A method of identifying priority spatial patterns for the management of potential ecological risks posed by heavy metals

Risk Assessment and Source Apportionment of Heavy Metals in Soils from Handan City

Soil-heavy metals are potentially harmful to the ecosystem and human health. Quantifying heavy metals sources is conducive to pollution control. In this study, 64 surface-soil samples were collected in Handan city. Cr, Mn, Ni, Cu, Zn, Cd and Pb were determined; then, their spatial distribution in the sampling area was drawn by ArcGIS. The pollution index (PI) method, geo-accumulation index (Igeo) method, Nemerow integrated pollution index (NIPI) and pollution load index (PLI) were used to evaluate the pollution level of heavy metals in surface soil; then, an ecological and health risk assessment of soil-heavy metals was carried out. Combined with the spatial distribution, correlation analysis, cluster analysis, PCA and PMF model, the pollution sources of heavy metals in soil were identified and apportioned. The results showed that the average content of Cd was nearly ten times that of the background limit, which was the most serious among the studied metals. In terms of non-carcinogenic risk, Cr had the highest value, followed by Pb. In terms of carcinogenic risk, Cd, Cr, and Ni had an acceptable or tolerable risk. Three pollution sources were identified by cluster analysis and PCA, including traffic sources with Cu, Pb and Cd as main loads, industrial sources with Mn, Cd and Zn as main loads, and natural sources with Cr and Ni as main loads. The PMF model analyzed three main factors: traffic source (17.61%), natural source (28.62%) and industrial source (53.77%). The source categories and the main load elements obtained from the source apportionment results were consistent with the source identification results.

A spatial prioritization method for identifying potential eco-risk distributions of heavy metals in soil and birds

Geochemical approaches are popular for evaluations based on heavy metal concentrations in sediments or soils for eco-risk assessment. This study proposes a systematic geochemical approach (SymGeo) to explore six heavy metals in topsoils and bird tissues and organs of the target birds. We assume that the proposed approach based on field-collected heavy metals in topsoils and feathers can predict the areas with the potential risk of the heavy metals in birds. Finite mixture distribution modeling (FMDM) was used to identify background values of the heavy metal concentrations in topsoil. A spatial enrichment factor (EF), potential contamination index (PCI), contamination degree (Cod), and potential ecological risk index (PRI) based on FMDM results for topsoil, and a potential risk index (PRI_bird) of heavy metals in the birds, were utilized for systematic prioritization of high eco-risk areas. Using multiple EF, PRI, and Cod results and multiple PRI-based maps of the heavy metals in feathers, we systematically prioritized risk areas where there is a high potential for heavy metal contamination in the birds. Our results indicate that heavy metal concentrations in the feather, liver, and kidney are not spatially cross-autocorrelated but are statistically significantly correlated with some heavy metals in topsoil due to external and internal depositions. Further, multiple EF, Cod, and RI distributions for topsoil, along with the PRI of the feather, showed that adequate coverages for potential risk for birds were greater than 71.05% in the top 30% and 84.69% in the top 20% potential eco-risk priority area of heavy metals in bird liver and kidney. Hence, our proposed approach suggests that assessments of heavy metals in bird feathers and topsoils without bird organs can be utilized to identify spatially high-risk areas. The proposed approach could be improved by incorporating water and sediment samples to enhance the crowdsourcing and the species-specific data.

Retraction of invasive Spartina alterniflora and its effect on the habitat loss of endangered migratory bird species and their decline in YNNR using remote sensing technology

Wetland environment and habitat loss increase the rate of biodiversity decline and affect our ecosystems. Yancheng National Nature Reserve (YNNR) is a protected area dedicated to endangered migratory bird species to overwinter. However, it currently has a record low influx of migrating birds and might therefore be losing its founding purpose. We used remote sensing technology to assess and quantify the impacts and effects of invasive halophytes Spartina alterniflora in the habitat loss and shrinkage of endangered bird wintering habitat from 2003 to 2018. We also attempted to ascertain the causes and triggers of avian population decline and its relationship with habitat loss, as these phenomena threaten and endanger species both locally and globally. Our study shows how YNNR has lost about 80% of migratory bird habitat to invasive S. alterniflora and Phragmites australis, a native halophyte plant in the reserve. Furthermore, shoreline erosion triggered the retraction of S. alterniflora and its backward growth toward Suaeda Salsa, the preferred foraging habitat for migratory birds in the zone, which is a possible cause of their decline.

Soil heavy metal contamination assessment in the Hun-Taizi River watershed, China

The Hun-Taizi River watershed includes the main part of the Liaoning central urban agglomeration, which contains six cities with an 80-year industrial history. A total of 272 samples were collected from different land use areas within the study area to estimate the concentration levels, spatial distributions and potential sources of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) with a geographic information system (GIS), principal component analysis (PCA) and canonical correspondence analysis (CCA). Only the concentration of Cd was over the national standard value (GB 15618–2018). However, the heavy metal concentrations at 24.54%, 71.43%, 63.37%, 85.71, 70.33%, 53.11%, and 72.16% of the sampling points were higher than the local soil background values for As, Cd, Cr, Cu, Hg, Ni, Pb and Zn, respectively, which were used as standard values in this study. The maximal values of Cd (16.61 times higher than the background value) and Hg (12.18 times higher than the background value) had high concentrations, while Cd was present in the study area at higher values than in some other basins in China. Cd was the primary pollutant in the study area due to its concentration and potential ecological risk contribution. The results of the potential ecological risk index (RI) calculation showed that the overall heavy metal pollution level of the soil was considerably high. Three groups of heavy metals with similar distributions and sources were identified through PCA. The results of the CCA showed that the distribution of mines was the strongest factor affecting the distributions of Ni, As, Zn, Pb, and Cd. However, Cu was strongly influenced by the distance to the nearest river. These findings can provide scientific support for critical planning and strategies for soil pollution control and removal to support the sustainable development of the study area.

Development of a model to simulate soil heavy metals lateral migration quantity based on SWAT in Huanjiang watershed, China

Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity of heavy metals. A model for heavy metal migration simulation was developed based on the SWAT (Soil and Water Assessment Tool) model. This model took into consideration the influence of soil pH value, soil particle size, runoff volume, sediment amount, concentration of water-soluble heavy metals dissolved in runoff and insoluble absorbed to the soil particles. This model was reasonable in Huanjiang watershed, Guangxi Zhuang Autonomous Region, south China, covering an area of 273 km². The optimal drainage area threshold was determined by analyzing the effects of watershed subdivision on the simulation results to ensure the simulation accuracy. The main conclusions of this paper were: (1) watershed subdivision could affect simulation migration quantity of heavy metals; (2) the quantity of heavy metals transported by sediment accounted for 97%-99% of the total migration quantity in the study watershed. Therefore, sediment played the most important role in heavy metal migration; (3) the optimal drainage area threshold percentage to ensure high simulation accuracy was determined to be 2.01% of the total watershed; (4) with the optimal threshold percentage, this model could simulate the migration quantity of As, Pb and Cd accurately at the total watershed and sub-watershed level. The results of this paper were useful for identifying the key regions with heavy metal migration.

Accumulation risk and sources of heavy metals in supratidal wetlands along the west coast of the Bohai Sea

The heavy metals Al, Cr, Cu, Ni, Pb, Zn, Fe, Mn, As, and Cd in the rainfall-driven supratidal wetlands along the west coast of the Bohai Sea (the areas are named site 1, site 2, site 3, and site 4 from south to north in the gradient in this study) are tested for their accumulation risks and sources. Results show that the distribution and enrichment of the heavy metals in the supratidal wetlands are lower in site 1 than in sites 2–4. The risk indices (RIs) of all sites are less than 150, indicating low–moderate risk. However, the RI values are primarily dominated by the risk indices (E_rⁱ) of As and Cd. The accumulative contribution values of E_rⁱ-As and E_rⁱ-Cd in sites 1, 2, 3, and 4 are 79.05%, 77.80%, 80.54%, and 76.43%, respectively. Additionally, the contamination degree (C_d) and the Nemero comprehensive pollution index (PN) of the supratidal wetland in site 1 are 6.86 and 0.74 respectively, indicating a low-risk state. By contrast, the C_d and PN values of the other three supratidal wetlands are higher than those of site 1, suggesting an increasing accumulation risk for heavy metals in sites 2, 3 and 4. Our analysis indicates that the heavy metals Al, Cr, Mn, and Fe in all the supratidal wetlands mainly originate from the weathering of rocks and their parent materials. Pb is significantly correlated with anthropogenic activities, while Cu, As, and Cd are likely induced by anthropogenic activities and atmospheric deposition. The sources of Ni and Zn should be determined on the basis of the situation of the wetland and its surrounding areas. For example, Ni is mainly affected by anthropogenic activities in site 2, whereas the origins of Ni are soil parent materials or atmospheric depositions in sites 1, 3, and 4. Our results can provide data to support the utilization strategy and sustainable development plans for marine space resources on the coast of the Bohai Sea.

The accumulation risk and sources for heavy metals Al, Cr, Cu, Ni, Pb, Zn, Fe, Mn, As, and Cd were analysed in rainfall-driven supratidal wetlands.

Quantitative contributions of the major sources of heavy metals in soils to ecosystem and human health risks: A case study of Yulin, China

Quantifying source-oriented risk can identify primary pollution sources to help alleviate risks to ecosystems and human health posed by soil heavy metals. Taking Yulin National Energy and Chemical Industry Base as an example, ecosystem and human health risk assessments of each identified source category were quantitatively calculated by combining the Potential Ecological Risk (RI) and Total Carcinogenic Risk (Total-CR)/Total Hazard Index (Total-HI) assessment models with the positive matrix factorization (PMF) receptor model. In this work, an analysis of the Geoaccumulation Index (I_geo), Contamination Index (P_i), RI, CR and HI of heavy metals (As, Cr, Cu, Zn, Cd, Pb, Hg and Mn) identified universal ecosystem risks and both carcinogenic and noncarcinogenic health risks in most sites. Source apportionment results indicated that the dominant source of heavy metals in the soil was coal-related activities (52.5%), followed by industrial activities (22.0%), traffic activities (13.2%) and agricultural activities (12.3%). The source-oriented quantitative risk assessment results showed that coal-related activities are the greatest contributor to RI and Total-HI, while industrial activities are the largest source of Total-CR, which should be controlled, to reduce the carcinogenic health risk posed by exposure to heavy metals.

Potential ecological risk assessment and predicting zinc accumulation in soils

The aims of this study were to investigate zinc content in the studied soils; evaluate the efficiency of geostatistics in presenting spatial variability of zinc in the soils; assess bioavailable forms of zinc in the soils and to assess soil-zinc binding ability; and to estimate the potential ecological risk of zinc in soils. The study was conducted in southern Poland, in the Malopolska Province. This area is characterized by a great diversity of geological structures and types of land use and intensity of industrial development. The zinc content was affected by soil factors, and the type of land use (arable lands, grasslands, forests, wastelands). A total of 320 soil samples were characterized in terms of physicochemical properties (texture, pH, organic C content, total and available Zn content). Based on the obtained data, assessment of the ecological risk of zinc was conducted using two methods: potential ecological risk index and hazard quotient. Total Zn content in the soils ranged from 8.27 to 7221 mg kg^-1 d.m. Based on the surface semivariograms, the highest variability of zinc in the soils was observed from northwest to southeast. The point sources of Zn contamination were located in the northwestern part of the area, near the mining-metallurgical activity involving processing of zinc and lead ores. These findings were confirmed by the arrangement of semivariogram surfaces and bivariate Moran's correlation coefficients. The content of bioavailable forms of zinc was between 0.05 and 46.19 mg kg^-1 d.m. (0.01 mol dm^-3 CaCl₂), and between 0.03 and 71.54 mg kg^-1 d.m. (1 mol dm^-3 NH₄NO₃). Forest soils had the highest zinc solubility, followed by arable land, grassland and wasteland. PCA showed that organic C was the key factor to control bioavailability of zinc in the soils. The extreme, very high and medium zinc accumulation was found in 69% of studied soils. There is no ecological risk of zinc to living organisms in the study area, and in 90% of the soils there were no potentially negative effects of zinc to ecological receptors.

Reclamation history and development intensity determine soil and vegetation characteristics on developed coasts

The question of where and how to carry out reclamation work in coastal areas is still not well addressed in coastal research. To answer the question, it is essential to quantify the impact of reclamation and the associated ecological and/or environmental responses. In this study, ordinary least square (OLS) analysis and geographical weighted regression (GWR) analysis were performed to identify the reclamation variables that affect soil and vegetation characteristics. Reclamation related variables, including residential population (RP), years of reclamation (YR), income per capita (IP), and land use-based human impact index (HII), were used to explain nitrate, ammonium, total phosphorous, and heavy metals in soil, and the height, density, and above-ground biomass of native hydrophytic vegetation. It was found that variables IP, RP, and HII could be used to explain the height of Scirpus and Phragmites australis as well as above-ground biomass with a R² value of no >0.55, and almost all the variables could explain the hydrophytic vegetation characteristics with a higher R² value. In comparison to OLS, GWR more reliably reflected the reclamation effects on soil and vegetation characteristics. By GWR analysis, total soil phosphorous, and nitrate and ammonium nitrogen could be explained by RP, YR, and HII, with the highest Ad-R² value of 0.496, 0.631 and 0.632, respectively. Both of the GWR and OLS analysis revealed that HII and RP were the better variables for explaining the soil and vegetation characteristics. This work demonstrated that coastal reclamation was highly spatial dependent, which sheds a light on the future development of spatial explicit and process-based models to guide coastal reclamation around the world.

Spatial distribution of trace elements and ecotoxicity of bottom sediments in Rybnik reservoir, Silesian-Poland

The aim of study was to integrate chemical analyses and toxicity bioassays in order to assess the environmental risk connected with the presence of trace elements in the sediments. This study examined the ecological significance of trace elements in bottom sediments by applying a set of complementary sediment quality assessment methods sediment quality guidelines (SQGs) (mean probable effect concentration quotient (PECQ)), potential ecological risk index (PERI), contamination degree (C d) and two bioassays: the bacterial luminescence inhibition test with Vibrio fischeri on sediment elutriates and the direct contact test with the ostracod crustacean Heterocypris incongruens. The samples were collected from 50 stations of Rybnik reservoir. The reservoir is a region with enormous concentration of industry, mainly hard coal mining, electric power industry, and transportation. Despite the high diversity in metal concentration in the sediments, the spatial distribution of trace elements in the sediments was very similar. Moreover, the strong positive correlations between individual pairs of trace elements indicate that they may derive from a similar source and move together. According to mean PECQs, 68 % of the samples were potentially non-toxic and 32 % of the samples were potentially toxic. PERI values suggested that 70 % of the sediment sampling sites exhibited low ecological risk from metal pollution while 24 % of the samples had severe and serious risk. Based on our combined evaluation, we believe that Cd and Cu in the sediment samples frequently caused adverse biological effects. Higher toxic responses were observed in the Microtox test than in the Ostracodtoxkit test. All the sediment samples were found toxic to V. fischeri, and 96 % of the samples had effect percentages >50 %. For H. incongruens, 12 % of the sediments were not toxic and 44 % had effect percentages >50 %. In order to perform a complex assessment of the environmental impact of metal pollution, both chemical and ecotoxicological analysis should be carried out.

A method for heavy metal exposure risk assessment to migratory herbivorous birds and identification of priority pollutants/areas in wetlands

Wetlands are important habitats for migratory birds but have been degraded by many anthropogenic factors including heavy metal contamination. Birds inhabiting wetlands are exposed to pollutants. In this study, a method for exposure risk assessment of migratory herbivorous birds and identification of priority pollutants/areas was developed and employed in East Dongting Lake wetland (EDT). Four heavy metals (Cr, Cu, Pb, and Cd) in sedge and soil samples from ten lesser white-fronted goose (Anser erythropus) habitats in EDT were investigated. Results showed that negative effect of Cr and Pb on lesser white-fronted goose may occur while the concentrations of Cu and Cd are considered to be relatively safe. Prioritize threats were decreased in the following sequence: Cr > Pb > Cu > Cd. Cr and Pb were considered to be the priority pollutants. Spatial interpolation based on geostatistical methods showed that Spring Breeze Lake should draw much attention. Furthermore, regions with high hazard index were identified to be priority areas of EDT for risk management.

Risk assessment of heavy metals from combustion of pelletized municipal sewage sludge

Fly ash and slag are important by-products obtained from combustion of municipal sewage sludge (MSS) after pelletization. The quantitative environmental impact assessment of heavy metals in fly ash and slag, compared to MSS, were performed in accordance with bioavailability and eco-toxicity, geo-accumulation index (GAI), risk assessment code (RAC), and potential ecological risk index (PERI). The results demonstrated that not only direct but also long-term bioavailability and eco-toxicity of heavy metals in fly ash and slag decreased except direct bioavailability and eco-toxicity of Pb in fly ash. The GAI demonstrated that combustion significantly weakened (P < 0.05) the pollution levels of heavy metals. PERI indicated that all risks attributed to heavy metals were significantly lowered (P < 0.05) from 777.07 (very high risk) in MSS to 288.72 (moderate risk) and 64.55 (low risk) in fly ash and slag, respectively. In terms of the RAC, seven heavy metals had low even no risk to the environments after combustion besides As in slag. The environmental risk of heavy metals in fly ash and slag was decreased compared with MSS. However, the results of PERI showed that fly ash had a moderate risk.

Characterizing the physical and demographic variables associated with heavy metal distribution along urban-rural gradient

This paper describes a study of how the demographic and physical variables affected the heavy metal (HM) contamination along the urban-rural gradient in PuDong New District, Shanghai. The road density (RDi) and the percentage of built-up areas (BAi) were calculated for various widths of buffers around the soil sampling sites. Through distance allocation, the demographic values of the population change index (PCI) were assigned, with the value being associated with the nearest town. We initiated the use of the population migration rate from 2000 to 2010, i.e., PCI, to represent the urbanization rate. Regression analysis between the soil HM concentrations and the PCI, the RD, and the BA was estimated. The results indicated that the PCI significantly affected the Cd and Cu distribution (p < 0.05), while the RD of the 3-km buffer affected the Pb concentrations. The BA of 2-km buffers affected the spatial distribution of Cd, Cu, and Zn. Zn was also affected by the RD within the 4-km buffer. Using the median values of the PCI and the BA of the 2-km buffer, and the RD of the 3-km buffer, logistic analysis was performed to identify the priority areas for managing HM hazards. The two identified priority areas were the towns of Kangqiao and Zhuqiao, both of which were rapidly urbanized areas with higher PCI values. Our research demonstrated that understanding the rate of urbanization may be as important as the degree of urbanization when examining associated HM contamination patterns.

Avian Conservation Areas as a Proxy for Contaminated Soil Remediation

Remediation prioritization frequently falls short of systematically evaluating the underlying ecological value of different sites. This study presents a novel approach to delineating sites that are both contaminated by any of eight heavy metals and have high habitat value to high-priority species. The conservation priority of each planning site herein was based on the projected distributions of eight protected bird species, simulated using 900 outputs of species distribution models (SDMs) and the subsequent application of a systematic conservation tool. The distributions of heavy metal concentrations were generated using a geostatistical joint-simulation approach. The uncertainties in the heavy metal distributions were quantified in terms of variability among 1000 realization sets. Finally, a novel remediation decision-making approach was presented for delineating contaminated sites in need of remediation based on the spatial uncertainties of multiple realizations and the priorities of conservation areas. The results thus obtained demonstrate that up to 42% of areas of high conservation priority are also contaminated by one or more of the heavy metal contaminants of interest. Moreover, as the proportion of the land for proposed remediated increased, the projected area of the pollution-free habitat also increased. Overall uncertainty, in terms of the false positive contamination rate, also increased. These results indicate that the proposed decision-making approach successfully accounted for the intrinsic trade-offs among a high number of pollution-free habitats, low false positive rates and robustness of expected decision outcomes.