UC Santa Barbara

Plastic trash, microplastics, and per- and polyfluoroalkyl substances (PFAS) are co-occurring, ubiquitous, and persistent urban pollutants with demonstrated adverse impacts on human and ecosystem health. Though their sources may differ, urban runoff is a major transport pathway for all three of these pollutants into surface waters. Given emerging regulatory and legislative responses at federal and state levels, accurately estimating these pollutants’ loads with measures of variance is critical to monitoring, determining risk, informing policy design, and ensuring compliance with remediation requirements. However, field campaigns to directly measure plastic trash, microplastics, and PFAS are time- and cost-intensive, resulting in data limitations. In the case of plastic trash, current single-pass surveying methods are known to underestimate environmental loads, and lack measures of effort and variance, preventing cross-study comparisons. Surface waters receiving plastic trash, microplastics, and PFAS via urban runoff may interact with groundwater, an important drinking water resource. Yet, studies measuring microplastics in groundwater are rare, and studies measuring both microplastics and PFAS in groundwater as well as in potentially interacting surface waters are rarer still. This dissertation addresses these limitations and knowledge gaps. In Chapter II, we demonstrate that multiple-pass removal surveys with depletion modeling, a well-established method in fisheries ecology, can be adapted to estimate plastic trash abundance with quantified variance and standardized sampling effort, enabling both the quantification of single-pass survey underestimation and cross-study comparison of plastic trash loads. In Chapter III, we compare plastic trash abundance estimates and standard errors from multiple-pass removal surveys with depletion modeling to those derived from a mark-recapture surveying approach, another well-established fisheries ecology method, to determine whether the two methods converge on similar estimates when applied to the same plastic trash within the same transect. In Chapter IV, we evaluate agreement between depletion-modeled trash mass estimates and qualitative trash level categories assigned using the On-Land Visual Trash Assessment method, California's primary single-pass trash assessment protocol. We also use Empirical Bayesian Kriging Regression Prediction to interpolate spatially explicit estimates of total trash mass, stratified by Priority Land Use across the sidewalk networks of three neighboring watersheds, with quantified uncertainty. In Chapter V, we determine the concentration and composition of microplastics and PFAS in municipal production well water and surface waters potentially interacting with the source aquifer in the same study area as Chapter IV. Together, these studies provide actionable insights for stormwater and water resource managers navigating plastic trash, microplastic, and PFAS regulations. We found that, on average, single-pass surveys underestimated plastic trash count and mass by 72% (SD ±12%) and 53% (SD ±17%) respectively when conducted across a variety of transect types in a coupled human and natural system, and by 48% (SD ±18%) and 46% (SD ±16%) respectively when conducted across more uniform transect types along an urban sidewalk network. When plastic trash was surveyed in the same transect using both a mark-recapture approach and multiple-pass removal survey with depletion modeling, we found that estimated plastic trash counts and associated standard errors were very similar: 268 (SE ±75) and 313 (SE ±73), respectively. We found that On-Land Visual Trash Assessments meaningfully distinguished sites categorized as "Not Littered" from those categorized as "Slightly Littered" and "Littered," but did not distinguish trash mass between "Slightly Littered" and "Littered" transects. Empirical Bayesian Kriging Regression Prediction revealed that trash density patterns were not consistent with Priority Land Use designations in one of three watersheds of interest, and that location-specific effects beyond Priority Land Use designations alone may suggest the need for watershed-wide intervention. Finally, microplastics and PFAS were detected in the majority of waters sampled, with plastic plumbing infrastructure identified as a potential source of microplastics in municipal production well water samples. Together, this body of work quantifies single-pass trash survey underestimation and offers managers two novel methods for estimating trash abundance with measures of variance. We also provide a spatially explicit methodological framework to interpolate trash mass at the watershed scale, determine agreement between mass-based trash loads and current primary statewide trash assessment categories, and characterize microplastic and PFAS concentrations across water resources, all within the same urban system.