Identification and Quantification of Physicochemical Parameters Influencing Chlorophyll-a Concentrations through Combined Principal Component Analysis and Factor Analysis: A Case Study of the Yuqiao Reservoir in China

Abstract

Algal outbreaks caused by excessive nutrients in lakes result in eutrophication.Chlorophyll-a, as a primary productivity feature, is used as a representative index of algal presence in lakes. Physicochemical parameters are known to affect the type and amount of nutrients in lakes, which are related to eutrophication. In this study, factor analysis was used in conjunction with principal component analysis to reveal the relationship between chlorophyll-a and its associated parameters. The combination of these two methods helps to identify the main influencing parameters by quantifying the respective extent of parameters using FA, after which the meaning is explained by PCA. We investigate physicochemical parameters, including temperature, dissolved oxygen (DO), pH, suspended solids, chemical oxygen demand (COD) and five-day biochemical oxygen demand, as well as nutrients, such as ammonium, nitrite, nitrate, total nitrogen, and total phosphorus (TP). Yuqiao Reservoir, an important drinking water source in northern China, has been affected by eutrophication for years. Analysis was performed using daily monitoring data of physicochemical parameters and chlorophyll-a concentrations collected from Yuqiao Reservoir between 2003 and 2014. Results show that main parameters affecting chl-a concentrations are TP, temperature, DO, COD, and nitrogen, with correlation coefficients of 0.977, 1.983, 1.797, and 1.595, respectively.

Spatial and Seasonal Assessment of Water Quality in the Lobo Stream River Basin, Brazil Using Multivariate Statistical Techniques

“…Negative correlations of DO with different variables were observed by Matta et al (2017) and Chen et al (2018) in different periods. However, (Barakat et al 2016) highlighted that the increase in temperature is responsible for the reduction of DO solubility in water, thus decreasing its concentration, a fact that explains the negative correlation of DO with Temp during the rainy season, corresponding to the period with higher air temperatures and consequently higher water temperatures.…”

“…This statistic can vary from 0 to 1, with the value closest to "0" indicating that PCA is not adequate (weak correlation) and the value closest to "1" indicates that the use of the analysis is adequate. Values above 0.5 are considered acceptable for the application of PCA (Finkler et al 2015, Chen et al 2018).…”

“…Bartlett's test of sphericity aims, at a significance level of 0.05, to reject the null hypothesis that says that the correlation matrix is an identity matrix, which would indicate that there is no correlation between the variables and the analysis should not be performed (Chen et al 2018).…”

“…Significant positive correlations between Cl-a and suspended solids have been found in other studies, where it was observed that the organic part of the solids, which corresponds to VSS, is more associated with Cl-a compared to the inorganic part. This relationship can be explained by the fact that in environments with certain level of eutrophication, the increase in solids concentration is a consequence of the growth of algae and some aquatic plants (Lim & Choi 2015, Zhang et al 2017, Chen et al 2018.…”

Effects of Air Pollution Control on Urban Development Quality in Chinese Cities Based on Spatial Durbin Model

“…The most commonly used multivariate statistical analysis method is Principal Component Analysis (PCA), which can select several important variables to reduce the number of factors by using linear transformation [34]. Application of the varimax rotation of the normalized component loading allows us to obtain a clear system by maximizing component load differences and eliminating invalid components [35].…”