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An Economic Analysis of
        Costs of
   Bioretention Cells
          and
   Stormwater Ponds
               By
          Ritu Sharma
       Clemson University
                     Background Information
   Urban stormwater runoff, a leading contributor to
    degradation of water-quality in estuaries, lakes, rivers,
    and bays was the most important source of impairment
    of waters along assessed ocean shoreline in the U.S. in
    the year 2000 (EPA 2002a).

   The U. S. Environmental Protection Agency (EPA)
    promulgated in Nov. 1990, Phase I (1987 amendment of
    the Clean Water Act ) of a comprehensive national
    program to address storm water discharges, which
    required:
       Construction sites disturbing more than 5 acres of land
       Facilities engaging in 10 other types of industrial activity and
       Municipal separate storm sewer systems (MS4) that serve at
        least 100,000 people in urban areas
    to obtain coverage under NPDES permit for discharge of
    stormwater runoff (EPA 1999b; EPA 1996).
   Phase II implemented in Dec 1999 extended the
    requirement of NPDES permits for:
       Construction sites disturbing 1 to 5 acres of land and

       MS4 operators serving less than 100,000 people (EPA 1999b).


   The NPDES permits requires regulated dischargers to
    implement SWPPP to reduce pollutants in runoff through
    a combination of structural and non-structural Best
    Management Practices (BMPs) (e.g., EPA 1999b).

   In SC, operators of construction sites that disturb at
    least five acres of land must install structural BMPs
    during construction, that remove at least 80% of the
    average annual load of pollutants in storm water
    discharges that will occur after construction has finished
    (Sadler).
   According to the standard for stormwater runoff set by
    the Stormwater Management and Sediment Reduction
    Act of 1991 in SC, “post-development peak discharge
    rates shall not exceed pre-development discharge rates
    for the 2- and 10-year frequency 24-hour-duration storm
    event” (SCDHEC, 2003b).

   Implementation of these federal and state regulations
    require the use of BMPs, which are of two types:
       Non-Structural BMP: consists of administrative, regulatory or
        management practices that have positive impacts on non-point
        source runoff (EPA, 2000b)

       Structural BMP: are designed facilities or modified natural
        environments that help clean the stormwater-quality. These
        include, among others, bioretention cells and various types of
        stormwater ponds, such as dry extended detention ponds and
        wet ponds (SMRC).
   Bioretention cells are:
       Specially designed landscaping area adapted to treat stormwater
        runoff.
       Most commonly found along the edges or medians of parking
        lots and residential streets.
       Usually built into and under landscapes that serve other
        purposes, such as beautification and shade.


   Stormwater ponds are:
       Basins whose outlets are designed to detain stormwater runoff
        from a storm for some minimum duration allowing sediments
        and associated particles to settle out.
       Require surface area that typically becomes unavailable for other
        uses.
   To see which BMP is most suitable in a given area,
    estimate of the cost of designing, installing and
    maintaining BMPs and the amounts of pollutant that they
    can remove should be analyzed.

   Earlier studies done in this field include:
       Report submitted to Chesapeake Research Consortium by Brown
        and Schueler (1997), examining the relationship between
        storage volume and construction costs of the BMPs.

       Estimated models of capital and maintenance costs of the most
        frequently used BMPs by Koustas and Selvakumar (2003).

       Analyzing construction and annual operating costs of various
        BMPs and selecting the most effective BMP for the removal of a
        class of pollutants and its associated cost, by Wossink and Hunt
        (2003).
   Additions to previous research made in this paper are:
       Costs of bioretention cells and stormwater ponds are adjusted
        for purchasing-power differences in time and space.

       The addition of the effects on real costs of factors other than
        water-quality or water-quantity volume like:
            the cost of land is counted as a cost of a stormwater pond because
             the surface area of a pond is no longer available for another land
             use.
            the effects of three additional input prices--engineering,
             construction, and landscape wages--on the combined design and
             construction costs of the two BMPs are estimated.

       A comparative study of the volume-to-cost relationship for the
        two BMPs, determining the storage volume below which a
        bioretention cell is cheaper than a stormwater pond to remove
        pollutants.
                       Data Sources
   The dataset compiles data from four different sources:
        A study conducted by Brown and Schueler at the Center for
         Watershed Protection (CWP); includes cost data on 37
         stormwater ponds, 12 bioretention cells.
        Report No. 344 (Wossink and Hunt) of the Water Resource
         Research Institute; includes cost data on 9 stormwater ponds
         and 13 bioretention cells.
        Engineering Resource Corporation and Clemson University in
         South Carolina; includes cost data on a stormwater pond and
         bioretention cell.
        Watershed Restoration Program (WRP) of the Montgomery
         County Department of Environmental Protection; includes data
         on 3 stormwater ponds.


   It consists of 29 extended detention ponds and 31 wet
    ponds. (Extended detention ponds are those which incorporate additional
    features to improve water-quality along with the usual water-quantity
    control.)
                              Variables
   The weekly wage data collected from BLS on:
       CONWAGE: construction wage data (SIC code 162), which
        included heavy construction, construction of water and sewer
        mains, pipelines, power lines and construction of heavy projects
        which were not specified elsewhere.
       ENGWAGE: Engineering wages data (SIC code 8711), which
        consists of engineering services like designing ship boats,
        industrial, civil, electrical and mechanical engineers, machine
        tool designers, marine engineering services and petroleum
        engineering services.
       LANDWAGE: Landscape wage data (SIC code 078), which
        included landscape counseling and planning, lawn and garden
        services, and ornamental shrub and tree services.

    The national average annual hours worked were also
    collected from BLS for each of these wages separately.
    The wage per hour was then calculated by dividing the
    weekly wage by the calculated hours worked per week.
   LANDVAL: the value of the particular use of land
    (residential/commercial) on the outskirts of the city on
    which the stormwater pond was located. It was
    calculated as the average of the ten randomly selected
    land prices from the tax assessors database.

   QUANVOL: Water-Quanity Volume
       the runoff from the drainage area for a ten-year storm event for
        the CWP and the WRP data.
       Measured as 0.5 times the drainage area for data from the
        report by Wossink and Hunt.


   QUALVOL: Water-Quality Volume
       Responses of survey done for the CWP and the WRP data.
       Measured as 0.24 inch times the drainage area for the
        stormwater ponds and was assumed equal to the QUANVOL for
        the bioretention cells for the data from the report by Wossink
        and Hunt.
   The data was classified into three different major land
    resource areas according to their locations:
       Piedmont region: have a clayey or loamy subsoil

       Coastal region: have a sandy surface layer with loamy subsoil.

       Sandhill Region: sandy subsoil


   ESTTOTCST: Estimated Total Cost (used for bioretention
    cells), consisted of design and engineering and
    construction cost.
       Construction costs: consisted of excavation and grading cost,
        cost of materials, cost of the control structures, cost of the
        sediment control practices, landscaping cost, and the
        appurtenance cost.
   ESTTOTCSTLND: Estimated Total Cost including land
    cost (used for stormwater ponds), calculated by adding
    land cost (surface area of the pond times the LANDVAL)
    to the total ESTTOTCST.

   The estimated total costs, land values and the three
    wages were appropriately adjusted, using the historical
    cost indices, to correspond to the year 2003 in
    Baltimore, Maryland. Baltimore was chosen as the point
    of reference because of its frequent use as a central
    location in the study.

   Pollutant removal data for both the BMPs were collected
    from six different sources, including the National Best
    Management Practice Database.
     Econometric Model and Estimation Procedure
   The simple model used in this study is specified as
    follows:

    where e is the error term, and WQV is used for both water-quantity
    and -quality volume.


   Logarithmic transformation of the above equation gives
    us:
         LESTTOTCST  ln( a)  b ln( WQV )  u            (Model 1)


   PROC REG procedure in SAS performed simple linear
    regression based on the equation above.
       QUALVOL was used for bioretention cells.
       QUANVOL was used for stormwater ponds.
       Values of 0<b<1 indicate the presence of economies of size.
   Logarithmic transformation of the complicated model
    incorporating the various inputs and land cost gives us:

    LESTTOTCSTLND  Intercept  cLQUANVOL
     dLCOASTQNV  eLQUALVOL  fLLANDVAL
     gLENGWAGE  hLCONWAGE  iLLANDWAGE  u1
                       (Stormwater Ponds)

    LESTTOTCST  Intercept  jLQUANVOL  kLQUALVOL
     lLCOASTQLV  mLSANDHILL QLV  nLENGWAGE
     oLCONWAGE  pLLANDWAGE  u2

                       (Bioretention Cells)
   The water-quantity volume of a BMP is assumed to
    increases by the same amount as the increase in the
    water-quality volume.

   The economies of water-quality size for bioretention cells
    located in the Piedmont region is as follows:
                  LESTTOTCST       QUALVOL
                              k j
                   LQUALVOL        QUANVOL
    The average of the ratio of QUALVOL to QUANVOL for those cells
    located in the piedmont region is considered for the above equation.

   These models were tested negative for heteroscedasticity
    (error term is constant and not related to any of the
    variables in the model) and spatial correlation (error
    terms are not related to each other due to the presence
    of location difference in the data).

   These cost functions are also tested for the homogeneity
    restriction of the factor prices, giving us a third set of
    results for each of the BMPs
            Results for Bioretention Cells

                         Estimates and p-value
Variable Name         Model 2        Model 3 (Restricted)
Intercept        -22.50173, 0.0029    -1.12931, 0.4997
LQUALVOL         -0.76805, 0.0532     -0.73557, 0.1260
LCOASTQLV         0.14083, 0.0118      0.01586, 0.7075
LSANDQLV         -0.16775, 0.0078     -0.23992, 0.0014
LQUANVOL          1.56436, 0.0006      1.70616, 0.0016
LENGWAGE          6.68941, 0.0058      0.64762, 0.6508
LCONSWAGE         0.88943, 0.3909      0.27093, 0.8283
LLANDWAGE        -0.04984, 0.9595      0.08146, 0.9466
Adj. R-Square         0.7967               0.6880
     Interpretations of Results for Bioretention Cells
   Both the QUANVOL and QUALVOL are significant
    determinants of the total adjusted costs of a cell.

   The effect of the water-quality volume, QUALVOL, on the
    cost is less by about 0.17% (Model 2) when the cell is
    located in the Sandhill region.
       Location of a cell in the Sandhill region can be expected to achieve
        low transportation cost of sand-one of the materials required for the
        building of a cell.


   Every 1% increase in the QUALVOL increases the total costs
    of the cell by
       0.76 % in the coastal region
       0.73 % in the Piedmont region
       0.63 % in the Sandhill region
    exhibiting economies of water-quality size in all the regions.
   The high value of the statistically significant estimate of
    the Engineering wage (ENGWAGE) can be due to various
    reasons:
       A typical bioretention cell can fit into a parking lot or a
        residential complex, requiring a high level of engineering
        sophistication for its construction.
       A highly paid engineer is likely to employ more sophisticated
        technologies to obtain superior results, causing a rise in the cost.
       Since the model does not consider material cost separately, a
        6.69% increase in the costs maybe due to the better quality
        materials used by a highly skilled engineer.
       This high number can be attributed to possible measurement
        errors in the data coupled with presence of a bias in the
        engineering wage.


   Model 3 cannot be used for our analysis as the likelihood
    ratio test indicated that we reject the null hypothesis of
    homogeneity restriction.
           Results for Stormwater Ponds
                         Estimates and p-value
Variable Name        Model 2       Model 3 (Restricted)
Intercept       -0.35585, 0.8731   -2.09249, 0.0710
LQUANVOL        0.84162, <.0001    0.84303, <.0001
LCOASTQNV       0.01290, 0.4219    0.01648, 0.2901
LEXTDEQNV       -0.05942, 0.0031   -0.06000, 0.0027
LQUALVOL        -0.02063, 0.8619   -0.02564, 0.8283
LLANDVAL        0.34192, 0.0016    0.30916, 0.0021
LENGWAGE        -0.32427, 0.6896   -0.13904, 0.8592
LCONSWAGE       -0.23756, 0.8212   -0.30876, 0.7679
LLANDWAGE       0.48586, 0.6885    1.13865, 0.2450
Adj. R-Square         0.8580             0.8586
         Interpretations of Results for Stormwater Ponds
   Assuming QUALVOL remains constant, 1% increase in the
    QUANVOL of the pond increases the total costs by 0.84%
    in the Piedmont region, suggesting economies of water-
    quantity size.

   LANDVAL is highly significant. For every 1% increase in the
    value of a unit of land, total costs of the stormwater pond
    increase by 0.19%.

   Total cost would be lower by 0.06% for extended
    detention ponds compared to wet ponds, for every 1%
    increase in the QUANVOL, holding QUALVOL constant.
       They are expected to be deeper with smaller surface area than a
        wet pond having the same amount of water-quantity volume.
       As land cost is a major constituent of the stormwater ponds, the
        decrease in surface area will lower the land cost and hence the
        total cost of the pond.
             Comparison between the two BMPs
Using model 2 for both the BMPs, we find the average effect of water-quantity
volume on the total cost of each of the BMP at the given input prices in each
region.

Total Cost
                 Bioretention cell




                                     Stormwater Pond




                                                       Water-Quantity Volume
             25832 cubic-feet
           Comparison between both the BMPS
   Estimated fixed costs are higher for stormwater ponds
    than bioretention cells.

   Cost of stormwater ponds increases at a slower rate for
    every one percent increase in the water-quantity volume
    compared to the bioretention cells.

   Finding the cross-over QUANVOL at which bioretention
    cells and stormwater ponds have the same cost indicate:
       A bioretention cell is a cheaper management practice than a
        stormwater pond in the Piedmont region for QUANVOL less than
        25,832 ft3.
       A bioretention cell is a less expensive method of removing
        pollutants in any feasible volume of water than a stormwater
        pond in the coastal areas.

   Calculation of these cross-over volume assumes that
    both the BMPs remove the same amount of pollutant
    Table below on the amount of pollutants removed by the two
     suggests that bioretention cells on average remove more pollutant
     than a stormwater pond.

                                       Average Amount of                    Average Amount of
    Type of Pollutant                  Pollutant Removed                    Pollutant Removed
                                       by Stormwater Ponds                  by Bioretention Cells
                                       (mg/L)                               (mg/L)
    Copper                             0.0042                               17.03854

    Lead                               0.0110                               12.69257

    Zinc                               0.0493                               0.60375

    Phosphorus                         0.1221                               0.59340

    Nitrates and Nitrites              0.1385                               0.14930

    Nitrogen                           0.1677                               3.6810

Source for stormwater ponds: National Best Management Practice Database (EPA, 1999)
Sources for bioretention cells: Inglewood demonstration project (EPA, 2000a) and Maryland’s Greenbelt and Landover
    field study (Davis)
                            Conclusions

   Both bioretention cells and stormwater ponds exhibit
    economies of size after adjusting for time and space and
    incorporating the input prices.

   Bioretention cells are likely to be cheaper than
    stormwater ponds as land price increases.

   Bioretention cells are cost effective in the coastal region
    but stormwater ponds are cost effective for most
    volumes of water treatment in the Piedmont region.
       Mean QUANVOL for stormwater ponds 336,152ft3 while the
        cross-over volume over which they become cheaper is 25,832ft3.

   Notwithstanding lack of sufficient information on
    maintenance costs, these models can be used by the
    EPA to improve the accuracy of its estimates of costs of
    compliance with water-quality regulation.

				
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