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World environmental and Water resources Congress 2023: Adaptive Planning and Design in an Age of Risk and Uncertainty

作者： Pasha, M. Fayzul K. Perez, Luis Weathers, Matthew Smith, Brennan Dept. of Civil and Geomatics Engineering California State Univ FresnoCA United States Water Power Program and Energy-Water Resource Systems Group Environmental Sciences Division Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (数字)9780784484852

ISBN: (纸本)9780784484852

A skeletonized water distribution system (WDS) model plays an important role in decision making process for its design and operations in planning phase. Given energy is the main driving force to operate a WDS efficiently and with the recent hikes in energy price, the investigation of energy flow in WDS is much more important than ever before. While a skeletonized network is easy to handle and takes less amount of time to run, it should represent the real-world scenario including the demand and hydraulics as accurately as possible. Failure to represent real-world scenario can mislead design and operational decisions including energy consumptions and delivery pressure. The purpose of this paper is to investigate how the energy flow in a WDS varies with the extent of the skeletonized network. Keeping the total demand constant for a network and the spatial distribution of the demand within a range in the skeletonized networks, how the energy consumption at the pump station, energy loss in the pipe, and the energy storage in the tank vary with the size of the skeletonized networks are investigated in this study. Energy balance model has been set up for each skeletonized model to observe the impact on energy flow for a series of models. Since the number of pipes and nodes can impact hydraulics, which eventually impact the energy flow, the paper considers two types of networks: branch and loop water distribution systems. The study has been applied to two hypothetical literature networks. Due to skeletonization, the flow pattern in the loop system changes more than that in the branch system causing higher percentage change of frictional energy loss in the loop system. The energy consumption or loss per unit demand per node in the skeletonized networks is found almost linear for the branch system. However, this parameter changes non-linearly in the skeletonized networks for the loop system. © World environmental and Water resources Congress *** rights reserved

关键词： Energy utilization

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Early surveillance of rice bakanae disease using deep learning and hyperspectral imaging

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aBIOTECH 2024年第3期5卷 281-297页

作者： Sishi Chen Xuqi Lu Hongda Fang Anand Babu Perumal Ruyue Li Lei Feng Mengcen Wang Yufei Liu College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China State Key Laboratory of Rice Biology and Breeding Zhejiang UniversityHangzhou 310058China Computational Modeling and Nanoscale Processing Unit National Institute of Food TechnologyEntrepreneurship and Management-ThanjavurMinistry of Food Processing IndustriesThanjavur 613005India College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China Global Education Program for AgriScience Frontiers Graduate School of AgricultureHokkaido UniversitySapporo 060-8589Japan

Bakanae disease,caused by Fusarium fujikuroi,poses a significant threat to rice production and has been observed in most rice-growing *** disease symptoms caused by different pathogens may vary,including elongated and weak stems,slender and yellow leaves,and dwarfism,as *** disease is likely to cause necrosis of diseased seedlings,and it may cause a large area of infection in the field through the transmission of ***,early disease surveillance plays a crucial role in securing rice *** monitoring methods are both time-consuming and labor-intensive and cannot be broadly *** this study,a combination of hyperspectral imaging technology and deep learning algorithms were used to achieve in situ detection of rice seedlings infected with bakanae *** data were obtained on the 9th,15th,and 21st day after rice infection to explore the physiological and biochemical performance,which helps to deepen the research on the disease *** data were obtained over these same periods of infection,and a deep learning model,named Rice Bakanae Disease-Visual Geometry Group(RBD-VGG),was established by leveraging hyperspectral imaging technology and deep learning *** on this model,an average accuracy of 92.2%was achieved on the 21st day of *** also achieved an accuracy of 79.4%as early as the 9th *** characteristic wavelengths were extracted to increase the feasibility of using portable spectral equipment for field ***,the model offers an efficient and non-destructive surveillance methodology for monitoring bakanae disease,thereby providing an efficient avenue for disease prevention and control.

关键词： Bakanae disease Hyperspectral imaging Deep learning Early surveillance Disease monitoring

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Evaluating the impact of fertilizer and crop prices on phosphorus concentrations in Great Lakes watersheds

Journal of the Agricultural and Applied Economics Associatio...

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Journal of the Agricultural and Applied Economics Association 2024年第4期3卷 756-773页

作者： Sampriti Sarkar Preet Lal Molly Sears Frank Lupi Department of Agricultural Food and Resource Economics Michigan State University East Lansing Michigan USA Environmental Science and Policy Program Michigan State University East Lansing Michigan USA Department of Civil and Environmental Engineering Michigan State University East Lansing Michigan USA

Crop and input prices affect agricultural production and water pollution. Fertilizer prices fluctuated over the past two decades, recently increasing substantially. Corn prices also increased after authorization of the Renewable Fuel Standard. This paper estimates the effect of fertilizer and corn prices on total phosphorus (TP) and dissolved phosphorus (DP) concentrations across 226 Great Lakes region watersheds. Findings indicate that a 10% rise in fertilizer prices reduces TP by 3% and DP by 6.9%. Counterfactual analysis shows that without recent fertilizer price hikes, nutrient concentrations would be higher, underscoring the impact of crop and input prices on phosphorus pollution.

关键词： corn production fertilizer application non-point source pollution phosphorus pollution

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Factors affecting the distribution of microplastics in soils of China

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Frontiers of environmental Science & engineering 2023年第9期17卷 157-176页

作者： Yin Liu Matthias CRillig Quan Liu Jingjing Huang Muhammad Amjad Khan Xiaohui Li Qin Liu Qingqing Wang Xuesong Su Linyi Lin Yang Bai Genmao Guo Yi Huang Yong Sik Ok Shan Hu Junfeng Wang Honggang Ni Qing Huang Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province/Center for Eco-Environmental Restoration Engineering of Hainan Province/State Key Laboratory of Marine Resource Utilization in South China Sea/College of Ecology and Environment Hainan UniversityHaikou 570228China Institute of Biology Ecology of PlantsFreie Universität Berlin/Berlin Brandenburg Institute of Advanced Biodiversity Research(BBIB)Berlin 14195Germany Hainan Inspection and Detection Center for Modern Agriculture Haikou 570100China Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural SciencesBeijing 100081China China College of Management and Economics Tianjin UniversityTianjin 300072China College of Environmental Sciences and Engineering Peking UniversityBeijing 100871China Korea Biochar Research Center APRU Sustainable Waste Management Program&Division of Environmental Science and Ecological EngineeringKorea UniversitySeoul 02841Republic of Korea School of Urban Planning and Design Peking University Shenzhen Graduate SchoolShenzhen 518055China

Microplastics(MPs)are found worldwide in high abundance,posing a potential threat to *** the ubiquity of MPs in the environment,very little is known about the regional distribution of MPs and underlying factors affecting this distribution in the field,which likely include human activity,but also features of the environment ***,out of a total of 1157 datapoints investigated in 53 Chinese studies,9.68%datapoints were removed as outliers in the heterogeneity *** review revealed that the abundance of MPs was highly *** addition,microplastic(MP)distribution maps based on China demonstrated that the highest abundance of MPs tended to occur near large rivers and central land affected by the intersection of two *** model-fitting and previous studies showed that MP abundance in China was correlated with longitude,agricultural mulching film usage per capita,temperature,and ***,due to the heterogeneity of MPs and the low matching degree between the current environmental data and the sampling points,this pattern was not as evident as reported in any single *** affecting the distribution of MPs can not be captured by linear relationships alone,and systematic selection of suitable environmental factors and further model optimization are needed to explore the cause of MP pollution in ***,this review revealed an uneven distribution of MPs and serves as a reference for model prediction to assess and control plastic pollution in natural soil environments.

关键词： Microplastic distribution Microplastic heterogeneity Effecting factors Agriculture Socio-economic factors

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Photocatalytic degradation of perfluorooctane sulfonic acid and perfluorooctanoic acid using titanium dioxide/graphene oxide nanocomposite immobilized on polyvinyl alcohol film

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Case Studies in Chemical and environmental engineering 2024年 10卷

作者： Boonchata, Putthicha Boontanon, Narin Jindal, Vinod Aung, Humm Kham Zan Zan Visvanathan, Chettiyappan Fujii, Shigeo Boontanon, Suwanna Kitpati Graduate Program in Environmental and Water Resources Engineering Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Research Center and Technology Development for Environmental Innovation Faculty of Environment and Resource Studies Mahidol University Department of Chemical Engineering Faculty of Engineering Mahidol University Graduate School of Global Environmental Studies Kyoto University

In full-scale units, the real application of nanoparticles photocatalytic degradation is still challenging due to the requirement of post separation for recovery of fine particles. This work investigated the removal efficiencies of perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) using titanium dioxide (TiO₂) nanoparticles coupling with graphene oxide (GO) sheets immobilized in polyvinyl alcohol (PVA) matrix via solution-casting and a heat-treatment process to achieve the TiO₂/GO/PVA nanocomposite film as a photocatalyst. The operative parameters were focused on initial solution pH value, GO concentration, and heat-treatment time, which subsequently determined the optimal indices for the catalyst film. The structure characterization of the Ti–O–C bond indicated that a strong interaction between GO and TiO₂ had been formed at the hydrolysis process while TiO₂/GO nanoparticles were chemically embedded in PVA matrix by the heat-treatment method. The photocatalytic degradation of PFOS and PFOA produced a nanocomposite film with 25 wt% TiO₂/GO that was treated at 120 °C for 3 h and exhibited a remarkable removal activity in acidic solution with a pH of 3. This condition efficiently degraded PFOS and PFOA by approximately 95.99 % and 96.89 %, respectively, through a photocatalytic reaction. This research presents a straightforward method to synthesize TiO₂/GO/PVA catalyst that influences persistent organic pollutants (POPs) under ultraviolet irradiation, which is of practical significance for environmental applications. © 2024 The Authors

关键词： Graphene oxide PFOA PFOS Photocatalytic Polyvinyl alcohol Titanium dioxide

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Production of 5-hydroxymethylfurfural from fructose via inherent catalytic properties of a biphasic system without external catalyst addition

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Green Chemistry 2023年第3期26卷 1533-1541页

作者： Huynh, Quang Tam Padilla, Alexander F. de Luna, Mark Daniel G. Huang, Po-Jung Chen, Pei-Shih Saidina Amin, Nor Aishah Chen, Ku-Fan Chang, Ken-Lin Institute of Environmental Engineering National Sun Yat-Sen University Kaohsiung804 Taiwan Energy Engineering Program National Graduate School of Engineering University of the Philippines Diliman Quezon City1101 Philippines Department of Chemical and Materials Engineering National Central University Taoyuan320317 Taiwan Department of Public Health College of Health Sciences Kaohsiung Medical University Kaohsiung Taiwan Johor Bahru Skudai81310 Malaysia Department of Civil Engineering National Chi Nan University Nantou545 Taiwan Net Zero Emissions and Resource Recycling Technology Research Center National Sun Yat-Sen University Kaohsiung804 Taiwan

5-Hydroxymethylfurfural (5-HMF) is the key to unlocking the potential of biomass materials to transform into fuels, materials, and chemicals. In this study, an effective biphasic reaction system composed of a reaction phase (aqueous phase) and an extraction phase (organic phase) was used for the conversion of fructose to 5-HMF. Deep eutectic solvents (DESs) composed of different hydrogen bond donors and hydrogen bond acceptors, the ionic liquid [BMIM]Cl, aqueous choline chloride, aqueous betaine hydrochloride, and ethylamine hydrochloride were used as the reaction phase, and different organic solvents, such as methyl isobutyl ketone (MIBK), dimethyl sulfoxide (DMSO), toluene, ethyl butyrate, and gamma-valerolactone (GVL), were used as the organic phase. Experiments were conducted under optimal conditions simulated using the reaction surface method to obtain the maximum 5-HMF yield. The highest yields of 5-HMF obtained in reactions with DESs were 67.86%, 68.69%, and 71.40% for ChCl : OA, ChCl : Lac, and EaCl : Lac, respectively. However, adding dimethyl sulfoxide and betaine hydrochloride aqueous solution to the fructose conversion system resulted in a maximum yield of 90.42% ± 1.46% of 5-HMF without the use of catalysts. This study also demonstrated that betaine hydrochloride could be effectively reused four times. A 5-HMF yield of at least 80% indicates a green process suited towards sustainable development. © 2024 The Royal Society of Chemistry.

关键词： Fructose

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Application of Machine Learning in Daily Reservoir Inflow Prediction of the Bhumibol Dam, Thailand 19

Application of Machine Learning in Daily Reservoir Inflow Pr...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Kraisangka, Jidapa Rittima, Areeya Sawangphol, Wudhichart Phankamolsil, Yutthana Tabucanon, Allan Sriratana Talaluxmana, Yutthana Vudhivanich, Varawoot Mahidol University Faculty of ICT Nakhon Pathom Thailand Mahidol University Faculty of Engineering Nakhon Pathom Thailand Mahidol University Environmental Engineering and Disaster Management Program Kanchanaburi Thailand Mahidol University Faculty of Environment and Resource Studies Nakhon Pathom Thailand Kasetsart University Faculty of Engineering Bangkok Thailand Kasetsart University Faculty of Engineering at Kamphaengsaen Nakhon Pathom Thailand

ISBN: (纸本)9781665485845

To mitigate floods and droughts in Thailand, the reservoir operations need accurate and reliable hydro-parameter information, e.g., inflow, to support decision making. In this paper, we explore and develop the predictive models for predicting the next-day inflow of the Bhumibol Dam, one of the major reservoirs of Thailand. We applied the machine learning techniques including decision tree, support vector regression, random forest, and extreme gradient boosting (XGBoost). Daily reservoir and climate Data from 2000 to 2021 were used in the analysis. After the series of experiments of model development, we finalize the model with the random forest algorithm having the best performance of MAE=4.232, MSE=83.823, and R2=0.867. However, we believe that the models and the feature sets can be further explored and developed to achieve the better accuracy. As a result, we could practically incorporate the inflow prediction model to aid decision making in the reservoir operation. © 2022 IEEE.

关键词： Reservoirs (water)

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Impacts of Faculty Development on Interdisciplinary Undergraduate Teaching and Learning in the Food-Energy-Water Nexus

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Journal of College Science Teaching 2022年第6期51卷 66-74页

作者： Sommers, Amie S. White, Holly Dauer, Jenny M. Forbes, Cory STEM education specialist in the Engineering and Computing Education Core College of Engineering University of Nebraska-Lincoln United States Ecology and Environmental Sciences program at the University of Maine United States School of Natural Resources at the University of Nebraska-Lincoln United States Department of Curriculum and Instruction Science Education STEM Education Research Collaboratorium and Resource Center College of Education University of Texas Arlington United States

To support undergraduate instruction and learning outcomes (i.e., systems thinking and decision-making in interdisciplinary contexts) grounded in the Food-Energy-Water Nexus (FEWNexus), we implemented a multiyear faculty development program around a new minor. In this article, we build on a previous study to investigate teaching in FEW Nexus minor courses, as well as student outcomes before and after participation in the faculty development program. We analyzed video recordings of courses to identify teaching style and scored pre- and postcourse student assessments of decision-making and systems thinking quantitatively. Post-program teaching was more student centered (50%) than pre-program (37.5%;p = 1.9e^-6). Faculty who taught courses with longer class periods incorporated more active learning than in short class periods (pre: p = 2.2e^-16;post: p = 2.2e^-16). Despite changes in instruction, we did not observe changes in decision-making and systems thinking outcomes. However, results indicate that providing faculty with resources and time can facilitate implementation of best practices and that further support and research are needed to connect these practices with positive outcomes. © 2022 National Science Teaching Association.

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Predicting rice diseases using advanced technologies at different scales: present status and future perspectives

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aBIOTECH 2023年第4期4卷 359-371页

作者： Ruyue Li Sishi Chen Haruna Matsumoto Mostafa Gouda Yusufjon Gafforov Mengcen Wang Yufei Liu College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China State Key Laboratory of Rice Biology and Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and InsectsZhejiang UniversityHangzhou 310058China Department of Nutrition and Food Science National Research CentreGiza 12622Egypt Central Asian Center for Development Studies New Uzbekistan UniversityTashkent 100000Uzbekistan Global Education Program for AgriScience Frontiers Graduate School of AgricultureHokkaido UniversitySapporo 060-8589Japan

The past few years have witnessed significant progress in emerging disease detection techniques foraccurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focuson image processing techniques using machine learning (ML) and deep learning (DL) models related tomulti-scale rice diseases. Furthermore, we summarize applications of different detection techniques,including genomic, physiological, and biochemical approaches. In addition, we also present the state-ofthe-art in contemporary optical sensing applications of pathogen–plant interaction phenotypes. Thisreview serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice cropsthrough ML and DL models.

关键词： Artificial intelligence Rice disease Model algorithms Imaging technology Plant-pathogen interactions High-throughput data

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Health risk assessment of soil contamination with heavy metals in a child care center co-located in vicinity to small scale industrial area: Case study of Thailand

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Case Studies in Chemical and environmental engineering 2024年 9卷

作者： Simatupang, Cathleen Ariella Santhaweesuk, Kanitthika Strezov, Vladimir Pongkiatkul, Prapat Boontanon, Narin Jindal, Ranjna Boontanon, Suwanna Kitpati Graduate Program in Environmental and Water Resources Engineering Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Nakhon Pathom 73170 Thailand School of Natural Sciences Faculty of Science and Engineering Macquarie University 2109 NSW Australia Department of Environmental Engineering King Mongkut's University of Technology Thonburi Bangkok 10800 Thailand Faculty of Environment and Resource Studies Mahidol University Nakhon Pathom 73170 Thailand Environmental Engineering and Management Program Department of Energy Environment and Climate Change School of Environment and Resources Development Asian Institute of Technology Pathumthani 12120 Thailand Graduate School of Global Environmental Studies Kyoto University Yoshida Sakyo-Ku Kyoto 606-8501 Japan

environmental impacts of small scale industries are still not well investigated, especially for estates where multiple small scale industries are clustered causing cumulative effects potentially impacting most vulnerable groups. This study aimed to investigate the concentrations of heavy metals (Mn, Fe, Ni, Cu, Pb, Al, Zn, and Cr) and the metalloid (As) in surface soils near the intensely active small-scale industrial area in Thailand, assess the contamination levels in the co-located child care center, and estimate potential human health risks from exposure to the heavy metals. Surface soil heavy metal(loid) elements were evaluated across a background area, area near main roads, a small-scale industrial area, and a child care centre. The concentrations of Al were found be the highest at all investigation sites, with the most elevated concentrations observed in the small-scale industrial area. The concentration of Pb in the industrial area reached 1176 mg/kg, exceeding the national standard and acceptable limit. Moreover, the contamination level for Cu, Pb, and Zn in the industrial area imply a considerable risk with enrichment factor EF > 40, and geo-accumulation index Igeo ≥5. Heavy metal levels (Ni, Cu, Pb) in the soil near the road and the child care center were similar, suggesting shared contamination sources. Conversely, Al, Zn, As, and Cr in the child care center had slightly higher concentrations than near the road but lower than the small-scale industrial area, indicating potential industrial influence on metal levels within the child care center. The principal component analysis showed Mn and Fe distributed in the background, while As, Pb, Ni, Cu, Al, Zn, and Cr accumulated in the small-scale industrial area. The findings indicate that small-scale industrial activities contribute to elevated levels of heavy metals in the soil, particularly within the child care center, posing significant ingestion risks, especially for children (HI > 1). Implementing conta

关键词： Children Contamination sources environmental impact PCA Surface soil

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