1. Evaluation of Street Sweeping as a Water Quality Management Tool in Three Residential Basins in Madison, WI Bill Selbig USGS – WRD Middleton, WI Bill Selbig USGS – WRD Middleton, WI

8. Can it Make a Difference?

9. Objectives Secondary 1.Evaluate benefits of different street sweepers 2.Evaluate benefits of various sweeping programs (frequency) 3.Characterize distribution of sediment particle size on street surfaces Primary 1.Determine if the dirt load on residential streets is reduced by street sweeping and if so, to what extent 2.Determine if reduction in street dirt load results in detectable change in water quality

10. Test - Pre Test - Post Control Response of Total Solids Concentration to Basin Change Paired Basin Approach

11. Selection of Basins -4 basins total (3 test basins and 1 control basin ) -3 basins equipped to monitor and sample stormwater -1 basin having only street dirt characterization BASIN NEEDS Proximity Age Topography Street condition Drain to a single point Logistics (power available?) SELECTION CRITERIA

13. Basin Area (ac.) ParcelStreet/SidewalkOther Control89.784%16% Crosswind52.478%22% Pelican58.275%20%2% City56.584%15%1% Land Use Within Control and Test Basins

15. Proposed Street Sweeping Schedule 2001 - 2004 * Introduction of Whirlwind sweeper and plastic bristles to study 20012002200320042005 January February March April May June July August September October November December *

16. 1.Characterize street dirt loading on weekly basis Accumulation rates Seasonal fluctuations Distribution over street (curb vs. centerline) Particle-size distribution Two – Pronged Approach to Evaluate Street Sweeping Effectiveness 2. Characterize pollutant loading during storm events Wash-off functions Seasonal fluctuations Particle-size distribution Bedload transport

19. 4.25 (s-1) 2 N = ---------------where, ā = mean (rā) 2 s = standard deviation r = allowable error N = number of subsamples required (Hansen et al 1984): Reducing Variability in Street Dirt Data Vacuuming 3 streets per basin Vacuum from curb to curb with 6” nozzle Vacuum strips are random but approximately 100 ft. apart Streets are measured individually then summed into a single basin

20. Reducing Variability in Street Dirt Data (cont.)

22. Street Lengths in Study Area StreetFeet Curb-miles

23. Detritus >2000um 1000 – 2000um 500 – 1000um 250 – 500um 125 – 250um 63 – 125um <63um Breakdown of particle sizes

24. Distribution of Particle Size

25. 4.67”11.86” May precip. Total Basin Street Dirt Load, in lbs./curb mi, for No Sweeping and Sweeping Years No Sweeping Sweeping No Sweeping

26. CROSSWIND CITY PELICAN CONTROL Comparison of total basin street dirt load, in lbs./curb mile, during non-sweeping phase June 2001 – September 2002 * * May – Sept. 2002

28. CROSSWIND CITY PELICAN CONTROL Comparison of total basin street dirt load, in lbs./curb mile, during sweeping phase April 2003 – September 2004

34. PELICAN ROBUST REGRESSION PRE SWEEPING (lbs./curb mi.) POST SWEEPING (lbs./curb mi.)

35. CROSSWIND ROBUST REGRESSION PRE SWEEPING (lbs./curb mi.) POST SWEEPING (lbs./curb mi.)

36. WHIRLWIND ROBUST REGRESSION PRE SWEEPING (lbs./curb mi.) POST SWEEPING (lbs./curb mi.)

37. Summary of Sweeper Efficiency Minimum initial load for which sweeping has a positive effect

38. Why do different technologies perform similarly? Majority of street dirt lies within 3 feet of the curb

41. Pre Sweeping Post Sweeping Broom technology cannot efficiently remove particles trapped in pockets or uneven surfaces

44. WATER QUALITY

45. Ammonia – Nitrogen NO2 + NO3 Kjeldahl Nitrogen Total Phosphorus Suspended Solids Total Dissolved Solids Chloride Hardness Calcium Magnesium Total Cadmium Dissolved Cadmium Total Copper Dissolved Copper Total Lead Dissolved Lead Total Zinc Dissolved Zinc Suspended Sediment Particle Size Dist. Constituent List Analyses performed by City of Madison Dept. of Public Health

55. Possible Reasons Water Quality Trends are Difficult to Detect Sweeper removal efficiencies not enough ISCO sample collection limitations Sample processing bias Inappropriate laboratory analyses Sweeper removal efficiencies not enough ISCO sample collection limitations Sample processing bias Inappropriate laboratory analyses Combination of all the above…

56. Sweeper Removal Not Enough 10 - 30% removal from street detectable in storm sewer? Wash-on distorts street dirt load Increase in smaller particle sizes after sweeper passes Do larger particles ever make it to storm sewer? 10 - 30% removal from street detectable in storm sewer? Wash-on distorts street dirt load Increase in smaller particle sizes after sweeper passes Do larger particles ever make it to storm sewer?

57. Increase in Smaller Particles

60. Sweeper Removal Not Enough 10 - 30% removal from street detectable in storm sewer? Wash-on distorts street dirt load Increase in smaller particle sizes after sweeper passes Do larger particles ever make it to storm sewer? 10 - 30% removal from street detectable in storm sewer? Wash-on distorts street dirt load Increase in smaller particle sizes after sweeper passes Do larger particles ever make it to storm sewer?

61. Sample Collection Small sample tube in large diameter pipe High velocities in pipe may reduce sampling ability Enrichment of sediment near bottom may affect results

62. Need to separate bedload from suspended load

66. Improving Trend Detection ISCO samplers do sample larger particles but maybe not a good representation Added bedload sampler to supplement Even though larger particles were sampled, laboratory procedure inappropriate for sediment-associated trace metals Revised sample processing techniques Improved laboratory procedures ISCO samplers do sample larger particles but maybe not a good representation Added bedload sampler to supplement Even though larger particles were sampled, laboratory procedure inappropriate for sediment-associated trace metals Revised sample processing techniques Improved laboratory procedures

67. Modified Sample Processing Remove larger particles from sample through sieve Analyze sample as two separate mediums; aqueous and solid Combine results into single event mean concentration Remove larger particles from sample through sieve Analyze sample as two separate mediums; aqueous and solid Combine results into single event mean concentration

68. Wet Sieving Initially removed particles >500um Separated into >1000, 500, and 250um fractions Now separating into only >250 and 125um fractions Initially removed particles >500um Separated into >1000, 500, and 250um fractions Now separating into only >250 and 125um fractions

70. Improved Correlation

71. Future Work Continue to collect street dirt and water- quality samples at the control and test basins through May 2005. Data analyses on different sweeper efficiencies Accumulation rates / Washoff function Rainfall influence on street dirt load Seasonality Report by Fall 2006. Continue to collect street dirt and water- quality samples at the control and test basins through May 2005. Data analyses on different sweeper efficiencies Accumulation rates / Washoff function Rainfall influence on street dirt load Seasonality Report by Fall 2006.

72. Work to boost study… Collect additional year of NO sweeping in Pelican basin Better correlation of QW Continue additional year of sweeping in Whirlwind basin Better correlation of QW 2004 not typical year Use data from study to help calibrate pollutant loading models (SLAMM) Parking Lots Polymers Collect additional year of NO sweeping in Pelican basin Better correlation of QW Continue additional year of sweeping in Whirlwind basin Better correlation of QW 2004 not typical year Use data from study to help calibrate pollutant loading models (SLAMM) Parking Lots Polymers