mineral particles together, forming macroaggregates in talc and chlorite groups. The present findings revealed critical microbial functions on accelerating mineral dissolution, oxidation, and aggregation of pyrite and various silicates, which provided the eco-engineered feasibility of hardpan-based technology for mine site rehabilitation.

Colloid (Nano- and Micro-Particle) Transport and Surface Interface in Groundwater by William P. Johnson and Eddy F. Pazmino is a textbook that consists of 111 pages and 11 chapters and serves as an introduction to colloids in groundwater, with a focus on their transport, because the distribution of the colloids in groundwater is mainly governed by their transport. Instead of a comprehensive review of contributions to the literature, this textbook is intended to directly summarize current knowledge of colloid transport in groundwater. This textbook can be helpful for both beginners and researchers to learn the models simulating colloid transport in groundwater and explore the complex mechanisms governing the transport. The book belongs to the Groundwater Project, the works of which are available for free via the website https://gw-project.org/, operated by the Groundwater Project. The Groundwater Project is a nonprofit organization in Canada that is committed to advancing education by creating free high-quality groundwater educational material that is available online for all. Investigation of colloid transport in groundwater is critical to understanding a variety of natural processes and engineered applications such as transport of pathogenic colloids (e.g., viruses, bacteria, and protozoa) and colloid-associated contaminants in the subsurface, and soil and groundwater remediation using nanomaterials (e.g., nanoscale zerovalent iron) and microbes. Deposition is one of the primary factors that govern transport of colloids in groundwater. This textbook presents the state-of-the-art using the Lagrangian method to quantify colloid deposition rates and transport. The Lagrangian approach quantifies colloid trajectories and, accordingly, the deposition and transport based on Newton's second law. The colloid trajectories are controlled by both nanoscale interactions between colloids and surfaces and pore-scale forces such as fluid drag, diffusion, and gravity. This textbook provides basic and advanced information on the aforementioned interactions and forces and how they can be addressed and simulated across the nano, pore, and continuum scales. This textbook has a logical organization of the content by sequentially presenting nanoscale interactions, pore-scale transport processes, and continuum-scale colloid transport (i.e., in an upscaling order). A feature of this textbook is that the authors have incorporated numerical modeling freeware (Parti-Suite) into the text to allow both early-career and advanced researchers to explore presented concepts. The software can clearly visualize trajectory simulations of colloid populations. In addition to the trajectory simulation, the Parti-Suite software provides calculations of colloid–surface interaction energies and forces and collector efficiencies, as well as simulation of the breakthrough curves and retention profiles from column transport experiments at continuum scale. Videos in the Parti-Suite software can be watched by clicking linked figures in the textbook. The Parti-Suite software can be freely downloaded via the link https://wpjohnsongroup.utah.edu/trajectoryCodes.html. Chapter 1 states the scope of this textbook, the book approach, and the goals of the book. Chapter 2 introduces groundwater colloids. In this chapter, the authors present the definition of colloids and the significance of investigating colloid transport in groundwater. They demonstrate that while this text does not directly address colloid aggregation, the mechanisms elucidated in this study facilitate an understanding of the colloid transport behavior in the presence of colloid aggregation. Chapter 3 shows the ranges of size from solutes to the largest colloids and highlights that forces such as gravity and diffusion distinguish the contrasting transport behaviors across the range from solutes to colloids. Because colloid–surface and other interactions are normally cast in either form, this chapter makes a review of distinguishing forces vs. energies by using release of an airborne particle at a given height on a wind-free day as an example. Chapter 4 first briefly introduces solute interaction with colloids. This chapter then introduces DLVO (Derjaguin–Landau–Verwey–Overbeek) theory, DLVO energy maps under favorable and unfavorable conditions (i.e., in the absence and presence of repulsion energy barriers, respectively), and the concept of the “zone of colloid–surface interaction” (over which DLVO interactions act). This chapter has a detailed description of the nanoscale interactions of colloids with surfaces, including van der Waals interaction, electric double layer force, and short-range interactions such as Born repulsion, Lewis acid–base interactions, and hydration repulsion. This chapter also shows how the impact of roughness on colloid–surface interactions is included in the DLVO module of Parti-Suite. Chapter 5 presents pore-scale colloid transport including delivery of colloids to collector surfaces, their subsequent interaction with surfaces, and their potential detachment following attachment. The chapter first reviews experimentally observed effects of favorable vs. unfavorable condition on pore-scale colloid motion in near-surface fluid, colloid attachment, colloid detachment, and the impact of roughness on colloid transport. The chapter then describes the process of simulating pore-scale colloid transport using a mechanistic force and torque balance for representative collectors. The chapter further discusses a number of approximate approaches developed to simulate pore-scale colloid transport, such as correlation equations as a shortcut to collector efficiency, and attachment efficiency as a shortcut to unfavorable collector efficiencies. The chapter finally compares colloid transport with solute transport at the pore scale. Chapter 6 presents experimental observations of colloid transport at the continuum scale and simulated continuum-scale transport. The chapter shows experimentally observed impacts of favorable vs. unfavorable conditions on breakthrough-elution concentration histories and profiles of retained colloid concentrations at the continuum scale, and practical implications of the continuum-scale experimental observations. The simulation of continuum-scale transport includes simulating continuum scale hydrodynamic processes and reactive transport using rate coefficients, and mechanistic linking of rate coefficients to pore- and nano-scale processes. This textbook is also aimed to correct ongoing misperceptions regarding mechanisms governing colloid transport, attachment, and retention. Examples of the misconceptions include: (a) smaller colloids undergo lesser filtration; (b) attaining equilibrium in batch experiments indicates that filtration does not apply (used to argue that nanoparticles partition rather than undergo filtration); (c) correlation equations are colloid filtration theory and correlation equations are empirical; (d) the attachment efficiency under unfavorable conditions reflects only the chemistry, and so is a single value across the physical parameters such as colloid size or fluid velocity; and (e) greater retention near the entrance of a porous medium is the same as nonexponential retention. This textbook increases the knowledge of colloid transport in groundwater through discriminating analysis and insightful organization of the material. I highly recommend this book to students, teachers, and practitioners in fields such as environmental science, hydraulics, hydrology, and hydrogeology. My own students have great experience of using Parti-Suite software for trajectory simulation of colloids in porous media. For example, the Parti-Suite software was used to simulate the trajectories of colloids from bulk solution to the collector surface to account for the impacts of surface roughness and hydrodynamics on colloid deposition by incorporating the impacts into surface torque balance, and the simulation was published in Environment Science and Technology (https://doi.org/10.1021/acs.est.1c07305). Chongyang Shen: Writing – original draft; Writing – review & editing. This review was supported by National Natural Science Foundation of China (41922047). The authors declare no conflict of interest.

Colloid transport in porous media plays important roles in many agricultural, environmental, and engineering processes. Colloids vary in their source, composition, shape and structure but they all possess large specific surface areas and have high reactivity. Deposition or attachment, release or detachment, and straining are the processes controlling colloid transport in saturated media; attachment to air-water interfaces and the contact line, and film straining are additional processes affecting colloid transport through unsaturated media. The interactions of colloids with interfaces can be described by classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, which considers van der Waals and electrical double layer forces and by extended DLVO, which includes non-DLVO forces (e.g., hydration, steric and hydrophobic). Current approaches to modeling colloid transport build on the classical colloid filtration theory. More complete mechanistic understanding of colloid retention and release processes and experimental validation will improve model development and our ability to manage both the risks and beneficial applications of environmental colloids.

As cultivated land quality has been paid more and more scientific attention, its connotation generalization and cognitive bias are widespread, bringing many challenges to the investigation and evaluation of regional cultivated land quality and its data analysis and mining. Establishing a systematic and interdisciplinary cognitive approach to cultivated land quality is urgent and necessary. Therefore, we explored and developed a conceptual framework of the model for the cultivated land quality analysis from the data perspective, including cultivated land quality ontology, mapping, correlation, and decision models. We identified the primary content of cultivated land quality perceptions and four cognitive mechanisms. We built vital technologies, such as the collaborative perception of the quality of cultivated land, intelligent treatment, diagnostic evaluation, and simulation prediction. Applying this analysis framework, we sorted out the frequency of indicators that characterize the function of cultivated land according to the literature in recent years and have built the cognitive system of cultivated land quality in the black soil region of Northeast China. The system’s central component was production capacity and it had three components: a foundation, a guarantee, and an effect. The black soil region cultivated land quality evaluation system has seven purposes involving 20–31 key indicators: production supply, threat control, farmland infrastructure regulation, cultivated land ecological maintenance, economics, social culture, and environmental protection. In various application contexts, the system had many critical supporting technologies. The results demonstrate that the framework has strong adaptability, efficiency, and scalability, which might offer a theoretical direction for further studies on the evaluation of the quality of cultivated land in the area. The analysis framework established in this study is helpful to deepen the understanding of cultivated land quality systems from the perspective of big data. Taking the big data of cultivated land quality as the driving force, combined with the technical methods of cultivated land quality analysis, the evaluation results of cultivated land quality under different scenarios and different objectives are optimized. In addition, the framework can serve the practice of farmland management and engineering improvement, adapt to the management needs of different objects and different scales, and achieve the combination of theory and practice.

Hypothesis: Analytical expressions for calculating Hamaker constant (HC) and van der Waals (VDW) energy/force for interaction of a particle with a solid water interface has been reported for over eighty years. This work further developed novel analytical expressions and numerical approaches for determining HC and VDW interaction energy/force for the particle approaching and penetrating air-water interface (AWI), respectively. Methods: The expressions of HC and VDW interaction energy/force before penetrating were developed through analysis of the variation in free energy of the interaction system with bringing the particle from infinity to the vicinity of the AWI. The surface element integration (SEI) technique was modified to calculate VDW energy/force after penetrating. Findings: We explain why repulsive VDW energy exists inhibiting the particle from approaching the AWI. We found very significant VDW repulsion for a particle at a concave AWI after penetration, which can even exceed the capillary force and cause strong retention in water films on a solid surface and at air- water-solid interface line. The methods and findings of this work are critical to quantification and understanding of a variety of engineered processes such as particle manipulation (e.g., bubble flotation, Pickering emulsion, and particle laden interfaces). (c) 2021 Elsevier Inc. All rights reserved.