Microplastics pollution in the soil mulched by dust-proof nets: A case study in Beijing, China

Abstract

As a driving factor of global changes, microplastics have gradually attracted widespread attention. Although MPs are extensively studied in aquatic systems, their presence and fate in terrestrial systems and soil are not fully understood. In China, construction-land must be mulched by dust-proof nets to prevent and control fine particulate pollution, which may cause MPs pollution and increase ecological risks. In order to understand the pollution characteristics and sources of MP in the soil covered by dust nets, we conducted a case study in Beijing. Our results revealed that the abundance of MPs in soil mulched by dust-proof nets ranged from 272 to 13,752 items/kg. Large-sized particles (>1000 μm) made up a significant proportion (49.83%) of MPs in the study area. The dominant MP polymer types were polyethylene (50.12%) and polypropylene (41.25%). The accumulation of MPs in construction-site soil mulched by dust-proof nets (average, 4910.2 items/kg) was significantly higher (P < 0.05) than that in unmulched soil (average, 840.8 items/kg), which indicates a dust-proof nets as an essential source of microplastics in the soil of construction land. We applied a remote-sensing data analysis technique based on remote imagery acquired from a high-resolution remote-sensing satellite combined with deep-learning convolutional neural networks to automatically detect and segment dust-proof nets. Based on high-resolution remote sensing images and using a U-net convolutional neural network, we extract the coverage area of Beijing's dust-proof nets (18.6 km²). Combined the abundance of MPs and the dust-proof nets' coverage area, we roughly estimate that 7.616 × 10⁹ to 3.581 × 10¹¹ MPs accumulated in the soil mulched by the dust-proof nets in Beijing. Such a large amount of MPs may cause a series of environmental problems. This study will highlight the understanding of soil MPs pollution and its potential environmental impacts for scientists and policymakers. It provides suggestions for decision-makers to formulate effective legislation and policies, so as to protect human health and protect the soil and the wider environment.

Keywords: Deep learning; Dust-proof nets; Microplastics pollution; Remote sensing; Soil.