Search

The last pandemic that hit all the countries in 2020 has inevitably led scientists and researchers to investigate and examine the indoor air quality in all types of enclosed spaces as people tend to spend most of their time inside the buildings. The students' group is one of the largest groups of people who spend most of their time in classrooms, characterized by a high occupant intensity and often by insufficient air quality. Therefore, the educational building is an important indoor environment for measuring air quality. This paper aims to investigate the factors that affect infection risk transmission and the strategies that can mitigate the transmissibility of the infection. The methodology involves two distinct elements: indoor environment quality factors and engineering control strategies. The results show that the factorsaffecting indoor air quality are relative humidity, temperature,CO2 and ventilation. Also, the control strategies that can mitigate the infectious risk and improve indoor air quality are ventilation, air filters and ultraviolet radiation.

This paper presents the outlines of a research project that aims to develop a semantic-based framework for delivering near real-time environmental footprint and informing effective operation and management strategies for the built environment. This paper argues that a semantic life cycle approach leveraging the value of real-time data can facilitate and enhance the accuracy of dynamic life cycle assessments. The methodology involves three distinct elements, namely semantics, dynamic data, and learning systems. Several use cases will be explored to validate the proposed methodology on real case studies. Following a review of related work, the methodology will be presented to explain the various components involved and the information exchange between different layers. The planned use case will be briefly introduced, followed by conclusion and future work.

The paper contributes to existing research on transmission of infectious diseases in indoor environments, with a focus on the SARS-Co V -2 virus, considered in an environment with a potentially high infectious risk, i.e. a university building. A multi-functional zone with variable occupancy schedules involving both students and staff is used as a case study. A computational fluid dynamics (CFD) model is developed to simulate and analyze three scenarios involving mixed, mechanical, and natural ventilation. Based on the physical and operational configuration of the selected zone, initial results show that mechanical ventilation involves areas of stagnant air (i.e. air velocity is less than 0.1m/s), while reliance on natural ventilation leads to increase in C02 levels. Hence, a mixed mode (natural and mechanical) ventilation is suggested. Then, based on the probability of the presence of (an) infected individual(s), considering the local COVID-19 incidence rate, initial estimates suggest that the Delta variant requires the air change rate (ACH) to be increased more than 1000 times, when compared to the original strain. The paper thus establishes a correlation between the prevalence of a given SARS-Co V -2 variant with the required air change rate, emphasizing the need to factor in not only the presence of infected individual(s), based on the local incidence rate, but also the viral charge of the dominant SARS-Co V -2 variant. The paper argues the need for a better controlled and optimized ventilation to ensure safer indoor environments.

Many seaports are facing increasing pressure to reduce their carbon footprint, while increasing their energy efficiency and global competitiveness. Moreover, energy consumption in seaports is continuously monitored to manage the increasing energy costs, these rising costs are reflected in the increased fuel demand. The fishing industry is one of the most energy intensive activity at seaports. In addition, the global human consumption of fish increased dramatically from 1950 to 2012. This paper will develop a roadmap to convert fishing ports into carbon-free ports. A number of techniques and methodologies will be used to analyze energy consumption in the port and buildings, and will include sustainability informed decision making. The overall objective of the net-zero port is to reduce energy dependence from the national grid by taking advantage of the electricity produced locally from solar energy. The roadmap that we have developed will contribute to the emergence of carbon-free fishery port ecosystem that can implement sustainable energy practices, including an assessment of the quality of the energy used in the fishery port and informed practices for promoting carbon-free societies.

The recent ongoing digital transformation of the energy landscape provides new opportunities to decarbonise energy-intensive industries, including the fish processing sector. The paper explores the potential of deploying multi-vector smart micro-grid solutions in fishery ports, sourced from dispatchable renewable generation, including solar energy. This is demonstrated in the Milford Haven Port in South Wales, United Kingdom. The proposed system is modelled using control scenarios developed based on data and energy models of the port. The control scenario makes energy use decisions based on the availability of dispatchable renewable sources and the price of energy from the local energy market. Also, we consider local energy storage by utilising the local electric fishing boat fleet as an alternative energy storage system. The results demonstrate optimised energy use through multi-vector smart micro-grid model by providing more than 70 percent reduction of energy use from grid.