Plastic waste discharge to the global ocean constrained by seawater observations

• Published in: Nature communications Vol. 14; no. 1; pp. 1372 - 12
• Main Authors: Zhang, Yanxu, Wu, Peipei, Xu, Ruochong, Wang, Xuantong, Lei, Lili, Schartup, Amina T., Peng, Yiming, Pang, Qiaotong, Wang, Xinle, Mai, Lei, Wang, Ruwei, Liu, Huan, Wang, Xiaotong, Luijendijk, Arjen, Chassignet, Eric, Xu, Xiaobiao, Shen, Huizhong, Zheng, Shuxiu, Zeng, Eddy Y.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13.03.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 704/172; 704/829; Abundance; Confidence intervals; Discharge; Emission analysis; Emission inventories; Emissions; Estimation; Humanities and Social Sciences; Laboratories; Marine ecosystems; Marine pollution; multidisciplinary; Ocean models; Outdoor air quality; Parameters; Plastic debris; Plastic pollution; Rivers; Science; Science (multidisciplinary); Seawater; Uncertainty
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-023-37108-5

Marine plastic pollution poses a potential threat to the ecosystem, but the sources and their magnitudes remain largely unclear. Existing bottom-up emission inventories vary among studies for two to three orders of magnitudes (OMs). Here, we adopt a top-down approach that uses observed dataset of sea surface plastic concentrations and an ensemble of ocean transport models to reduce the uncertainty of global plastic discharge. The optimal estimation of plastic emissions in this study varies about 1.5 OMs: 0.70 (0.13–3.8 as a 95% confidence interval) million metric tons yr −1 at the present day. We find that the variability of surface plastic abundance caused by different emission inventories is higher than that caused by model parameters. We suggest that more accurate emission inventories, more data for the abundance in the seawater and other compartments, and more accurate model parameters are required to further reduce the uncertainty of our estimate. Estimating the amount of plastics that enters the ocean is subject to significant uncertainty. This study uses ocean plastic abundance data to refine our estimate and reduce this uncertainty, enabling more effective control and mitigation polices.