Pollution and Ecological Risk Evaluation of Heavy Metals in the Soil and Sediment around the HTM Tailings Pond, Northeastern China

Abstract

Tailings ponds are a main heavy metal pollution source in mining areas. In this study, the geo-accumulation index (Igeo) and the potential ecological risk index (RI) are used to evaluate the environmental impact of Hongtou Mountain (HTM) tailings pond on the surrounding area. Farmland soil, surface water, and sediment samples in the Hun River around the HTM tailings pond were collected. Heavy metal contents in the samples were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Results show that Cu, Zn, and Cd content in the farmland soil and sediment around the lower reaches of the Hun River (HTM tailings pond section) are obviously higher than the upper reaches. The Igeo values show that the farmland soil near the outlet of the tailings pond is the most polluted area. Cu was classified as moderate–strongly pollution, Zn was moderately pollution, and Cd was strongly pollution. Cd is the major pollutant in farmland soil, the monomial ecological risk (Eri) for Cd is a very high potential ecological risk. The potential ecological risk of sediment in the dry season is more serious than in the raining season. In the dry season, the Igeo index shows strong pollution for Cu and Cd at the confluence of the Hun River and the tributary from the HTM tailings pond, and a moderate–strongly pollution for Zn. Whereas, the Eri index shows that the monomial ecological risk for Zn at H3 is low, and Cu is moderate. The potential ecological risk at H3 is high, and Cd is the main source of the ecological risk around the HTM tailings pond.

Land Use Change and Its Impact on Landscape Ecological Risk in Typical Areas of the Yellow River Basin in China

“…In view of the relation between landscape pattern and ecological risk, the landscape disturbance index and landscape vulnerability index are used to construct a LERA model [ 21 , 22 , 23 , 24 , 25 ]. The landscape disturbance index is composed of landscape fragmentation index, landscape separation index, and landscape subdimension index.…”

“…The ecological risk assessment index system is constructed from the risk source intensity, the receptor exposure, and the risk effect. The other model directly evaluates the LER from the landscape pattern and uses the landscape ecological index from the perspective of landscape ecology to reflect the ecological effect of land use and land cover change (LULCC) [ 23 , 24 , 25 , 26 ]. Comparing these two models, the conclusion is that the model based on the landscape perspective is more suitable for evaluating the ecological risks caused by human activities, since human activities will have an immense influence on the landscape pattern.…”

Assessment of the Heavy Metal Contamination of Roadside Soils Alongside Buddha Nullah, Ludhiana, (Punjab) India

“…Thus, the study of heavy metal pollution in soils is the need of the hour. Many studies have been conducted to explore the spatial distribution of heavy metal pollution in roadside soils [17][18][19][20][21][22][23][24].…”

“…However, a number of parameters, the huge data and the variability of data, can designate the level of pollution, but make it difficult to compare the pollution levels of various sites. To overcome this problem, a broad ranging approach has been applied by various researchers to assess the soil pollution, which includes the usage of various indices, such as the heavy metal pollution index (HPI), geoaccumulation index (Igeo), enrichment factor (EF), contamination factor (CF) and ecological risk index (RI) [21,24,[34][35][36][37][38][39][40][41].…”

Lead-Zinc Mine Tailings Valorization Through Fly Ash-Based Geopolymer for Building Material: Synthesis, Microstructure, and Mechanical Properties

“…The continuous in ow of toxic substances, radioactive elements, and other harmful substances into the ecosystem, polluting the soil, is indeed a serious outcome of tailings storage. (W. Zhang et al 2020), water (Sheoran and Sheoran 2006)and air (Csavina et al 2012).…”