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The Water Quality Characteristics and Quality Status of Bengkulu River and Nelas River, Bengkulu Province: Conditions for The Last Six Years

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IOP Conference Series: Earth and environmental Science 2022年第1期950卷

作者： I Khalik A Sapei S Hariyadi E Anggraeni Natural Resources and Environmental Management Study Program Graduate School of IPB University Bogor Indonesia Public Health Study Program STIKES Tri Mandiri Sakti Bengkulu Indonesia Department of Civil and Environmental Engineering IPB University Bogor Indonesia Department of Aquatic Resources Management IPB University Bogor Indonesia Department of Agroindustrial Technology IPB University Bogor Indonesia

The existence of extractive activities around the river has a negative impact on the quality of river water. This study aims to provide an overview of water quality characteristics and water quality status of Bengkulu River and Nelas River in Bengkulu Province. The data used is river quality monitoring conducted by the Environment and Forestry Service of Bengkulu Province from 2014 to 2019. Measurements are carried out twice a year representing, the dry season (March to June) and the rainy season (September to December). The observation stations representing upstream, middle and downstream of rivers conditions. The parameters observed were physical, chemical, and biological parameters. The water quality status is determined using the Storet Index. The results show that both rivers have Storet Index >-31. It means that these river water are heavily polluted. Parameters that have exceeded the water quality standard are TSS, DO, BOD, COD, Fe, Mn, Cu, and total coliform. The river water quality parameters, especially heavy metals, may be caused by open land being washed and carried into the river body. The existence of population and animal activities as well as industrial waste outlets at upstream also affect the decline of river water quality.

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Upcycling waste polyethylene terephthalate (PET) bottles into high-performance activated carbon for electrochemical desalination

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Chemosphere 2024年 364卷 143029页

作者： Jhen-Cih Wu Jui-Yao Chang Xiangzhou Yuan Eakalak Khan Yong Sik Ok Chia-Hung Hou Graduate Institute of Environmental Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Korea Biochar Research Center APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering Korea University Seoul 02841 South Korea Ministry of Education of Key Laboratory of Energy Thermal Conversion and Control School of Energy and Environment Southeast University Nanjing 210096 China. Department of Civil and Environmental Engineering and Construction University of Nevada Las Vegas Las Vegas NV 89154 USA. Korea Biochar Research Center APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering Korea University Seoul 02841 South Korea. Electronic address: yongsikok@korea.ac.kr. Graduate Institute of Environmental Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan Research Center for Future Earth National Taiwan University No. 1 Sec. 4. Roosevelt Rd. Taipei 10617 Taiwan. Electronic address: chiahunghou@ntu.edu.tw.

Upcycling waste polyethylene terephthalate (PET) bottles has attracted intensive research interests. This simultaneously alleviates plastic pollution and achieves a waste-to-resource strategy. Waste PET water bottles were used to fabricate value-added activated carbon (AC) electrodes for capacitive deionization (CDI). The KOH activation temperature (greater than 700 °C) prominently affected the physi-chemical properties and desalination performance of PET-derived activated carbons (PET-AC). Profiting from a large Brunauer-Emmet-Teller specific surface area (1448 m g) with a good mesoporous structure (the ratio of the mesopore volume to the total pore volume was 41.3%), PET-AC-1000 (activated at 1000 °C) possessed a huge specific capacitance of 108 F g for capacitive ion storage. Moreover, when utilized as the electrode material in single-pass CDI, PET-AC-1000 exhibited a maximum electrosorption capacity of 10.82 ± 0.11 mg g and a low level of energy consumption (0.07 kWh mol), associated with good electrochemical charging-discharging cyclic stability. The results provide a promising facile approach to tackle the challenge of plastic pollution and promote the advancement of electrode materials for economic affordable and energy-efficient electrochemical desalination process, which meets the United Nations (UN) sustainable development goals (SDGs).

关键词： Activated carbon Capacitive deionization Circular economy Polyethylene terephthalate waste Sustainable development goals 6 (SDG6) Clean water and sanitation

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Direct Comparison of RT-ddPCR and Targeted Amplicon Sequencing for SARS-CoV-2 Mutation Monitoring in Wastewater

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SSRN 2022年

作者： Lou, Esther G. Sapoval, Nicolae McCall, Camille Bauhs, Lauren Carlson-Stadler, Russell Kalvapalle, Prashant Lai, Yanlai Palmer, Kyle Penn, Ryker Rich, Whitney Wolken, Madeline Ensor, Katherine B. Hopkins, Loren Treangen, Todd J. Stadler, Lauren B. Department of Civil and Environmental Engineering Rice University 6100 Main Street MS 519 HoustonTX77005 United States Department of Computer Science Rice University 6100 Main Street HoustonTX77005 United States Systems Synthetic and Physical Biology Graduate Program Rice University 6100 Main Street HoustonTX77005 United States Houston Health Department 8000 N. Stadium Dr. HoustonTX77054 United States Department of Statistics Rice University 6100 Main Street MS 138 HoustonTX77005 United States

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3;hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing. © 2022, The Authors. All rights reserved.

关键词： SARS

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Correction: Characterizing country-specific human and ecosystem health impact and damage cost of agricultural pesticides: the case for Thailand

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The International Journal of Life Cycle Assessment 2022年第12期27卷 1377-1377页

作者： Mankong, Phatchari Fantke, Peter Phenrat, Tanapon Mungkalasiri, Jitti Gheewala, Shabbir H. Prapaspongsa, Trakarn Graduate Program in Environmental and Water Resources Engineering Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand Quantitative Sustainability Assessment Department of Environmental and Resource Engineering Technical University of Denmark Kongens Lyngby Denmark Department of Civil Engineering Faculty of Engineering Naresuan University Phitsanulok Thailand Technology and Informatics Institute for Sustainability (TIIS) National Metal and Materials Technology Center (MTEC) National Science and Technology Development Agency (NSTDA) Pathum Thani Thailand The Joint Graduate School of Energy and Environment (JGSEE) King Mongkut’s University of Technology Thonburi Bangkok Thailand Centre of Excellence On Energy Technology and Environment Ministry of Higher Education Science Research and Innovation Bangkok Thailand

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Seasonal Inflow Forecasts Based on Non-Homogeneous Hidden Markov Models: The Case of Orós Reservoir, Northeastern Brazil 18

Seasonal Inflow Forecasts Based on Non-Homogeneous Hidden Ma...

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18th World environmental and Water Resources Congress 2018: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management

作者： Hernández, Luis Carlos Hernández Reis, Dirceu Silveira Environmental Technology and Water Resources Graduate Program Dept. of Civil and Environmental Engineering Univ. of Brasilia Brasília Brazil Dept. of Civil and Environmental Engineering Univ. of Brasilia Brasília Brazil

ISBN: (数字)9780784481400

ISBN: (纸本)9780784481400

This study explores the use of non-homogeneous hidden Markov models (NHMMs) to forecast streamflows into the Orós Reservoir, located in the State of Ceará, Northeastern Brazil. These models employ hydro-climatic information from a given year to predict the next year inflow. The Orós Reservoir is a key infrastructure in the water resources system of the state, where most rivers present very high temporal variability, which is a challenge for water managers. Streamflow forecast systems at the climate scale (months ahead) can be very useful for the challenging process of water allocation in the region. This paper explores the use of NHMMs to provide a probabilistic one-year ahead forecast of the mean annual flow for the Orós Reservoir. Results based on a forecast verification study based on 60 years of independent data show that NHMMs with two or three hidden states, employing the NINO3 climate index as exogenous variable, provides forecasts with an average value of the continuous ranked probability skill score of about 0.2-0.25, meaning that they are better than climatology. It is also evident that those models performed much better during dry years than during wet years, which may be related to lack of other climate indices. © 2018 American Society of civil Engineers.

关键词： Hidden Markov models

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Evolutionary polynomial modeling for interpretable drought prediction and resilient resource management

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Ecological Informatics 2025年 90卷

作者： Tulio J. Francisco Bruno da Silva Macêdo Zaher Mundher Yaseen Nikolay O. Nikitin Matteo Bodini Angela Gorgoglione Camila M. Saporetti L. Goliatt Computational Modeling Program Federal University of Juiz de Fora Juiz de Fora 35501-170 MG Brazil Systems and Automation Engineering Graduate Program Federal University of Lavras Lavras 37200-000 MG Brazil Civil and Environmental Engineering Department King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia ITMO University St. Petersburg 197101 Russian Federation Dipartimento di Economia Management e Metodi Quantitativi Università degli Studi di Milano Via Conservatorio 7 20122 Milano Italy Department of Fluid Mechanics and Environmental Engineering (IMFIA) School of Engineering Universidad de la República Montevideo 11300 Uruguay Department of Computational Modeling Polytechnic Institute Rio de Janeiro State University Nova Friburgo 22000-900 RJ Brazil Department of Computational and Applied Mechanics Federal University of Juiz de Fora Juiz de Fora 36036-900 MG Brazil

Droughts are natural hazards that exist in nature and can have a serious impact on the environment and society, which includes water shortages, crop failures, fires and, in some cases, soil manipulation. To assess and predict droughts, various methods, such as the Standardized Precipitation Index (SPI), were designed to segregate drought trends and excess rainfall over a period ranging from 3 to 48 months. This study proposes an innovative approach to predicting drought use, the Evolutionary Polynomial Expansion with Feature Selection (EPEFS) model, a hybrid method that integrates polynomial regression with feature selection to increase accuracy and interpretability. The methodology was applied to historical precipitation data from six meteorological stations in Türkiye, covering the period from 1971 to 2016. The drought index Standardized Precipitation Index (SPI) was used as the primary indicator, with predictions made for three different time scales: SPI-3, SPI-6 and SPI-12. Furthermore, a time series cross-validation strategy was employed to ensure performance assessment. The EPEFS model obtained R 2 coefficients of 0.880, 0.903 and 0.929 for SPI-3, SPI-6 and SPI-12, respectively, surpassing the other models analyzed. Furthermore, the model presented less complexity in the generated expressions. The results suggest that the EPEFS model holds promise as a robust and interpretable tool for drought forecasting, with potential applications in early warning systems and mitigation strategies.

关键词： Climate change Standardized precipitation index Machine learning Polynomial regression Feature selection

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Moisture availability and microbial activation in spacecraft 70

Moisture availability and microbial activation in spacecraft

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70th International Astronautical Congress, IAC 2019

作者： Bope, Ashleigh Haines, Sarah R. Nastasi, Nicholas Horack, John M. Meyer, Marit E. Dannemiller, Karen C. Environmental Sciences Graduate Program Ohio State University ColumbusOH43210 United States Department of Civil Environmental and Geodetic Engineering College of Engineering Ohio State University ColumbusOH43210 United States Division of Environmental Health Sciences College of Public Health Ohio State University ColumbusOH43210 United States Department of Mechanical and Aerospace Engineering College of Engineering and John Glenn College of Public Affairs Ohio State University ColumbusOH43210 United States NASA Glenn Research Center ClevelandOH44135 United States

We spend much of our time in built environments where we are continually exposed to microorganisms. Within indoor environments on earth, or in environments such as occupied spacecraft, these bacterial and fungal exposures can impact human health. Exposures to microbial growth may be particularly harmful, which is predominantly influenced by moisture availability to dust that contain microbes. This dust is hydroscopic and quickly absorbs water from the air;therefore, when ambient relative humidity levels reach a certain threshold, microbial growth will occur. Different microbial species may be harmful in different ways, but the occurrence of active growth may be the most important factor regardless of taxonomy. In confined environments such as spacecraft elevated moisture conditions are expected due to human activities such as breathing, hygiene routines, food preparation and exercise. These activities have diurnal variations which will influence the water availability for microbial growth over time. NASA has a robust monitoring program for spacecraft that is designed to eliminate or mitigate any potential health effects originating from microorganisms. However, the current standards do not account for microbial growth in spacecraft. Our goal is to propose improved microbial standards for spacecraft based on expected microbial growth due to elevated relative humidity, which is easy to measure. Standards will protect human health and spacecraft integrity. Our hypothesis is that we can determine if growth will be activated based on the number of hours per day spent above a relative humidity threshold. The environment will be considered acceptable if growth is prevented. The first step in creating these standards is to experimentally determine the time required for activation of microbial growth under various moisture conditions. We will consider currently available data collected from incubations performed on house dust from earth to estimate what the activation of mic

关键词： NASA

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Prevalence of Neonicotinoid Insecticides in Paired Private-Well Tap Water and Human Urine Samples in a Region of Intense Agriculture Overlying Vulnerable Aquifers in Eastern Iowa

SSRN

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SSRN 2022年

作者： Thompson, Darrin A. Kolpin, Dana W. Hladik, Michelle L. Lehmler, Hans-Joachim Meppelink, Shannon M. Poch, Matthew C. Vargo, John D. Soupene, Victor A. Irfan, Nafis Md. Robinson, Morgan Kannan, Kurunthachalam Beane Freeman, Laura E. Hofmann, Jonathan N. Cwiertny, David M. Field, R. William University of Iowa College of Public Health Iowa CityIA United States University of Iowa Center for Health Effects of Environmental Contamination Iowa CityIA United States U.S. Geological Survey Central Midwest Water Science Center Iowa CityIA United States U.S. Geological Survey California Water Science Center SacramentoCA United States State Hygienic Laboratory The University of Iowa Iowa CityIA United States Interdisciplinary Graduate Program in Human Toxicology University of Iowa Iowa CityIA United States University of Iowa Department of Internal Medicine Iowa CityIA United States University of Dhaka Institute of Nutrition and Food Science Dhaka Bangladesh Department of Pediatrics New York University School of Medicine New YorkNY United States Department of Environmental Medicine New York University School of Medicine New YorkNY United States Occupational and Environmental Epidemiology Branch Division of Cancer Epidemiology and Genetics National Cancer Institute RockvilleMD United States Department of Civil and Environmental Engineering University of Iowa Iowa CityIA United States Public Policy Center University of Iowa Iowa CityIA United States

A pilot study among farming households in eastern Iowa was conducted between December 2018 and February 2019 to assess human exposure to neonicotinoids. The study area was in a hydrologic setting where groundwater is vulnerable to surface-applied contaminants, and in a region of intense crop and livestock production. In addition to paired outdoor (hydrant) water and indoor (tap) water samples where private wells are being used as the source of drinking water, urine samples were collected before bedtime, during the night, and first morning void from 47 adult male pesticide applicators. Neonicotinoids (NEOs) were detected in 53% of outdoor and 55% of indoor samples, with two or more NEOs in 13% of samples. Clothianidin was the most frequently detected neonicotinoid (outdoor: 53%, maximum (max): 570.6 nanograms per liter [ng/L];indoor: 55%, max: 140.5 ng/L), followed by imidacloprid (outdoor: 13%, max: 3.0 ng/L;indoor: 11%, 29.3 ng/L), and thiamethoxam (outdoor: 6%, max: 16.1 ng/L;indoor: 6%, max: 13.1 ng/L). Human exposure was widely detected in urine samples. A median of 10 different NEOs and/or transformation products (TPs) were detected in urine, with five NEOs detected in all 115 urine samples analyzed, including clothianidin (max: 4.7 micrograms per gram [µg/g]), nitenpyram (max: 1.1 µg/g), thiamethoxam (max: 3.4 µg/g), 6-chloronicotinic acid (max: 7.0 µg/g), and thiacloprid amide (max: 1.5 µg/g). Dinotefuran (max: 2.9 µg/g), imidaclothiz (max: 15.3 µg/g), acetamiprid-N-desmethyl (max: 16.9 µg/g), and N-desmethyl thiamethoxam (max: 3.3 µg/g) were found in > 70% of urine samples. The study results indicate that while the consumption of private well tap water provides a human exposure pathway, the companion urine results provide evidence that diet and/or other exposure pathways (e.g., occupational, house dust) may contribute to exposure more than water contamination. © 2022, The Authors. All rights reserved.

关键词： Aquifers

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A robotic dating coaching system leveraging online communities posts

arXiv

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arXiv 2020年

作者： Jo, Sihyeon Joung, Eun Gyo So, Minseob Jung, Donghwi Nespoli, Giulia Seo, Seung-Woo Kim, Keonwoo Yoo, Seungryong Kim, Seong-Woo Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Technology Management Economics and Policy Program Seoul National University Seoul Korea Republic of Department of Industrial Engineering Seoul National University Seoul Korea Republic of Department of Civil and Environmental Engineering Seoul National University Seoul Korea Republic of Department of Industrial Design Seoul National University Seoul Korea Republic of Graduate School of Engineering Practice Seoul National University Seoul Korea Republic of

Can a robot be a personal dating coach? Even with the increasing amount of conversational data on the internet, the implementation of conversational robots remains a challenge. In particular, a detailed and professional counseling log is expensive and not publicly accessible. In this paper, we develop a robot dating coaching system leveraging corpus from online communities. We examine people’s perceptions of the dating coaching robot with a dialogue module. 97 participants joined to have a conversation with the robot, and 30 of them evaluated the robot. The results indicate that participants thought the robot could become a dating coach while considering the robot is entertaining rather than helpful. © 2020, CC-BY.

关键词： Social networking (online)

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Corrigendum to "Variations of oxidative potential of PM2.5 in a medium-sized residential city in South Korea measured using three different chemical assays" [920 (2024) 171053]

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The Science of the total environment 2024年 926卷 172075页

作者： Pyung-Rae Kim Sung-Won Park Young-Ji Han Myong-Hwa Lee Thomas M Holsen Cheol-Heon Jeong Greg Evans Agriculture and Life Sciences Research Institute Kangwon National University Chuncheon Gangwon-do 24341 Republic of Korea. Dept. of Interdisciplinary Graduate Program in Environmental and Biomedical Convergence Kangwon National University Chuncheon Gangwon-do 24341 Republic of Korea. Dept. of Environmental Science Kangwon National University Chuncheon Gangwon-do 24341 Republic of Korea Gangwon particle pollution research and management center Kangwon National University Chuncheon Gangwon-do 24341 Republic of Korea. Electronic address: youngji@kangwon.ac.kr. Gangwon particle pollution research and management center Kangwon National University Chuncheon Gangwon-do 24341 Republic of Korea Dept. of Environmental Engineering Kangwon National University Chuncheon Gangwon-do 24341 Republic of Korea. Dept. of Civil and Environmental Engineering Clarkson University Potsdam NY 13699 USA. Dept. of Chemical Engineering and Applied Chemistry University of Toronto Toronto Ontario MS5 3E5 Canada.

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