Blue Economy and Resilient Development: Natural Resources, Shipping, People, and Environment

European Union (EU) policy encourages the development of a blue economy (BE) by unlocking the full economic potential of oceans, seas, lakes, rivers and other water resources, especially in member countries in which it represents a low contribution to the national economy (under 1%). However, climate change represents a main barrier to fully realizing a BE. Enabling conditions that will support the sustainable development of a BE and increase its climate resiliency must be promoted. Romania has high potential to contribute to the development of the EU BE due to its geographic characteristics, namely the presence of the Danube Delta-Black Sea macrosystem, which is part of the Romanian Lower Danube Euroregion (RLDE). Aquatic living resources represent a sector which can significantly contribute to the growth of the BE in the RLDE, a situation which imposes restrictions for both halting biodiversity loss and maintaining the proper conditions to maximize the benefits of the existing macrosystem. It is known that climate change causes water quality problems, accentuates water level fluctuations and loss of biodiversity and induces the destruction of habitats, which eventually leads to fish stock depletion. This paper aims to develop an analytical framework based on multiple linear predictive and forecast models that offers cost-efficient tools for the monitoring and control of water quality, fish stock dynamics and biodiversity in order to strengthen the resilience and adaptive capacity of the BE of the RLDE in the context of climate change. The following water-dependent variables were considered: total nitrogen (TN); total phosphorus (TP); dissolved oxygen (DO); pH; water temperature (wt); and water level, all of which were measured based on a series of 26 physicochemical indicators associated with 4 sampling areas within the RLDE (Brăila, Galați, Tulcea and Sulina counties). Predictive models based on fish species catches associated with the Galati County Danube River Basin segment and the “Danube Delta” Biosphere Reserve Administration territory were included in the analytical framework to establish an efficient tool for monitoring fish stock dynamics and structures as well as identify methods of controlling fish biodiversity in the RLDE to enhance the sustainable development and resilience of the already-existing BE and its expansion (blue growth) in the context of aquatic environment climate variation. The study area reflects the integrated approach of the emerging BE, focused on the ocean, seas, lakes and rivers according to the United Nations Agenda. The results emphasized the vulnerability of the RLDE to climate change, a situation revealed by the water level, air temperature and water quality parameter trend lines and forecast models. Considering the sampling design applied within the RLDE, it can be stated that the Tulcea county Danube sector was less affected by climate change compared with the Galați county sector as confirmed by water TN and TP forecast analysis, which revealed higher increasing trends in Galați compared with Tulcea. The fish stock biodiversity was proven to be affected by global warming within the RLDE, since peaceful species had a higher upward trend compared with predatory species. Water level and air temperature forecasting analysis proved to be an important tool for climate change monitoring in the study area. The resulting analytical framework confirmed that time series methods could be used together with machine learning prediction methods to highlight their synergetic abilities for monitoring and predicting the impact of climate change on the marine living resources of the BE sector within the RLDE. The forecasting models developed in the present study were meant to be used as methods of revealing future information, making it possible for decision makers to adopt proper management solutions to prevent or limit the negative impacts of climate change on the BE. Through the identified independent variables, prediction models offer a solution for managing the dependent variables and the possibility of performing less cost-demanding aquatic environment monitoring activities. Full article

Heavy metal pollution is still present in the Danube River basin, due to intensive naval and agricultural activities conducted in the area. Therefore, continuous monitoring of this pivotal aquatic macro-system is necessary, through the development and optimization of monitoring methodologies. The main objective of the present study was to develop a prediction model for heavy metals accumulation in biological tissues, based on field gathered data which uses bioindicators (fish) and oxidative stress (OS) biomarkers. Samples of water and fish were collected from the lower sector of Danube River (DR), Danube Delta (DD) and Black Sea (BS). The following indicators were analyzed in samples: cadmium (Cd), lead (Pb), iron (Fe), zinc (Zn), copper (Cu) (in water and fish tissues), respectively, catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), malondialdehyde (MDA) (in fish tissues). The pollution index (PI) was calculated to identify the most polluted studied ecosystem, which revealed that Danube River is seriously affected by the presence of Fe (IP = 4887) and strongly affected by the presence of Zn (IP = 4.49). The concentration of Cd in fish muscle tissue was above the maximum permitted level (0.05 µg/g) by the EU regulation. From all analyzed OS biomarkers, MDA registered the highest median values in fish muscle (145.7 nmol/mg protein in DR, 201.03 nmol/mg protein in DD, 148.58 nmol/mg protein in BS) and fish liver (200.28 nmol/mg protein in DR, 163.67 nmol/mg protein, 158.51 nmol/mg protein), compared to CAT, SOD and GPx. The prediction of Cd, Pb, Zn, Fe and Cu in fish hepatic and muscle tissue was determined based on CAT, SOD, GPx and MDA, by using non-linear tree-based RF prediction models. The analysis emphasizes that MDA in hepatic tissue is the most important independent variable for predicting heavy metals in fish muscle and tissues at BS coast, followed by GPx in both hepatic and muscle tissues. The RF analytical framework revealed that CAT in muscle tissue, respectively, MDA and GPx in hepatic tissues are most common predictors for determining the heavy metals concentration in both muscle and hepatic tissues in DD area. For DR, the MDA in muscle, followed by MDA in hepatic tissue are the main predictors in RF analysis. Full article

Maritime transport is one of the main activities of the blue economy, which plays an important role in the EU. In this paper, we aim to assess the impact of maritime transport, related investment, and air pollution on economic growth within 20 countries of the European Union, using eight panel data regression models from 2007 to 2018. Our results confirm that maritime transport, air pollutants (NO_x and SO₂) from maritime transport, and investment in maritime port infrastructure are indeed positively correlated with economic growth. In other words, an increase of 10% in these factors has generated an associated increase in economic growth rate of around 1.6%, 0.4%, 0.8%, and 0.7% respectively. Alongside the intensity of economic maritime activities, pollution is positively correlated with economic growth, and thus it is recommended that policymakers and other involved stakeholders act to diminish environmental impacts in this sector using green investment in port infrastructure and ecological ships, in accordance with the current European trends and concerns. Full article

The rapid spread of online learning demonstrates that it is becoming one of the trends in the development of vocational education in the modern world. Along with the obvious advantages of online learning such as cost reduction, cross-border opportunities for receiving it, and adaptability for students, educational institutions encounter specific difficulties: a lack of optimal teaching methods, inflexibility of the institutional environment to the use of new teaching technologies, the transformation of communication between teachers and students, and technological unpreparedness for the development of online learning. At the same time, the need to solve the problem of accessibility of education and fill the shortage of labor resources in Russia, in particular its Arctic zone (AZRF), will contribute to the spread of online learning practices. To consider developing online education, this article, on the one hand, presents the results of a study of the regional employers’ confidence in education in a non-traditional format and, on the other hand, shows the readiness of vocational educational institutions to implement training programs in a distance format. The main research method was a questionnaire survey, in which 2240 organizations and 344 professional educational institutions located in the Russian Arctic took part. The survey results indicate that more than half of employers (58%) declared the applicability of online learning in the Russian Arctic, but about 40.6% of companies do not consider applicants with a diploma from online education. At the same time, employers’ confidence in distance learning in higher education is lower than in vocational secondary education. Additionally, the majority of institutions of higher education (62.5%) believe in the possibility of using distance education in the Russian Arctic, while organizations of vocational secondary education (64.98%) have the opposite opinion. Based on the results of the study, recommendations for federal and regional authorities were prepared. Full article

The main research objective of this study is to examine how coastal urban communities in the Arctic Zone of the Russian Federation (AZRF) organize the sustainable development (and emerging blue economy) strategy planning process. Along with this general objective, this study focuses on four more specific questions: First, to examine whether the sustainable development and blue economy concepts are integrated into the urban development strategies and whether they are a real priority for the northern coastal communities? Second, to figure out which local government and civil society institutions are involved in the policy planning process and whether this sphere of local politics is transparent and open to public discussions? Third, to find out which specific aspects of the sustainable development and coastal blue economy concepts are given priority in the municipal development strategies? Finally, to discuss whether the AZRF coastal sustainable development/blue economy strategies aim to solve short-term/most pressing problems or they suggest long-term policies built on sustainability principles and are oriented to solve fundamental socioeconomic and ecological problems of the AZRF coastal communities? The hypothesis of this study is that a properly designed strategy planning system would be helpful for both familiarizing northern municipalities with the blue economy concept and its effective implementation. This research is based on several empirical cases, including major Arctic coastal urban centers/ports—Anadyr, Arkhangelsk, Dudinka, Murmansk, Naryan-Mar, Pevek, Sabetta, and Severodvinsk. Full article

As a vital element affecting economic efficiency, the impact of marine industrial structure upgrading on marine economy has become a hot topic, and China is not an exception. This paper analyzed the dynamic relationship of marine industrial structure upgrading and marine economy efficiency to verity the “structural bonus” and “cost disease” effects. The results confirmed the existence of cost disease in China’s marine economy, although occasionally it illustrated structural bonus effects with the improvement of the regional marine economy efficiency. The spatial Durbin model (SDM) was introduced to study the spillover effect of local marine industrial structure upgrading (MISU) on the adjacent regions’ marine economy efficiency, and this spillover effect was verified to have agglomerate characteristics in China’s coastal areas. Then several countermeasures were proposed to realize marine ecological civilization and promote regional cooperation in the development of China’s marine economy. Full article

Fisheries has always played a vital role in supporting livelihoods and ensuring food security and sustainable economic and social development in Southeast Asia. Historically, rural and coastal communities across the region have heavily relied on the fish trade as an indispensable source of income and employment. With the establishment of the Regional Comprehensive Economic Partnership (RCEP) between Association of Southeast Asian Nations (ASEAN) economies and large fish traders like China, Japan, South Korea, Australia, and New Zealand, there is a threat for smaller countries to lose competitive advantages in the regional market. By studying bilateral trade flows between fifteen RCEP members in 2010–2019 and matching indicative untapped trade potentials (ITP method) with revealed comparative (RCA method), relative trade (RTA method), and competitive (Lafay index) advantages across 210 pairs of countries, the authors found substantial misbalances between potential values of country-to-country trade and actual advantages of RCEP economies. To optimize gains from intraregional trade for both smaller and larger RCEP members, this study identified advantageous and disadvantageous trading destinations and product categories for individual countries. The recommendations were then generalized along the four groups of economies based on their level of income, contribution to overall RCEP trade in fish, and the share of fishery products in the national trade turnover. From a practical side, the study adds to the knowledge about the fish trade in Asia by detailing how countries can better utilize individual combinations of advantages. From a methodological side, the approach can be employed widely outside the RCEP to establish a reliable picture of potential gains or losses of a particular country in trade with its counterparts across varied sets of competitive advantages. Full article

This paper aims to analyze the scientific production of the blue economy and coastal tourism research fields to identify research topics and publication patterns. Accordingly, bibliometric analysis was selected as a quantitative meta-analysis literature review method. Scopus was the main database for extracting the scientific production in blue economy and coastal tourism. Various bibliometrics analysis techniques were used to analyze 476 and 49 publications in blue economy and coastal tourism, respectively. The main results are summarized as follows: (i) the number of publications in the blue economy scientific sector has increased significantly, and (ii) contrarily, a relatively small body of blue economy literature is concerned with the coastal tourism sector despite its significant role in the blue economy. Full article

In light of about 80% of international freight traffic carried by sea, maritime supply chains’ stability is pivotal to global connectivity. For over a year now, the transboundary mobility of vessels and cargoes has been restricted by diverse forms of the COVID-19 containment measures applied by national governments, while the lockdowns of people, businesses, and economic activities have significantly affected the growth prospects of various maritime connectivity initiatives. This study investigates how the pandemic-related public health, trade, and market factors have shifted the connectivity patterns in the Polar Silk Road (PSR) transport corridor between China, South Korea, Japan, Russia, and four economies of Northern Europe. The causality links between the Shipping Connectivity Index (SCI) and the number of COVID-19 cases and deaths, trade volumes with China and the rest of the world, and price indexes of minerals, fuels, food, and agricultural products are revealed separately for eight countries and thirty-five ports. The study algorithm is built on the consecutive application of the Augmented Dickey-Fuller (ADF) and the Phillips-Perron (PP) stationarity tests, the Autoregressive Distributed Lag (ARDL) method, the Fully-Modified Ordinary Least Squares (FMOLS) and the Dynamic Ordinary Least Squares (DOLS) robustness checks, and the Toda-Yamamoto causality test. Tight trade-connectivity links are recorded in all locations along the China-PSR transport corridor in 2015–2019, but in 2020, the relationships weakened. Bidirectional influences between the number of COVID-19 cases and connectivity parameters demonstrate the maritime sector’s sensitivity to safety regulations and bring into focus the role of cargo shipping in the transboundary spread of the virus. The authors’ four-stage approach contributes to the establishment of a methodology framework that may equip stakeholders with insights about potential risks to maritime connectivity in the China-PSR maritime trade in the course of the pandemic. Full article

Maritime transport and sustainable development require a recognizable global approach. The state, as the dominant structure in the world, enables the realization of sustainable maritime transport aims through its instruments. Therefore, it is very significant to consider the national maritime policies because the effective implementation of the global policy is impossible without considering the adequate mechanisms at the state level. The adopted Montenegrin strategic documents impact the institutional framework set-up of the Blue Economy (BE) sectors and potentials for ecologically sustainable maritime transport. Although there are no practical directions for the sustainable use of sea resources, Montenegro is affirmatively oriented to the BE concept. Knowing that Montenegro is in the process of the pre-accessing EU phase, it is of importance to be on the right road to creating a national maritime transport policy including environmental practices, to become part of the strategic implementation of the BE. The paper provides recommendations that can serve for the successful follow-up of the BE activities in Montenegro and the wider area. Full article

The main aim of our paper is to study peculiarities of two periods, i.e., the pre-conflict period (2004–2013) and conflict period (2014–2018), in the context of the impact of the demographic structure of the population on the economic growth and development of coastal regions of Ukraine. In the first step of the analysis, we investigate the relationship between the demographic shifts and selected economic indicators, using the Pearson’s correlation coefficient. In the next step of the analysis, we focus on the quantification of the impact of demographic indicators on the economic variables, based on the panel model with fixed effects. The received results confirm that the influence of the demographic stricture on the economic state of coastal regions changed significantly in the conflict period in comparison with the pre-conflict period, especially concerning income, unemployment, and the openness of the economy. Additionally, our findings show that while economic differences existed between the Azov Sea regions and the Black Sea regions in the pre-conflict period, they disappeared due to the economic deterioration of the Azov Sea regions during the conflict period. It is concluded that war affects adversely the population’s demographic structure, which inhibits the growth and economic development of Ukrainian coastal regions. Full article

In Agenda 2063, the African Union focused on making the use of ocean resources a priority in the new frontier of its blue economy. However, most African countries are still lagging in taking the initial steps of identifying and prioritising blue economy sectors and understanding the risk to sea and ocean health. Many have not developed integrated blue economy strategies and road maps, and this delays the progress and vision for an African blue economy envisaged by Agenda 2063 and 2050 Africa’s Integrated Maritime Strategy. For Africa, however, the blue economy offers greater opportunity beyond the economy and the environment. It presents Africa with a unique opportunity to achieve its national objectives, to improve regional integration, and to exert influence in the global setting. In this review, we agree with Schot and Steinmueller (2018) that we need to develop new framings and begin to experiment with new policy practices to address social and environmental challenges. Furthermore, we maintain that existing theories and knowledge based on innovation studies in Africa may be significant for designing and implementing policies towards climate change mitigation, blue economy governance, and sustainability transitions. Finally, we conclude by highlighting how experimentation is the key feature of transformative innovation policy that Africa has to employ in its blue economy while emphasizing how Africa (and the Global South generally) are in a unique position to develop their own transformation models that are different from those of the Global North. Full article