Sustainability assessment of technologies for resource recovery in two Baltic Sea Region case-studies using multi-criteria analysis

Highlights • Participation of local stakeholders is important part of sustainability assessments. • Scale of implementation can determine whether the benefits to outweigh the costs. • Implementation of innovations can be less sustainable than current systems. • Stakeholders did not prioritize technical performance of innovations.Sustainability assessments can be a powerful tool in decision-making regarding technical innovations. In this study, a sustainability assessment of technical systems for recovering nutrients and carbon from domestic wastewater is presented. Multi-criteria analysis was used to calculate a sustainability score of three different technical systems compared to a baseline in two case-studies: the Fyriså river catchment in Sweden and the Słupia river catchment in Poland. Two participatory workshops with local stakeholders were held in each case-study, the first to co-develop the system alternatives and sustainability criteria and the second to collect stakeholder weighting of the criteria. Although the systems assessed in both case studies were similar, the resulting sustainability scores were different. In Fyris, although the differences in scores was small, the preferred alternative was introduction of source-separation followed by a large redesign of the treatment and phosphorus extraction from incinerated sludge was the least sustainable alternative. For the Słupia systems the scores varied more, and the preferred system was a large redesign of the wastewater treatment followed by ammonia stripping of the reject water and the source-separation alternative received the lowest score. In both case-studies, the more costly system received highest sustainability score indicating the large potential benefits of enhancing resource recovery from domestic wastewater. Stakeholders did not prioritize technical aspects over the other sustainability criteria, yet most of research on resource recovery interventions is focused on technical performance

Understanding variation in national climate change adaptation: securitization in focus

Climate change is recognized today not just as a pressing and prominent issue on government agendas but also one that has been increasingly ‘securitized’ in a variety of national and global settings. We know little, however, if climate change adaptation, as a subset of climate action, has followed a similarly securitized path. This article addresses that question, exploring not only if climate change adaptation has been securitized but also what type of securitization – threat-oriented or risk-oriented – has emerged. Turning our empirical focus to three national settings of Norway, Sweden, and The Netherlands, we look for signs of securitization as well as whether securitization has been facilitated, shaped, or even blocked by existing governance features in each setting. We use this study to link the securitization literature with environmental governance approaches by building a novel analytical framework. Our findings show some intriguing and unexpected patterns, including evidence of risk-oriented securitization couched nevertheless as ‘business as usual’. We contribute to the growing debate on securitization in environmental governance while also casting new light on national climate change adaptation processes.publishedVersio

Circular nutrient solutions for agriculture and wastewater : a review of technologies and practices

This paper summarizes key findings from a series of systematic reviews and comprehensive efforts to collate evidence and expert opinions on circular solutions for recovery and reuse of nutrients and carbon from different waste streams in the agriculture and wastewater sectors. We identify established and emerging approaches for transformation towards a more circular nutrient economy with relevance to SDGs 6 and 14. The paper cites the example of the Baltic Sea Region which has experienced decades of fertilizer overuse (1950s–1990s) and concomitant urban sources of excessive nutrients. Regulations and incentive policies combining the nitrogen, phosphorus and carbon cycles are necessary if circular nutrient technologies and practices are to be scaled up. Pricing chemical fertilizer at levels to reflect society’s call for circularity is a central challenge. Highlights • Development of a circular nutrient economy in the EU is reviewed. • The socio-economic value of organic waste products from agriculture & municipalities needs to increase. • Opportunities are found in the new EU Circular Economy Package & Fertilizing Products Regulations. • Further implementation is possible with the Common Agriculture Policy (nutrient management tool) and Waste Framework Directive for recycling. • The Baltic Sea Region case is explored being sensitive to eutrophication with ongoing international efforts to introduce nutrient circularity

Decentralized solutions for island states: Enhancing energy resilience through renewable technologies

Decentralized grid solutions could be a feasible alternative to improve resilience and mitigate cascading effects in island states. Our study explores approaches that reduce the risk of infrastructure failures and promote decentralized utility planning in islands. A novel framework is proposed to conduct a power system resilience assessment by integrating vulnerability assessments and energy system modelling approaches through network analysis. The framework is applied to an island context, where vulnerability to hydroclimatic hazards, geographic isolation, restricted access to energy sources, small population bases inadequate for substantial infrastructure investments, dependence on imported energy, lack of energy source diversification, and fragile ecosystems have exacerbated energy insecurity. As a case study, we have applied the framework to Cuba. We simulate disruptions in vulnerable network nodes in Cuba to determine the municipalities that are most impacted by the simulated cascading failures. We designed and optimized the lowest cost decentralized solutions to increase resilience either by acting as the baseload electricity source or as a complementary backup system to complement in case of a power outage. Then, the resilience of the designed system was assessed using power system resilience metrics. The study results show Regla municipality in Cuba as the most vulnerable hotspot for electricity distribution. Upon the different system comparisons, ancillary systems outperform backup systems in enhancing power system resilience, especially in the context of a disruptive event, supplying up to 53 MWh/day more, although they have higher investment costs. Based on this research, resource planners and policymakers can understand vulnerable node points and prioritize the necessary investments for the preferred system choice to alleviate impacts of energy insecurity on the Island States

Predicting agricultural drought indicators: ML approaches across wide-ranging climate and land use conditions

Agricultural drought can severely reduce crop yields, lead to large economic losses and health impacts. Combined climate and land use variations determine key indicators of agricultural drought, including soil moisture and the Palmer drought severity index (PDSI). This study investigated the use of machine learning (ML) methods for predicting these indicators over Sweden, spanning steep climate and land use gradients. Three data arrangement methods (multi-features, temporal, and spatial) were used and compared in combination with seven ML/deep learning (DL) models (random forest (RF), decision tree, multivariate linear regression, support vector regression, autoregressive integrated moving average (AMIRA), artificial neural network, and convolutional neural network). Seven investigated features, obtained from Google Earth Engine, were used in the ML/DL modeling (soil moisture, PDSI, precipitation, evapotranspiration, elevation, slope and soil texture). The temporal ARIMA model (found most suitable for local scale prediction) and the multi-features RF model (more suitable for national-scale prediction) emerged as best performing for soil moisture prediction (with MAE of 9.1 and 11.95, and R2 of 0.79 and 0.59, respectively). All models generally performed better in predicting the soil moisture than the PDSI indicator of drought. For drought indicator prediction and mapping, previous-year average monthly soil moisture emerged as the most important feature, combined with the four additional corresponding features of PDSI, precipitation, evapotranspiration and elevation