Revealing the Full Picture of Agricultural Plastic Legacy Pollution: Toward “Zero‐Leakage” Management in Chinese Farmlands

The theme for World Environment Day on June 5, 2025, was “Beat Plastic Pollution.” Indeed, by affecting different environmental compartments, plastic pollution has emerged as a global concern, with agricultural plastic mulch films being a major source of farmland contamination (Rillig et al. 2024; Thompson et al. 2024). Significantly, as the world's leading plastic mulch film-consuming country, China uses approximately 68% of global plastic mulch film produced globally (Dai et al. 2025). The increasing application of plastic mulch film has led to persistent residue accumulation, which degrades soil integrity, hinders hydrological and nutrient processes, and results in weak germination and loss of crop yield (Zhang et al. 2020; Huang and Xia 2024; Landrigan et al. 2025). Despite rising concerns, there is limited systematic, nationwide research on agricultural plastic pollution in China, particularly in terms of trend prediction and impact assessment. To date, the common approaches for precise quantification of plastic mulch film debris include remote sensing–based mapping of plastic mulch film coverage, geostatistical methods, substance flow analysis, and machine learning algorithms (Zhou et al. 2023; Zhang et al. 2025). In fact, these methods have several limitations when they are applied at a regional scale, including data scarcity, poor model interpretability, and insufficient capacity to simulate dynamic policy scenarios, thus restricting their applicability to national-scale debris monitoring and policymaking. This critical knowledge gap has significantly hindered the development and targeted implementation of evidence-based policies aimed at controlling plastic mulch film contamination in China. Once regarded as a breakthrough in boosting agricultural productivity and water-use efficiency, plastic mulch film is now recognized as a double-edged sword within China's agricultural systems. These limitations underscore the need for integrated modeling approaches—a gap addressed by Dai et al. (2025). In the study published in Global Change Biology, Dai et al. (2025) offer a national inventory of macroplastic residues (> 5 mm) in Chinese croplands, providing quantitative predictions of environmental impact trends from 1993 to 2050. Marked by its integration of comprehensive datasets and methodologically robust modeling, their study is the most detailed and authoritative quantification of agricultural plastic pollution in China to date. With China accounting for approximately 68% of global plastic mulch film consumption, Dai et al. (2025) bridge the gap between localized empirical observations and the data requirements of national-scale policy formulation by integrating 3145 field survey sites and over three decades of national mulch usage statistics. Dai et al. (2025) achieve high-resolution spatiotemporal quantification of plastic pollution burdens across China's croplands. They employ a zero-intercept linear regression model to assess the relationship between historical cumulative plastic mulch film usage and residual mass retention in soils. Grounded in a robust empirical dataset, their model exhibits broad applicability and highlights three distinct advantages. First, even in the absence of comprehensive sampling, the model integrates existing field observations with historical usage data and facilitates effective county-level extrapolation nationwide. Thus the method significantly enhances spatial coverage and estimation accuracy. Second, the transparent zero-intercept linear formulation explicitly captures the cumulative relationship between mulch film input and residual accumulation. This measure allows for cross-regional comparisons and policy-response simulations. Third, the model is characterized by a strong dynamic predictive capacity. This enables the authors to design future scenarios with varying rates of biodegradable mulch replacement and quantitatively evaluate the potential effectiveness of each in mitigating residue accumulation trends. Therefore, by integrating scientific assessment, policy guidance, and risk forecasting, their study presents a cohesive analytical framework. This modeling paradigm constitutes a methodological breakthrough in attributing sources of environmental plastic pollution while offering a “China solution” for advancing the global monitoring and management of agricultural plastic pollution. Furthermore, it underscores a quintessential sustainability paradox: while enabling China to “feed an additional 85 million people,” plastic mulch films have undermined the ecological foundations of agricultural production. Dai et al. (2025) emphasize a “zero-leakage” management objective while cautioning against the misconception of “zero-use,” thus providing a more pragmatic alternative to uniform, regionally imposed plastic-restriction policies. Dai et al. (2025) not only evaluate current levels of plastic pollution in agricultural soils but also forecast future trends under varying policy scenarios, specifically examining biodegradable mulch replacement rates of 0%, 20%, 40%, and 60%. Their findings present a critical warning: if existing practices remain unchanged, cumulative plastic residues could reach 6.24 million metric tons by 2050. By integrating policy-driven scenario analysis, the study provides substantial practical value and strategic insight for decision-making, thereby supporting China's agricultural transition from a focus on quantity to one of quality and sustainability. In conclusion, the study by Dai et al. (2025) represents a significant leap forward in agricultural plastic film mulch research, leveraging interdisciplinary collaboration, multiscale modeling, and decades of empirical data. Despite persistent challenges arising from data limitations and complex underlying processes, their study enhances scientific rigor and policy relevance by employing standardized sampling protocols, a transparent model architecture, and robust scenario analyses. The creation of a national spatiotemporal inventory of plastic mulch film contamination marks a crucial step toward the systemic governance of nonpoint-source plastic pollution in Chinese agriculture, offering a quantitative foundation for targeted mitigation efforts. In the future, the national policies and local control techniques about plastic film mulch are urgently required to combat microplastic pollution toward “zero-leakage” management in China. Nevertheless, there is still a gap in determining high-precision and long-term plastic film mulch inventory on a national scale. Future research should incorporate multi-source remote sensing data, field sample datasets, and robust algorithms to precisely evaluate plastic film mulch debris and further better understand residue migration and transformation dynamics in soil. Besides, the policy practices including thicker (or biodegradable) plastic film, affordable machinery, and adequate economic rewards for recycling plastic film are also feasible measures in reducing plastic film mulch contamination. However, the campaign for controlling plastic film mulch pollution involves several state ministries and administrations in China. The government's decision-making may lag behind the development of plastic film mulch pollution. Therefore, a powerful steering committee with a more effective institutional framework may be necessary to curb and further reverse plastic film mulch contamination, while refining risk assessment strategies and response frameworks to facilitate a region-specific, adaptive approach to farmland plastic pollution control. Zhidong Zhang: data curation, visualization, writing – original draft, writing – review and editing. Zhongling Guo: funding acquisition, methodology, writing – review and editing. This study was supported by the National Natural Science Foundation of China (grant no. 42271002) and the Foundation of Central Guidance for Local Scientific and Technological Development (grant no. 246Z3705G). The authors declare no conflicts of interest. This article is a Invited Commentary on Dai et al., https://doi.org/10.1111/gcb.70297. The authors have nothing to report.