The cultivation of seaweed as a feedstock for third generation biofuels is gathering interest in Europe, however, many questions remain unanswered in practise, notably regarding scales of operation, energy returns on investment (EROI) and greenhouse gas (GHG) emissions, all of which are crucial to determine commercial viability. This study performed an energy and GHG emissions analysis, using EROI and GHG savings potential respectively, as indicators of commercial viability for two systems: the Swedish Seafarm project's seaweed cultivation (0.5 ha), biogas and fertilizer biorefinery, and an estimation of the same system scaled up and adjusted to a cultivation of 10 ha. Based on a conservative estimate of biogas yield, neither the 0.5 ha case nor the up-scaled 10 ha estimates met the (commercial viability) target EROI of 3, nor the European Union Renewable Energy Directive GHG savings target of 60% for biofuels, however the potential for commercial viability was substantially improved by scaling up operations: GHG emissions and energy demand, per unit of biogas, was almost halved by scaling operations up by a factor of twenty, thereby approaching the EROI and GHG savings targets set, under beneficial biogas production conditions. Further analysis identified processes whose optimisations would have a large impact on energy use and emissions (such as anaerobic digestion) as well as others embodying potential for further economies of scale (such as harvesting), both of which would be of interest for future developments of kelp to biogas and fertilizer biorefineries.

Coastal areas around the world are experiencing environmental problems such as climate change and eutrophication. These, in turn, lead to emerging challenges with excessive amounts of biomass that impact coastal communities. Developing utilisation strategies for marine biomass is therefore highly relevant and forms part of the blue growth research field. In response to environmental concerns, as a waste management strategy and as part of blue growth research initiatives, several Baltic Sea coastal projects have been initiated in recent years to study utilisation of maritime biomass. However, the sustainability of these utilisation strategies has not been critically appraised. Therefore, the work presented in this thesis explored some key sustainability aspects of two Baltic Sea case studies utilising common reed (Kalmar, Sweden) and mass-occurring filamentous macroalgae (Trelleborg, Sweden) for biogas and biofertiliser recovery. Energy analyses suggested that both case studies could provide a positive energy balance and have the potential to achieve nutrient recovery. Moreover, a contingent valuation study in Trelleborg demonstrated considerable welfare benefits of biomass utilisation. These findings indicate that marine biomass utilisation strategies highlight potential to contribute to environmental and welfare benefits of these coastal communities.

Eutrophication and global warming have created major problems with decaying macroalgae on Baltic Sea beaches. A considerable amount of this biomass is retrieved, only to be returned to the sea when the tourist season ends. It is therefore essential to implement systems whereby the retrieved biomass is utilised. One potential system is anaerobic digestion for biogas and biofertiliser recovery, but knowledge about non-market benefits is lacking. This study estimated the willingness-to-pay (WTP) for algae retrieval and utilisation in a case study area and examined methods for incorporating preference uncertainty information into WTP estimates. This was done by gathering data using two different methods and comparing the results. In addition, results obtained from an open-ended interval (OEI) format were compared with those from a payment card. A substantial mean WTP was found. The two elicitation formats produced similar mean WTP estimates. However, the OEI format produced weaker results, with a significantly higher level of stated preference uncertainty and an elevated zero response rate. Comparisons of preference uncertainty information gathered with two different methods yielded unexpected results and to some extent contradicted findings on interval size in the OEI format as a good measure of preference uncertainty.