Controls on Suspended Particle Properties and Water Clarity along a Partially-Mixed Estuary, York River Estuary, Virginia Kelsey A. Fall1, Carl T. Friedrichs1, Grace M. Cartwright1, and David G. Bowers2 1Virginia Institute of Marine Science 2School of Ocean Sciences, Bangor University

Kd: Diffuse Light Attenuation Coefficient Motivation: Water clarity a major water quality issue in the Chesapeake Bay. Despite decreases in sediment input water clarity has continued to deteriorate. Annual means of ZSDKd for the Chesapeake Bay. Ratio of scattering to absorption. ZSD: Secchi Disk Depth Kd: Diffuse Light Attenuation Coefficient (Gallegos et al.,2011). The main motivation behind this study is the fact that like many coastal systems water clarity is a major water quality issue in the Chesapeake Bay. Despite decreases in sediment input over the last couple of decades conditions have continued to deteriorate. Gallegos 2011 compiled historical monitoring data from the Chesapeake Bay and noticed a long term decreasing trend in ZSDKd with no increase in remote sensing reflectance (so no significant change in particulate backscattering). This trend suggests the something about the water’s composition is changing. He then ran various model simulations found that the most likely cause of this trend is an increase in smaller, more organic rich particles. Typical estuarine particles are not single solid particles, but clusters of inorganic and organic particles and water, called flocs. Floc are challenging to observe in-situ, so their influence on the optical properties of the system have yet to be completely defined. Gallegos et al. (2011) suggests the most likely explanation for theses trends is an increase in the concentration of continually suspended, smaller, organic rich particles. 1/12

Objective: Investigate the controls on suspended particle properties (size, concentration, composition) evaluate the influence of these particles on light attenation. YORK RIVER CHESEAPEAKE BAY VIMS Latitude Longitude Study Site: York River Estuary, VA, U.S.A Partially mixed, muddy, microtidal estuary located adjacent to the lower Chesapeake Bay. Depths along the main channel decrease from ~20 m near the mouth to ~6 m near ETM. Exhibits spatial patterns in stratification, physical mixing, total suspended solids, organic solids. Suspended solids are dominated by flocs. This study: Utilized observations collected at different stations along the York from 2013-2015. West Point ETM Average Total Suspended Solids (TSS) Average Salinity Surface Bottom Surface Bottom TSS mgL-1 Salinity (ppt) Distance from the Mouth (km) Distance from the Mouth (km) 2/12

Coastal Hydrodynamics and Sediment Dynamics (CHSD) Water Column Profiler Pump sampler: Total suspended solids (TSS) and organic content LISST-100X: Particle Sizes ~2.5-500 μm Beam attenuation (beam c) from optical transmission Particle Imaging Camera System (PICS): Particle Sizes ~30-1000 μm Individual particle densities and settling velocities Acoustic Doppler Velocimeter (ADV) provide estimates of: current velocities and mass concentration of suspended particle matter Bottom: turbulence/bed stress, bulk settling velocity CTD with a turbidity sensor water clarity proxy Radiometer or LI-COR light sensor Vertical profile of diffuse light attenuation (Kd) CHSD Profiler ADVs PICS LISST CTD Pump Sampler Pump Sampler ADVs PICs [Added “total suspended solids”, shortened ADV entry, added “vertical profile”] ADVs provide information about physical parameters as well as bulk particle characteristics LISST and PICS provide particle size information. LISST gives particle distribution spectrums from 2-500 microns. PICs provides particle sizes and settling velocities for particles 30- Previously, water clarity information from a CTD with a turbidity sensor and for this project we will also use a Li-Cor Light sensor or Radiometer. CTD LISST (Smith and Friedrichs, 2014, 2010; Cartwright et al., 2013; 2009; Fugate and Friedrichs, 2002). 3/12

Characterization of Particle Size (Area and Volume) with the LISST and PICS LISST (2.5-500 μm) uses laser diffraction to determine VC in size class i (VCi) then PICS (30-1000 μm) uses particle imaging analysis to measure the major and minor axis lengths and calculates equivalent spherical diameter and projected area. Example from surface water June 2013: Particle Size μm LISST PICS Volume Concentration Distribution [Vi] VCi μL/L Ai cm2/L Area Concentration Distributions [Ai] Particle Size μm LISST PICS 4/12

Characterization of Particle Size (Area and Volume) with the LISST and PICS Combine PICS and LISST to create new volume and area distributions from 2.5-1000 μm where: 2.5-60 μm: LISST 60-200 μm: Linearly weighted average of LISST and PICS 200-1000 μm: PICS Example from surface water June 2013: Particle Size μm Volume Concentration Distribution [Vi] VCi μL/L Ai cm2/L Area Concentration Distributions [Ai] Particle Size μm LISST AVG PICS LISST AVG PICS 4/12

Characterization of Particle Size (Area and Volume) with the LISST and PICS Combine PICS and LISST to create new volume and area distributions from 2.5-1000 μm where: 2.5-60 μm: LISST 60-200 μm: Linearly weighted average of LISST and PICS 200-1000 μm: PICS Example from surface water June 2013: Volume Concentration Distribution [Vi] Area Concentration Distributions [Ai] Ai cm2/L Particle Size μm LISST AVG PICS LISST AVG PICS Particle Size μm VCi μL/L 5/12

Characterization of Particle Size (Area and Volume) with the LISST and PICS Define particle characteristics with new distributions ( D50A, AT, ρa ): D50A : Median particle size based on area distribution. AT: Total area per liter (AT=Σai) ρa: Effective density (ρa=TSS/VCT, where VCT=Total Volume Concentration) Example from surface water June 2013: Volume Concentration Distribution [Vi] Area Concentration Distributions [Ai] Ai cm2/L Particle Size μm D50v≈74 μm D50A ≈11 μm AT≈206 cm2/L Particle Size μm VCi μL/L 5/12

*Most of the AT attributed to smaller particles Characterization of Particle Size (Area and Volume) with the LISST and PICS Define particle characteristics with new distributions ( D50A, AT, ρa ): D50A : Median particle size based on area distribution. AT: Total area per liter (AT=Σai) ρa: Effective density (ρa=TSS/VCT, where VCT=Total Volume Concentration) *Most of the AT attributed to smaller particles *Quite a bit of difference between D50v and D50A Example from surface water June 2013: Volume Concentration Distribution [Vi] Area Concentration Distributions [Ai] Ai cm2/L Particle Size μm D50v≈74 μm D50A ≈11 μm AT≈206 cm2/L Particle Size μm VCi μL/L 5/12

What do Suspended Particles (Flocs) in the York look like? PICS Video Collected 30 km upstream PICS Video Collected 9 km upstream 3 mm 4 mm YR151026 YR130612 Typically larger particles and higher concentrations are observed at 30 km than at 9 km upstream. 6/12

D50A increases as TSS increases Trends in Particle Size (in terms of D50A) in the Upper Water Column of the York *Different Symbols/colors represent different cruises A. TSS versus D50A TSS (mg/L) D50A (microns) D50A increases as TSS increases 7/12

D50A decreases as organic Trends in Particle Size (in terms of D50A) in the Upper Water Column of the York *Different Symbols/colors represent different cruises A. TSS versus D50A B. Organic Fraction versus D50A TSS (mg/L) Organic Fraction D50A (microns) D50A (microns) D50A increases as TSS increases D50A decreases as organic content increases 7/12

D50A increases as TSS increases D50A decreases as organic Trends in Particle Size (in terms of D50A) in the Upper Water Column of the York *Different Symbols/colors represent different cruises A. TSS versus D50A B. Organic Fraction versus D50A C. Effective Density versus D50A TSS (mg/L) Organic Fraction ρa (kg/m2) D50A (microns) D50A (microns) D50A (microns) D50A increases as TSS increases D50A decreases as organic content increases D50A decreases as effective density increases 7/12

Characterization Light Attenuation in the Upper Water Column of the York attenuation = amount of light lost through either absorption or scattering . Beam Attenuation Coefficient ( beam c) from LISST (laser=670 nm) Calculated from transmission, T and instrument path length, x (LISST x=0.05m): Absorbed Light Scattered Light Initial Intensity, Io Final Intensity, IT Light Source: 670 nm Laser Detector with 0.0269 ° acceptance angle Transmission is the ratio of the intensity of light reaching a receiver through a sample relative to the light intensity in pure water. LISST beam c VERY sensitive to scattering Assume CDOM is not absorbing at 670 nm x 8/12

Characterization Light Attenuation in the Upper Water Column of the York attenuation = amount of light lost through either absorption or scattering . Beam Attenuation Coefficient ( beam c) from LISST (670 nm) Calculated from transmission, T and instrument path length, x (LISST x=0.05m): Assumed loss Scattered Light Absorbed Light Initial Intensity, Io Final Intensity, IT Light Source: 670 nm Laser Detector with 0.0269 ° acceptance angle Transmission is the ratio of the intensity of light reaching a receiver through a sample relative to the light intensity in pure water. LISST beam c VERY sensitive to scattering Assume CDOM is not absorbing at 670 nm x *LISST beam c EXTREMELY SENSITIVE to scattering Small acceptance angle 8/12

Characterization Light Attenuation in the Upper Water Column of the York attenuation = amount of light lost through either absorption or scattering . Beam Attenuation Coefficient ( beam c) from LISST (670 nm) Calculated from transmission, T and instrument path length, x (LISST x=0.05m): Assumed loss Scattered Light Absorbed Light Initial Intensity, Io Final Intensity, IT Light Source: 670 nm Laser Detector with 0.0269 ° acceptance angle Transmission is the ratio of the intensity of light reaching a receiver through a sample relative to the light intensity in pure water. LISST beam c VERY sensitive to scattering Assume CDOM is not absorbing at 670 nm x *LISST beam c EXTREMELY SENSITIVE to scattering Small acceptance angle The effect of water is removed during LISST calibration. CDOM (and most) Absorption minimal at 670 nm 8/12

LICOR: Measures Scalar Ed Characterization Light Attenuation in the Upper Water Column of the York attenuation = amount of light lost through either absorption or scattering . Vertical Diffuse Attenuation of PAR, Kd : Change of downward irradiance (Ed) with depth (z) measured by either Radiometer or LICOR Most popular parameter used to characterize systems the availability of photosynthetic useful radiant energy (400-700 nm). Example Ed from 10/26/15 LICOR: Measures Scalar Ed (Almost angles) TRIOS: Measures Ed from 0-180° Transmission is the ratio of the intensity of light reaching a receiver through a sample relative to the light intensity in pure water. “Best single parameter by means to characterize systems by the availability of photosynthetic useful radiant energy.” The linear regression coefficient (i.e. slope) of the logarithm of deck-corrected Ed with respect to depth yields Kd (Kirk, 1994). 9/12

LICOR: Measures Scalar Ed Characterization Light Attenuation in the Upper Water Column of the York attenuation = amount of light lost through either absorption or scattering . Vertical Diffuse Attenuation of PAR, Kd : Change of downward irradiance (Ed) with depth (z) measured by either Radiometer or LICOR Most popular parameter used to characterize systems the availability of photosynthetic useful radiant energy (400-700 nm). Example Ed from 10/26/15 Kd captures absorbance (Water, CDOM, Particles), and scattering (Particles). LICOR: Measures Scalar Ed (Almost angles) TRIOS: Measures Ed from 0-180° Transmission is the ratio of the intensity of light reaching a receiver through a sample relative to the light intensity in pure water. “Best single parameter by means to characterize systems by the availability of photosynthetic useful radiant energy.” The linear regression coefficient (i.e. slope) of the logarithm of deck-corrected Ed with respect to depth yields Kd (Kirk, 1994). 9/12

As TSS increases up estuary, both beam c and Kd increase. Relationship between Attenuation and TSS in the Upper Water Column of the York A. Beam c versus TSS Kdm-1 TSS (mgL-1) B. Kd versus TSS beam c m-1 TSS (mgL-1) As TSS increases up estuary, both beam c and Kd increase. *Different Symbols/colors represent different cruises 10/14

So what about the particles? Relationship between Attenuation and Area in the Upper Water Column of the York A. Beam c versus AT B. Kd versus AT beam c m-1 Kd m-1 AT (cm2/L) AT (cm2/L) Attenuations are explained better by AT than TSS. Beam c less noisy than Kd due Influence of absorption (CDOM, Water, Particles).. So what about the particles? *Different Symbols/colors represent different cruises 11/14

Relationship between Attenuation and Area in the Upper Water Column of the York A. Beam c versus AT B. Kd versus AT beam c m-1 Kd m-1 AT (cm2/L) AT (cm2/L) CDOM is unlikely to absorb at 670 nm, and effect of water is removed during LISST calibration so cp ≈ beam c. *Different Symbols/colors represent different cruises 11/14

Kd captures absorbance (400-700 nm), so it’s a bit more complicated. Relationship between Attenuation and Area in the Upper Water Column of the York A. Beam c versus AT B. Kd versus AT beam c m-1 Kd m-1 AT (cm2/L) AT (cm2/L) CDOM is unlikely to absorb at 670 nm, and effect of water is removed during LISST calibration so cp ≈ beam c. Kd captures absorbance (400-700 nm), so it’s a bit more complicated. *Different Symbols/colors represent different cruises 11/14

KdDISS varies as a function of salinity. Relationship between Attenuation and Area in the Upper Water Column of the York A. Beam c versus AT B. Kd versus AT beam cp m-1 Kd m-1 ployfit=least squares Based on change in intercept due to salinity, best-fit equation for KdDISS for the York: KdDISS=1.67 - 0.0667*Salinity AT (cm2/L) AT (cm2/L) Find KdDISS (CDOM +water) using intercept between Kd vs AT with the following assumptions: At AT=0, Kd= KdDISS KdDISS varies as a function of salinity. Freshwater is the main source of CDOM Analysis showed shift in intercept as a function of salinity. *Different Symbols/colors represent different cruises 11/14

*Still see influence due to absorption by particles Relationship between Attenuation and Area in the Upper Water Column of the York A. Beam c versus AT B. Kdp versus AT Kdp m-1 beam cp m-1 ployfit=least squares AT (cm2/L) AT (cm2/L) cp ≈ beam c KdDISS = 1.67 - 0.0667*Salinity Kdp=Kd-KdDISS *Still see influence due to absorption by particles *Different Symbols/colors represent different cruises 12/14

Cp not very sensitive to density while Kdp increases with density. Controls on Attenuation Efficiency (Beam cp/AT and diffuse Kdp/AT): Influence of density (ρa) If you take out the effect of area, what other properties influence beam cp and Kdp? B. Kdp efficiency versus ρa A. Beam cp efficiency versus ρa cp /AT Kdp /AT Be sure to say why this matters!!! conceptually this is consistent with the idea that as particles become more opaque they absorb more light. ρa (kg/m3) ρa (kg/m3) Cp not very sensitive to density while Kdp increases with density. Higher density particles absorb more light per area increasing Kdp/AT. But high and low density particles scatter the same amount of light per area, so cp/AT remains constant. *Different Symbols/colors represent different cruises 13/14

Conclusions Observations found small, organic particles suggested by Gallegos et al., 2011. Preliminary results from the York indicate importance of these small, more organic particles on total particle area concentration (AT). Attenuations coefficients (beam c and Kd) are better explained by total particle area concentration (AT) than total suspended solids (TSS). C less noisy than Kd. Beam attenuation due to particles (beam cp) was not sensitive to density but was strongly proportional to total particle area (AT). Beam cp (scattering) is controlled mostly by particle area (Bowers et al., 2011; Neukermans et al.,2012). Particle Diffuse Attenuation Coefficient (KdP) increased more strongly with density than beam attenuation (beam cp). Kd PAR (absorption and scattering) is influenced by area and density (Bowers et al., 2011). Future work will include (i) many more sampling cruises and (ii) Further analysis incorporating other proxies to strengthen estimates of Kdp (iii) Further analysis of spatial and temporal trends in floc properties and water clarity . 14/14

Acknowledgements Tim Gass Wayne Reisner Funding: Jarrell Smith Jennifer Stanhope Steve Synder Erin Shields Danielle Tarpley Hunter Walker