Diffuse Pollution Conference Dublin 2003 A NEW MODELING APPROACH FOR ESTIMATING FIRST FLUSH METAL MASS LOADING

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1 Diffuse Polluion Conference Dublin 23 A NEW MODELING APPROACH FOR ESTIMATING FIRST FLUSH METAL MASS LOADING Lee-Hyung Kim, Masoud Kayhanian 2, Sim-Lin Lau 3 and Michael K. Sensrom 3 Dep. of Civil and Environmenal Engineering, Kongju Naional Universiy, 82 Shinkwan-dong, Kongju-si, Chungnamdo, 34-7, Korea 2 Cener for Environmenal and Waer Resources Engineering, Dep. of Civil and Environmenal Engineering, Universiy of California, Davis, California, 9566, USA 3 Dep. of Civil and Environmenal Engineering, Universiy of California, Los Angeles, California, , USA ABSTRACT The purpose of his sudy was o invesigae polluan mass loading from major highways in Souhern California, wih emphasis on inerpreaion of even mean concenraions and firs flush effecs. The resuls of monioring eigh sies during he sorm seasons found ha meal conaminans had higher concenraions a he early sages of sorm evens compared wih oher sages of rain sorms. A new washoff model was developed o predic he even mean concenraions of meal conaminans aking firs flush effec ino accoun. Model variable parameers included average daily raffic, aneceden dry period, rain inensiy, oal runoff volume, and runoff coefficien. The resuls obained using he washoff model were compared wih measured values and found o fi well for heavy meals wih R 2 ranging from.8 o.95. KEY WORDS: Washoff model; even mean concenraion (EMC); firs flush; meal conaminans, mass loading. INTRODUCTION In he Unied Saes, many naural waers are classified as impaired because of polluan inpus from non-poin sources. Heavy meals are among he lis of major polluans of concern from hese non-poin sources. Heavy meals come from some naural sources such as minerals in rocks, vegeaion, sand, and sal. However, large amoun of heavy meals in road surfaces are from wear and ear of various vehicle componens such as ires, engine pars, brake pads; auo body rusing; lubricans; and fuel combusion (USEPA, 995). In general, meals are accumulaed during dry days and washed from highways during sorm evens. These meals are usually absorbed by soil paricles and moved o receiving waers during sorm evens. The federal governmen Clean Waer Ac was esablished o preven large mass loading of hese polluans ino receiving waers. As par of an ongoing effor o miigae he highway runoff polluans, he California Deparmen of Transporaion engaged in various sorm waer characerizaion sudies hroughou he sae (Kayhanian e al., 2). One of hese specialized sudies was he firs flush (FF) characerizaion. The firs flush characerizaion sudy was carried ou joinly by he Deparmen of Civil and Environmenal Engineering a he Universiy of California, Davis (UCD) and Los Angeles (UCLA) campuses. The FF characerizaion sudy has been ongoing since 998 and several aspecs of FF characerizaion have been published in Ma e al., 22; Lau e al., 22; Kayhanian e al., 22. Ofen he polluan concenraions declines over ime, which ends o creae greaer emission raes a he beginning of runoff. This phenomenon is ofen called a firs flush, and he exisence of a firs flush can influence he selecion of bes managemen pracices (BMPs). The exisence of firs flush is debaed and many defining crieria exis (Thornon and Saul,987; Geiger,987; Gupa and Saul, 996; Sansalone and Buchberger, 997; Larsen e al., 998; Sansalone e al., 998; Vorreier and Hickey, 994; Deleic, 998; Sage e al., 995; Berrand-Krajewski e al., 998). The firs flush phenomenon has mos ofen been observed in small waersheds, paricularly if he amoun of imperviousness area is proporionally high. To esimae he polluan loads from small and larger waersheds, models are ofen used o predic polluan concenraions. Differen models have been used, including regression, sochasic, and deerminisic simulaion (Irish Jr. e al., 998). The main difference beween hese models is he assumpion of he origin of polluans. Mos of he models commonly use concenraions or loads of polluans as variables ha are dependen upon runoff volume, rainfall inensiy, raffic inensiy, aneceden dry days, surrounding land use, ec. Generally, i is difficul o consider all facors because many differen sie-specific condiions exis, such as he presence or absence of sree sweeping, soil sauraion, wind direcion, ec. Regression models have been criicized as poor predicors of fuure evens or for differen regions (Driscoll e al., 99). No model, however, is available o ake firs flush ino accoun as par of he mass loading compuaion. This paper will provide a new approach defining firs flush crieria and is applicaion for EMCs and mass loading calculaions. METHODS Figure shows he eigh highway monioring sies. All were seleced o include primarily highway runoff. Samples have been colleced since he 999 rainy season. Table summarizes he monioring periods and parial characerisics of each sie. 4-38

2 Diffuse Polluion Conference Dublin 23 : Sie Locaion 5 URS23 UCLA 45 UCLA2 UCLA UCLA3 Sana Monica Glendale 2 USC Los Angeles 6 URS8-23C 2 URS6-2F 5 Km CDM7- LAX Sana Monica Bay CDM Long Beach Pacific Ocean San Pedro Bay Figure. Monioring locaions in Souhern California Monioring was performed by collecing 4L grab samples. Generally, five samples were colleced in he firs hour. The firs sample was colleced a he very beginning of runoff. Addiional samples were colleced each hour unil he end of he runoff. Rainfall and runoff raes were also measured wih auomaed monioring equipmen. Addiional informaion on sample collecion, equipmen, analyical consiuens and oher relaed iems can be found in Kayhanian e al. 22 and Ma e al., 22. Table. Monioring sie descripions Sie Name Freeway Locaion ADT (cars/day) Waershed Area (m 2 ) Monioring Period UCLA 328, curren UCLA , curren UCLA , curren CDM7-2 76, CDM & 65 22, URS , 29 2-curren URS6-2F 6 26,6 7 2-curren URS8-23C , 25 2-curren Washoff Model Developmen Because of random characerisics of runoff qualiy and quaniy, he EMCs canno be deermined by simple saisical averages of measured polluan concenraions in sormwaer runoff. The sources of uncerainy are generally caused by uncerainies in magniude of rainfall inensiy, experimenal errors, and lack of sufficien daa. Gupa and Saul (996) used muliple linear regression analysis for daa inerpolaion and Larsen (998) calculaed EMCs using he medium poin mehod. Many researchers (Charbeneau and Barre 998; Deleic and Mahsimivic 998; Irish Jr. e al. 998; Osuch- Pajdzinska and Zawilski 998; Deleic e al. 2) used mass emission raes from he exponenial washoff model o esimae EMCs. The exponenial model ignores many differen rends in concenraions normally observed during monioring. For insance, i is no possible o predic diluion wih an exponenial model. Concenraion reducion occurs whenever a paricular quaniy of polluans mixes wih a large runoff volume. The diluion in sormwaer occurs essenially as a coninuous process and varies wih rainfall rae. I is generally assumed ha a polluan has an iniial mass on he waershed area ha exised before he rainfall and a remaining mass ha sill exiss afer he rainfall. The washoff mass is he difference beween oal and remaining mass. The oal mass on he waershed changes wih ime due o inpus from we or dry deposiion, auomobiles, and oher sources. During he sorm even, he mass inpu from auomobiles can be high and can affec runoff concenraions during he sorm (Shaheen 975). As menioned earlier, he mechanism affecing he concenraion changes wih ime is he diluion of iniial polluan mass. However, he mass from air and auomobiles during a sorm even can creae he opposie rend, coninuously adding o he washoff mass. The washoff rae can be described such as Equaion. α= Washoff rae coefficien C () = Polluan concenraion a ime Q RU = Runoff volumeric rae, m 3 /sec dc [ ()] QRu( ) C () = α () d V 4-39

3 Diffuse Polluion Conference Dublin 23 T and 3 V Toal runoff volume Q () d, m = = Ru Rearranging and inegraing Equaion, we obain: β = Inergraion consan By leing QRu() d QRu () d = = V T V Q () d Ru QRu () d ln [ C ()] = α + ln ( β) (2) V () and aking he exponenial of boh sides, Equaion 2 becomes: ( ) β [ α ()] Where, V () = Normalized Cumulaive Volume, V (). C = Exp V (3) Finally, as saed earlier, he mass inpu during a sorm even can be considered as anoher concenraion erm (ã), which originaes from auomobiles, air and oher facors. Thus, ( ) [ ()] C = β Exp α V + γ (4) Where, he concenraion can also be defined from mass emission rae: M = C Q (5) ( ) () Ru () M () = Polluan mass emission rae a ime, M () Md ( ) = = = Ru C () Md () Q Q d Q d Q d () () () () Ru Ru Ru (6) The denominaor of equaion 6 afer inegraing becomes The difference in wo normalized volumes over ime and - is: Q () d Q () d = [ V () V ( ) ] V (7) Ru Ru [ V() V ( ) ] By subsiuing equaions 8 ino 6 and rearranging, we obain: β = (8) V () Md () (9) β V () V ( ) = C The righ side of Equaion 9 has unis of mass/volume or concenraion. This new concenraion erm is a key premise of he model. Le Md () V = C [ V () ] Equaion 9 now can be expressed as follows:, where C is defined as new concenraion. C C V β V () ( ) = [ ()] () By equaing equaions 4 and, we obain: 4-4

4 Diffuse Polluion Conference Dublin 23 β Exp α V + γ = C β V () V [ () ] [ () ] () Summarizing and leing ββ = β and γβ = γ, he new washoff model is expressed as follows: [ ] [ ] C V () = β V () Exp α V () + γ V () (2) In Equaion 2, a para meer is needed o describe he iniial condiion (δ ), which ideally should be relaed o aneceden dry periods. The new washoff model is finally expressed as follows: { } [ ()] δ () γ β [ α ()] C V = + V + Exp V (3) The new washoff model has wo differen pars or funcions. The firs is a linear, γ V β V () Exp α V (). form of a gamma ype funcion, [ ] () + δ, and he second akes he In order o use he model as a predicive ool, i is necessary o predic he oal runoff volume, which mus be based upon weaher forecas or oher informaion. Equaion 3 has four parameers ha are relaed o aneceden dry periods, rainfall inensiy and runoff coefficien. The ä is an iniial concenraion relaed o aneceden dry periods. The parameers á and ã are relaed o oal runoff. The â is relaed o rainfall, runoff coefficien and sorm duraion. RESULTS AND CONCLUSIONS Runoff Coefficien The runoff coefficiens are shown in Figure 2 as a funcion of oal rainfall. The average is.87. Evens wih less rainfall have lower runoff coefficiens, and lie below he regression line. This phenomenon is well esablished in he lieraure and is relaed o sauraion of he sie. A ypical runoff coefficien plo is shown in Figure 2. Toal Volume of Runoff (m 3 ) Runoff Coefficien =.87 No. of Evens = 4 R2 =.98 Toal Volume of Rainfall (m 3 ) Figure 2. Runoff coefficien plo Saisical Summaries of Measured Meal Concenraions Figure 3 shows he box plos of measured concenraion for seven meals. The box plos show minimum, median, maximum, sandard deviaions, upper/lower 95 percen confidence inervals and ouliers for each meal. For example, he concenraion ranges.7-.2 µg/l, µg/l, µg/l, µg/l for oal Cd, Cu, Pb, and Zn, respecively under 95 percen confidence inervals. These plos clearly showed ha here are large differences beween minimum and maximum concenraions. These differences are assumed o be parially due o variaions in rainfall inensiy and aneceden dry periods. In mos cases i was deermined ha large fracion of meal conaminans is in dissolved phase. However, he raios of oal o dissolved fracion for all meal conaminans were no he same. For example, as shown in Figure 3, he raio of T-Pb and D-Pb is subsanially higher han oher meal polluans. Because of hese exreme variaion of polluan concenraions from even o even, he use of medium concenraion in modeling effor can inroduce large error, paricularly when only a few samples are colleced. Similarly, because he EMC values are affeced by rainfall and aneceden dry periods he exponenial model may no fi he observed daa and ha can resul in large errors. The new modeling approach inroduced in his paper will delineae some of hese errors. Firs Flush Crieria I is imporan o know he probabiliies and magniude of he firs flush. True esimaion of he firs flush magniude is difficul, due o random characerisics of runoff qualiy and quaniy, uncerainies in rainfall inensiy and magniude, experimenal errors, and lack of sufficien daa. Models o predic firs flush of meal polluans are rare. Therefore, he exisence and imporance of firs flush has been debaed. If firs flush exiss, i is more pracical and cos effecive o capure and rea more of he earlier runoff volume and bypass he remaining runoff volume. 4-4

5 Diffuse Polluion Conference Dublin 23 Figure 3. Box plos for measured dissolved and oal concenraions and relaed EMCs for seven meals Figure 4 shows he example of displaying firs flush in he case of oal Zn. The resuls were obained by fiing he model o each sorm even and hen using he model resuls o calculae mass emission raes. The lef side of Figure 4 shows oal Zn mass emission raes for successive normalized runoff volumes ranging from o percen wih he incremen of percen. This mehod of ploing shows ha he firs percen of he normalized volume carries he greaes mass of polluans. The righ side of Figure 4 shows mass firs flush raio (MFF). For example he MFF for oal Zn is 2.2, which means ha 22 percen of he normalized oal Zn mass is washed off in he firs percen of normalized runoff. The M FF raio declines as he sorm proceeds and he MFF 2 and MMF 3 decline o.4 and., respecively. Figure 4. Washoff polluan mass and volume These analyses were performed on seven meal parameers and we concluded ha meal firs flush peaked a abou 3 percen of he normalized flow. This means ha he firs flush is usually occurred in he firs 3 percen of oal runoff volume. The ranges of firs flush observed are shown in Figure 5. The measured evens are divided ino MFF 3 raios greaer han.67 (high), beween and.67 (medium) and less han. (non-firs flush). Mos evens produced MFF 3 ranging from o.67. In general, abou 8 percen of he evens for oal Pb, 88 percen of he evens for oal Cd and oal Cu, and 83 percen of he evens for oal Ni have shown firs flush based on normalized mass and volume. 4-42

6 Diffuse Polluion Conference Dublin 23 Figure 5. Fracions of firs flush evens Meal Polluographs Figure 6 shows he measured meal concenraion profiles agains ime and rainfall and flow rae in he background (his ype of plo is known as a polluograph). As shown, he concenraions of Cu and Zn were consisenly greaer Ni and Pb Dissolved Cu (ug/l) 4 2 Toal Cu (ug/l) U CLA3, /2 4/ Fl ow Ra e Rai nfall (in) To a l Cu Disso lved Cu To a l Zn 2 Toal Zn (ug/l) 2 Dissolved Zn (ug/l) Dissolved Ni (ug/l) Toal Ni (ug/l) UC LA3, 2 / 7/ 2 F lo w Ra e R ai nfall (i n) T o a l Ni D isso lve d Ni T o a l P b D isso lve d P b Toal Pb (ug/l) 3 2 Dissolved Pb (ug/l) Time (min) Time (min) Figure 6. Typical polluographs for oal and dissolved Cu, Pb, Ni, and Zn during wo represenaive sorm evens The concenraions of boh dissolved and oal Cu and Zn also showed a general declining paern as sorms progress. As previously discussed, he monioring resuls also showed ha Cu and Zn are predominanly presen in he dissolved phase. This observaion was consisen during he enire monioring periods. For example, he dissolved Cu concenraion for sorm even /8/, was approximaely imes greaer han hose presen in he pariculae phase. For he same sorm even, he concenraion of dissolved Zn was approximaely 36 imes more han he pariculae Zn concenraion. Conrary o Zn, he concenraion of dissolved Pb in mos of he 2-2 samples were below he deecion limis (5 µg/l) and mos of he Pb concenraion in runoff samples was found o be in he pariculae phase. This phenomenon was also observed in sudies performed by Sansalone and Buchberger (997), and Legre and Pagoo (999). Unlike Pb, he amoun of dissolved Ni found in runoff samples was approximaely he same as hose found in he pariculae phase Facors Affecing EMCs and Mass Loadings Figure 7 shows he affecs of parameers such as average daily raffic (ADT), waershed area, aneceden dry days (ADD), sorm duraion (STORM -DUR), volume of oal rainfall (T-RAIN), volume of oal runoff (T-RUN), runoff coefficien (RC) and average rainfall inensiy(ari) on oal Pb mass loadings. The consan value for each predicor is summarized in Table 2. As indicaed, average daily raffic, aneceden dry periods, oal rainfall, and average rainfall inensiy are among he parameers ha affec oal Pb mass loading more han he oher parameers. I is imporan o noe ha ä value is highly dependen on aneceden dry periods, á and ã are relaed o oal runoff, and â is relaed o rainfall, runoff coefficien and sorm duraion. From our colleced daa, however, no significan correlaions among EMCs, mass loading and sorm characerisics could be observed. 4-43

7 A A B G D R T T S A A EA ER_ Diffuse Polluion Conference Dublin 23 ADT AREA ADD STORM_DURT_RAIN T_RUN RC DELTA GAMMA BETA ALPHA ARI Figure 7. An example correlaion plo of parameers affecing oal Pb mass loading Model Performance and Implicaions The washoff model is capable of predicing meal concenraions based on linear, exponenial, and gamma funcion using defined parameers. Figure 8(a) shows examples of measured and prediced meal concenraions for oal and dissolved Cu and Zn for sorm evens during December 4, 2. The prediced resuls by washoff model agree well wih measured resuls. Figure 8(b) compares he measured and prediced (model) resuls for oal Cu. As shown, a good fi for measured and model resuls was obained for oal Cu wih R 2 ranging from.8 o.95. The residuals, no shown in he figure, are unbiased. Meal polluan concenraions prediced by he washoff model can be used o predic even mean concenraions for differen sages of sorm evens. This new modeling approach will enable engineers o compue meal polluan mass loadings for specific porion of a sorm even (i.e., early sage) ha may be more pracical o rea han by reaing he enire runoff volume. Table 2. Summary of predicing variables used in washoff model o compue oal Pb mass loading Facors ADT AREA ADD STORM-DUR T-RAIN T-RUN RC δ γ β α ARI ADT AREA ADD STORM-DUR T-RAIN T-RUN RC δ γ β α ARI

8 Diffuse Polluion Conference Dublin 23 (a) (b) Figure 8. (a) Measured and prediced concenraions of oal Cu and Zn versus normalized flow (b) Correlaion beween measured and prediced oal Cu CONCLUSIONS A new washoff model was developed o predic mass emission raes of meals from highway runoff during firs flush. Several predicor parameers were inroduced in his model o esimae rapidly declining concenraions in he early par of he sorm as well as slowly declining concenraions in he laer par of he sorm. This new model can be calibraed based on prediced sormwaer runoff using esimaed rainfall volume and is no dependen on coninuous flow measuremen. The model can be used o esimae EMCs and mass loading raes. Major findings of his sudy were: Mos meal polluans showed firs flush on concenraion and mass basis. The range of meal concenraions from early sages of a sorm compared o he final sages of he sorm can be enfold. This large variaion can inroduce rare error ha is normally associaed wih oher modeling approaches. Mass firs flushes were also observed and classified as: high, medium and non-firs flush cases. Approximaely 8 percen of he sorm evens exhibied a high or medium firs flush. Among he predicor variables, iniial condiion variable (δ ) and runoff coefficien found o have he sronges influence on he meal washoff mass loading esimaion. Oher imp oran model variables were found o be average daily raffic, aneceden dry period, oal runoff volume and average rainfall inensiy. The resuls obained using washoff model was compared wih measured values and found o fi well for heavy meals wih R 2 ranging from.8 o.95. ACKNOWLEDGEMENT Financial suppor for his sudy was provided by he California Deparmen of Transporaion (Calrans), Division of Environmenal Analysis under conracs 43A4 and 43A73. REFERENCES Berrand-Krajewski J., Chebbo G. and Sage A. (998). Disribuion of polluan mass vs volume in sormwaer discharges and he firs flush phenomenon, Wa. Res., 32(8), Charbeneau R.J. and Barre M.E. (998). Evaluaion of mehods for esimaing sormwaer polluan loads, J. of Waer Environmenal Research, 7(7), Deleic A. (998). The firs flush load of urban surface runoff, Wa. Res., 32(8), Deleic A., Ashley R. and Res D. (2). Modeling inpu of fine granular sedimen ino drainage sysems via gully-pos, Wa. Res., 34(5), Deleic A.B. and Mahsimivic C.T. (998). Evaluaion of waer qualiy facors in sorm runoff from paved areas, J. of Environ. Engineering, 24(9), Driscoll E.D., Shelley P.E. and Srecker E.W. (99). Polluan loading and impacs from sormwaer runoff, Analyical Invesigaion and Research Repor, Vol. III, FHWA-RD-88-8, Federal Highway Adminisraion, USA. Geiger W. (987). Flushing effecs in combined sewer sysems, Proceedings of he 4 h In. Conf. on Urban Drainage. 4-46, Lausanne, Swizerland. Gupa K. and Saul A.J. (996). Specific relaionships for he firs flush load in combined sewer flows, Wa. Res., 3(5), Irish Jr. L.B., Barre M.E., Malina Jr. J.F. and Charbeneau R.J. (998). Use of regression models for analyzing highway sorm-waer loads, J. of Environ. Engineering, 24(), Kayhanian M., Kummerfeld S., Kim L-H., Gardiner N. and Tsay K. (22). Lier polluograph and loadgraph, Proceedings of 9h Inernaional Conference on Urban Drainage, Sepember 8-3, Porland, Oregon. Kayhanian, M., J. Johnson, H. Yamaguchi, and S. Borroum. (2). Calrans sorm waer managemen program, Sormwaer, Vol. 2, No. 2, pp Larsen T., Broch K. and Andersen M.R. (998), Firs flush effecs in an urban cachmen area in Aalborg, Wa. Sci. & Tec., 37(),

9 Diffuse Polluion Conference Dublin 23 Lau, S. L., M. Ma, M. Kayhanian and M. K. Sensrom (22). Firs flush of organics in highway runoff, Proceeding of 9 h Inernaional Conference on Urban Sorm Drainage, Sepember 8-3, Porland, Oregon... Legre M. and Pagoo C. (999). Evaluaion of polluan loadings in he runoff waer from a major rural highway, Sci. To. Environ., 235, Ma, M., S. Khan, S. Li, L.H. Kim, H. Ha, S. L. Lau, M. Kayhanian and Michael K. Sensrom (22). Firs flush phenomena for highways: how i can be meaningfully defined, Proceeding of 9 h Inernaional Conference on Urban Sorm Drainage, Sepember 8-3, Porland, Oregon. Osuch-Pajdzinska E. and Zawilski M. (998). Model of sorm sewer discharge, I: descripion, J. of Environ. Engineering, 24(7), Sage A., Chebbo G. and Berrand-Krajewski J. (995). The firs flush in sewer sysem, Proceeding of he 4 h In. Conf. on Sewer Solids-Characerisics, Movemen, Effecs and Conrol, 58-65, Dundee, UK. Sansalone J.J. and Buchberger S.G. (997). Pariioning and firs flush of meals in urban roadway sorm waer, J. of Environ. Engineering, 23(2), Sansalone J.J., Koran J.M., Smihson J.A. and Buchberger S.G. (998). Physical characerisics of urban roadway soils ranspored during rain evens, J. of Environ. Engineering, 24(5), Shaheen, D.G. (975). Conribuion of urban roadway usage o waer polluion, EPA 6/2-75-4, U.S. EPA, Washingon, D.C. Thornon R.C. and Saul A.J. (987). Temporal variaion of polluans in wo combined sewer sysems, Proceedings of he 4 h In. Conf. on Urban Drainage, 5-52, Lausanne, Swizerland. USEPA (995). Conrolling nonpoin source runoff polluion from roads, highways and bridges, U.S. EPA, Repor EPA- 84-F-95-8a, USA. Vorreier L. and Hickey C. (994). Incidence of he firs flush phenomenon in cachmens of he Sydney region, Naional Conf. Publicaion-Insiuion of Engineers, Vol. 3, , Ausralia. 4-46