在农业土壤中确定重金属的危险热点和影响因素,使用空间二变量分析和随机森林分析
Xiaohang Xu1, Zhidong Xu2, Longchao Liang3
1Key Laboratory of Karst Georesources and Environment, Ministry of Education, College of Resources and Environmental Engineering, Guizhou University, Guiyang 550025, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China.
The Science of the total environment
|September 21, 2024
概括
农业土壤中的重金属 (化物) 构成生态和健康风险. 一种新的方法确定了热点,并发现流量和过时的行业是关键因素,需要有针对性的管理策略.
科学领域:
- 环境科学 环境科学
- 土壤科学 土壤科学
- 公共卫生 公共卫生
背景情况:
- 农业土壤中的重金属化物 (HM) 对土壤健康和人类福祉构成双重风险.
- 之前的研究经常孤立地解决生态或健康风险,阻碍了全面的热点识别和管理.
- 统一的方法对于有效的风险评估和缓解在农业环境中至关重要.
研究的目的:
- 开发和应用一种新的综合方法来识别农业土壤HM风险热点.
- 确定导致HM积累和相关风险的关键环境和人为因素.
- 为减轻农业土壤中HM污染的有针对性的管理策略提供信息.
主要方法:
- 使用空间二变量分析和随机森林建模来分析2995个土壤样本的大数据集.
- 积极矩阵因子化被用来调查HM来源.
- 生态和健康风险评估与空间统计和机器学习相结合.
主要成果:
- 确定了高风险的热点,特别是与乡镇企业相关的徐چان和南阳.
- 人类活动,特别是车辆交通 (约37.8%),是主要的HM来源.
- 土壤类型和PM2.5度分别成为关键的自然和人为影响因素.
结论:
- 综合空间和机器学习方法有效地识别HM风险热点和驱动因素.
- 建议有针对性的干预措施,重点关注车辆排放和升级工业污染控制.
- 解决生态和健康风险对于可持续的农业用地管理至关重要.
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