• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

评估中国主要农作物中的重金属相关风险,并制定相应土壤修复的融资策略。

Evaluating heavy metals-related risk in staple crops and making financing strategy for corresponding soil remediation across China.

机构信息

Gansu Academy of Eco-environmental Sciences, Lanzhou 730030, China; School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.

College of Architecture & Civil Engineering, Faculty of Urban Construction, Beijing University of Technology, Beijing 100124, China.

出版信息

J Hazard Mater. 2024 Dec 5;480:136135. doi: 10.1016/j.jhazmat.2024.136135. Epub 2024 Oct 10.

DOI:10.1016/j.jhazmat.2024.136135
PMID:39405717
Abstract

China's staple crops face heavy metal (HMs) contamination, a widespread issue lacking a national assessment. We used machine learning (ML) to assess risks of 8 HMs in rice, wheat, and maize, and estimated a financing strategy for soil remediation via linear optimization and computable general equilibrium (CGE). The accumulation of HMs in crops depends on Soil-HMs, climate, soil properties, and crop types. Cd and Hg pose major soil pollution risks, while Cr, Pb, and Cd are the most threatening in crops. High-risk zones are located at the warm temperature and subtropical zones, with wheat most vulnerable. Over a quarter (26.77 %) of the nation's croplands are classified as high-risk, with a significant 60.89 % falling into the medium-risk category, leaving merely 12.34 % of the agricultural land in a safe condition. The estimated remediation cost is 58596.73 billion RMB and the crop loss is 808.03 billion RMB in a ten-year remediation period at the context of secure crop supply. The reallocation of social investment rather than raising new taxation for the remediation is beneficial to the GDP increase and social welfare despite some loss in the household income and enterprise income. This study provides a comprehensive evaluation for Crop-HMs risk and remediation policy, crucial for national crop security.

摘要

中国的主要农作物面临重金属(HM)污染,这是一个缺乏全国性评估的普遍问题。我们使用机器学习(ML)评估了水稻、小麦和玉米中 8 种 HM 的风险,并通过线性优化和可计算一般均衡(CGE)估算了土壤修复的融资策略。作物中 HM 的积累取决于土壤-HM、气候、土壤特性和作物类型。Cd 和 Hg 构成了主要的土壤污染风险,而 Cr、Pb 和 Cd 对作物的威胁最大。高风险区域位于温暖的温度和亚热带地区,小麦最脆弱。全国超过四分之一(26.77%)的耕地被归类为高风险,有显著的 60.89%属于中风险类别,只有 12.34%的农业用地处于安全状态。在确保作物供应的情况下,十年修复期内的估计修复成本为 58596.73 亿元人民币,作物损失为 8080.3 亿元人民币。重新分配社会投资而不是为修复筹集新税有利于 GDP 增长和社会福利,尽管家庭收入和企业收入会有一些损失。本研究为作物-HM 风险和修复政策提供了全面评估,对国家作物安全至关重要。

相似文献

1
Evaluating heavy metals-related risk in staple crops and making financing strategy for corresponding soil remediation across China.评估中国主要农作物中的重金属相关风险,并制定相应土壤修复的融资策略。
J Hazard Mater. 2024 Dec 5;480:136135. doi: 10.1016/j.jhazmat.2024.136135. Epub 2024 Oct 10.
2
Predicting heavy metal concentration in crop grain using automated machine learning models.使用自动化机器学习模型预测作物籽粒中的重金属浓度。
Ying Yong Sheng Tai Xue Bao. 2025 Jun;36(6):1889-1897. doi: 10.13287/j.1001-9332.202506.018.
3
Assessing heavy metal pollution and livestock health risks in sewage water-irrigated fodder systems: a comprehensive study.评估污水灌溉饲料系统中的重金属污染和家畜健康风险:一项综合研究。
Environ Monit Assess. 2025 Jul 2;197(8):839. doi: 10.1007/s10661-025-14327-5.
4
Biological roles of soil microbial consortium on promoting safe crop production in heavy metal(loid) contaminated soil: A systematic review.土壤微生物群落促进重金属(类)污染土壤安全作物生产的生物学作用:系统评价。
Sci Total Environ. 2024 Feb 20;912:168994. doi: 10.1016/j.scitotenv.2023.168994. Epub 2023 Dec 2.
5
Source apportionment and health risks of heavy metals in agricultural soils near mining areas: APCS-MLR and Monte Carlo approaches.矿区周边农田土壤重金属的源解析及健康风险:APCS-MLR和蒙特卡罗方法
Environ Geochem Health. 2025 Aug 7;47(9):364. doi: 10.1007/s10653-025-02683-7.
6
Diffusive gradient in thin films combined with machine learning to discern the accumulation characteristics and driving factors of Cd and Cu in soil-rice systems.薄膜扩散梯度结合机器学习以识别土壤-水稻系统中镉和铜的积累特征及驱动因素。
J Hazard Mater. 2025 Sep 5;495:138924. doi: 10.1016/j.jhazmat.2025.138924. Epub 2025 Jun 16.
7
Assessment of heavy metal sources and health risks in soil-crop systems of fragmented farmland.碎片化农田土壤-作物系统中重金属来源及健康风险评估
Front Public Health. 2025 Jul 31;13:1637595. doi: 10.3389/fpubh.2025.1637595. eCollection 2025.
8
Accumulation of heavy metals(loids) in soils and crops at a decentralized metal recycling site: Health risk assessment and pollution management.分散式金属回收站点土壤和农作物中重金属(类金属)的积累:健康风险评估与污染管理
Environ Monit Assess. 2025 Aug 8;197(9):997. doi: 10.1007/s10661-025-14445-0.
9
AI-assisted systematic review on remediation of contaminated soils with PAHs and heavy metals.人工智能辅助的多环芳烃和重金属污染土壤修复的系统评价。
J Hazard Mater. 2024 Apr 15;468:133813. doi: 10.1016/j.jhazmat.2024.133813. Epub 2024 Feb 17.
10
An integrated GIS-pXRF approach assesses ecological and human health risks from heavy metals in county level soils.一种集成的地理信息系统-便携式X射线荧光光谱法评估县级土壤中重金属对生态和人类健康的风险。
Sci Rep. 2025 Jul 2;15(1):22834. doi: 10.1038/s41598-025-05989-9.

引用本文的文献

1
Understanding microbial biomineralization at the molecular level: recent advances.理解微生物生物矿化的分子水平:最新进展。
World J Microbiol Biotechnol. 2024 Sep 16;40(10):320. doi: 10.1007/s11274-024-04132-6.