Integrated coastal zone management in the context of COVID-19

Beach litter in three South American countries: A baseline for restarting monitoring and cleaning after COVID-19 closure

The COVID-19 pandemic caused that most countries established the closure of many beaches, affecting the scientific monitoring of thousands of coastal sectors. This article shows the status of beach litter in South America before and after COVID-19 closure. The data were obtained during the years 2019, 2020 and 2022 on 25 beaches using a technique BLAT-QQ. The results show that cigarette butts were the most frequent type of litter, meanwhile Brazil should improve cleanliness of general gross litter and gross polystyrene. Colombia gross vegetation litter and small vegetation litter, and Ecuador organic litter from animals. The results shown in qualitative and quantitative manner facilitate their understanding for managers, scholars and activists interested on beach litter monitoring. This baseline is useful to analyse regional and worldwide marine litter trends with the purpose to start or restart monitoring of tourist beaches from a science-based method.

Quantitative analysis of the impact of COVID-19 on ship visiting behaviors to ports- A framework and a case study

Corona Virus Disease 2019 (COVID-19) outbreak leads to a significant downturn in the global economy and supply chain. In the maritime sector, trade volume slumped by 3.8% in 2020 compared with 2019. To explore the impacts of COVID-19 on ship visiting behaviors, a framework is proposed to analyze the impact of COVID-19 on port traffic using Automatic Identification System (AIS) data. Firstly, a ship travel behavior-based model is proposed to identify the vessel anchoring and berthing. Then, the diversity in vessel anchoring and berthing time are analyzed, reflecting the impact of COVID-19. The port congestion caused by COVID-19 is quantified by accounting for the number of visiting ships and their residence time. Finally, a case study is carried out on vessels in the Beibu Gulf, China, operating from 2019 to 2020. The results show that the average anchoring time and berthing time increase by 62% and 11% for cargo ships and by 112% and 63% for oil tankers after the outbreak of COVID-19 compared with that before COVID-19. And the density of ships increases in the port area in 2020. Accordingly, the relevant improvements and countermeasures are proposed to reduce the adverse impact of the epidemic on the port navigation system. The paper has the potential to provide a reference for port management and improving port navigation efficiency in the post-pandemic era.

Cruise tourism in the context of COVID-19: Dilemmas and solutions

COVID-19 cases on international cruise ships have attracted extensive attention from the international community as well as the world's tourism and shipping industry. This virus highlighted the plight that must be faced by cruise ships in complicated times and situations such as pandemics. The comparative method is adopted to analyze the management measures taken by the "Diamond Princess", "Costa Serena", "Westerdam" and "Grand Princess" cruises in response to the COVID-19 pandemic and then to summarize the common dilemmas faced by these cruise ships, including defects of their internal environment, unclear health-care obligations during an epidemic, weak collaboration between the parties involved and their limited performance, and widespread infodemic and unfavorable public opinion. Given these dilemmas, measures are suggested to deal with the "cruise dilemma", including establishing and defining isolation standards on boards, enhancing the capacity of international organizations, the international community's joint response to the pandemic, promoting cooperation between countries, building an effective mechanism for the broad participation of the whole society, and standardizing the release of information and reasonably guiding public social opinion.

Explore the mechanism for seafarers to reconnect with work after post-pandemic psychological distress (PAPIST19): The moderating role of health-supporting climate

Covid-19 has disrupted the lives of employees all over the world. After experiencing a prolonged yet ongoing destructive event (i.e. Covid-19), finding an effective and non-invasive way to get employees back and engage in work is a huge challenge for scholars. Few studies have focused on returning to work after a traumatic event (limited time), but the post-pandemic psychological stress caused by the Covid-19 (PAPIST₁₉) has not received much attention. Current research addresses this gap and uses a comprehensive model drawn from the transactional model of stress and the Kahn psychological framework to advance the work of predicting PAPIST₁₉. Specifically, the current research investigates how PAPIST₁₉ is related to job engagement, and emotional exhaustion and how job reattachment mediates the relationship. In addition, we use health support climate (HSC) as a boundary condition in our model, which can weaken the impact of PAPIST₁₉ and enhance the effectiveness of job reattachment in reducing emotional exhaustion and increasing job engagement. To test our model, we collected data in multiple waves from Chinese seaports, where seafarers came to work after the restrictions were lifted in China. The current research is one of the earliest scholarly contributions. It paved the way for the research to solve the problem of workers returning to work after large-scale destructive events, and discussed important implications.

Beach tourists behavior and beach management strategy under the ongoing prevention and control of the COVID-19 pandemic: A case study of Qingdao, China

The sudden outbreak of COVID-19 has led beach tourism to a complete halt in January 2020, disrupting millions of livelihoods and businesses. Due to the economic importance of beach tourism, many governments reopened tourist beaches after the number of confirmed cases decreased. It is essential to open beaches orderly to meet the needs of tourists, maintain beach's health and restore coastal economy under the new reality. This paper selected Qingdao in China as a case study, drew on a questionnaire survey among beach tourists, summarized the effects of the COVID-19 on beach tourism industry and tourism enterprise, analyzed beach tourists' psychology and behavior, and developed beach management strategy under the ongoing prevention and control of COVID-19. The results showed that the COVID-19 pandemic caused severe damage to beach tourism which bases on travel and mobility, and this industry was temporarily suspended. With the changing epidemic situation, beach tourism witnessed a gradual recovery from stagnation to local tourism. Meanwhile, tourism enterprises were hit by the devastating impact of the COVID-19, causing problems such as business reduction, tense cash flow, high operating cost and unclear market prospect. Under the normalization of pandemic prevention, tourists did not have severe fear and anxiety about the pandemic, and placed great importance on the prevention and control measures, emergency measures and pandemic risk level of the beach destination. The pandemic also reshaped the perception and mode of beach tourism. Ecological tourism, travelling with family, and local tourism became the primary choices for tourists. Beach congestion, health status, and the quality of tourism services were the biggest concerns for tourists. Additionally, social media and short video APP became the new marketing channels. Finally, beach management strategies were proposed from the aspects of pandemic prevention and control, emergency management, information communication, tourist management, service management, and environmental management.

Deep Learning and Internet of Things for Beach Monitoring: An Experimental Study of Beach Attendance Prediction at Castelldefels Beach

Smart seaside cities can fully exploit the capabilities brought by Internet of Things (IoT) and artificial intelligence to improve the efficiency of city services in traditional smart city applications: smart home, smart healthcare, smart transportation, smart surveillance, smart environment, cyber security, etc. However, smart coastal cities are characterized by their specific application domain, namely, beach monitoring. Beach attendance prediction is a beach monitoring application of particular importance for coastal managers to successfully plan beach services in terms of security, rescue, health and environmental assistance. In this paper, an experimental study that uses IoT data and deep learning to predict the number of beach visitors at Castelldefels beach (Barcelona, Spain) was developed. Images of Castelldefels beach were captured by a video monitoring system. An image recognition software was used to estimate beach attendance. A deep learning algorithm (deep neural network) to predict beach attendance was developed. The experimental results prove the feasibility of Deep Neural Networks (DNNs) for beach attendance prediction. For each beach, a classification of occupancy was estimated, depending on the number of beach visitors. The proposed model outperforms other machine learning models (decision tree, k-nearest neighbors, and random forest) and can successfully classify seven beach occupancy levels with the Mean Absolute Error (MAE), accuracy, precision, recall and F1-score of 0.03, 92.7%, 92.9%, 92.7%, and 92.7%, respectively.

Estimating the effect of COVID-19 epidemic on shipping trade: An empirical analysis using panel data

The unexpected outbreak of COVID-19 epidemic is an unpredictable event in shipping trade. In this paper, we mainly investigate the gaps that occur in the shipping trade between China and different regions during the period February-October 2020 and to provide useful information for operation management of shipping industry. The data include a panel obtained from the National Statistics Institute to analyze the gap where a selected group of shipping trade in three regions are considered: European Union, North America, and Southeast Asia. On this basis, a dynamic panel data model is proposed to estimate the trend. We observe that government prevention and control measures have a negative impact on export trade, while import trade increases accordingly.

Early impact of COVID-19 pandemic on the molluscan shellfish supply chain in China

A farm-level survey and a market survey were conducted in China to study the impact of the COVID-19 on the shellfish supply chain in the early stage of the pandemic in 2020. 114 farms of 36 cites participated in an online survey from mid-July to late August, and 23 markets in five cities were investigated from June to November. The series results are expected to provide an insight for the fisheries and aquaculture sector to mitigate the impact of the pandemic on participants in the shellfish supply chain and to improve of the ability of the government to respond to such events in the future. Shellfish farmers and sellers have experienced a sharp drop in profits, largely due to shrinking demand. Relying on local employees and suppliers, shellfish farming activities have rapidly resumed since the gradual reopening from February. Nevertheless, demand has been slow to recover due to public concern about contamination of seafood with the virus. Additionally, we analyzed the ability and attitude of farms of different size to cope with the pandemic and the plight of shellfish sellers, and discussed government supports for different size farms and improvements in seafood distribution channels.