亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Spatio-Temporal Pattern of Groundwater Nitrate-Nitrogen and Its Potential Human Health Risk in a Severe Water Shortage Region

环境科学 地下水 耕地 污染物 污染 危害 水资源管理 人类健康 地理 经济短缺 环境卫生 环境保护 生态学 医学 农业 生物 语言学 哲学 岩土工程 考古 政府(语言学) 工程类
作者
Wujuan Mi,Minghua Zhang,Yuan Li,Xiaoxuan Jing,Wei Pan,Xin Xing,Chen Xiao,Qiusheng He,Yonghong Bi
出处
期刊:Sustainability [Multidisciplinary Digital Publishing Institute]
卷期号:15 (19): 14284-14284 被引量:1
标识
DOI:10.3390/su151914284
摘要

Groundwater nitrate-nitrogen (GNN) has been one of the most widespread pollutants. However, there is still a poor understanding of GNN pollution and its potential effects on human health. In this study, GNN in Taiyuan, a region of severe water scarcity in northern China, was tracked from 2016 to 2020; the spatio-temporal distribution characteristics of GNN were demonstrated and the potential human health risks to infants, children, and adults were assessed. The results showed that the concentration of GNN varied from 0.1 to 43.3 mg L−1; the highest mean concentration was observed in 2016 and the lowest value appeared in 2020. GNN concentration declined over time, which was closely related to the proactive environmental policies of Tiyuan city. GNN levels were considerably greater in urban areas than in rural areas (p < 0.001), and the forest had a very low level of GNN, which was significantly different from the grassland, farmland, and construction land (p < 0.001). According to the hazard quotient, the impacts of GNN on human health revealed age specificity, namely in the order of infants > children > adults. It was concluded that the interception effect of the forest could effectively alleviate groundwater pollution pressures, and more forest land is necessary for human health risk prevention in the severe water shortage areas to alleviate GNN pollution.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
6秒前
向前发布了新的文献求助10
11秒前
111完成签到 ,获得积分10
19秒前
fjq95133完成签到 ,获得积分10
43秒前
科研通AI6.3应助向前采纳,获得10
1分钟前
1分钟前
马伯乐完成签到 ,获得积分10
1分钟前
blueskyzhi完成签到,获得积分10
1分钟前
向前发布了新的文献求助10
1分钟前
桐桐应助陈俊豪采纳,获得10
1分钟前
1分钟前
陈俊豪发布了新的文献求助10
1分钟前
沙海沉戈完成签到,获得积分0
2分钟前
科研通AI6.2应助向前采纳,获得10
2分钟前
2分钟前
向前发布了新的文献求助10
2分钟前
Chan完成签到,获得积分10
3分钟前
Ya完成签到 ,获得积分10
3分钟前
张起灵完成签到 ,获得积分10
3分钟前
3分钟前
完美世界应助麻辣小龙虾采纳,获得10
4分钟前
4分钟前
4分钟前
彭于晏应助麻辣小龙虾采纳,获得10
4分钟前
4分钟前
4分钟前
田様应助yanwei采纳,获得10
5分钟前
赘婿应助向前采纳,获得10
5分钟前
今后应助麻辣小龙虾采纳,获得10
5分钟前
5分钟前
向前发布了新的文献求助10
5分钟前
5分钟前
5分钟前
2111355981完成签到 ,获得积分10
5分钟前
Hello应助麻辣小龙虾采纳,获得10
5分钟前
5分钟前
胡萝卜完成签到,获得积分10
5分钟前
5分钟前
6分钟前
6分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6362214
求助须知:如何正确求助?哪些是违规求助? 8175805
关于积分的说明 17224164
捐赠科研通 5416914
什么是DOI,文献DOI怎么找? 2866596
邀请新用户注册赠送积分活动 1843775
关于科研通互助平台的介绍 1691531