Study of parameters affecting the behaviour of trace elements in a polluted estuary. Canonical correlation analysis as a tool in environmental impact assessment

Amigo, José Manuel; Gredilla, Ainara; Vallejuelo, Silvia Fdez‐Ortiz de; Diego, Alberto de; Madariaga, Juan Manuel

doi:10.1016/j.chemolab.2012.09.001

Cited by 7 publications

(5 citation statements)

References 39 publications

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“…Canonical correlation analysis (CCA) is a well-established method that calculates the linear correlation between each one of the scores (TX and TY) and two independent PCA models X and Y (Amigo et al, 2012;Naes and Martens, 1984;Sharma et al, 2006) as indicated in equations (1) and (2):…”

Section: Data Treatmentmentioning

confidence: 99%

“…Methods such as principal component analysis (PCA), widely employed in several environmental areas (Rojo-Nieto et al, 2013;Terrado et al, 2006), partial least squares-discriminant analysis (PLS-DA), artificial neural networks (ANNs) (Álvarez-Guerra et al, 2010), cluster analysis (Chen et al, 2012) or positive matrix factorisation (PMF) (Jang et al, 2013) are presented in the literature as a complement to classic univariate statistics, often unveiling concealed environmental information (Álvarez-Guerra 4 et al, 2010;Chen et al, 2012;Gredilla et al, 2013;Jang et al, 2013;Navarro et al, 2006). Canonical correlation analysis (CCA) is an exploratory method designed to study the relationship between data matrices containing different information within the same samples, which make it especially attractive in the field of environmental monitoring (Amigo et al, 2012;Galloway et al, 2002). This allows one to link the behaviour of variables of different nature that, otherwise, would be very difficult to assess (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…This allows one to link the behaviour of variables of different nature that, otherwise, would be very difficult to assess (e.g. relating metal content in water with physico-chemical variables (Amigo et al 2012). …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Relationship between levels of polycyclic aromatic hydrocarbons in pine needles and socio-geographic parameters

Fernández-Varela

Ratola

Alves

et al. 2015

Journal of Environmental Management

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The ability of pine needles to capture polycyclic aromatic hydrocarbons (PAHs) from the surrounding air is well known. In this work the current knowledge of this affinity will be enhanced, investigating the plausible links between the concentrations of PAHs found in pine needles collected in different sites in Portugal, and several socio-geographic variables with environmental relevance. Canonical correlation analysis (CCA) has proven to be a suitable and innovative technique to look for relationships within environmental datasets. In the current work, CCA will simultaneously include chemical information (concentration of PAHs found in pine needles) and socio-geographic information associated to the sampling areas. In order to be more robust in these conclusions, Pinus pinea and Pinus pinaster species were considered separately, allowing an accurate direct comparison between them. The information concerning the different seasons and land occupation was also taken into account. Our results demonstrate how CCA can be a useful tool in environmental impact assessment, and highlight the importance of pine needles as trustful biomonitors of the influence of socio-geographic parameters on the levels of PAHs in a given area.

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Section: Data Treatmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Relationship between levels of polycyclic aromatic hydrocarbons in pine needles and socio-geographic parameters

Fernández-Varela

Ratola

Alves

et al. 2015

Journal of Environmental Management

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“…It has also been applied to a number of environmental quality assessments with agreeable results. CCA has been used in water quality correlation analysis of the Nervion-Ibaizabal estuary in the Basque country of Spain [20], the Caspian sea in the southwest [21], and the Kalen river in Iran [22]. In this article, canonical correlation analysis (CCA) is employed to determine the relationship between shipping and related water environment in the Yangtze river.…”

Section: Introductionmentioning

confidence: 99%

Canonical Correlation Study on the Relationship between Shipping Development and Water Environment of the Yangtze River

et al. 2020

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The sustainable development of the Yangtze River will affect the lives of the people who live along it as well as the development of cities beside it. This study investigated the relationship between shipping development and the water environment of the Yangtze River. Canonical correlation analysis is a multivariate statistical method used to study the correlation between two groups of variables; this study employed it to analyze data relevant to shipping and the water environment of the Yangtze River from 2006 to 2016. Furthermore, the Yangtze River Shipping Prosperity Index and Yangtze River mainline freight volume were used to characterize the development of Yangtze River shipping. The water environment of the Yangtze River is characterized by wastewater discharge, ammonia nitrogen concentration, biochemical oxygen demand, the potassium permanganate index, and petroleum pollution. The results showed that a significant correlation exists between Yangtze River shipping and the river’s water environment. Furthermore, mainline freight volume has a significant impact on the quantity of wastewater discharged and petroleum pollution in the water environment.

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“…Opitz-Stapleton et al [5] used correlation and composite analysis to reveal the physical relationships between different climate factors and streamflow. Amigo et al [6] used canonical correlation analysis to express deep insight into the link between different physicochemical properties and the concentration of metals in an estuary. Risko et al [7] used singular value decomposition analysis to select the predictors of seasonal streamflow in West-Central Florida.…”

Section: Introductionmentioning

confidence: 99%

Monthly Streamflow Forecasting Using EEMD-Lasso-DBN Method Based on Multi-Scale Predictors Selection

Chen

Wei

Qiu

2018

Water

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For the inherent characteristics of a raw streamflow times series and the complicated relationship between multi-scale predictors and streamflow, monthly streamflow forecasting is very difficult. In this paper, an method was proposed integrating the ensemble empirical mode decomposition (EEMD), least absolute shrinkage and selection operator (Lasso) with deep belief networks (DBN) for forecasting monthly streamflow time series, which is EEMD-Lasso-DBN (ELD) method. To develop the ELD model, the raw streamflow time series was resolved into different elements, including intrinsic mode functions (IMFs) and residue series, using the EEMD technique. The predictors of each IMF element and residue were screened using the Lasso technique from a large number of candidate predictors, respectively. Then, the DBN models were built to simulate the complex relationship between the resolved elements and the selected predictors, respectively. The predicted results of the IMFs and residual series were assembled as an ensemble forecast for the raw streamflow time series and were compared with the other models. The monthly streamflow series from Tennessee, in the USA, were investigated using the ELD method. It was found that each IMF has different characteristics and physical meaning, corresponding to different predictors. The proposed ELD model can significantly improve the accuracy of monthly streamflow forecasting.

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Study of parameters affecting the behaviour of trace elements in a polluted estuary. Canonical correlation analysis as a tool in environmental impact assessment

Cited by 7 publications

References 39 publications

Relationship between levels of polycyclic aromatic hydrocarbons in pine needles and socio-geographic parameters

Relationship between levels of polycyclic aromatic hydrocarbons in pine needles and socio-geographic parameters

Canonical Correlation Study on the Relationship between Shipping Development and Water Environment of the Yangtze River

Monthly Streamflow Forecasting Using EEMD-Lasso-DBN Method Based on Multi-Scale Predictors Selection

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