Ecological risk of copper and zinc and their different bioavailability change in soil-rice system as affected by biowaste application

Wan, Yanan; Huang, Qingqing; Wang, Qi; Ying, Ma; Su, Dechun; Qiao, Yuhui; Jiang, Rongfeng; Li, Huafen

doi:10.1016/j.ecoenv.2020.110301

Cited by 22 publications

(7 citation statements)

References 44 publications

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“…It is affected by various factors, including the total concentration of PTEs in soil, as well as soil physical and chemical properties [38][39][40]. Numerous studies have analyzed the shift of PTEs in soil-rice system [41][42][43][44]. Brus et al (2009) built a multiple linear regression (MLR) model to estimate the Cd concentration in rice grains using the total Cd concentration in soil, soil pH, soil clay, and soil organic matter (SOM) as predictors (R 2 = 0.66) [45].…”

Section: Introductionmentioning

confidence: 99%

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Xie

Zhu³

et al. 2021

Land

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Potentially toxic element (PTE) pollution in farmland soils and crops is a serious cause of concern in China. To analyze the bioaccumulation characteristics of chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) in soil-rice systems, 911 pairs of top soil (0–0.2 m) and rice samples were collected from an industrial city in Southeast China. Multiple linear regression (MLR), support vector machines (SVM), random forest (RF), and Cubist were employed to construct models to predict the bioaccumulation coefficient (BAC) of PTEs in soil–rice systems and determine the potential dominators for PTE transfer from soil to rice grains. Cr, Cu, Zn, and Ni contents in soil of the survey region were higher than corresponding background contents in China. The mean Ni content of rice grains exceeded the national permissible limit, whereas the concentrations of Cr, Cu, and Zn were lower than their thresholds. The BAC of PTEs kept the sequence of Zn (0.219) > Cu (0.093) > Ni (0.032) > Cr (0.018). Of the four algorithms employed to estimate the bioaccumulation of Cr, Cu, Zn, and Ni in soil–rice systems, RF exhibited the best performance, with coefficient of determination (R2) ranging from 0.58 to 0.79 and root mean square error (RMSE) ranging from 0.03 to 0.04 mg kg−1. Total PTE concentration in soil, cation exchange capacity (CEC), and annual average precipitation were identified as top 3 dominators influencing PTE transfer from soil to rice grains. This study confirmed the feasibility and advantages of machine learning methods especially RF for estimating PTE accumulation in soil–rice systems, when compared with traditional statistical methods, such as MLR. Our study provides new tools for analyzing the transfer of PTEs from soil to rice, and can help decision-makers in developing more efficient policies for regulating PTE pollution in soil and crops, and reducing the corresponding health risks.

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Section: Introductionmentioning

confidence: 99%

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Xie

Zhu³

et al. 2021

Land

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“…Studies have shown that food consumption has been the main pathway of heavy metals exposure for humans in polluted areas apart from occupational exposure [ 10 ]. Cu and Zn are essential for the human physiological function of the human body at appropriate concentrations, while a deficit or excess of Cu and Zn can cause several diseases [ 11 , 12 ]. Cd and Pb are non-essential elements for the human body and can adversely affect human health at high levels of exposure.…”

Section: Introductionmentioning

confidence: 99%

Heavy Metal in Rice and Vegetable and Human Exposure near a Large Pb/Zn Smelter in Central China

Wang

Song

et al. 2021

IJERPH

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Non-ferrous metal smelting is a significant source of anthropogenic heavy metal emission and has led to severe environmental pollution that ultimately threatens the health of local residents. In this study, we determined concentrations of copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb), as well as Pb isotopic compositions in rice, vegetables and human hair in areas surrounding the Zhuzhou Pb/Zn smelter in Hunan, China and we assessed the health risks associated with rice and vegetable consumption for local residents. Results showed that rice and vegetable samples were significantly contaminated by Cd and Pb. Age and source of rice were important factors for the enrichment of heavy metal concentrations in human hair. The ratios of Pb isotopes in human hair (1.164–1.170 for 206Pb/207Pb and 2.102–2.110 for208Pb/206Pb) were comparable to those in rice (1.162–1.172 for 206Pb/207Pb and 2.098–2.114 for208Pb/206Pb) and were slightly lower than those in vegetables (1.168–1.172 for 206Pb/207Pb and 2.109–2.111 for208Pb/206Pb), indicating that Pb in human hair mainly originated from food ingestion. A non-carcinogenic risk assessment showed that Cd exposure was the dominant health risk for local residents. This study suggested that crops planted surrounding the smelter were seriously contaminated with Cd and human exposure was related to dietary intake.

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“…The HM contents in the maize tissues showed a signi cantly positive correlation with soil bioavailable HM contents, which is consistent with the results of previous studies (Bai et al, 2013;Bai et al, 2017b) (Table 5). The soil bioavailable HM contents could accurately predict HM uptake by plants (Wan et al, 2020)Generally, SS is associated with stronger correlation than CMR and CM, and Zn and Ni showed better correlation than other HMs. The differences may be attributed to the various accumulation potentials of tissues for different HM species.…”

Section: The Accumulation and Bioconcentration Of Heavy Metals In Maizementioning

confidence: 95%

“…In addition to increasing the HM contents in arable land, OA application also enhances HM bioavailability (Qiutong & Mingkui, 2017). OA application can promote HM transfer in soil-plant systems, exposing humans to the risk of soil HM contamination (Jolly et al, 2013;Wan et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Long-term Impact of Organic Amendments on the Bioavailability of Heavy Metals in Mudflat Soil and Their Uptake by Maize

Bai

et al. 2021

Preprint

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Organic amendments (OAs) can be a sustainable and effective method for mudflat soil improvement. A long-term field experiment was conducted to investigate the potential of OA application to mudflat soil improvement. We measured the pH, soil organic matter (SOM), salinity, maize growth, and heavy metal (HM) accumulation in OA-amended soils and maize tissues 23 months after three OAs, sewage sludge (SS), Chinese medical residue (CMR), and cattle manure (CM), were applied at the application rates of 0, 30, 75, 150, and 300 t ha-1. OA application significantly increased the SOM and decreased the salinity of mudflat soils. Additionally, CMR and CM application decreased soil pH. The maize biomass and HM contents in soil and maize increased after OA application. The bioavailability and bioconcentration of HMs were generally in the sequence of SS>CMR>CM. The average bioavailability ratios of HMs were in the order of Cd>Zn>Cu>Mn>Ni. The bioconcentration of Zn and Cd by maize was highest, followed by Mn, Cu, and Ni. SOM, pH, and salinity were the important factors regulating soil available HMs and, subsequently, HM accumulation in maize. Among the three OAs, SS is most effective in decreasing soil salinity and increasing the SOM, bioavailability and bioconcentration of HMs. On the other hand, CM was the best OA because it promoted significant maize growth yet maintained low HM contamination risk.

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Ecological risk of copper and zinc and their different bioavailability change in soil-rice system as affected by biowaste application

Cited by 22 publications

References 44 publications

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Heavy Metal in Rice and Vegetable and Human Exposure near a Large Pb/Zn Smelter in Central China

Long-term Impact of Organic Amendments on the Bioavailability of Heavy Metals in Mudflat Soil and Their Uptake by Maize

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