Crowd-Based Observations of Riverine Macroplastic Pollution

摘要: Macroplastic pollution (> 0.5 cm) negatively impacts aquatic life and threatens human livelihood on land, in oceans river systems. Reliable information the origin, fate pathways of plastic systems is required to optimize prevention, mitigation reduction strategies. Yet, accurate long-term data transport are still lacking. Current macroplastic monitoring strategies involve labor intensive sampling methods, require investment infrastructure, therefore infrequent. Crowd-based observations riverine may potentially provide frequent cost-effective collection over a large geographical range. We extended CrowdWater citizen science app for hydrological with module rivers. In this paper, we demonstrate potential crowd-based floating riverbanks. analyzed from two case studies: (1) measured Klang (Malaysia), (2) riverbanks along Rhine (the Netherlands). yield similar estimates (2,000–3,000 items h−1), cross-sectional distribution (3–7 percent point difference) polymer categories (0–6 as reference observations. It also highlighted high temporal variation transport. The riverbank provided first most downstream stretch Rhine, revealing peaks close urban areas an increasing density toward mouth. mean methods (573–1,033 km−1). These results highlight value including future reliable estimations transport, density, spatiotemporal composition larger number locations than conventional methods.