POLLUTANTS IN ENV
POLLUTANTS IN ENV ESM 222
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This 12 page Class Notes was uploaded by Weston Batz on Thursday October 22, 2015. The Class Notes belongs to ESM 222 at University of California Santa Barbara taught by A. Keller in Fall. Since its upload, it has received 49 views. For similar materials see /class/226959/esm-222-university-of-california-santa-barbara in Environmental Science and Resource Management at University of California Santa Barbara.
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Date Created: 10/22/15
B0CHLOR NamraM enua nn Decisinniupponiystem Veniun mm User s Manua Addendum WWWWWM WWW Wm WM hmmm mmmmm mem Wm WM WWMWWW WWWWWW WWW DISCLAIMER BIOCHLOR is made available on an asiis basis Without guarantee or warranty of any kind express or implied The United States Government Groundwater Services Inc the authors and the reviewers accept no liability resulting from the use of BIOCHLOR or its documentation Implementation of BIOCHLOR and interpretation of the predictions of the model are the sole responsibility of the user TABLE OF CONTENTS BIOCHLOR Natural Attenuation Decision Support System Air Force Center for Environmental Excellence Technology Transfer Division Section Page No INTRODUCTION I NEW FEATURES IN VERSION 7 7 I RATE CONSTANT DECISION SUPPORT FOR ESTIMATING RATE CONSTANTS SOURCE DECAY ANIMATION FOR CENTERLINE OUTPUT REVISED FEATURES TROUBLESHOOTING TIPS MINIMUM SYSTEM REQUIREMENTS GUIqu APPENDICES AI DOMENICO ANALYTICAL MODEL WITH DECAYING SOURCE 7 AI ACKNOWLEDGMENTS 9 RTOC l ll 0R ADDPN39DTTM March 2002 INTRODUCTION BIOCHLOR is a screening model that simulates remediation by natural attenuation RNA of dissolved solvents in groundwater The software programmed in the Microsoft Excel spreadsheet environment and based on the Domenico analytical solute transport model has the ability to simulate liD advection 37D dispersion linear adsorption and biotransformation via reductive dechlorination the dominant biotransformation process at most chlorinated solvent sites Dissolved solvent degradation is assumed to follow a sequential first order decay process BIOCHLOR includes three different model types 1 Solute transport Without decay 2 Solute transport With biotransformation modeled as a sequential firstiorder decay process 3 Solute transport With biotransformation modeled as a sequential firstiorder decay process With 2 different reaction zones ie each zone has a different set of rate coefficient values Groundwater Services Inc Houston Texas developed BIOCHLOR for the Air Force Center for Environmental Excellence AECEE Technology Transfer Division at Brooks Air Force Base The mathematical technique to solve the coupled reactive transport equations was developed by researchers formerly with the Battelle Pacific Northwest National Laboratory New Features in Version 22 BIOCHLOR Version 22 includes the following new features rate constant decision support source decay and animation A rate constant decision support feature was incorporated to help users estimate rate constants required for model calibration In addition to simulating a source of constant concentration BIOCHLOR Version 22 models a decaying source which allows the simulation of both plume expansion and contraction Lastly an animation feature has been incorporated which permits the visualization of plume behavior This document describes these new features Users should continue to refer to the existing BIOCHLOR Version 10 User s Manual Aziz et al 2000a as the primary source of information about BIOCHLOR Rate Constant Decision Support For Estimating Rate Constants A new feature in BIOCHLOR Version 22 is rate constant decision support which helps users estimate rate constants to be used in BIOCHLOR simulations The use of an appropriate biotransformation rate constant is important because the model is typically sensitive to the magnitude of the rate constants Although rate constants can be taken from the literature the values reported for a given chlorinated constituent can vary by as much as 34 orders of magnitude Biotransformation rate constants are siteispecific and will be dependent on the size of the dechlorinating microbial population the availability of electron donors and environmental conditions Many rate constants in the general literature are derived from laboratory microcosm studies Typically these laboratoryiderived values overestimate the rate of biotransformation seen in the field because of the difficulty in simulating field conditions in a laboratory environment Aziz et al 2000b The best approach for determining rate constants is to calibrate BIOCHLOR to field data for a given sampling event To estimate rate constants change the rate constant for PCE degradation RTOCHT 0R ADDFN39DTTM March 2002 until the PCB predicted concentrations match the PCB field data Then change the TCE rate constant until the TCE predicted concentrations match the field data Continue estimating rate constants for the other constituents In this way siteispecific rate constants are estimated and the model is then considered calibrated Using the siteispecific rate constants predictive simulations can be conducted by increasing the simulation time to estimate future plume behavior To speed the calibration process BIOCHLOR Version 22 incorporates the Buschek and Alcantar 1995 rate constant estimation method Which automatically provides an approximate calibration of the model to entered siteispecific field data This feature can be accessed from the Biotransformation section on the input screen by pressing the quot7 Help button The Buschek and Alcantar approach uses the equations in Table 1 Which assume 17D dispersion steadyistate conditions and biotransformation only in the aqueous phase Although this equation has the potential to overestimate biotransformation rate constants by lumping the effects of lateral and vertical dispersion With biotransformation it quickly yields a reasonable first approximation of the rate constants These rate constant estimates can be manually refined subsequently A minimum of four data points is required for rate constant determination This approach is most appropriate for parent constituents Caution should be exercised in using this approach With daughter constituents as daughter product generation is not accounted for in this method The Bushek and Alcantar 1995 method starts With the 17D steadyistate solution to the advectionidispersion equation By plotting the contaminant concentration on a logarithmic scale versus distance downgradient plotted on a linear scale the slope m of the line is determined by linear regression The biotransformation rate constant 7 is determined using the slope m and the third equation in Table 1 In addition BIOCHLOR also calculates the r2 for the linear regression This method is intended for lizone simulations only because it uses all the field data entered in Section 7 of the model Table 1 Equations Used in Buschek and Alcantar 1995 Rate Constant Estimation Method 0 5 Where Cx Ca exp 7 I 410G J 9 is the biotrans rate constant lyr 206X v5 v3 is the seepage velocity ftyr xx is the longitudinal dispersivity ft m is the slope of the 111 conc vs 1 l7 4M 05 distance 1 ft m l l X x is the distance downgradient ft Zax Vs j CD is the initial concentration mg L Cx is the concentration at distance x mg L V 2 1 4a 1 20am 1 Use of Literature Values Although it is preferable to use siteispecific field data to estimate rate constants field data are not always available In these cases the user may opt to assume that no biotransformation is occurring the most conservative option Alternately if there is evidence of biotransformation by virtue of the production of daughter products then literature values for the biotransformation rate constant may be used As noted previously it is difficult to select an appropriate biotransformation rate constant because these parameters are siteispecific RTOC HT 0R ADDPN39DTTM March 2002 depending on the number and type of bacteria present the amount of electron donor and environmental conditions To provide users with more reasonable literature values the BIOCHLOR model was calibrated with chlorinated solvent plume data from the BIOCHLOR database Aziz et al 2000b to yield fieldiderived rate constants as shown on Table 2 Most of the sites in the BIOCHLOR database had significant BTEX electron donor concentrations so these rate constants should only be used at sites with evidence of significant electron donor Table 2 Rate Constants Estimated Using BIOCHLOR Rate Constants 1yr Minimum 25th Percentile Median 75th Percentile Maximum Mean n PCE 08 w 11 w 24 14 3 TCE 03 05 12 24 32 15 10 cDCE 01 07 12 22 209 35 9 VC 04 06 17 49 122 36 7 TCA 16 w 24 w 32 24 2 DCA 02 w 03 w 12 05 3 r 2 lnsufficent data to calcula e Rate Constant Decision Support in BIOCHLOR BIOCHLOR Version 22 provides guidance for the selection of fieldiderived biotransformation rate constants for chlorinated ethenes and chlorinated ethanes This guidance is provided through the quot7 Help button in the Biotransformation section of the input screen The user is first asked whether there is evidence of reductive dechlorination at the site If not biotransformation rate constants of zero should be employed If there is evidence of reductive dechlorination BIOCHLOR queries the user as to the amount of electron donor present If the concentration of electron donor is gt0l mgL or hydrogen concentrations are present at gt 1 nM then the user is presented with rate constants for the chlorinated constituents that range from the minimum value to the 75 h percentile as determined in the BIOCHLOR database study Table 2 For constituents with limited data the maximum value was used as the upper limit If low levels of electron donor are present but there is still evidence of biotransformation then BIOCHLOR suggests using a rate constant less than the minimum value Source Decay Dense noniaqueous phase liquids DNAPLs such as PCB and TCE can act as continuing sources of groundwater contamination The rate at which constituents in the DN FL or source dissolve into the groundwater ultimately determines the concentration of dissolved contaminants in the plume and the lifetime ofa dissolved plume ln BIOCHLOR Version 10 the transport model incorporates a source term of constant concentration over time as used in the original Domenico model Domenico 1987 In BIOCHLOR Version 22 the user has the option of modeling a source with constant or decaying concentration over time Source decay is modeled as a first order process This approach RTOC l U 0R ADDFN39DTTM March 2002 captures all processes that can lead to depressed aqueousiphase concentrations in the source zone including decreased dissolution rate from the DNAPL biotransformation or any other degradation processes After selecting the Decaying source option accessed through the Source Options button on the input screen enter a source decay rate constant k for all of the constituents This value must be previously calculated by plotting temporal aqueous concentrations in a source area well on a semiilog plot and determining the slope as shown in Figure 1 Note that Excel will calculate a slope in units of ldays This slope must be converted to units of lyr as required by Biochlor 22 A new tool called BIOSOURCE is currently being developed for the AFCEE by Groundwater Services Inc This tool will assist the user in determining source decay constants Be aware that the source decay constant k is different from the biotransformation constant 7 k5 describes how the concentration in a source area well decreases as the DNAPL is depleted of the constituent of concern whereas 7 is the biotransformation rate constant for a constituent in the plume 100000 10000 1000 0100 Concentration m gL 0010 0001 1189 22591 42193 61595 8997 10499 Time yr Figure 1 Determination of ks Using Aqueous Concentrations in Source Area Wells The equations describing groundwater transport and biotransformation with a decaying source are presented in Appendix Al The decaying source feature can only be used with oneizone simulations The user is restricted to ks values that are less than l R7VS40L to prevent unstable complex solutions A safety factor of 20 is also incorporated Animation for Centerline Output The addition of a decaying source permits the 39 39 of e panding and 39 O plumes as the simulation time is increased To help the user Visualize plume movement an animation feature similar to that in BIOSCREEN is incorporated in BIOCHLOR This animation feature can be accessed by pressing the Run Centerline button on the input screen which directs the user to the Individual constituent page The centerline output screen shows the concentration along the centerline of the plume y0 Clicking on Prepare Animation divides the simulation into 10 separate time periods and RTOCHT 0R ADDFN DTTM March 2002 shows the movement of the plume based on either the Biotransformation or No Degradation model After the first animation is completed the user can step forward or backward in time by pressing the Next or Prev buttons or all 10 simulations can be replayed by pressing the Replay button Revised Features There are two minor changes to features originally present in BIOCHLOR Version 11 First the longitudinal dispersivity alpha x can now be entered directly on the input screen or the user can press the Calc Alpha x button to receive assistance with the alpha x calculation The options for calculating alpha x remain the same as in Version 11 however the relations linear or Xu and Eckstein are based on the estimated plume length Lp instead of scale x Whichever option is chosen alpha x remains constant over the extent of the plume s The second change involves the order of the output screens To facilitate model calibration the user is now directed to the Individual constituent page first instead of the output page showing all the constituents simultaneously Troubleshooting Tips SpreadsheetRelated Problems The buttons won39t work BIOCHLOR is built in the Excel spreadsheet environment and to enter data one must click anywhere outside the cell where data was just entered If you can see the numbers youjust entered in the data entry part of Excel above the spreadsheet the data have not yet been entered Click on another cell to enter the data is displayed in a number box The cell format is not compatible with the value eg the number is too big to fit into the window To fix this press the Unprotect Sheet button Then select the cell pull down the format menu select Cells and click on the Number tab Change the format of the cell until the value is visible If the values still cannot be read select the format menu select Cells and click on the Font tab Reduce the font size until the value can be read DIVO is displayed in a number box The most common cause of this problem is that some input data are missing In some cases entering a zero in a box will cause this problem Double check to make certain that data required for your run have been entered in all of the input cells Note that for vertical dispersivity BIOCHLOR will convert a 0 in the data entry cell to a very low number to avoid DlVO errors There once were formulas in some of the boxes on the input screen but they were accidentally overwritten Press the closest C button or click on the Restore Formulas button on the bottom righthand side of the input screen The graphs seem to move around and change size This is a feature of Excel When graph scales are altered to accommodate different plotted data the physical size of the graphs will change slightly sometimes resulting in a graph that spreads out over the fixed axis legends You can manually resize the graph to make it look nice again by doubleiclicking on the graph and resizing it refer to the Excel User s Manual The source dialog boxes keep closing If you press Enter when inputting data in a dialog box then the dialog box will close Do not press Enter and move to the next cell by using the mouse RTOC HT 0R ADDPN DUM March 2002 and clicking or by using tabs If you do press quotEnterquot by accident simply select your source option again The scale on the 37D graphic on the array page is not even This is a feature of Excel There is no way of creating an even scale when using unevenly spaced data in a 37D graphic Common Error Messages Unable to Load Help File The most common error message encountered with BIOCHLOR is the message Unable to Open Help File after clicking on a Help button Depending on the version of Windows you are using you may get an Excel Dialog Box a Windows Dialog Box or you may see Windows Help load and display the error This problem is related to the ease with which the Windows Help Engine can find the data file BIOCHLRZZHLP Here are some suggestions in decreasing order of preference for helping WinHelp find it 1 If you are asked to find the requested file do so The file is called BIOCHLRZZHLP and it was installed in the same directoryfolder as the BIOCHLOR model file N Use the PileOpen menus from within Excel instead of doubleiclicking on the filename or Program Manager icon to open the BIOCHLOR model file This sets the current directory to the directory containing the Excel file youjust opened 9 Change the WinHelp call in the VBA Module to hard code the directory information That way the file name and its full path will be explicitly passed to WinHelp Go to the Tools menu and select Macro Enter btnBasic Helpiclick for the macro you are searching for This will take you to all the help files Enter the new path P As a last resort you can add the BIOCHLOR directory to your path located in your AUTOEXECBAT file and this problem will be cured You will have to reboot your machine however to make this work Minimum System Requirements The BIOCHLOR model requires a computer system capable of running Microsoft Excel 97 or 2000 for Windows Operation requires an IBMicompatible PC equipped with a Pentium II or later processor A minimum of 64 MB of system memory RAM is strongly recommended Installation and StartUp The software is installed by copying the BIOCHLOR model file BlOCHLORZles and the BIOCHLOR help file BlOCHLRZZhlp to the same folder on your computer hard drive To use the software start Excel and load the BIOCHLOR model file from the FileOpen menu You may see a message box that asks you whether you want to disable or enable the macros Eor BIOCHLOR to operate effectively you must enable the macros RTOC l TT 0R ADDFN39DTTM March 2002 lIIIIIIIIIIIIIIIIII APPENDIX Al DOMENICO ANALYTICAL MODEL WITH DECAYING SOURCE To model a decaying source in BIOCHLOR the Domenico 1987 semiianalytical solution for reactive transport With first order biological decay was modified to incorporate a decaying source boundary condition The revised model assumes that the source decays exponentially via a first order expression ie CD exp ikst The source decay constant k must be determined by the user prior to using BIOCHLOR as discussed on page 4 The modification of the Domenico solution was accomplished by extending a 17D solution to the advectionidispersion equation that incorporated a decaying boundary condition to a 3D solution by analogy Van Genuchten and Alves 1982 BIOCHLOR evaluates centerline concentrations at y0 20 and the 27D array at 20 The boundary conditions assumptions limitations and model equation are discussed beloW The initial conditions of the source decay BIOCHLOR model are l Cx y z 0 0 Initial concentration 0 for x y z gt 0 2 C0 Y Z 0 Coeikst Source concentration for each vertical plane source CO at time 0 The user can also opt to model the source as a continuous source With constant concentration as described in Appendix Al in the Biochlor User s Manual Aziz et al 2000a The key assumptions in the model are l The aquifer and flow field are homogenenous and isotropic N The groundwater velocity is fast enough that molecular diffusion in the dispersion terms can be ignored may not be appropriate for simulation of transport through clays 3 Adsorption is a reversible process represented by a linear isotherm The key limitations to the model are l The model should not be applied Where pumping systems create a complicated flow field 2 The model should not be applied Where vertical flow gradients affect contaminant transport 3 The model should not be applied Where hydrogeologic conditions change dramatically over the simulation domain RTOC l ll 0R ADDFN39DTTM March 2002 Modi ed Domenico Model with First Order Biotransformation and Source Decay C0 1 CXyzte f l l t1 4 t kR l erfc x V ax 5 V KIT 1 4axt ksRVSU5l exp w Zax L 2DIXVI J XE14D xl ksRVs0 5 X Vt14aXl ksRVS05 EXP 20 J erfc 2a VI l x l J K f erfl w erfi m 22 2 2 1 05 05 fzerf 0 9 05 t Z ayx t 2ayx Z0ZX 2aZX De n itio n s Cx A A offcenterline ofplume at time t mgL Ca Concentration in Source Area at t0 mgL x Distance downgradient of source 11 y Distance from plume centerline of source ft 2 Distance from top ofsaturated zone to measurement point assumedto be 0 concentration is always given at top of saturated zone orX Longitudinal groundwater dispersivity ft oiy Transverse groundwater dispersivity oz Vertical groundwater dispersivity ne Effective Soil Porosity it First Order Degradation Rate Coef cientyr391 vs Seepage Velocity yrKine v Chemical Velocity yrvs R K Hy aulic Conductivity yr R Constituent retardation factor i Hydraulic Gradient cmcm Y Source Width 11 z Source Thickness 11 k5 Source Decay Constant lyr The most important modifications to the original Domenico model are 1 An exponentially decaying source boundary condition is employed instead of a constant source N Biotransformation is assumed to occur only in the aqueous phase The original Domenico model was derived assuming that biotransformation occurred equally rapidly in the soil and aqueous phases To make this adjustment the rate constants were divided by the retardation factor 3 To simulate a spatiallysvarying source BIOCHLOR superimposes three Domenico models each with a different concentration and source width Connor et 31 1994 The original Domenico mode was derived for a single planar source of constant concentration RTOCHT OR ADDPN DUM March 2002 APPENDIX A2 ACKNOWLEDGMENTS BlOCHLOR Version 22 was developed for the Air Force Center for Environmental Excellence Brooks APB San Antonio Texas by Groundwater Services Inc AECEE Project Officer Mr Jim Gonzales BlOCHLOR Version 22 Carol E Aziz PhD and Charles Newell PhD PE Developers Groundwater Services Inc phone 713 52276300 2211 Norfolk Ste 1000 fax 713 52278010 Houston Texas 77098 ceazizgsi7netcom cjnewellgsi7netcom BIOCHLOR Manual Addendum Carol E Aziz PhD and Charles Newell PhD PE Groundwater Services Inc BIOCHLOR V 22 REViEW Team Dr Jerome Cruz ManTech Environmental Research Services lnc National Risk Management Research Laboratory Ada OK Dr Mingyu Wang ManTech Environmental Research Services lnc National Risk Management Research Laboratory Ada OK Mr Abu Noman ManTech Environmental Research Ahsanuzzaman Services lnc National Risk Management Research Laboratory Ada OK Dr David Jewett Center for Subsurface Modeling Support National Risk Management Research Laboratory Ada OK References Abramowitz M and IA Stegun 1972 Handbook of Mathematical Eunctions with Eormulas Graphs and Mathematical Tables Dover Publications Inc New York Aziz CE C Newell R Gonzales PHaas TP Clement YAW Sun 2000a BlOCHLOR Version 10 User s Manual EPA600R700008 Aziz CE AP Smith C Newell and R Gonzales 2000b BlOCHLOR Chlorinated Plume Database Prepared for the Technology Transfer Division Air Force Center for Environmental Excellence Brooks APB Texas
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