Launching the Grand Challenges for Ocean Conservation

The ten most pressing Grand Challenges in Oceans Conservation were identified at the Oceans Big Think and described in a detailed working document:A Blue Revolution for Oceans: Reengineering Aquaculture for SustainabilityEnding and Recovering from Marine DebrisTransparency and Traceability from Sea to Shore:  Ending OverfishingProtecting Critical Ocean Habitats: New Tools for Marine ProtectionEngineering Ecological Resilience in Near Shore and Coastal AreasReducing the Ecological Footprint of Fishing through Smarter GearArresting the Alien Invasion: Combating Invasive SpeciesCombatting the Effects of Ocean AcidificationEnding Marine Wildlife TraffickingReviving Dead Zones: Combating Ocean Deoxygenation and Nutrient Runof

Selecting eco-friendly thermal systems for the "Vittoriale Degli Italiani" historic museum building

Thermal systems installed in museums should guarantee the maintenance of the optimal hygrothermal parameters ranges for the conservation of their collection materials. Considering the preservation of historic buildings, according to their historical and landscaping constraints, not all the thermal system typologies could be installed in these buildings' typologies. Therefore, the main aim of this paper is to present some indications for the choice of the best thermal system solutions for a considered historic museum building, called Vittoriale degli Italiani, in the north of Italy, taking into account their installation feasibility and their related environmental impacts. The methodology includes a monitoring of the current hygrothermal parameters as well as the assessment of design heat and cooling loads related to the maintenance of the optimal hygrothermal parameters ranges for the conservation of collection materials. In addition, a Life Cycle Assessment (LCA) of each selected system typology is considered for highlighting the most eco-friendly solution among the suitable ones. The obtained results highlights the feasible thermal system solutions able to maintain the hygrothermal parameters between the optimal ranges with a lower environmental impact in the Vittoriale degli Italiani historic museum building

Screening of energy efficient technologies for industrial buildings' retrofit

This chapter discusses screening of energy efficient technologies for industrial buildings' retrofit

Preventive conservation strategies for sustainable urban pollution control in museums

The last 40 years have seen major changes in the sources and concentrations of urban pollution (nitrogen dioxide, sulfur dioxide, hydrogen sulfide, and particulates). During this time, research has advanced our understanding of the impact of pollutants on objects in urban museums. As a consequence, pollutant control has become an important aspect of preventive conservation. There is also increased awareness of the need for pollution control strategies that are sustainable at an organizational and global level. This report, prepared by a chemist, a conservator, and two building scientists, reviews strategies for minimizing the impact of urban pollution on museum collections. The results of new research funded by the UK government identify current (1999) internal pollution levels in both naturally ventilated and air-conditioned museums with particle and gaseous filtration, in relation to external concentrations, ventilation strategies, and the characteristics of the internal fabric and finishes of these buildings. The last 40 years have seen major changes in the sources and concentrations of urban pollution (nitrogen dioxide, sulfur dioxide, hydrogen sulfide, and particulates). During this time, research has advanced our understanding of the impact of pollutants on objects in urban museums. As a consequence, pollutant control has become an important aspect of preventive conservation. There is also increased awareness of the need for pollution control strategies that are sustainable at an organizational and global level. This report, prepared by a chemist, a conservator, and two building scientists, reviews strategies for minimizing the impact of urban pollution on museum collections. The results of new research funded by the UK government identify current (1999) internal pollution levels in both naturally ventilated and air-conditioned museums with particle and gaseous filtration, in relation to external concentrations, ventilation strategies, and the characteristics of the internal fabric and finishes of these buildings

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

Open-source digital technologies for low-cost monitoring of historical constructions

This paper shows new possibilities of using novel, open-source, low-cost platforms for the structural health monitoring of heritage structures. The objective of the study is to present an assessment of increasingly available open-source digital modeling and fabrication technologies in order to identify the suitable counterparts of the typical components of a continuous static monitoring system for a historical construction. The results of the research include a simple case-study, which is presented with low-cost, open-source, calibrated components, as well as an assessment of different alternatives for deploying basic structural health monitoring arrangements. The results of the research show the great potential of these existing technologies that may help to promote a widespread and cost-efficient monitoring of the built cultural heritage. Such scenario may contribute to the onset of commonplace digital records of historical constructions in an open-source, versatile and reliable fashion.Peer ReviewedPostprint (author's final draft

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs