Source apportionment of potentially toxic elements in soils of the Yellow River Delta Nature Reserve, China: The application of three receptor models and geostatistical independent simulation

Spatial distribution and source identification of potentially toxic elements in Yellow River Delta soils, China: An interpretable machine-learning approach

Identifying the driving factors and quantifying the sources of potentially toxic elements (PTEs) are essential for protecting the ecological environment of the Yellow River Delta. In this study, data from 201 surface soil samples and 16 environmental variables were collected, and the random forest (RF) and Shapley additive explanations (SHAP) methods were then combined to explore the key factors affecting soil PTEs. An innovative t-distributed random neighbor embedding-RF-SHAP model was then constructed, based on the absolute principal component score and multivariate linear regression model, to quantitatively determine PTE sources. Although average PTE concentrations did not exceed the risk control values, PTE distributions exhibited significant differences. It was found that sodium, soil organic matter, and phosphorus contents were the three most important factors affecting PTEs, and human activities and natural environmental factors both influence PTE contents by altering the soil properties. The proposed model successfully determined PTE sources in the soil, outperforming the original linear regression model with a significantly lower RMSE. Source analysis revealed that the parent material was the main contributor to soil PTEs, accounting for more than half of the total PTE content. Industrial and agricultural activities also contributed to an increase in soil PTEs, with average contributions of 19.91 % and 17.44 %, respectively. Unknown sources accounted for 10.83 % of the total PTE content. Thus, the proposed model provides innovative perspectives on source parsing. These findings provide valuable scientific insights for policymakers seeking to develop effective environmental protection measures and improve the quality of saline-alkali land in the Yellow River Delta.

Contamination, sources and health risks of potentially toxic elements in the coastal multimedia environment of South China

Coastal ecosystems are vulnerable to the accumulation of potentially toxic elements (PTEs), which pose a threat to marine ecosystems and human health. In this study, the concentrations of eight PTEs in a typical area of South China were analysed, and their distributions, seasonal variations, pollution degrees, potential health risks and sources in seawater, sediment and organisms were evaluated. The comprehensive pollution index (CPI), pollution load index (PLI), potential ecological risk index (PERI) and target hazard quotient (THQ) were applied to assess seawater, sediment and organism quality, respectively. The annual mean concentrations of Zn, Hg, Cr and As in the bottom seawater were higher than those in the surface water while those of Pb, Mn and Cu were higher in the surface seawater. The mean content of Hg was higher than the corresponding background value of that in China Shelf Sea sediment. Marine organisms have a high enrichment capacity for Cu, Zn, Cr, Hg, As and Mn in seawater. Based on CPI, the seawater was generally not polluted by PTEs. The PLI and PERI results demonstrated that Hg was the main contamination element in surface sediment. The total target hazard quotient (TTHQ) analysis illustrated that long-term consumption of some fish by children poses a noncarcinogenic health risk, while that risk to adults is negligible. Natural sources, agricultural activity sources, coal burning and industrial emission sources were the main sources of the PTEs in surface sediments according to positive matrix factorization (PMF) model.

Multivariate statistical analysis of potentially toxic elements in the sediments of Quanzhou Bay, China: Spatial relationships, ecological toxicity and sources identification

In this paper, the spatial distribution, pollution degree, ecological toxicity and possible sources of seven potentially toxic elements (PTEs) collected from the surface sediments of Quanzhou Bay (QZB) were analyzed by obtaining concentration measurements. The results indicated that the areas with high Cu, Pb, Zn and Hg concentrations were mainly located in the Luoyang River estuary, while the areas with high contents of Cd and As appeared in the Luoyang River estuary area and in the southern part of QZB, respectively. The contamination indices showed that the Cd pollution degree was slight to serious, while other elements were slightly enriched. The calculation results of the potential ecological risk index (RI) and toxic risk index (TRI) indicated that Cd was the main element posing ecological risk among the PTEs of sediments in QZB, followed by Hg. Moreover, in approximately 30% of the surveyed sites, PTEs exhibited low toxicity to aquatic ecosystems. Finally, the self-organizing map (SOM) and positive matrix factorization (PMF) model were used to determine the PTEs sources. Natural sources, industrial emissions, and the combustion of fossil fuels were three main sources for PTEs in the surface sediments of QZB. This study provides a reference for assessing sediment pollution and managing marine pollution in QZB.

Ecological and human health risk assessment of heavy metals based on their source apportionment in cropland soils around an e-waste dismantling site, Southeast China

An accurate understanding of soil heavy metal (HM) pollution characteristics and source apportionment, and a recognition of the major factors influencing ecological and human health risks (HHRs) are essential for soil HM pollution control and remediation. In this study, 212 surface soils (0-20 cm) and 15 profile soils (0-100 cm) were collected from cropland soils around an e-waste dismantling site in Taizhou city, Zhejiang Province, China. Spatial analysis was used to evaluate the pollution characteristics of HMs (Cd, Cu, Pb, Zn, Cr and Ni). Principal component analysis (PCA) and positive matrix factorization (PMF) were also conducted to quantify their source contributions. A modified source-oriented HHR assessment integrated source-oriented ecological risk and source-oriented HHR assessment was developed to describe the major factors that influenced HHR. Results showed that 94.81 %, 88.21 %, 36.79 % and 47.17 % of Cd, Cu, Pb and Zn, respectively, in surface soils exceeded their screening values in the soil environmental quality standard for agricultural soils (GB 15618-2018). Spatial analysis indicated that high values of Cd, Cu, Pb and Zn were distributed near the e-waste dismantling site. The results of PCA and PMF showed that the primary sources of HMs in the study area are e-waste dismantling activities, natural sources and atmospheric deposition, which contribute 27 %, 46 % and 27 % of HM pollutants, respectively. The results of source-oriented ecological risk and HHR assessment indicated that e-waste dismantling activities and natural sources were primary sources for ecological risk and HHR. However, source-oriented HHR assessment may underestimate the contribution of e-waste dismantling activities by ignoring HM pollution levels. The modified source-oriented HHR assessment highlights that e-waste dismantling activities were major factor that affect noncarcinogenic risk. This study could provide important data support for subsequent environmental remediation of soil HM pollution in cropland soils around e-waste dismantling sites.

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO₂), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.