Comprehensive risk assessment of heavy metals in national soil-rice systems and prediction of metal concentration in human blood.

随着城市化进程的不断加快，不同用地类型上产生的降雨径流中重金属含量高且差异较大，而目前仍缺乏对降雨径流所携带的重金属风险评价的研究.以苏州城区为研究对象，选取商业区、居住区、历史文化保护区和文教区，监测降雨径流中铜（Cu）、锌（Zn）和铅（Pb）3种常见重金属浓度，通过物种敏感性分布（SSD）曲线获取预测无效应浓度（PNEC），基于重金属的生态有效性，应用风险商（RQ）法对重金属的生态风险进行评价.结果表明：以6场有效降雨事件的事件平均浓度（EMC）统计结果的平均值为分析依据，对照《地表水环境质量标准》（GB 3838—2002），苏州城区径流中的Zn、Cu浓度满足Ⅱ类水质标准，Pb浓度则劣于Ⅴ类水质标准；主要受地面交通活动和屋面材料的影响；在不同用地类型内Cu、Pb和Zn浓度的分布存在一定差异，商业区受重金属污染程度最为严重，其余3种用地类型均不同程度受到不同重金属的污染，对应的3种重金属的生态风险在不同用地类型内也显示相同规律；不同的重金属产生不同的环境行为，导致对水生生物的毒性差异较大，降雨径流中的重金属浓度在水环境中产生的有效生态风险程度为Pb > Cu > Zn.研究认为Cu、Zn和Pb对淡水生物的生态风险均达到高风险程度，而我国目前的《地表水环境质量标准》未充分考虑生态影响，低估了部分重金属的生态风险.;With the rapid development of urbanization, heavy metal pollution resulting from runoff increase and vary greatly in different land use. However, there is still a lack of research on the risk assessment of heavy metal carried by the runoff. In Suzhou urban area, four land use types including commercial area, residential area, historical and cultural protection area, and cultural and educational area were selected to monitor the content of Cu, Zn and Pb in rainfall runoff. Further, the ecological risk of these three heavy metals was evaluated by risk quotient (RQ), which was on the basis of predicted no-effect concentration (PNEC) obtained by species sensitivity distribution (SSD) curve. Based on the event mean concentration (EMC) of six effective rainfall events, compared with the Environmental Quality Standard for Surface Water (GB 3838-2002), statistical results show that Zn and Cu in the rainfall runoff meet grade Ⅱ water quality standard, while Pb is inferior to grade V water quality standard, which are mainly affected by the traffic activities and roofing materials in different land use types. Correspondingly, commercial area is polluted by all these three heavy metals worst, the other areas are polluted in different degrees by different heavy metals, resulting in a large difference in toxicity to aquatic organisms. Generally, the ecological risks by heavy metals in rainfall runoff are in high-risk degree, and in the order of Pb > Cu > Zn. Therefore, the current environmental quality standard for surface water in China does not fully consider the ecological impact and underestimates the ecological risks of heavy metals.

Exploring the pollution characteristics and ecological risks of urbanization on lakes in urban fringe areas has guiding significance for the control and scientific management of heavy metal pollution in lakes in urban fringe areas. Taking the West Lake in Kaifeng city as an example, the samples of the sediments and surface water of the lake were collected, and the contents of heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) were measured, assessing the degree and ecological risk of heavy metal pollution using the Geo-Accumulation Index (Igeo) and Potential Ecological Risk Index methods (RI); and the sources of pollution were identified. The results show that the heavy metal concentrations in the surface water of the West Lake in Kaifeng city are generally low; average concentrations of Cd, Cu, Zn, Cr, Ni, Pb, and As in sediments are 3.120, 1.810, 1.700, 1.540, 1.000, 0.990, and 0.430 times higher than the background value of fluvo-aquic soil, respectively. The sequence of the average Igeo from high to low is Cd (1.020) > Cu (0.220) > Zn (0.160) > Cr (0.000) > Pb (−0.610) > Ni (−0.640) > As (−1.850). Among them, contaminations with Pb are classed as moderately polluted; As pollution is relatively light, while other heavy metals are unpolluted. The average Potential Ecological Risk Coefficient (E) values for seven heavy metals are Cd (93.500) > Cu (9.040) > Ni (4.990) > Pb (4.950) > As (4.290) > Cr (3.080) > Zn (1.700). Cd is at a considerable potential ecological risk, while other heavy metals are at low ecological risks. Heavy metal pollution in sediment of West Lake in Kaifeng mainly comes from traffic activities such as yacht machinery wear and gasoline burning. The research findings provide a scientific foundation for developing effective mitigation strategies against heavy metal contamination in peri-urban lacustrine ecosystems.

Probabilistic ecological risk assessment of heavy metals using the sensitivity of resident organisms in four Korean rivers

Despite the prevalence of discharge of large volumes of heavy-metal-bearing seawater from coal-fired power plants into adjacent seas, studies on the associated ecological risks remain limited. This study continuously monitored concentrations of seven heavy metals (i.e. As, Cd, Cr, Cu, Hg, Pb, and Zn) in surface seawater near the outfall of a coal-fired power plant in Qingdao, China over three years. The results showed average concentrations of As, Cd, Cr, Cu, Hg, Pb, and Zn of 2.63, 0.33, 2.97, 4.63, 0.008, 0.85, and 25.00 μg/L, respectively. Given the lack of data on metal toxicity to local species, this study investigated species composition and biomass near discharge outfalls and constructed species sensitivity distribution (SSD) curves with biological flora characteristics. Hazardous concentrations for 5% of species (HC5) for As, Cd, Cr, Cu, Hg, Pb, and Zn derived from SSDs constructed from chronic toxicity data for native species were 3.23, 2.22, 0.06, 2.83, 0.66, 4.70, and 11.07 μg/L, respectively. This study further assessed ecological risk of heavy metals by applying the Hazard Quotient (HQ) and Joint Probability Curve (JPC) based on long-term heavy metal exposure data and chronic toxicity data for local species. The results revealed acceptable levels of ecological risk for As, Cd, Hg, and Pb, but unacceptable levels for Cr, Cu, and Zn. The order of studied heavy metals in terms of ecological risk was Cr > Cu ≈ Zn > As > Cd ≈ Pb > Hg. The results of this study can guide the assessment of ecological risk at heavy metal contaminated sites characterized by relatively low heavy metal concentrations and high discharge volumes, such as receiving waters of coal-fired power plant effluents.

This study selected Guiyu Town, Guangdong Province as the research area, the content of 15 kinds of metals (As, Be, Cd, Co, Cr, Cu, Hg, Li, Mn, Ni, Sb, Sn, Pb, V, and Zn) in the soil was determined, and the content of heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in the rice of this research area was identified. Multivariate statistical analysis and a human health risk assessment model were used to investigate the distribution characteristics and health risk of heavy metals in a soil-rice system. The results showed that Hg, Sb, and Sn in the surface soil surrounding the electronic waste dismantling area have obvious accumulation effect. The average content of Cd and Hg exceeds the Ⅱ standard limit of the "Environmental Quality Standard for Soil" (GB 156182-1995), and that Guiyu Town is more seriously polluted than Chendian Town and Simapu Town. The multivariate statistical analysis showed that Cu, Sb, Ni, Zn, Sn, Pb, and Hg originated from the surrounding electronic waste dismantling activities, Cd and Be originated from other man-made sources of pollution, and V, Li, Cr, Co, As, and Mn originated from natural sources. Heavy metal evaluation concentration in the soil-rice system by heavy metal migration accumulated in rice are in compliance with national food hygiene standards, and the enrichment ability is Cd > Zn > Cu > Ni > As > Cr > Hg > Pb. Soil heavy metal health risk assessment results showed that children are more susceptible to heavy metal pollution, and handling-oral ingestion is the main way of soil exposure risk. The non-carcinogenic risk and carcinogenic risk of heavy metals in the soil of each town are acceptable. The health risk in Guiyu Town through ingestion of rice is mainly from the elements that include As, Cr, Cu, and Ni.

For persistent organic pollutants, a concern of environmental supervision, predicted no-effect concentrations (PNECs) are often used in ecological risk assessment, which is commonly derived from the hazardous concentration of 5% (HC5) of the species sensitivity distribution (SSD). To address the problem of a lack of toxicity data, the objectives of this study are to propose and apply two improvement ideas for SSD application, taking polycyclic aromatic hydrocarbons (PAHs) as an example: whether the chronic PNEC can be derived from the acute SSD curve; whether the PNEC may be calculated by HC10 to avoid solely statistical extrapolation. In this study, the acute SSD curves for eight PAHs and the chronic SSD curves for three PAHs were constructed. The quantity relationship of HC5s between the acute and chronic SSD curves was explored, and the value of the assessment factor when using HC10 to calculate PNEC was derived. The results showed that, for PAHs, the chronic PNEC can be estimated by multiplying the acute PNEC by 0.1, and the value of the assessment factor corresponding to HC10 is 10. For acenaphthene, anthracene, benzo[a]pyrene, fluoranthene, fluorene, naphthalene, phenanthrene, and pyrene, the chronic PNECs based on the acute HC10s were 0.8120, 0.008925, 0.005202, 0.07602, 2.328, 12.75, 0.5731, and 0.05360 μg/L, respectively.

Bio-based plasticisers have been developed as sustainable alternatives to phthalate-based plasticisers. However, limited information on their potential ecotoxicological effects on aquatic organisms could hinder their widespread adoption in the market. This study addresses this gap by providing ecotoxicological data on epoxidised methyl oleate (EMO), a potential bio-based plasticiser. This study evaluated the acute toxicity of EMO on five aquatic species (Moina macrocopa, Daphnia magna, Chlamydomonas reinhardtii, Chlorella vulgaris and Macrobrachium lanchesteri) to develop a species sensitivity distribution (SSD) curve for determining the predicted no-effect concentration (PNEC) of EMO for ecological risk assessment. Additionally, the biodegradation potential of EMO in aquatic environments was assessed using the OECD 301F Manometric Respiratory Test. These results indicate that EMO exhibits a concentration-dependent toxic effect on all tested species. The SSD curve, developed using a normal distribution and a Maximum Likelihood Estimation fit model, yielded 0.359 mg/L for hazardous concentration for 5% of species (HC05). This HC05 value suggests that EMO poses a minimal ecological risk, as it exceeded the water solubility limit (0.012 mg/L). Furthermore, EMO demonstrated favourable biodegradation potential under aerobic conditions. At a concentration of 30 mg/L, EMO achieved 60% biodegradation within four days of incubation, whereas at 100 mg/L, the same level of biodegradation was achieved by Day 11. These findings underscore the importance of assessing the environmental impact of bio-based plasticisers and highlight the EMO’s potential as an eco-friendly alternative to less biodegradable, petroleum-based plasticisers.

Assessing ecological risk of heavy metals in sediment cores using in-situ monitoring and species sensitivity distribution.

Heavy metals (HMs) are naturally occurring elements that have high natural background levels in the environment. Therefore, it is important to conduct ecological risk assessment and identify potential sources of HMs. In the past, studies were conducted at the regional scale. The accuracy of those studies could not meet the needs of spatial planning and natural resource management. Therefore, it is necessary to conduct ecological risk assessment at the township scale. In this study, 1092 soil samples (from 0-20 cm depth) were collected in the town of Reshui, an area with high background levels of soil HMs with the parent material of carbonatite, which is commonly found in Southwest China. The town of Reshui is a multi-ecological risk superimposed area where the ecological risk is high. In this study, concentrations of HMs (Cd, Cr, As, Hg, Pb, Cu, Zn, and Ni) in the topsoil were analyzed, and statistical analysis (SA), geographic information system (GIS) modeling, and positive matrix factorization (PMF) analysis were performed. The geoaccumulation index (Igeo) and potential ecological risk index (PERI) were applied for the ecological risk assessment and quantification of the sources of the soil HMs. The mean values of HM concentrations in the topsoil were 18.1, 1.18, 174.1, 202.2, 0.09, 71.1, 34.9, and 167.2 mg ·kg-1for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, respectively, which were considerably higher than the average background value (ABV) in soils in Yunnan Province except for As and Pb. The average concentrations of Cd, Cr, Cu, and Ni exceeded the screening values specified in the soil contamination risk in agricultural land (GB 15618-2018) by 5.82, 1.16, 4.04, and 1.02 times, respectively. The Igeo value shows that the major pollutant is Cu in the surface soil of the study area, followed by Cr, and Cd. Speciation analysis of HMs indicates that HMs (Cr, As, Pb, Cu, Zn, and Ni) mainly exist in the residual form, mostly from the geological background with low bioavailability. The potential effective components of Hg have higher levels, but the total amount of Hg and its pollution risk are lower. Cd has a high bioavailability ratio, is easy to enter the soil solution and be absorbed by crops, and is the HM with the highest pollution risk in the study area. The PERI shows that the proportions of low ecological risk, moderate risk, and high risk soil samples are 44.23%, 54.40%, and 1.37% of the total number of samples, respectively. Hg and Cd were the major sources of risk because of their high toxicity coefficient. The PMF analysis indicates that there are four major sources of HMs in the study area: human activity, natural sources, coal mining and traffic emissions, and agricultural sources with the risk contribution ratios of 9.29%, 53.67%, 11.23%, and 25.81%, respectively. The PMF analysis effectively quantified the ecological risk from these sources, providing a reference for further pollution control and prevention measures.

In ecological risk assessment, the Predicted No Effect Concentration (PNEC) of a substance is generally derived by one of two methods: either by applying an Assessment Factor (AF) or by using a Species Sensitivity Distribution (SSD). With the AF method, which is the conventional way, the PNEC is determined by dividing the lowest No Observed Effect Concentration (NOEC) by an AF of a certain fixed magnitude. With the SSD method, which is becoming increasingly used in the European Union and the United States, an HC5 value (Hazardous Concentration for 5% of species) is estimated from the NOEC and then divided by an AF to derive the PNEC. This study aimed to explore the most appropriate AF and the most effective application of each method. The performances of the SSD and AF methods were compared on the assumption that the better method is that in which more PNECs are lower than HC5. We concluded that the performance of these methods depends on sample size and variation in species sensitivity. As the sample size increases (i.e., if there are more toxicity data), the performance of each method increases. The performance of the AF method is better when variation in species sensitivity is small (i.e., all species tend to have a similar NOEC), but it declines as variation in sensitivity rises, implying that persisting with either of the methods may misrepresent the ecological risk. Our results suggest that the variation in sensitivity is an important factor affecting the ecological risk and more effort should be paid to understanding why the variation varies depending on chemical substances.

Predicted no-effect concentration for eight PAHs and their ecological risks in seven major river systems of China

The necessity for the aquatic ecological risk assessment for benzophenone-3 (BP-3) is increasing due to its high toxic potential and high detection frequency in freshwater. The initial step in the ecological risk assessment is to determine predicted no-effect concentration (PNEC). This study derived PNEC of BP-3 in freshwater using a species sensitivity distribution (SSD) approach, whilst existing PNECs are derived using assessment factor (AF) approaches. A total of eight chronic toxicity values, obtained by toxicity testing and a literature survey, covering four taxonomic classes (fish, crustaceans, algae, and cyanobacteria) were used for PNEC derivation. Therefore, the quantity and quality of the toxicity data met the minimum requirements for PNEC derivation using an SSD approach. The PNEC derived in this study (73.3 μg/L) was far higher than the environmental concentration detected in freshwater (up to 10.4 μg/L) as well as existing PNECs (0.67~1.8 μg/L), mainly due to the difference in the PNEC derivation methodology (i.e., AF vs. SSD approach). Since the SSD approach is regarded as more reliable than the AF approach, we recommend applying the PNEC value derived in this study for the aquatic ecological risk assessment of BP-3, as the use of the existing PNEC values seems to unnecessarily overestimate the potential ecological risk of BP-3 in freshwater.

Water pollution by metals and metalloids promotes toxic effects to aquatic biota especially in mining regions. Environmental legislation applied to protect aquatic life from the toxicity of metals relies on the definition of protective values (PVs) for each compound. Among methods used to define PVs, Species Sensitivity Distribution (SSD) curves enable the derivation of the Predicted No Effect concentration (PNEC). In this context, this is one of the first studies to propose the construction of acute and chronic split SSD curves built separately for three groups of freshwater organisms (algae, invertebrates and fish) to derive PNEC values for the 14 metals most commonly observed in iron ore mining tailings. Data used to construct split SSD curves were derived from the USEPA ECOTOX knowledgebase and EnviroTox databases and segregated according to the freshwater organism group and as “acute” or “chronic” toxicity. Then, split SSD curves were built using a minimum of nine species for each group to determine the hazardous concentration to 5% of species (HC5) and PNEC values for each group. Once PNEC were derived, a framework was proposed to calculate the Bioavailabity Factor (BioF) used to adjust values for local bioavailability conditions considering water quality characteristics in different regions. The lowest acute PNEC were observed for algae and invertebrates and corresponded to Silver (Ag). Nearly half of calculated PNEC were below current PVs in practice in Brazil, United States (US), United Kingdom (UK), Canada and European Union (EU). Results reinforce the pertinence of: (i) splitting SSD curves to define PVs for metals; and (ii) taking bioavailability into consideration to correct PNEC for local conditions. In addition, outcomes suggest that it is critical to rethink PVs related to metals for aquatic life protection, mainly in Brazil and Minas Gerais state, a region known for extensive mining activity. Finally, PNEC values obtained in this study may be used for ecological risk assessment studies, especially in areas affected by mining and other activities that result in pollution by metals and metalloids, such as Brazil.

Roadside soils are regarded as a reservoir for heavy metal pollution, which potentially leads to ecosystem deterioration as well as serious hazard to human health. A comprehensive investigation was conducted for the levels, relationship with soil properties, and potential sources of heavy metals (Hg, Cu, Zn, Pb, Cd, and Cr) in roadside soils in six cities (Changzhi, Jincheng, Yuncheng, Linfen, Xinzhou, Datong) of Shanxi Province; and the corresponding ecological risk and human health risk associated with the concentrations of heavy metals were addressed. Heavy metal concentrations of 112 roadside soil samples in the surveyed cities were, in decreasing order, Zn, Cu, Cr, Pb, Cd, and Hg, which were higher than corresponding background values. The highest concentrations were in Changzhi. The results of Pearson correlation analysis demonstrated that positive correlations in varying degrees existed between soil properties such as electrical conductivity, total nitrogen, total phosphorus, and total organic carbon with specific heavy metals and that negative correlations were observed for clay and electrical conductivity. Anthropogenic sources related to traffic emissions and industrialization were the main sources of heavy metals in roadside soils according to principal component analysis. The ecological risk assessments were achieved by pollution index and potential risk index, indicating that contamination with Hg was the most serious, which posed the highest risk to the ecosystems in the surveyed cities; and the ecological risk in Changzhi ranked at the top compared with other cities. For the human health risk assessment, the results demonstrated that the noncarcinogenic and carcinogenic risks were in the acceptable range in the surveyed cities. However, there was a higher health risk from heavy metal exposure for children than adults, and the main exposure pathway was soil ingestion. In addition, Changzhi was the city with the highest noncarcinogenic and carcinogenic risks, and the main human health risks were posed by Cr contamination in roadside soil, which was different from the results of ecological risks. Both results of ecological and health risk assessment demonstrated that the higher risk exhibited in southern and southeastern cities than northern cities in Shanxi Province. Environ Toxicol Chem 2023;42:1485-1500. © 2023 SETAC.

Conflicting results of ecological and health risk assessment of perfluorinated compounds in major river basins in China.