摘要
COD代表了水体受还原性物质污染的程度。相对于采用传统方法检测COD,存在检测时间长且操作复杂等缺点,紫外光谱法以其检测速度快,无需使用化学试剂等特点成为了主流的检测方法。基于朗伯-比尔定律,以邻苯二甲酸氢钾粉末配置的COD标准溶液为研究对象,针对低温环境下利用紫外光谱法检测COD精度的问题,分别对COD的最佳检测波长和温度对COD检测值的影响进行研究。同时选择长春市某地区地表水为研究对象,验证COD最佳检测波长在实际水样中的适用性及温度补偿模型的准确度。在研究检测波长对COD检测值的影响时,选用256, 266, 276, 286和296 nm共5个波长对样本进行回归分析,它们的吸光度分别为A256,A266,A276,A286,A296,将吸光度A与COD标准溶液浓度值进行线性回归,通过拟合结果得出:276, 286和296 nm处模型具有代表性,且在286 nm处拟合效果最好, 296 nm次之,最后为276 nm,其中286 nm处相关系数r为0.994 6,决定系数R2为0.989 4,波长为296 nm处和方差SSE=0.011 4,预测均方根误差RMSE=0.037 7,但其决定系数R2较低,可见在286 nm处COD检测值与吸光度具有最高的相关性,又探究了标准温度(20℃)下8 mg·L^-1的COD实际水样和标准水样的光谱吸收情况,得出286 nm同样适用于实际水样的检测,可见286 nm处为最佳检测波长。在研究温度对COD检测值的影响时,采集不同温度下COD实际水样与标准水样的紫外吸收光谱,经过分析得出:COD实际水样中紫外光谱吸收度会随温度升高而增大。为了减弱在COD测量中温度的影响,根据最小二乘原则,建立温度补偿模型。利用实际水样验证温度补偿模型的准确度,同时进行误差分析,分析结果表明:COD的实际值与补偿后值的最大相对误差为6.38%,最小相对误差为0.63%,且多数相对误差集中在4%,由此可见, COD温度补偿模型补偿精度高,效果良好。结果表明:COD检测选取的最佳波长及温度补偿模型可有效的提高COD低温检测精度。
COD represents the degree of water pollution by reducing substances, compared with the traditional method to detect COD, the detection time is long and the operation is complicated. Ultraviolet spectroscopy has become a mainstream detection method due to its fast detection speed and no need for chemical reagents. Based on the Lambert Beer law, using potassium hydrogen phthalate powder to prepare standard solution as an experimental object, aiming at the detection accuracy of COD ultraviolet spectrum at low temperature, the optimal detection wavelength of COD and the influence of temperature on the detection value of COD were studied respectively. At the same time, the surface water in a certain area of Changchun City is selected as the research object to verify the applicability of the best COD detection wavelength in the actual water sample and the accuracy of the temperature compensation model. When studying the influence of detection wavelength on COD detection value, choose A256, A266, A276, A286, A296 five wavelengths to regression analysis samples, including A256, A266, A276, A286, A296 is A wavelength of 256, 266, 276, 286 and 296 nm absorbance, the absorbance of A linear regression with the COD standard solution, can be seen from the fitting data 276, 286 and 296 nm model representative, 286 nm in fitting out the best effect, 296 nm, Finally, it is 276 nm, of which the correlation coefficient r of 286 nm is 0.994 6 and the determination coefficient R2 is 0.989 4, SSE=0.011 4 and RMSE=0.037 7 at 296 nm, but the determinant coefficient R2 is low. It can be seen that 286 nm is the highest correlation and the smallest error. The results show that 286 nm is also suitable for the detection of actual water samples, and 286 nm is the best detection wavelength. When studying the influence of temperature on COD detection value, UV absorption spectra of COD water samples and standard water samples were collected at different temperatures. The results show that the UV absorption of COD solution increases with the increase of temperature. After thoroughly studying the spectral absorption of the actual and standard water samples with the same concentration of COD at the standard temperature(20 ℃), in order to eliminate the influence of temperature on COD measurement, a temperature compensation model was established by the least square method. The accuracy of the temperature compensation model is verified by the actual water sample, and the error analysis is carried out at the same time. The results show that the maximum relative error between the actual value of COD and the compensated value is 6.38%, the minimum relative error is 0.63%, and most of the relative errors are concentrated in 4%, which shows that the fitting effect of the model is good. Thus, COD temperature compensation model has high compensation accuracy and good effect. Finally, the conclusion is drawn that the best wavelength and temperature compensation model selected for COD detection can effectively improve the accuracy of COD low temperature detection.
作者
李鑫
苏成志
于丹阳
盛宇博
常川
石磊
姜吉光
LI Xin;SU Cheng-zhi;YU Dan-yang;SHENG Yu-bo;CHANG Chuan;SHI Lei;JIANG Ji-guang(College of Mechanical and Electric Engineering,Changchun University of Science and Technology,Changchun 130022,China;Institute of Artificial Intelligence,Changchun University of Science and Technology,Changchun 130022,China)
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2020年第8期2403-2408,共6页
Spectroscopy and Spectral Analysis
基金
国际科技合作基金项目(20160414030GH)
吉林省教育厅基金项目(JJKH20181124KJ)资助。
关键词
化学需氧量
低温补偿模型
紫外光谱法
吸光度
Chemical oxygen demand
Low temperature compensation model
Ultraviolet spectrometry
Absorbance