Pottinger A Samuel, Geyer Roland, Biyani Nivedita, Martinez Ciera C, Nathan Neil, Morse Molly R, Liu Chao, Hu Shanying, de Bruyn Magali, Boettiger Carl, Baker Elijah, McCauley Douglas J
Eric and Wendy Schmidt Center for Data Science and Environment, University of California Berkeley, Berkeley, CA, USA.
Department of Environmental Science, Policy & Management, University of California Berkeley, Berkeley, CA, USA.
Science. 2024 Dec 6;386(6726):1168-1173. doi: 10.1126/science.adr3837. Epub 2024 Nov 14.
Plastic production and plastic pollution have a negative effect on our environment, environmental justice, and climate change. Using detailed global and regional plastics datasets coupled with socioeconomic data, we employ machine learning to predict that, without intervention, annual mismanaged plastic waste will nearly double to 121 million metric tonnes (Mt) [100 to 139 Mt 95% confidence interval] by 2050. Annual greenhouse gas emissions from the plastic system are projected to grow by 37% to 3.35 billion tonnes CO equivalent (3.09 to 3.54) over the same period. The United Nations plastic pollution treaty presents an opportunity to reshape these outcomes. We simulate eight candidate treaty policies and find that just four could together reduce mismanaged plastic waste by 91% (86 to 98%) and gross plastic-related greenhouse gas emissions by one-third.
塑料生产和塑料污染对我们的环境、环境正义和气候变化产生负面影响。利用详细的全球和区域塑料数据集以及社会经济数据,我们运用机器学习预测,若不进行干预,到2050年,每年管理不善的塑料垃圾将几乎翻倍至1.21亿吨(95%置信区间为1.00至1.39亿吨)。同期,塑料系统的年度温室气体排放量预计将增长37%,达到33.5亿吨二氧化碳当量(30.9至35.4亿吨)。联合国塑料污染条约为重塑这些结果提供了契机。我们模拟了八项候选条约政策,发现仅四项政策就能共同将管理不善的塑料垃圾减少91%(86%至98%),并将与塑料相关的温室气体总排放量减少三分之一。