Ridding our rivers of plastic: A framework for plastic pollution capture device selection.

Rivers are a major pathway for the transport of plastics into the ocean. Plastic pollution capture devices offer one way to reduce the accumulation of plastic in the environment. This paper provides a framework for selecting a device to reduce plastic pollution in freshwater, synthesizing information of forty prevailing plastic pollution capture devices. We distinguish three major components of plastic pollution technology (booms, receptacles, and watercraft vehicles) and collect details on each technology including its features, limitations, efficiency, reported costs, and maintenance requirements. A framework is developed to aid in device selection by water and waste managers, which highlights the need for a watershed assessment, an understanding of site conditions, the attainment of community buy-in, and a long-term maintenance plan. While plastic pollution capture devices can help reduce the flux of plastic waste from freshwater, management of plastic waste at the source is also needed to ultimately clean our oceans and waterways.

Implications of Using Different Water Sources When Hydrologically Compacting Bioretention Columns.

Many investigators have conducted research on bioretention systems both in the laboratory and field. There is little consensus on which sources of water are best suited to hydrologically compact bioretention columns. Water with low ionic strength can leach ions from soil media, resulting in a different soil chemistry environment than would be found in typical bioretention applications. Soil columns were hydrologically compacted with three different water sources often used in column studies: deionized water, tap water, and rain water. Influent and effluent samples for each water source were measured for pH, conductivity, copper, zinc, and phosphate. On average, deionized water yielded larger percentage increases between influent and effluent for pH, conductivity, copper, and zinc, indicating that deionized water leaches out more ions from bioretention media than tap water or rain water. To maintain soil chemistry similar to the field, rain water or tap water should be used in column studies.

Nitrate and phosphate removal through enhanced bioretention media: mesocosm study.

Bioretention is an evolving type of Green Stormwater Infrastructure (GSI) designed to attenuate peak flows, reduce stormwater volume, and treat stormwater. This article examines the capabilities of a bioretention soil mixture of sand and compost enhanced with aluminum-based drinking water treatment residuals to reduce nutrients from stormwater runoff. Columns with and without a saturation zone and vegetation were compared to examine their role in removing nitrate and ortho-phosphate from stormwater. Results show that utilization of a saturation zone can significantly reduce nitrate in effluent water (71% compared to 33% without a saturated zone), even in a newly constructed system. However, ortho-phosphate reduction was significantly better in the columns without a saturated zone (80%) compared to columns with (67%). Plants did not significantly improve removal. This suggests amendments such as aluminum-based water treatment residuals for phosphorus removal and a saturation zone for nitrogen removal are needed during the initial establishment period.

Using regression tree analysis to improve predictions of low-flow nitrate and chloride in Willamette River Basin watersheds.

The use of regression tree analysis is examined as a tool to evaluate hydrologic and land use factors that affect nitrate and chloride stream concentrations during low-flow conditions. Although this data mining technique has been used to assess a range of ecological parameters, it has not previously been used for stream water quality analysis. Regression tree analysis was conducted on nitrate and chloride data from 71 watersheds in the Willamette River Basin to determine whether this method provides a greater predictive ability compared to standard multiple linear regression, and to elucidate the potential roles of controlling mechanisms. Metrics used in the models included a variety of watershed-scale landscape indices and land use classifications. Regression tree analysis significantly enhanced model accuracy over multiple linear regression, increasing nitrate R² values from 0.38 to 0.75 and chloride R² values from 0.64 to 0.85 and as indicated by the ΔAIC value. These improvements are primarily attributed to the ability for regression trees to more effectively handle interactions and manage non-linear functions associated with watershed heterogeneity within the basin. Whereas hydrologic factors governed the conservative chloride tracer in the model, land use dominated control of nitrate concentrations. Watersheds containing higher agricultural activity did not necessarily yield high nitrate concentrations, but agricultural areas combined with either small proportions of forested land or greater urbanization generated nitrate levels far exceeding water quality standards. Although further refinements are recommended, we conclude that regression tree analysis presents water resource managers a promising tool that improves on the predictive ability of standard statistical methods, provides insight into controlling mechanisms, and helps identify catchment characteristics associated with water quality impairment.

Testing the hydrological landscape unit classification system and other terrain analysis measures for predicting low-flow nitrate and chloride in watersheds.

Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use-elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification scheme.