Water Quality Impairment from Contaminants on Particles: Size-Dependent Composition in Roadway Runoff and Measurements of Small Particles and Associated.

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Presentation transcript:

Water Quality Impairment from Contaminants on Particles: Size-Dependent Composition in Roadway Runoff and Measurements of Small Particles and Associated Contaminants in Highway Runoff. Peter G. Green, Hyun-Min Hwang, Masoud Kayhanian, and Thomas M. Young Department of Civil & Environmental Engineering, University of California, Davis UCDavis.edu Session C7 3:35-3:55pm Monday, May 8 th, room C3

Abstract: Small particles critically affect water quality. Besides reducing water clarity, sparingly soluble pollutants such as polycyclic aromatic hydrocarbons (PAHs) and some heavy metals are predominantly transported on particles. We have conducted a series of studies on non-point-source (NPS) roadway-derived fine particles, defined here as <63um – traditionally the upper limit of ‘silt’ and a size range which is readily suspended in moving water and which settles slowly. At the finest, we have examined the elemental composition of particles in the size range of 0.1 to 0.3um, commonly considered ‘colloidal’ – that is, non-settling. (Importantly, these also readily pass through filters of 0.45um or larger pore-size.) In addition we have begun characterizing the sources of particles and particle-bound pollutants, and studied the solubilization of metals by dissolved organic matter.

Locations of studies Arcade Creek Davis I-80 Interstate 680 Calif. Highway 91 in Corona I-80 Vacaville Fairfield Maintenance Yard Interstate 880 (Also 3 sites near UCLA: US-101 & 2 on I-405)

Monitoring of CTR Pollutants in Stormwater Runoff Collected at Caltrans Facilities

Concentrations typically highest at beginning of rainy season, but also quite high later –following long dry periods. (I-80 Vacaville)

Concentrations typically highest at beginning of rainy season, but also quite high later –such as during small storms. (I-80 Davis)

Abundant Fine Particles in Highway Runoff

Methods Filtration in field, during storms Stokes-law settling in lab, same day Flow cytometry – particle sorting (by light scattering) Particle counts by light-scattering (Liquilaz) in lab and at highway road-side Ultrafiltration (1kDa cut-off, ~1nm) Analysis by GC-MS and ICP-MS

Particle Sorter Schematic (DykoCytomation MoFlo Cell Sorter )

Fraction of total particle mass in sub-micron size range. Note clear trend in Pb.

Cumulative Elemental Composition of Particles in Highway Storm-water

Distribution of PAHs in 2um to 63um Size-Classes of Particles in Highway Stormwater

PAHs on colloidal particles >90% of heaviest PAHs which ‘filter’ are not actually dissolved.

Note very high level of Cd on brakes – due to anti-squeak coating! (Fractional composition out of 21 element total.)

Lee Read M.S. Thesis: Figure 1. The influence of DOC on copper (Cu) desorption (Lu and Young, unpublished) Dissolved organic matter solubilizes copper.

Figure 2. Metal desorption from particles in contact with constant DOC concentration over time, DOC = 19.2 mg/L Time (hours) Dissolved Cu and Zn Concentrations (ppb) Dissolved Ni and Pb Concentrations (ppb) CuZn NiPb Time scale of metal solubilization. (H.L.Read, M.S. thesis 2005)

Initial mobilization of Cu Progression through storm DOC(mg/L) pH (6.8 to 7.2) Cu(% F/UF)

Conclusions: Several different approaches have successfully begun to characterize with size-dependent detail the elemental and organic composition of non-point source pollution from highway and urban run-off, as well as directly from vehicles. For PAHs (especially heavier PAHs) dramatic water quality improvements are only achieved where all but the finest (~1um) particles are removed. For heavy metals, continuous improvement in water quality is seen as ever smaller particles are removed – all the way into the colloidal (<0.5um) range.

Acknowledgements: We gratefully acknowledge support from Caltrans, University California Toxics Research and Training Program, and the EPA Superfund Basic Research program. Data has kindly been shared by graduate students Carol Wong, Daekyun Kim, Jon Money and Lee Read. On-going collaboration with Prof. Mike Stenstrom, UCLA, with post-doc Sim-Lin Lau and other group members.