Shuyou Zhang, Jianqiang Sun, Qing Zhou, Xudong Feng, Jie Yang, Kankan Zhao, Anping Zhang, Songhe Zhang, Yijun Yao
{"title":"Microplastic contamination in Chinese topsoil from 1980 to 2050.","authors":"Shuyou Zhang, Jianqiang Sun, Qing Zhou, Xudong Feng, Jie Yang, Kankan Zhao, Anping Zhang, Songhe Zhang, Yijun Yao","doi":"10.1016/j.scitotenv.2024.176918","DOIUrl":null,"url":null,"abstract":"<p><p>China's soil is experiencing significant microplastic contamination. We developed a machine-learning model to assess microplastic pollution from 1980 to 2050. Our results showed that the average abundance of microplastics in topsoil increased from 45 items per kilogram of soil in 1980 to 1156 items by 2018, primarily due to industrial growth (39 %), agricultural film usage (30 %), tire wear (17 %), and domestic waste (14 %). During the same period, microplastic levels in cropland rose from 98 to 2401 items per kilogram of soil, and exposure levels for the Chinese population increased from 808 to 3168 items per kilogram. By 2050, a reduction in the use of agricultural films is expected to decrease cropland contamination by half. However, overall levels are anticipated to remain steady due to other persistent sources, indicating a continued spread of microplastics into subterranean environments, water bodies, and human systems. This study highlights China's microplastic challenges and suggests potential global trends, emphasizing the need for increased awareness and intervention worldwide.</p>","PeriodicalId":422,"journal":{"name":"Science of the Total Environment","volume":" ","pages":"176918"},"PeriodicalIF":8.2000,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of the Total Environment","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.scitotenv.2024.176918","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
China's soil is experiencing significant microplastic contamination. We developed a machine-learning model to assess microplastic pollution from 1980 to 2050. Our results showed that the average abundance of microplastics in topsoil increased from 45 items per kilogram of soil in 1980 to 1156 items by 2018, primarily due to industrial growth (39 %), agricultural film usage (30 %), tire wear (17 %), and domestic waste (14 %). During the same period, microplastic levels in cropland rose from 98 to 2401 items per kilogram of soil, and exposure levels for the Chinese population increased from 808 to 3168 items per kilogram. By 2050, a reduction in the use of agricultural films is expected to decrease cropland contamination by half. However, overall levels are anticipated to remain steady due to other persistent sources, indicating a continued spread of microplastics into subterranean environments, water bodies, and human systems. This study highlights China's microplastic challenges and suggests potential global trends, emphasizing the need for increased awareness and intervention worldwide.
期刊介绍:
The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.
The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.