Assessing irreversible fouling behavior of membrane foulants in the ultrafiltration of natural water using principal component analysis of fluorescence excitation-emission matrices

2011 ◽  
Vol 11 (2) ◽  
pp. 179-185 ◽  
Author(s):  
R. H. Peiris ◽  
H. Budman ◽  
R. L. Legge ◽  
C. Moresoli
Keyword(s):  
Principal Component Analysis ◽  
Particulate Matter ◽  
River Water ◽  
Membrane Fouling ◽  
Principal Component ◽  
Drinking Water Treatment ◽  
Component Analysis ◽  
Monitoring And Control ◽  
Fluorescence Excitation ◽  
Natural River Water

Natural river water is comprised of different foulant components such as natural organic matter and colloidal/particulate matter. Both individual and combined contributions of these foulant components results in different fouling behaviour. The ability to characterize these contributions that lead to reversible and irreversible membrane fouling would be beneficial for the implementation of fouling monitoring and control strategies for membrane-based drinking water treatment operations. A fluorescence excitation-emission matrix and principal component analysis-based approach was able to qualitatively estimate the accumulation of humic substances (HS)-, protein- and colloidal/particulate matter-like foulant components in membranes during the ultrafiltration (UF) of natural river water. A bench-scale flat sheet UF cross-flow set-up and successive permeation and membrane backwashing cycles were used. Analysis of the accumulation of these foulant components revealed that the increased levels of colloidal/particulate matter accumulation in the membranes appeared to have increased the extent of irreversible fouling by HS-like matter whereas lower irreversible fouling by protein-like matter was observed with increased colloidal/particulate matter accumulation. The results also indicate that the combined contributions by these foulants are important in the fouling of membranes during the UF of river water.

Distribution characteristics and source analysis of metal elements in indoor PM2.5 in high-rise buildings during heating season in Northeast China

2019 ◽  
Vol 29 (8) ◽  
pp. 1087-1100 ◽  
Author(s):  
Li Bai ◽  
Zijian He ◽  
Wanyue Chen ◽  
Yujie Wang
Keyword(s):  
Principal Component Analysis ◽  
Particulate Matter ◽  
Enrichment Factor ◽  
Northeast China ◽  
Principal Component ◽  
Component Analysis ◽  
Enrichment Factors ◽  
Heating Season ◽  
Metal Elements ◽  
High Rise

This study aims to investigate whether sources of metal elements in fine particulate matter and their distribution in high-rise buildings vary with floor levels. Inductively coupled plasma emission spectrometry (ICP-AES) was used to determine the contents of 11 common heavy metals in PM2.5 samples collected from different floors of a high-rise residential building in Northeast China during the heating season. The sources of metal elements in PM2.5 samples on different floors were analysed by the enrichment factor method and the principal component analysis method. The concentration of metal elements is higher in lower floors (<7th floor) and lower in higher floors (>7th floor). The enrichment factor method shows that the enrichment factors of As, Cd, Cu and Pb may be seriously affected by human sources, while the enrichment factors of the other seven metals are less than 10, indicating that their sources may be natural sources. The principal component analysis shows that the main sources of indoor metal elements in high-rise residential buildings are divided into four main components, including coal combustion (31.44%), automobile emissions and transportation (21.60%), soil dust, particulate matter discharged from agricultural production and atmospheric dust (13.43%), metallurgical, chemical and ore mining (12.61%).

scholarly journals Principal Component Analysis of Blast Furnace Drainage Patterns

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 519 ◽  
Author(s):  
Mauricio Roche ◽  
Mikko Helle ◽  
Henrik Saxén
Keyword(s):  
Principal Component Analysis ◽  
Blast Furnace ◽  
Principal Component ◽  
Component Analysis ◽  
Monitoring And Control ◽  
Process Data ◽  
Drainage Patterns ◽  
Process Operation ◽  
Operating Blast Furnace ◽  
And Control

Monitoring and control of the blast furnace hearth is critical to achieve the required production levels and adequate process operation, as well as to extend the campaign length. Because of the complexity of the draining, the outflows of iron and slag may progress in different ways during tapping in large blast furnaces. To categorize the hearth draining behavior, principal component analysis (PCA) was applied to two extensive sets of process data from an operating blast furnace with three tapholes in order to develop an interpretation of the outflow patterns. Representing the complex outflow patterns in low dimensions made it possible to study and illustrate the time evolution of the drainage, as well as to detect similarities and differences in the performance of the tapholes. The model was used to explain the observations of other variables and factors that are known to be affected by, or affect, the state of the hearth, such as stoppages, liquid levels, and tap duration.

scholarly journals MODELLING IKPOBA RIVER WATER QUALITY USING PRINCIPAL COMPONENT ANALYSIS (PCA) METHOD

2019 ◽  
Vol 10 (1) ◽  
pp. 59-74 ◽  
Author(s):  
Ehizonomhen Solomon Okonofua ◽  
Ifeanyi Benjamin Nwadialo ◽  
M. O. Ekun
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
River Water ◽  
Principal Component ◽  
Treatment Method ◽  
Component Analysis ◽  
River Water Quality ◽  
Brewery Wastewater ◽  
Two Samples ◽  
Intense Activity

This paper examined the effects of brewery wastewater on the quality of water in Ikpoba River which has experienced significant pollution over the years, with the intention of determining the main pollutant in the river water. Samples were recovered from eight (8) different locations covering a total distance of 750 m: one sample from upstream at 150 m from the effluent discharge location, two samples from effluents discharge point and five samples from downstream location at 150 m interval. Samples were taken twice monthly in March, May and July, 2014 during period of intense activity of production. The physcio-chemical analyses of the twenty-five (25) selected parameters were calculated and values obtained were used to calculate the water Quality index of the river. The results indicated that Ikpoba River is severely polluted (WQI = -5429792.89, in SN1, March, 2014) as a result of untreated brewery effluent hence Principal Component Analysis (PCA) was applied to determine the parameter that contributes mainly to the pollution and those that contributed minimally. Evaluation of the PCA results shows that the only reoccurring parameter is Copper hence it is concluded that Copper is the only component factor that influences the river water quality throughout the period under study. Therefore, it is strongly recommended that any proposed treatment method must be targeted at the removal of copper in addition to other factors of high contributory effects.

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