PS 43-64 - Combining environmental and socioeconomic data to identify drivers of plastic pollution in stormwater retention ponds

Background/Question/Methods

Plastic pollution is a global issue that impacts every ecosystem on earth. As a uniquely anthropogenic pollutant, it may be assumed plastic pollution would be most severe in highly urbanized areas; however existing literature on plastic pollution in terrestrial ecosystems has found urbanized land use to be a poor predictor of plastic pollution severity. There is thus a gap in our understanding of the drivers of plastic pollution within the urban landscape. Because stormwater ponds integrate and serve as sentinels of activity in their contributing areas, they provide an opportunity to evaluate socioenvironmental drivers of plastic pollution. This research accordingly aims to 1) characterize the size, polymer type, and quantity of macro- and micro- plastic pollution in urban stormwater ponds and 2) identify relationships between environmental and socioeconomic characteristics within stormwater basins and the properties of plastic pollution in ponds. Environmental predictors include nutrient levels, land use, and impervious surface cover, while socioeconomic predictors include median income and population demographics. Ponds were selected along a gradient of urban land use types and sampled during the dry season. Macroplastics were collected through visual surveys, while microplastics were isolated from soil samples through density extraction. Polymer type was identified through Raman spectroscopy.

Results/Conclusions

Macroplastic pollution was found in 95% of sampled ponds (21 of 22). The density of collected macroplastic pollution ranged from 0 to 1.96 g per m² (median = 0.03 g per m²). Microplastic results are pending. The correlation between the density of macroplastic pollution and percent of urban land use in a pond’s watershed was modest (Spearman’s Rho = 0.34, p-value = 0.067). Models that only consider drainage-basin land use may be weak predictors of material delivered to receiving ponds because they do not account for the variation in human activity that may occur within any land use type. Therefore, models seeking to predict pollutant delivery from landscapes to stormwater ponds or other receiving systems may benefit by incorporating more detailed social data. Results from this study will help elucidate relationships between the built environment, socioeconomic watershed characteristics, and plastic pollution in stormwater receiving ponds to help manage and mitigate stormwater pollution.