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«Deriving Reliable Pollutant Removal Rates for Municipal Street Sweeping and Storm Drain Cleanout Programs in the Chesapeake Bay Basin A report ...»

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CENTER FOR WATERSHED PROTECTION

Deriving Reliable Pollutant Removal Rates for Municipal

Street Sweeping and Storm Drain Cleanout Programs in

the Chesapeake Bay Basin

A report prepared by the Center for Watershed Protection as fulfillment of the U.S. EPA

Chesapeake Bay Program grant CB-973222-01

Neely L. Law

Center for Watershed Protection

Katie DiBlasi and Upal Ghosh

University of Maryland Baltimore County

Department of Civil and Environmental Engineering

With contributions from:

Bill Stack City of Baltimore Department of Public Works Water Quality Management Division Steve Stewart Baltimore County Department of Environmental Protection and Resource Management Ken Belt and Rich Pouyat U.S. Forest Service Northern Research Station as part of the Baltimore Ecosystem Study Clair Welty University of Maryland Baltimore College Center for Urban and Environmental Research and Education September 2008 Acknowledgements The report is supported by the U.S. EPA Chesapeake Bay Program grant CB-973222-01 and the dedicated support from research project team partners through contributed staff services, laboratory analysis and monitoring equipment. The grant supported the graduate research for Katie DiBlasi supervised by Dr. Upal Ghosh at the University of Maryland Baltimore County (UMBC), Department of Civil and Environmental Engineering. Katie DiBlasi steadfastly (and not without amusement) vacuumed the streets of Baltimore as part of her Masters thesis. Katie’s competence and resourcefulness with assistance from Yan Zhuang at UMBC, provided a comprehensive analysis of the monitoring data.

Baltimore City Department of Public Works provided overall coordination of the street sweeping and storm drain cleanout practices and sample collection for monitoring activities in the City. Special thanks to Bill Stack, Prakash Mistry, Norm Seldom, Matthew Cherigo and James Spencer and the Baltimiore City street sweeper crews. The Ken Belt and Richard Pouyat from the U.S. Forest Service Northern Research Station as part of the Baltimore Ecosystem Study provided essential resources to include staff and equipment for sample collection and data analysis as part of a larger monitoring effort in Watershed 263. Steven Stewart and Megan Brosh from the Baltimore County Department of Environmental and Resource Management planned, coordinated andimplemented the storm drain inlet monitoring element of the project. Chemical analysis was provided by John Burnett at the Baltimore County Department of Public Works. Claire Welty, Director of the Center for Urban and Environmental Research and Education at UMBC for her overall guidance and thoughtful contributions to the project. Of course, there wouldn’t be an end without a beginning and for that I am greatly appreciative of Tom Schueler who got this project off the ground at the Center for Watershed Protection.

Project Team

The Center for Watershed Protection (CWP) coordinated the research project team, which included the City of Baltimore Department of Public Works (DPW), Baltimore County Department of Environmental Protection and Resource Management (DEPRM), and the Department of Civil and Environmental Engineering at the University of Maryland-Baltimore County (UMBC). Other partners on the project team include the Center for Urban Environmental Research and Education (CUERE) at UMBC and the U.S. Forest Service Northern Research Station (FS-NRS) as part of the Baltimore Ecosystem Study (BES).

Executive Summary The research project report provides information to support pollutant removal efficiencies for street sweeping and storm drain cleanout practices for Phase I and II communities in the Chesapeake Bay watershed. Information and data was gathered for this project through a comprehensive literature review, a basin-wide municipal survey of existing street sweeping and storm drain cleanout practices, and an intensive field monitoring program within two study catchments located in Watershed 263 in Baltimore, MD and additional sites in Baltimore County.

Street sweeping and storm drain cleanout practices rank among the oldest practices used by communities for a variety of purposes to provide a clean and healthy environment, and more recently to comply with National Pollutant Discharge Elimination System stormwater permits. The ability for these practices to achieve pollutant reductions is uncertain given current research findings. Only a few street sweeping studies provide sufficient data to statistically determine the impact of street sweeping and storm drain cleanouts on water quality and to quantify their improvements. The ability to quantify pollutant loading reductions from street sweeping is challenging given the range and variability of factors that impact its performance, such as the street sweeping technology, frequency and conditions of operation in addition to catchment characteristics. Fewer studies are available to evaluate the pollutant reduction capabilities due to storm drain inlet or catch basin cleanouts.

A multi-faceted monitoring study was completed to provide locally-derived pollutant removal reductions for street sweeping and storm drain cleanout practices. The monitoring program including water quality and flow, bedload, first flush, precipitation, source area street particulate matter, and storm drain inlet accumulation and chemical characterization. A ‘before-and after’ study design was used based on the inability to find a suitable control catchment to implement a paired watershed study design. An insufficient number of samples were collected given the conditions experienced during the study period to statistically detect differences in the street sweeping treatment on water quality. Monitoring efforts, however, did reveal key findings to determine factors contributing to the effectiveness of street sweeping and storm drain cleanout practices such as the particle size distribution of the street particulate matter picked-up by sweeping and its chemical composition, along with the significance of leaf litter and other organic material in storm drains and its contributions to pollutant loadings.





To synthesize the diverse research findings from this and other studies, a conceptual model was developed to provide pollutant removal efficiencies for TS, TN and TP for street sweeping and storm drain cleanout practices. The conceptual model is defined by a set of bounding conditions and assumptions that were made based on the literature, survey findings and monitoring data collected as part of the project.

i For a given set of assumptions and sweeping frequencies, it is expected that the range in pollutant removal rates from street sweeping for total solids (TS), total phosphorus (TP) and total nitrogen (TN) are: 9 – 31%, 3-8% and 3-7%, respectively. The lower end represents monthly street sweeping by a mechanical street sweeper, while the upper end characterizes the pollutant removal efficiencies using regenerative air/vacuum street sweeper at weekly frequencies.

–  –  –

The conceptual model is also applied to estimate the efficiency with which storm drain inlets trap, or store material to reduce the total pollutant loading at the receiving waters.

Data generated from this study and others find that the particle size distribution in storm drains is similar to the street particulate matter and organic material comprised a large fraction of the accumulated material. For a given set of assumptions and cleanout frequencies, it is expected that the range in pollutant removal efficiencies for TS, TP and TN estimated to range from 18-35%, less than 1-2% and 3-6%, respectively.

–  –  –

The compilation and analysis of the data collection from this and other research studies provided valuable information to evaluate the effectiveness of these municipal practices.

As a result, the following recommendations are made with respect to street sweeping and storm drain cleanout practices to reduce pollutant loadings to the Chesapeake Bay

watershed:

Programmatic

• Adopt the pollutant removal efficiencies presented herein for mechanical and regenerative air or vacuum assist street sweepers used at weekly and monthly frequencies. Based on the municipal practices survey, few communities with the Chesapeake Bay use the more efficient street sweeping technologies or sweep at frequencies to achieve the pollutant removal efficiencies presented in this report.

• Develop street sweeping and storm drain maintenance program efforts to target areas and times during the year in communities that may receive the greatest impact from street sweeping or storm drain cleanouts.

• Implement a downspout disconnection program and/or an urban stormwater retrofit program that redirects and treats stormwater before it reaches the storm drainage system (via parking lots, roads, sidewalks, alleyways) in ultra-urban catchments, such as those in this study.

ii

• Expand MS4 stormwater programs to include a curb-side leaf litter pick-up program that is able to maximize the reduction of leaf litter and prevent it from entering the storm drain. This is important for two reasons, 1) street sweepers avoid leaf piles and this reduces the effectiveness of this practice (sweepers may also emulsify leafy debris and make it more easily entrained by runoff, and 2) the decomposition of leaves and other organic debris in storm drain inlets or catch basins can create an environment suitable for the release of inorganic nitrogen and transport to receiving waters.

Research

• Conduct additional research on the implications of storm drain cleanout practices to include catch basins and chemical analysis of particle size distributions to estimate the pollutant load reductions from the different particle size classes

• Further evaluate stormwater monitoring techniques that can be used to account for the ‘missing load’ that occurs when using current sampling techniques to reduce potential bias in reported pollutant removal efficiencies.

• Research and develop alternative sampling techniques that can be used to collect more representative stormflow throughout the depth of flow and storm event.

• Adopt whole water sampling as a method to measure sediment in stormwater as an initial step to reduce the bias.

• Quantify bedload contributions to the total stormwater pollutant load. Although it may comprise a small portion of total stormwater load it can have a much larger impact due to the chemical characteristics of the material.

–  –  –

Introduction The report is organized into six major sections, which are summarized below.

1. Project Overview and Background – This section provides an overview of the project purpose and scope. Key findings from the literature review and municipal practices survey are summarized. A description of the conceptual model is presented that is used to estimate pollutant removal efficiencies for street sweeping and storm drain cleanout practices presented in section 5.0.

2. Study Area – A description of the study area in Baltimore City for the monitoring component of the project is presented.

3. Study Design and Sampling Methods – This section presents a description of the study design used to evaluate the effectiveness of street sweeping and storm drain cleanout practices. The sampling methods are described for monitoring water quality and flow, bedload, first flush, precipitation, source area street particulate matter, and storm drain inlet accumulation and chemical characterization.

4. Monitoring Results and Analysis – This section summarizes the data generated on all monitoring components and presents statistical and observational findings of that data. Results between the pretreatment and treatment period are presented along with the particle size and chemical characterization of street particulate matter and material sampled from storm drain inlets. Loading rates (or yields) of street particulate matter are presented.

5. The Impacts of Street Sweeping and Storm Drain Cleanout Practices on Stormwater Quality – This section is presented in two major sections that describe the pollutant loading reductions from street sweeping and storm drain cleanout practices and the caveats and issues associated with these values. The conceptual model is applied to estimate pollutant removal efficiencies for these practices.

6. Conclusions and Recommendations – Summary concluding remarks on the project findings are provided with a set of nine key recommendations on the future applications of the research project results.

1.0 Project Overview and Background Street sweeping and storm drain cleanouts rank among the oldest practices used to control storm water pollution; however, very limited and sometimes conflicting data has been published in regard to their performance in removing nutrients and other pollutants from stormwater runoff (Selbig and Bannerman 2007, Breault et al. 2005, Burton and Pitt, 2002, Mineart and Singh, 1994, Sutherland and Jelen, 1997). Despite this uncertainty, many Chesapeake Bay municipalities routinely use one or both practices to comply with their National Pollutant Discharge Elimination System (NPDES) storm water permits. Source control of pollutant loadings from streets can be an important component to a Municipal Separate Storm Sewer System (MS4) stormwater program to achieve needed pollutant reductions. Street sweeping and storm drain cleanouts may be of particular value in reducing pollutants from ultra-urban areas, where few other best management practices (BMPs) are feasible.

The Urban Storm Water Work Group (USWG) of the Chesapeake Bay Program has recognized the importance of defining more accurate pollutant removal efficiencies for street sweeping and storm drain cleanout practices as a top priority for its BMP tracking system. Currently, the Chesapeake Bay Watershed model does not define any removal efficiencies for these practices.

The purpose of this research project is to provide information to gain a better understanding of the impact street sweeping and storm drain cleanouts have on reducing

pollutant loadings to surface water. The objectives of the project are to:



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