Influence of the inherent properties of drinking water treatment residuals on their phosphorus adsorption capacities

Batch experiments were conducted to investigate the phosphorus（P） adsorption and desorption on five drinking water treatment residuals（WTRs） collected from different regions in China. The physical and chemical characteristics of the five WTRs were determined. Combined with rotated principal component analysis, multiple regression analysis was used to analyze the relationship between the inherent properties of the WTRs and their P adsorption capacities. The results showed that the maximum P adsorption capacities of the five WTRs calculated using the Langmuir isotherm ranged from 4.17 to8.20 mg/g at a p H of 7 and further increased with a decrease in p H. The statistical analysis revealed that a factor related to Al and 200 mmol/L oxalate-extractable Al（Alox） accounted for 36.5% of the variations in the P adsorption. A similar portion（28.5%） was attributed to an integrated factor related to the p H, Fe, 200 mmol/L oxalate-extractable Fe（Feox）, surface area and organic matter（OM） of the WTRs. However, factors related to other properties（Ca,P and 5 mmol/L oxalate-extractable Fe and Al） were rejected. In addition, the quantity of P desorption was limited and had a significant negative correlation with the（Feox＋ Alox） of the WTRs（p 〈 0.05）. Overall, WTRs with high contents of Alox, Feoxand OM as well as large surface areas were proposed to be the best choice for P adsorption in practical applications.

Interpretation of water quality parameters for Villages of Sanganer Tehsil, by using Multivariate Statistical analysis

In this study, the factor analysis techniques is applied to water quality data sets obtained from the Sanganer Tehsil, Jaipur District, Rajasthan (India). The data obtained were standardized and subjected to principal components analysis (PCA) extraction to simplifying its interpretation and to define the parameters responsible for the main variability in water quality for Sanganer Tehsil in Jaipur District. The PCA analysis resulted in two factors explaining more than 94.5% of the total variation in water quality data set. The first factor indicates the variation in water quality is due to anthropogenic sources and second factor shows variation in water quality due to organic sources that are taking place in the system. Finally the results of PCA reflect a good look on the water quality monitoring and interpretation of the surface water.

Regulation effects of water and nitrogen on yield,water,and nitrogen use efficiency of wolfberry

Wolfberry(Lycium barbarum L.)is important for health care and ecological protection.However,it faces problems of low productivity and resource utilization during planting.Exploring reasonable models for water and nitrogen management is important for solving these problems.Based on field trials in 2021 and 2022,this study analyzed the effects of controlling soil water and nitrogen application levels on wolfberry height,stem diameter,crown width,yield,and water(WUE)and nitrogen use efficiency(NUE).The upper and lower limits of soil water were controlled by the percentage of soil water content to field water capacity(θ_(f)),and four water levels,i.e.,adequate irrigation(W0,75%-85%θ_(f)),mild water deficit(W1,65%-75%θ_(f)),moderate water deficit(W2,55%-65%θ_(f)),and severe water deficit(W3,45%-55%θ_(f))were used,and three nitrogen application levels,i.e.,no nitrogen(N0,0 kg/hm^(2)),low nitrogen(N1,150 kg/hm^(2)),medium nitrogen(N2,300 kg/hm^(2)),and high nitrogen(N3,450 kg/hm^(2))were implied.The results showed that irrigation and nitrogen application significantly affected plant height,stem diameter,and crown width of wolfberry at different growth stages(P<0.01),and their maximum values were observed in W1N2,W0N2,and W1N3 treatments.Dry weight per plant and yield of wolfberry first increased and then decreased with increasing nitrogen application under the same water treatment.Dry weight per hundred grains and dry weight percentage increased with increasing nitrogen application under W0 treatment.However,under other water treatments,the values first increased and then decreased with increasing nitrogen application.Yield and its component of wolfberry first increased and then decreased as water deficit increased under the same nitrogen treatment.Irrigation water use efficiency(IWUE,8.46 kg/(hm^(2)·mm)),WUE(6.83 kg/(hm^(2)·mm)),partial factor productivity of nitrogen(PFPN,2.56 kg/kg),and NUE(14.29 kg/kg)reached their highest values in W2N2,W1N2,W1N2,and W1N1 treatments.Results of principal component analysis(PCA)showed that yield,WUE,and NUE were better in W1N2 treatment,making it a suitable water and nitrogen management mode for the irrigation area of the Yellow River in the Gansu Province,China and similar planting areas.

Water Quality Analysis of Fuping Section of the Shichuan River Based on Different Evaluation Methods

In order to study the water quality of the Shichuan River basin in Fuping,Shaanxi Province,based on improved Nemerow index method,comprehensive pollution index method and principal component analysis method,eight water quality indexes such as pH,dissolved oxygen(DO),total dissolved solids(TDS),COD,total hardness,total phosphorus,total nitrogen and Zn in three monitoring sections of Fuping section of the Shichuan River in Shaanxi Province were detected and analyzed.The results show that the water quality of the surface water in the Shichuan River basin is gradeⅢorⅣwater,that is,the water is slightly polluted and moderately polluted.It is necessary to monitor the water quality after regulation and clarify the main factors causing the water pollution.

Assessment of the Water Quality Index in the Semani River in Albania

Nowadays the human activity has increased the pressure on surface water quality. The purpose of this study is to assess the environmental quality of the Seman River water (in Southern part of Albania) through a 5-year monitoring program of 14 parameters (pH, DO, EC, TSS, Cl-, NO-3, Total-N, Total-P, BOD5, Cu2+, Ni2+, Pb2+, Cd2+ and Temp. °C), that determine the environmental status of this waterbody, as well as the application of WQI (CCME) through a multivariable approach. Based on the cluster dendogram results, it can be concluded that during wet seasons such as winter-spring, there are more sediments which influence other physic-chemical parameters, while during dry seasons (summer-autumn) there are more decomposition reactions of elements released by sediments and influenced by temperature. PCA analysis determines whether the groups of factors correlate strongly or not, depending on the internal structures of the groups and variables “heavy” or latent and vary from season to season with differentiated contributions to the water quality. All three factors influence WQI to the extent of 56% in the summer and spring season and 64% and 40% in the autumn and winter season, respectively.

Identification of Mine Water Inrush Source Based on PCA-BP Neural Network

It is of great significance to analyze the chemical indexes of mine water and develop a rapid identification system of water source, which can quickly and accurately distinguish the causes of water inrush and identify the source of water inrush, so as to reduce casualties and economic losses and prevent and control water inrush disasters. Taking Ca2+, Mg2+, Na+ + K+, , , Cl-, pH value and TDS as discriminant indexes, the principal component analysis method was used to reduce the dimension of data, and the identification model of mine water inrush source based on PCA-BP neural network was established. 96 sets of data of different aquifers in Panxie mining area were selected for prediction analysis, and 20 sets of randomly selected data were tested, with an accuracy rate of 95%. The model can effectively reduce data redundancy, has a high recognition rate, and can accurately and quickly identify the water source of mine water inrush.

咖啡豆品质评价体系构建及国产咖啡豆品质评价

为探索我国咖啡豆用于现磨咖啡和速溶咖啡两种用途时的品质评价方法,筛选评价指标,首先通过Delphi评价法和序关系分析法从基本品质指标中筛选主要品质指标,构建品质指标体系。随后测定采自云南和海南不同产区53个咖啡豆样品的主要品质指标成分差异,基于相关性分析、主成分分析和聚类分析筛选不同用途咖啡豆的特征性品质指标,基于样品的主成分综合得分进行逐步多元线性回归。最终筛选出粒度、口感、香味、碳水化合物含量为速溶咖啡用咖啡豆特征性品质指标;粒度、口感、香味、咖啡因含量为现磨咖啡用咖啡豆的特征性品质指标,确定适用于速溶咖啡的主栽品种为卡蒂姆和铁皮卡,主产区为云南;适用于现磨咖啡的咖啡豆主栽品种为卡蒂姆,主产区为云南。

西北煤电集聚区不同水体水化学特征及氟成因

为探明西北煤电集聚区不同水体水化学特征以及氟离子分布成因,以鄂尔多斯市补连塔矿区为研究对象,采用Piper三线图、主成分分析、相关性分析等方法,对采集的55个水样进行测试,结合非致癌健康评价模型对地下水中氟离子进行健康风险评估.结果表明:所有水样均呈现出弱碱性;Na^(+)、SO_(4)^(2-)是地表水以及深层地下水的优势离子,浅层地下水的优势离子为Ca2+和HCO_(3)-;地表水的水化学类型主要以SO_(4)·Cl-Na和HCO_(3)·SO_(4)-Na型为主,浅层地下水的化学类型较多,主要以SO_(4)·Cl-Na·Ca、HCO_(3)-Na·Mg、HCO_(3)-Mg和SO_(4)·Cl-Ca型为主,深层地下水则以HCO_(3)·SO_(4)-Ca和SO_(4)-Na型为主;其水化学特征主要受硅酸盐风化溶解作用影响,同时采煤活动促进了不同水体之间水化学转化;地表水、浅层地下水与深层地下水中F变化范围分别在0.16~4.82,0~0.69,0.08~6.26mg/L,地下水中F有19.35%的风险指数超过HQ=1,推测该地区地下水的高氟现象对人类健康产生一定的影响.

浙江省灵江流域地表水化学特征及灌溉适宜性

[目的]灵江是浙南诸河流域重要河流,在浙南一带具有典型性和代表性。分析灵江流域地表水体的水化学特征和演化机理及其灌溉适宜性,为该区域生态保护和高质量发展提供科学依据。[方法]综合利用数理统计、Piper三线图、主成分分析和离子比等方法对流域地表水体进行水化学统计分析及成因判别;通过绘制Wilcox图和USSL图评估流域内地表水体灌溉适宜性。[结果]①灵江流域地表水的化学类型在空间上具有分带性。从中上游(Ⅰ区)-下游温黄平原河网区(Ⅱ区)-台州湾入海口(Ⅲ区)水化学类型从HCO_(3)-Ca型向Cl-Na型过渡。②Ⅰ区地表水的化学特征主要受到岩石风化作用中的硅酸盐岩溶解影响,少量受碳酸盐岩溶解影响;Ⅱ区地表水的水化学特征主要受硅酸盐岩溶解影响,Ⅲ区地表水的化学特征主要受蒸发盐岩溶解影响。③Ⅰ,Ⅱ区地表水的K^(+),Na^(+)主要来源于硅酸盐矿物溶解,Ca^(2+),Mg^(2+),HCO^(-)_(3),SO^(2-)_(4)主要受硅酸盐岩溶解,少量来源于碳酸盐岩的溶解。NO^(-)_(3)则主要来源于人类活动。④Ⅰ,Ⅱ区地表水适用于农业灌溉,Ⅲ区地表水灌溉适宜性较差,易引起盐碱害。[结论]灵江流域地表水体的水化学组分受天然溶解及人类活动共同影响,中上游和下游温黄平原河网区地表水适宜农业灌溉,台州湾入海口地表水易引起盐碱害,在制定农业灌溉及生态保护和高质量发展规划时应予以重视。

基于地下水化学特征的水封油库水幕系统有效性评价

水幕系统有效性是地下水封油库安全稳定运行的重要基础条件,然而目前评价水幕系统有效性的方法并不高效便捷。以我国首个大型地下水封油库工程为背景,采集油库运行期现场水样和岩样进行水质检测分析和电镜扫描试验,获取库址区地下水水化学类型和岩石的矿物成分组成特征。采用数理统计方法,基于地下水水化学特征获得了不同部位地下水之间的水力联系,开展水幕系统有效性评价。研究表明:油库运行初期库址区地下水主要为HCO^(3)—Na•Ca型水,围岩中的钾长石、钠长石和钙长石发生水化学反应,地下水中的K^(+)、Na^(+)、Ca^(2+)和HCO_(3)^(-)浓度总体呈上升趋势,pH值总体呈下降趋势;Cl^(-)浓度低于造成钢筋腐蚀的浓度,地下水对洞库支护系统无明显腐蚀作用;洞库周边监测孔地下水与水幕供水的水化学特征相似,说明水幕系统与油库围岩之间存在较好的水力联系,形成良好的水封效果。该研究可为判断地下水封油库运行情况提供重要依据,并为评价水幕系统有效性提供了一种科学方法。

基于自然要素的大尺度河流水环境承载力评价与预测

水环境承载力是保护水环境的重要指标,用于水资源的合理规划与管理,确保水环境的可持续利用。为探讨适用于大型河流的更为系统全面的水环境承载力评价指标体系,在现有水环境承载力研究的基础上,选取长江干流为研究对象,以“自然要素、水资源、生态环境、社会经济”4个方面作为指标层,共选取25个具体指标,运用改良的主成分分析法对长江干流水环境承载力的时空尺度变化趋势进行了评价,通过ARIMA模型预测了长江干流未来3年水环境承载力的发展情况。结果表明,综合指标分值在时间尺度上的变化整体呈上升趋势,综合得分由-1.66逐渐上升为1.26,从Ⅳ级(差)上升为Ⅰ级(优),未来3年将继续保持小幅度上升趋势。

新型3UPRR并联机构的运动学分析与多目标优化

根据基于方位特征方程的并联机构拓扑设计理论和方法,提出一种三平移3UPRR并联机构,通过矢量法建立运动学方程并计算得到位置正解和逆解。分别研究工作空间、灵巧度、全域同向系数、全域最小奇异值等性能指标。建立多维性能指标优化目标,选择具有降维和多重信息有效融合特点的主成分分析法(PCA),得到不依赖主观选择的机构评价函数,通过给定运动轨迹仿真验证支链驱动副位移连续且无明显突变跳跃。最后通过SolidWorks软件模拟零件抓取过程进行仿真验证,研究可为该类机器人的设计应用奠定理论基础。

基于随机森林预测模型的小清河复航前后水质对比研究

小清河是山东省内从济南流向莱州湾的一条河道,在断航26年之后于2023年7月复航。本文着重探讨小清河复航前后辛丰庄断面水文水质指标的变化情况,并进一步分析主要污染因子在复航前后的变化情况。通过相关性分析和主成分分析的综合结果表明,确定复航后可能对小清河水质产生重要影响的水质指标为CODMn和TP;通过随机森林模型进行预测分析的结果表明:复航后三个月内,相关水质的关键指标均保持稳定,且优于Ⅲ类水质标准。研究表明复航对小清河水质并未产生显著影响。这一研究不仅为未来的小清河长期复航计划提供有力支持,同时也对国家“三水统筹”政策的贯彻实施具有重要意义。

水质因子对冷萃咖啡主要成分及风味的影响

为探究水质因子对冷萃咖啡主要成分及感官风味的影响,本研究选择6种不同的市售水通过冷萃的方式制备咖啡萃取液,采用高效液相色谱(HPLC)技术和顶空固相微萃取-气质联用(HS-SPME-GC-MS)技术鉴定6组冷萃咖啡液,比较分析6组冷萃咖啡理化指标、非挥发性成分、挥发性成分、感官评价的差异,并进行相关性和主成分分析(PCA)。结果显示,不同类型的水样主要离子含量差异较大,水中离子对冷萃咖啡的萃取浓度、萃取率、pH、可滴定酸、咖啡因、葫芦巴碱和呋喃类挥发性化合物整体有较大影响,对总酚、绿原酸、咖啡酸、抗氧化活性影响较小。水中的Ca^(2+)、Mg^(2+)、HCO_(3)^(−)与冷萃咖啡的萃取浓度、萃取率、咖啡因、葫芦巴碱呈显著正相关(P<0.05),与可滴定酸值呈显著负相关(P<0.05)。糠醇、5-甲基糠醛、1-糠基吡咯、糠基甲基硫醚、2-异丁基-3-甲氧基吡嗪、乙酸糠醇酯这些挥发性化合物与水中总离子含量有较大关联。PCA图分析显示,水中较低的离子含量能促进咖啡花果风味的体现,随着水中Ca^(2+)、Mg^(2+)、HCO_(3)^(−)的增加,咖啡的花果味、酸味、甜味会有不同程度的减弱。较高的离子含量(尤其是Na^(+)、K^(+))能促进咖啡焦糖味、苦涩味的体现,Na^(+)、K^(+)对糠醇含量影响较大,Ca^(2+)、Mg^(2+)、HCO_(3)^(−)对1-糠基吡咯、5-甲基糠醛、糠基甲基硫醚含量影响较大,而用中等的离子含量的水冲泡的冷萃咖啡有较好的坚果味、烘焙味、甜味、风味和总体感官评价。研究结果可为深入认识水质因子对咖啡理化特性与主要成分的影响提供一定理论依据。

张家口柴宣盆地浅层地下水水化学特征及水质评价

地下水作为张家口地区的主要供水水源,近年来受人类活动影响水质有恶化的趋势,影响了当地的用水安全,确定地下水化学特征与水质状况对水资源合理利用具有重要意义。基于2020年水质数据,选取Ca^(2+)、Mg^(2+)、K^(+)、Na^(+)、HCO^(-)_(3)、TH、pH、TDS、SO_(4)^(2-)、Cl^(-)、Al^(3+)、NO^(-)_(3)、F^(-)、Cr^(6+)等水质因子,通过数理统计法、Piper三线图、Gibbs图和岩石风化端元图对张家口柴宣盆地地区浅层地下水水化学特征进行分析,并采用模糊综合评价和改进内梅罗指数法对水质进行评价。结果表明:研究区地下水是Ca^(2+)和HCO^(-)_(3)为主的弱碱性淡水,微硬水、硬水和极硬水分别占39.51%、34.57%和25.93%;沿地下水流向,地下水化学类型由HCO_(3)-Ca·Mg、HCO_(3)-Na、SO_(4)·Cl-Na型转变为HCO_(3)-Ca·Mg、HCO_(3)-Na、SO_(4)·Cl-Ca·Mg型,水化学组分的空间分布特征主要受到硅酸盐、碳酸盐的风化溶解和人类活动影响;地下水水质整体满足III类标准,但部分地区水质较差;沿着地下水流向,水质逐渐变差,主要受原生地质环境和工业、农业污染的影响。

神南矿区水质特征及水环境保护研究

为保护矿区水环境质量,在神南矿区进行水样采集检测,运用描述性统计等方法对研究区水环境现状进行研究并分析其控制因素,以此提出矿区水环境保护措施。研究结果表明,神南矿区水环境总体呈碱性,地表水与地下水化学类型主要为HCO_(3)·SO_(4)-Ca,老空水则以SO_(4)·HCO_(3)-Na·Mg为主;地表水水质较差不宜饮用,地下水水质整体较好,老空水水质极差,大都不宜灌溉;地表水、地下水环境主要遭到生活污水的影响,同时也受农业活动威胁,老空水环境则受到采矿活动的破坏。

滇池流域捞鱼河湿地水质评价与时空变化特征

对滇池流域捞鱼河湿地的水质现状进行分析与评价,为改善湿地水环境状况提供数据支撑.分析了2022年1月至12月份捞鱼河湿地中12个监测位点的水体TN、TP、COD、Chla、NH_(3)-N、pH、DO、T和S共9个指标,采用主成分分析法对捞鱼河湿地主要污染指标进行筛选和评价.结果表明:12月份水质最好,6月份水质最差;水体流经捞鱼河湿地净化后,以湿地入水口11号位点为参照点,其他位点水体的TP和TN削减率分别为10.73%~61.22%和2.20%~34.04%,湿地净化效果较好,但湿地水体水质为劣Ⅴ类.氮磷是捞鱼河湿地水体的限制性营养元素,磷是水体富营养化的最主要限制因子,农业面源污染和未收集的点源是影响湿地水质的主要因素.

深圳龙岗沙湾河水污染特征及水质评价

2021年,研究团队选取深圳市龙岗区沙湾河进行水质监测,采用单因子评价法、单因子水质标识指数法、综合污染指数法、综合水质标识指数法和主成分分析法进行水质评价。结果表明:单因子评价法与单因子水质标识指数法一致得出氨氮、总磷是沙湾河水质的主要影响因子;综合污染指数法评价结果显示,沙湾河水质污染程度基本达到“较清洁”状态;综合水质标识指数法评价结果显示,沙湾河水质基本满足地表水Ⅲ类要求;主成分分析法评价结果显示,河流受有机物、营养盐影响较为显著,雨季水质仍有较大提升空间。本研究表明各种水质评价方法结果虽有差异,但能从不同角度反映河流水质状况,使用多种评价方法能充分挖掘水质数据的意义、更好反映河流水质特征。

基于PCA和SVM的遥感影像水体提取方法及验证

针对内陆湖泊水质及光谱特性空间差异性大、支流水系结构复杂而导致的遥感影像水体提取精度低的问题,提出了结合光谱主成分分析(PCA)及支持向量机(SVM)的PCA-SVM水体提取算法。基于GF-1卫星遥感影像,对原始影像光谱波段特征进行PCA降维,从中优选熵、方差、差异性纹理特征向量,结合原始波段及归一化差分水体指数(NDWI),构建了8维特征向量,并基于SVM算法提取湖泊水体。以巢湖洪水期与非洪水期影像为研究实例,分别采用NDWI法、传统SVM算法及PCA-SVM算法对水体进行提取,并进一步基于PCA-SVM算法对2020年汛期巢湖洪水期淹没演变过程进行反演和跟踪,定量解析特征向量组合及SVM惩罚系数C对水体提取性能的影响。结果表明:PCA-SVM算法提取的湖泊完整、支流连续,显著改善了含蓝藻水体漏提、建筑物误提等问题;洪水期和非洪水期提取结果的F1分数分别为95.08%和97.95%,虚警率分别为5.43%和1.13%,提取精度显著高于NDWI法和SVM算法。

Water Quality Assessment of Dachangshan ArtificialHabitat Development Demonstration Area

[Objective] The paper was to evaluate the water quality environment in Dachangshan artificial habitat development demonstration area.[Method] From 2013 to 2015, an environmental survey was conducted for eight voyages in Dachangshan artificial habitat development demonstration area of Changhai County, Dalian City, and 20 hydrochemical indexes including salinity, pH, and COD were monitored. The water quality of thesea area was analyzed by principal component analysis and single factor index method. [Result] Except for that the control area of the August 2014voyage belonged to IIclass sea water standard, the water quality in other stations of all voyages conformed toIclass sea water standard. Totally 20water quality indicators were synthesized into six principal components using principal component analysis, which explained 79.165% of the results;the principal component score was ranged from -1.536 to 3.706; the score in August 2014 was the highest, and the evaluation results were basicallyconsistent with the results of single factor index analysis. [Conclusion] The overall water quality is good in Dachangshan artificial habitat development demonstration area.