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Passive cooling energy systems are significantly important in achieving efficient design and performative built environment. Encouragingly, there are many passive cooling energy systems at three spatial levels of macro, meso and micro. In this research study, these energy systems are identified and are assessed in a SWOT analysis evaluation. Apart from social and economic implications that are broad and effective for most of passive cooling energy systems, this study focuses on the energy systems’ implications across five indicators of practice, health, environment, energy and policy, which are significant for disciplines of sustainable energy systems and the built environment. This study aims to evaluate the interdependency of each indicator across three spatial levels and then argue for methods that can be considered for potential implementation of passive cooling energy systems. Furthermore, this study offers a holistic overview of all available passive cooling energy systems and argue based on interplay between five indicators across the three studied spatial levels. This study focuses on warmer climate zones (e.g. hot and dry; hot and humid), where passive cooling is expected to me more effective and obligatory. As a result, this study aims to help energy specialists, policy makers, planners and designers to evaluate how they can utilize passive cooling energy systems based on the key studied indicators. Finally, this paper gives an overview of gaps in policy and practice implementation of such systems in practice and their effectiveness at various spatial levels of the built environment.

AbstractClimate change effects along with anthropogenic activities present the main factors that threaten the existence of heritage sites across the north Nile Delta of Egypt close to the coastline of the Mediterranean Sea. Observing the changes in the landscape close to the archaeological sites is an important issue for decision‐makers in terms of reducing the negative impact of natural events and human activities. The coastal heritage sites are becoming strongly threatened by the rising sea level phenomena that will happen due to global warming. Focusing on the distribution of the archaeological sites, this study aims to detect the areas at risk of shoreline erosion or accretion in the northern shoreline of the Nile Delta. In this study, the changes in the northern shoreline of the Nile Delta were observed and calculated during the last hundred years based on the integration between the old topographic maps from surveys in 1900, 1925 and 1945, optical satellite images captured by Landsat in 1972, 1986 and 2000; Sentinel2 2021; and the Radar SRTM data. The results of this study showed that the changes were enormous with a great shoreline erosion process over the last 121 years recorded along the shoreline in the periods between 1900–1925, 1925–1945, 1945–1972, 1972–1986, 1986–2000 and 2000–2021. The areas eroded were about 5.3, 4.7, 5.6, 8.9, 2.5 and 5.4 km2, respectively. Such negative movements caused the loss of two heritage sites, and the expected changes will lead to the loss of additional heritage sites in the next 500 years. Furthermore, a model was suggested for protecting the coastal heritage sites threatened by the risk of submergence. This study can help the decision‐makers to detect the coastal archaeological sites at risk and create innovative solutions for protecting these irreplaceable heritage sites.

The transition to low carbon energy systems poses challenges in terms of energy efficiency. In building refurbishment projects, efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings, together with other benefits. Measured building performance, however, often reveals a significant gap between the predicted energy use (design stage) and actual energy use (operation stage). For this reason, lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement. In this research, interpretable regression models are built with data at multiple temporal resolutions (monthly, daily and hourly) and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves (TRVs) and gas absorption heat pumps (GAHPs) as well as giving insights on the performance of the building as a whole. Further, as part of modelling research, time of week and temperature (TOWT) approach is reformulated and benchmarked against its original implementation. The case study chosen is Hale Court sheltered housing, located in the city of Portsmouth (UK). This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS. The results obtained are used to illustrate possible extensions of the use of energy signature modelling, highlighting implications for energy management and innovative building technologies development.

The introduction of natural gas in the Greek energy market broadened the options in the field of space heating. Residents in five major Greek cities can choose from a variety of different fuels and systems for heating their houses or working spaces; 12 more cities will be connected to the gas network within the next 5 years. Considering that space heating is the major energy consuming activity in the Greek building sector and that the environmental constrains imposed by the Kyoto protocol will be met only with difficulty, if at all, a strategy concerning the developments in space heating seems to be necessary. This however presupposes an elaborate analysis of the overall performance of the alternative systems, taking into consideration the particular conditions of the Greek energy system and the ‘established’ way of designing residential and mixed-use buildings. The present paper aims to present the empirical comparative results related to the three most popular heating systems operated in Greek multi-apartment and mixed-use buildings, which use three different fuels, respectively: a central oil-fired boiler, a unitary gas-fired boiler and unitary heat pumps.

In the light of The Paris Agreement (COP 21), global leaders reached a consensus to curtail the increase in global temperature up to 2.0 °C ideally 1.5 °C pre-industrial level. Likewise, it has become a pathway to accomplish long-term goals of achieving carbon neutrality. In this regard, this paper aims to explore the role of green process innovation and environmental orientation toward environmental performance for achieving the long-term goal of carbon neutrality. In addition, this paper also discovers a mediating role of green competitive advantage in said context. Using data from a survey among managers of equipment manufacturing sector, the study employed structural equation modeling technique and found that green process innovation, environmental orientation and green competitive advantage significantly influence environmental performance. Subsequently, mediation analysis indicated that green competitive advantage partially mediates the relation from green process innovation and environmental orientation to environmental performance. In light of the carbon neutrality targets, the study highlight that improving environmental performance through green process innovation and environmental orientation can be a way-forward for manufacturing sector to play its role to achieve carbon neutrality. The study concludes with theoretical and practical implications.

Abstract Cost-effectively decarbonising the power sector and household energy use using variable renewable energy will require that electricity consumption becomes much more flexible and responsive to constraints in supply and the distribution network. In recent years residential demand response (DR) has received increasing attention that has sought to answer, based on current evidence, questions about how much consumers will engage with DR. This paper critically reviews the evidence base for residential consumer engagement with DR and draws out several important limitations in it. We argue for a more action-oriented focus on developing practical strategies to enable and unlock greater loadshifting and consumer engagement with DR within a changing technology and regulatory context. A number of recommendations are put forward for accelerating UK consumer engagement with DR, presented under three broad strategies: (a) promote awareness of smart tariffs, smart meters and storage and automation behind-the-meter devices as mutually-supportive components within a common ‘DR technology cluster’; (b) deliver targeted support for adoption of electric vehicles and other storage and automation technologies; (c) enable and support informed adoption of DR-enabling products and services through ‘smarter’ digital comparison tools (DCTs), data portability, and faster, simpler switching. The interdependency between components within this DR technology cluster delivers efficiency but also poses a risk that one delayed component (e.g., smart metering) will hold-up policy and industry support for other components. The urgency of decarbonisation goals makes it necessary to push forward as many of these elements as possible rather than the pace being set by the slowest.

Biogas is one of the most attractive renewable resources due to its ability to convert waste into energy. Biogas is produced during an anaerobic digestion process from different organic waste resources with a combination of mainly CH4 (~50 mol/mol), CO2 (~15 mol/mol), and some trace gasses. The percentage of these trace gases is related to operating conditions and feedstocks. Due to the impurities of the trace gases, raw biogas has to be cleaned before use for many applications. Therefore, the cleaning, upgrading, and utilization of biogas has become an important topic that has been widely studied in recent years. In this review, raw biogas components are investigated in relation to feedstock resources. Then, using recent developments, it describes the cleaning methods that have been used to eliminate unwanted components in biogas. Additionally, the upgrading processes are systematically reviewed according to their technology, recovery range, and state of the art methods in this area, regarding obtaining biomethane from biogas. Furthermore, these upgrading methods have been comprehensively reviewed and compared with each other in terms of electricity consumption and methane losses. This comparison revealed that amine scrubbing is one the most promising methods in terms of methane losses and the energy demand of the system. In the section on biogas utilization, raw biogas and biomethane have been assessed with recently available data from the literature according to their usage areas and methods. It seems that biogas can be used as a biofuel to produce energy via CHP and fuel cells with high efficiency. Moreover, it is able to be utilized in an internal combustion engine which reduces exhaust emissions by using biofuels. Lastly, chemical production such as biomethanol, bioethanol, and higher alcohols are in the development stage for utilization of biogas and are discussed in depth. This review reveals that most biogas utilization approaches are in their early stages. The gaps that require further investigations in the field have been identified and highlighted for future research.

Abstract The use of electric bus fleets has become a topical issue in recent years. Several companies and municipalities, either voluntarily or to comply with legal requirements, will transition to greener bus fleets in the next decades. Such transitions are often established by fleet electrification targets, which dictate the number of electric buses that should be in the fleet by a given time period. In this paper we introduce a comprehensive optimization-based decision making tool to support such transitions. More precisely, we present a fleet replacement problem which allows organizations to determine bus replacement plans that will meet their fleet electrification targets in a cost-effective way, namely considering purchase costs, salvage revenues, operating costs, charging infrastructure investments, and demand charges. We account for several charging infrastructure options, such as slow and fast plug-in stations, overhead pantograph chargers, and inductive (wireless) chargers. We refer to this problem as the electric bus fleet transition problem, and we model it as an integer linear program. We apply our model to conduct computational experiments based on several scenarios. We use real data provided by a public transit agency in order to draw insights into optimal transition plans.