Compositional mapping, uncertainty assessment, and source apportionment via pollution assessment-based receptor models in urban and peri-urban agricultural soils

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F23%3A97376" target="_blank" >RIV/60460709:41210/23:97376 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s11368-022-03417-3" target="_blank" >https://link.springer.com/article/10.1007/s11368-022-03417-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11368-022-03417-3" target="_blank" >10.1007/s11368-022-03417-3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Compositional mapping, uncertainty assessment, and source apportionment via pollution assessment-based receptor models in urban and peri-urban agricultural soils

Popis výsledku v původním jazyce

Purpose: Healthy soil and the environment rely on practical risk assessment, controls to improve environmental performance, and the efficient application of receptor models. The primary focus of the study is to evaluate multiple receptor models used to estimate source distribution. Methods: This study collected 115 soil samples from the Frydek Mistek district of Czech Republic. Potentially toxic element (PTE) (Pb, As, Cr, Cd, Ni, Mn, Cu, and Zn) concentrations were measured using inductively coupled plasma optical emission spectrometry. Pollution indices like pollution index, ecological risk, geoaccumulation index, and enrichment factor were hybridized with positive matrix factorization (PMF) to create pollution index-PMF (PI-PMF), ecological risk-PMF (ER-PMF), geoaccumulation index-PMF (IGEO-PMF), and enrichment factor-PMF (EF-PMF). ABC composite mapping technique was used to visualize and determine the interaction between PTEs. Results: The use of composite mapping multimaps with varying color patterns aided in identifying and establishing the source relationship between PTEs. Pollution assessment-based receptor models (PAB-RMs) revealed that the EF-PMF outperformed the PI-PMF, ER-PMF, IGEO-PMF, and PMF receptor models. EF-PMF outperformed other receptor models in model assessments such as coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The hybridized receptor models performed better in terms of error reduction, as the PAB-RMs’ reduction of DISP (displacement) intervals ratio showed smaller intervals than the parent model. Conclusion: The combination of PMF and pollution assessment indices yielded positive results. By optimizing efficiency and reducing error, the current study provides a more reliable receptor model for estimating source distribution.

Název v anglickém jazyce

Compositional mapping, uncertainty assessment, and source apportionment via pollution assessment-based receptor models in urban and peri-urban agricultural soils

Popis výsledku anglicky

Purpose: Healthy soil and the environment rely on practical risk assessment, controls to improve environmental performance, and the efficient application of receptor models. The primary focus of the study is to evaluate multiple receptor models used to estimate source distribution. Methods: This study collected 115 soil samples from the Frydek Mistek district of Czech Republic. Potentially toxic element (PTE) (Pb, As, Cr, Cd, Ni, Mn, Cu, and Zn) concentrations were measured using inductively coupled plasma optical emission spectrometry. Pollution indices like pollution index, ecological risk, geoaccumulation index, and enrichment factor were hybridized with positive matrix factorization (PMF) to create pollution index-PMF (PI-PMF), ecological risk-PMF (ER-PMF), geoaccumulation index-PMF (IGEO-PMF), and enrichment factor-PMF (EF-PMF). ABC composite mapping technique was used to visualize and determine the interaction between PTEs. Results: The use of composite mapping multimaps with varying color patterns aided in identifying and establishing the source relationship between PTEs. Pollution assessment-based receptor models (PAB-RMs) revealed that the EF-PMF outperformed the PI-PMF, ER-PMF, IGEO-PMF, and PMF receptor models. EF-PMF outperformed other receptor models in model assessments such as coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The hybridized receptor models performed better in terms of error reduction, as the PAB-RMs’ reduction of DISP (displacement) intervals ratio showed smaller intervals than the parent model. Conclusion: The combination of PMF and pollution assessment indices yielded positive results. By optimizing efficiency and reducing error, the current study provides a more reliable receptor model for estimating source distribution.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40104 - Soil science

Projekt

<a href="/cs/project/EF16_019%2F0000845" target="_blank" >EF16_019/0000845: Centrum pro studium vzniku a transformací nutričně významných látek v potravním řetězci v interakci s potenciálně rizikovými látkami antropogenního původu: komplexní posouzení rizika kontaminace půdy pro kvalitu zemědělské produkce</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

JOURNAL OF SOILS AND SEDIMENTS

ISSN

1439-0108

e-ISSN

1439-0108

Svazek periodika

23

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

22

Strana od-do

1451-1472

Kód UT WoS článku

000905881200001

EID výsledku v databázi Scopus

2-s2.0-85145058779