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Pollutant Load Reductions for Total Maximum Daily Loads for Highways (2013)

Chapter: Chapter Four - Matrix/Toolbox

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Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
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Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
×
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Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
×
Page 38
Page 39
Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
×
Page 39
Page 40
Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
×
Page 40
Page 41
Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
×
Page 41
Page 42
Suggested Citation:"Chapter Four - Matrix/Toolbox." National Academies of Sciences, Engineering, and Medicine. 2013. Pollutant Load Reductions for Total Maximum Daily Loads for Highways. Washington, DC: The National Academies Press. doi: 10.17226/22571.
×
Page 42

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36 Background Based on the results of the literature review as discussed in the previous chapter, a BMP matrix/toolbox was developed to provide state DOTs with easy access to TMDL-related BMP performance and cost data. The matrix/toolbox is pre- sented in Tables 20–23. Table 20 includes relative performance categories (high, medium, low, and negative) for some of the more common structural highway BMPs based on pollut- ant removal efficiencies (i.e., percent pollutant removed). This performance metric was chosen because it is ubiquitous in the literature and is accepted by many state and federal regulatory agencies. The categories are defined as follows: high = >65%, medium = 31%–65%, low = 0%–30%, and negative = <0% (i.e., the BMP is exporting the pollutant). The performance data were derived from ten different sources that are pro- vided in the table as hyperlinks where the reader may obtain more detailed information. Five life-cycle cost data sources are also provided in the table. However, cost data could not be adequately synthesized because the source reports use differ- ent methods of cost estimating and different reporting units. In addition, they do not assess the same types of BMPs. Therefore, direct comparison was not possible. For the purposes of this table, the cost sources were grouped with certain BMP types based on certain assumptions [e.g., “fil- tering practices (sand) above and below ground” from King and Hagan (2011) is equivalent to Austin and Delaware sand filters from Caltrans (2004)]. This was necessary because BMP naming conventions are not standardized nationwide. BMP definitions are generally provided in the source reports; however, they may not be consistent or grouped in a similar fashion. In addition to the hyperlinks, the full web addresses for all of the sources used in Table 20 is provided in the References at the end of this report. The second table in the BMP matrix/toolbox (Table 21) is a companion to Table 20; it provides definitions of the BMPs listed in Table 20. Sources were specifically chosen from the same state as the sources in Table 20 to avoid mixing naming conventions and definitions from different states as discussed earlier. Tables 22 and 23 are repeated from earlier sections in this report: Table 22 is the same as Table 9 in International Stormwater BMP Database in chap- ter three and Table 23 is the same as Table 10 in Nonstructural Best Management Practice Performance in chapter three. They are repeated here to present all the information in one place for easier viewing and accessibility for the reader. Table 22 presents more detailed quantitative performance data (beyond low, medium, and high categories) from the International Stormwater BMP Database, including influent/ effluent concentrations and summary statistics. Note, how- ever, that these data are not necessarily all from highway applications, although several DOTs contribute data to the database. Table 23 provides quantitative performance data for nonstructural BMPs to the extent that data were available in the literature. In general, the BMP matrix/toolbox focuses on the more prevalent TMDL pollutants of concern (TSS, nutrients, fecal coliform, total metals) based on our impres- sion of the most pressing needs of the DOTs. Many other TMDL pollutants of concern exist (e.g., biological integrity, PCBs, polycyclic aromatic hydrocarbons, pesticides; see Table 1); however, little to no information was found on the ability of highway BMPs to address these pollutants. The intention of the report is to provide a user-friendly compendium of information with both qualitative and quan- titative data on structural and nonstructural highway BMPs. The matrix is considered to be reasonably comprehensive in that it derives information from 13 unique sources (10 for performance and 5 for costs, with 2 sources overlapping). Although some details have been omitted for clarity, the inter- ested reader is encouraged to access the complete reports by means of hyperlinks. Additional information is available in several places: (1) the earlier sections of this report (see Institutional Practices for Total Maximum Daily Load Imple- mentation and Total Maximum Daily Load Implementation Plans in chapter three for nonstructural practices, and Lit- erature Review on Highway Best Management Practices Performance Studies in chapter three for structural BMPs); (2) the References section at the end of this report, which includes almost 70 sources; and (3) the state DOT interview summaries in Appendix B. Finally, the reader is referred to an ongoing NCHRP study (25-40) entitled, “Long-Term Performance and Life-Cycle Costs of Stormwater Best Management Practices.” TIMELInE oF ToTaL MaXIMuM daILY Load and naTIonaL PoLLuTanT dIScHargE ELIMInaTIon SYSTEM PErMIT dEVELoPMEnT ProcESS In addition to the BMP matrix/toolbox, an idealized timeline is also presented summarizing actions by states or the EPA and DOTs during the TMDL and NPDES permit develop- ment process. The timeline is not specific to any state, but rather is intended as a generic sequence of events that could apply anywhere. The objective of the timeline is to show how chapter four MaTrIX/TooLBoX

37 Common Structural BMPs Used by DOTs Life-Cycle Cost Sources TSS TN TP Fecal Coliform Total Zn Total Cu Total Pb Performance Source(s) Infiltration Basina [1], [8], [9], [10]b Highc — High High High — — [2]b EDB lined [1], [10] Medium Low Low — Medium Low Low [1] EDB unlined [1], [10] High Low Medium — Medium–High Medium High [1] Infiltration Trench [1], [5], [8], [10] High — High High High — — [2] Biofiltration Strip [1], [9] High Low Negative — High Medium Medium [1] Biofiltration Swale [1], [5], [9] Medium Low Negative — High Medium High [1] Austin Sand Filter [1], [5], [8], [10] High Medium Medium Medium Medium–High Medium High [1], [2] Delaware Sand Filter [1], [5], [8], [10] High Low Low–Medium High High High High [1], [2] Wet Basin [1], [5], [8], [10] High Medium Negative–Low High High High High [1], [2] Vegetated Buffer Strips — Medium–High Negative Negative–Medium Variable High — — [2] Dry Detention Pond [5], [9] , [10] Variable Low–Medium Low–Medium — Variable — Variable [3], [4] Vegetated Swales [8], [10] Low–Medium — Low Low High — — [2] Bioretention [8], [9], [10] High — High — — — — [5] Constructed Wetland [5], [8], [9], [10] High Low–Medium Medium–High — Medium Medium High [5], [6], [7] Permeable Friction Course — High — — — High Medium High [11], [12] Media Filter Drain/Ecology Embankment — High Medium — High High — [13] Performance and life-cycle cost data sources are provided as hyperlinks (hit Control + Left Click). aDefinitions of BMPs are provided in Table 21. bSources: [1] = Caltrans (2004): http://www.dot.ca.gov/hq/oppd/stormwtr/Studies/BMP-Retro-fit-Report.pdf; [2] = Hon et al. (2003): http://www.utexas.edu/research/ctr/pdf_reports/0_4252_1.pdf; [3] = Keblin et al. (1998): http://ntl.bts.gov/lib/24000/24700/24753/2954_1.pdf; [4] = Oregon State University et al. (2006): http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_565.pdf; [5] = MnDOT (2005): http://www.lrrb.org/pdf/ 200523.pdf; [6] = Farrell and Scheckenberger (2003): http://www.cawq.ca/cgi-bin/journal/pdf_view.cgi?language=english&article=84; [7] = Yu et al. (n.d.): http://www.northinlet.sc.edu/training/media/resources/ Constructed%20Wetlands%20SW%20Mgmt.pdf and http://www.northinlet.sc.edu/training/media/resources/Constructed%20Wetlands%20SW%20Mgmt.pdf; [8] = Arika et al. 2006: http://www.lrrb.org/pdf/ 200549A.pdf; [9] = URS Corporation (2010): Transportation Oversight Committee, prepared for North Carolina Department of Transportation, July 2010 [Online]. Available: https://connect.ncdot.gov/resources/ hydro/Stormwater%20Resources/Stormwater%20Runoff%20from%20Bridges%20-%20May%202012.pdf; [10] = King and Hagan (2011): http://www.mde.state.md.us/programs/Water/TMDL/TMDLImplementation/ Documents/King_Hagan_Stormwater%20Cost%20Report%20to%20MDE_Final%20Draft_12Oct2011.pdf; [11] = Barrett (n.d.): http://www.rmc-foundation.org/images/PCRC%20Files/Hydrological%20&%20 Environmental%20Design/Stormwater%20Quality%20Benefits%20of%20a%20Permeable%20Friction%20Course.PDF [12] = Eck et al. (2012): http://ascelibrary.org/action/showAbstract?page=174&volume=138& issue=2&journalCode=joeedu; [13] = WSDOT (2006): http://www.wsdot.wa.gov/NR/rdonlyres/3D73CD62-6F99-45DD-B004-D7B7B4796C2E/0/EcologyEmbankmentTEER.pdf. Control + Left Click on hyperlinks to access report. cRemoval efficiencies are defined as follows: High = >65%, Medium = 31%–65%, Low = 0%–30%, Negative = <0% (i.e., net export of pollutant). TABLE 20 RELATIVE PERFORMANCE CATEGORIES (high, medium, low, and negative; see footnote c for definitions) OF SOME COMMON STRUCTURAL HIGHWAY BMPs BASED ON PERCENT REMOVAL EFFICIENCY

38 BMP Type Definition Source Infiltration Basin An infiltration basin is a depression used to detain stormwater for short periods until it percolates to the groundwater table. It functions as a BMP through filtration of runoff and adsorption of pollutants using site vegetation and soils. Caltrans (2010b) Extended Detention Basin An extended detention basin is an empoundment lined with either vegetated soil or concrete. Stormwater runoff is conveyed from freeways to these basins through the storm drain system. Stormwater collects in the basins and the outlet allows water to drain slowly, while sediment and other particulate forms of pollutants settle out. Caltrans (2007) Infiltration Trench An infiltration trench is typically a long and narrow excavation that is lined with filter fabric and backfilled with stone aggregate or gravel to form an underground basin. Runoff is diverted to the trench and infiltrates into the soil. Caltrans (2010a) Biofiltration Strip Biofiltration strips are relatively flat, vegetated areas that accept stormwater runoff as sheet flow. Caltrans (2010a) Biofiltration Swale Biofiltration swales are vegetated conveyance channels that concentrate flow. Caltrans (2010a) Austin Sand Filter The Austin Sand Filter includes a sedimentation basin and a filtration basin. The sedimentation basin captures and detains the design water quality runoff volume (typically for 24 h) prior to discharge to the filtration basin. The sedimentation basin removes floatable debris and coarse suspended solids, and prevents premature clogging of the filter media surface. The sedimentation chamber effluent discharges to the filtration basin typically through a perforated riser. In the filtration basin, the water first passes through a sand layer, then through a geotextile layer, and finally into a gravel underdrain. Caltrans (2010a) Delaware Sand Filter The Delaware unit consists of separate sedimentation and filter chambers, but differs from the Austin design in that a permanent pool is maintained in the sedimentation chamber. Ideally, runoff enters the sedimentation chamber as sheet flow. As runoff enters the chamber, water remaining in the device from previous storms is displaced and flows over a weir into the sand filter chamber. Hon et al. (2003) Wet Basin A wet basin holds a permanent pool of water designed to detain and treat a runoff water quality volume. The basin supports plant species that provide constituent removal by biological processes. In addition, the vegetation may help reduce erosion of the side slopes and trap sediments. Sedimentation processes also occur in the basin. Wet basins are usually deep enough to prevent resuspension of particles, and should be sited where a permanent pool of water can be maintained from a dry weather flow source. Caltrans (2010a) TABLE 21 DEFINITIONS OF STRUCTURAL BMPs USED IN TABLE 20 (continued on next page)

39 BMP Type Definition Source Vegetated buffer strip Vegetated buffer strips differ from vegetated swales (see below) in that runoff occurs as sheet flow rather than being conveyed as concentrated flow in a channel. Vegetated buffer strips usually are densely vegetated and have a uniformed slope. Hon et al. (2003) Dry Detention Pond The primary purpose of a dry detention pond is to control the peak flow associated with the runoff from a watershed. Reduction in the rate of flow can limit the frequency of occurrence of erosion, thereby reducing the sediment load to the receiving waters. The secondary purpose of the pond is to temporarily store runoff to allow the removal of particulate material by settling. Keblin et al. (1998) Vegetated Swale Biofiltration swales or vegetated swales are broad, shallow channels that are lined with dense vegetation on the side slopes and channel bottom to aid in pollutant removal. Swales are designed to convey storm water with an appropriate amount of detention time to allow for pollutants to be trapped, promote infiltration, and also reduce the velocity of the flow. Hon et al. (2003) Bioretention Bioretention systems are essentially landscaped depressions to which stormwater runoff is diverted and stored. Once in the depression, the landscaped trees, shrubs, and other vegetation help to remove the water through uptake, while the runoff infiltrates into the soil below. The underlying soil may consist of the original soil or it may be nonnative soil such as sand that is installed during construction. Also, depending on the permeability of the underlying soil, a bioretention system may include a perforated underdrain that collects and removes infiltrated water. MnDOT (2005) Constructed Wetland Constructed wetland systems are similar to retention and detention systems, except that a major portion of the water surface area contains wetland vegetation. MnDOT (2005) Permeable Friction Course Roadway material 25–50 mm thick applied over regular impermeable pavement Barrett (n.d.) Media Filter Drain/Ecology Embankment Linear flow-through treatment devices designed for highway side- slopes, medians, borrow ditches, or other linear depressions in areas of limited right-of-way. WSDOT (2006) TABLE 21 (continued) DOTs can respond to specific actions by states/EPA during the process to help them develop an effective TMDL imple- mentation program. From the state/EPA side, the timeline begins with the inclusion of the water body on the 303(d) list of impaired waters and the development of the draft and final TMDL, and continues with proposing an NPDES permit with TMDL-related requirements and then finalizing the NPDES permit. On the DOT side, the actions highlight the need to sub- mit data and engage with the regulatory agency early on in the TMDL development process (before the TMDL modeling pro- cess). An additional DOT action is to review and comment on the draft TMDL and NPDES permit in order to negotiate a position that is favorable to the DOT, especially as related to TMDL requirements. The overall process is summarized in a timeline graphic in Figure 9. There are some excellent examples of DOTs that follow this general approach. For example, NCDOT collaborates with the regulatory agency early on in the TMDL develop- ment process (typically providing data, expertise, and some- times funding) to ensure the process is based on the best available science. This has translated into tangible benefits for the DOT, including the ability to help define its WLA and form a reasonable TMDL implementation strategy, and a recognition and understanding by the state that highway environments are unique entities that require a unique TS4 permit. Another example is WSDOT, which negotiates with its regulatory agency to develop reasonable “action items” to address TMDL requirements in their NPDES permit; these action items are developed by a single full-time equivalent working with the regulatory agency.

40 BMP Type Median (95% Conf. Interval)* Median (95% Conf. Interval)* Median (95% Conf. Interval)* Median (95% Conf. Interval)* Median (95% Conf. Interval)* Median (95% Conf. Interval)* Median (95% Conf. Interval)* TSS In mg/L TSS Out mg/L TN In mg/L TN Out mg/L TP In mg/L TP Out mg/L FC In # / 100 mL FC Out # / 100 mL TZn In ug/L TZn Out ug/L TCu In ug/L TCu Out ug/L TPb In ug/L TPb Out ug/L Grass Strip 43.1 (36.0, 45.0) 19.1 (16.0, 21.5) 1.34 (1.06, 1.50) 1.13 (1.00, 1.23) 0.14 (0.11, 0.15) 0.18 (0.15, 0.20) NA NA 103.3 (86.0, 120.0) 24.3 (16.0, 26.0) 24.52 (19, 26) 7.30 (6.4, 7.9) 8.83 (6.6, 11.5) 1.96 (1.30, 2.20) Bioretention 37.5 (29.2, 45.0) 8.3 (5.0, 9.0) 1.25 (1.06, 1.35) 0.90 (0.74, 0.99) 0.11 (0.08, 0.12) 0.09 (0.07, 0.10) NA NA 73.8 (62.0, 83.5) 18.3 (7.7, 25.0) 17.0 (11.0, 23.0) 7.67 (4.60, 9.85) 3.76 (2.49, 5.5) 2.53 (2.50, 2.50) Bioswale 21.7 (16.2, 26.0) 13.6 (11.8, 15.3) 0.75 (0.60, 0.92) 0.71 (0.63, 0.82) 0.11 (0.09, 0.12) 0.19 (0.17, 0.20) 4720 (2120, 5500) 5000 (2600, 6200) 36.2 (30.0, 40.0) 22.9 (20.0, 26.6) 10.86 (8.70, 13.20) 6.54 (5.7, 7.7) 3.93 (2.80, 5.00) 2.02 (1.80, 2.29) Detention Basin 66.8 (52.3, 76.1) 24.2 (19.0, 26.0) 1.40 (1.03, 1.57) 2.37 (1.75, 2.69) 0.28 (0.25, 0.30) 0.22 (0.19, 0.24) 1480 (789, 1900) 1030 (500, 1900) 70.0 (40.0, 95.0) 29.7 (17.1, 38.2) 10.62 (7.78, 14.00) 5.67 (4.0, 6.8) 6.08 (3.86, 8.0) 3.10 (2.15, 4.30) Manufactured Device 34.5 (30.0, 36.8) 18.4 (15.0, 19.9) 2.27 (1.98, 2.65) 2.22 (1.90, 2.41) 0.19 (0.16, 0.22) 0.12 (0.10, 0.13) NA NA 87.7 (79.0, 95.0) 58.5 (52.8, 63.5) 13.42 (11.90, 14.70) 10.16 (7.94, 11.0) 8.24 (6.77, 9.56) 4.63 (3.80, 5.16) Manufactured Device-F** NA NA NA NA NA NA 478 (200, 1300) 1890 (200, 3000) NA NA NA NA NA NA Manufactured Device-P** NA NA NA NA NA NA 2210 (900, 3000) 2750 (1400, 5000) NA NA NA NA NA NA Media Filter 52.7 (45.9, 58.2) 8.7 (7.4, 10.0) 1.06 (0.85, 1.25) 0.82 (0.68, 0.99) 0.18 (0.16, 0.19) 0.09 (0.08, 0.10) 1350 (725, 2300) 542 (200, 625) 77.3 (68.2, 86.0) 17.9 (15.0, 20.0) 11.28 (10.0, 12.68) 6.01 (5.1, 6.6) 10.5 (8.02, 11.79) 1.69 (1.30, 2.00) Porous Pavement 65.3 (45.0, 80.3) 13.2 (11.0, 14.4) NA NA 0.15 (0.12, 0.16) 0.09 (0.08, 0.09) NA NA 57.6 (49.6, 66.0) 15.0 (12.5, 16.8) 13.07 (11.45, 15.3) 7.83 (6.80, 8.10) 4.30 (3.28, 5.47) 1.86 (1.38, 2.21) Retention Pond 70.7 (59.0, 79.0) 13.5 (12.0, 15.0) 1.83 (1.60, 1.98) 1.28 (1.19, 1.36) 0.30 (0.27, 0.31) 0.13 (0.12, 0.14) 1920 (970, 2650) 707 (200, 1160) 53.6 (49.0, 59.0) 21.2 (20.0, 23.0) 9.57 (8.0, 10.0) 4.99 (4.06, 5.0) 8.48 (6.80, 9.41) 2.76 (2.00, 3.00) Wetland Basin 20.4 (16.6, 24.4) 9.06 (7.0, 10.9) 1.14 (1.04, 1.28) 1.19 (1.04, 1.21) 0.13 (0.11, 0.14) 0.08 (0.07, 0.09) 13000 (5080, 21000) 6140 (230, 11800) 48.0 (40.6, 53.2) 22.0 (16.7, 24.3) 5.61 (4.36, 6.34) 3.57 (3.00, 4.00) 2.03 (1.57, 2.24) 1.21 (1.00, 1.55) Wetland Channel 20.0 (17.0, 22.0) 14.3 (10.0, 16.0) 1.59 (1.38, 1.78) 1.33 (1.05, 1.56) 0.15 (0.13, 0.17) 0.14 (0.13, 0.17) NA NA 23.0 (16.0, 30.0) 15.6 (11.0, 20.0) 4.52 (3.80, 5.10) 4.81 (3.61, 5.2) 2.94 (1.90, 4.20) 2.49 (1.40, 3.11) *Computed using the BCa bootstrap method described by Efron and Tibishirani (1993) **For bacteria, manufactured devices are broken down into inlet insert/filtration (Manufactured Device – F) and physical settling/straining devices (Manufactured Device – P). NA = Limited or no data available. <values> Hypothesis testing shows statistically significant decrease in median concentration for this BMP type. <Values> Hypothesis testing shows statistically significant increase in median concentration for this bmp type. Data are from the international stormwater bmp database (www.bmpdatabase.org). TABLE 22 INFLUENT/EFFLUENT SUMMARY STATISTICS FOR TOTAL SUSPENDED SOLIDS (TSS), TOTAL NITROGEN (TN), TOTAL PHOSPHORUS (TP), FECAL COLIFORM (FC), TOTAL ZINC (TZN), TOTAL COPPER (TCU), AND TOTAL LEAD (TPB) AS ADAPTED FROM GEOSYNTEC CONSULTANTS AND WRIGHT WATER ENGINEERS (2012)

41 BMP/Study TSS Nutrients (phosphorus, nitrogen) Metals (copper, lead, zinc) Street Sweeping Performance modeled with sweeping frequency from twice weekly to biweekly (HECI 2006) 45 to 70% reduction in annual loads 35 to 60% reduction in phosphorus annual loads 25 to 60% reduction in annual loads Spreadsheet model assuming sweeping frequency of 6 to 12 times per year (HECI 2006) 25 to 35 lb removed per lane mile per year <0.1 lb phosphorus removed per lane mile per year <0.1 lb removed per lane mile per year Catch Basin Cleaning Spreadsheet model with cleaning frequency from every 3 months to once in 5 years (HECI 2006) 0 to 45% reduction in annual loads Alameda County study with cleaning frequencies from monthly to annual (HECI 2006) 8 to 70 lb removed per cleanout; generally a decline in removal per cleanout with higher frequency Spreadsheet model with frequency ranging from every 4 days to every 40 days (HECI 2006) 35 lb removed per cleanout; constant regardless of frequency 0.00003 lb phosphorus removal per catch basin per cleaning 0.0000012 to 0.0000064 lb removal per catch basin per cleaning MD NPDES Accounting Protocol (specifics on pollutants not given) (MDSHA 2012) 2000 lb removed by cleaning is equivalent to 0.4 impervious acres of structural BMP treatment Tree Planting Reforestation (NVPDC 1996) Nonpoint source runoff concentrations for phosphorus reduced from 0.205 to 0.15 mg/L and for nitrogen reduced from 0.139 to 0.078 mg/L as examples MD NPDES Accounting Protocol (specifics on pollutants not given) (MDSHA 2012) 1 acre of planting is equivalent to 0.38 impervious acres of structural BMP treatment Stream Restoration Site-specific evaluation (CCBWQA 2011) 90–220 lb phosphorus immobilized per mile per year MD NPDES Accounting Protocol (specifics on pollutants not given) (MDSHA 2012) 100 linear feet of restoration is equivalent to 1 impervious acre of structural BMP treatment TABLE 23 NON-STRUCTURAL BMP PERFORMANCE MEASURES

42 1From EPA (2009). 2Example from Chesapeake Bay TMDL implementation plan, but varies from state to state. FIGURE 9 Idealized timeline of TMDL and NPDES permit development process. DOT actions are shown on the top of the arrow and state/EPA actions are shown on the bottom.

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TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis 444, Pollutant Load Reductions for Total Maximum Daily Loads for Highways presents information on the types of structural and non-structural best management practices currently being used by state departments of transportation, including performance and cost data.

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