Ecology / 6. Environmental Monitoring

 

Ph.D. Proskurnin OA, Smirnov SA

Scientific - Research Institution “Ukrainian Scientific Research Institute of Ecological Problems”, Ukraine

Ph.D. Rybalova OV, Ph.D. Belan SV

National University of Civil Defense of Ukraine

Using Monte - Carlo method for assessment of environmental risk caused by wastewater discharges into a watercourse

 

One of the biggest environmental problems in economically developed countries is a contamination of water bodies (WB) by industrial, field, agricultural and municipal wastewater (WW). In a number of post-Soviet countries, particularly in the Russian Federation and Ukraine, in order to provide the contamination level above the safe one it is developed and approved standards of pollutants discharge. The standard of pollutants discharge is a limit mass of the substance, which is allowed to discharge into WW per unit time [1, 2].

Elaboration of the standard of pollutants discharge includes the calculation of allowable WW amount. The calculation is based on the assessment of WB condition at a fixed level of contamination. In the first phase the actual level of contamination is validated. A disadvantage of the current approach to solving this problem is the neglecting probabilistic nature of the content of pollutants in WW withdrawing into WB. In methodological literature instability of WW is determined only by the requirement to take into account an arithmetic mean value as the actual concentrations of substances [3, 4]. (In order to increase representativeness of the observation samples Ukrainian methodology [3] requires before averaging the concentrations exclude the minimum and maximum values). Overall, however, the calculation is rather deterministic: it defines the permissible concentration of substances in WW which, according to calculation, does not lead to exceeding the legally approved maximum of permissible concentration (MPC) of the substances in WB. Thus, to include the consideration of the probabilistic nature of WW is actual, as well as to consider the parameters of the probabilistic nature of WB condition in the zone of discharge influence. This will increasingly allow reflect the real nature of the process WB contamination.

The most perspective direction in solving this problem seems to be the usage of ecological risk assessment mechanism. According to the classical definition, risk is a measure of uncertainty, which can be assessed by probabilistic method [5] In practice, we use different criteria of this uncertainty. In most cases as an environmental risk we understand either the risk of adverse changes in the environment, or expectation of damage due to such changes [6]. Since in the rationing sanitation problems only a possible fact of exceeding the MPC in WW is taken into account without the analysis of its consequences for ecosystems and humans, it is advisable to use the first definition of environmental risk, i.e. to consider the risk as a probability of violation of environmental quality standards of WB due to WW discharge.

In [7] a method for calculating the permissible concentrations of substances in WW by environmental risk assessment is described. However, described mechanism was based on a significant assumption, that the concentration of the substance in WW regarded as a random variable is distributed according to the normal law. But this is true only if the process of formation of WW compounds is affected approximately by equivalent factors [8]. In the case of sanitation (including water treatment), this condition can not be met, and therefore it is necessary to provide an arbitrary law of substance concentration distribution of in WW. For this purpose a universal Monte Carlo method can be used, which was previously used to determine the risk of technogenic accidents at potentially hazardous facilities [9]. In this paper we consider the use of Monte Carlo method for estimation of the probability of exceeding the MPC in WB below the WW discharge. The problem is considered on the example of a conservative pollutant.

The basis of the Monte Carlo method is based on the following mathematical regularity [10]. If there is a random variable x, then its distribution function F(x) can also be considered as a random variable. In this case, regardless to the law of initial value x distribution the value of F(x) is uniformly distributed on the interval [0 , 1]. This implies that the possible values x may be derived from the equation

,                                           (1)

where a  is  lower boundary of determining the value x; p(x) is density of distribution; wÎ  [ 0 , 1] - uniformly distributed random variable .

Equation (1 ) of each realization of the random variable wÎ  [ 0, 1 ] puts in one correspondence the realization of x , distributed according to given law F(x). This allows to simulate the behavior of a random variable x by generating a random number value w.

Applied to the problem of environmental risk assessment this pattern can be used as following. If we represent a risk indicator I as a function  and generate several times the value wiÎ [0, 1], i=1÷N,  by the sample  we can judge about the distribution of I. In particular , the sample allows to calculate the non-exceedance probability of a given value .

In this problem  as a risk indicator serves the concentration of conservative substance in control section (CS) , which is expressed by a balance equation

,                                                      (2)

where Сфон, С, Скс  is concentration of the substance in the background section respectively (BS ) above WW discharge, in WB and in ; Qфон, q - , respectively is a water flow rate in the BS and  WW flow rate.

Concentration of C  in the right side of equation ( 2) is a random variable which may be represented as an argument of the distribution function , i.e. as. w- quantile (Fig. 1) .

 

Figure 1 - Representation of the C concentration in the form w- quantile

 

In this case, the risk indicator is presented as a function of w:

 

 

where F-1 -  is the inverse function of the distribution function F(C).

In practical problems, the function F(C) can be constructed empirically according to field observations, followed by smoothing.

Below is a demo, which is based on developed and approved standard of municipal WW discharge in Alushta (Crimea) in the river Ulu Uzen (small river of Crimea) [11]. As an indicator of pollution in this example ammonia nitrogen is considered. Table 1 shows the content of the substance in WW after refining at biological wastewater treatment plants.

 

Table 1 - The content of ammonia nitrogen in municipal WW in Alushta in 2009

Month of Year

1

2

3

4

5

6

7

8

9

10

11

12

Concentration of C , mg/dm 3

0,86

0,79

0,62

1,20

0,65

0,62

0,52

0,78

0,61

0,74

0,77

0,78

 

Design conditions for determination of ammonia nitrogen maximum concentration in WW has been adopted as the following [11] :

- Water flow in the FS Qфон = 0.03 m3 / s;

- WW flow q = 0,02 m3 / s;

- concentration of ammonia nitrogen in the FS Qфон = 0.05 dm 3 ;

- MPC of ammonia nitrogen (at the moment of standards elaboration) 0.39 mg/dm 3.

In the paper [11], the calculation of allowable concentration was conducted in accordance with the existing procedure [3] excluding the probabilistic nature of the substance concentration in WB and without environmental risk assessment . As allowable concentration it was adopted estimated actual concentration (mean value, excluding the maximum and minimum values) , equal to C = 0.720 mg/dm 3. Adoption of the actual concentration as permissible due to the fact that the concentration does not result in exceeding the maximum permissible concentration in CS. Due to the short distance between the WW discharge and the CS we can neglect the water self-cleaning. Then the concentration of the substance in the CS is

 

 

In order to assess the environmental risk on the base of Table 1 it was built the empirical distribution function F(C) followed by a linear smoothing (Fig. 3) . Level of risk acceptability is assumed to be 0.05.

 

Figure 3 - The empirical probability distribution function of the concentration C

 

The result of calculation of the random variable Скс for N = 10000 is the following : in 91115 cases Скс £MAC; in other cases - Скс > MPC. Thus, the probability that the concentration of ammonia nitrogen in the CS will exceed MPC makes (10000-91115) / 10000 » 0,09. Consequently, the value of considered environmental risk exceeds acceptable level .

Fig . 4 shows a histogram of the value Скс distribution.

 

Figure 4 - Histogram of the value Скс distribution

Conclusion. The proposed algorithm for environmental risk assessment, which is based on the Monte Carlo method , allows us to calculate the probability of non-exceedance concentration level of a substance in the WB in the zone of WW discharge influence. In speculating process the law of concentration distribution in the WW was taken arbitrary , the method of risk assessment can be attributed to the non-parametric .

It should be noted that the adoption of an acceptable level of pollution in MPC is not critical in terms of the calculation algorithm. As the acceptable level of contamination it can be accepted an environmental standard for water bodies, which is defined as the upper limit of the third category of water quality according to the classification of surface water quality [12].

Subject for further research is the complication of the problem in terms of assessing the WW discharge influence directly on human health.

 

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