Value of land as a pollutant sink for international waters

Ecological Economics 30 (1999) 419–431

ANALYSIS

Value of land as a pollutant sink for international waters

Ing-Marie Gren a,b,*a Department of Economics, Swedish Uni6ersity of Agricultural Sciences, Box 7013, 750 07 Uppsala, Sweden

b Beijer International Institute of Ecological Economics, Royal Swedish Academy of Sciences, Box 50005,104 05 Stockholm, Sweden

Received 8 July 1998; received in revised form 30 December 1998; accepted 4 January 1999

Abstract

The purpose of this paper is to analyse and compare the values of a marginal change in the area of land as apollutant sink under different decision-making contexts and objectives: international coordination versus nationalpolicies for pollutant reduction, and maximization of net benefits versus minimization of costs for pollutantreductions. The analytical results show that a coordinated policy between countries generates a higher value of amarginal change in the supply of land as a pollutant sink than an uncoordinated policy. It is also shown that thevalue is lower (higher) under the decision objective of maximizing net benefits when the efficient pollutant load ishigher (lower) than the load target under the cost effectiveness approach. An application to the Baltic Sea drainagebasin land as a nitrogen sink for the management of eutrophication reveals that the differences between values underdifferent policy contexts and objectives can be quite large in magnitude. © 1999 Elsevier Science B.V. All rightsreserved.

Keywords: Transboundary pollutants; Pollutant sinks; Coordination; Net benefit maximization; Cost effectiveness

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1. Introduction

Over the past 20 years, the benefits of variousland uses have been recognized, not only withrespect to their traditional harvest yields, but alsowith regard to their ability to act as a pollutantsink for water management. One example is pro-vided by wetlands’ capacity to purify water by

reducing leaching of pesticides and nutrients todownstream watersheds (e.g. Mitsch and Gos-selink, 1986; Kusler and Kentula, 1990). Gren etal. (1997) showed that land cover types such aswetlands, grassland and energy forest provide lowcost options for the achievement of nutrient re-ductions to the Baltic Sea. The value of landacting as a pollutant sink should then be ac-counted for when considering its conversion intoother uses. However, a comparison of net benefitsfrom alternative land uses requires an appropriate

* Correspondence to Uppsala address.E-mail address: [email protected] (I.-M. Gren)

0921-8009/99/$ - see front matter © 1999 Elsevier Science B.V. All rights reserved.

PII: S 0921 -8009 (99 )00007 -5

I.-M. Gren / Ecological Economics 30 (1999) 419–431420

measurement of the net value in all uses. Thepurpose of this paper is to analyse and estimatethe value of land as a pollutant sink under differ-ent decision contexts and objectives.

When we regard an ecosystem’s capacity toreduce leaching of pollutants as an input for theproduction of water quality its value can be calcu-lated as associated impacts on net welfare bymeans of the production function approach(Maler, 1991a; Barbier, 1994, 1997; Gren, 1995;Bystrom, 1999). The value of the pollutant sinkfunctioning is then determined by the valuation ofwater quality, the effectiveness in producing waterquality, and the cost as compared to other pollu-tant reduction measures. The optimal choices ofinputs and water quality are, in turn, determinedby type of decision framework. In this paper, twoclasses of decision contexts and objectives areidentified for the management of internationalwaters. The alternative decision contexts are coor-dinated and uncoordinated choices of water qual-ity improvement options, and the objectives to beachieved are formulated either as maximization ofnet benefits or as minimization of costs for achiev-ing a certain water quality target.

As demonstrated in Barbier (1997) and Free-man (1991), the design of property rights for acommon property resource and associated deci-sion context affects the value of an ecosystem asan input into the production of a common prop-erty resource. The difference with this paper ascompared to the approach of Barbier and Free-man is the large-scale international aspect. Thereis a relatively large literature on net benefits fromemission reductions under different internationalcooperative frameworks (Barett, 1990; Kaitala etal., 1991; Maler, 1991b; Hoel, 1992). There arealso numerous studies on the valuation of ecosys-tem life support values, especially wetland valua-tion (see Gren and Soderqvist, 1994, for a survey).However, the combination of ecosystem valuationand transboundary environmental impacts, whichis the approach applied in this study, is rare.

The paper is organized as follows. The first twosections contain an analytical decomposition offactors affecting the value of land as a pollutionabatement option. Next, the approach is appliedto the valuation of Baltic Sea coastal wetlands as

nitrogen sinks. The paper ends with a brief sum-mary and some concluding comments.

2. Basic model and decision framework

This paper contains two basic components forthe analysis and calculation of the value of landas a pollutant sink. One is a description of pollu-tant transports among the countries sharing thecommon water body. The other is modelling ofalternative decision contexts and objectives. In thefollowing, the construction of simple models ofpollutant transports and decision frameworks arepresented. By means of these models, the value ofland as a pollutant sink in a country is calculatedas the impact on net benefits or abatement costsfrom a marginal increase in the current area ofpollutant sink. Land as a pollutant sink is hereinterpreted as the area of land with relatively lowpollutant leaching. A switch in the area of landfrom high to low leaching then implies a netdecrease in pollutant leaching, the effectiveness ofwhich, as measured in tons of pollutant reduc-tions to the water body, depends on the differencein leaching between the high and low leachingland covers.

2.1. Pollutant transport modelling

If there were no pollutant transports betweencountries, there would be no difference in out-comes between coordinated and uncoordinatedpollution abatement policies. However, in the caseof international waters we have to deal with twotypes of transboundary pollutants: air and waterstreams. Simplified models for these transportsare presented in this section.

For each country i, where i=1,…,N differentcountries, there are two types of pollutant path-ways to the water body under study: direct, Ei,and indirect deposition, Pi. Direct deposition isdefined as the pollutant emissions in region, Ei,which are transported directly into the waterbody. It is assumed that this direct deposition canbe calculated as a share of total emissions fromthe region, aiEi. Total pollutant load from acountry i to the common water body, Li, is thenwritten as

I.-M. Gren / Ecological Economics 30 (1999) 419–431 421

Li=Pi+aiEi (1)

Indirect deposition, Pi, refers to the pollutantsdeposited on land and further transported bywater streams to the international water body.The total deposition on land within a country isdetermined by the emissions from all countries,which are deposited on land within the country. Itis assumed that these transboundary air pollutantscan be described by a matrix where each elementa ji measures that share of country j ’s emissionsthat is transported to country i. When aii= (1−ai) there are no transboundary pollutanttransports.

Total pollutant deposited on land within theterritory of each country, Sja jiE j, is subjected totransformation during the transport from the de-position localization to the water body understudy. The level of Pi is then dependent, not onlyon the pollutant deposition within the regions, buton other factors, such as the composition of land,climate, geology and hydrology. For example,there is a great difference in nutrient leachingbetween forest areas and bare arable land. An-other simplification of the model is the discrimi-nation between only two types of land, relativelyhigh leaching land, AHi, and low leaching land,ALi, or land covered by pollutant sink. The indi-rect deposition of pollutants from country i to thewater body, Pi, is then written as

Pi=Pi(ALi, AHi, SjejiE j) (2)

where ALi+AHi=ATi and ATi is the total area ofland in region i. In principle we expect Pi to beincreasing in E j and AHi and decreasing in ALi.The simplification of pollutant transports made inEq. (2) occurs for at least two reasons. One is thatthe spatial distribution of different land covertypes within a drainage basin affects the pollutantload to the water body. For example, high leach-ing land located close to the water body implieslarger Pi than if the same land is located upstreamin the drainage basin. The reason is the transfor-mation of pollutants during the water and soiltransports from the pollutant source to the waterbody. The second reason is the complex dynamicrelation between surface and subsurface transportof pollutants. However, the consideration of these

factors would not alter the principal analyticalresults in this section, although they will probablyhave a strong empirical importance. Therefore, inorder to focus on the role of institutional andinformational settings, these dynamic and spatialfactors are excluded from the analysis.

The transboundary dispersion of water qualityimpacts is determined by the water streams. It isassumed that these transports between surround-ing regions can be described by a matrix whereeach element, e ji, denotes the fraction of pollutantload from region j, L j, which affects region i. Thewater quality for a region, W i, can then be writ-ten as

W i=W i(Sje jiL j) (3)

Water quality is assumed to be measured so thata higher W i implies improved water quality. It isthen expected that W i is decreasing in L j.

2.2. Decision contexts and objecti6es

Based on the above description of pollutanttransports, we can identify two types of optionsfor improving the water quality: emission-orientedabatement measures, Ri, and land use-orientedoptions increasing the area of low leaching land,ALi, or pollutant sinks. Pollutant emission from acountry i is then initial emission, Eio, which couldbe measured at a certain base year, minus Ri, orEi=Eio−Ri. Common to all decision contextsand objectives is the choice of these two pollutantload reduction measures. Another common fea-ture for all types of decisions is that the value ofland as a pollutant sink is calculated as a mar-ginal increase in the current area of pollutant sinkin each country i, ALi*.

In an international context there are no supernational authorities who are able to enforce con-tracts on cooperation between regions. Countriesor regions will then cooperate only if they makegains as compared to a situation where they acton their own. It is therefore of interest to calculateand compare the outcomes when countries coor-dinate their policies with the outcomes from singlecountry decisions. Two types of international in-stitutional frameworks are therefore analysed.One is where all regions coordinate their choices


of Ri and ALi for obtaining a common objective.The other is the uncoordinated case where eachcountry makes its own choice taking other coun-tries’ decisions as given.

Ideally, when sufficient information is available,we would solve for the efficient choices of Ri andALi by maximizing net benefits under the twoinstitutional settings. However, estimatingchanges in the supply of public goods in monetaryterms is far from a trivial matter. In the case ofwater quality improvements this implies the trans-lation of water quality changes, such as pollutantconcentration ratios, into welfare terms. For ex-ample, changes in pollutant loads affect reproduc-tion of commercial fish and bathing water quality.We thus have to deal with multi-attribute valua-tion, which is a relatively recent research area (e.g.Dale et al., 1996). It is therefore likely that benefitestimates of water quality impacts are not avail-able. Further, we might not even obtain informa-tion on water quality impacts from pollutanttransports in biological terms. The reason is thelack of data on marine pollutant transports forlarge international water bodies (Gren et al.,1997). Therefore, two types of decision objectivesare identified depending on the availability ofmarine pollutant transports and benefits esti-mates. In the case of information availability, netbenefits are maximized. When sufficient informa-tion does not exist, the cost effectiveness decisionrule is applied. The decision is then formulated asachieving a certain reduction in the pollutant loadto the water body at minimum cost.

We thus have four different combinations ofinstitutional and informational settings: coordi-nated and uncoordinated choices of Ri and ALi

where either net benefits are maximised or costsare minimized for a certain target in the load ofpollutants to the water body. Under all foursituations it is assumed that there exists costfunctions for each type of measure, CiR and CiA,which are increasing and convex in Ri and ALi

respectively. When maximizing net benefits, valu-ation functions are assumed to exist for eachcountry, Vi(W i) which are increasing and concavein W i. The four different decision models and theassociated first-order conditions with respect tothe optimal choice of ALi are written as presentedin the following.

Coordinated maximization of total net benefits(IB), implies that total net benefits for all coun-tries are maximized, which gives

Max Si [Vi(W i)−CiR(Ri)−CiA(ALi)]

Ri, ALi,

s.t. (1)− (3)

ALi5ALi* (4)

The associated first-order conditions for an opti-mum read

Sj [VW jj WL j

j e ijPR ia i+SjVW jWL jj LP je jiPR ja ij]

=CR ii (5)

Sj(VW jWL jj e ijPA Li

i )−CA Lii =a iIB (6)

where subindexes denote partial derivatives, j=i=1,…,N different countries, and a iIB is the La-grangian multiplier of the constraints on the areaof pollutant sinks, which is positive when theconstraint is binding. This multiplier is interpretedas the value of a marginal increase in Ai*, whichconstitutes our measurement of the pollutant sinkvalue of land in country i. From Eq. (6) we cansee that its magnitude is determined by the differ-ence in marginal benefits minus marginal costs.When ALi* does not bind at the actual area ofpollutant sinks, there is no marginal pollutantsink value.

The first-order condition (Eq. (5)) also revealstwo types of international spillover impacts froma marginal change in pollutant emissions in coun-try i. The first term within brackets in Eq. (5)disregards the transboundary air transports butincludes the dispersion of water quality impacts toother countries by the marine transport coeffi-cients e ij. The second term shows somewhat morecomplicated spillover effects by considering trans-boundary air and water pollution. First, the emis-sion reduction in country i gives rise to adeposition and leaching reduction in other coun-tries through ((P j/(R j)aij. Then, the pollutantload reduction in each country j generates disper-sion of water quality impacts to all other coun-tries through the marine transport coefficients e ji.


In Gren (1997) it is shown that the considerationof these two spillover effects, instead of only oneas in most papers on transboundary pollutants, islikely to reduce the difference between outcomesfrom coordinated and uncoordinated policies.However, in this paper we are mainly concernedwith the comparison of the value of marginalchanges in the area of pollutant sinks. In subse-quent analysis we will therefore abolish the first-order conditions for optimal choices of emissionreduction measures.

Coordinated minimization of total costs (IC) forachieving a certain maximum pollutant loadtarget, L*, is written as

Min SiN[CiR(Ri)+CiA(ALi)]

Ri, ALi

s.t. (1)− (2)

SiNLi5L*

ALi5ALi* (7)

and the first-order conditions with respect to theoptimal choice of ALi is

lPA Lii −CA Li

i =a iIC (8)

where l]0 is the Lagrange multiplier on thepollutant load restriction, which measures thechange in total costs from a marginal change inthe pollutant load restriction. Whether or not a iIC

is positive depends on the cost and effectiveness ofland as a pollutant sink as compared to abate-ment options in all countries.

The corresponding decision problems under na-tional policies is written in the same way as Eqs.(6) and (7), except for the absence of summationover all countries in the objective function. Undernational minimization of costs, a restriction isimposed only on the country’s pollutant load tothe water body. The associated first-order condi-tions under National maximization of net benefits(NB), is then written as

VW ii WL i

i e iiPA Lii −CA Li

i =a iNB (9)

The corresponding condition under National min-imization of costs (NC) is

l iPA Lii −CA Li

i =a iNC (10)

where the Lagrange multiplier, l i, measures thechange in costs from a marginal change in thepollution requirement Li* which considers onlythe reduction options in the country. The multi-plier on the overall reduction target, l, measureschanges in total costs from a marginal change inL* where reduction options in all countries aretaken into account.

3. Comparison of pollutant sink values

Assuming positive values of a marginal changein ALi*, we can see from the first-order conditionsEqs. (6) and (8)–(10) that

a iIB=a iIC=a iNB

=a iNC when Sj(#V j/#W j)(#W j/#L j)e ij=l

= (#Vi/#W i)(#W i/#Li)e ii=l i

That is, the marginal sink values are the samewhen there are no transboundary impacts by thewater streams, when the efficient level of pollutantload reduction corresponds to the cost effectivelevel at the international and national decisionlevels, and when l=l i for all i=1…,N countries.The last condition implies, in principle, that thereare no differences in pollutant reduction costsbetween the countries. It is very unlikely thatthese three conditions are fulfilled, at least forrelatively large international waters with severalsurrounding countries. We then have the situationthat the value of a marginal change in the area ofpollutant sink in a country depends on the deci-sion context and objectives, which is analysed inthe following section.

In order to compare the values under coordi-nated and uncoordinated actions, we take thedifference between the international and nationalvalues of a marginal change in land to be thepollutant sink in country i under maximization ofnet benefits and minimization of costs, respec-tively. The difference under the maximization ofnet benefits is then written as

a iIB−a iNB= %N

j, j" i

VW jj WL j

j e ijPA Lii (11)

Obviously, we have a iIB\a iNB as long as ((V j/(W j)((W j/(L j)e ij\0 where j" i. That is, the


value of a marginal change in the area of pollu-tant sinks in country i is higher under coordinatedpolicies as long as there are any dispersion im-pacts of water quality and when positive valua-tions of water quality improvements exists in atleast one other country.

Under the cost effectiveness approach we have

a iIC−a iNC= (l−l i)PA Lii (12a)

Eq. (12a) is positive or negative depending on therelation between l and l i. These Lagrange multi-pliers are equal to the derivatives of the total andnational cost functions for changes in pollutantloads at L* and Li*, respectively, which impliesthat Eq. (12a) can be rewritten as

a IC−aNC= − (CL* −CL i*i (Aio, Eio))PA Li

i ,

C=SiCi(Aio, Rio) (12b)

and Aio and Rio denote the optimal choices ofland use- and emission-oriented measures, respec-tively. The relation between a IC and aNC is thusdetermined by the relation between the interna-tional and national marginal costs for pollutantload reductions at the restrictions L* and Li*,respectively. Assuming negative and concave costfunctions in L* and Li*, respectively, the differ-ence between a IC and aNC is positive for marginaldecreases in L* and Li* when the marginal cost ofpollutant load reductions in country i is relativelylow as compared to other countries. Then, anincrease in ALi* implies cost savings in all coun-tries where pollutant reduction options are moreexpensive than the cost of the increase in ALi*. Onthe other hand, the national value of a marginalchange in ALi* is higher when the national mar-ginal cost for pollutant reductions is relativelyhigh.

When we instead focus on the role of informa-tion provision, we take the differences betweenthe values of marginal change in the area ofpollutant sinks between the efficient and cost ef-fective policies. This difference under coordinatedpolicies is written as

a iIB−a iIC= (SjVW jj WL j

j e ij−l)PA Lii (13)

and under national policies we have

a iNB−a iNC= (VW ii WL i

i e ii−l i)PA Lii (14)

Under both international and national policies formaximizing net benefits we have that marginalbenefits from pollutant reductions are equal to themarginal cost. Since the Lagrange multipliers l

and l i measure the marginal costs of pollutantload reductions at the cost effective load targets,Eqs. (13) and (14) are both zero when the efficientlevel of pollutant load coincides with the costeffective target. When the efficient loads arehigher (lower) than cost effectiveness targets, thedifferences in Eqs. (13) and (14) are negative(positive). The values of sinks are then lower(higher) under maximization of net benefits thanwhen costs are minimized.

4. Application to the Baltic Sea

The Baltic Sea has suffered from eutrophicationsince the beginning of 1970s. Eutrophication maycause an increase in the production of algae, someof which are toxic. When decomposed, all algaedemand oxygen which results in oxygen deficits atthe sea bottom. This deficiency in turn generatessea bottom areas without biological life, whichcurrently occur in 25% of the deep sea bottomareas of the Baltic Sea (Turner et al., 1999).Further, the composition of fish species changes.In the case of Baltic Sea the stock of commercialcod decreases while trash fish stock increases.Nitrogen loads constitute the major source ofeutrophication to the major parts of the BalticSea (Wulff and Niemi, 1992; Elmgren, 1997).

In Gren et al. (1997), data on nitrogen trans-port and costs of nitrogen abatement measuresused in this study are reported. The relatively lowleaching land uses, or pollutant sinks, includedare: construction of wetlands, cultivation of catchcrops, energy forestry, and pasture. Catch cropsrefer to certain grass crops which are sown at thesame time as an ordinary spring crop, but start togrow when the spring crop is harvested and thusmakes use of the remaining nutrient in the soil.Other abatement measures include reductions inuse of nitrogen fertilizers, decreases in livestockholdings, improvements in sewage treatmentplants’ cleaning capacity, installation of catalystsin cars and ships, and scrubbers in stationarycombustion sources.


However, as emphasised in Gren et al. (1997),there were several difficulties in finding appropri-ate data on costs and nitrogen transports for theselarge-scale calculations. In this study, furtherdifficulties appear when finding data on marinewater transports of nitrogen, which is required forcalculating benefits from nitrogen reduction. Esti-mates of benefits from nitrogen reductions to theBaltic Sea are found in Soderqvist (1996) andMarkowska and Z: ylicz (1996). These studies aredesigned in order to make appropriate compari-sons between Sweden and Poland of willingness topay for an improvement of the ecological condi-tions of the Baltic Sea which corresponds to thesituation prior to the 1950s. The results from theSwedish study are then transferred to Denmark,Germany and Finland, and the Polish to Estonia,Lithuania, Latvia and Russia. The results showan annual willingness to pay of 31 000 millionSwedish crowns (SEK).

As is common with many methods for estimat-ing monetary values of changes in the supply ofan environmental good, only one change in thesupply is considered. This method makes it verydifficult to trace marginal benefits between theinitial supply and that in the valuation scenario,which is required for the purpose of this paper. Alinear relation between nitrogen reductions andbenefits has therefore been assumed, which im-plies a constant environmental marginal benefit,and, further, that this is the same for all regions.The marginal benefit is obtained simply by divid-ing total benefits by 500 000 tons of N, whichcorresponds to a 50% decrease in total nitrogenload to the Baltic Sea. This level of nitrogenreduction is suggested by Wulff and Niemi (1992)in order to obtain the ecological conditions corre-sponding to the 1950s. The estimated marginalbenefit is then SEK 62/kg N reduction.

Information on nitrogen marine transports isobtained from Wulff et al. (1990) where trans-ports between three major Baltic Sea basins—Baltic Proper, Bothnia Sea, and BothniaBay—are calculated. According to the results,20% of the nitrogen load to the Baltic proper istransported to the northern basins, i.e. BothniaSea and Bothnia Bay. These northern basins areshared by Finland and northern Sweden. Due to

the marine streams there is no transport fromthese basins to the Baltic Proper. Therefore, it isassumed that Finland and Northern Sweden re-ceive 20% of total nitrogen load from all otherregions. Further, the loads from Northern Swedenand Finland imply marine environmental impactsonly on these regions.

Unfortunately, the basin nutrient transport cal-culations contain no estimates of the transportbetween regions within each basin, which meansthat there are no estimates of marine nitrogentransports between the eight countries sharing theBaltic Proper basin. Therefore, arbitrary assump-tions have been made which are based on someinformation on the coasts of the countries. Whenthe coast lines contain islands and vegetation,more of nitrogen impact occurs on the coast ofthe emitted country and vice versa. It is regardedthat the coasts of Poland are very ‘open’ in thesense that they contain little vegetation which cancontain nutrients. It is, therefore, simply assumedthat all the Polish nitrogen load entering theBaltic Sea is equally divided between all BalticProper countries. For the remaining countries it isassumed that 0.3 of the impact occurs on the owncoast while the remaining part is equally dividedby the other countries.

In Table 1, the calculated nitrogen loads, mar-ginal costs and benefits for each region in thedrainage basin are presented (1 USD=SEK 7.99,December 17, 1998). In addition, the area of eachdrainage basin is given.

The largest single country is Sweden whichcovers about one-quarter of the total Baltic Seadrainage basin area. Poland is the country withthe highest nitrogen loads to the Baltic Sea andaccounts for about one-third of the total load.The total calculated anthropogenic load of nitro-gen from the drainage basin amounts to 706 000tons of N, which corresponds to approximately70% of the total load which also includes back-ground leaching and air deposition from sourceslocated outside the drainage basin (Turner et al.,1999). Other published estimates of nitrogen loadvary between 400 000 and 1 400 000 tons of nitro-gen (HELCOM, 1993; Stalnacke, 1996). Theseestimates are based on measurements of nutrientconcentrations at different river mouths along the


Baltic Sea coasts. However, there is much uncer-tainty in our estimates, which implies that, al-though well within the range of other estimates,they must be interpreted with much caution.

The last two columns present marginal costs andbenefits, respectively, from reductions in the nitro-gen load to the coastal waters of the Baltic Sea. Theestimates of marginal costs show that the costs ofpollutant sink measures are neither the lowest northe most expensive options. The low cost emissionreduction options are decreases in nitrogen fertiliz-ers and improvements of the cleaning capacity atthe sewage treatment plants. The most expensivemeasures are reduction in air emissions, which isexplained by their low impacts on the Baltic Sea.The marginal benefit measures the impact as mea-sured in monetary terms in that country. Forexample, a reduction by 1 kg N of Danish nitrogenloads generates a benefit of SEK 18.6 for theDanish people. Water quality exports to othercountries sum to SEK 62−18.6=43.4. The lowestown marginal benefit is obtained in Poland, whichis due to our assumption of an ‘open’ coast.

Values of a marginal increase in the nitrogen sinkarea are calculated for different types of pollutantsinks by means of non-linear programming(Brooke et al., 1992). The results show that thevalues of marginal increases in the area of wetlands

are positive in most countries under all four deci-sion frameworks, while they are zero in most casesfor the other three types of nitrogen sink areas(Table 2).

All countries share the feature that the values ofmarginal increases in wetlands are higher undercost effective decision rules than when net benefitsare maximized. As demonstrated in the foregoingsection, this is a reflection of the higher nitrogenreduction target under the cost effective approaches(see Table 3 for optimal nitrogen reductions, costsand net benefits under alternative decision rules).Another result, which is expected from the analysisin the foregoing section and the numbers presentedin Table 1, is that the values are higher undercoordinated polices for maximization of netbenefits than when each country maximizes its ownnet benefits. Values are higher under coordinationof minimization of costs for low-cost countries withrelatively large reductions, i.e. Denmark, Poland,Russia, Estonia, Latvia and Lithuania.

The results in Table 2 also reveal that thedifferences in values for a country can be consid-erable depending on the choice of problem formu-lation. Germany is exceptional due to the largeload of nitrogen air transports which are expen-sive to reduce. The requirement of a 50% reduc-tion for each country is therefore very expensive

Table 1Drainage basin area, nitrogen loads, marginal costs and benefits from nitrogen reductions to the Baltic Sea

Nitrogen** load Marg. benefitsMarg. costs (SEK/kg N)**Drainage* basin area,Region(SEK/kg N)(1000 sq. km) (1000 ton N/year)

Land as sinks Others

33.3 61Denmark 22–157 0.1–440 18.637.20.1–68041–25469Finland 308.0

245 15–101316.5 0.1–937Poland 6.228.3 96 10–61 0.1–937 18.6Germany

Russia 14–113328.4 0.1–1500 12.43546.1 18 41–303 0.1–357 18.6Estonia65.6 31 43–306 0.1–536 18.6Latvia

12.40.1–50036–283Lithuania 4566.0278.0 48 101–419 0.1–290 37.2N. Sweden

0.1–37530–12157147.2S. Sweden 18.6

706Total 1571.3

* From Sweitzer et al. (1995).** From Gren et al. (1997).


Table 2Calculated values for Baltic drainage basin land as nitrogen sinks under alternative decision rulesa

Region Wetlands Catch crops Energy forests Ley

IB NB IC NC IC NC IC NC IC NC

0.70 20.9 7.77 0.40Denmark 0.041.540.61 0.92 0.19Finland 0.30 0.20 0.27 0.07 0.15

0.47 14.4 35.11.10Germany0.30Poland 4.07 0.83 0.03 0.030.09Russia 1.97 0.14 0.01

0.01 1.03 1.95 0.01 0.010.02EstoniaLatvia 0.030.15 2.81 2.00 0.02 0.01

0.13 6.92 1.12 0.03 0.020.59LithuaniaN. Sweden 0.24 0.09 0.09 0.07S. Sweden 0.10 5.12 0.12 0.13 0.03 0.12

a Values are in 1000 SEK/ha; a blank box indicates zero value; IB, maximization of international net benefits; NB, maximizationof national net benefits; IC, minimization of international costs for a 50% total N-reduction; NC, minimization of costs for a 50%reduction in national N-loads.

for Germany, which, in turn, gives its very highvalue of increased wetland area. But, the variationin values is also high for other countries. Forexample, the highest value is more than 25 timeshigher than the lowest values in Denmark, Latviaand Lithuania. On the other hand, wetlandrestoration is a relatively uninteresting nitrogenreduction option in Finland and North Sweden.One important reason is that the nitrogen reten-tion capacity of wetlands, which is dependent onclimatic factors, is relatively low in these regions.Another important factor is the relatively largecurrent areas of wetlands in these regions, whichimplies a rather low value of further increases.

The estimated values of wetlands as nitrogensinks are significant when compared with profitsfrom traditional use of arable land. In Finland,Germany, Denmark, and Sweden profits fromhigh yield arable land vary between SEK 2000and 6000 per ha, and in the other countries be-tween SEK 500 and 2000 per ha (Elofsson, 1997).The value of a marginal increase in the area ofwetlands is thus considerable under cost mini-mization decisions. It can then achieve a levelwhich is about three times higher than the highestprofit level from conventional crops. Under inter-national coordination of the maximization of netbenefits, the values are lower and correspond to,at the most, about one-quarter of the highestprofit level (Denmark and Estonia).

However, the empirical calculations containseveral assumptions due to lack of data. Changesin any of these parameters will, by all likelihood,affect the results. One example is provided by thedifficulty to obtain information on current area ofwetlands. The source used in this paper (Janssonet al., 1995), relies on geographical informationsystems (GIS) data, which is known to be rela-tively weak in identifying wetlands. When thewetland area is doubled in all countries, the valuesunder the cost effective decisions become zero forFinland and North Sweden and are reduced by atleast two-thirds for all other regions (Table 4).Further, the values of other nitrogen sink optionsbecome zero in all countries except Finland.

5. Concluding comments

The purpose of this paper has been to analyseand estimate values of marginal increases in landsuitable for pollutant sinks under four differentdecision frameworks for the management of inter-national waters, coordinated and uncoordinatedmaximization of net benefits or minimization oftotal costs for given pollutant load targets. Theanalytical results show that the value of a mar-ginal change in the area of pollutant sinks in acountry under coordinated policies is always


Table 3Optimal nitrogen reductions as a percentage, net benefits and costs in millions of SEKa

NBRegion ICIB NCs

Net ben. % Net ben. %% Costs % Costs

Denmark 34 1303 21 483 59 3442 50 17342018 16 244 42 3702 50Finland 4445231074 9 271 3114 8028Germany 50 3074

42Poland −545 15 75 55 1020 50 4562842 11 31 52Russia 137346 50 493

1080 17 173 5639 692Estonia 50 9638Latvia 1064 30 97 58 1103 50 88237Lithuania 897 38 142 56 1781 50 761

2004 40 437 4742 1766N. Sweden 45 100637S. Sweden 917 19 213 58 3116 54 2849

10 654 16Total 216635 50 35257 50 47572

a IB, maximization of international net benefits; NB, maximization of national net benefits; IC, minimization of international costsfor a 50% total N-reduction; NC, minimization of costs for a 50% reduction in national N-loads.

higher or equal to the value under separate policieswhen net benefits are maximized. The correspond-ing value when costs are minimized instead dependson whether the country under study has relativelyhigh or low cost options. The values under coordi-nated policies are higher for low cost countries andlower for countries with expensive pollutant reduc-tion options. When instead we focus on the role ofaccess to data on environmental benefits, we con-clude that there are no differences in pollutant sinkvalues between maximizing net benefits and mini-mizing costs when the efficient pollutant loadscoincide with the cost effectiveness targets. Thevalues are higher (lower) under cost effective objec-tives than when net benefits are maximised whenthe cost effective targets are lower (higher) than theefficient pollutant loads.

The analysis is applied to the management of theeutrophicated Baltic Sea, where the load of nitro-gen plays an important role. Four different alterna-tives of land as pollutant sinks—wetlands, catchcrops, energy forests, and pasture—are included asnitrogen reduction options together with reduc-tions in emission of nitrogen from nitrogen fertiliz-ers, manure, households, industry and traffic. Theapplication reveals two major results. First, in-creases in the area of wetlands turn out to be themost interesting nitrogen sink option in a majorityof the Baltic Sea countries: Poland, Germany,

Denmark, Russia, Estonia, Latvia, and Lithuania.Relatively low costs of wetlands as pollution miti-gation options are also found in other studies (e.g.Gren, 1993; Bystrom, 1999). Important reasons arethe small areas of wetlands due to their conversioninto arable land (Wittgren et al., 1991), and therelatively low marginal costs of nitrogen reductionsby restoring wetlands in these countries. Second,the value of a marginal increase in the wetland areavaries considerably depending on decision frame-work. For example, the value of a marginal increasein Denmark amounts to about SEK 8000/ha undernational minimization of costs and to about SEK700/ha when national net benefits are minimized.

Needless to say, both the analysis and its appli-cation contain several simplifications. There are, inprinciple, three classes of simplification: the deter-ministic and static approach, the limited cost con-cept, and the difficulties associated with obtainingdata for the empirical estimates. With regard to thefirst type of simplification, it may take several yearsbefore pollutants emitted at a certain location reachcoastal waters. Both the timing and the amount ofpollutant reaching the coastal waters are highlydependent on climatic conditions. Further, thebiological impacts associated with a certain deposi-tion of pollutants into a water body are highlyuncertain as measured in quantitative terms.


Table 4Calculated values of restored wetlands as nitrogen sinks under alternative decision rules when the area of wetlands is doubleda

Region Wetlands Catch crops Energy forest Ley grass

IB NB IC NC IC NC IC NC IC NC

0.29 5.89 8.10Denmark 1.590.20Finland 0.30 0.01 0.03 0.1

80.47 4.39 31.7Germany 1.26

Poland 0.33 1.23 0.22Russia 0.09 0.56 0.14

0.02 0.28 0.150.03EstoniaLatvia 0.17 0.04 0.71 0.09

0.14 2.23 0.270.64LithuaniaN. SwedenS. Sweden 0.18 1.44 0.14

a Values are in 1000 SEK/ha; a blank box indicates zero value; IB, maximization of international net benefits; NB, maximizationof national net benefits; IC, minimization of international costs for a 50% total N-reduction; NC, minimization of costs for a 50%reduction in national N-loads.

The costs estimated in this paper refer only tothe gross cost and not to the net costs of themeasures. This assumption implies an overesti-mate of costs of measures which, not only reducenitrogen loads, but also have other environmentalimpacts. For example, in addition to reducingeutrophication, decreases in nitrogen oxides alsoreduce damaging impacts of acid rain and groundlayer ozone. The multi-functional aspects of wet-lands have been demonstrated in Gren (1995)where it is shown that other environmental valuesassociated with the construction of wetlands fornitrogen abatement can be as high as the value ofwater quality improvement. Another limitation ofthe cost concept concerns the neglect of eventualdispersion of impacts on several sectors of theeconomies due the implementation of pollutantreduction measures. As demonstrated in Johanes-son and Randas (1996), the structural impacts ofnitrogen reductions can be considerable in Swe-den, the Baltic States, Finland and Denmark.Another simplifying assumption is that of zerocosts for implementing pollutant reduction mea-sures. In an international context like the BalticSea where countries differ with respect to eco-nomic development and institutional set-ups forenvironmental management, the implementation

costs of pollutant reduction options are likely todiffer greatly between regions. Eckerberg et al.(1996) show that the implementation of measuresreducing nitrogen loads from the agricultural sec-tor differs between Sweden, Denmark, Finland,Estonia, Latvia and Lithuania.

The third simplification concerns all the as-sumptions necessary for calculating the empiricalresults. The main difficulties have been to connectnitrogen emission sources with their nitrogenloads to the Baltic Sea coastal waters and toobtain information on nitrogen transport bymarine water. The reason for the first problem isthe differences in statistical units and regionaldivision for measuring emissions and loads to thecoastal waters. Nitrogen loads are measured asnitrogen concentration ratios at river mouths invarious parts of the Baltic Sea, and nitrogen useand emission are presented for different economicsectors in the surrounding countries. The linkingof nitrogen emissions to associated coastal loadsrequires information on localization of nitrogenemission, and associated transports into thecoastal water. At the very best, such informationhas been available only for a few scattered areasin the drainage basin. As shown by Bystrom(1998), the calculation of nitrogen transport is


important for determining the cleaning effective-ness of coastal wetlands, and, hence, the costs forwetlands as an option for reducing nitrogen loadsto the Baltic Sea. The empirical results must,therefore, be interpreted with caution. Due tothese difficulties with the data and the otherabove-mentioned analytical simplifications, thisstudy should be regarded as a first step towards amore appropriate analysis of the role of land as apollutant sink in an international context.

Acknowledgements

I am very much indebted to R. Freeman, andtwo anonymous referees for their valuable com-ments. Financial support from Swedish Councilof Agricultural and Forestry Research is grate-fully acknowledged.

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Value of land as a pollutant sink for international waters