Spatial Distribution and Pollution Assessment
of Potentially Toxic Elements in Urban Forest Soil
of Nanjing, China

Zhang, Junye; Yu, Fei; Pang, Shaofeng; Yu, Yuanchun

doi:10.15244/pjoes/92812

Cited by 5 publications

(5 citation statements)

References 32 publications

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“…Therefore, it is crucial to obtain a comprehensive understanding of the content and distribution of heavy metals in the soil [14,15]. Although China's exploration into heavy metals in urban soil commenced relatively recently, contemporary scholars have diligently investigated the content, distribution, and sources of soil heavy metal pollution in numerous large-and medium-sized cities, including Haikou, Beijing, Nanjing, and Shanghai [16][17][18][19][20][21][22][23]. The single factor index method was employed to assess the heavy metal pollution of the soil near the river, revealing severe pollution in the area, particularly from Cd [24].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Heavy Metal Contamination and Ecological Risk in Soil within the Zheng–Bian–Luo Urban Agglomeration

Chen,

Zhang,

Wong

et al. 2024

Processes

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As urbanization accelerates, the contamination of urban soil and the consequent health implications stemming from urban expansion are increasingly salient. In recent years, a plethora of cities and regions nationwide have embarked on rigorous soil geological surveys with a focus on environmental quality, yielding invaluable foundational data. This research aims to develop scientifically robust and rational land-use planning strategies while assessing the levels of heavy metal pollution and associated risks. The urban agglomeration encompassing Zhengzhou, Luoyang, and Kaifeng (referred to as Zheng–Bian–Luo Urban Agglomeration) in Henan Province was designated as the study area. Leveraging the Nemerow comprehensive index method alongside the Hakanson potential ecological risk assessment method, this study delved into the pollution levels and potential ecological ramifications of nine heavy metals, namely Cr, Mn, Ni, Cu, Zn, As, Cd, Pb, and Co. Research indicates that the hierarchy of individual potential ecological risks ranges from most to least significant as follows: Cd > Pb > Cr > Ni > Cu > Zn > As > Mn > Co. The concentrations of Cd in both Zhengzhou and Kaifeng surpassed the established background levels. Furthermore, the mean single-factor pollution index values for the heavy metals Cd and Zn exceeded 1, signifying a state of minor pollution. The Nemerow comprehensive index P of Cd and Zn is between 1 < Pcomp ≤ 2, which is considered mild pollution. The comprehensive P values of the other seven metal elements are all less than 0.7, reaching a clean (alert) level. Predominantly, the primary potential risk factor in the superficial soil of the Zheng–Bian–Luo urban agglomeration is Cd, while the ecological risk implications associated with other heavy metal elements are comparatively minimal. The soil environmental quality within the designated study area remains secure, although certain localized areas pose potential risks of heavy metal pollution. A comprehensive assessment of the current state of soil heavy metal pollution is essential to establish a theoretical foundation and provide technical support for soil environmental protection, pollution mitigation, and sustainable utilization.

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Section: Introductionmentioning

confidence: 99%

Assessment of Heavy Metal Contamination and Ecological Risk in Soil within the Zheng–Bian–Luo Urban Agglomeration

Chen,

Zhang,

Wong

et al. 2024

Processes

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“…To overcome these shortcomings, various mathematical theories such as the fuzzy mathematic method [4,[14][15][16], analytic hierarchy process [17,18], grey theory method [19], and extension method [20] have been presented to specify the pollution grade of samples based on measured values of some pollution indicators. These methods have made some achievements in evaluating soil heavy metal pollution, but they have some limitations in their processes.…”

Section: Introductionmentioning

confidence: 99%

The Evaluation of Heavy-Metals Pollution in Soil Based on a Comprehensive Connection Cloud Model

Wu,

Wang,

Long

2023

Pol. J. Environ. Stud.

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Evaluation of heavy metal pollution in soil mass relies mainly on index methods. Choosing suitable methods to process indexes is key to obtaining accurate and reasonable evaluation results. Connection cloud models have been commonly used to evaluate pollution indexes. However, generating a cloud at each grade for each index is a tedious calculation. To address the randomness and fuzziness of soil heavy metal pollution evaluation indicators, we propose a comprehensive connection cloud model that couples the connection clouds of all indicators at each grade as sub-clouds. We establish the model by combining the weights of each indicator to determine the soil heavy metal pollution grade. The proposed model is effective and feasible for the evaluation of soil heavy metal pollution, as demonstrated through examples and comparisons with other methods. The comprehensive connection cloud model overcomes the traditional cloud models' defect of requiring normal distribution for evaluated indicators and considers the interaction between indicators. Thus, it provides a novel route for uncertainty analysis, considering the fuzzy randomness between multiple interrelated indicators.

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“…Much research has reported the sediment quality status of lakes, rivers, reservoirs and groundwater in China, such as the freshwater Poyang Lake [12], eutrophic plateau Erhai Lake [11], Taihu Lake [13,14], deep mountain Sayram Lake [15], the reservoirs of Tongjiqiao Reservoir [16], Three Gorges Reservoir [17] and groundwater [18,19] they were all contaminated with heavy metals to varying degrees, anthropogenic contaminate having become a serious public environmental problem in some lakes. With the rapid developing industrial operations and fast urban expansion since 1970s, soil, water and sediment polluted by heavy metals has been both serious and widespread in many provinces [20][21][22]. For the past few years, researchers have studied the contaminate status of trace elements in arid soil [23], water [24] and sediments [25], as well as ecological heavy metal risks.…”

Section: Introductionmentioning

confidence: 99%

Ecological Heavy Metals Risk of Saline Lake Sediments in Northwestern China

Li¹,

Jiang²,

Yan³

et al. 2020

Pol. J. Environ. Stud.

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Lake sediment as a potential sink and source of contaminants, it is still relatively less known about than the ecological heavy metals risk in an arid region saline lake. The goal of this study aimed to reveal concentrations of Cr, Ni, Cu, Zn, As, Cd and Pb in saline lake sediments, and to evaluate its pollution status, potential ecological risks and sources for sediments in the study area. Here we analyzed 13, 15 and 8 sediment samples from Ebinur Lake, Barkol Lake and Dabancheng Saline Lake, respectively. The mean concentrations of Cr (74.55 mg kg -1 ), Cu (27.75 mg kg -1 ), Zn (73.00 mg kg -1 ), As (37.65 mg kg -1 ), and Cd (0.31 mg kg -1 ) were higher than the background values of the Xinjiang, and the mean enrichment factor (EF) and geo-accumulation index (I geo ) showed that As (EF = 7.44, I geo = 1.35) and Cd (EF = 11.09, I geo = 0.50) in saline lake sediments were moderate and partially seriously contaminated, while Cr, Zn and Cu caused moderate pollution. The potential ecological (RI) seven heavy metals risk assessment degree decreased in the following sequence: Cd (78.77)>As (32.22)>Cu (5.22)>Ni (4.28)>Pb (3.27)>Cr (3.21)>Zn (1.07), and the RI for Cd exhibited moderate to considerable risk. The As and Cd were the major risk factors among the seven metals. Correlation analysis, principal component analysis and hierarchical cluster analysis deduced that Cu, Ni, and Zn originate mainly from a geological background, while As, Cd and Cr were mainly from anthropogenic sources. Anthropogenic activities lead to heavy metals enrichment in sediments, while As and Cd are the primary contaminants in saline lake sediments in northwestern China.

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Spatial Distribution and Pollution Assessment of Potentially Toxic Elements in Urban Forest Soil of Nanjing, China

Cited by 5 publications

References 32 publications

Assessment of Heavy Metal Contamination and Ecological Risk in Soil within the Zheng–Bian–Luo Urban Agglomeration

Assessment of Heavy Metal Contamination and Ecological Risk in Soil within the Zheng–Bian–Luo Urban Agglomeration

The Evaluation of Heavy-Metals Pollution in Soil Based on a Comprehensive Connection Cloud Model

Ecological Heavy Metals Risk of Saline Lake Sediments in Northwestern China

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