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Natural phenomena like hyporheic zone depths show intrinsic statistical behavior due to large variability of related parameters. In the previous researches, authors proposed a deterministic method to delineate hyporheic zone depth using a simple field temperature measurement, and studied a probabilistic method to present a proper statistical distribution model for hyporheic zone depth. As a next step forward, this research proposes remediation strategies on contaminated groundwater system in relation to hyporheic zone depth management. Primarily, demand of hyporheic zone depth to achieve a required recovery ratio is predetermined. The field hyporheic zone depth is, then, changed according to each strategies. The two probabilistic variables, demand and field values, are modified such that the difference are reduced. The index applied to evaluate each strategy in this paper was adopted from the concept of reliability index. This approach is frequently used in many fields of science and engineering, including a safety design of structures. The key point of safety design involves sufficiency of safety margins between a strength criterion and the requirements, and this is what the reliability index evaluates. The paper is structured to introduce reliability-based approach in terms of general concept and hyporheic zone depth management first, and proceeds to a development of index. The paper concludes with performance evaluation of strategies. This paper is of value because a combination of the previous research on the probabilistic property extraction of hyporheic zone depth and the presented approach of performance evaluation has potential to offer another useful tool to the remediation of contaminated groundwater.Acknowledgement: This research was funded by the Korea Ministry of Environment through the strategic EcoSSSoil Project at the Korea Environmental Industry and Technology Institute (grant no. 2019002820004) and National Research Foundation of Korea (NRF), funded by the Ministry of Education (grant numbers 2019R1I1A2A01057002 and 2019R1A61A0303

Quantitative and qualitative estimation of soil ecosystem has been studied for understanding importance of soil ecosystem. However, estimation of soil ecosystem is a complex process and requires numerous soil properties. The main objectives of this research was i) to select minimum data set of soil properties, ii) to develop quantitative estimation protocol for estimating soil ecosystem and iii) apply the developed protocol for quantification of soil ecosystem in water supply conservation area in Korea. In order to select minimum data set of soil indicators, national soil database provided by Rural Developed Administration (RDA) was used as a raw data set and principal component analysis was used for choosing the minimum data set. Total of 11 soil properties including 4 physical properties (bulk density, sand and clay contents, available water capacity), 5 chemical properties (pH, electric conductivity, soil organic matter, available phosphorus, cation exchange capacity), and 2 biological properties (soil respiration, soil enzyme concentration) were selected for soil indicators. Three representative models (more is better, optimum, and less is better) were obtained for each soil indicators and scaled from 0 to 1 for quantification. Developed quantification protocol was applied in 250 locations from water supply conservation area. The average score for provisioning, regulating, and supplying ecosystem service was 0.50, 0.68, and 0.82 respectively. Based on quantitative estimation of soil ecosystem service in Korea, provisioning ecosystem service including biomass production and water storage needs to be improved.

In the carbon neutral era, soil carbon became more important. Soil carbon pools (2400 Gt) are about three times larger than atmospheric pools, and soil carbon sequestration can store large amounts of organic carbon. Soil carbon storage has been reported as an effective tool to mitigate climate change in various studies, including the IPCC. Among them, it is known that agricultural soil can sequester carbon every year through sustainable soil management. In this study, we investigated changes in soil carbon storage (excluding volcanic soils) using the results of the Monitoring Project on Agri-Environmental Quality in South Korea from 1999 to 2018. Land use was categorized into paddy, upland, orchards and greenhouses. The soil organic carbon content of cultivated land has increased steadily over the past two decades, with annual organic carbon increases of 0.16 g kg-1 in paddy, 0.26 g kg-1 in upland and 0.33 g kg-1 in orchard, and 0.21 g kg-1 in greenhouse. In the 2000s, the use of chemical fertilizers decreased and the amount of livestock manure compost increased, which seems to have increased soil organic carbon. As a result of calculating the total annual increase in soil organic carbon in the entire cultivated land, it was found that 770,000 tons of C were stored in the soil (0-20 cm) per year. This corresponds to about 11% (2.8 million tons CO2-eq) of the 24.7 million tons CO2-eq of Korea's agricultural and livestock greenhouse gas emissions in 2018. South Korea also presented a scenario to achieve carbon neutrality by 2050, but currently does not include a method for using carbon sequestration. Looking at changes in soil carbon over the past 20 years, we found that soil can make a significant contribution to carbon neutrality if we introduce soil management that increases soil carbon and quantify the carbon sequestration. Therefore, it is judged necessary to introduce a soil management method that can maximize the carbon sequestration of the soil.

Due to climate change, soil moisture may increase, and outflows could become more frequent, which will have a considerable impact on crop growth. Crops are affected by soil moisture; thus, soil moisture prediction is necessary for irrigating at an appropriate time according to weather changes. Therefore, the aim of this study is to develop a future soil moisture (SM) prediction model to determine whether to conduct irrigation according to changes in soil moisture due to weather conditions. Sensors were used to measure soil moisture and soil temperature at a depth of 10 cm, 20 cm, and 30 cm from the topsoil. The combination of optimal variables was investigated using soil moisture and soil temperature at depths between 10 cm and 30 cm and weather data as input variables. The recurrent neural network long short-term memory (RNN-LSTM) models for predicting SM was developed using time series data. The loss and the coefficient of determination (R2) values were used as indicators for evaluating the model performance and two verification datasets were used to test various conditions. The best model performance for 10 cm depth was an R2 of 0.999, a loss of 0.022, and a validation loss of 0.105, and the best results for 20 cm and 30 cm depths were an R2 of 0.999, a loss of 0.016, and a validation loss of 0.098 and an R2 of 0.956, a loss of 0.057, and a validation loss of 2.883, respectively. The RNN-LSTM model was used to confirm the SM predictability in soybean arable land and could be applied to supply the appropriate moisture needed for crop growth. The results of this study show that a soil moisture prediction model based on time-series weather data can help determine the appropriate amount of irrigation required for crop cultivation.

This study presents the results of the water retention characteristics of six groups (0.25 mm to 8.35 mm) of expanded perlite (EP) produced from two crushed raw perlite rocks of Turkey (A) and China (B). The particle size proportions of EPs showed that the particle size less than 1.68 mm was higher in B than that of A and the particle size distribution curves (PSDC) of three samples of EP A and B were similar, while the percent finer value (DN) of B was higher than that of A in all corresponding particle sizes. Volumetric water content (θv) for EPs of A and B were obtained at 11 levels of matric potentials between 0 to −50 kPa (sandbox with kaolin-plate) and −50 to −1500 kPa (pressure chamber), respectively, after fully saturating the uniformly packed EP in open-ended metal round rings. The results showed that the shapes of measured WRCs and particle size distribution curves of EP A and B were similar, while the percent values of PSDC were higher than those values of θv corresponding to each water potential greater than 0.1 kPa. The WRCs of respective EP showed that a substantial decline started at about −1 kPa and approached the residual water content (θr) observed at −500 kPa for all measurements. θv for all particle sizes of the EP A and B was not only decreased with the increasing matric potential but also distinctive with increasing particle size greater than 2.36 mm. θr was increased with decreasing particle size. For these results, we assumed that θv of the different particle sizes of EP A and B could be determined by actual pore volume excluding occluded pore volume depending on size and surface area in the EP particles.

Veterinary antibiotics (VAs) released into the environment are a concern because of the possibility for increasing antibiotic-resistance genes. The concentrations of six VAs, chlortetracycline, oxytetracycline, tetracycline, sulfamethazine, sulfamethoxazole, and sulfathiazole, in manure-based compost, soil, and crops were measured using liquid chromatography–tandem mass spectrometry. Mass balance analysis was conducted based on the measured antibiotic concentration, cultivation area, and amount of manure-based compost applied. The result showed that the detected mean concentration of VAs ranges was 3.52~234.19 μg/kg, 0.52~13.08 μg/kg, and 1.05~39.57 μg/kg in manure-based compost, soil, and crops, respectively, and the substance of VAs detected in different media was also varied. Mass balance analysis showed that the VAs released from the manure-based compost can remain in soil (at rates of 26% to 100%), be taken up by crops (at rates of 0.4% to 3.7%), or dissipated (at rates of 9% to 73%) during the cultivation period. Among the six VAs, chlortetracycline and oxytetracycline mainly remained in the soil, whereas sulfamethoxazole and sulfathiazole were mainly dissipated. Although we did not verify the exact mechanism of the fate and distribution of VAs in this study, our results showed that these can vary depending on the different characteristics of VAs and the soil properties.

Heavy metal pollution in soil can have detrimental effects on soil ecosystems and human health. In situ remediation techniques are widely used to reduce the bioavailable fractions of heavy metals in soil. The main objective of this study was to examine the reduction of the bioavailable fractions of As and Pb in paddy soil with artificial lightweight material (ALM) manufactured from recycled materials. A total of four treatments, including a control (no amendment), ALM10 (10% of ALM in soil), ALM10+L (10% ALM combined with 0.5% lime), and ALM10+FeO (10% ALM combined with 0.5% FeO), were applied to paddy fields, and rice (Oryza sativa L.) was cultivated after 32 weeks. The highest reduction efficiencies for the bioavailable fractions of As and Pb in soil were observed in the ALM10+FeO (52.8%) and ALM10+L treatments (65.7%), respectively. The uptake of As decreased by 52.1% when ALM10+FeO was applied to paddy soil, and that of Pb decreased by 79.7% when ALM10+L was applied. Correlation analysis between bioavailable heavy metals in soil and soil chemical properties showed that soil pH, electrical conductivity (EC), P2O5, and soil organic matter (SOM) were the main factors controlling the mobility and bioavailability of As and Pb. Overall, the efficiencies of As and Pb reduction increased synergistically in both soil and plants when FeO and lime were combined with the ALM. In future studies, long-term monitoring is necessary to examine the longevity of soil amendments.

Heavy metal pollution in the environment is a critical issue, engendering ecosystem deterioration and adverse effects on human health. The main objective of this study was to evaluate heavy metal adsorbents by modifying industrial byproducts. The bottom ash was sintered and evaluated for Cd and Pb sorption. Three adsorbents (bottom ash, sintered bottom ash (SBA), and SBA mixed with microorganisms (SBMA)) were tested to evaluate the sorption kinetics and mechanism using a lab-scale batch experiment. The results showed that the highest sorption efficiency was observed for Cd (98.16%) and Pb (98.41%) with 10% SBA. The pseudo-second-order kinetic model (R2 &gt, 0.99) represented the sorption kinetics better than the pseudo-first-order kinetic model for the SBA and SBMA, indicating that chemical precipitation could be the dominant sorption mechanism. This result is supported by X-ray photoelectron spectroscopy analysis, demonstrating that -OH, -CO3, -O, and -S complexation was formed at the surface of the sintered materials as Cd(OH)2 and CdCO3 for Cd and PbO, and PbS for Pb. Overall, SBA could be utilized for heavy metal sorption. Further research is necessary to enhance the sorption capacity and longevity of modified industrial byproducts.

Biological desulfurization processes of landfill gas yield an enormous amount of biologically produced S (BPS) as a byproduct. Capability of BPS to remove Cd

We use the latest projections of climate and land use change (year 2070) to assess potential global soil erosion rates by water erosion (interrill and rill processes) (Borrelli et al., 2020) using the RUSLE-based semiempirical modeling platform (GloSEM) (Borrelli et al., 2017). With some degree of uncertainty, GloSEM allows prediction of both state and change of soil erosion, identifying hotspots thanks to its high resolution (250 × 250 m) and predicting future variation based on projections of change in land use, soil conservation practices, and climate change.Three alternative scenarios (2.6, 4.5, and 8.5) are tested using the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) (LUH2 data) and 14 General Climate Models (GCMs) (WorldClim data), for a total of 42 modelling scenarios.In the 2015 scenario, we estimate global soil erosion equal to 43 (+9.2/−7) Pg yr−1; with a study area covering ∼95.5% of the Earth’s land surface (in Borrelli et al. 2017 the study area was ~84.1% of the Earth’s land surface). The future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6–10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. By contrast, climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Quantitatively, 56.1 (+20.6+ /- 16.4) Pg yr−1, 64.8 (+28.5/-21.4) Pg yr−1, and 71.6 (+32.5/-24.7) Pg yr−1 are predicted for the SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios, respectively.The modeling framework presented in this study adopts standardized data in an adequate format to communicate with adjacent disciplines and moves us toward robust, reproducible, and open data science. ReferencesBorrelli, P., Robinson, D.A., Fleischer, L.R., Lugato, E., Ballabio, C., Alewell, C., Meusburger, K., Modugno, S., Schütt, B., Ferro, V. and Bagarello, V., 2017. An assessment of the global impact of 21st century land use change on soil erosion. Nature communications, 8(1), pp.1-13.Borrelli, P., Robinson, D.A., Panagos, P., Lugato, E., Yang, J.E., Alewell, C., Wuepper, D., Montanarella, L. and Ballabio, C., 2020. Land use and climate change impacts on global soil erosion by water (2015-2070). Proceedings of the National Academy of Sciences, 117(36), pp.21994-22001.

16 Pags.- 12 Figs.- 8 Tabls., Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper., Nejc Bezak and Matjaž Mikoš would like to acknowledge the support of the Slovenian Research Agency through grant P2-0180. Diana Vieira is funded by national funds (OE), through FCT – Fundação para a Ciência e a Tecnologia, I.P., in the scope of the framework contract foreseen - DL57/2016 (CDL-CTTRI-97-ARH/2018 - REF.191-97-ARH/2018), and acknowledges CESAM financial support of through (UIDP/50017/2020+UIDB/50017/2020). Jae E. Yang and Pasquale Borrelli are funded by the EcoSSSoil Project, Korea Environmental Industry & Technology Institute (KEITI), Korea (Grant No. 2019002820004). Walter Chen is funded by the Ministry of Science and Technology (Taiwan) Research Project (Grant Number MOST 109-2121-M-027-001).

40 Pags.- 10 Figs.- 2 Tabls.- Suppl. Informat. The definitive version is available at: https://www.sciencedirect.com/science/journal/00489697, To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named ‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions., Jae E. Yang and Pasquale Borrelli are funded by the EcoSSSoil Project, Korea Environmental Industry & Technology Institute (KEITI), Korea (Grant No. 2019002820004). Diana Vieira is funded by national funds (OE), through FCT – Fundação para a Ciência e a Tecnologia, I.P., in the scope of the framework contract foreseen - DL57/2016 (CDL-CTTRI-97-ARH/2018 - REF.191-97-ARH/2018), and acknowledges CESAM financial support of through (UIDP/50017/2020+UIDB/50017/2020). Walter Chen is funded by the Ministry of Science and Technology (Taiwan) Research Project (Grant Number MOST 109-2121-M-027-001). Nejc Bezak and Matjaž Mikoš would like to acknowledge the support of the Slovenian Research Agency through grant P2-0180.

The soil science community needs to communicate about soils and the use of soil information to various audiences, especially to the general public and public authorities. In this global review article, we synthesis information pertaining to museums solely dedicated to soils or which contain a permanent exhibition on soils. We identified 38 soil museums specifically dedicated to soils, 34 permanent soil exhibitions, and 32 collections about soils that are accessible by appointment. We evaluate the growth of the number of museums since the early 1900s, their geographical distribution, their contents, and their attendance. The number of museums has been continuously growing since the early 1900s. A noticeable increase was observed from 2015 to 2019. Europe (in a geographical sense), Eastern and South-East Asia have the highest concentration of soil museums and permanent exhibitions related to soils. Most of the museums' attendance ranged from 1000 to 10,000 visitors per year. Russia has the largest number of soil monoliths exhibited across the world's museums, whereas the ISRIC-World Soil Museum has the richest and the most diverse collection of soil monoliths. Museums, collections, and exhibitions of soil play an important role in educating the population about this finite natural resource that maintains life on the planet, and for this reason, they must be increasingly supported, extended, and protected.

Soil erosion is a major global soil degradation threat to land, freshwater, and oceans. Wind and water are the major drivers, with water erosion over land being the focus of this work; excluding gullying and river bank erosion. Improving knowledge of the probable future rates of soil erosion, accelerated by human activity, is important both for policy makers engaged in land use decision-making and for earth-system modelers seeking to reduce uncertainty on global predictions. Here we predict future rates of erosion by modeling change in potential global soil erosion by water using three alternative (2.6, 4.5, and 8.5) Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. Global predictions rely on a high spatial resolution Revised Universal Soil Loss Equation (RUSLE)-based semiempirical modeling approach (GloSEM). The baseline model (2015) predicts global potential soil erosion rates of 43+9.2−7 Pg yr−1, with current conservation agriculture (CA) practices estimated to reduce this by ∼5%. Our future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6–10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. Climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Accepting some degrees of uncertainty, our findings provide insights into how possible future socioeconomic development will affect soil erosion by water using a globally consistent approach. This preliminary evidence seeks to inform efforts such as those of the United Nations to assess global soil erosion and inform decision makers developing national strategies for soil conservation., Proceedings of the National Academy of Sciences of the United States of America, 117 (36), ISSN:0027-8424, ISSN:1091-6490

Chemical amendments have been used to remediate soils contaminated with heavy metals. However, there is little understanding on the impacts of these amendments on the physiological and biochemical functions of plants and soil. This study used in situ microcosm experiment to understand the effect of chemical amendments on antioxidant and soil enzyme activity in plant and soil with respect to heavy metal reduction. Three chemical amendments—acid mine drainage sludge (AMDS), limestone (LS), and steel slag (SS)—were applied to soil at 3, 5, and 10% mixing ratios, and lettuce (Lactuca sativa) was cultivated in that soil for 30 days. The results showed that bioavailable Cd and Pb in soil was reduced by 9.8–40.5% and 4.2–92.5%, respectively. The most efficient amendment for heavy metal reduction was AMDS. The uptake of Cd and Pb also decreased by 0.5–66.1 and 21.6–79.5%, respectively, depending on the amendment type and application ratio. The activity of three antioxidants—catalase (CAT), ascorbate peroxidase (APX), and glutathione reductase (GR)—was generally higher than the control with no amendments. This result indicated that there was minimal inhibition of antioxidant activity due to the reduction of heavy metal uptake. Also, no significant difference was observed in chemical amendments applied soil compared to control in terms of soil enzyme activity. However, correlation analysis between heavy metal concentration in soil and two soil enzyme activities showed that significantly negative correlation (p

In the Republic of Korea, the conservation of soil and groundwater quality has been stimulated by recognizing that these natural resources are critically important components of the earth’s biosphere and are directly related to human health. This chapter devotes to the discussion of the present status, impacts, management strategies, and perspectives of trace metals in soil and groundwater in Korea. Metal accumulation in soils is closely connected to the specific local sources such as discharges from smelters, metal-based industries, chemical manufacturing industries, active, inactive, and abandoned mining sites, and irrigation water. Metal concentrations in soils and crops are subject to change due to different environmental situations. Research concerning metal speciation, transformation, and bioavailability in Korean soils has been much more limited than that on metal distribution. Metal concentrations in soils from the metal mining areas are much higher than those in other areas.

This study is to develop the Web GIS-based surface soil erosion prediction system that informs soil information such as daily potential soil erosion, soil quality, and best management practices (BMPs). The system involves three functions that are: 1) to predict daily potential soil erosion in the study areas (e.g., Jaun-Cheon, Bukhan-Gang, Namhan-Gang, and Gyoungan-Cheon); 2) to provide the current levels of soil qualities at field scale; 3) to recommend BMPs which can improve soil qualities. This study developed a module based on MUSLE and assessed the availability of the module comparing with the measured data at sample fields (3%, 9% slope). After verification of the module, the Web GIS-based system was developed using a user-friendly interface. The users can obtain the visualized soil erosion information through the interface and compare the amount of soil erosion using the single field or multi-fields analysis tool developed in this study. Moreover, the users can find the current level of soil qualities at fields they selected and gain various applicable BMPs information. The system enables to inform non-experts to soil information without using a complex model and equation. Therefore, the system can play a significant role in recognizing the importance of soil resources and enacting laws relative to soil conservation.

In the age of big data, constructing a database plays a vital role in various fields. Especially, in the agricultural and environmental fields, real-time databases are useful because the fields are easily affected by dynamic nature phenomena. To construct a real-time database in these fields, various sensors and an Internet of Things (IoT) system have been widely used. In this study, an IoT system was developed to construct soil properties database on a real-time basis and aim to a big data system analysis that can assess ecosystem services provided from soil resources. The IoT system consisted of three types of soil sensors, main devices, sensor connectors, and subsidiary devices. The IoT system can measure soil temperature, moisture, and electrical conductivity (EC) data on a five-minute interval. Also, the devices were applied to two test-beds near Chuncheon city in South Korea and have been testing for the stability and availability of the system. In a further study, we will add various soil sensors and functions into the developed IoT system to improve their availability. If the developed IoT system becomes to be stable and functional, it can contribute to constructing soil properties database on a real-time basis and a big data system that assesses soil ecosystem services.

Heavy metal pollution and greenhouse gas (GHG) emissions from soil are two major detrimental sources in the agriculture environment because of concerns about crop safety and global warming. Applying amendments on site is a common technique used for heavy metal remediation and the reduction in GHG emissions. This study aims to evaluate the effect of different amendments on the reduction in both bioavailable heavy metals and GHG emissions from soil. Four different amendments, namely bottom ash (BA), sintered material (SM), sintered material combined with lime (SM + L), and FeO (SM + FeO) were applied to upland fields, followed by maize (Zea mays L.) cultivation from April to October. Subsequently, SM + FeO treatment demonstrated the highest bioavailability reduction efficiency for As at 79.1%, and SM + L treatment had a high efficiency for the reduction in Cd and Pb by 64.6% and 41.4%, respectively. SM + FeO treatment also reduced bioaccumulated As and Pb in maize grain by 59.3% and 66.2%, respectively. Furthermore, SM + FeO treatment demonstrated the highest reduction efficiency for cumulative N2O emissions by 70.7%, compared to the control soil. Among the four different amendments, the efficiency of heavy metal and GHG emission reduction was in the following order: SM + FeO > SM + L > SM > BA. Overall, SM combined with FeO is a promising amendment for reducing and managing both heavy metal pollution and GHG emissions in soil.

Biological desulfurization processes of landfill gas yield an enormous amount of biologically produced S (BPS) as a byproduct. Capability of BPS to remove Cd2+ from aqueous solutions was tested and its removal efficiency was compared to that of granular activated carbon (GAC). Kinetics of Cd2+ removal by BPS was a two-stage process with an initial rapid adsorption showing 45% of initial Cd2+ was removed within 5 min, followed by a slower adsorption. Cadmium adsorption onto the BPS fitted the Langmuir isotherm model and maximum adsorption capacity of the BPS (63.3 mg g−1) was 1.8 times higher than that of GAC (36.1 mg g−1). Thermodynamic parameters showed that Cd2+ adsorption by BPS was favorable and endothermic. Data from XPS proved the main adsorption mechanism to be complexation of Cd2+ with sulfides in the BPS. Results demonstrated that BPS can be recycled as a novel adsorbent for Cd2+ removal from wastewater.

Excessive transport of fine sediment, and its associated pollutants, can cause detrimental impacts in aquatic environments. It is therefore important to perform accurate sediment source apportionment to identify hot spots of soil erosion. Various tracers have been adopted, often in combination, to identify sediment source type and its spatial origin; these include fallout radionuclides, geochemical tracers, mineral magnetic properties and bulk and compound-specific stable isotopes. In this review, the applicability of these techniques to particular settings and their advantages and limitations are reviewed. By synthesizing existing approaches, that make use of multiple tracers in combination with measured changes of channel geomorphological attributes, an integrated analysis of tracer profiles in deposited sediments in lakes and reservoirs can be made. Through a multi-scale approach for fine sediment tracking, temporal changes in soil erosion and sediment load can be reconstructed and the consequences of changing catchment practices evaluated. We recommend that long-term, as well as short-term, monitoring of riverine fine sediment and corresponding surface and subsurface sources at nested sites within a catchment are essential. Such monitoring will inform the development and validation of models for predicting dynamics of fine sediment transport as a function of hydro-climatic and geomorphological controls. We highlight that the need for monitoring is particularly important for hilly catchments with complex and changing land use. We recommend that research should be prioritized for sloping farmland-dominated catchments.

Adding coal ash to acid waste decreases its acidity and supplies essential nutrients to plants. The effects of coal ash on acid coal mine waste and acid mine drainage were investigated in the field. Treatments were mixtures of coal mine waste with coal ash (0, 20, and 40%). Addition of coal ash increased the pH of coal mine waste and leachate by 3.11 and 3.03 units, respectively. After stabilization, the concentrations in the leachate decreased from 4.65 to 0.44 mg L−1 for Fe and from 0.31 mg L−1 to “not detected” for Pb. The organic matter content and cation exchange capacity increased significantly (approximately twofold each), for coal mine waste with coal ash. Moreover, plant growth on coal mine waste that had been treated with coal ash was greatly stimulated. The application of coal ash offers an environmentally compatible, cost-effective way to remediate coal mine waste or leachate contaminated with heavy metals.