Comparing the applicability of ecological risk indices of metals based on PCA-APCS-MLR receptor models for ports surface sediments

Chih-Feng Chen; Yee Cheng Lim; Yun-Ru Ju; Frank Paolo Jay B Albarico; Chiu-Wen Chen; Cheng-Di Dong

doi:10.1016/j.marpolbul.2022.114361

Comparing the applicability of ecological risk indices of metals based on PCA-APCS-MLR receptor models for ports surface sediments

Mar Pollut Bull. 2022 Dec;185(Pt B):114361. doi: 10.1016/j.marpolbul.2022.114361. Epub 2022 Nov 17.

Authors

Chih-Feng Chen¹, Yee Cheng Lim¹, Yun-Ru Ju², Frank Paolo Jay B Albarico³, Chiu-Wen Chen⁴, Cheng-Di Dong⁵

Affiliations

¹ Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan.
² Department of Safety, Health and Environmental Engineering, National United University, Miaoli 36063, Taiwan.
³ Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan; Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan; College of Fisheries and Allied Sciences, Northern Negros State College of Science and Technology, Sagay City 6122, Philippines.
⁴ Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan. Electronic address: cwchen@nkust.edu.tw.
⁵ Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan. Electronic address: cddong@nkust.edu.tw.

PMID: 36403305
DOI: 10.1016/j.marpolbul.2022.114361

Abstract

This study collected surface sediments from seven ports in Taiwan and analyzed their characteristics along with 10 metals. Enrichment factor (EF), relative EF (REF), potential ecological risk index (PERI), and mean effect range median quotient (m-ERM-q) were used to evaluate the levels of metal contamination and ecological risks in sediments. Principal component analysis (PCA) and the absolute principal component score-multiple linear regression (APCS-MLR) model were applied to quantify the main factors affecting the variations in sediment metals. The different normalization techniques that vary between indexes significantly affect the estimates of risk levels for sediment metals. APCS-MLR model confirmed the significant difference among the sediment quality indices in the degree of anthropogenic pollution, ranging in the order of REF (normalized with reference site and Fe, 97.0 %), PERI (normalized with reference site, 85.5 %), EF (normalized with crust and Fe, 79.4 %), and m-ERM-q (not normalized, 56.6 %).

Keywords: Anthropogenic; Ecological risks; Harbor; Metal; Normalization; Sediments.

MeSH terms

Environmental Pollution*
Linear Models
Metals*
Principal Component Analysis
Taiwan

Substances

Metals