Analysis of Historical Sources of Heavy Metals in Lake Taihu Based on the Positive Matrix Factorization Model

Characterization and Risk Assessment of Heavy Metals in River Sediments on the Western Bank of Taihu Lake, China

In this study, nine heavy metals (Cd, Cr, As, Hg, Pb, Cu, Ni, Be, and Sb) in the sediments of 17 typical rivers on the western bank of Taihu Lake were determined. Several statistical methods were applied to analyze the distribution, sources, pollution status, and potential ecological risk of these metals. The mean concentrations of heavy metals in sediments other than Be exceeded their local background values. Geoaccumulation index and potential ecological risk index analyses demonstrated that most sediment samples were contaminated and may pose ecological risks, especially those from the Taihu Lake estuary. In particular, Cd concentrations indicated moderate contamination and potentially serious to severe ecological risk. Principal component, cluster, and correlation analyses demonstrated that Ni, Sb, Cr, and Cu were derived from industrial sources, whereas the other metals had complex origins.

Heavy Metals in River Sediments: Contamination, Toxicity, and Source Identification-A Case Study from Poland

This study investigated the spatial distribution, contamination, potential ecological risks and quantities of pollutant sources of six heavy metals (HMs) in sediments of 47 rivers. The catchments of the investigated rivers are situated in Poland, but some of them are located in Slovakia, the Czech Republic, and Germany. Cluster analysis was applied to analyze the spatial distribution of Cd, Cr, Cu, Ni, Pb, and Zn in river sediments. Moran I and Getis-Ord Gi* statistics were calculated to reveal the distribution pattern and hotspot values. Principal component analysis (PCA) and positive matrix factorization (PMF) were used to identify pollution sources. Furthermore, geochemical indices and sediment quality guidelines allowed us to assess sediment contamination and potential toxic effects on aquatic biota. The results showed that in 1/3rd of the rivers, the HM pattern and concentrations indicate sediment contamination. The EF, PLI, and MPI indices indicate that concentrations were at a rather low level in 2/3rd of the analyzed rivers. Only in individual rivers may the HMs have toxic effects on aquatic biota. Spatial autocorrelation analysis using the Moran I statistic revealed a random and dispersed pattern of HMs in river sediments. PCA analysis identified two sources of HMs' delivery to the aquatic environment. Cr, Cu, Ni, Pb, and Zn originate from point and non-point sources, while Cd concentrations have a dominant natural origin. The PMF identified three sources of pollution. Among them, urban pollution sources are responsible for Cu delivery, agricultural pollution for Zn, and industrial pollution for Ni and Cr. Moreover, the analysis showed no relationship between catchment land-use patterns and HM content in river sediments.

The sources risk assessment combined with APCS/MLR model for potentially toxic elements in farmland of a first-tier city, China

With the rapid economic development, potentially toxic elements (PTEs) are continuously migrating, transforming, and enriching in farmland through atmospheric deposition and other media, posing threats to food security and human health. At present, there are few quantitative studies on the health risks of PTEs sources in farmland. In this study, absolute principal component score-multiple linear regression (APCS-MLR) receptor model was used to quantify the pollution sources of PTEs in farmland in Suzhou of Yangtze River Delta Economic Zone, China. Combined with geoaccumulation index (I_geo) and health risk assessment model, the source risk of PTEs was further quantified. The results show that Cd has reached the level of unpolluted to moderate polluted (0 < I_geo < 1); the total hazard index (THI) and total carcinogenic risk (TCR) index of PTEs are acceptable for adults, but not for children (THI > 1, TCR > 1 × 10^-4). The results of APCS-MLR source apportionment were industrial sources (25.65%), agricultural sources (20.00%), traffic sources (16.81%), and domestic pollution sources (9.71%). The I_geo values of all pollution sources were less than 0, and no ecological risk was caused. The contribution patterns of pollution sources to THI and TCR in adults and children are similar. Industrial pollution sources pose the greatest non-carcinogenic risk to humans, accounting for 47.35% and 47.26% of adults and children, respectively; for carcinogenic risks, domestic pollution sources contribute the most among all identified pollution sources, accounting for 27.71% and 27.73% of adults and children, respectively. In general, this study emphasizes the need to strengthen the supervision of industrial pollution sources and domestic pollution sources in the study area to reduce the health risks to children.

Determination of priority control factors for the management of soil trace metal(loid)s based on source-oriented health risk assessment

Trace metal(loid)s (TMs) in soils can seriously threaten the ecological environment and human health. With the limitation of resources and costs, determining priority control factor is critical for managing soil TM pollution. To explore the pollution characteristics, source apportionment, and human health risk of TMs, a total of 209 surface soil samples were collected from Anqing City, China. Results showed that all the average values of TM concentration, except for Cr, were higher than their corresponding background value. Using a Positive matrix factorization model coupled with Correlation analysis, four sources (including agricultural sources, atmospheric deposition sources, industrial sources, and natural sources) were identified as the determinants for the accumulation of soil TMs, with the contribution rates of 12.4%, 8.1%, 64.1%, and 15.4%, respectively. The assessment of probabilistic health risks revealed that Non- carcinogenic risks of all populations were acceptable (HI < 1), while Carcinogenic risks were all at a high level (TCR > 10E-04). Agricultural pollution and As were identified as priority control factors, according to the analysis results of the relationship among TMs, pollution sources and health risks. Our findings provide scientific support for decision-makers to formulate target control policies and reduce management costs of soil pollution.

Pollution characteristics and source identification of soil metal(loid)s at an abandoned arsenic-containing mine, China

Mining activities can result in serious contamination of soil by heavy metal(loid)s. In this study, the sources and spatial distribution of metal(loid)s, and the risks to public health from these metal(loid)s at an abandoned arsenic mine site were explored. The mean concentrations of arsenic (As), cadmium (Cd), mercury (Hg), manganese (Mn), lead (Pb), antimony (Sb), strontium (Sr), and thallium (Tl) in the soil in the mining area were higher than the mean background values. The main pollutants from the mining activities were As, Hg, and Sb. Five pollutant sources were identified using an approach that combined statistical methods, a positive matrix factorization model, and historical information analysis. As, Hg, Sb, and Tl were associated with the mining resources and related activities (37.29%); Mn (15.57%) and Sr (15.96%) were mainly from crustal origin and pedogenesis, respectively; Pb, Sb, and Tl were mainly from industrial sources (17.57%), and Cd was mainly from the production and application of phosphorous fertilizer (13.60%). Using incremental spatial autocorrelation crystallized that As, Hg, and Sb were mainly contained within 500 m of their source. There were formed existing non-carcinogenic hazards and carcinogenic risks from As, and potential carcinogenic risks from Cd, in the soil for those living locally.

Application of APCA-MLR receptor model for source apportionment of char and soot in sediments

Black carbon (char and soot) has attracted increasing attention due to its important role in the global carbon cycle, adsorption of pollutants (polycyclic aromatic hydrocarbons (PAHs) and heavy metals), climate effects and threats to human health. However, few studies have included source analysis of black carbon (char and soot). In this study, the levels of char, soot and PAHs in sediments of West Taihu Lake were assessed, and an absolute principal component analysis followed by multiple linear regression (APCA-MLR) receptor model was used to successfully analyze the material sources of char and soot, providing a new perspective and method for exploring the sources of char and soot. The contributions of coal combustion sources to char and soot are 62.0% and 43.2%, respectively, which are significantly higher than those of biomass combustion sources (13.7% and 19.8%). The contributions of oil combustion sources to char and soot are 24.3% and 37.0%, respectively. The contributions of coal, oil and biomass combustion to char and soot have similar spatial distributions: the coal combustion sources and biomass combustion sources are mainly affected by urban development, which is largely distributed in the northwest of the study area, whereas the oil combustion sources are mainly affected by automobile traffic and lake ports, which are mainly distributed in the west of the study area, and these effects decrease with an increase in offshore distance.

Characterizing the anthropogenic-induced trace elements in an urban aquatic environment: A source apportionment and risk assessment with uncertainty consideration

The spatial distribution of water quality status, especially in water bodies near intensively urbanized areas, is tightly associated with patterns of human activities. For establishing a robust assessment of the sediment quality in an urban aquatic environment, the source apportionment and risk assessment of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg, and Pb in sediments from an anthropogenic-influenced lake were carried out with considering uncertainties from the analysis methods, random errors in the sample population and the spatial sediment heterogeneity. The distribution analysis of the trace metals with inverse distance weighting-determined method showed that the pollutants were concentrated in the middle and southern areas of the lake. According to the self-organizing map and constrained positive matrix factorization receptor model, agricultural sources (24.8%), industrial and vehicular sources (42.5%), and geogenic natural sources (32.7%) were the primary contributors to the given metals. The geogenic natural had the largest random errors, but the overall result was reliable according to the uncertainty analysis. Furthermore, the stochastic contamination and ecological risk models identified a moderate/considerable contamination level and a moderate ecological risk to the urban aquatic ecosystem. With consideration of uncertainties from the spatial heterogeneity, the contamination level of Hg, and the ecological risk of Cd in had a 20-30% probability of the increase.

High Abundances of Microplastic Pollution in Deep-Sea Sediments: Evidence from Antarctica and the Southern Ocean

Plastic pollution in Antarctica and the Southern Ocean has been recorded in scientific literature since the 1980s; however, the presence of microplastic particles (<5 mm) is less understood. Here, we aimed to determine whether microplastic accumulation would vary among Antarctic and Southern Ocean regions through studying 30 deep-sea sediment cores. Additionally, we aimed to highlight whether microplastic accumulation was related to sample depth or the sediment characteristics within each core. Sediment cores were digested and separated using a high-density sodium polytungstate solution (SPT) and microplastic particles were identified using micro-Fourier-transform infrared spectroscopy (μFTIR). Microplastic pollution was found in 93% of the sediment cores (28/30). The mean (±SE) microplastics per gram of sediment was 1.30 ± 0.51, 1.09 ± 0.22, and 1.04 ± 0.39 MP/g, for the Antarctic Peninsula, South Sandwich Islands, and South Georgia, respectively. Microplastic fragment accumulation correlated significantly with the percentage of clay within cores, suggesting that microplastics have similar dispersion behavior to low density sediments. Although no difference in microplastic abundance was found among regions, the values were much higher in comparison to less remote ecosystems, suggesting that the Antarctic and Southern Ocean deep-sea accumulates higher numbers of microplastic pollution than previously expected.

A modified receptor model for historical source apportionment of polycyclic aromatic hydrocarbons in sediment

Pollution of polycyclic aromatic hydrocarbons (PAHs) in the environment is becoming increasingly serious with the development of the economy. Source analysis is the key step in reducing PAHs pollution in the environment, and existing methods are usually based on receptor models. However, when these methods are applied to the distribution of PAHs in sediments, overestimation or underestimation often occurs. Therefore, this paper proposes an improved model based on principal component analysis and multiple linear regression. The model has been applied to study the pollution of PAHs in sediments of Taihu Lake in China over several decades. Compared with existing models, principal component analysis followed by multiple linear regression of source (PCA-MLRS) can identify specific emission sources and quantify the impact of each emission, and the source resolution accuracy of the strong toxic molecules BaP and DBA is significantly higher than that of other models. Biomass combustion source is the main material source of Phe, Ant, Flu and Pyr in Taihu Lake sediment, and their contribution rates are 85.2%, 44.8%, 58.9% and 62.2%, respectively. The coal combustion source is the main material source of the 5-ring molecule BaP and the 6-ring molecules InP and BP. The contribution rates of coal combustion to BaP, InP and BP are 70.1%, 72.9% and 72.1%, respectively, and this contribution has increased since 1985. The contribution of petroleum oil combustion source and coal combustion source to PAHs in sediments of Taihu Lake is consistent. They are the main sources of heavy molecular PAHs such as BaA, BbF, BkF and DBA, and their contributions are 56.5%, 36.8%, 43.9% and 67.3% respectively. The results are related to the different emission and management characteristics of PAHs from different sources and the different behavior characteristics of low and high molecular weight PAHs in the environment.

Temporal-spatial trends in potentially toxic trace element pollution in farmland soil in the major grain-producing regions of China

Pollution from potentially toxic trace elements (PTEs) is becoming serious and widespread in farmland soils in China, threatening food security and human health. Few large-scale studies systematically analyzed their temporal-spatial trends over vast spatially elaborate sites. The soil health status of the main grain producing areas was first announced based on a total of 3662 spatially elaborate farmland topsoil sites from the 1980s to the 2000s. Nearly 21.5% of sites were polluted, although only slightly. Pollution from the Cd, Ni, Cu, Zn, and Hg was more serious. Pollution was more extensive in the south than in the north. There was an increasing trend in the PTE concentrations, especially Cd with a growth of 21–25%, and in the proportion of mixed pollution at the sites (19.3%), Cd (21.5%), Pb (3.6%), Zn (5.7%), Cu (7.0%), and Hg (3.1%). Furthermore, temporal variations in severe Cd pollution and mixed-level Hg pollution in the north are severer. This study may provide guidance for policymakers regarding the protection and high-risk area of PTE contamination in the soils.

Tracing anthropogenic cadmium emissions: From sources to pollution

Cadmium (Cd), a widely concerned heavy metal, is toxic to humans and ecosystems. In this paper, a Cd-polluted town in southeast China was selected to estimate the Cd emissions of human activities into surface water, soil and atmospheric environment. The analysis shows that the total amount of Cd emitted into the environment in 2015 was approximately 43.5 kg, and the majority of those emissions were discharged into the water, accounting for approximately 90.4% of the total Cd emissions. The remaining Cd emissions into the soil and atmosphere accounted for 9.5% and 0.1%, respectively. The industrial production (IP) is the dominant source of anthropogenic Cd emissions, which contributes to 62.1% of the total emissions. The other contributors include aquaculture (AQ), wastewater treatment (WT), living consumption (LC), crop farming (CF) and animal breeding (AB); each accounted for less than 10% of the total emissions. Pigment production is the largest source of IP emissions. According to the results of correlation analysis, the pigment enterprises are responsible for the heavy Cd pollution in local soil. By comparing the spatial position and combing with the local watercourses, the study reveals that the irrigated watercourse is the transmission channels of soil Cd pollution. This study contributes to the analysis of connecting the emission inventory, environmental media and transmission channels of the heavy metal Cd and provides policy supports for the local governments to adopt a life cycle Cd management approach.

Determination of influencing factors on historical concentration variations of PAHs in West Taihu Lake, China

The adsorption of polycyclic aromatic hydrocarbons (PAHs) by components such as elemental carbon (EC), total organic carbon (TOC), and particles is different, and EC and PAHs are good materials for reconstructing historical human activity patterns and pollution conditions. In this study, the effects of EC (soot and char), TOC and particles of different grain size on PAHs in surface sediments were quantitatively analysed, and their historical concentrations in a sediment core from western Taihu Lake were reconstructed. The contents of soot, TOC, clay, EC and char explained 57.2%, 27.6%, 26.0%, 24.0% and 16.4%, respectively, of the PAH concentrations in surface sediments. The correlation between the soot and PAH levels was significantly higher than that between the char, TOC, and clay contents and PAH levels, and PAHs were mainly affected by the local economic development and human activity, as indicated by metrics of population, highway mileage, coal burning, and industrial output. With the development of the economy of the Taihu Lake Basin, the composition of PAHs in the sediments has changed: the proportion of low-molecular-weight PAHs decreased from 42.4% to 17.5%, and that of high-molecular-weight PAHs increased from 58.7% to 82.5%. The concentration of PAHs in pore water from Taihu Lake over the past 100 years was reconstructed and ranged from 43.1 to 961.2 μg L^-1, with an average of 180.7 μg L^-1. After China's reform and opening up, the concentrations of various PAHs in Taihu Lake changed from safe to chronic pollution levels. The ratios of lead (Pb) isotopes and the diagnostic ratios of PAHs showed that the main sources of PAHs in western Taihu Lake sediments were human activities such as coal and petroleum combustion.

Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China

In order to quantitatively study the effect of environmental protection in China since the twenty-first century and the environmental pollution projected for the next ten years (under the model of extensive economic development), this paper establishes a Bayesian regulation back propagation neural network (BRBPNN) to analyze the typical pollutants (i.e., cadmium (Cd) and benzopyrene (BaP)) for Taihu Lake, a typical Chinese freshwater lake. For the periods 1950–2003 and 1950–2015, the neural network model estimated the BaP concentration for the database with Nash-Sutcliffe model efficiency (NS) = 0.99 and 0.99 and root-mean-square error (RMSE) = 3.1 and 9.3 for the total database and the Cd concentration for the database with NS = 0.93 and 0.98 and RMSE = 45.4 and 65.7 for the total database, respectively. In the model of extensive economic development, the concentration of pollutants in the sediments of Taihu reached the maximum value at the end of the twentieth century and early twenty-first century, and there was an inflection point. After the early twenty-first century, the concentration of pollutants was controlled under various environmental policies and measures. In 2015, the environmental protection ratio of Cd and BaP reached 52% and 89%, respectively. Without environmental protection measures, the concentrations of Cd and BaP obtained from the neural network model is projected to reach 2015.5 μg kg⁻¹ and 407.8 ng g⁻¹, respectively, in 2030. Based on the results of this study, the Chinese government will need to invest more money and energy to clean up the environment.

Modeling of Trace Metal Migration and Accumulation Processes in a Soil-Wheat System in Lihe Watershed, China

Samples of wheat and soil were collected in the Lihe watershed in East China, the migration and accumulation processes of four common trace metals (Cu, Pb, Cd and Ni) in each part of the wheat plant (root, stem, leaf and grain) were analyzed, and a mechanistic model was proposed to simulate these processes based on wheat growth techniques. Model results show that Cu and Cd migrate more easily with wheat grains, while most Pb and Ni accumulate in roots. Modeling results were shown to be relatively good, with an error of 25.29% in value and 26.38% in fluctuation, and had smaller dispersion degree than actual measurement results. Monte Carlo simulation results also match quite well with actual measurement results, and modeling results are slightly smaller in the simulation of Leaf-Cu, Grain-Cu and Leaf-Ni. Trace metal pollution risk in wheat is evaluated based on this model; our results show that the northwest and northeast parts in the research area are not suitable for growing wheat. In general, this model is relatively accurate, and can evaluate the wheat pollution risk before seeding wheat, providing scientific references for the early selection of wheat safety sowing areas.