提高硫化物标准溶液稳定性的研究

提高硫化物标准溶液稳定性的研究林小琪（广西南宁市环境监测站,南宁５３００１２）①去离子除ＤＯ、ＣＯ２水：将当天去离子水通入高纯氮气至饱和而成。②ｐＨ＝９２的硼砂缓冲液：称取Ｎａ２Ｂ４Ｏ７·１０Ｈ２Ｏ１９０７ｇ溶于１０００ｍｌ水中。③硫化钠纯化：将...     

Bi（Ⅱ）──APDC共沉淀富集脱脂棉分离FAAS测定水中痕量Pb、Cd

Ｂｉ（Ⅱ）──ＡＰＤＣ共沉淀富集脱脂棉分离ＦＡＡＳ测定水中痕量Ｐｂ、Ｃｄ王林涛，杨玲（云南玉溪地区环境监测站，６５３１００）取加热浓缩至２０ｍｌ的水样，加入Ｂｉ（Ⅱ）（１００μｇ／ｍｌ）３ｍｌ、ＡＰＤＣ３ｍｌ，ＮａＯＡＣＨＯＡＣ缓冲液２ｍｌ，调ｐＨ至...     

石河子市地下水环境背景值

采集并测定了石河子市１９个地下水背景水样，分别确定了该市潜水和承压—自流水中Ｋ＋、Ｎａ＋、Ｃａ２＋、Ｍｇ２＋、Ｃｌ－、ＳＯ、ＨＣＯ、ＮＯ、Ｆ－、总硬度、矿化度、可溶性ＳｉＯ２、ＣＯＤ、ｐＨ、Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ、Ｍｎ、Ｖ、Ｌｉ、Ｍｏ、Ｓｅ、Ｈｇ、Ｉ、Ａｓ、Ｃｒ＋５、Ｃ６Ｈ５ＯＨ、ＣＮ－、ＡＢＳ的环境背景值．     

地表水BOD_5的快速预测预报

地表水五日生化需氧量（ＢＯＤ５）的测试需要五天时间，分析周期较长。本文建立了ＢＯＤ５与高锰酸盐指数（ＣＯＤＭｎ）、ＢＯＤ５与溶解氧（ＤＯ）之间的直线回归方程，通过测定地表水的ＣＯＤＭｎ和ＤＯ可分别对地表水的ＢＯＤ５实现快速预测预报。现场使用溶解氧测定仪检测ＤＯ，可立即预报地表水的ＢＯＤ５。     

海河下游水体中DO与NH_3-N、COD_(Mn)相关关系探讨

本文应用近年来海河下游监测数据对ＤＯ与ＮＨ３Ｎ和ＣＯＤＭｎ进行一元线性回归，得到两回归方程：ＮＨ３Ｎ＝－１２８ＤＯ＋１０５４；ＣＯＤＭｎ＝－１１３ＤＯ＋１６９２。并经相关系数和回归系数显著性检验，表明在９９９％的置信水平下ＤＯ与ＮＨ３Ｎ和ＣＯＤＭｎ线性相关均极其显著     

石油化工工业区区域废水中COD_（Cr）和COD_（Mn）的相关性研究

连续同时监测天津市大港石化发展规划区区域废水中的ＣＯＤＣｒ和ＣＯＤＭｎ，并考查其线性相关性后得出ＣＯＤＣｒ＝４．９６ＣＯＤＭｎ＋１１６．３，相关系数为０．７５０。该回归方程适用于类似石油化工工业区区域废水中ＣＯＤＣｒ和ＣＯＤＭｎ间的换算     

BOD_5快速测定方法研究

本文提出了用差压式ＢＯＤ测定仪快速测定ＢＯＤ５的方法。藉２．５ｄ的试验数据，通过数学模拟，可求得其动力学常数ＢＯＤｕ和Ｋ，再给定时间为５ｄ，就可通过ＢＯＤ动力学关系求得ＢＯＤ５值。本方法理论严密，省时准确     

二溴羟基苯基荧光酮-OP胶束荧光熄灭法测定地面水中的微量铁(Ⅲ)

本文基于Ｆｅ（Ⅲ）二溴羟基苯基荧光酮（ＤＢＨ—ＰＦ）ＯＰ体系的荧光熄灭效应,提出一种测定微量铁（Ⅲ）的新荧光方法,在ｐＨ３８４８的缓冲介质范围内和ＯＰ存在下,Ｆｅ（Ⅲ）与ＤＢＨＰＦ形成１∶３的络合物,络合物的最大激发波长和发射波长分别是３６５ｎｍ和５６０ｎｍ。铁（Ⅲ）量在０１６～１８０μｇ／Ｌ范围内与△Ｆ成线性关系,检测限为０１６μｇ／Ｌ,方法用于地面水中微量铁的测定,结果满意。     

硝化细菌富集培养方法研究

探讨利用提高基质－氨氮浓度的方式富集硝化细菌的可行性，结果表明，温度为３０℃，ｐＨ为６．５～８．０，溶解氧（ＤＯ）的质量浓度高于２ｍｇ／Ｌ时，经过１２～１３周的富集培养，污泥中硝化细菌浓度是未经富集污泥中硝化细菌浓度的１２．５～２０．０倍。     

对酸、中、碱性土壤中有效元素用E－Na试液提取原子吸收测定的初探

对酸、中、碱性土壤中有效元素用Ｅ－Ｎａ试液提取原子吸收测定的初探王国志（云南玉溪地区环境监测站，６５３１００）①用ＥＤＴＡ－柠檬酸钠为提取液测定有效元素Ｃｕ、Ｚｎ时，最佳提取液浓度为０．１３４Ｍ。②当提取液ｐＨ值用ＮａＯＨ调到８．５左右，测定有效元素...     

地表水体中藻类的生长对pH值及溶解氧含量的影响

论述了水质富营养化后藻类生长对pH值及DO的影响,并对pH的变化给出了定量公式,对水中藻类的生长给出了pH限值。     

南京市地表水溶解氧分布特征及低氧成因初探——以外秦淮河七桥瓮为例

于2018—2021年对南京市及国考断面七桥瓮进行水质调查,分析其溶解氧变化特征,采用水质水量联合评价及皮尔逊相关分析法,并结合水文气象等相关信息,对南京市地表水溶解氧分布特征及国考七桥瓮断面低氧成因进行研究分析。结果表明,南京市地表水溶解氧浓度夏季最低,中心主城区及附近区域溶解氧浓度均相对较低。七桥瓮断面溶解氧浓度在2.25~11.07 mg/L,其中5—9月溶解氧易出现超标波动。溶解氧浓度昼间高于夜间,与pH值呈正相关关系,与水温、高锰酸盐指数、氨氮、总磷均呈负相关关系。水温和上游来水带入的耗氧污染物是七桥瓮断面溶解氧偏低的主要成因,其中,溶解氧浓度与水温相关性最为显著。研究结论可为七桥瓮断面稳定达标提供基础支撑,为秦淮河流域精准治污提供技术依据,为南京市水环境多源同治提供治理思路。     

基于在线自动监测的钦州湾海域水质参数周年时空变化特征

通过分析位于钦州湾的2个海水水质自动监测站2009-2010年的自动监测数据，发现钦州湾水温、盐度、溶解氧季节变化明显，海水表层水温变化是引起钦州湾溶解氧含量变动的主要原因；钦州湾海水表层盐度及pH值主要受钦江、茅岭江径流及潮汐涨落的影响；处于河口区域，受大陆径流影响显著的海域使用海水水质标准来评价有欠妥当。     

Monitoring the impact of dissolved oxygen and nitrite on anoxic biofilm in continuous denitrification process

An anoxic biofilm involved in continuous denitrificationprocess was monitored to investigate the effect of differentconcentrations of influent dissolved oxygen (DO) or nitrite onthe biofilm. Microelectrode measurements evidenced nitrateremoval activity of biofilm. When different concentrations ofDO were applied to the reactor, generally decreasedconcentrations of DO were observed as bed depth increased fromthe bottom of the reactor. Greatest decrease of the DO wasobserved in the lower 20% of the bed depth. Nitrate removalefficiency was inversely proportional to influent DOconcentrations (8.3-11.9 DO mg L^-1) or nitrite loadingrates (0-5.5 N-NO₂ ^- kg m^-3 day^-1) employed in this study. Nitrite loading rates to achieve morethan 90% of nitrate removal efficiency were 1.46 N-NO₂ ^-kg m^-3 day^-1 or less at pH 7.5 and 0.34 N-NO₂ ^- kg m^-3 day^-1 or less at pH 6.8. Nitrate removal efficiency was 63% or more within the lower 20% of the bed depth at the nitrite loading rates that allowed more than 90% of nitrate removal efficiency of the reactor. The results of this study provide first quantitative data that nitrate removalperformance of an anoxic biofilm is inhibited by DO or nitrite,reported to be a limiting factor in the suspended biologicaldenitrification process.     

太阳山湿地浮游植物优势功能群季节演替特征及驱动因子分析

为探明太阳山湿地浮游植物优势功能群季节演替规律及其主要驱动因子,于2019年4月(春季)、7月(夏季)、10月(秋季)和2020年1月(冬季)采样分析了太阳山湿地浮游植物的种类组成、优势种、丰度、生物量及季节变化,同时测定了水环境理化因子指标,采用冗余分析方法研究了浮游植物优势功能群的优势度、丰度与水环境因子之间的关系。结果表明:太阳山湿地浮游植物可分为22个功能类群;优势功能群的季节演替和空间分异特征明显,存在一定的规律性。春、秋、冬3个季节的浮游植物以硅藻门为主,夏季以绿藻门和蓝藻门为主。春季优势功能群主要为D、C、P,以硅藻门种类为主;夏季优势功能群主要为J、Lo、TC、M、H1,以硅藻门、绿藻门、蓝藻门种类为主;秋季优势功能群主要为D、S1、MP,以硅藻门、绿藻门种类为主;冬季优势功能群主要为D、X3,以硅藻门种类为主。影响太阳山湿地浮游植物优势功能群季节演替的水环境因子有水温(WT)、pH、溶解氧(DO)、透明度(SD)、盐度(Sal)、氮磷营养元素含量、化学需氧量(COD_Cr)和高锰酸盐指数(COD_Mn)。4个湖区浮游植物优势功能群的时空差异与水环境因子密切相关,其中,西湖区浮游植物优势功能群的季节演替驱动因子为pH、DO、WT、总磷(TP),东湖区为pH、DO、WT、氮磷营养元素含量,南湖区为pH、DO、COD_Cr、五日生化需氧量(BOD₅),小南湖区为pH、DO、WT、BOD₅、COD_Cr、TP。pH、DO、WT、BOD₅、SD等水环境因子的季节差异以及TP、TN、氨氮(NH₃-N)、COD_Mn等水环境因子的湖区差异是太阳山湿地浮游植物优势功能群出现季节演替的主要原因。     

湖北省地表水水质评价指标及监测方式研究

选取湖北省100个国控断面2019年1—12月手工和自动监测数据,采用因子分析和聚类分析相结合的方法对水质评价指标进行优化筛选,结果表明,高锰酸盐指数、氨氮、总磷、pH、溶解氧等5项指标可以代表湖北省地表水水质的主要影响因子,从而实现水质监测指标的降维。对手工和自动2种监测方式进行比对,证明自动监测pH、溶解氧、高锰酸盐指数、总磷和氨氮5项水质评价指标的数据、评价结果与手工监测具有较强的一致性,用自动监测5项指标进行水质评价是合理、可行的,并能减轻手工监测的工作量。     

东江中游水质时空分异特征及影响因素研究

运用多元统计方法，对东江中游水质自动站（河源临江站和惠州剑潭站）2009-2012年水质监测数据进行时空分异特征及影响因素研究。结果表明：水站水质在Ⅰ类～Ⅲ类之间；空间特征差异为 T 与 TB 差异不显著，pH 值、EC、DO、IMn、NH3-N 及 TP均存在极显著差异；水期体征差异为河源临江站除 DO各水期差异显著外，其他指标差异不明显，惠州剑潭站 pH值、EC、IMn与 TP各水期均呈显著差异，NH3-N 水期差异不显著。Pearson 相关性分析表明，T 是制约河源临江站水体 DO的主要相关因子，营养盐作用相对较低；惠州剑潭站水体 DO 与 T、TP及 IMn呈极显著负相关关系。通过因子分析，识别出影响惠州剑潭水质的主因子，量化了水体理化性质、地表径流及人为污染对水质变化的贡献。     

Artificial neural network modeling of dissolved oxygen in reservoir

The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.     

Water Quality Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

Evaluation of pollution load of Lahore Canal by quantification of various pollutants through physicochemical characterisation

The work describes the physicochemical analysis of the water samples collected from Lahore Canal to evaluate pollution load at different points of the canal. Different physical and chemical pollutants such as temperature, pH, electrical conductivity, total dissolved and suspended solids, turbidity, chlorides, sulphates, nitrates, oils and grease, dissolved oxygen, chemical oxygen demand and biological oxygen demand (BOD) were analysed. The data was analysed through analysis of variance, which showed that the p values for dissolved oxygen (DO), chemical oxygen demand (COD), BOD, electrical conductivity, total dissolved solid (TDS), total suspended solid (TSS), turbidity, oil and grease, sulphates, and nitrates are <0.05, while p value of temperature, pH, and chlorides are 1.000, 0.984, and 0.070, respectively, which are >0.05. Further regression analysis revealed that the simple line regression modal is fit for turbidity and TSS, electrical conductivity and TDS, COD and DO, BOD and DO, and BOD and COD. The studies reveal that Lahore Canal is receiving a considerable amount of physical and chemical pollutants at different points.