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Remediation of soil and groundwater contaminated with organic chemicals using stabilized nanoparticles: Lessons from the past two decades

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Frontiers of environmental Science & engineering 2020年第5期14卷 83-102页

作者： Zhengqing Cai Xiao Zhao Jun Duan Dongye Zhao Zhi Dang Zhang Lin National Engineering Lab for High-concentration Refractory Organic Wastewater East China University of Science and TechnologyShanghai 200237China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China College of Water Resources&Civil Engineering China Agricultural UniversityBeijing 100083China Environmental Engineering Program Department of Civil EngineeringAuburn UniversityAuburnAL 36849USA School of Environment and Energy South China University of TechnologyGuangzhou 510006China

Due to improved soil deliverability and high reactivity,stabilized nanoparticles have been studied for nearly two decades for in situ remediation of soil and groundwater contaminated with organic *** large amounts of bench-and field-scale experimental data have demonstrated the potential of the innovative technology,extensive research results have also unveiled various merits and constraints associated different soil characteristics,types of nanoparticles and particle stabilization ***,this work aims to critically overview the fundamental principles on particle stabilization,and the evolution and some recent developments of stabilized nanoparticles for degradation of organic contaminants in soil and *** specific objectives are to:1)overview fundamental mechanisms in nanoparticle stabilization;2)summarize key applications of stabilized nanoparticles for in situ remediation of soil and groundwater contaminated by legacy and emerging organic chemicals;3)update the latest knowledge on the transport and fate of stabilized nanoparticles;4)examine the merits and constraints of stabilized nanoparticles in environmental remediation applications;and 5)identify the knowledge gaps and furore research needs pertaining to stabilized nanoparticles for remediation of contaminated soil and *** instructions of this invited special issue,this review is focused on contributions from our group(one of the pioneers in the subject field),which,however,is supplemented by important relevant works by *** knowledge gained is expected to further advance the science and technology in the environmental applications of stabilized nanoparticles.

关键词： Stabilized nanoparticle In-situ remediation Organic contaminant Soil remediation Groundwater Fate and transport

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Assessing the Performance of Machine Learning Algorithms for water Level Prediction in the Chao Phraya River and its Tributaries: A Focus on Low and High water Levels

SSRN

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SSRN 2024年

作者： Priyasiri, Wilmat D.S.M. Rittima, Areeya Kraisangka, Jidapa Sawangphol, Wudhichart Phankamolsil, Yutthana Talaluxmana, Yutthana Graduate Program in Environmental and Water Resources Engineering Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Thailand Faculty of Information and Communication Technology Mahidol University Thailand Environmental Engineering and Disaster Management Program Mahidol University Kanchanaburi Campus Thailand Department of Water Resources Engineering Faculty of Engineering Kasetsart University Thailand

High precision of hydrological prediction is crucial for real–time operation of flood and drought risk mitigation and strategic planning. This study assessed the predictive performances of three Machine Learning (ML) algorithms;XGBoost, Random Forest (RF), and Multi–Layer Neural Networks (MLNNs) for water level prediction with a focus on low and high water levels. The one–day and one–week water level prediction models for six key gauged stations along the Chao Phraya River and its major tributaries were accordingly developed. Selecting the combination of input features was carried out and structured in the prediction model at all gauged stations based on the physical river–reservoir system using past water level, rainfall, controlled reservoir outflow, and upstream discharges with different travel times. The statistical evaluation indicated that both XGBoost and RF, the tree–based ML models, with rainfall input robustly outperformed than MLNNs, as it strongly achieved higher R2 from 0.957 to 0.999 for model training and from 0.743 to 0.995 for model testing and lower MAE, MSE, and RMSE values for all prediction scenarios. Among these three ML algorithms applied for daily prediction, RF demonstrated the superior performance for low water level prediction exhibiting the smallest percentage error of overestimating lying between +0.0088% and +0.9380%. XGBoost, RF, and MLNNs, demonstrated acceptable performance level for high water level prediction as it shows small percentage error of both overestimating and underestimating lying between –2.2696% and +1.1587%. Additionally, it can capture the entire testing dataset with high precision than weekly model. © 2024, The Authors. All rights reserved.

关键词： Rain

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Estimation of groundwater recharge using wetspass model in the Phanom Thuan Song Phi Nong-Bang Len Operation and maintenance projects, Thailand 22

Estimation of groundwater recharge using wetspass model in t...

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22nd Congress of the International Association for Hydro-Environment engineering and Research-Asia Pacific Division: Creating Resilience to water-Related Challenges, IAHR-APD 2020

作者： Teerapunyapong, Pattarapong Phankamolsil, Yutthana Rittima, Areeya Talaluxmana, Yutthana Tabucanon, Allan Sriratana Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand Environmental Engineering and Disaster Management Program Diversion of Engineering Mahidol University Kanchanaburi Thailand Department of Water Resources Engineering Faculty of Engineering Kasetsart University Bangkok Thailand Faculty of Environment and Resource Studies Mahidol University Nakhon Pathom Thailand

WetSpass model was applied in this study to simulate and visualize the distribution of groundwater recharge and amount of yearly and seasonal averages groundwater recharge during 2000-2017. The study area covers the Phanom Thuan-Song Phi Nong-Bang Len Operation and Maintenance Projects in western region of Thailand where groundwater has been used as an alternative source of water for irrigation and industrial sectors. The recharge rates performed by WetSpass model were consequently compared with those achieved by empirical relations namely;Chaturvedi Formula (CF), Sehgal Formula (SF), Krishna Rao Formula (KRF), and Bhattacharya Formula (BF). It was exhibited that average rate of yearly groundwater recharge for calibration periods during 2000-2010 was 178.05 mm/yr with RMSE, r2, and d of 48.72 mm, 0.78 and 0.66, respectively. However, average rate of groundwater recharge for validation periods during 2011-2017 was slightly increased which was 186.35 mm/yr with RMSE, r2, and d of 55.09 mm, 0.24 and 0.53, respectively. The simulation result obtained from WetSpass shows that the average annual recharges in the Phanom Thuan, Song Phi Nong, and Bang Len Operation and Maintenance Projects are 22.5%, 22.4%, and 14.8% of average annual rainfall, respectively according to the different soil types. The average groundwater recharges in clay, loam soil, and sandy loam soils are approximately 14.8%, 24.6%, and 25.7% of average annual rainfall, respectively. Moreover, groundwater recharges in dry and wet seasons are quantified as 12.0%, and 88.0% of average annual recharge due to seasonal variation of rainfall magnitudes. © 2020 22nd Congress of the International Association for Hydro-Environment engineering and Research-Asia Pacific Division, IAHR-APD 2020: "Creating Resilience to water-Related Challenges". All rights reserved.

关键词： Rain

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Statistical analysis of chemical release rates from soils

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Soil and Sediment Contamination 1999年第5期8卷 541-558页

作者： Opdyke, Daniel R. Loehr, Raymond C. Environmental and Water Resources Engineering Program University of Texas at Austin Austin TX 78712 United States

Two statistical methods for determining the precision of best-fit model parameters generated from chemical rate of release data are discussed. One method uses the likelihood theory to estimate marginal confidence intervals and joint confidence regions of the release model parameters. The other method uses Monte Carlo simulation to estimate statistical inferences for the release model parameters. Both methods were applied to a set of rate of release data that was generated using a field soil. The results of this evaluation indicate that the precision of F (the fraction of a chemical in a soil that is released quickly) is greater than the precision of k1 (the rate constant describing fast release), which is greater than the precision of k2 (the rate constant describing slow release). This occurs because more data are taken during the time period described by F and k1 than during the time period described by F and k2. In general, estimates of F will be relatively precise when the ratio of k1 to k2 is large, estimates of k1 for soil/chemical matrices with a high F will be relatively precise, and estimates of k2 for soil/chemical matrices with a low F will be relatively precise, provided that sufficient time is allowed for full release.

关键词： Chemical release Diesel Endpoints Monte carlo Soils

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Projecting Spatial Patterns of Flood Hazard: Recent Climate and Future Changes over Yangtze River Basin

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Chinese Journal of Population,resources and Environment 2010年第3期8卷 83-88页

作者： He Shanfeng Ge Quansheng Wu Shaohong Dai Erfu Shi Chunjian Li Mingqi Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China Henan Polytechnic University Jiaozuo Henan 454000 China Graduate School of Chinese Academy of Sciences Beijing 100049 China Environmental and Water Resources Engineering University of Delaware Newark DE 19716 USA

Projection of hazard changes in climate extremes is critical to assessing the potential impacts of climate change on human and natural systems. Using simulations of providing regional climates for impacts studies, five indicators (rainstorm days, maximum 3-day precipitation, elevation, gradient and distance from river or lake) were selected to project the spatial patterns of flood hazard over Yangtze River Basin for the baseline period (1961– 1990) and future (2011–2100) under SRES B2 scenario. The results showed the mean annual rainstorm days over the basin by the near-term, mid-term and long-term would increase from 3.9 days to 4.7, 4.9 and 5.1 days, and the mean annual maximum 3-day precipitation from 122 mm to 143, 146 and 149 mm, respectively. The flood hazard of the basin would become more severe, especially in the middle and lower reaches. Flood hazard grade 5 by the nearterm, mid-term and long-term would extend from 10.99% to 25.46, 28.14 and 29.75%, respectively.

关键词： climate change extreme weather event SRES B2 scenario PRECIS synthetic weighted mark method

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Human-nature relationships and its implications on the management of eastern arc water catchments of Tanzania

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water Science 2023年第1期37卷 11-17页

作者： Lema, M.W. Kapinga, A.G. Madamombe, G.T. Kwawuvi, D. Department of Environmental Engineering and Management University of Dodoma Dodoma Tanzania Department of Environmental Management Pan Africa University Life and Earth Sciences Institute (PAULESI) University of Ibadan Ibadan Nigeria Environmental Management Renewable Energy and Climate Change Research Centre Harare Institute of Technology Harare Zimbabwe Graduate Research Program on Climate Change and Water Resources University of Abomey-Calavi du Benin Abomey Benin

This study is aimed at understanding the Human–Nature Relationships (HNRs) in the Lower Mngeta and Upper Zigi catchments, as parts of Eastern Arc water catchment areas, in the United Republic of Tanzania. This study employed the Theory of Planned Behavior (TPB) and Norm-Activation Model (NAM) to understand the position of humans in the two catchments’ ecosystems. The study design involved Focus Group Discussions, Key Informant Interview, and Household Questionnaire Surveys. A total of 310 (185 males and 125 females) villagers were involved in this study. Furthermore, four HRN typologies, master over nature, partner with nature, a participant in nature, and steward of nature, were adopted. The study findings indicated that there was no significant difference (X ² test, p > 0.05) in HNRs between the two catchments. Moreover, master over nature typology was dominant in both catchments, with values of 59.4% (n = 200) and 59.5% (n = 85) in Lower Mngeta and Upper Zigi, respectively. The main reason is that HNR is dependent on the nature of the livelihood activities and the mode of subsistence of a particular community. It was also found that the communities in Lower Mngeta and Upper Zigi catchments are mostly dependent on agricultural and hunting activities that highly depended on the two catchment resources. This study, therefore, recommends an increase in the level of community participation in all decision-making activities, as well as an increase in environmental education for sustainable utilization and management of the two catchment resources. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Catchment master Mngeta participant Zigi

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Heavy metals in agricultural soil in China: A systematic review and meta-analysis

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Eco-Environment & Health 2022年第4期1卷 219-228页

作者： Moyan Wen Ziqi Ma Daniel BGingerich Xiao Zhao Dongye Zhao College of Water Resources and Civil Engineering China Agricultural UniversityBeijing 100083China Department of Civil Environmental and Geodetic EngineeringThe Ohio State UniversityColumbusOH 43210USA Department of Integrated Systems Engineering The Ohio State UniversityColumbusOH 43210USA Environmental Engineering Program Department of Civil EngineeringAuburn UniversityAuburnAL 36849USA

Research about farmland pollution by heavy metals/metalloids in China has drawn growing ***,there was rare information on spatiotemporal evolution and pollution levels of heavy metals in the major grainproducing *** extracted and examined data from 276 publications between 2010 and 2021 covering five major grain-producing regions in China from 2010 to *** evolution characteristics of main heavy metals/metalloids was obtained by *** addition,subgroup analyses were carried out to study preliminary correlations related to accumulation of the ***(Cd)was found to be the most prevailing pollutant in the regions in terms of both spatial distribution and temporal *** Huang-Huai-Hai Plain was the most severely *** of Cd,mercury(Hg)and copper(Cu)increased from 2010 to 2015 when compared with the 1990 background ***,the levels of five key heavy metals(Cd,Cu,Hg,lead[Pb]and zinc[Zn])showed increasing trends from 2016 to 2021 in all five *** pH and mean annual precipitation had variable influences on heavy metal *** soil and areas with less rainfall faced higher pollution *** cropped with mixed species showed smaller effect sizes of heavy metals than those with single upland crop,suggesting that mixed farmland use patterns could alleviate the levels of heavy metals in *** various soil remediation efforts,farmland projects only held a small market *** findings are important to support the research of risk assessment,regulatory development,pollution prevention,fund allocation and remediation actions.

关键词： Heavy metal Agricultural soil Soil pollution Meta-analysis Spatiotemporal evolution

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Optimizing land use for carbon neutrality: A scenario analysis in the Jakarta metropolitan area

Sustainable Futures

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Sustainable Futures 2025年 9卷

作者： Runsen Zhang Chui Ying Lee Marissa Malahayati Yan Xu Shin-ichi Onodera Mitsuyo Saito Iwan Ridwansyah Ruci Wang Graduate School of Frontier Sciences The University of Tokyo Kashiwa 2778563 Japan Town & Gown Innovation Institute for Future Hiroshima University Higashi-Hiroshima 7398521 Japan Environment Natural Resources and the Blue Economy (ENB) World Bank-Indonesia Representative Office Jakarta 12190 Indonesia School of Geography Science and Geomatics Engineering Suzhou University of Science and Technology Suzhou 215009 China Graduate School of Advanced Science and Engineering Hiroshima University Higashi-Hiroshima 7398521 Japan Research Center for Limnology and Water Resources National Research and Innovation Agency (BRIN) Bogor 16911 Indonesia Center for Environmental Remote Sensing Chiba University Chiba 2638522 Japan

This study developed a model for optimizing land use for carbon neutrality, integrating land use demand forecasting and spatial allocation models to systematically analyze land use changes in the Jakarta metropolitan area. The model incorporated carbon dioxide (CO 2 ) emission constraints to direct the structural optimization and spatial distribution of land use, with the aim of minimizing overall CO 2 emissions. Using a combination of mixed-integer programming, discrete choice models, and cellular automata (CA), the model effectively simulated land use dynamics, considering various spatial factors and constraints. The model’s accuracy was validated through numerical simulations, revealing a high degree of alignment with observed data. Scenario simulations identified the significant impacts of different development strategies on land use patterns and CO 2 emissions. The largest increase in CO 2 emissions was observed under the high economic development scenario due to rapid urbanization and industrialization, whereas the low-carbon development scenario resulted in a slower growth in emissions, highlighting the effectiveness of sustainable land use strategies. The findings highlight the importance of integrating land use models with carbon emission assessments to support sustainable development and achieve carbon neutrality goals in rapidly urbanizing regions such as Jakarta.

关键词： Carbon neutrality Jakarta Land use Optimization model Scenario simulation

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Change of winter wheat planting area and its impacts on groundwater depletion in the North China Plain

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Journal of Geographical Sciences 2019年第6期29卷 891-908页

作者： WU Xifang QI Yongqing SHEN Yanjun YANG Wei ZHANG Yucui KONDOH Akihiko Graduate School of Science and Engineering Chiba University Key Laboratory of Agricultural Water Resources Hebei Key Laboratory of Water-Saving AgricultureCenter for Agricultural Resources ResearchInstitute of Genetics and Developmental BiologyCAS Center for Environmental Remote Sensing Chiba University

The North China Plain is one of the most water-stressed areas in China. Irrigation of winter wheat mainly utilizes groundwater resources, which has resulted in severe environmental problems. Accurate estimation of crop water consumption and net irrigation water consumption is crucial to guarantee the management of agricultural water resources. An actual crop evapotranspiration(ET) estimation model was proposed, by combining FAO Penman-Monteith method with remote sensing data. The planting area of winter wheat has a significant impact on water consumption; therefore, the planting area was also retrieved. The estimated ET showed good agreement with field-observed ET at four stations. The average relative bias and root mean square error(RMSE) for ET estimation were –2.2% and 25.5 mm, respectively. The results showed the planting area and water consumption of winter wheat had a decreasing trend in the Northern Hebei Plain(N-HBP) and Southern Hebei Plain(S-HBP). Moreover, in these two regions, there was a significant negative correlation between accumulated net irrigation water consumption and groundwater table. The total net irrigation water consumption in the N-HBP and S-HBP accounted for 12.9×10~9 m^3 and 31.9×10~9 m^3 during 2001–2016, respectively. Before and after 2001, the decline rate of groundwater table had a decreasing trend, as did the planting area of winter wheat in the N-HBP and S-HBP. The decrease of winter wheat planting area alleviated the decline of groundwater table in these two regions while the total net irrigation water consumption was both up to 28.5×10~9 m^3 during 2001–2016 in the Northwestern Shandong Plain(NW-SDP) and Northern Henan Plain(N-HNP). In these two regions, there was no significant correlation between accumulated net irrigation water consumption and groundwater table. The Yellow River was able to supply irrigation and the groundwater table had no significant declining trend.

关键词： North China Plain planting area winter wheat remote sensing net irrigation water consumption

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Changes in toxicity and mobility resulting from bioremediation processes

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Bioremediation Journal 1997年第2期1卷 149-163页

作者： Loehr, Raymond C. Webster, Matthew T. Environmental and Water Resources Engineering Program Civil Engineering Department University of Texas at Austin Austin TX 78712 United States

Bioremediation is a commonly used process for the remediation of soils and sludges containing hydrocarbon compounds. The extent of chemical concentration reduction that occurs in bioremediation processes and the concentration of residual chemicals varies widely for different soils and sludges and for different processes. Along with changes in chemical concentration, measures of toxicity and chemical mobility are important information as site remediation decisions are increasingly being made within a risk-based corrective action framework. This review article presents illustrative data from studies that evaluated the effectiveness of bioremediation processes and that contained information about changes in chemical mobility and soil or sludge toxicity. The weight-of-evidence data presented indicated that, as part of the bioremediation process, there is a reduction of the apparent toxicity of the soils and sludges that were treated. In addition, remaining chemical constituents generally were less mobile. The patterns were consistent for both laboratory and field-scale bioremediation studies. © 1997 by Battelle Memorial Institute.

关键词： Hydrocarbons

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