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Water quality assessment and the problem of marine ecosystem stability

 

 

This chapter concisely describes some of the most salient aspects of water pollution and water quality assessment and its impact on the marine ecosystem. Section 9.1 provides some background on the sources of White Sea water pollution and the context of water quality degradation and marine ecosystem stability. Section 9.2 describes a dedicated assessment of the White Sea ecosystem as impacted by water quality changes. Section 9.3 summarizes the main results.

 

9.1 BACKGROUND

 

A consequence of industrial and economic activity in cities and towns located in the vicinity of the White Sea is the production of waste products eventually entering the marine environment through land and river runoff as well as atmospheric precipita- tion. The numerous pulp-and-paper factories in the cities of Archangelsk and Novodvinsk greatly contribute to the industrial contamination of the region (Troyanskaya et al., 1998; Yufit et al., 1998). The Kandalaksha aluminum industrial complex is one of the main sources of industrial pollution of the White Sea Basin (MREC, 1998). Another source of pollution of the White Sea arises from waste water coming from the nearby cities, towns, and settlements. According to the data of the Archangelsk Regional Environmental Centre (AREC), in 1997 91% of the entire volume of waste water was untreated and allowed into natural water bodies (rivers, lakes, and the White Sea proper). River runoff is the main pathway of pollutants into the White Sea, accounting for 95% of the entire volume of pollutants arriving in the sea. According to the data available for 1990-1994, 2,867-5,100 tons of oil products, 10-51 tons of phenols, 754-1,435 tons of deter- gents, and 6,297-1,246 tons of chlorinated pesticides are introduced annually into the White Sea (NDHMS, 1991, 1992, 1993, 1994, 1995). Long-distance atmospheric


 

transport also contributes to White Sea contamination (White Sea .. ., 1995). There are other sources of pollution, such as the inflowing Barents Sea water, ship cruising and accidents, etc. At the same time, it should be mentioned that by the end of the 1990s, the transport of pollutants to the White Sea had decreased considerably, especially with regard to synthetic surface-active substances (SSAS).

In general, the impacts of pollutants on marine biota can vary considerably. Depending upon the actual concentration of pollutants in the marine environment, they affect the indigenous zooplankton, phytoplankton, and bacterioplankton com- munities in different manners. The abundance of pollutants can be somewhat reduced due to a variety of natural processes: dilution, current transport, bottom deposition, chemical and biochemical decomposition, and removal due to the adsorption on bottom sediments. All of these processes are influenced by a number of hydrological and hydrochemical environmental parameters, such as turbulent mixing, sea roughness, currents, water temperature and salinity, skylight illumination, pH, alkalinity, concentration of nutrients and suspended matter, and land and river runoff chemical composition. In fact, there are numerous links and relationships, perhaps, even between one and the same pair of model components under various external conditions. This largely complicates the task of modeling in- water processes. However, in order to attain a reliable estimate of present - and especially future - alterations to the marine ecosystem, mathematical modeling of the marine ecosystem is indispensable.



In recent years, when describing the state of living systems, experts frequently concentrated on the capability of the targeted system to confront external impacts (or, more precisely, the impacts external for each subsystem constituting the entire system). Analyzing this property, one usually operates with terms such as robust- ness , sustainability , and stability . In spite of the terms being synonymous, it can be reasonable to speak about the sustainability of the ecosystem (or, at least, its biotic component: community, association, and population) on the basis of estimates of the stability of its individual characteristics, each being relevant to concrete properties of the system.

Ecological sustainability assumes the capability of a system to preserve the condition of equilibrium or the ability of a biological (ecological) system to retrieve the initial equilibrium state if the system s equilibrium has been disturbed. It is clear that the influence of some factors brings about insignificant changes in the structure and functioning of an ecosystem and its biocenoses, whereas other factors can cause considerable disturbances in some of the inter-relationships

inherent in the ecosystem, and consequently undermine its sustainability.

Thus, the problem of marine ecosystem sustainability is a central one in the contemporary ecology. In this connection, the major challenge consists of obtaining quantitative evaluations of impacts that are able to disturb the sustain- ability of the ecosystem under investigation. Such an evaluation of sustainability limits the requirements determining maximum permissible loads that should not be exceeded; otherwise, some of the parameters of the ecosystem could be altered so significantly that the ecosystem would be destroyed completely - equivalent to an ecological catastrophe.


9.2

Determining maximum admissible loads (MAL) is perhaps the most important and complicated problem facing the ecological assessment of anthropogenic impacts on marine ecosystems, with the problem being directly relevant to that of ecosystem sustainability.

 

 

9.2 ASSESSMENT OF THE WHITE SEA ECOSYSTEM

 

In order to assess the state of the ecosystem of the White Sea, we firstly collected available data from numerous sources mostly provided by the State Hydrometeor- ological Service. These data were then organized as dedicated databases on the hydrology and hydrochemistry of the White Sea, for the periods 1984-1986 and 1989-1990. A total of 700 stations provided these data. Apart from the data on seawater temperature, salinity and chlorinity, concentration and dissolved oxygen saturation, and pH and alkalinity, the database contains (for various stations and standard horizons) information on nutrients and pollutants proper. The relevant quantitative data on the following variables have been incorporated into the database.

 

Nutrients

1 Phosphate phosphorus.

2 Silicon.

3 Nitrite nitrogen.

4 Nitrate nitrogen. 5 Ammonia nitrogen.

 

Pollutants

1 Oil and oil products.

2 Detergents (SSAS).

3 Phenols.

4 Chlororganic pesticides.

4.1 Dichlorodiphenilotrichloroethane (DDT).

4.2 Dichlorodiphenilodichloroethylene (DDE).

4.3 Dichlorodiphenilodichloroethane (DDD)

4.4 Alpha-isomer of hexachlorocyclohexane (o:-HClCH) 4.5 Gamma-isomer of hexachlorocyclohexane (r-HClCH).

 

Thus, the total number of variables is about 13. These are either both nutrients and, in certain concentrations, pollutants (biogenic compounds), or water- contaminating substances (i.e., pollutants proper). To assess the level of pollution of water of the White Sea, we considered it necessary to use the water pollution (or contamination) index (WPI). To compare our data with the WPI values obtained by the Hydrometeorological Service, we suggested a more precise definition of WPI. In fact, below the WPI definition adopted by the Hydrometeorological Service is presented (Methodical Recommendations .. ., 1988). As stated in this document,


 

water quality assessment is presently hampered because it is based on a comparison of mean concentrations observed at water quality control stations using the estab- lished maximum permissible concentration (MPC) values for each individual con- stituent. As a result, various reference and information sources have to specify the monitored substances, the degree to which MPCs are exceeded for all cases, and so on. It becomes especially difficult if the tendency of water quality variation for a long-term period needs to be identified. If in one and the same water body, the concentrations of some constituents decrease and those of other ones grow, it becomes extremely difficult to assess the inherent water quality and reveal the pollution process dynamics. That is why the Hydrometeorological Service initiated an attempt of a complex assessment of water quality. The WPI data presently available have been obtained by the Hydrometeorological Service using this approach.

Although the above approach has more advantages than other complex evalu- ations, strictly speaking, such indices should not be called complex estimates of the ecosystem quality . An adequate index of the ecosystem state of a water body, including its biotic and abiotic constituents, has not been worked out so far. Never- theless, a simplified assessment, using the WPI, makes it possible to compare the water quality of various water bodies (independent of the presence of pollutants). This allows the perennial identification of tendencies in water quality variations, and provides a much better and simpler form of data presentation. The WPI for seawater is:

1 4 Ci

WPI = 4 MPC (9.1)

i=1

where WPI stands for the strictly limited number of indices (variables) having the largest values, independent of whether or not they exceed the MPC, including dissolved oxygen. For seawater, the WPI is calculated not for individual stations, but for control regions. To present water quality as a single estimate, indices inde- pendent of the limiting problematic parameter are chosen; if the substance concen- trations are equal, the preference is given to substances having a toxicological problematic nature. The degree to which the dissolved oxygen concentration exceeds MPC is calculated as a ratio: the norm/the content .

The MPCs of pollutants and environment state indices are listed in Table 9.1. Seawater quality classification according to the pollution index is given in Table 9.2 (Yearbook of the White Sea .. ., 1990).

To assess the quality of natural water, the Russian State Service of Observation and Monitoring of Environmental Pollution (RSSOMEP) uses, apart from the WPI, the following variables (Yearbook of The White Sea .. ., 1990):

 

• Weighted seasonal means of volume concentrations of oxygen and pollutants, calculated from the weighted mean concentrations for certain depths.

• Mean annual concentrations of pollutants, defined as averaged weighted means of seasonal concentrations.


9.2

Table 9.1. MPCs of pollutants and indices of the environment state of seawater.

Yearbook of the White Sea ... (1990).

 

Water bodies relevant to fisheries

 

      Ingredients and     Limiting     MPC High level of pollutant content Extremely high level of pollutant content
No. indices index (mg l-1) (mg l-1) (mg l-1)
Ammonium salt Toxicological 2.9
  (nitrogen)        
Nitrite-ion Toxicological 0.02 0.2 2.03
  (nitrogen)        
Nitrate-ion Sanitary-toxicological 9.1
  (nitrogen)        
Oil and oil Toxicological 0.0 1.5 5.05
  products        
5 Phenols Toxicological 0.001 0.030 0.10
Detergents Toxicological 0.1 1.0 10.0
Chlororganic Toxicological Absent 0.0001 0.0018
  pesticides        
Dissolved General requirements Not below: 3.0 3.0
  oxygen   Winter - 4.0    
      Summer - 6.0    
pH General requirements 6.5-8.5    

Criteria high level of contamination and extremely high level of contamination are established by the Russian Agency Goskomhydromet.

For these substances, whose presence in natural waters is not envisaged by the relevant normative documents, the Limited Allowable Level is conditionally established by the Goskomhydromet at the level of 0.01 mkg l-1.

 

Table 9.2. Assessment criteria of seawater pollution.

 

Water quality class     Characteristic     WPI WPI value variation (%) for revealing the tendency of seawater quality change
I Very clean WPI < 0.25 or
  II   Clean WPI = 0.25 0.25 < WPI < 0.75   > 50
III Moderately polluted 0.75 < WPI < 1.25 > 30
IV Rather polluted 1.25 < WPI < 1.75 > 25
V Polluted 1.75 < WPI < 3 > 20
VI Strongly polluted 3 < WPI < 5 > 15
VII Extremely polluted 5 < WPI > 10

 

• Minimum and maximum concentrations of pollutants and environmental char- acteristics observed during the period of control of marine water quality.

• MPC units showing by how many times given concentrations of pollutants exceed the respective maximum permissible levels.

 

The calculations were performed according to the following, somewhat different algorithms (options):

 

Algorithm 1. The algorithm calculates the weighted mean value for the station, and subsequently, the weighted mean for the region is obtained.

1 Proceeding from the initial data (i.e., the database for 1989), for each pollutant ( i), and each station (s), the weighted mean concentration of the pollutant is calculated:

 
+
N-1 r ci + ci 1 l


Cis= i=1


2 (hi+1 - hi )

hN - h1 (


 

9.2)


where i = 1 ... N, the number of the depth level and hi = depth in meters of the

i-th level.

2 From the calculated values of Cis, the mean concentration value of the i

pollutant is determined for the entire volume of water of a given region Cir:

1 ns

Cir= n Cis (9.3)

s s=1

3 In the studied region, for every pollutant and the dissolved oxygen concentra- tion, relevant Cir/MPC ratios are calculated (for dissolved oxygen, a reverse ratio is taken). The MPC values for various pollutants are assumed in accor- dance with Table 9.1. Dissolved oxygen, 6 mg/l (summer), 4 mg/l (winter); nitrites, 20 µg/l; nitrates, 9,100 µg/l; ammonia nitrogen, 2,900 µg/l; oil products, 0.05mg/l; detergents, 0.1 mg/l; phenols, 0.001 mg/l; and chlororganic pesticides, 0.01 µg/l (assumed for calculations).

4 Based on the calculations conducted under item 3, four maximum values of

Cir/MPC ratios are chosen, and the WPI for the entire region r is calculated:

1 4 ( Cir \


WPIr = 4

i=1


MPC


 

max


(9.4)


 

Algorithm 2. The algorithm calculates the mean regional value at a given depth, subsequently, the weighted mean for the entire water column is obtained. Algorithm 2 is analogous to Algorithm 1, but the calculations under item 1 follow those of item 2, which means that for each ith variable the mean values of Ciri are found for the ith depth. After that, the weighted mean concentration for the whole water column is calculated for the region r.


Sec. 9.3]


 

9.3
Conclusion 335


 

1 The mean concentration value of the ith variable is found for each depth and region - performed by averaging the respective concentrations over all stations and depths:

1 ns

Ciri= n Cisi (9.5)

s s=1

2 Based on the values obtained under item 1, the weighted mean value of the ith variable is found for the entire region:

N-1 r ciri + ciri 1 l


+

 

Cir= i=1


2 (hi+1 - hi )

hN - h1 (


 

9.6)


The subsequent steps follow items 3 and 4 of Algorithm 1.

 

The water pollution indices for the region, calculated according to the above two algorithms differ by not more than 10%, which is within the same limits of their difference from the data published in the Yearbooks by the Territorial Department of the Hydrometeoservice. Algorithm 1 has been adopted here for subsequent calculations since this algorithm closely complies with the approach by the Departments of the Hydrometeoservice.

The results of several options of calculations of the WPI for different areas of the White Sea for 1986 and 1984-1989 are presented in Figures 9.1-9.3 (see color section). Figure 9.1 shows the WPI values calculated for three water layers for individual regions in 1986: 0-10 m, 10-20 m, and 20 m-bottom. Figure 9.2 illustrates the WPI values for different months of 1986. Figure 9.3 presents the WPI values for several years for various regions of the Barents Sea.

It can be seen from the assessed WPI values that the cleanest waters are in the Gorlo and Voronka, and the least clean are in Dvinskiy Bay. Our qualitative estima- tions explicitly indicate that there are no very clean waters in the White Sea (WPI < 0.25), only relatively clean and moderately polluted waters (0.75 < WPI < 1.75). A more complete vision of the extent of water pollution is displayed in Table 9.2.

 

 

9.3 CONCLUSION

 

Studies of the main aspects of economic development of the White Sea region show that even with the most favorable scenario of economic development, accompanied by an increase in the regional maximum gross output, the emissions of industrial and municipal pollutants will not exceed 10-30%. Assuming that the ratio between the pollutant concentrations will remain constant, the WPI will change by 10-30%. The relevant quantitative estimations are given in Figures 9.4 and 9.5 (see color section). Based on the analyses of the results of the WPI calculations it might be stated that an additional increase in pollution of the White Sea water by 10-30% can


 

hardly lead to significant changes in its ecosystem, as these changes are at the limits of natural interannual variability.

Relatively serious consequences for Dvinskiy Bay are possible, but unlikely. The index of water pollution in each region of the White Sea will not exceed 3.0. It implies that the water quality will not be worse than class V (dirty). Therefore, in all probability, it will not lead to any serious environmental consequences for the White Sea in general nor its individual regions.


 


Date: 2016-03-03; view: 658


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