Health risk assessment and the application of CF-PMF: a pollution assessment–based receptor model in an urban soil

Purpose This study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination factor-positive matrix factorization), and to estimate the extent of contamination across seven cities in the Frydek-Mistek district. Nevertheless...

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Published inJournal of soils and sediments Vol. 21; no. 9; pp. 3117 - 3136
Main Authors Agyeman, Prince Chapman, Ahado, Samuel Kudjo, John, Kingsley, Kebonye, Ndiye Michael, Vašát, Radim, Borůvka, Luboš, Kočárek, Martin, Němeček, Karel
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021
Springer Nature B.V
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Abstract Purpose This study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination factor-positive matrix factorization), and to estimate the extent of contamination across seven cities in the Frydek-Mistek district. Nevertheless, the impact of agricultural production and industrial activities on urban soil and the livelihood of the indigenous peoples in the study area as well as the source contribution of the individual PTEs is unknown. Methods This study collected 49 soil samples across seven towns in the Frydek-Mistek district, which are primarily agricultural and industrially oriented urbanized communities. The samples were air-dried, and the potentially toxic elemental (PTEs) (i.e., Pb, As, Cr, Ni, Mn, Cu, and Zn) concentrations measured using portable x-ray fluorescence. Results Nemerow Pollution index and modified contamination degree indicated that the urban contamination levels were between low and moderate contamination level with a few cases of high contamination levels. The degree of contamination and the contamination factor showed varying levels of contamination for PTEs, with a high level of contamination and a low to high level of contamination, respectively. PTEs displayed a low to high pattern of spatial distribution in urban soil around Trinec, Bystice, Hrcava, and Harirov. The source of the PTEs was detected using principal component analysis, and the source apportionment of the PTEs was further assessed using CF-PMF (contamination factor-positive matrix factorization). Comparison of the CF-PMF receptor model and the EPA-PMF receptor model revealed that the novel receptor model performed better. The root mean square error (RMSE) and the mean absolute error (MAE) of the new receptor model marginal errors reduced significantly. RMSE and MAE for the CF-PMF receptor model for all the PTEs for instance As, Cr, Cu, Mn, Ni, Pb, and Zn are 11.56, 97.85, 17.30, 527.26, 37.16, 32.12, and 68.02 (RMSE) and 11.58,95.00, 17.26, 520.85, 37.04, 32.13, and 68.03 (MAE) were lesser than the EPA.PMF receptor model respectively. Health risk computed indicated that there was no potential carcinogenic and non-carcinogenic risk being exposed to the people living within the study area. Conclusion We propose using the novel receptor model CF-PMF because its output has shown to be optimal with minimal error and improved efficiency when compared to the parent model EPA-PMF. In general, continuous introduction of agro-related inputs and other anthropogenic activities surges PTEs levels in urban soils. Thus, constructive yet efficient steps, appropriate control, and mitigation measures are required to abate pollution sources that may be sowed to the soil.
AbstractList Purpose This study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination factor-positive matrix factorization), and to estimate the extent of contamination across seven cities in the Frydek-Mistek district. Nevertheless, the impact of agricultural production and industrial activities on urban soil and the livelihood of the indigenous peoples in the study area as well as the source contribution of the individual PTEs is unknown. Methods This study collected 49 soil samples across seven towns in the Frydek-Mistek district, which are primarily agricultural and industrially oriented urbanized communities. The samples were air-dried, and the potentially toxic elemental (PTEs) (i.e., Pb, As, Cr, Ni, Mn, Cu, and Zn) concentrations measured using portable x-ray fluorescence. Results Nemerow Pollution index and modified contamination degree indicated that the urban contamination levels were between low and moderate contamination level with a few cases of high contamination levels. The degree of contamination and the contamination factor showed varying levels of contamination for PTEs, with a high level of contamination and a low to high level of contamination, respectively. PTEs displayed a low to high pattern of spatial distribution in urban soil around Trinec, Bystice, Hrcava, and Harirov. The source of the PTEs was detected using principal component analysis, and the source apportionment of the PTEs was further assessed using CF-PMF (contamination factor-positive matrix factorization). Comparison of the CF-PMF receptor model and the EPA-PMF receptor model revealed that the novel receptor model performed better. The root mean square error (RMSE) and the mean absolute error (MAE) of the new receptor model marginal errors reduced significantly. RMSE and MAE for the CF-PMF receptor model for all the PTEs for instance As, Cr, Cu, Mn, Ni, Pb, and Zn are 11.56, 97.85, 17.30, 527.26, 37.16, 32.12, and 68.02 (RMSE) and 11.58,95.00, 17.26, 520.85, 37.04, 32.13, and 68.03 (MAE) were lesser than the EPA.PMF receptor model respectively. Health risk computed indicated that there was no potential carcinogenic and non-carcinogenic risk being exposed to the people living within the study area. Conclusion We propose using the novel receptor model CF-PMF because its output has shown to be optimal with minimal error and improved efficiency when compared to the parent model EPA-PMF. In general, continuous introduction of agro-related inputs and other anthropogenic activities surges PTEs levels in urban soils. Thus, constructive yet efficient steps, appropriate control, and mitigation measures are required to abate pollution sources that may be sowed to the soil.
PURPOSE: This study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination factor-positive matrix factorization), and to estimate the extent of contamination across seven cities in the Frydek-Mistek district. Nevertheless, the impact of agricultural production and industrial activities on urban soil and the livelihood of the indigenous peoples in the study area as well as the source contribution of the individual PTEs is unknown. METHODS: This study collected 49 soil samples across seven towns in the Frydek-Mistek district, which are primarily agricultural and industrially oriented urbanized communities. The samples were air-dried, and the potentially toxic elemental (PTEs) (i.e., Pb, As, Cr, Ni, Mn, Cu, and Zn) concentrations measured using portable x-ray fluorescence. RESULTS: Nemerow Pollution index and modified contamination degree indicated that the urban contamination levels were between low and moderate contamination level with a few cases of high contamination levels. The degree of contamination and the contamination factor showed varying levels of contamination for PTEs, with a high level of contamination and a low to high level of contamination, respectively. PTEs displayed a low to high pattern of spatial distribution in urban soil around Trinec, Bystice, Hrcava, and Harirov. The source of the PTEs was detected using principal component analysis, and the source apportionment of the PTEs was further assessed using CF-PMF (contamination factor-positive matrix factorization). Comparison of the CF-PMF receptor model and the EPA-PMF receptor model revealed that the novel receptor model performed better. The root mean square error (RMSE) and the mean absolute error (MAE) of the new receptor model marginal errors reduced significantly. RMSE and MAE for the CF-PMF receptor model for all the PTEs for instance As, Cr, Cu, Mn, Ni, Pb, and Zn are 11.56, 97.85, 17.30, 527.26, 37.16, 32.12, and 68.02 (RMSE) and 11.58,95.00, 17.26, 520.85, 37.04, 32.13, and 68.03 (MAE) were lesser than the EPA.PMF receptor model respectively. Health risk computed indicated that there was no potential carcinogenic and non-carcinogenic risk being exposed to the people living within the study area. CONCLUSION: We propose using the novel receptor model CF-PMF because its output has shown to be optimal with minimal error and improved efficiency when compared to the parent model EPA-PMF. In general, continuous introduction of agro-related inputs and other anthropogenic activities surges PTEs levels in urban soils. Thus, constructive yet efficient steps, appropriate control, and mitigation measures are required to abate pollution sources that may be sowed to the soil.
PurposeThis study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination factor-positive matrix factorization), and to estimate the extent of contamination across seven cities in the Frydek-Mistek district. Nevertheless, the impact of agricultural production and industrial activities on urban soil and the livelihood of the indigenous peoples in the study area as well as the source contribution of the individual PTEs is unknown.MethodsThis study collected 49 soil samples across seven towns in the Frydek-Mistek district, which are primarily agricultural and industrially oriented urbanized communities. The samples were air-dried, and the potentially toxic elemental (PTEs) (i.e., Pb, As, Cr, Ni, Mn, Cu, and Zn) concentrations measured using portable x-ray fluorescence.ResultsNemerow Pollution index and modified contamination degree indicated that the urban contamination levels were between low and moderate contamination level with a few cases of high contamination levels. The degree of contamination and the contamination factor showed varying levels of contamination for PTEs, with a high level of contamination and a low to high level of contamination, respectively. PTEs displayed a low to high pattern of spatial distribution in urban soil around Trinec, Bystice, Hrcava, and Harirov. The source of the PTEs was detected using principal component analysis, and the source apportionment of the PTEs was further assessed using CF-PMF (contamination factor-positive matrix factorization). Comparison of the CF-PMF receptor model and the EPA-PMF receptor model revealed that the novel receptor model performed better. The root mean square error (RMSE) and the mean absolute error (MAE) of the new receptor model marginal errors reduced significantly. RMSE and MAE for the CF-PMF receptor model for all the PTEs for instance As, Cr, Cu, Mn, Ni, Pb, and Zn are 11.56, 97.85, 17.30, 527.26, 37.16, 32.12, and 68.02 (RMSE) and 11.58,95.00, 17.26, 520.85, 37.04, 32.13, and 68.03 (MAE) were lesser than the EPA.PMF receptor model respectively.Health risk computed indicated that there was no potential carcinogenic and non-carcinogenic risk being exposed to the people living within the study area.ConclusionWe propose using the novel receptor model CF-PMF because its output has shown to be optimal with minimal error and improved efficiency when compared to the parent model EPA-PMF. In general, continuous introduction of agro-related inputs and other anthropogenic activities surges PTEs levels in urban soils. Thus, constructive yet efficient steps, appropriate control, and mitigation measures are required to abate pollution sources that may be sowed to the soil.
Author Ahado, Samuel Kudjo
Kočárek, Martin
John, Kingsley
Kebonye, Ndiye Michael
Vašát, Radim
Borůvka, Luboš
Agyeman, Prince Chapman
Němeček, Karel
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IngestDate Thu Jul 10 22:59:06 EDT 2025
Fri Jul 25 23:00:12 EDT 2025
Tue Jul 01 01:38:23 EDT 2025
Thu Apr 24 23:04:09 EDT 2025
Fri Feb 21 02:47:50 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 9
Keywords Spatial distribution
Urban soil
Health risk assessment
Contamination factor-positive matrix factorization
Principal component analysis
Language English
LinkModel DirectLink
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  ident: 2988_CR1
  publication-title: Springer
  doi: 10.1007/s10661-007-9678-2
– volume: 65
  start-page: 863
  year: 2006
  ident: 2988_CR69
  publication-title: Chemosphere
  doi: 10.1016/j.chemosphere.2006.03.016
– volume: 379
  start-page: 109
  year: 2007
  ident: 2988_CR8
  publication-title: Sci Total Environ
  doi: 10.1016/j.scitotenv.2007.02.037
– ident: 2988_CR38
– volume: 165
  start-page: 1008
  year: 2009
  ident: 2988_CR27
  publication-title: J Hazard Mater
  doi: 10.1016/j.jhazmat.2008.10.118
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Snippet Purpose This study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination...
PurposeThis study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination...
PURPOSE: This study was carried out to assess human health risk exposure, to apply a novel pollution assessment–based receptor model CF-PMF (contamination...
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SubjectTerms Agricultural production
air drying
Anthropogenic factors
carcinogenicity
Carcinogens
Chromium
Contamination
Copper
Earth and Environmental Science
Environment
Environmental assessment
Environmental Physics
Factorization
Fluorescence
health effects assessments
Health risk assessment
Health risks
human health
Human influences
Indigenous peoples
Industrial areas
Lead
livelihood
Manganese
Mitigation
Nickel
pollution
Pollution abatement
Pollution index
Pollution sources
principal component analysis
Principal components analysis
Receptors
risk
Risk assessment
Root-mean-square errors
Sec 3 • Remediation and Management of Contaminated or Degraded Lands • Review Article
Soil
Soil contamination
Soil pollution
Soil Science & Conservation
Soils
Spatial distribution
urban soils
urbanization
X-radiation
X-ray fluorescence
Zinc
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Title Health risk assessment and the application of CF-PMF: a pollution assessment–based receptor model in an urban soil
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