Data_Sheet_3_Crowd-Based Observations of Riverine Macroplastic Pollution.CSV

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

大型塑料污染（Macroplastic，粒径＞0.5 cm）会对水生生物造成负面影响，同时威胁陆地、海洋与河流系统沿岸的人类生计。为优化塑料污染的预防、缓解与减排策略，亟需获取河流系统中塑料污染物的来源、归趋与迁移路径的可靠信息。但目前仍缺乏准确且长期的塑料迁移观测数据。当前的大型塑料污染监测策略多采用劳动密集型采样方法，且需投入基础设施建设，因此监测频次普遍偏低。针对河流大型塑料污染的众包观测，有望在大范围地理区域内实现高频次、低成本的数据采集。我们在原用于水文观测的公民科学（Citizen Science）应用CrowdWater中，新增了河流塑料污染观测模块。本研究验证了针对河流漂浮大型塑料与岸带大型塑料的众包观测潜力。我们对两个案例研究的数据进行了分析：（1）马来西亚巴生河（Klang）的漂浮塑料观测数据；（2）荷兰莱茵河（Rhine）沿岸岸带塑料观测数据。巴生河的漂浮塑料众包观测结果，与参考观测结果在塑料迁移量（2000~3000件/小时）、断面分布（差异为3~7个百分点）与聚合物类别占比（差异为0~6个百分点）的估算结果均保持一致。同时该观测也揭示了河流塑料迁移过程中显著的时间变异性。岸带观测首次获取了莱茵河最下游河段的大型塑料污染数据，结果显示塑料污染峰值出现在城区附近，且向河口方向塑料密度逐渐升高。众包观测与参考方法得到的岸带平均塑料密度估算结果同样相近（573~1033件/千米）。上述结果凸显了将河流大型塑料污染众包观测纳入未来监测策略的重要价值。相较于传统监测方法，众包观测可在更多监测点位获取塑料迁移量、密度、时空变异性与材质组成的可靠估算结果。