A dynamic model to evaluate the critical loads of heavy metals in agricultural soil.

A dynamic model to evaluate the critical loads of heavy metals in agricultural soil.

Feng, Wenli;Guo, Zhaohui;Xiao, Xiyuan;Peng, Chi;Shi, Lei;Ran, Hongzhen;Xu, Wenxuan;
Ecotoxicology and environmental safety 2020 Vol. 197 pp. 110607
170
feng2020aecotoxicology

Abstract

Estimation of critical load (CL) is important for soil environmental management and pollution prevention. We developed a mass balance-based dynamic critical load (DCL) model, which improved the model performance, applicability and functionality compared with the traditional one. Paddy soils in two typical fields in central south China and two scenarios were chosen as case studies. The result of case study showed that atmospheric deposition was the main source of Cd, Cu, Pb, and Zn in the soils, with percentage contributions ranging from 59.9 to 79.8%. Crop uptake, particularly the rice straw harvest, was the primary output pathway, accounting for 35.1-71.2% of the total output flux. The critical loads also known as annual input limits (I) of heavy metals in the paddy soils were calculated by the developed DCL model. For example, the Imax of Cd was recommended as 0.05 kg ha in the paddy soils under the default scenario for a protection period of 40 years, and that became 0.12 kg ha and 0.17 kg ha under the straw removal scenario in the two typical fields, respectively. The scenario simulation suggested that the straw removal strategy reduced the total concentrations of heavy metals (C) in the soils and notably increased the I. Meanwhile, the sensitivity analysis indicated that the changes of C and I can be controlled by adjusting the partition coefficient (K), plant uptake factor (PUF) and input flux. The mass balance-based DCL model provides a reference method to establish the standard for controlling heavy metal inputs to agricultural soil, this will be helpful to develop strategies for the prevention of soil contamination.

Citation

ID: 109194
Ref Key: feng2020aecotoxicology
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
109194
Unique Identifier:
S0147-6513(20)30446-2
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet