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Investigation into heavy metals in storm wastewater from Vilnius Zirmunai district and pollutantits spread model in Neris river/Sunkiuju metalu kiekiu tyrimas lietaus nuoteku isleistuvuose nuo Vilniaus Zirmunu rajono ir ju sklaidos modelis upeje.

1. Introduction

Urban environment is a complicated system, because 70-90% of all the soil lies under the streets, pedestrian paths, buildings and therefore, its natural environmental recovery takes a lot of time, a natural energy and material circulation are destroyed. Street surface could protect soil from pollution like a filter, however natural filtration disappears and in this way, pollutants, heavy metals in this case (zinc, copper, lead, manganese, nickel, chrome) from the streets flow to the waste pipes and directly to the rivers (German et al. 2002]). Zinc (Zn) keeps in soil up to 70-510 years, cadmium (Cd)--13-1100 years, copper (Cu)--310-1500 years, lead (Pb)--749-5900 years (Jankauskaite 2002; TaraSkevicius et al. 1998). Heavy metals cannot ruin or be destroyed, they accumulate in living organisms and have a harmful influence on human beings and living organisms and water biota (Lee et al. 2006; Brannvall et al. 2007).

One of the major pollutants in the city is transportat. Large amounts of transport pollutants go directly on the streets and around the driving part of the road (Juceviciene 2003; Csereklye 2010). Most of the heavy metals from transport spread through flue gas, oils (during accidents), wearing tires and brakes, deteriorating street surface (Davis et al. 2001; Sorme et al. 2002).

The main goal of the investigation is to determine through experiment, the pollution of uncleaned storm wastewater, outflowing into the Neris river through outflow pipes, with heavy metals starting from Zirmunai district and make a model for pollutant spread in the river stream.

2. Investigation methodology

For performing a test for heavy metals concentration in storm wastewater outflow, the researchers chose Zirmunai district in Vilnius city with the biggest number of inhabitants (Fig. 1). For acquiring the relation between storm wastewater outflow and those of heavy metals from the vehicles, the street sweeping samples from the street points having the greatest amount of vehicle flows and sludge samples from the outflow pipes in Zirmunai district are taken. The samples taken are studied at research lab in the Department of Environmental Protection at VGTU according to methodology: "Measuring the concentration of heavy metals in the sewage, soil, ground and sludge with a flame atomic absorption spectometry".

Dried samples are sieved through Retsch AS200 sieves up to 1 mm sieve. Each sample is weighed by 0.500 g each and reduced with a 12 ml nitric acid (HN[O.sub.3]) and hydrochloric acid (HCl) solution with an appropriate proportion 1:3. Ready-made samples are mineralized with Milestone Microwave. After the mineralization process, sample solutions are diluted by 50 ml distilled water and analyzed with flame atomic absorption spectrometer Buck Scientific 210 VGP.


3. Investigation results

Concentration of heavy metals (Cr, Zn, Mn, Ni, Pb, Cu) (mg/l) in street sweeps (Fig. 2) and in sludge from the storm wastewater outflow pipes (Fig. 3) are measured with a flame atomic absoprtion spectrometer.

The highest concentrations are those of Mn, Zn, Cu (in street sweep) and Pb (in sludge). According to the hygienic norms (HN 60:2004) heavy metals in street sweeps and sludge exceed the norms 11 times (Table 1).

According to the data analyzed, concentration of heavy metals in street sweeps have no direct dependency on transport intensity. It is clearly indicated in Fig. 4, where the concentration of the major heavy metals Zn and Mn in street sweep are presented subject to transport intensity.


Consequently, concentration of heavy metals in street sweeps depends on the surrounding environment (green zones, surrounding companies and industry, fuel, vehicle repair shops), frequency and time of vehicle stops because of the traffic jams and crossroads, driving speed, number of accidents, frequency of street sweeps works (sweeps export). Part of heavy metals get to streets from roofs (Cu, Zn, Pb), wearing street surfaces. A general concentration of heavy metals (general pollution) in Zirmunai geographical territory is presented in Fig. 5. The highest rate of pollution is seen around points 6 and 9. These points are close to the Neris river valley. Close points are car parking lot, car repair shop, administrative buildings, electricity company--in comparison with other points, the latter streets are rarely swept or almost never swept (point 6), karting field, administrative and residential houses, fuel station (point 9). The higher concentration of heavy metals lies in the northern part of Zirmunai. The lowest concentrations are at points 11 and 14. Around these points, there are crossroads without traffic light-control, however, there's a market, residential houses, many trees (point 11), administrative buildings, fuel station, supermarket and streets are often cleaned (point 14).


Generalized concentrations of heavy metals in street sweeps from different points and in sludge from outflow pipes are given in Table 2. Every analyzed point with samples taken belongs to different sewage collection pool, where the water is released to the river. A more detailed information on transport quantity flows and sampling points for eacht pool is also given in Table 2.

The highest concentration of heavy metals is found in outflow pipes 1, 4 and 7. Outflow pipes 1 and 7 are installed near bridges. The named three pipes belong to the pools with intensive transport.


4. A model for the spread of pollutants in the river

Phoenics 3.5 program (acronym: Parabolic Hyperbolic Or Elliptic Numerical Integration Code Series), belonging to CHAM (Concentration Heat and Momentum Limited) is applied to constitute a model for determening the heavy metals concentration in the Neris river stream. This is a powerful Computational Fluid Dynamics (CFD) software presenting qualitative info on:

* How the fluids flow (air, water, steam, oil, blood, etc.) in equipment and around, for example in:

** engines,

** buildings,

** human body,

** rivers, lakes, oceans, etc.;

* how the composition of chemical and physical medium changes;

* how the forces influence the submerged bodies.

Phoenics program depends on three major functions:

1. task making (pre-processing), where the user describes situation to be solved;

2. modeling (data-processing), where the program calculates the determined conditions by the laws of science;

3. data provision (post-processing), where calculation results are provided in a graphical form (PHOENICS Overview ... 2007).

Program for modeling solves a differential equation by Navie-Stocks (1) (Baltr?nas et al. 2004, 2008; Ruther et al. 2005):

div([rho][??][PHI] - [[GAMMA].sub.[PHI]]grad[PHI] = [S.sub.[PHI]], (1)

where: [rho]--thickness kg/[m.sup.3]; [PHI]--dependent variable (enthalpy, power of turbulence, etc.); [??]--speed vector; [[GAMMA].sup.[PHI]]--[PHI] variable diffusion coefficient (coefficient of kinematic viscosity of movement equations, difussion coefficient of diffussion equations); [S.sub.[PHI]]--[PHI] member of variable flow rate equation.

A model for the spread of heavy metals in the Neris river from six storm wastewater outflows is made. Computerized modeling system--a tool for determening water quality when the pollutants get to the river.

Modeling process starts at the task window (Phoenics Commander Window), where task data are entered in to Q1 file.

The required data for making a model for the Neris river:

* size of the river (domain):

x--width 40 m (Neris is 80 m wide, but in this case, only half of the river is analyzed in Zirmunai district),

y--depth 3 m,

z--length 4000 m in Zirmunai district, while a segment taken for this model is 200 m;

* water pressure P = 1.0 x [10.sup.5] Pa;

* water density p = 9.98 x [10.sup.2] kg/[m.sup.3];

* river speed V = 1 m/s;

* water speed from the outflow pipes W = 2 m/s;

* concentration C (mg/[m.sup.3]) of heavy metals (Pb, Mn, Cr, Zn, Cu, Ni).

After filling the Q1 file and before the program makes calculations, information should be read with Phoenics Satellite. Information is transferred in this way to the Satellite. Before providing a graphical representation of results, equations are solved with the help of Solver (Jankaite 2009; Paliulis 2006; Phoenics ... 2008).

For making the model, friction power, when the speed of water in the river V is close to zero beside the shore line and on the water ground, is considered. In this model, the total concentration of heavy metals from each outflow pipe and spread of pollutants analysed by the direction of river flow is taken.

Fig. 6 shows heavy metal spread in the river from the outflow pipe 1 (outflow 1) with the highest concentration. The background of concentration is seen until the 30 m distance. At a 23 m distance the concentration reaches around 2 m depth, but it is around 8 times smaller. The highest concentration spreads up to 6-7 m of the river length and 0.4 m depth.


From the outflow pipe 3 (outflow 3) spread of pollutants is hardly visible, because concentration of heavy metals here is the smallest. At this point, concentration of pollutants stops spreading after 4-5 m length to the direction of river flow and spreads up to the depth of 0.3 m (Fig. 7).

Spread of pollutants from all the outflow pipes is shown in Fig. 8. Spread of pollutants grows together with the river flow and in this way pollutants spread in the river depth and width, therefore the named model shows a smaller background of concentration from the first outflow pipes. Pollutants move downstream because of advection and concentration decreases because of their spread and mixing with water. From the third outflow pipe concentration reaches river ground where the heavy metals accumulate in the sludge, living organisms and do not disappear from the natural cycle.

Distance of the spread of pollutants depends on the turbulance, water vortex, speed. The Neris river debit is 116 [m.sup.3] /s, pollutants are flown about 600 m in a day, it means about 25 m an hour (Pollution of ... 2008).



5. Conclusions

1. According to the experimental model data, by performing a flame atomic absorption spectrometry method, heavy metal concentration in street sweep, as determined from the sweep out of intensive transportation points in Zirmunai district, directly depends on transport amounts. Heavy metals concentration in street sweep from the streets is influenced by the nearby residing companies, oil stations, car repair shops, other buildings, frequency of car stops and their speed, street cleaning frequency, greenery.

2. Heavy metals concentration from the storm wastewater outflow pipes depends on the pollution level and car quantity in that pool, which itself falls into another pool.

3. The highest concentrations measured are Mn, Zn, Cu (in street sweep) and Pb (in sludge). According to the Hygienic standards HN 60:2004 (Highest permissible concentrations of hazardous chemical substances in the soil) heavy metals in street sweep and sludge exceed the permissible levels 1.1-11 times.

4. Average concentration of every heavy metal Pb, Mn, Cr, Zn, Cu, Ni in street sweeps is 2-3 times higher than in sludge from the outflow pipes.

5. The analysed heavy metals Pb, Mn, Cr, Zn, Cu, Ni from storm wastewater outflow pipes without any cleaning fall directly to the river and flow by the direction of the river. Concentration of pollutants, as the model shows, decreases because of turbulance.

doi: 10.3846/jeelm.2010.28


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Saulius Vasarevicius (1), Asta Mineikaite (2), Petras Vaitiekunas (3)

Dept of Environmental Protection, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania

E-mail: (1); (2); (3)

Submitted 3 June 2008; accepted

Saulius VASAREVICIUS. Dr Assoc. Prof. (since 1999), senior research worker, Institute of Environmental Protection, Vilnius Gediminas Technical University (VGTU). Doctor of Science (environmental engineering), VTU (now VGTU), 1995. Master of Science, VTU, 1991. First degree in Civil Engineering and Management, Vilnius Civil Engineering Institute (VISI, now VGTU), 1989. Publications: author of more than 30 research papers and monographs. Probation in Germany. Research interests: environmental management, air pollution, waste management.

Asta MINEIKAITE. Master (Environmental Management and Cleaner Production Program), Dept of Environmental Engineering, Vilnius Gediminas Technical University (VGTU). Bachelor of Science (Environmental Engineering), VGTU, 2006. Research interests: water pollution, environmental management.

Petras VAITIEKUNAS. Dr Habil. Prof. of Dept of Environmental Protection, Vilnius Gediminas Technical University (VGTU). Doctor Habil of Science (energy and thermal engineering) Lithuanian Energy Institute, 1999. Doctor of Science Laboratory of Fluid Dynamics in Heat Exchangers Lithuanian Energy Institute, 1972. Employment: Professor (2002), Associate Professor (1997). Publications: author of 1 monograph, 2 educational books, over 230 research papers. Work on probation: Prof D. Brian Spalding, Concentration, Heat and Momentum Limited, Bakery House, 40 High Street, Wimbledon Village, London SW19 5AU, UK (PHOENICS 1.4 EP CFD), January- February 1996, and (PHOENICS 3.1 VR CFD), April-May 1998. Membership: prize-winner of the Republic of Lithuania (2006), a corresponding Member of International Academy of Ecology and Life Protection. Research interests: hidrodynamics, convective heat and mass transfer and thermophysics, computational fluid dynamics, mathematical modeling of transfer processes in the environment.
Table 1. Heavy metals excess in samples by MPC

                              Sweeps from street

   MPC          Cr        Zn       Mn        Ni      Pb       Cu
 (mg/kg)       100       300      1500       75      100      100

                                   no exceed

Background      30        26       427       12      15       8.1
   MPC      in 1 point  to 11x  no exceed   to 3x   to 5x   to 11x

                              Sludge from outflows

MPC (mg/l)      Cr        Zn       Mn        Ni      Pb       Cu
               0.5       0.4       --        0.2     0.1      0.5
            no exceed   to 4x      --      to 1.5x  to 4x  no exceed

Table 2. Heavy metals concentration in outflow and pollution in each

               Pollution evaluation by          Points No. of
Outflow      sumarized heavy metals from       sweep analyses
  No.              outflow (mg/l)             which belongs to
          Cr    Zn    Mn    Ni    Pb    Cu

   1      0,2   1,5   4,4   0,3   0,4   0,1     2        3
   3            0,4                     0,2     1        5
   4      0,2   0,5   1,9   0,3   0,4   0,2   4   6      7
   5      0,1   0,5   1,8   0,2   0,3           8        9
   6      0,2   0,4   2,2   0,2   0,3   0,2          12
   7      0,2   1,1   1,6   0,2   0,4   0,3   10   11  13  14
  MPC     0,5   0,4         0,2   0,1   0,5

               Pollutution evaluation by
Outflow        sumarized heavy metals in
  No.                sweeps (mg/l)

          Cr     Zn    Mn    Ni    Pb    Cu

   1      0,6   2,5    2,9   0,4   0,5   1,4
   3      0,6   2,3    2,5   0,3   0,7   0,8
   4      0,8   6,5    3,8   0,8   0,7   1,5
   5      0,5   4,0    3,5   0,4   0,7   2,0
   6      0,2   0,9    1,3   0,2   0,1   0,4
   7      0,7   12,4   5,1   0,7   3,6   1,9
  MPC     0,5   0,4    --    0,2   0,1   0,5

Outflow   Automobiles quantity in      automobiles
  No.     street points (unit/hour)  quantity in peak
                                      points of each

   1         186         533               719
   3         483         191               674
   4      387   315      203               905
   5            308       97               405
   6               312                     312
   7      216   135   250   543           1144

Cells in grey exceed MPC and have maximum values of transport

Empty cells--results are above confidence interval

Fig. 3. Heavy metals concentration in outflow *Comment. There are
gaps in outflow 3 of Ni, Cr, Mn, Pb and 5 of Cu, because results
are above confidence interval

     Cu     Ni     Cr     Zn     Mn      Pb

1   0,06   0,30   0,24   1,48   14,37   0,41
3   0,18                 0,37
4   0,38   0,29   0,21   0,52    1,93   0,41
5          0,20   0,13   0,51    1,83   0,27
6   0,12   0,30   0,19   0,36    2,25   0,33
7   0,34   0,28   0,21   1,12    1,57   0,35

Note: Table made from bar graph.
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Author:Vasarevicius, Saulius; Mineikaite, Asta; Vaitiekunas, Petras
Publication:Journal of Environmental Engineering and Landscape Management
Geographic Code:4EXLT
Date:Sep 1, 2010
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