Effect of soil organic matter-mediated electron transfer on heavy metal remediation: Current status and perspectives

Kou, Bing; Yuan, Ying; Zhu, Xiaoli; Ke, Yuxin; Wang, Hui; Yu, Tingqiao; Tan, Wenbing

doi:10.1016/j.scitotenv.2024.170451

Cited by 25 publications

(2 citation statements)

References 197 publications

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“…Soil organic matter can retain soil moisture and stabilize soil structure, allowing soil to rebound after compaction (Défossez et al, 2014;Kou et al, 2024). Studies have indicated that soil organic matter increases the ability of soil to resist compaction by influencing the bonding between soil particles and the effects of friction to increase the stability of soil aggregates (Lamandé et al, 2017;Zhang et al, 2006).…”

Section: Factors Affecting Soil Compactionmentioning

confidence: 99%

Soil compaction due to agricultural machinery impact: A systematic review

Zhang,

Jia,

Fan

et al. 2024

Land Degrad Dev

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Soil compaction is generally viewed as one of the most serious soil degradation problems and a determining factor in crop productivity worldwide. It is imperative to understand the processes involved in soil compaction to meet the future global challenges of food security. In this work, we used co‐occurring keyword analysis to summarize 3491 papers on soil compaction over the past 40 years, elaborating on the main research focuses such as the causes, influencing factors, and effects of soil compaction on crops, and the mitigation and prevention of soil compaction. This review provides a comprehensive discussion of the effects of soil compaction, including altering soil structure, increasing bulk density (BD) and penetration resistance (PR), and reducing porosity and soil hydraulic properties. Notably, based on the 387 data points of 11 papers about BD, our results demonstrated soil compaction on average, increased BD by 7.6%, 6.9%, and 3.2% in the medium‐, coarse‐, and fine‐textured soils, respectively. Based on the 264 data points of 18 papers, in the 0–30 cm soil layer, compaction increased penetration resistance (by 91% in the coarse‐textured, 84.2% in the medium‐textured, and 8.8% in the fine‐textured soils). Compacted soil limits the access of crop roots to water and nutrients, leading to poor root development and reduced crop productivity. There was a difference in soil compaction sensitivity between the different crops, but crop growth and yield showed an overall worsening trend with increasing degrees of compaction. This review collected data points on 142 crop yields and found that wheat, barley, corn, and soybean yields decreased by an average of 4.1%, 15.1%, 37.7%, and 22.7%, respectively, in the BD range of 1.1–1.8 Mg/cm3 after compaction. Additionally, the effectiveness of different compaction mitigation measures, including natural, tillage, and biological, is systematically discussed. Compared with soil compaction mitigation measures, prevention should be the top priority although there is still a lack of practical prevention methods. Soil conditions and agricultural machinery type are the main factors affecting the risk of soil compaction in the process of soil compaction. Therefore, it is particularly important to optimize the soil working conditions in the field and the type of farm machinery used to reduce the risk of soil compaction. This initiative is pivotal for ensuring sustainable systems for food production and recovering crop productivity from compacted soil.

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Section: Factors Affecting Soil Compactionmentioning

confidence: 99%

Soil compaction due to agricultural machinery impact: A systematic review

Zhang,

Jia,

Fan

et al. 2024

Land Degrad Dev

View full text Add to dashboard Cite

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“…Existing research primarily selects environmental factors across both natural and socio-economic aspects. From a natural perspective, soil moisture [28], vegetation coverage [21], organic matter [29,30], elevation, and slope [31] are considered important factors influencing soil heavy metal content. In addition, precipitation also plays an important role in soil heavy metal content through leaching and adsorption processes [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution Prediction of Soil Heavy Metals Based on Random Forest Model

Nie,

Chen,

Sun

et al. 2024

Sustainability

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Mastering the spatial distribution of soil heavy metal content and evaluating the pollution status of soil heavy metals is of great significance for ensuring agricultural production and protecting human health. This study used a machine learning model to study the spatial distribution of soil heavy metal content in a coastal city in eastern China. Having obtained six soil heavy metal contents, including Cr, Cd, Pb, As, Hg, and Ni, environmental variables such as precipitation, soil moisture, and population density were selected. Random forest (RF) was used to model the spatial distribution of soil heavy metal content. The research findings indicate that the RF model demonstrates a robust predictive capability in discerning the spatial distribution of soil heavy metals, and environmental factor variables can explain 60%, 52.3%, 53.5%, 63.1%, 61.2%, and 51.2% of the heavy metal content of Cr, Cd, Pb, As, Hg, and Ni in soil, respectively. Among the chosen environmental variables, precipitation and population density exert notable influences on the predictive outcomes of the model. Specifically, precipitation exhibits the most substantial impact on Cr and Ni, whereas population density emerges as the primary determinant for Cd, Pb, As, and Hg. The RF prediction results show that Cr and Ni in the study area are less affected by human activities, while Cd, Pb, As, and Hg are more affected by human industrial and agricultural production. Research has shown that using RF models for predicting soil heavy metal distributions has certain significance.

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