Screening analysis of river seston downstream of an effluent discharge point using near-infrared reflectance spectrometry and wavelet-based spectral region selection

被引:11
作者
De Medeiros, VM
Araújo, MCU
Galvao, RKH
Da Silva, EC
Saldanha, TCB
Toscano, IAS
De Oliveira, MDSR
Freitas, SKB
Neto, MM
机构
[1] Univ Fed Paraiba, CCEN, Dept Quim, BR-58051970 Joao Pessoa, Paraiba, Brazil
[2] Inst Tecnol Aeronaut, Div Engn Eletron, BR-12228900 Sao Jose Dos Campos, Brazil
基金
巴西圣保罗研究基金会;
关键词
industrial effluents; River Seston; screening analysis; near-infrared reflectance spectrometry; spectral range selection; wavelet transform;
D O I
10.1016/j.watres.2005.05.018
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A methodology for screening analysis of river seston downstream of an industry effluent by using near-infrared reflectance spectrometry was developed. A wavelet transform (WT)-based strategy is used to select a spectral region in which the effect of the effluent on the optical properties of the seston is more evident. The methodology was applied to samples from the River Mumbaba in northeast Brazil. Four sites were monitored: two upstream (I and 2), one at the discharge point of the effluent (3), and another downstream (4). Soft Independent Modelling of Class Analogies (SIMCA) models were built for site I and were then applied to the classification of samples from sites 2 and 4. The results reveal that the WT-based spectral region selection is essential to ensure good sensitivity and specificity with respect to the detection of events associated to the effluent discharges at site 3. In fact, the changes in site 4 caused by the effluent are masked by other environmental factors when the full spectrum is employed. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3089 / 3097
页数:9
相关论文
共 22 条
[1]   Variable selection in wavelet regression models [J].
Alsberg, BK ;
Woodward, AM ;
Winson, MK ;
Rowland, JJ ;
Kell, DB .
ANALYTICA CHIMICA ACTA, 1998, 368 (1-2) :29-44
[2]   Classification of commercial apple beverages using a minimum set of mid-IR wavenumbers selected by Procrustes rotation [J].
Andrade, JM ;
Gómez-Carracedo, MP ;
Fernández, E ;
Elbergali, A ;
Kubista, M ;
Prada, D .
ANALYST, 2003, 128 (09) :1193-1199
[3]  
[Anonymous], 1993, Ten Lectures of Wavelets
[4]  
[Anonymous], 1998, Chemometrics: A Practical Guide
[5]   Characterisation of natural organic matter from the Nordic typing project water samples by chemometric analysis of their near infrared spectral profiles [J].
Christy, AA ;
Egeberg, PK .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2000, 50 (02) :225-234
[6]   A solution to the wavelet transform optimization problem in multicomponent analysis [J].
Coelho, CJ ;
Galvao, RKH ;
Araujo, MCU ;
Pimentel, MF ;
da Silva, EC .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2003, 66 (02) :205-217
[7]   Inferring lake water chemistry from filtered seston using NIR spectrometry [J].
Dåbakk, E ;
Nilsson, M ;
Geladi, P ;
Wold, S ;
Renberg, I .
WATER RESEARCH, 2000, 34 (05) :1666-1672
[8]   A strategy for selecting calibration samples for multivariate modelling [J].
Dantas, HA ;
Galvao, RKH ;
Araújo, MCU ;
da Silva, EC ;
Saldanha, TCB ;
José, GE ;
Pasquini, C ;
Raimundo, IM ;
Rohwedder, JJR .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2004, 72 (01) :83-91
[9]   Quantitative analysis of near infrared spectra by wavelet coefficient regression using a genetic algorithm [J].
Depczynski, U ;
Jetter, K ;
Molt, K ;
Niemöller, A .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1999, 47 (02) :179-187
[10]   Optimal wavelet filter construction using X and Y data [J].
Galvao, RKH ;
José, GE ;
Dantas, HA ;
Araujo, MCU ;
da Silva, EC ;
Paiva, HM ;
Saldanha, TCB ;
de Souza, ESON .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2004, 70 (01) :1-10