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Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant

Mapping spatial distribution of soil contaminants at contaminated sites is the basis of risk assessment. Hotspots can cause strongly skewed distribution of the raw contaminant concentrations in soil, and consequently can require suitable normalization prior to interpolation. In this study, three nor...

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Autores principales: Yuan, Yumin, Yang, Kai, Cheng, Lirong, Bai, Yijuan, Wang, Yingying, Hou, Ying, Ding, Aizhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735471/
https://www.ncbi.nlm.nih.gov/pubmed/36497545
http://dx.doi.org/10.3390/ijerph192315470
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author Yuan, Yumin
Yang, Kai
Cheng, Lirong
Bai, Yijuan
Wang, Yingying
Hou, Ying
Ding, Aizhong
author_facet Yuan, Yumin
Yang, Kai
Cheng, Lirong
Bai, Yijuan
Wang, Yingying
Hou, Ying
Ding, Aizhong
author_sort Yuan, Yumin
collection PubMed
description Mapping spatial distribution of soil contaminants at contaminated sites is the basis of risk assessment. Hotspots can cause strongly skewed distribution of the raw contaminant concentrations in soil, and consequently can require suitable normalization prior to interpolation. In this study, three normalization methods including normal score, Johnson, and Box-Cox transformation were performed on the concentrations of two low-molecular weight (LMW) PAHs (i.e., acenaphthene (Ace) and naphthalene (Nap)) and two high-molecular weight (HMW) PAHs (i.e., benzo(a)pyrene (BaP) and benzo(b)fluoranthene (BbF)) in soils of a typical coking plant in North China. The estimating accuracy of soil LMW and HMW PAHs distribution using ordinary kriging with different normalization methods was compared. The results showed that all transformed data passed the Kolmogorov-Smirnov test, indicating that all three data transformation methods achieved normality of raw data. Compared to Box-Cox-ordinary kriging, normal score-, and Johnson-ordinary kriging had higher estimating accuracy of the four soil PAHs distribution. In cross-validation, smaller root-mean-square error (RMSE) and mean error (ME) values were observed for normal score-ordinary kriging for both LMW and HMW PAHs compared to Johnson- and Box-Cox-ordinary kriging. Thus, normal score transformation is suitable for alleviating the impact of hotspots on estimating accuracy of the four selected soil PAHs distribution at this coking plant. The findings can provide insights into reducing uncertainty in spatial interpolation at PAHs-contaminated sites.
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spelling pubmed-97354712022-12-11 Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant Yuan, Yumin Yang, Kai Cheng, Lirong Bai, Yijuan Wang, Yingying Hou, Ying Ding, Aizhong Int J Environ Res Public Health Article Mapping spatial distribution of soil contaminants at contaminated sites is the basis of risk assessment. Hotspots can cause strongly skewed distribution of the raw contaminant concentrations in soil, and consequently can require suitable normalization prior to interpolation. In this study, three normalization methods including normal score, Johnson, and Box-Cox transformation were performed on the concentrations of two low-molecular weight (LMW) PAHs (i.e., acenaphthene (Ace) and naphthalene (Nap)) and two high-molecular weight (HMW) PAHs (i.e., benzo(a)pyrene (BaP) and benzo(b)fluoranthene (BbF)) in soils of a typical coking plant in North China. The estimating accuracy of soil LMW and HMW PAHs distribution using ordinary kriging with different normalization methods was compared. The results showed that all transformed data passed the Kolmogorov-Smirnov test, indicating that all three data transformation methods achieved normality of raw data. Compared to Box-Cox-ordinary kriging, normal score-, and Johnson-ordinary kriging had higher estimating accuracy of the four soil PAHs distribution. In cross-validation, smaller root-mean-square error (RMSE) and mean error (ME) values were observed for normal score-ordinary kriging for both LMW and HMW PAHs compared to Johnson- and Box-Cox-ordinary kriging. Thus, normal score transformation is suitable for alleviating the impact of hotspots on estimating accuracy of the four selected soil PAHs distribution at this coking plant. The findings can provide insights into reducing uncertainty in spatial interpolation at PAHs-contaminated sites. MDPI 2022-11-22 /pmc/articles/PMC9735471/ /pubmed/36497545 http://dx.doi.org/10.3390/ijerph192315470 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yuan, Yumin
Yang, Kai
Cheng, Lirong
Bai, Yijuan
Wang, Yingying
Hou, Ying
Ding, Aizhong
Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant
title Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant
title_full Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant
title_fullStr Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant
title_full_unstemmed Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant
title_short Effect of Normalization Methods on Accuracy of Estimating Low- and High-Molecular Weight PAHs Distribution in the Soils of a Coking Plant
title_sort effect of normalization methods on accuracy of estimating low- and high-molecular weight pahs distribution in the soils of a coking plant
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735471/
https://www.ncbi.nlm.nih.gov/pubmed/36497545
http://dx.doi.org/10.3390/ijerph192315470
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