Date Published: June 14, 2019
Publisher: Public Library of Science
Author(s): Ing-Marie Gren, Frank Melzner.
Mussel farming has been recognised as a low cost option for mitigating damage caused by eutrophication in the Baltic Sea. However, uncertain nutrient removal owing to weather and environmental conditions at the mussel farm site has not been previously considered. The purpose of this study was to estimate whether mussel farming has cost advantages even in conditions of uncertainty. To this end, the replacement cost method was used for the valuation of ecosystem services and a numerical cost minimisation model was constructed based on the safety-first approach to account for uncertainty in nutrient removal. This study showed that the value of mussel farming depends on the cost at the farm, and the impact on the mean and variability of nutrient removal in relation to other abatement measures. The study also pointed out the need of data on the decision makers’ risk attitudes and measurement of uncertainty. The application to the Baltic Sea showed that the total value of mussel farming increased from 0.34 billion Euro/year to 0.41 or 1.21 billion Euro when accounting for uncertainty depending on assumption of probability distribution. The increase was unevenly distributed between the Baltic Sea countries, with it found to be lower for countries equipped with highly productive mussel farms and long coastlines.
Like many other seas and lakes, the Baltic Sea suffers from eutrophication due to excess loads of nitrogen and phosphorous. Damage from eutrophication is manifested as increased frequency in the blooming of toxic algae and changes in the composition in fish species, usually to the detriment of commercial species (e.g. ). The Baltic Sea has the world’s largest sea bottoms with no biological life . Awareness of this damage was raised in early 1970s, but progress towards making improvements is slow. One reason for this is the difficulty of regulating nutrients from the agricultural sector, which accounts for 60% of the nitrogen loads and 50% of the phosphorus loads . Mussel farming has been suggested as a promising abatement option since it reduces the nutrient content in the sea through the cultivation and harvesting of mussels, which can be used as feed, food or an energy source [4,5,6].
According to the replacement cost method, a cleaning technology has a value only if its introduction reduces the total abatement cost for achieving a certain nutrient load reduction target (e.g. ). The value is then calculated as the difference in total minimum costs for reaching the targets with and without mussel farming as a nutrient-removal option. Since this value is determined by the construction of the cost minimisation model under uncertain nutrient abatement, it is briefly presented below.
The conceptual approach presented in Section 2 shows that data are needed on nutrient loads in the business-as-usual (BAU) scenario, nutrient removal and costs of mussel farming and other abatement measures and their capacity constraints, nutrient reduction targets and achievement probabilities. The most up-to-date data on BAU loads of nutrients from the various countries with coastal zones on the Baltic Sea are from HELCOM , which reports nutrient loads for 2010. The total load of nitrogen is 895 ktonnes N and that of phosphorus is 35.8 ktonnes P (Table 1). Poland accounts for the largest amount of both these nutrients with 33% of total N load and 40% of total P load. It was assumed that the abatement capacity in each country corresponded to 70% of the BAU loads. Measurements of uncertainty in decreases in these loads were obtained from Elofsson , who calculated the coefficient of variation (i.e. standard deviation divided by the mean load) for loads from the different catchments in the Baltic Sea.
The numerical cost minimisation problem is solved using GAMS with the CONOPT solver . Without uncertainty and mussel farming, the total minimum cost for achieving the BSAP targets amounts to 3.44 billion Euro, which corresponds to approximately 0.3% of total GDP in the catchment in 2015 . The marginal costs of other abatement measures without any mussel farming at the nutrient targets, the so-called shadow costs of the targets, amount to 9.51 Euro/kg N reduction and 412.07 Euro/kg P reduction. The first test of whether or not nutrient removal by mussel farming has a value is if the marginal removal cost is below these marginal abatement costs (Table 2).
As in all quantitative analyses, the results depend on the assigned parameter values and chosen model construction. Nevertheless, the calculated total minimum cost for reaching the BSAP nutrient targets without mussel farming of 3.44 billion Euro is in the same order of magnitude as the estimates obtained for reaching the same BSAP targets, but with other numerical optimisation models [35, 36]. The costs obtained by Elofsson  and Hasler et al.  amount to 3.74 and 4.06 billion Euro, respectively. The lower cost in the current study is explained by the inclusion of a larger number of abatement measures, such as the reduction in airborne emissions, and the consideration of overall nutrient load targets rather than specific targets for each marine basin.
The main conclusion drawn from this study is that the consideration of uncertainty in all nutrient abatement increases the value of nutrient removal by mussel farming in the Baltic Sea from 0.34 billion Euro per year to 0.41 or 1.21 billion Euro depending on assumption of probability distribution. There are two main reasons for this increase. One is that the consideration of uncertainty is expressed in a safety-first setting, which implies that the target becomes more stringent because of the risk discounting of uncertain abatement. This implies that the cost of reaching nutrient targets without mussel farming becomes relatively high. The other reason is that the uncertainty as measured by coefficient of variation is slightly lower for nutrient removal by mussel farming than for other abatement measures, which implies a relative cost advantage for this abatement measure.