Water Quality Research Journal最新文献_第3页

Passive monitoring of soluble pesticides linked to cannabis cultivation: a multi-scale analysis 与大麻种植有关的可溶性农药被动监测:多尺度分析

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-11-17 DOI: 10.2166/wqrj.2022.101

Ivan D. Medel, M. Gabriel, Greta M Wengert, M. Filigenzi, D. Clifford

{"title":"Passive monitoring of soluble pesticides linked to cannabis cultivation: a multi-scale analysis","authors":"Ivan D. Medel, M. Gabriel, Greta M Wengert, M. Filigenzi, D. Clifford","doi":"10.2166/wqrj.2022.101","DOIUrl":"https://doi.org/10.2166/wqrj.2022.101","url":null,"abstract":"\u0000 Several studies have documented the use of pesticides in cannabis cultivation. In northern California, one of the top cannabis production regions, several studies have identified cannabis-related impacts on multiple terrestrial wildlife species. To date, research has not focused on the potential for cannabis-related pesticides to contaminate downstream waterways and aquatic species. We conducted a two-part multi-scale study utilizing polar organic chemical integrative samplers (POCIS) to monitor pesticide contamination (1) immediately downstream and upstream of illegal public land cannabis cultivation complexes in low-order tributaries and (2) below a gradient of private land cannabis cultivation operations within higher-order streams. Diazinon and carbofuran were confirmed within sensitive headwater streams downstream of illegal public land cultivation sites in remote settings within four National Forests. Diazinon demonstrated higher downstream transport potential, with overland and in-stream flow distances totaling up to 186 m downstream of cultivation areas. While carbofuran displayed greater temporal longevity, being detected over 490 days after the last estimated pesticide application, no positive detections were identified within POCIS deployed within higher-order catchments. The utility of targeted POCIS deployed within low-order catchments is validated and confirms downstream cannabis-related water contamination on National Forest lands.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45770584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diffuse agricultural pollution of groundwater: addressing impacts in Denmark and Eastern England 地下水的农业扩散污染：应对丹麦和英格兰东部的影响

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-11-16 DOI: 10.2166/wqrj.2022.022

S. Foster, T. Bjerre

引用次数: 2

A simulation–optimization framework for reducing thermal pollution downstream of reservoirs 减少水库下游热污染的模拟优化框架

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-10-31 DOI: 10.2166/wqrj.2022.018

M. Sedighkia, B. Datta, S. Razavi

引用次数: 0

Removal of acid yellow dye 17 from aqueous solutions using an activated bone char 用活化的骨炭从水溶液中去除酸性黄色染料17

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-10-25 DOI: 10.2166/wqrj.2022.016

Agegnehu Alemu, Endalkachew Kerie

{"title":"Removal of acid yellow dye 17 from aqueous solutions using an activated bone char","authors":"Agegnehu Alemu, Endalkachew Kerie","doi":"10.2166/wqrj.2022.016","DOIUrl":"https://doi.org/10.2166/wqrj.2022.016","url":null,"abstract":"\u0000 Textile dyes are causing serious environmental problems in the world. The treatment of dyes from textile wastewater is necessary to protect the environment. Adsorbents with high adsorption potential from local materials are required to solve these problems. In this study, the treatment of acid yellow 17 dye from aqueous solutions was carried out using an activated bone char, collected from slaughterhouses. The dye removal performance was measured using a UV-Vis spectrometer. Adsorption experiments were carried out in a batch process under different operating conditions including initial dye concentration, adsorbent dose, contact time, and solution pH. From the experimental data, the maximum dye removal efficiency of 91.43% was achieved at an optimum pH of 2, contact time of 120 min, initial dye concentration of 50 mg/L, and adsorbent dose of 20 g/L. The adsorption models: adsorption isotherm and adsorption kinetics of acid yellow 17 dye onto the activated animal bone char, data fitted well with the Langmuir isotherm model (R2 = 0.9245) and pseudo-second-order model (R2 = 0.9967), respectively. This study indicated that the activated bone char, which is obtained from animal slaughterhouses and discharged as waste into the environment has a high potential to remove acid yellow 17 dye from polluted water.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43254513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Machine learning-based prediction of harmful algal blooms in water supply reservoirs 基于机器学习的供水水库有害藻华预测

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-10-19 DOI: 10.2166/wqrj.2022.019

Bongseok Jeong, Maria Renee Chapeta, Mingu Kim, Jinho Kim, Jihoon Shin, YoonKyung Cha

{"title":"Machine learning-based prediction of harmful algal blooms in water supply reservoirs","authors":"Bongseok Jeong, Maria Renee Chapeta, Mingu Kim, Jinho Kim, Jihoon Shin, YoonKyung Cha","doi":"10.2166/wqrj.2022.019","DOIUrl":"https://doi.org/10.2166/wqrj.2022.019","url":null,"abstract":"\u0000 Harmful algal blooms (HABs) pose a potential risk to human and ecosystem health. HAB occurrences are influenced by numerous environmental factors; thus, accurate predictions of HABs and explanations about the predictions are required to implement preventive water quality management. In this study, machine learning (ML) algorithms, i.e., random forest (RF) and extreme gradient boosting (XGB), were employed to predict HABs in eight water supply reservoirs in South Korea. The use of synthetic minority oversampling technique for addressing imbalanced HAB occurrences improved classification performance of the ML algorithms. Although RF and XGB resulted in marginal performance differences, XGB exhibited more stable performance in the presence of data imbalance. Furthermore, a post hoc explanation technique, Shapley additive explanation was employed to estimate relative feature importance. Among the input features, water temperature and concentrations of total nitrogen and total phosphorus appeared important in predicting HAB occurrences. The results suggest that the use of ML algorithms along with explanation methods increase the usefulness of predictive models as a decision-making tool for water quality management.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45529160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Impact of water characteristics on UV disinfection of unfiltered water 水质特性对未过滤水紫外线消毒的影响

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-10-17 DOI: 10.2166/wqrj.2022.006

Mehrnaz Soleimanpour Makuei, Faezeh Ketabchi, Nicolás M. Peleato

{"title":"Impact of water characteristics on UV disinfection of unfiltered water","authors":"Mehrnaz Soleimanpour Makuei, Faezeh Ketabchi, Nicolás M. Peleato","doi":"10.2166/wqrj.2022.006","DOIUrl":"https://doi.org/10.2166/wqrj.2022.006","url":null,"abstract":"\u0000 The objective of this study was to examine the impact of unfiltered water conditions on UV disinfection. UV biodosimetry tests were conducted over a year using water samples from two treatment plants that apply UV without filtration. The influence of turbidity, absorbance, and zeta potential on UV dose–response curves was analyzed to evaluate relationships between unfiltered water quality and log-inactivation of surrogate organisms. It was observed that diminishing inactivation with increasing UV dose (tailing effect) was governed principally by the surface charge of particulate matter. The increased tailing level observed in raw waters was postulated to be due to having more neutral surface charges, resulting in elevated electrostatic attraction between particles and microorganisms that increased UV resistance. Inactivation at a dose of 35 mJ/cm2 in water samples with low turbidity levels (0.38 NTU) and relatively negative surface charge resulted in 3.0 log-removal in comparison with 2.2 and 2.0 log-removal for samples with turbidity levels of 1.57 and 0.61 NTU, respectively. The results of this study highlight the risks of UV disinfection of unfiltered supplies with respect to the effects of water quality characteristics on UV effectiveness and could be employed to optimize the estimation of UV disinfection potential.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45968409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative photo-degradative treatment of dyeing industry wastewater containing diazo dye by UV/Peroxydate and UV/Persulfate − oxidation processes UV/过氧酸盐和UV/过硫酸盐氧化法对比光降解染料废水

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-09-05 DOI: 10.2166/wqrj.2022.012

Yasmine Laftani, Baylassane Chatib, A. Boussaoud, M. Hachkar, Mohammed El Makhfouk

{"title":"Comparative photo-degradative treatment of dyeing industry wastewater containing diazo dye by UV/Peroxydate and UV/Persulfate − oxidation processes","authors":"Yasmine Laftani, Baylassane Chatib, A. Boussaoud, M. Hachkar, Mohammed El Makhfouk","doi":"10.2166/wqrj.2022.012","DOIUrl":"https://doi.org/10.2166/wqrj.2022.012","url":null,"abstract":"\u0000 Generation of anion sulfate radicals (SO4•−) and hydroxyl radicals (HO•) by UV/Persulfate and the UV/Peroxydate processes have been successfully studied to degrade Ponceau S dye. Under [PS] = 0.06 mM; [H2O2] = 2 mM; [S2O82-] = 2 mM, the UV/Persulfate process was effective (kapp = 0.163 min−1) than the UV/Peroxydate process (kapp = 0.054 min−1). The lack of dissolved oxygen, the excess of hydrogen peroxide (H2O2) dosage at 2 mM, and the alkaline pH of 10.01 significantly reduced the UV/Peroxydate efficiency. The scavenging effect of the hydrogenocarbonates and nitrates on the PS dye degradation by the UV/Persulfate process was significant, whereas chlorides had a slight influence. The composition of seawater in chlorides, sulfates, carbonates, and bromides decreased the photoactivity of the studied processes. The presence of phenol showed that the reactive affinity of the (HO•) is more superior to the SO4•−. The UV/Persulfate process achieved 82.35% of chemical oxygen demand removal against 59.56% for the UV/Peroxydate in about 100 min. This study demonstrated that the UV/Persulfate process is a viable option for PS dye degradation. To the best of our knowledge, this is the first report for studying the PS dye degradation under some varying new operational factors. However, the identification of by-products, their nature, and their concentration requires special attention.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43593576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of machine learning approaches in predicting estuarine dissolved oxygen (DO) under a limited data environment 机器学习方法在有限数据环境下预测河口溶解氧中的应用

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-08-11 DOI: 10.2166/wqrj.2022.002

M. A. Z. Siddik

{"title":"Application of machine learning approaches in predicting estuarine dissolved oxygen (DO) under a limited data environment","authors":"M. A. Z. Siddik","doi":"10.2166/wqrj.2022.002","DOIUrl":"https://doi.org/10.2166/wqrj.2022.002","url":null,"abstract":"\u0000 The application of machine learning (ML) approaches to predict estuarine dissolved oxygen (DO) from a set of environmental covariates including nutrients remains unexplored due to nutrient data unavailability. Employing data from 12 southwest coastal Florida water quality stations, the applicability of four ML models – support vector machine (SVM), random forest (RF), decision tree, and Wang–Mendel – was examined in predicting DO under a limited nutrient data environment. Monthly water temperature, pH, salinity, total nitrogen (TN), and total phosphorus (TP) data were used for model development. The multiple linear regression model was trained as benchmarks to compare the ML model performances. The site-specific RF and SVM showed superior model efficiency (Nash–Sutcliffe Efficiency > 0.80) when all the predictor variables were used for model development. However, models trained without nutrients demonstrated reduced prediction accuracy. Modeling by synthesizing all site data under TN-limited, TP-limited, and TN- & TP-co-limited regimes illustrated a preferable performance of RF. Overall, the study rendered two crucial conclusions that could complement the existing approaches to estimate total daily loads for environmental management: (1) nutrients serve as a necessary predictor of estuarine DO dynamics and (2) RF performs better among the ML methods under a limited data environment.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45019755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Oxygen aeration efficiency of gabion spillway by soft computing models 石笼溢洪道充氧效率的软计算模型

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-08-06 DOI: 10.2166/wqrj.2022.009

Rathod Srinivas, N. K. Tiwari

{"title":"Oxygen aeration efficiency of gabion spillway by soft computing models","authors":"Rathod Srinivas, N. K. Tiwari","doi":"10.2166/wqrj.2022.009","DOIUrl":"https://doi.org/10.2166/wqrj.2022.009","url":null,"abstract":"\u0000 The current paper deals with the performance evaluation of the application of three soft computing algorithms such as adaptive neuro-fuzzy inference system (ANFIS), backpropagation neural network (BPNN), and deep neural network (DNN) in predicting oxygen aeration efficiency (OAE20) of the gabion spillways. Besides, classical equations, namely multivariate linear and nonlinear regressions (MVLR and MVNLR), including previous studies, were also employed in predicting OAE20 of the gabion spillways. The analysis of results showed that the DNN demonstrated relatively lower error values (root mean square error, RMSE = 0.03465; mean square error, MSE = 0.00121; mean absolute error, MAE = 0.02721) and the highest value of correlation coefficient, CC = 0.9757, performed the best in predicting OAE20 of the gabion spillways; however, other applied models, such as ANFIS, BPNN, MVLR, and MVNLR, were giving comparable results evaluated to statistical appraisal metrics of the relative significance of input parameters based on sensitivity investigation, the porosity (n) of gabion materials was observed to be the most critical parameter, and gabion height (P) had the least impact over OAE20 of the spillways.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44152683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Effective phosphate removal from sewage water using zerovalent iron nanomaterial as an adsorbent 零价铁纳米材料吸附剂有效去除污水中的磷酸盐

IF 2.3 4区环境科学与生态学

Water Quality Research Journal Pub Date : 2022-07-30 DOI: 10.2166/wqrj.2022.007

Ipsita Som, Sourav Suman, Mouni Roy, Srimanta Gupta, R. Saha

{"title":"Effective phosphate removal from sewage water using zerovalent iron nanomaterial as an adsorbent","authors":"Ipsita Som, Sourav Suman, Mouni Roy, Srimanta Gupta, R. Saha","doi":"10.2166/wqrj.2022.007","DOIUrl":"https://doi.org/10.2166/wqrj.2022.007","url":null,"abstract":"\u0000 In recent times, nano zerovalent iron (nZVI) particles have attracted significant attention from researchers for their effectiveness in removing phosphates, a hazardous contaminant, found in groundwater and surface water. nZVI possesses some excellent characteristics such as high reactivity, high surface area, and effective surface-to-volume ratio. In this study, nZVI was characterized by X-ray diffraction, Brunauer–Emmett–Teller (BET) surface area analyzer, Fourier transform infra-red (FT-IR), field emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM) techniques. The effect of variations in nZVI dosage, pH, ionic strength, and coexisting anions on the removal of phosphate from laboratory-based synthetic water was explored. A maximum phosphate removal efficiency of 96% was achieved at an initial phosphate concentration of 25 mg/L, a nZVI dosage of 560 mg/L, and a shaking rate of 500 rpm, and pH 2 was attained within 120 min. Kinetic and equilibrium studies revealed that the adsorption of phosphate follows a pseudo-2nd-order kinetic model and a Temkin isotherm model, respectively. A thermodynamic study confirmed that phosphate adsorption is a spontaneous and endothermic process. Finally, nZVI was proved to be stable up to five cycles. nZVI was further applied for the removal of phosphate from sewage water, which was collected from Saheb bandh, Purulia district of West Bengal, Eastern India.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48239603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2