ORIGINAL RESEARCH
Using Near Infrared Spectroscopy to Quickly Analyze Different Nitrogens during the Shortcut Biological Removal of Nitrogen from a Polluted River
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Ming Li 1,2
,
 
Hua Zhang 1,2
,
 
,
 
,
 
,
 
Tao Ma 1,2
,
 
Yiqi Xu 1,2
,
 
 
 
 
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1
Key Laboratory of Anhui Province of Water Pollution Control and Wastewater Reuse, School of Environment and Energy Engineering, Anhui Jianzhu University, Hefei, China
 
2
School of Environmental and Energy Engineering, Anhui Jianzhu University, Hefei, P.R. China
 
3
Anhui Zhonghuan Environmental Protection Technology Co., Ltd
 
 
Submission date: 2018-04-06
 
 
Final revision date: 2018-06-01
 
 
Acceptance date: 2018-06-10
 
 
Online publication date: 2019-03-05
 
 
Publication date: 2019-04-09
 
 
Corresponding author
Hua Zhang   

Anhui Jianzhu University, No.292 Ziyun Road, huangjianpaper@163.com Hefei, China
 
 
Pol. J. Environ. Stud. 2019;28(4):2623-2631
 
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ABSTRACT
During shortcut biological nitrogen removal in a polluted river, total nitrogen, ammonia nitrogen and nitrite nitrogen were quantified by near infrared spectroscopy and the synergy interval partial least squares (siPLS) algorithm. Spectral data of 138 water samples were obtained with a near infrared spectrometer. In addition, the real values of total nitrogen, ammonia nitrogen and nitrite nitrogen were measured with traditional chemical methods. SiPLS analysis models of total nitrogen, ammonia nitrogen and nitrite nitrogen were built through the siPLS algorithm based on spectral data and real values. The results obtained from the siPLS analysis model of total nitrogen revealed that, when the full spectra were divided into 19 intervals, the combination of the 7th, 12th and 19th subintervals yielded the best model. The correction coefficient (Rp) is 0.9931, with the root mean squared error of calibration (RMSECV) being 1.7869. The results obtained from the siPLS analysis model of ammonia nitrogen indicated that, when the full spectra were divided into 16 intervals, the combination of the 1st, 7th, 15th and 16th subintervals yielded the best model. The Rp is 0.9947 and the RMSECV is 1.3419. For nitrite nitrogen, the siPLS analysis model indicated that, when the full spectra were divided into 16 intervals, the combination of the 7th and the 11th subintervals yielded the best model. The Rp and RMSECV was 0.9951 and 1.0518. These findings demonstrated that the proposed approach may effectively analyze the concentrations of total nitrogen, ammonia nitrogen and nitrite nitrogen during the treatment of a polluted river based on shortcut biological nitrogen removal. This approach, which is based on near infrared spectroscopy, is fast and accurate for the detection of different types of nitrogen in water.
eISSN:2083-5906
ISSN:1230-1485
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