A comprehensive evaluation of influencing factors of neonicotinoid insecticides (NEOs) in farmland soils across China: First focus on film mulching

• Published in: Journal of hazardous materials Vol. 470; p. 134284
• Main Authors: Hou, Jie, Wang, LiXi, Wang, JinZe, Chen, LiYuan, Han, BingJun, Li, YuJun, Yu, Lu, Liu, WenXin
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.05.2024
• Subjects: agricultural land; agroecosystems; algorithms; China; greenhouses; Influencing factors; Microplastics; Multiple linear regression model; Neonicotinoid insecticides; Random Forest model; regression analysis; soil; total nitrogen; China; Microplastics; Neonicotinoid insecticides; Influencing factors; Random Forest model; Multiple linear regression model
• ISSN: 0304-3894; 1873-3336; 1873-3336
• DOI: 10.1016/j.jhazmat.2024.134284

Neonicotinoid insecticide (NEO) residues in agricultural soils have concerning and adverse effects on agroecosystems. Previous studies on the effects of farmland type on NEOs are limited to comparing greenhouses with open fields. On the other hand, both NEOs and microplastics (MPs) are commonly found in agricultural fields, but their co-occurrence characteristics under realistic fields have not been reported. This study grouped farmlands into three types according to the covering degree of the film, collected 391 soil samples in mainland China, and found significant differences in NEO residues in the soils of the three different farmlands, with greenhouse having the highest NEO residue, followed by farmland with film mulching and farmland without film mulching (both open fields). Furthermore, this study found that MPs were significantly and positively correlated with NEOs. As far as we know this is the first report to disclose the association of film mulching and MPs with NEOs under realistic fields. Moreover, multiple linear regression and random forest models were used to comprehensively evaluate the factors influencing NEOs (including climatic, soil, and agricultural indicators). The results indicated that the random forest model was more reliable, with MPs, farmland type, and total nitrogen having higher relative contributions. [Display omitted] •Soils with various mulching levels had significantly different NEO residue levels.•NEO residue levels positively correlated with MPs in agricultural soils.•Nine climatic, soil and agricultural factors significantly correlated with NEOs.•MPs and film mulching affected the NEO concentration and needed attention.