Copper and Solids Removed Via Street Sweeping 3/27/07. Kirsten Sinclair Rosselot Prepared for the Brake Pad Partnership

Similar documents
Watershed Modeling of Copper Loads to San Francisco Bay

2008 AWRA Spring Specialty Conference March 17-19, 2008

Watershed Modeling of Copper Runoff to San Francisco Bay from Brake Pad Wear Debris

Sarah Connick, Project Manager, Sustainable Conservation

Watershed Modeling of Copper Loads to San Francisco Bay

Module 4a: The Role of Street Cleaning in Stormwater Management

Urban Runoff Literature Review

Wisconsin Dept. of Natural Resources. Department of Civil and Environmental Engineering. Wisconsin Dept. of Natural Resources, Madison, WI

WATERSHED MODELING FOR THE ENVIRONMENTAL FATE AND TRANSPORT OF COPPER FROM VECHICLE BRAKE PAD WEAR DEBRIS DRAFT WORK PLAN.

Appendix B (Based on Table 4-1 of the Copper Action Plan) Summary of Urban Runoff and Watershed Management Baseline Copper Control Actions 1

Appendix B (Based on Table 4-1 of the Copper Action Plan) Summary of Urban Runoff and Watershed Management Baseline Copper Control Actions 1

Building Consensus for Focused Growth San Francisco Bay Area. Greenbelts: Local Solutions for Global Challenges Conference March 23, 2011

WinSLAMM Modeling to Define Sediment Removal Rates for Street Sweeping Scenarios in the Chesapeake Bay Watershed

WinSLAMM, the Source Loading and Management Model

The Source Loading and Management Model (SLAMM)

The Role of Street Cleaning in Stormwater Management. Robert Pitt 1, Roger Bannerman 2, and Roger Sutherland 3

WinSLAMM v 10 Theory and Practice

Table 2 Discharges for San Diego Creek

AWRA 2008 SPRING SPECIALTY CONFERENCE San Mateo, California

Brake Pad Partnership. Air Deposition Modeling of Copper from Brake Pad Wear Debris in Castro Valley Creek Watershed

Effects of Climate Change on Range Forage Production in the San Francisco Bay Area. Chaplin-Kramer and George, 2013 PLoS ONE 8(3)

Scientific Investigations Report By Robert F. Breault, Kirk P. Smith, and Jason R. Sorenson

Traction sand. Spillage- Septic waste, plastics. Metal Salts, pure metals carbonates

Executive Summary EXECUTIVE SUMMARY. ES.1 Monitoring Program Objectives. ES.2 Summary of Monitoring Results

Vehicle Service Facilities

HAUL ROAD EMISSIONS. = Annual emissions of each contaminant, (lbs/year) = Maximum hourly emissions of each contaminant, (lbs/hour)

April 2003 RTPA BACM Submittal

Developing a Framework to Advance Statewide Phosphorus Reduction Credits for Leaf Collection

Plaza and Sidewalk Cleaning

efigure 1. Annual average ambient air pollutants at representative air monitoring sites from

A Demonstration of SIMPTM s Ability to Predict Fine Sediment Discharges from Existing Urbanized Landscapes Tributary to Lake Tahoe

CHAPTER ONE a vision for tomorrow

LAURIE JOHNSON CONSULTING Progress Report: CCSF Lifelines Council Interdependency Study

Program Effectiveness Assessment and Improvement Plan for Marin, Napa, Solano, and Sonoma Counties

FOSSIL-FREE BAY AREA. A cleaner future for the region s energy. September 2016

San Francisco Bay Region

City of Sunnyvale. General Plan Structure

GreenPlan Modeling Tool User Guidance

The New Economies of the Redwood Region in the 21 st Century 1

report final Decennial Model Update Executive Summary Contra Costa Transportation Authority Cambridge Systematics, Inc.

Appendix J: The Project Stormwater Control Plan by Lea & Braze Engineering, Inc.

Construction Best Management Practices Handbook BEST MANAGEMENT PRACTICES

ANNUAL SSO REPORT FOR 2014

Stormwater Bio-Infiltration Pilot Project Concept Proposal Submitted by

Review of Potential Measures to Reduce Urban Runoff Loads of PCBs to San Francisco Bay

Regional economic development: The case of the Bay Area s Economic Prosperity Strategy

Water Pollution Control for Work in Sensitive Areas

Generating a Representative Sample of Brake Pad Wear Debris

Quality of Highway Runoff at Two Locations in Amman City: A Preliminary Investigation

APPENDIX E: TOOL FOR EVALUATING STORMWATER DATA. Section 1 Basis for Using the Charts as a Screening Tool

Beth Baldwin Watershed Management Planning Specialist Contra Costa Clean Water Program April 30, 2015

Dollar Amount. R $155, Env. Ed. Programs; 2. Alhambra Creek study

BPP Technical Studies

P8 Enhancements & Calibration to Wisconsin Sites

Chapter 5. Congestion Management Program. Chapter 5

State of the Estuary Report 2015

Storm Water Products

LAURIE JOHNSON CONSULTING CCSF Lifelines Council Interdependency Study. The Final Stretch

K. UTILITIES AND SERVICE SYSTEMS SETTING SEWER AND WASTEWATER TREATMENT PLANT CAPACITY WATER. IV. Environmental Setting, Impacts, and Mitigation

Characteristics of Firearm-related Injuries

CHAPTER C - EMPLOYMENT IMPLICATIONS OF ALTERNATIVE SYSTEMS FOR SOLID WASTE MANAGEMENT. Terrance Pang

APPENDIX J-3. Orcem Stormwater Management and Treatment Facilities Design Summary

Contents Chapter 1: Introduction Chapter 2: Identification and Description of Santa Clara Basin Watershed

Bay Area Reasonable Assurance Analysis Guidance Document

Estimating Risks in Urban Agriculture

Reissued MRP: How is it the same and how is it different

Urban Area Dry Diffuse Pollutants Washoff Composition

Bay Area Hydrology Model

BRAKE PAD PARTNERSHIP: SAN FRANCISCO BAY MODELING

Diazinon and Pesticide-Related Toxicity in Bay Area Urban Creeks

1) What is the drainage area of Chatham Hall compared to Lake James? Is the drainage area into Lake James bigger than Chatham?

Achieving a Cleaner Power Portfolio through Local Choice. Greg Brehm Director of Power Resources Marin Clean Energy May 18, 2015

Iron Mountain Mine Shasta County, California

Chapter 12 - Emerging Technologies

DRAFT PTP-06. Activity: Water Quality Units

Rock Sock (RS) Rock Sock height.

REPORT TO MAYOR AND COUNCIL

Removing Dissolved Pollutants from Stormwater Runoff. Andy Erickson, Research Fellow St. Anthony Falls Laboratory March 8, 2012

RED. California Wireless E Routing on Empirical Data. Shaving Time Saving Lives - A Success Story

REPORT TO MAYOR AND COUNCIL

Informational Webinar July 29, 2014

CONSTRUCTION AND DEMOLITION DEBRIS DISPOSAL SITE GUIDELINES

STORMWATER QUALITY DESCRIPTIONS USING THE THREE PARAMETER LOGNORMAL DISTRIBUTION.

VEHICLE PARTICULATE EMISSIONS ANALYSIS

Newport Bay Water Quality Programs and Projects

Annual Reporting for FY Regional Supplement for Pollutants of Concern and Monitoring

GUIDELINES FOR STORMWATER BACTERIA REDUCTIONS THROUGH BMP IMPLEMENTATION NY/NJ HARBOR TMDL DEVELOPMENT

Sunday, February 24, 13. Heavy Metal Toxicity

CITY OF SARATOGA ROAD MAINTENANCE FEES ANALYSIS

Re: Item 5a: Proposed Regional Means-Based Transit Fare Program Framework. Dear Chair Josefowitz and Programming and Allocations Committee Members:

Stakeholder Meeting #1

Vehicle and Equipment Cleaning

Applicability of Inlet Filters, Oil/Water Separators, and Hydrodynamic Separators

Under a Changing Climate:

Contaminant run off from impervious surfaces such as carparks and roofs

Notice of Preparation for the Copeland Creek Stormwater Detention Basin (CIP Project )

SLAMM, the Source Loading and Management Model Robert Pitt and John Voorhees

Guidance on Determining Feasibility and Sizing of Rainwater Harvesting Systems

Field Evaluation of a Stormceptor Model STC 1200 Westwood, Massachusetts. Prepared by: Stormceptor Group of Companies

U.S. 101 / San Mateo County Smart Corridor Project

Transcription:

and Solids Removed Via Street Sweeping 3/27/07 Kirsten Sinclair Rosselot Prepared for the Brake Pad Partnership The Brake Pad Partnership is conducting a study whose purpose is to gain a better understanding of the sources of elevated copper concentrations in the San Francisco Bay. The overall effort includes assessing the magnitude of copper released in the Bay area, followed by modeling of the environmental fate and transport of these estimated releases. A previous report provides estimates of copper released to roadways in brake pad wear debris (Rosselot, 2006). The copper found in street sweeper dirt is landfilled and is therefore prevented from entering storm water runoff. This report provides estimates of releases of copper and solids removed from roadways in the San Francisco Bay area watersheds via street sweeping. These estimates are intended for use in the Brake Pad Partnership's modeling effort. Most of the values used for estimating removal of copper via street sweeping were taken from a study conducted in New Bedford, Massachusetts (Breault et al, 205). This study included three field efforts: (1) measurement of street-dirt accumulation from two residential areas, after specific time intervals; (2) collection of street dirt for analysis of chemical composition; and (3) controlled measurement of street-sweeper efficiency. The authors of the study state that the most important result of this preliminary study is the similarity observed between this study s data and those collected by others from across the Nation. They note that [f]or example, average street-dirt-accumulation rates measured in this study (14 g/curb-m/d) are similar to those measured by others (9 to 15 g/curb-m/d); estimated total recoverable concentrations of arsenic (4 ppm), cadmium (0.9 ppm), chromium (261 ppm), copper (404 ppm), lead (335 ppm), nickel (31 ppm), and zinc (260 ppm) in street dirt collected in this study are for the most part similar to average concentrations of these contaminants measured by others The street-dirt-accumulation rates cited in the above paragraph are from Pitt et al, 2004, and the authors were comparing the concentrations they found to those of Sartor and Gaboury, 1984. In the study, copper concentrations were measured as either "total recoverable copper" or "total copper." The authors describe the difference in these values as follows: Total concentrations are determined by using a strong acid digestion, which dissolves the mineral matrix; therefore, total concentrations include those elements that compose the minerals in the sample. Total recoverable concentrations are determined by using a weak acid digestion, which generally does not dissolve the mineral matrix; therefore, total recoverable concentrations include only those elements that are sorbed to the surface of particles in the sample. Elements measured by means of total recoverable methods are generally considered the result of human activities and are commonly considered to be the geochemically or biologically available fraction. The above quote is included here to illustrate the authors' definitions of "total recoverable copper" and "total copper." However, the assumption made by the authors that total recoverable copper indicates copper from anthropogenic sources is questionable. This assumption is based on studies of metals/contaminants that have sorbed from an aqueous phase onto solid (natural) particulates such as soils and sediments. When the particulate materials themselves are the source of contaminants, and the contaminants are dispersed throughout the entire particle mass,

then this means of distinguishing between anthropogenic and nonanthropogenic sources is no longer valid. Based on the work that has been done with brake pad wear debris for the Brake Pad Partnership (e.g., at Clemson University, by Jim Trainor, and at Clarkson University), it is known that it takes a very rigorous digestion to get all of the brake pad wear debris copper in a dissolved form for analysis. In fact, the required digestion process for dissolving copper from brake pad wear debris is much more rigorous than what the authors of the study used for their total copper measurements. In this description of the methodology for estimating copper and solids removed via street sweeping in the San Francisco Bay area, "recoverable copper" refers to "total recoverable copper." Average street-dirt-accumulation rates measured in this study were 14 g/curb-meter/d (or 8,200 kg/curb-mile/y). These rates were measured by washing a portion of a street before and after an accumulation period and sampling the wash water. The overall average street-sweeper efficiency, determined as a particle-size-weighted average, ranged from 20 to 31 percent for the mechanical sweeper. Street sweeper efficiency is the ratio of dirt recovered to dirt accumulated, and is measured by applying a known mass of dirt to a street and measuring the amount of dirt swept by a sweeper. The recoverable copper concentration in mechanical sweeper dust was found to be 43 ppm. Measurements of both total recoverable copper and total concentrations of copper in street dirt resulted in a ratio of total recoverable copper to total copper of about 60% for most size fractions. These values, combined with information about the number of swept curb miles in Alameda County, taken from the 2000-2001 issue of "Clean Water," were used to calculate street dirt and copper removed via street sweeping for Alameda County. The number of sweeper miles in Alameda County was 266,000 curb miles for that year. Of course, nearly all of these sweeper miles were on streets that were swept more than once during the year. If it is assumed that the average swept street is swept on three out of four weeks, then there are an average of 39 sweep events per swept road per year. This means that the number of swept curb miles in Alameda County is 6,820. Note that there are no available data about the frequency with which swept roads are swept. Most swept streets are swept on a weekly basis with some swept more frequently and some swept less frequently. Street sweeping activities are suspended during rain. Thus, the assumption that the average swept street is swept on three out of four weeks is judgment-based. Street sweeper efficiency was assumed to be the midpoint of the range found in the New Bedford study for mechanical sweepers. This is equivalent to 0.25 g sweepings/g dirt. Values along with their estimated standard uncertainties are given in Table 1. Statistically based uncertainties were not available, so standard uncertainties were calculated by assuming a flat distribution across a judgment-based range of potential "true" values for each variable. The standard uncertainty for such a distribution is half the range divided by the square root of three (NIST, 2005). The formulas for calculating solids and copper removed via street sweeping in Alameda County are:

kg dirt g sweepings solids removed = 8, 200 0.25 6,820 swept curb-mi curb-mi y g dirt = 6 14 10 kg solids/y ( 6,820 swept curb-mi) ( ) kg dirt g recoverable Cu g sweepings recoverable Cu removed = 8, 200 0.000043 0.25 curb-mi y g sweepings g dirt = 600 kg Cu/y total Cu total Cu removed = ( recoverable Cu removed ) 1.7 = 1000 kg Cu/y recoverable Cu These estimates are highly uncertain. If the Kline-McClintock equation is used to calculate a standard uncertainty in the calculated result, the standard uncertainties shown in Table 1 result in a standard uncertainty for solids removed of 4 10 6. The standard uncertainty calculated for recoverable copper and total copper removed is 300 and 600, respectively. (The Kline-McClintock equation is the first term in the Taylor series approximation for the propagation of uncertainty and can be used to calculate the uncertainty in the result of a function if the variables in the function are not co-related.) The values for dirt and copper removed in Alameda County were extrapolated to the subwatersheds in the San Francisco Bay watershed based on the ratio of vehicle miles traveled in the sub-watershed to vehicle miles traveled in Alameda County, as shown in Table 2. Vehicle miles traveled are assigned to the sub-watersheds based on data that is available by county and by the population of the sub-watershed. Extrapolating by vehicle miles traveled introduces uncertainties. However, it is the most appropriate choice, partly because brake pad wear debris releases to roadways were apportioned according to vehicle miles traveled. It is recognized that for some of the less urbanized sub-watersheds, using this ratio to extrapolate from Alameda County results in an overly high estimate of copper and solids removed from roads by street sweeping. However, the overall amounts of copper removed by street sweeping relative to the copper released directly to roadways from brakes are small, and this bias is not expected to have a significant effect on the overall results. The uncertainty introduced by extrapolating according to the ratio of vehicle miles traveled was assumed to be such that the "true" extrapolation value would be between 0.5 and 1.5 of the ratio. References Alameda Countywide Clean Water Program A Consortium of Local Agencies. Clean Water. Vol. 2, No. 4. Fall 2001. Breault, RF, KP Smith, JR Sorenson. Residential Street-Dirt Accumulation Rates and Chemical Composition, and Removal Efficiencies by Mechanical-and Vacuum-Type Sweepers, New Bedford, Massachusetts, 2003 04. USGS Scientific Investigations Report 2005-5184. Available at http://pubs.usgs.gov/sir/2005/5184/pdf/sir2005_5184_all.pdf. 2005.

National Institute of Standards and Technology (NIST). http://physics.nist.gov/cuu//. Accessed on 3/22/2005. Adapted from BN Taylor and CE Kuyatt. Technical Note 1297. Guidelines for evaluating and expressing the uncertainty of NIST measurement results. Rosselot, K. released from brake lining wear in the San Francisco Bay area. Prepared for the Brake Pad Partnership. February 2006. Pitt, R.E., Williamson, D., Voorhees, J., and Clark, S., 2004, Review of historical street dust and dirt accumulation and washoff data in James, W., Irvine, K.N., McBean, E.A., and Pitt, R.E., eds., Effective modeling of urban water systems: Niagara Falls, NY, Computational Hydraulics Institute, p. 43. Sartor, J.D., and Gaboury, D.R., 1984, Street sweeping as a pollution control measure Lessons learned over the past ten years: Science of the Total Environment, v. 33, p. 171 183.

Table 1. Tabulated values for calculating solids and copper removal via street sweeping in Alameda County and their uncertainty. Parameter Value Range (Estimated) Estimated Standard 265,500-266,500 289 Sweeper miles in Alameda County, mi 266,000 Number of sweep events per swept road 39 32-46 4 Street dirt accumulation, g/curb-meter/d 14 9-19 Street dirt accumulation, kg/curb-mile/y 8,224 1,696 Sweeper efficiency (dirt removed:dirt 20%-31% accumulated) 0.25 0.03 Recoverable copper concentration in sweeper dust, mass fraction 0.000043 0.000039-0.000047 0.00002 Ratio of total copper to recoverable copper 1.7 1.5-1.9 0.1 Solids removed, 14 million 4 million Recoverable copper removed, 603 361 Total copper removed, 1,005 605

Table 2. Estimated Solids, Recoverable, and Total Removed from San Francisco Bay Area Watersheds Via Street Sweeping. Vehicle Miles Traveled Ratio (for extrapolation from Alameda County to subwatersheds) in Vehicle Miles Traveled Ratio Solids in Solids Recoverable in Recoverable Total in Total Subwatershed Alameda County 1.000 0.000 14,022,544 3,693,818 603 361 1,005 605 Upper Alameda 0.152 0.044 2,136,917 570,702 92 55 153 92 Santa Clara Valley Central 0.254 0.073 3,560,697 973,597 153 92 255 155 Castro Valley 0.024 0.007 340,161 89,637 15 9 24 15 East Bay North 0.169 0.049 2,374,969 636,299 102 61 170 103 Upper Colma 0.069 0.020 965,799 255,134 42 25 69 42 Marin South 0.102 0.029 1,426,441 378,081 61 37 102 62 Coyote 0.417 0.120 5,849,799 1,694,350 252 153 419 257 East Bay Central 0.606 0.175 8,504,648 2,689,989 366 228 609 382 East Bay South 0.128 0.037 1,801,784 479,308 77 46 129 78 Solano West 0.117 0.034 1,639,289 435,351 70 42 117 71 Napa 0.139 0.040 1,951,579 520,030 84 50 140 84 North Napa 0.017 0.005 242,732 63,952 10 6 17 10 North Sonoma 0.006 0.002 90,076 23,728 4 2 6 4 Marin North 0.065 0.019 918,247 242,506 39 24 66 40 Contra Costa Central 0.329 0.095 4,609,942 1,290,756 198 120 330 201 Petaluma 0.045 0.013 636,905 167,981 27 16 46 27 Santa Clara Valley West 0.526 0.152 7,369,328 2,240,149 317 196 528 328 Upper San Lorenzo 0.024 0.007 337,202 88,857 14 9 24 15 Contra Costa West 0.118 0.034 1,650,773 438,450 71 43 118 71 Peninsula Central 0.374 0.108 5,238,856 1,491,203 225 137 375 230 Sonoma 0.021 0.006 297,883 78,490 13 8 21 13 Upper San Francisquito 0.009 0.003 127,473 33,580 5 3 9 6 Upper Corte Madera 0.021 0.006 289,603 76,307 12 7 21 12 Total SF Bay Watershed 3.734 52,361,104 2,252 3,753