0
Meta Analysis ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 1 ? Systematic review or meta-analysis. Synthesizes findings across many studies. Strongest evidence. Environmental Sources Marine & Wildlife Policy & Risk Sign in to save

Nationwide meta-analysis of microplastic distribution and risk assessment in China's aquatic ecosystems, soils, and sediments

Journal of Hazardous Materials 2024 20 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 65 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Qiannan Duan, Hailong Zhang, Qiannan Duan, Qiannan Duan, Qiannan Duan, Baoxin Zhai, Baoxin Zhai, Baoxin Zhai, Qiannan Duan, Qiannan Duan, Baoxin Zhai, Baoxin Zhai, Chen Zhao, Pengwei Yan, Pengwei Yan, Chen Zhao, Chen Zhao, Kangping Liu, Jianchao Lee, Kangping Liu, Kangping Liu, Xiangyi Yang, Xiangyi Yang, Xiangyi Yang, Xiangyi Yang, Weidong Wu, Xiangyi Yang, Xiangyi Yang, Hailong Zhang, Chi Zhou, Chi Zhou, Hailong Zhang, Hailong Zhang, Wei Kang Baoxin Zhai, Pengwei Yan, Pengwei Yan, Pengwei Yan, Pengwei Yan, Pengwei Yan, Xiangyi Yang, Lei Huang, Lei Huang, Lei Huang, Xiangyi Yang, Wei Kang Jianchao Lee, Jianchao Lee, Jianchao Lee, Jianchao Lee, Baoxin Zhai, Weidong Wu, Weidong Wu, Weidong Wu, Chi Zhou, Chi Zhou, Chi Zhou, Chi Zhou, Chi Zhou, Xudong Quan, Xudong Quan, Xudong Quan, Xudong Quan, Wei Kang, Wei Kang, Wei Kang, Wei Kang Wei Kang Wei Kang

Summary

A nationwide meta-analysis of 7,766 sampling sites across China found that microplastic distribution is influenced by economic development, population density, and geography, with generally higher concentrations in prosperous areas. The pollution varies significantly across water, soil, and sediment compartments, highlighting the need for AI-based regulatory frameworks to manage standardized risk assessment.

Study Type Review

Microplastic (MP) accumulation has recently become a pressing global environmental challenge. As a major producer and consumer of plastic products, China's MP pollution has garnered significant attention from researchers. However, accurate and comprehensive investigations of national-level MP pollution are still lacking. In this study, we systematically collated a national MP pollution dataset consisting of 7766 water, soil, and sediment sampling sites from 544 publicly published studies, revealing the spatiotemporal distribution and potential risks of MP pollution in China. The results indicate that MP distribution is influenced by various regional factors, including economic development level, population distribution, and geographical environment, exhibiting considerable range and complexity. MP concentrations are generally higher in economically prosperous areas, but the degree of pollution varies significantly across different environmental media. Given the uncertainty and lack of standardized data in traditional microplastic risk assessment methods, this article highlights the urgency of developing a comprehensive big data and artificial intelligence (AI)-based regulatory framework. This work provides a substantial amount of accurate MP pollution data and offers a fresh perspective on leveraging AI for microplastic pollution regulation.

Sign in to start a discussion.

Share this paper