Source Apportionment Of Heavy Metals Research Articles

Contamination, fraction, and source apportionment of heavy metals in sediment of an industrialized urban river in China

In this study, we conducted an analysis of the heavy metal concentrations, health risk assessment, fraction and source interpretation in surface and core sediments from main stream of the Pearl River and Pearl River Estuary (RRE) area. Results showed that the higher deposited heavy metal concentrations in sediments occur at the Pearl River. The concentrations of heavy metals in surface sediments from the studied locations are in a descending order: Zn > Cr > Cu > Ni > Pb > Cd. Regarding chemical fractions, Cd showed the highest proportion of acid soluble fraction (F1) among all studied heavy metals. The high mobility of Cd poses a significant threat to water bodies and the surrounding environment. The potential ecological risk index (RI) showed the Pearl River sediments exhibited significantly higher values than the estuary sediments. Cd was found to be the primary contributor to potential ecological risk, accounting for 74% of RI. The health risk assessment showed the total hazard index (HI) for child was exceeded 1 mainly driven by Zn, indicating that the child population was at risk of non-carcinogenic effects. Besides, unacceptable carcinogenic risk in both Pearl River and estuary area were observed for children. The positive matrix factorization (PMF) model was used to ascertain sources of six heavy metals and apportion their contributions in sediments. The results showed that the source contributions of natural, industrial, and mixed sources from coal combustion and traffic emissions accounted for 39.81%, 34.10%, 26.10%.

Pollution Assessment and Source Apportionment of Heavy Metals in the Surrounding Soil of Typical Mining Areas in Tongling, Anhui Province

To study the level of heavy metal pollution and ecological risks in the soil around typical mining areas in Tongling, a total of 150 soil samples were collected from the study area. The content characteristics of 10 elements, namely, As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Fe, and Zn, in the soils were analyzed. Methods including enrichment factor, the geo-accumulation index, single-factor pollution index, Nemero comprehensive pollution index, and potential ecological risk index were used to evaluate the pollution status of heavy metals in the soil of the study area. The pollution sources of heavy metals in the soil were also analyzed using correlation analysis, cluster analysis, and principal component analysis. The results showed that except for Cr and Fe, the average contents of the other eight heavy metal elements were higher than the soil background values in the study area. Pb, Zn, As, Cu, and Cd had a high degree of variation and were significantly affected by external interference. The spatial distribution showed that both Cr and Ni showed a decreasing trend from the edge to the central region, whereas the other eight heavy metals showed a decreasing trend from the central region to the surrounding areas. The pollution level of Cd and Cu in the soil of the research area was relatively severe. The overall ecological risk was at a medium to low level. Cd and Hg were the main contributing factors. As, Cd, Cu, Fe, Mn, Pb, and Zn mainly came from agricultural, industrial, and transportation sources, whereas Cr and Ni were mainly from natural sources. However, the sources of Hg were relatively complex. The research results can provide a scientific basis for the prevention and control of soil heavy metal pollution in metal mining areas, as well as the remediation of mine pollution.

Pollution Characteristics and Source Apportionment of Heavy Metals in Topsoil of Counties Along the Shandong Section of the Yellow River

The 25 counties along the Shandong section of the Yellow River are the core areas for promoting the ecological protection and high-quality development of the Yellow River in Shandong Province. Moreover, it is of great significance to study the current situation, sources, and potential risks of heavy metal pollution in the topsoil in this region. In this study, 103 soil samples were collected from the 25 counties along the Shandong section of the Yellow River, and the contents of eight heavy metals （As, Cu, Pb, Cr, Zn, Ni, Cd, and Hg） were determined. The pollution characteristics of heavy metals were analyzed and evaluated using the geological accumulation index and potential ecological risk index. Correlation analysis and the positive matrix factorization （PMF） model were used to analyze the sources of heavy metals. The results showed that the average contents of Cu and Cr were lower than that of the background values of soils, whereas the average contents of As, Pb, Zn, Ni, Cd, and Hg were 1.16, 1.42, 1.05, 1.14, 2.29, and 1.85 times higher than that of the background values, respectively, and the average contents of all eight elements were lower than the screening value of soil pollution risk in agricultural land. In terms of different heavy metal variations, the coefficient of variation （CV） of Cu and Cd was higher than 0.500, indicating high variations, whereas As, Pb, Cr, Zn, Ni, and Hg showed moderate variation. Cd and Hg were slightly polluted, whereas the other six elements were not polluted. Cd and Hg had a moderate potential ecological risk level, whereas the other six elements were at a low level. Correlation analysis and PMF model showed that the sources of heavy metals in the study area were influenced by four factors, i.e., agricultural activities, natural sources, industrial emissions, and atmospheric dust from coal combustion and vehicle exhaust emissions, and the relative contribution rates were 32.4%, 34.9%, 16.5%, and 16.2%, respectively.

Pollution Assessment and Source Apportionment of Heavy Metals in Sediments of Subsidence Section of Luling Mine in the Tuohe River, China

Pollution Assessment and Source Apportionment of Heavy Metals in Sediments of Subsidence Section of Luling Mine in the Tuohe River, China

A Modified Model for Quantitative Heavy Metal Source Apportionment and Pollution Pathway Identification.

Current source apportionment models have successfully identified emission sources and quantified their contributions. However, when being utilized for heavy metal source apportion in soil, their accuracy needs to be improved, regarding migration patterns. Therefore, this work intended to improve the pre-existing principal component analysis and multiple linear regression with distance (PCA-MLRD) model to effectively locate pollution pathways (traffic emissions, irrigation water, atmospheric depositions, etc.) and achieve a more precise quantification. The dataset of soil heavy metals was collected from a typical area in the Chang-Zhu-Tan region, Hunan, China in 2021. The identification of the contribution of soil parent material was accomplished through enrichment factors and crustal reference elements. Meanwhile, the anthropogenic emission was identified with principal component analysis and GeoDetector. GeoDetector was used to accurately point to the pollution source from a spatial differentiation perspective. Subsequently, the pollution pathways linked to the identified sources were determined. Non-metal manufacturing factories were found to be significant anthropogenic sources of local soil contamination, mainly through rivers and atmospheric deposition. Furthermore, the influence of irrigation water on heavy metals showed a more pronounced effect within a distance of 1000 m, became weaker after that, and then gradually disappeared. This model may offer improved technical guidance for practical production and the management of soil heavy metal contamination.

Pollution Source Apportionment of Heavy Metals in Cultivated Soil Around a Red Mud Yard Based on APCS-MLR and PMF Models

In order to explore the characteristics and sources of heavy metal pollution in cultivated soil around a red mud yard in Chongqing， the content and spatial distribution characteristics of eight heavy metal elements （Cd， Cr， Hg， Ni， Pb， As， Cu， and Zn） in the soil were analyzed， and the single factor pollution index method and Nemerow comprehensive pollution index method were used to evaluate the characteristics of heavy metal pollution in soil. On the basis of correlation analysis， the APCS-MLR and PMF models were used to quantitatively analyze the sources of heavy metals. The results showed that the average contents of the other seven heavy metal elements were higher than the background values of Chongqing soil， except for that of Cr. The heavy metals Cd， Hg， and As were moderately polluted， and Pb， Cu， Ni， and Zn were mildly polluted. The spatial distribution pattern of Cr， Ni， Pb， Cu， and Zn in the soil was similar， and there was a very significant positive correlation between them （P < 0.01）. The spatial distribution characteristics of Cd， Hg， and As were significantly different， and there was no significant correlation between them （P > 0.05）. The source apportionment showed that the sources of heavy metals in the soil in the study area were relatively complex， and the APCS-MLR and PMF models could identify the same four pollution sources， namely red mud yard percolation emission and natural sources， thermal power generation emission sources， agricultural activities and natural sources， and non-ferrous metal smelting emission sources. There was little difference in the results of source apportionment between the two models. The contribution rates of the four pollution sources in the APCS-MLR model were 51.8%， 18.0%， 15.9%， and 14.3%， respectively， whereas those in the PMF model were 45.9%， 12.8%， 21.5%， and 19.8%， respectively.

Combining Cd and Pb isotope analyses for heavy metal source apportionment in facility agricultural soils around typical urban and industrial areas

Facility agriculture enhances food production capabilities. However, concerns persist regarding heavy metal accumulation resulting from extensive operation of this type of farming. This study integrated the total content, five fractions, and isotope composition of Cd and Pb in intensively farmed soils in regions characterized by industrialization (Shaoguan, SG) and urbanization (Guangzhou, GZ), to assess the sources and mechanisms causing metals accumulation. We found significantly more severe Cd/Pb accumulation and potential mobility in SG than GZ. Cd displayed higher accumulation levels and potential mobility than Pb. The distinct isotopic signals in SG (−0.54 to 0.47‰ for δ114/110Cd and 1.1755 to 1.1867 for 206Pb/207Pb) and GZ (−0.86 to 0.12‰ for δ114/110Cd and 1.1914 to 1.2012 for 206Pb/207Pb) indicated significant differences in Cd/Pb sources. The Bayesian model revealed that industrial activities and related transportation accounted for over 40% and approximately 30%, respectively, of the average contributions of Cd/Pb in SG. While urban-related (26.6%) and agricultural-related (26.3%) activities primarily contributed to Cd in GZ. The integration of δ114/110Cd and 208Pb/206Pb has further enhanced the regional contrast in sources. The present study established a comprehensive tracing system for Cd-Pb, providing crucial insights into the accumulation and distribution of these metals in facility agricultural soils.

Remarkable contamination characteristics, potential hazards and source apportionment of heavy metals in surface dust of kindergartens in a northern megacity of China

It is essential to understand the impact of heavy metals (HMs) present in the surface dust (SD) of kindergartens on children, who are highly sensitive to contaminated dust in cities in their growth stage. A study was conducted on 11 types of HMs present in the SD of 73 kindergartens in Beijing. This study aims to assess the pollution levels and sources of eleven HMs in Beijing’s kindergartens surface dust (KSD), and estimate the potential health risks in different populations and sources. The results indicate that Cd has the highest contamination in the KSD, followed by Pb, Zn, Ni, Ba, Cr, and Cu. The sources of these pollutants are identified as industrial sources (23.7%), natural sources (22.1%), traffic sources (30.4%), and construction sources (23.9%). Cancer risk is higher in children (4.02E-06) than in adults (8.93E-06). Notably, Cr is the priority pollutant in the KSD, and industrial and construction activities are the main sources of pollution that need to be controlled. The pollution in the central and surrounding areas is primarily caused by historical legacy industrial sites, transportation, urban development, and climate conditions. This work provides guidance to manage the pollution caused by HMs in the KSD of Beijing. Environmental implicationChildren within urban populations are particularly sensitive to pollutants present in SD. Prolonged exposure to contaminated SD significantly heightens the likelihood of childhood illnesses. The pollution status and potential health risks of HMs within SD from urban kindergartens are comprehensively investigated. Additionally, the contributions from four primary sources are identified and quantified. Furthermore, a pollution-source-oriented assessment is adopted to clearly distinguish the diverse impacts of different sources on health risks, and the priority pollutants and sources are determined. This work holds pivotal importance for risk management, decision-making, and environmental control concerning HMs in KSD.

Speciation characteristics, ecological risk assessment, and source apportionment of heavy metals in the surface sediments of the Gomishan wetland

Metal contamination is one of the worldwide environmental issues. The main aim of this study was to evaluate the concentration, probable environmental risk, and source of investigated elements (Al, As, Co, Cr, Cu, Fe, Mn, Ni, and Zn) in sediments and water of the Gomishan wetland. Sediment contamination indices revealed sediments were solely polluted by As. The potential ecological risk index (RI), toxic risk index (TRI), and chemical speciation assessments indicated no major ecological hazards for investigated metals. Correlation analysis and principal component analysis (PCA) indicated that all studied metals in the Gomishan wetland sediments derived from natural sources. HPI, and HEI indices showed that the water quality in terms of hazardous components was inappropriate for aquatic life.

Concentration, spatial distribution, and source apportionment of heavy metals in agricultural soils from the Yarlung Zangbo River Basin, Tibetan Plateau

In this study, 112 agricultural topsoil samples were collected from the Yarlung Zangbo River Basin (YZRB) and its two tributaries, and the concentrations, spatial distribution, source apportionment, and potential ecological risk of eight heavy metals (Cd, Hg, Pb, Cr, Cu, Zn, Ni and As) were analyzed. The mean concentrations of Cu, Pb, Zn, Cr, Ni, Cd, As, Hg and Pb were 33.91, 28.21, 86.93, 109.04, 73.58, 0.12, 21.49 and 0.05 mg/kg, respectively. Except for Pb, the concentration of heavy metals in soil exceeded the corresponding local background values, but did not exceed the national soil pollution risk screening values. In terms of spatial distribution, it showed that the heavy metals were enriched in the Nianchu River, and followed by Lhasa River and YZRB mainstream. Furthermore, the ecological risks were ordered as Hg > Cd > As > Ni > Cu > Pb > Cr > Zn, and the potential ecological risk index of the YZRB fell in the range of moderate ecological risk. The high-risk areas were in the facility agriculture fields of the Nianchu River, which was mainly related to agricultural activities. In addition, the positive matrix factorization results showed traffic, agricultural activities, natural weathering of the parent minerals, and atmospheric transport sources were the four sources in soils of the YZRB. This work will provide a scientific reference to develop appropriate pollution control measures and facility farmlands management in the YZRB of Tibetan Plateau.

Quantitative source apportionment of heavy metals in sediments from the Bohai Sea, China

In this study, the sources of nine heavy metals (Cd, As, Hg, Cu, Pb, Ni, Cr, Zn, and Co) in the sediments of the Bohai Sea were quantitatively identified through a positive factor matrix to provide better advice for marine and coastal management. In Bohai Sea sediments, most metals fell below detectable contamination levels, including As, Cu, Pb, Ni, Cr, Zn, and Co. Unfortunately, Bohai Sea sediments were moderately to significantly enrich with Cd and Hg, posing potentially adverse ecological risks to aquatic ecosystems. Our modeled results showed three factors representing natural, anthropogenic, and atmospheric deposition sources. Enriched Cd and Hg were likely derived from anthropogenic activities through river runoff and atmospheric deposition due to adjacent Zn smelting and chlor-alkali production, respectively. The other metals were mainly derived from natural sources.

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models

The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors.

The spatial distribution and source apportionment of heavy metals in soil of Shizuishan, China

Environmental pollution of heavy metals in the typical coal industrial city should be paid more attentions nowadays. The spatial distribution and source apportionment of 8 heavy metals (i.e., Cd, Cr, Co, Zn, Ni, Cu, Pb and Mn) from topsoil samples (158) of Shizuishan city in Ningxia Hui Autonomous Region of China were investigated using principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geographic information system (GIS). These results showed that the mean concentrations of Cd, Cr, Co, Zn, Ni, Cu and Pb were higher than their soil background values in Ningxia. 99.36% of soil samples were heavily polluted according to analysis of integrated Nemerow pollution index (PN), whereas 81.65% of soil samples exhibited the highly strong potential ecological risk by ERI (the comprehensive of potential ecological risk index) values. The source apportionment results showed that eight heavy metals in soil were mainly from natural (32.39%), industrial (26.56%), traffic emission/coal consumption (20.18%) and atmospheric deposition source (12.73%). Typically, Zn, Mn and Ni were derived from natural source, whereas Cr and Co were mainly derived from industrial sources. Cu was from the multiple sources, whereas Pb and Cd were weighted primarily from traffic emission/coal consumption source and atmospheric deposition source, respectively. These findings were crucial for the prevention and control of heavy metals pollution in Shizuishan city.

Synergistic/antagonistic toxicity characterization and source-apportionment of heavy metals and organophosphorus pesticides by the biospectroscopy-bioreporter-coupling approach

Many anthropogenic chemicals are manufactured and eventually enter the surrounding environment, threatening food security and human health. Considering the additive or synergistic effects of pollutant mixtures, there is an expanding need for rapid, cost-effective and field-portable screening methods in environmental monitoring. This study used a recently developed biospectroscopy-bioreporter-coupling (BBC) approach to investigate the binary toxicity of Ag(I), Cr(VI) and four organophosphorus pesticides (dichlorvos, parathion, omethoate and monocrotophos). Ag(I) and Cr(VI) altered the toxicity mechanisms of pesticides, explained by the synergistic or antagonistic effect of Ag/Cr-induced cytotoxicity and pesticide-induced genotoxicity. The discriminating Raman spectral peaks associated with organophosphorus pesticides were 1585 and 1682 cm−1, but 750, 1004, 1306 and 1131 cm−1 were found in heavy metal and pesticide mixtures. More spectral alterations were related to pesticides rather than Ag(I) or Cr(VI), hinting at the dominant toxicity mechanisms of pesticides in mixtures. Ag(I) supplement significantly increased the levels of reactive oxygen species induced by organophosphorus pesticides, attributing to the increased permeability of cell membrane and entrance of toxic substances into the cells by the oligodynamic actions. This study lends deeper insights into the interactions between microbes and pollutant mixtures, offering clues to assess the cocktail effects of multiple pollutants comprehensively.

Source Analysis and Risk Assessment of Heavy Metals in Soil of County Scale Based on PMF Model

This study explores the pollution characteristics, risks, and sources of heavy metals in small-scale areas. Rongcheng District, Jieyang City, Guangdong Province was considered as the study area and enrichment factor (EF), pollution load index (PLI), potential ecological risk index (RI), and US EPA health risk assessment model were used to evaluate its environmental risk. Moreover, the source apportionment of heavy metals was analyzed through correlation analysis, the characteristic of spatial distribution, and a PMF model. The results showed that the mean concentrations of ω(Cr), ω(Hg), ω(As), ω(Pb), ω(Ni), ω(Cd), ω(Cu), and ω(Zn) were 54.87, 0.25, 8.35, 56.00, 15.38, 0.35, 30.56, and 124.23 mg·kg-1, respectively. The mean concentrations of all elements exceeded the local soil background value. In terms of EF level, Cr, As, Pb, and Ni showed negligible accumulation; Zn and Cu showed minor accumulation; and Hg and Cd showed moderate accumulation. The mean value of the pollution load index was 2.37, with a severe pollution level, and the eight elements were in different pollution levels. In total, the study region suffered severe ecological risk, Hg and Cd presented strong ecological risk, and other elements presented slight ecological risk. The non-carcinogenic risks under the three exposure paths were within the acceptable level. The carcinogenic risks (CR) of adults and children were 9.81E-05 and 5.59E-04, respectively, and Cr and As were the main contributors of CR. The results showed that the four sources of heavy metals were transportation sources (37.02%), parent material sources (18.53%), atmospheric deposition sources (26.49%), and industrial sources (17.96%).

Source Analysis Based on the Positive Matrix Factorization Models and Risk Assessment of Heavy Metals in Agricultural Soil

Soil heavy metal pollution is a severe and growing problem, and it is crucial to assess the level of soil heavy metal contamination and determine the origins of pollutants. However, there is limited research on soil heavy metal source apportionment and its carcinogenic and non-carcinogenic hazards. Positive Matrix Factorization (PMF) is a powerful technique for source apportionment of pollutants in environmental matrices such as atmospheric particulate matter and soil, as it can handle missing and imprecise data to ensure data reliability, among other benefits. In order to explore the distribution characteristics and main sources of heavy metals in agricultural land, the contents of Cd, Cr, Cu, Pb, and Ni were collected and determined. The positive matrix factorization (PMF) model was used to analyze the source of heavy metals in the soil in the study area, and the human health risk evaluation was carried out. The results showed that (1) the coefficient of variation of Cd in the four areas was much higher than that of the other four heavy metals, which showed strong variability; (2) the content and distribution of heavy metals in different regions were different under the influence of different environments; (3) the PMF model analysis showed that the heavy metal pollution sources in the four areas were divided into two types: the soil parent material, which had industrial pollution, traffic pollution, and agricultural pollution; and the contribution rate of each pollution source; (4) the non-carcinogenic risks of heavy metals in children at all points in the study area were greater than those of adults, and the carcinogenic risks were the opposite of the carcinogenic risk in the study area. And the most serious carcinogenic risk in the study area was the harm caused by oral ingestion of heavy metal Cr into the adults’ bodies.

Source apportionment of heavy metals in PM2.5 samples and effects of heavy metals on hypertension among schoolchildren in Tianjin.

The prevalence of hypertension in children has increased significantly in recent years in China. The aim of this study was to provide scientific support to control ambient heavy metals (HMs) pollution and prevent childhood hypertension.In this study, ambient HMs in PM2.5 were collected, and 1339 students from Tianjin were randomly selected. Positive matrix factorization (PMF) wasused to identify and determine the sources of HMspollution. The generalized linear model, Bayesian kernel machine regression (BKMR) and the quantile g-computation method were used to analyze the relationships between exposure to HMsand the risk of childhood hypertension. The results showed that HMs in PM2.5 mainly came from four sources: soil dust, coal combustion, incineration of municipal wasteand the metallurgical industry. The positive relationships between As, Se and Pb exposures and childhood hypertension risk were found. Coal combustion and incineration of municipal waste were important sources of HMs in the occurrence of childhood hypertension.Based on these accomplishments, this study could provide guidelines for the government and individuals to alleviate the damaging effects of HMs in PM2.5. The government must implement policies to control prime sources of HMs pollution.

Ecological risk, dynamics in fingerprinting, and source apportionment of heavy metals in soils from plateau in Upper Yellow River, Qinghai Province, China

Ecological risk, dynamics in fingerprinting, and source apportionment of heavy metals in soils from plateau in Upper Yellow River, Qinghai Province, China

Occurrence, Bioavailability, and Environmental Risk of Heavy Metals and Metalloids in the Sediment and Drawdown Area of Fengshuba Drinking Water Reservoir

ABSTRACT Heavy metal and metalloid pollution in reservoir systems has attracted widespread attention due to their toxic, persistent, and nonbiodegradable characteristics. This study investigated the distribution and risks of heavy metals and metalloids in the sediment and drawdown area of the Fengshuba reservoir system. Sediment phase exhibited substantial heavy metal and metalloid pollution and higher ecological risk that the drawdown phase. There were significant differences in the structure and composition of the total metal content and the bioavailable fraction between the sediment and the drawdown area, which indicates that the total metal content and the bioavailable fraction might dominantly regulate by a complex combination of sediment characteristics. Positive Matrix Factorization model was used to identify sources of heavy metals and metalloids pollution and revealed that heavy metals and metalloids contamination in Fengshuba reservoir might originate from anthropogenic activities. Evaluations from risk assessment show that As and Cd in the reservoir system may pose health risks. Knowledge of distribution, potential risk assessment, and source apportionment of heavy metals and metalloids in the Fengshuba drinking water is critical in promoting the sustainable development of the reservoir, developing water management and conservation strategies in the Fengshuba reservoir.

Source-oriented ecological and resistome risks associated with geochemical enrichment of heavy metals in river sediments

Heavy metals (HMs) pose ecological and resistome risks to aquatic systems. To efficiently develop targeted risk mitigation strategies, apportioning HM sources and assessing their source-oriented risks are essential. Although many studies have reported risk assessment and source apportionment of HMs, yet few have explored source-specific ecological and resistome risks associated with geochemical enrichment of HMs in aquatic environments. Therefore, this study proposes an integrated technological framework to characterize source-oriented ecological and resistome risks in the sediments of a plain river in China. Several geochemical tools quantitatively showed Cd and Hg had the highest pollution levels in the environment, with 19.7 and 7.5 times higher than their background values, respectively. Positive matrix factorization (PMF) and Unmix were comparatively used to apportion sources of HMs. Essentially, the two models were complementary and identified similar sources including industrial discharges, agricultural activities, atmospheric deposition and natural background, with contributions of 32.3–37.0%, 8.0−9.0%, 12.1−15.9% and 42.8−43.0%, respectively. To analyze source-specific ecological risks, the apportionment results were integratively incorporated into a modified ecological risk index. The results showed anthropogenic sources were the most significant contributors to the ecological risks. Particularly, industrial discharges majorly contributed high- (44%) and extremely high (52%) ecological risk for Cd, while agricultural activities posed a greater percentage of considerable-(36%) and high- (46%) ecological risk for Hg. Furthermore, the high-throughput sequencing metagenomic analysis identified abundant and diverse antibiotic resistance genes (ARGs), including some carbapenem-resistance genes and emerging genes such as mcr-type in the river sediments. Network and statistical analyses displayed significant correlations between ARGs and geochemical enrichment of HMs (ρ > 0.8; P-value <0.01), indicating their important impacts on resistome risks in the environment. This study provides useful insights into risk prevention and pollution control of HMs, and the framework can be made applicable to other rivers facing environmental challenges worldwide.