Chemical oxygen demand reduction in coffee wastewater through chemical flocculation and advanced oxidation processes

The removal of the natural organic matter present in coffee processing wastewater through chemical coagulation-flocculation and advanced oxidation processes （AOP） had been studied. The effectiveness of the removal of natural organic matter using commercial flocculants and UV/H202, UV/O3 and UV/H2O2/O3 processes was determined under acidic conditions. For each of these processes, different operational conditions were explored to optimize the treatment efficiency of the coffee wastewater. Coffee wastewater is characterized by a high chemical oxygen demand （COD） and low total suspended solids. The outcomes of coffee wastewater treatment using coagulation-flocculation and photodegradation processes were assessed in terms of reduction of COD, color, and turbidity. It was found that a reduction in COD of 67% could be realized when the coffee wastewater was treated by chemical coagulation-flocculation with lime and coagulant T-1. When coffee wastewater was treated by coagulation-flocculation in combination with UV/H2O2, a COD reduction of 86% was achieved, although only after prolonged UV irradiation. Of the three advanced oxidation processes considered, UV/H2O2, UV/O3 and UV/H2O2/O3, we found that the treatment with UV/H2O2/O3 was the most effective, with an efficiency of color, turbidity and further COD removal of 87%, when applied to the flocculated coffee wastewater.

Simultaneous Determination of Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD5) in Wastewater by Near-Infrared Spectrometry

To rapidly determine the pollution extent of wastewater, the calibration models were established for deter-mination of Chemical Oxygen Demand and Biological Oxygen Demand in wastewater by partial least squares and near infrared spectrometry of 120 samples. Spectral data preprocessing and outliers’ diagnosis were also discussed. Correlation coefficients of the models were 0.9542 and 0.9652, and the root mean square error of prediction (RMSEP) were 25.24 mg?L-1 and 12.13 mg?L-1 in the predicted range of 28.40~528.0 mg?L-1 and 16.0~305.2 mg?L-1 for Chemical Oxygen Demand and Biological Oxygen Demand, respectively. By statistical significance test, the results of determination were compared with those of stan-dard methods with no significant difference at 0.05 level. The method has been applied to simultaneous de-termination of Chemical Oxygen Demand and Biological Oxygen Demand in wastewater with satisfactory results.

Environmental capacity of chemical oxygen demand in the Bohai Sea: modeling and calculation

A three-dimensional advection-diffusion model coupled with the degradation process is established for describing the transport of chemical oxygen demand (COD). Comparison of the simulated distribution of COD at the surface in the Bohai Sea in August, 2001 with field observations, shows that the model simulates the dataset reasonably well. The Laizhou Bay, Bohai Bay, and Liaodong Bay were contaminated heavily near shore. Based on the optimal discharge flux method, the Environmental Capacity (EC) and allocated capacities of COD in the Bohai Sea are calculated. For seawater of Grades I to IV of the Chinese National Standard, the ECs of COD in the Bohai Sea were 77×104 t/a, 116×104 t/a, 154×104 t/a and 193×104 t/a, respectively. The Huanghe (Yellow) River pollutant discharge accounted for the largest percentage of COD at 14.3%, followed by that of from the Liugu River (11.5%), and other nine local rivers below 10%. The COD level in 2005 was worse than that of Grade II seawater and was beyond the environmental capacity. In average, 35% COD reduction is called to meet the standard of Grade I seawater.

Spatial distribution and diurnal variation of chemical oxygen demand at the beginning of the rainy season in the Changjiang (Yangtze) River Estuary

A field observation was carried out in the Changjiang (Yangtze) River Estuary from May 19 to 26, 2003. A total of 29 stations, including 2 anchored stations, were occupied through almost the whole salinity gradient. Based on the observation data, biogeochemistry of chemical oxygen demand (COD) was examined. Spatial distribution pattern of COD shows that it decreased downstream. The COD concentration varied generally within a narrow range of 1.24–1.60 mg/L in the zone around the river mouth, beyond which it decreased rapidly to 0.20 mg/L. In the mixed water zone, the fluctuation in COD was smaller at 2 m above the bottom layer than at the surface layer in 48 h. In the seawater zone, the 48-h fluctuation at the surface was the largest, followed by that of 5 m below the surface and 2 m above the bottom layers in a range of from 2.50 to 0.55 mg/L. Freshwater discharge was the dominant source of COD in the estuary. The average COD beyond the river mouth was 2.7 mg/L, which accorded with the Chinese seawater quality Grade I. Relationships between dissolved oxygen and biogeochemical parameters such as suspended particulate matter, dissolved organic matter and chlorophyll-a were also discussed.

On-Line Measurement of the Chemical Oxygen Demand in Wastewater in a Pulp and Paper Mill Using Near Infrared Spectroscopy

Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce online predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of online COD measurements in wastewater using NIR spectroscopy.

Analysis of the Correlation among Three Oxygen Demand Indexes in Surface Water

Based on the monitoring data of chemical oxygen demand(COD),permanganate index(I Mn)and five-day biochemical oxygen demand(BOD 5)of surface water in Tongling section of Yangtze River,the linear relationship among the three indexes in the annual data analysis and the internal reasons,as well as the linear relationship and changes among the three indexes in different seasons were analyzed.The results reveal that in terms of the whole year,COD,I Mn and BOD 5 had a significant correlation and good linear relationship.The fitting slopes of the three indexes were 3.89 of COD/I Mn,4.39 of COD/BOD 5 and 1.16 of I Mn/BOD 5,respectively,which corresponded to the proportional relationship among the three indexes.From the perspective of seasonal changes,there was a very significant correlation between the three indexes in spring and summer.In autumn and winter,only COD and I Mn had a good correlation,but they had a poor correlation with BOD 5.

PVDF/PVA共混膜的制备及其在去除污水COD中的应用

以聚乙烯醇(PVA)、聚偏氟乙烯(PVDF)为原料,聚乙烯吡咯烷酮为溶剂,制备了PVDF/PVA共混膜。将该膜应用于膜生物反应器处理污水,测试化学需氧量(COD)去除率和膜的使用性能。结果表明:膜的水通量随PVA加入量的增加而逐渐增加,在牵伸比为1.7时,膜的水通量达到最大值;平板膜用清水清洗后,膜的水通量恢复率较高,膜的运行周期经第一次清洗后下降了18 h,经第二次和第三次清洗后,膜的运行周期基本稳定在6~8 h,COD去除率高于90%,表明该膜具有良好的使用性能。

基于KPCA-PSO-ELM算法的地表水化学需氧量紫外-可见吸收光谱检测研究

化学需氧量(COD)是水质检测重要指标之一,反映水体有机物含量。传统的COD化学检测方法存在操作繁琐,等待时间长,二次污染等缺点。紫外-可见吸收光谱法是目前水体化学需氧量检测中应用最为广泛的方法之一,具有检测快速、无污染等特点。为了满足地表水化学需氧量快速、实时、在线监测等要求,采用紫外-可见吸收光谱进行测量,提出了内核主成分分析(KPCA)结合粒子群优化极限学习机(PSO-ELM)预测模型,满足当前对地表水化学需氧量快速、实时监测的要求。对光谱进行Savitzky-Golay(SG)滤波以降低随机噪声的影响;用积分光谱代替原光谱,以降低信号波动带来的影响;再将得到的光谱信息归一化,消除不同光谱数据量纲的影响。将预处理后的数据利用KPCA算法将全光谱数据压缩为5个特征,有效解决光谱信息冗余的问题;采用PSO算法对ELM的权重和偏置进行优化极大提高了模型的精度。对217个河流、长江及支流、湖库等地表水样本按照7∶3随机划分成训练集和测试集,并进行建模测试,其中训练集拟合优度(R2)为0.930 2、均方根误差(RMSE)为0.363 0 mg·L^(-1)、测试集拟合优度R2为0.931 9、均方根误差(RMSE)为0.400 7 mg·L^(-1)。为了验证提出的基于KPCA全光谱数据压缩方法对预测模型的提升效果,分别对比了主成分分析(PCA)、连续投影算法(SPA)、套索回归(LASSO)等特征处理算法。PCA-PSO-ELM模型的RMSE为0.715 1 mg·L^(-1)、 SPA-PSO-ELM模型的RMSE为0.473 7 mg·L^(-1)、 LASSO-PSO-ELM模型的RMSE为0.412 6 mg·L^(-1), KPCA-PSO-ELM模型较上述三种模型,RMSE分别降低了78.46%、 18.22%、 2.97%,结果表明KPCA是一种高效的光谱降维算法,能够有效消除光谱冗余信息,提升模型预测精度。基于KPCA-PSO-ELM预测模型结合紫外-可见吸收光谱可以实现对地表水COD快速、实时检测,为在线COD检测场景提供方法支撑。

化学需氧量精品实验项目的建设与探索

以“环境监测实验”课程中经典的“化学需氧量(CODcr)测定”实验项目为例,从教学理念、教学内容和教学方法等开展精品实验项目建设。在教学理念上,遵循工程教育专业认证的“OBE”教学理念,将传统实验项目改进为探究性实验项目,以培养学生的动手能力、研究能力和思维能力。在传统课内实验教学基础上,引入前沿监测知识和新型测试技术,建立常规实验与拓展实验相结合的教学内容,引入两种测试方法的比较与总结环节,以此提高学生学习的主动性和综合能力。精品实验项目的建设,丰富了实验教学内涵,提高了实验教学效果,满足新时期环境学科一流人才培养的需要。

基于斑马鱼模型评估金华市主要水系的环境风险

近年来,金华市实施了一系列“治水”工程,以便将水体的各项理化指标控制在标准以下,改善水环境质量。考虑到水中多种污染物之间可能存在的协同或加成等效应,在各理化指标达标情况下仍可能存在对水生生物正常生长发育构成潜在威胁的因素。为了准确评估“治水”工程对金华市水环境的改善效果,本研究综合运用化学分析与生物评价相结合的方法评估“治水”工程后金华市主要水系的水环境质量。研究发现,在以三江交汇点为中心的9个采样点中,化学需氧量(COD)的检出浓度均低于我国地表水Ⅰ类标准,金华市主要水系中有机物相对含量较低。对19种金属元素的浓度检测表明:Cd在梅溪采样点的检出浓度(1.22μg·L^(-1))略高于其地表水I类标准,Mn在秋滨污水厂出水(210.4μg·L^(-1))、Sb在梅溪(8.88μg·L^(-1))和义乌江(6.24μg·L^(-1))水样中的检出浓度均高于其国家地表水特定标准限值。此外所检测的金属元素在所研究区域内均可达到相应的地表水水质要求。生物评价结果表明,斑马鱼胚胎可以在所有采样点水样中正常生长发育,且其体内的热休克蛋白(HSP70)和金属硫蛋白(MT)及抗氧化系统均未受到明显干扰。由此可见,金华市实施的系列“治水”工程可以有效控制水环境中重金属及有机物的含量,且水质总体良好,对鱼类早期的生长发育并未产生任何干扰效应。

基于PIWT-IPSO-BP的污水厂出水COD含量的预测模型

在农业灌溉的领域中,化学需氧量(Chemical Oxygen Demand,COD)的测定是衡量水体中有机物污染程度的一个重要指标。当COD浓度超过60mg/L时,其对土壤质量和农作物的生长产生的负面影响成为不容忽视的问题。这一现象可能会严重影响农作物的产量和质量,进而对农作物生产的可持续性构成挑战。因此,有必要精确预测污水处理厂出水COD浓度的变化趋势,从而促进其在农业灌溉中的有效应用。研究结合了改进的小波变换、改进的粒子群优化(Improved Particle Swarm Optimization,IPSO)算法和反向传播BP(Back Propagation,BP)神经网络作为预测模型。鉴于COD受到众多因素的影响,这些因素之间存在复杂的耦合关系,采用PCA进行特征提取。考虑到数据采集的过程中不可避免的噪声干扰,应用小波降噪对原始数据进行处理,以确保数据质量,提高模型准确性。在此基础上,基于BP神经网络算法构建污水处理厂出水COD的预测模型。为了解决BP神经网络参数选择可能遇到的盲目性问题,引入改进的粒子群算法对模型进行参数优化,以提高预测精度。实验结果表明,提出的PIWT-IPSO-BP模型预测效果良好,其平均绝对误差、均方根误差和决定系数分别为0.222、0.386和0.984。该模型在一定程度上改善了数据噪声、多因子制约等问题,为污水循环利用技术应用于农业灌溉方面提供了参考依据。

近红外光谱污水COD分析系统设计

为了解决利用近红外光谱技术测定污水中的化学需氧量技术中样本数据集参数存在数据过拟合、干扰因素大、检测界面不直观等问题,本文采用一维卷积神经网络技术,建立水样近红外特征与污染指标成分含量之间的关系模型,并利用MATLAB的图形用户界面设计分析界面。实验结果表明,该方法预测结果良好,可实现水质污染的定性及定量的快速检测。

生物质活性炭的制备及其在有机废水处理中的应用

生物质活性炭是一种功能性多孔碳材料,以高碳生物质资源作为原料,经炭化、活化加工制成,具有原料来源广、表面官能团与孔结构丰富、吸附性能与改性潜力优良等特点。近年来许多学者以生物质为原料制备了功能多样的活性炭,实现了活性炭在多种有机废水处理场景的应用,对有机废水的处理取得了显著的成果。综述了活性炭制备过程中常用的炭化和活化方法,对比分析了表面酸碱改性、氧化与还原改性、金属负载改性、微生物负载改性等活性炭改性方法,总结了活性炭在吸附净化、絮凝沉降、厌氧消化、生物滤池与人工湿地过滤等有机废水处理场景的应用,并对活性炭制备技术发展前景做了展望。

重铬酸盐法与快速消解分光光度法测定化学需氧量的对比

文章通过对重铬酸盐法和快速消解分光光度法检出限、精密度、正确度和不同行业的实际样品的分析,以及操作过程中的试剂前处理、操作步骤、消解时间、计算公式、产生废液量及实验效率的比较,着重讨论了两种检测方法的准确性与适用性。经分析可知,两种检测方法对实际水样中COD的测定结果相近。检出限、精密度、正确度均符合检测方法的要求,结果无明显差异。快速消解分光光度法所用试剂无需前处理、仪器操作简单、消解时间短、实验结果直接读取无需计算且产生废液量少,实验效率更高,在大批量快速检测或突发检测中的适用性远高于重铬酸盐法。

表面活性剂与纳米颗粒协同稳定Pickering有机硅乳液的制备及其应用性能

针对目前有机硅平滑剂乳液往往存在分散稳定性差或高剂量表面活性剂引起的应用性能降低等问题,以聚丙烯酸异辛酯的共聚物胶乳(PEHA)为Pickering颗粒,协同表面活性剂,用于制备“油/水”Pickering有机硅乳液,并将其用于织物后整理。考察了PEHA粒径、表面亲水改性及PEHA质量分数对有机硅乳液分散稳定性的影响,通过对整理残液化学需氧量(COD)和整理织物表面摩擦因数的研究,考察了表面活性剂与Pickering纳米颗粒协同稳定对有机硅乳液应用性能的影响。结果表明:PEHA颗粒吸附在有机硅液滴的表面,形成机械阻隔,提升有机硅乳液的分散稳定性,180 nm的PEHA颗粒的稳定效率最佳,90 nm时的稳定效率最差;表面亲水改性能显著提高PEHA稳定乳液的效率,在质量分数仅为10%时,即可实现乳液稳定;最佳稳定方案可使表面活性剂质量分数降低60%以上;浸轧整理织物时,相比表面活性剂独自稳定的体系,Pickering体系吸附织物效率更高,整理后残液的COD值降低63%,整理织物表面静、动摩擦因数分别降低至0.51与0.49,即“Pickering/表面活性剂”协同稳定有机硅乳液具有良好的应用性能。

噻二唑衍生物的制备及性能评价

针对现有噻二唑衍生物制备工艺中废水化学需氧量(COD)极高的问题,探索以去离子水替代乙醇作为反应溶剂,并引入相转移催化剂促进固-液两相反应,开发了制备噻二唑衍生物的绿色环保新工艺;进而,采用红外光谱、液相色谱、质谱等手段对新工艺合成的产物进行了结构表征,采用铜片腐蚀试验和四球试验评价了合成产物的金属腐蚀抑制性能、极压性能和减摩性能。结果表明:采用新工艺合成产物过程中产生的废水COD为2000 mg/L,与传统工艺产生的废水COD(700000 mg/L)相比显著降低,说明新工艺符合绿色环保要求;采用传统工艺和新工艺分别合成了2,5-双(叔壬基二硫代)-1,3,4-噻二唑,其金属腐蚀抑制性能、极压性能、减摩性能相当,且优于市售噻二唑衍生物类金属减活剂T561。

高岭土-尿素改性玉米秸秆生物炭去除污水中COD研究

以固体废弃物资源玉米秸秆为原料,并使用尿素与高岭土对其进行化学改性,通过管式炉高温制备改性玉米秸秆生物炭(NKBC),该材料制备工艺简便,成本低,对环境友好。研究了NKBC对污水中化学需氧量(COD)的吸附性能,包括吸附等温线、吸附动力学等。结果表明:NKBC对COD的吸附平衡投料量为0.50g/L,去除率为68%~70%,吸附平衡时间为1h,且pH对NKBC去除COD影响较小。通过分析可知,此吸附拟合模型遵循Langmuir模型与Freundlich模型以及准二级动力学模型,说明NKBC的吸附过程既涉及单层吸附,又涉及多层吸附。循环使用5次后,NKBC对COD的去除率依然保持在较高水平。实验证明,NKBC具有出色的去除和循环性能。

胍胶压裂返排液COD的电化学降解实验研究

为研究电化学法对胍胶压裂返排液中化学需氧量(COD)的去除效果,本实验采用Al和Fe极板作为电极材料。通过响应面法分析了反应过程,并考察了反应动力学模型。实验结果显示,Al极板在2.5 cm间距、135 mA/cm^(2)电流密度下,经过120 min处理,可实现85.29%的COD去除率。响应面模型系数具有显著的相关性,且模型的精确度和可信度均符合要求。去除COD的过程符合一级动力学模型。对于Fe极板,同样的极板间距和电流密度条件下,90 min处理后,取上清液进行60 min的二次电化学反应,并在每30 min加入40 mL H_(2)O_(2)。最终,COD去除率提升至97.65%,浓度降至80 mg/L,满足国家污水综合排放标准(<100 mg/L)。

畜禽养殖污水处理中微波催化氧化法的参数优化

该研究拟对微波催化氧化处理畜禽养殖污水技术进行参数优化。以厌氧消化池内的污水为研究对象,分别研究了pH、微波时间、微波功率、催化剂用量、过氧化氢用量5个因素对化学需氧量(COD)去除率的影响;采用响应曲面法中的Box-Behnken试验设计,以COD去除率为响应值,以微波时间、微波功率、活性炭用量为影响因素,建立数学模型。通过方差分析可知,影响因素显著性顺序为:微波功率>活性炭用量>微波时间,微波功率和微波时间的交互作用对COD去除率影响显著;模型预测的最佳条件组合为:微波时间14.83 min,微波功率320 W,活性炭用量14 g·L^(-1),COD去除率为89.79%,该反应条件下3组平行试验的COD平均去除率为90.27%,与预测值相对误差为0.54%。采用微波催化氧化技术处理畜禽污水,可以满足《畜禽养殖业污染物排放标准》(GB18596)中对COD<100 mg·L^(-1)的一级排放要求。

近红外光谱的水体污染指标COD定量预测模型

针对传统化学需氧量(chemical oxygen demand, COD)检测存在检测成本高、耗时、易造成二次污染,以及现有检测模型泛化性较差等不足,难以满足水环境实时监测需求的问题,提出基于近红外光谱技术的COD快速无损定量预测模型.实验结果表明,本模型在污水COD光谱数据集上的预测性能,相较于传统机器学习算法和现有其他深度学习算法更优.测试的决定系数(R^(2))和均方根误差(E_(RMS))分别达到0.992 1和27.47 mg·L^(-1),模型卷积层的输出特征可解释性强,能有效表征关键波长点.该预测模型为实际水体COD含量快速检测提供一种新的方法.