A framework for monitoring, modelling and managing water quality in the Forth Estuary, Scotland

Journal of Environmental Management (1991) 33, 311-325

A Framework for Monitoring, Modelling and Managing Water Quality in the Forth Estuary, Scotland Ian Moffatt,* Nick Hanleyt and Stephen Hallett$ *The Australian National University, NARU, P.O. Box 41321, Darwin, N.T., Australia, tDepartments of Environmental Science and Economics, University of Stirling, Stirling, Scotland FK9 4LA, U.K. and ~Soil Survey and Land Resource Centre, Silsoe Campus, Silsoe, MK4S 4DT, U.K. Received 25th June 1990

A framework for monitoring, modelling and managing water quality in the Forth estuary, Scotland, is presented. The data on over 200 determinands was kindly supplied by the Forth River Purification Board and is contained in a relational database. A description of the detailed analysis of some of the physical-biochemical parameters of water quality is given. In particular, the possibility of building dynamic simulation models and integrating these with sophisticated geographical information systems (GIS) is outlined as part of the integrated framework being developed by the research team. The third aspect of the study is to integrate alternative management decisions into the investigation of water quality in the Forth estuary. A distinctive feature of this research is the attempt to explore various economic options such as transferable discharge permits, and their impact on water quality, rather than rely solely on consent agreements. Again, the ways in which these economic incentives are embedded in the framework are discussed. Finally, the progress in this research which is directed at monitoring, modelling and managing water quality in the Forth estuary is discussed.

Keywords: water quality, relational database management systems, dynamic simulation modelling, geographical information systems, economic optimization. 1. Introduction One of the major problems often confronting interdisciplinary research is to try to achieve a balance between basic scientific research and policy orientated work. For scientists, basic research attempts to develop, articulate and refine a theoretical explanation of a particular system of interest in order to understand the ways in which that system functions. In policy or strategic research, however, the main aim of the work is to provide information, often on a series of alternative scenarios, added to control or regulate the system of interest for the relevant decision-makers. In the case of water quality, it is abundantly clear that both basic research and policy orientated work is 311 0301~4797/91/080311 + 15 $03.00/0

9 1991 AcademicPress Limited

Water quality in the Forth estuary, S c o t l a n d

312

required, at least if we are to contribute to providing a better environment for present and future generations. Current, on-going research at Stirling, funded by the Economic and Social Research Council (ESRC), is attempting to develop an integrated framework for monitoring, modelling and managing water quality in the Forth estuary, Scotland. The purpose o f this paper is to describe the progress in attempting to combine the environmental and economic considerations of water quality in the management of a major Scottish estuary. In a sense this is a report on the progress to date in achieving a balance between basic scientific and strategic orientated research. The Forth estuary, like other industrialized embayments, is a complex environmental system. This system includes both physico-ecological processes as well as socio economic uses of the water resource. These processes combine to affect the quality of the water in the estuary. The Forth estuary itself is defined as the area of land and water located between the Forth rail bridge and the road bridge at Stirling (Figure 1). This definition corresponds to that used by the Forth River Purification Board (FRPB) (McClusky, 1987). Over the last two decades, more than 180 papers have been published on various aspects of the environment o f the estuary. Less than 5 % of this total has been concerned with monitoring, modelling and managing water quality of the estuary (Hallett et al., 1989a). Increasingly, however, new demands are being placed on the estuary and these may affect both current water quality and also future uses of the resource base. It is, therefore, important that a framework is established which can be used to integrate monitoring activities and simulation modelling, including the use of geographical information systems (GIS), to replicate the behaviour o f the physico ecological changes in the estuary and to explore the impact of different management strategies aimed at improving the quality of water in an ecologically sound and economically efficient manner.

,~Stirl!ng Upper estuary ~'-~,. ~-~ i ~ //~~

/ estuary

f

h

~ Firthof Forth .......

Ga

r-omourgn

0

5

I0

15

20

Figure 1. Location of the Forth estuary. (Source: Forth River Purification Board.)

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2. Monitoring

There are many definitions of pollution. In this paper, however, pollution will be defined as the introduction into an estuarine environment, by humankind, of materials which would not normally be found in that situation or would not, without their intervention, be present in the same concentration (Helliwell and Bossanyi, 1975). The causes of pollution in estuaries include: polluted rivers entering the estuary; industrial and sewage effluent discharges into the estuary or coastal water; dumping of waste material offshore; escapes from vessels afloat; the intentional discharge or escape of sewage, sludge and industrial waste from long pipe outfalls; toxic substances drifting in-shore from nuclear and industrial plants; and airborne deposition of pollutants into the estuary (Wisdom, 1975). In order to ascertain the type and concentration of pollutants in an estuary, it is essential to monitor the changing water quality. As Lewis and Stephenson wrote, "monitoring is considered essential for establishing baseline data so that the significance and cause of variations in the condition of the estuary can be properly judged" (Lewis and Stephenson, 1975). Water quality in the Forth estuary is monitored regularly by the Forth River Purification Board (FRPB). Their monitoring involves water- and land-based sampling as well as the use of an automated telemetric buoy which sends data via satellite links to a mainframe computer for storage in a relational database. The use of other forms of monitoring by remote sensing have been advocated and used in several estuarine studies, but were not available in this particular study (Lo, 1986). Hence, much of the monitoring is taken from field sampling by the FRPB and the automatic buoy (Webb and Metcalfe, 1987). The research team would like to thank colleagues in the FRPB for their support in this aspect of the research project. The data set collected and collated by the FRPB is held in an O R A C L E relational database management system (RDBMS). Data is accessed through the use of the SQL (structured query language) (Schmidt and Brodie, 1983; Gittings and Healey, 1987; Sayles, 1989). The tidal waters data set is held in a database named T C H E M (tidal waters chemistry). This data set contains information on some 200 determinands recorded in the estuarine waters of the Forth over several years. The details of the purpose of the surveys, and the frequency and the duration of the data collected in this on-going monitoring operation are also stored in the database (Table 1). This database has been used as the basis for the FRPB Annual Reports as well as for more detailed scientific papers (McClusky, 1987; Hallett et al., 1989a,b). A three-fold typology of pollutants in the Forth estuary has been produced (Table 2). For each of these parameters, simple descriptive statistics were used to show variation over time, including the maximum and minimum values, the mean, median, 5% trimmed mean, standard deviation and standard error of the mean for the parameters, for every time period for all sampled sites. In some cases, the data were collected over a long time period and it was therefore possible to plot and analyse the data as a time-series. An example of the ways in which the data can be portrayed and analysed is given in Table 3 and Figure 2 (see Hallett et al., 1990, for a detailed report). In general terms, however, at each station or site, several of the determinands are recorded at precise times at several depths. These data are then transferred to the relational database so that the details of each sample can be readily ascertained prior to the laboratory analysis. The locations of over 40 water quality monitoring sites operated by the Forth River Purification Board (FRPB) have been recorded using a geographical information system (GIS) (LASERSCAN and the IBM PC compatible-based system IDRISI). Mapping of the results was conducted using the mainframe application U N I M A P , part of the

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Water quality in the Forth estuary, Scotland

TABLE 1. A summary of the surveys undertaken by the FRPB in the Forth estuary Survey name

Purpose of survey

Begun

Frequency of survey

Forth Estuary Water Quality

To assess the chemical status of the waters Assess chemical status of the waters of the Firth Check compliance with EEC directive of designated waters Assess seasonal trends and export of materials Provide continuous record of water quality near Alloa Compliance with EEC directive

1957

18 per annum

1977

Yearly

1981

Quarterly

1987

Weekly

1987

Servicing visits

1985

4 per annum

Check compliance with DOE EQS for List II substances Monitoring, compliance with EEC directives Provide water quality data for predictive model Assess physico-chemical status Assess physico-chemical status of sediments Determine "hot-spots", assess long-term changes Assess concentrations in flounder and eelpout EQS compliance with PCP, Cd and Gamma-HCH Assess area affected by LVS discharge in terms of PCP To check EQS compliance of PCP discharge from Caldwells PM Long-term plankton survey Assess chemical status of estuary waters

1985

4 per annum

1983

4 per annum

1986

4 during summer

1979 1979

Every 2 years Every 2 years

1981

Yearly

1981

Annual

1987 1988

4 per annum (ex. PCP) Undecided

1988

12 per annum

1981 1957

2 per week Periodic

Firth of Forth Water Quality Firth, Shellfish Waters Bridges Water Column Water Quality Monitoring Stn Cadmium Directive Shore Sampling Inner Firth of Forth Metals Lower Estuary Trace Metals River Carron Surveys Estuary Sediment Survey Seafield Sediment Survey Mussel Watch Mercury in Indigenous Fish Largo Bay: Directive Monitoring Leven Valley Sewer PCP Survey Inverkeithing Bay PCP

Port Edgar Pier Survey Forth Estuary Shore Survey

Source: data extracted from FRPB TCHEM database. U N I R A S software suite. An analysis of the consent agreements, i.e. the maximum permissible emission of pollutants to enter a water body, has identified the major point sources of pollution entering the estuary, which have also been added to the GIS. By using kriging techniques and the GIS, some of the point source patterns of pollution have been "spread" throughout the estuary to give a crude surrogate impression of the three-dimensional spread of specific pollutants in the Forth estuary. Obviously, great care has to be taken in using these data as there are inevitably variations in the original data, and there must be further inaccuracies when spreading the data to form a threedimensional image of the pollutants in the estuary. I f these limitations are borne in mind,

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TABLE 2. Classification of parameters used in the Forth estuary study Physical-biological

Nutrients

Trace metals

Salinity Temperature Dissolved oxygen Biological oxygen demand Chlorophyll Suspended solids

Nitrate Nitrite Ammonia Phosphate Silicate --

Zinc Copper Nickel Lead Cadmium --

TABLE 3. Descriptive statistics of biological oxygen demand at Bannockburn N

N*

85

1

Mean Median T R M E A N 2.647

2-300

2.579

STDEV

SEMEAN

Min

Max

Q1

Q3

1.196

0-130

0.700

6.300

1-750

3.550

Notes. The readings analysed were at a depth of 2 m and were taken between the Julian dates of 2444267 to 2447742. TRMEAN is the 5% trimmed mean; SEMEAN is the standard error of the mean, [STDEV/ SQRT(N)]; Q1 and Q3 are the first and third quartiles, respectively. TABLE 4. An example of a materials balance approach Pollutant type

Transfer coefficients

Section of the estuary

Water flow-arbitrary units

B-type

C-type

B-type

C-type

1. River 2. Reach 2 3. Reach 3

450"0 475.0 525.0

2-4 2.8 (1.18) 3.0 (0-65)

400.0 410.5 399.5

0-143 ( - 1.03) 0.067 ( - 0 - 8 2 )

-0.026 -0.028

Note. See text for an explanation--note that all "flows" are in arbitrary units; the terms in parentheses are due to the decay of the B-type pollutants.

t h e n the d a t a represent the best a v a i l a b l e i n f o r m a t i o n for this research project. A s d a t a b a s e s b e c o m e m o r e readily a v a i l a b l e for d e t a i l e d r e s e a r c h using G I S a p p l i c a t i o n s , t h e n it is essential t h a t care is t a k e n in a s c e r t a i n i n g the reliability a n d integrity o f the d a t a - - t o g e t h e r with the strengths a n d weaknesses o f the s a m p l i n g f r a m e s a n d the a c t u a l m e a s u r e m e n t ( M a c M i l l a n , 1989; O p p e n s h a w , 1989). F r o m the b r i e f analysis o f the d a t a on v a r i o u s p o l l u t a n t s in the F o r t h estuary, it can be o b s e r v e d t h a t the levels o f all o f the p o l l u t a n t s tested fall well b e l o w the c u r r e n t E n v i r o n m e n t a l Q u a l i t y S t a n d a r d s (EQSs) a n d the c u r r e n t E E C directives ( p e r h a p s with the exception o f those o f the R e d List s u b s t a n c e s - - b u t s o m e o f these are still to be carefully m o n i t o r e d ) . O n e n o t a b l e e x c e p t i o n is the level o f e s t u a r i n e dissolved oxygen, which, d u r i n g p e r i o d s o f high e n v i r o n m e n t a l stress ( s u m m e r low flow conditions), often sags b e l o w the E Q S o f 4.5 mg/1 at a p o i n t some 18-20 k m d o w n s t r e a m f r o m Stirling Bridge. This s i t u a t i o n is p r o d u c e d b y a c o m b i n a t i o n o f several p o i n t source discharges entering the e s t u a r y at this p o i n t - - t o g e t h e r with relatively low localized d i l u t i o n a n d dispersal rates. It is clear that, as M a c k a y (1975) writes "the pollution of estuaries results mainly from activities on land, including industrial processes, methods of sewage treatment, and specific planning policy and it can only be reduced and controlled at these levels. This simple and obvious fact seems to be frequently

316

Water quality in the Forth estuary, Scotland 7I~llIlilllllllltilllltll[lllllllll[tltllllllltttltl6

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I i I I I I I ]II

[

I

2447651

Figure 2. Time series plot of biologicaloxygendemand data for Bannockburn. overlooked by those who assume that, if we identify and measure pollution, we have virtually cured it." In order to reduce pollution, it is essential to develop a model of the estuarine system so that the behaviour of the pollutants and the ways in which various pollution control options may be implemented and assessed can be explored (Wisdom, 1975). 3. M o d e l l i n g

There are several distinct advantages in developing models of estuaries: they aid our understanding of the dynamics of these complex, open environmental systems; they allow us to replicate the behaviour of some pollutants in the estuary; they guide the search for further data collection and monitoring methodologies; and they enable alternative water quality control options to be examined before applying these on real world systems. In the U.K., estuarine models are used for all these purposes by many water PLCs, industrial dischargers and River Purification Boards (Moffatt, 1990; Moffatt et al., 1990b). This section describes a dynamic simulation model o f the Forth estuary. The aim of the model is to try to replicate the temporal pattern of water quality in the estuary for some of the pollutants described above, and then to explore the impact of alternative economic incentives to improve the quality o f the water in the estuary. Consider the sketch map of a hypothetical estuary (Figure 3), which is divided into three reaches. The first input is river flow at the head of the estuary, set arbitrarily at 450 units per time unit. The first set o f pollutants, described crudely as either B for biodegradable or C for conservative (non-biodegradable), enter the hypothetical estuary as part of an in-flowing river. The values for these flows are measured as 25 units per day. In a river system the total load would now be 475 units per day--but, in an estuary, the flow may be reversed due to tidal and other effects. Hence, the impact o f the pollutants joining the estuary may be increased further by an inland flow from downstream. For

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Head fRiVwer~ " ~ ' ~ .

Estuary

Point source one

Mouth

/J 9 - !

Effluent discharge

Point source two

Reach one

Reachtwo

450 Units

25 Units

2"4 4OO

I0 60O

Reach three

50 Units 9 Flow 5 9 Pollutant B :500 9 Pollutant C

Figure 3. A hypothetical estuary with two polluted reaches.

simplicity, however, it will be assumed here that this type of flow does not occur. It must be stressed that this type of flow will, of course, occur in a real estuary--which is one reason why the estuarine environments are so difficult to model when compared to riverine systems. In the third stretch of the estuary, a further 50 units of water are added to the system. Hence, as the estuary enters the sea the total volume of water is 525 units. With regard to the dispersion of pollutants in the estuarine water, it is essential to make a distinction between the biodegradable (B) type of pollutant and the conservative (C) type of pollutant. Suppose before the first input pollution of 400 units of total dissolved solids are monitored and similarly 2-4 units of a B-type pollutant are measured: it is then possible to use the materials balance approach to calculate the quantity of B and C pollutants in successive reaches o f the estuary. These calculations are shown below and in Table 4. At the tidal limit of the estuary, i.e. just before the first new pollutants enter the system, the flow is 450 units and the quality of the water, with regard to the two pollutants of type B and C, is 2.4 and 400 units, respectively. By using a materials balance approach, it is possible to write a general formula for calculating the a m o u n t of the biodegradable and conservative pollutants in any kth reach of the estuary as:

WP,k-- (WFk-, • P,k-1) + (IFk • P,k) ( WFk-I + IFk)

(1)

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Water quality in the Forth estuary, Scotland

where WP,~ = water quality for pollutant i in reach k; WF~_ ~= water flow entering reach k from previous reach k - 1 ; I F k = w a t e r flow entering reach k from point source; P,k = concentration of pollutant i in reach k; and P,k-1 = concentration of pollutant i input into previous reach k - 1. The calculations for any pollutant in any reach of the estuary can thus be calculated. For example, assuming a river has an inflow of 450 units, and measures of 2.4 and 400 units for type B and C pollutants, respectively, then, when the first point source pollutants enter the estuary with a flow of 25 units per day, the formula results in an increase to 2.8 and 410.5 in turn for the two pollutants. Similarly, at the next point source, 50 units are injected into the estuary with a measure of 5 and 300 units of pollutants B and C, then the net effect within the estuary would become a value of 3-0 and 399.5 units (Table 4). It will be noted that, in this illustrative example, the B-type pollutants do not biodegrade. In a real estuary, these pollutants would, of course, biodegrade and diffuse in a complex manner depending on various factors. These factors would include the type of biodegradable pollutant; the water temperature and the length of time the water temperature is constant, then an exponential decay factor can be applied to a specific biodegradable pollutant resulting in the predicted values in successive reaches being calculated. Applying this logic to the illustrative example, the values for the B-type pollutants are 1.18 and 0.65, respectively, and are shown in parentheses in Table 4. These new values, which take into account the biodegradation of specific pollutants, also alter the transfer coefficients for the B-type of pollutants. In all cases, the absolute value is chosen rather than the positive or negative signed value. An algorithm has been written to solve the mass-balance equations for n point sources of pollution entering the Forth estuary. This algorithm is embedded in a dynamic simulation model of the estuary which relaxes most of the restrictive assumptions used in this illustrative example (Moffatt et al., 1990a). Whilst the mathematics underlying a materials balance approach to modelling the movement of water and pollutants in an estuary are quite straightforward, the actual modelling of estuarine systems is not so easy to achieve. In particular, the materials balance equations have to be incorporated into a model which includes the twice daily rhythm of the tides, the biochemistry of the pollutants and the interactions of the various pollutants with the rest of the ecology of the estuary. Currently, a one-dimensional dynamic model is being developed which permits the calculation of both biodegradable and conservative pollutants in the Forth estuary (Moffatt et al., 1990a). This model is in its prototype stage of development, but its purpose is to predict the water quality in the estuary for different emissions from given point sources. As in the conceptual example above, each reach of the estuary is defined by the axial length of water between successive point sources--including rivers, sewage outfalls and industrial effluent from water pipes. By simulating the movement of biodegradable and conservative substances in the estuary, it is possible to calculate the transfer coefficients for each reach of the estuary for any given pollutant. In Table 4 the transfer coeff• for B- and C-type pollutants in each reach of the estuary are given. These are based upon the general formula: TC,k

-

P,k -- Pik- 1 P,k

(2)

where TC,k is the transfer coefficient for the ith pollutant in the kth reach of the estuary and P,k is pollutant i in reach k.

I. M o f f a t t

et aL

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Under steady-state conditions, it is possible to represent the marginal increase in the pollution load on a reach o f the estuary (k) by pollutant (/) by discharger (j) by a set of constants a~k, i = 1, 2 . . . . . n - 1. Hence, if P,j represents the quantity of a particular pollutant i discharged into the estuary by polluter j, j = 1 , . . . , m - 1, then the concentration of the pollutant i in reach k, S,k, is given as:

S, k = ~ ajkP i u (i=1 .... n-l)

(3)

)=1

If the reduction in the dissolved oxygen below saturation level in reach k is the focus of the modelling activity, then this reduction in dissolved oxygen in reach k caused by the release of pollutant i by discharger j may be denoted at any given instant by the parameter b~k. The total reduction in the dissolved oxygen below saturation level in the reach k is: m

In

1

Snk = Z

Z

J=l

t=l

b~kPij

(4)

These two equations allow for discharges that alter either dissolved oxygen demand or include a conservative toxin or both. In order to ease the modelling process, it may be worthwhile to disaggregate these two types of pollutants, i.e. conservative and nonconservative (i.e. biodegradable) so that the different impacts on water quality can be assessed. The formulation above is predicted on the assumption that the release of any pollutant from a point source is independent of other pollutants in the estuary. Obviously, this is a major restrictive assumption and it can be relaxed as follows. If it is assumed that interactions (synergistic effects or additive combinations of other pollutants) do affect the quality of the water in the estuary, then by using a lethal threshold concentration measure L C (Sprague, 1970) it is possible to calculate the number of toxic units for combinations of toxins at any given site. This will, of course, be restricted by the data available in the database. Nevertheless, if the total toxic units is greater than, or equal to, unity, then the mixture is predicted to be lethal to 50% of the fish in reach of the estuary (LCso). The net result of this approach to modelling water quality is to impose a second constraint on the model such that those pollutants which exhibit acute toxic effects are represented as: N-I

Sir <<,T*k ,= 1 LCs0,

(5)

LCso , is the strength of pollutant i, and T*k is the permitted level of toxins in stretch k of the river, consistent with the desired level of water quality as represented by the current consent agreements. Given an estimated set of values for the coefficients ajk and b~k, it is relatively easy to specify formally a set of emission rights to achieve the desired level of water quality, when the latter is specified in terms of constraints of the form: S,k <~S*

(6)

where S* is the maximum allowed level of pollutant i in reach k of the estuary consistent with satisfying the water quality objective. In general terms, then, the simulation model of water quality for the Forth estuary has the form:

320

Water quality in the Forth estuary, Scotland

WQ,k= WQB~+ WQC~

(7)

where WQ is water quality for pollutant i in reach k, and WQB and WQC are the component parts of water quality attributed to biodegradable pollutants (e.g. dissolved oxygen), including toxins, and WQC are conservative pollutants. Given the quality of the data and its spatio-temporal variation in both sampling and the "spread" pattern as obtained by the GIS, it is clear that the model will not be able to give point-by-point predictions for any pollutant in the estuary. All that can be reasonably achieved is a "good fit" between the model predictions and the statistical distribution around the mean for any pollutant i in the kth reach of the estuary. This statistical measure will include mean and standard deviations as well as the box-andwhisker plots which portray inter-quartile variation in the distribution of a specific pollutant. To aim for more accuracy in testing the model would require both better data and a more robust three-dimensional model of the estuary. Whilst the mathematics underlying this approach to modelling the movement of water and pollutants in an estuary are quite straightforward, the actual modelling of estuarine systems is not so easy to achieve. The model will, however, be able to simulate the transfer coefficients for particular pollutants in different reaches of the estuary. These predicted patterns of pollution can be compared with the empirically determined transfer coefficients derived from a statistical analysis of the relevant data in the relational database. A transfer coefficient can be defined as the rate of change in the concentration of a particular pollutant between successive reaches of the water body. Once these observed and predicted patterns of estuarine pollution are derived, then it is possible to explore different estuarine management strategies to improve water quality in the Forth or other estuaries.

4. Management Estuaries are very complex systems, and even careful monitoring and modelling do not, in themselves, constitute rational management of these sensitive environments. Since the Third Report of the Royal Commission on Environmental Pollution (RCEP, 1972) one of the aims of estuarine management has been the establishment, maintenance and improvement of the diversity of the biota and habitats both in the body of the estuarine water and along adjacent shores. In the case of a badly polluted estuary, the Royal Commission suggests that, as a first phase, the estuarine water needs to be o f good quality throughout its length to permit the passage of salmonoid fish. In cases where this water quality is achieved in an estuary, further improvements should be effected by careful management to ensure that bottom dwellers and benthic organisms can develop and show increased diversity. In the case of the Forth estuary, the over-riding managerial responsibility resides with the Forth River Purification Board. The primary purpose of the FRPB is "the maintenance or improvement of Water Quality in its area" (FRPB, 1988, p. 52). This RPB is responsible for a catchment of 4655 kmZ--which is the second smallest area of the Scottish Boards--but contains 25% of the population of Scotland residing within it (1.3 million people). Furthermore, the area has one of the largest petro-chemical plants in the U.K. located adjacent to the southern shores of the estuary. Clearly, with a large population and industrial complex adjacent to the estuary there will be inevitable conflicting demands on the use of this water resource (Leatherland, 1987).

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With the re-organization of Local Government in 1975, the former Lothian and Forth Boards were unified to form the current FRPB (Collett and Leatherland, 1985). One of the major advantages of this unification was that the entire catchment including a sea-ward area covered by Tidal Water Orders of 1311 km 2 was brought under one authority which could then manage the entire water quality in the drainage basin. The work of the FRPB has been greatly strengthened by the implementation of various pollution control acts. In particular, the realization of Part II of the 1974 Control of Pollution Act during 1983-1985, the Dumping at Sea Act 1974, the Food and Environment Act 1985 and the recent Water Act 1989, plus the recent EEC Directives, have given rise to the possibility of improving the quality of water in the U.K. and elsewhere in Europe. The indicators are that concern over such matters will increasingly be represented in future legislation, as witness the present EC actions over sewage dumping at sea and long sea outfalls. The above Acts, together with the greater awareness of environmental issues by both the public and the mainstream political parties--which are all going through some form of " G r e e n " conversion--have raised environmental issues to a position of high priority in the current government (Leatherland, 1987; Hallett et al., 1989b). Water quality in the estuary has improved since the re-organization of the two river boards into the one authority. In 1970, for example, Covill and Davies demonstrated the gross pollution of the Firth of Forth in the Lothian River Board's jurisdiction (Covill and Davies, 1970). By 1987, however, Leatherland was able to show that by using the consent system (i.e. emission limits) the "'levels o f potential pollutants in the waters of the Forth were mostly either already low or declining as a consequence of reduced emissions" (Leatherland, 1987, pp. 295-296). In one sense, it can be argued that the current system of regulation is operating very effectively via the use of the consent agreements. If, however, the management of water pollution control in the Forth and other estuaries is concerned with the assessment of the contribution of each discharge in order to promote an effective and economic programme (Collett and Leatherland, 1985), then it is obviously sensible to examine alternative management strategies which may further improve water quality in estuarine environments to the greatest economic effect. In particular, the approaches advocated by economists may be worthy of serious consideration (Pearce et al., 1989; Mackay, 1975). Environmental economists have argued that a number of economic measures utilizing the market mechanism, such as transferable discharge rights (TDRs) and emission taxes, could be used to allow water quality objectives to be met at a lower cost than is the case with the current command and control consent strategy. The full details of these economic incentives are discussed elsewhere (Hanley et al., 1990). But as these ideas are not that well known beyond the discipline of economics, it is worthwhile to briefly outline here the arguments for these two incentive-based systems. Since the early 1970s, economists have argued that such incentive-based systems offer a wide variety of advantages over the current consent system of regulation for the achievement of target levels of environmental quality. The main advantage claimed is that of efficiency: that is, that incentive-based systems involve lower resour6e cost expenditure on the part of the pollution generators. Put simply, society is deemed to be interested in achieving environmental quality targets with the lowest possible expenditure of resources. The idea of efficient pollution taxes originated in the work of Baumol and Oates (1971, 1975). Such taxes would be levied either on the rate of emission of potentially polluting substances (such as SO 2 emissions from a power plant) or on inputs used as

Water quality in the Forth estuary, Scotland

322

part of a potentially polluting process (such as a tax on fossil fuels). A tax policy is efficient if it allows all pollution sources to adjust their emission levels until the costs of reducing emissions by one more unit [marginal abatement cost (MAC)] is equal to the tax rate. This can be demonstrated to be in the firm's self-interest. If there is only one tax rate, then we arrive at the following condition, given two firms A and B and a tax rate of t, where MAC represents the costs to the firm, at the margin, of achieving reductions in emission levels: MAC A = t = MAC B

(8)

Under certain circumstances this is a necessary and sufficient condition for costminimization. Problems arise, however, in calculating the tax rate (especially if MAC functions are shifting through time), and when the marginal impact of emissions on environmental quality are spatially determined to a significant level. Furthermore, if firms do not or cannot cost-minimize, then the target level o f emissions reduction may not be forthcoming. A tradeable p e r m i t s y s t e m works by creating a market in "rights to emit". Here, an environmental policy agency (EPA) decides on a target level of emissions, and issues only enough permits to cover this total (a permit allowing for a specified portion of the desired limit of emission). Emitting without sufficient permits would be an illegal activity. Permits would either be initially auctioned, or distributed freely, on an equal or pro-rata basis. Firms could then buy and sell permits. We would expect those firms with relatively high pollution control costs to be buyers, and tl',ose with relatively low control costs to be sellers. The system is capable of generating an efficient outcome as, again, firms may adjust their levels of emissions until, in this instance, the marginal abatement costs for each firm are equal to the market clearing permit price. In fact, in a given situation, this price should be the same as the efficient pollution tax rate described in the preceding paragraph. How can we test the claims of economists that tax or tradeable permits are better options for the control of pollution than the current control-and-command regulations, as currently practised through the consent system? The most common means of doing this is to combine some kind of mathematical programming m o d e l - - a t the simplest level a linear programming (LP) model--with a model of the ecosystem being regulated. The purpose of the linear programming model is to simulate the behaviour of costminimizing firms when different policy options are introduced. The least cost tax rate, and the market-clearing permit price, are both calculated by finding dual values ("shadow prices") for the constraint which restricts emissions to the target level. If the polluting impact of the emissions depends on their location in space and time, then a transfer coefficient matrix (hjk) is derived from the dynamic one-dimensional simulation model of the environment--in this specific case, the Forth estuary--to link emissions to ambient pollution levels. Thus, for j = 1. . . . . n sources of emissions, and k = 1. . . . . m monitoring points, the problem can be set up as follows for a single pollutant: Minimize Cj(ej) Subject to: ~ e x hjk <~P t I

for a l l k

(9)

I. Moffatt e t al.

323

and %/>0

for a l l j

where Cj are abatement costs, dependent on the level of emissions and pt is the target maximum pollution level. For an application of water quality management in a simpler river system, see O'Neil et al. (1983). In the case of the more complex estuarine environment, this approach has not been attempted in a theoretically rigorous and empirically tested manner for both taxes a n d tradeable permits--although an earlier study (Rowley et al., 1979) did attempt this type o f approach for the Tees estuary using only taxes on emissions. The major purpose of our research is to attempt to integrate models of economic incentive schemes with a dynamic environmental simulation model, in order to explore various scenarios which could improve the quality of water in the Forth estuary in an effective and economic manner. By combining the data sets with a dynamic simulation model, a GIS and a linear programming model, a series of alternative management strategies for improving water quality can be examined. Two important issues must be taken into consideration: first, will the simulations lead to a further improvement in estuarine water quality? Second, if such improvements do occur, which alternative is the most efficient? If the scenarios can give affirmative answers to these questions, then it may be suggested that this approach could form the basis of new environmental policies for improving water quality. 5. Conclusion

This paper has described the on-going research into monitoring, modelling and managing water quality for estuarine environments. By using a relational database the water quality data, made available by the FRPB, have been accessed through the use of a query language (SQL) and some of the 200 determinands or parameters have been subjected to a statistical analysis. An example of the results of this empirical analysis is presented above (see Hallett et al., 1990, for details, and FRPB Annual Reports, 1977 et seq.). The empirical analysis provides a base line for the modelling efforts. Whilst the illustrative example, described above, is very simple, it is worth mentioning that a dynamic simulation model is currently being developed by the research team (Moffatt et al., 1990a). This model attempts to replicate several major pollutants in the Forth estuary. In particular, the model predicts the transfer coefficients for conservative and biodegradable pollutants in various reaches of the estuary. By calibrating and testing the model for its sensitive parameters, a series of simulations will be performed on other independent data sets extracted from the database. These simulations will predict the concentrations of several pollutants along the mean axial length of the estuary. The transfer coefficients for each of the pollutants will be predicted--as these provide essential information for the economic model. Geographical information systems have been incorporated in the monitoring and modelling sectors of this research to provide details of the specific locations of the point sources into the estuary as well as the sampling points carried out in the monitoring surveys. It would be interesting to try and use the GIS to simulate a three-dimensional pattern of pollutants in the Forth estuary through time--but the data may not permit such an extrapolation into the space time domain. The transfer coefficients predicted by the dynamic simulation model are used by the

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Water quality in the Forth estuary, Scotland

e c o n o m i c m o d e l to c a l c u l a t e t h e least c o s t s o l u t i o n to t h e p r o b l e m o f w a t e r p o l l u t i o n c o n t r o l in t h e e s t u a r y u s i n g a l i n e a r p r o g r a m m i n g p a c k a g e . By s i m u l a t i n g d i f f e r e n t s c e n a r i o s f o r c o n t r o l l i n g w a t e r q u a l i t y p o l l u t i o n , it is a n t i c i p a t e d t h a t a n e c o n o m i c a l l y a n d e n v i r o n m e n t a l l y s o u n d set o f p o l i c y r e c o m m e n d a t i o n s c a n be p r o d u c e d . We would like to thank all those people who were kind enough to discuss the various issues raised in this paper. In particular, representatives of the Forth River Purification Board, who supplied the water quality data used in this study. Useful comments were also received from the Confederation of British Industries-Scotland Environment Committee; the Scottish Development Department; the Department of the Environment; and the Centre for Economic and Environmental Development. All views expressed in this paper are, however, the sole responsibility of the present authors, who also take full blame for any errors and omissions.

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