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© 2020 Elsevier Ltd Free cooling of buildings uses the nocturnal outdoor air as a heat sink via a ventilation process. This could be performed by storing the night coolness for use during the daytime as appropriate. Due to the latent heat capacity, phase change material (PCM) could play anessential role in the effective operation of the free cooling systems by shifting the daytime peak load to the night. However, there is a scarceness on the technology application in hot climates. This paper presents results of a parametric investigation into the application of PCMs as thermal energy storage (TES) to provide sustainable cooling to buildings in hot arid climate by making use of the night-time free cooling. The proposed TES medium comprises an arrangement of metallic modules filled with RT28HC PCM. Numerous geometrical configurations and operational parameters have been assessed. A transient CFD simulation has been employed using ANSYS Fluent software. Validation of the numerical results with experimental data has shown a good agreement. The results have demonstrated that the temperature difference between the PCM and the air, at appropriate air flow rate would have a significant impact on the performance of the system. A free cooling system based on the proposed arrangement has the potential to meet around 42% of a typical building cooling load and has the ability to save up to 67% of building cooling energy load in summer season compared to conventional air-conditioning systems in hot arid climates.

Abstract The effect of the thermal environment on performance and productivity has been a focus of interest among indoor environmental researchers for nearly a century, but most of that work has been conducted in relative isolation from the cognate disciplines of human performance evaluation. The present review examines thermal environmental effects on cognitive performance research conducted across multiple disciplines. After differentiating performance from productivity, we compare the two dominant conceptual models linking thermal stress to performance; (1) the inverted-U concept and (2) the extended-U relationship. The inverted-U specifies a single optimum temperature (or its corresponding subjective thermal sensation) at which performance is maximised. In contrast, the extended-U model posits a broad central plateau across which there is no discernible thermal effect on cognitive performance. This performance plateau is bounded by regions of progressive performance decrements in more extreme thermal conditions. The contradictions between these opposing conceptual models might derive from various confounding factors at play in their underlying research bases. These include, inter alia, environment-related, task-related, and performer-related factors, as well as their associated two-way and three-way interaction effects. Methodological discrepancies that might also contribute to the divergence of these conceptual models are evaluated, along with the proposed causal mechanisms underlying the two models. The weight of research evidence reviewed in this paper suggests that the extended-U hypothesis fits the relationship between moderate thermal environments and cognitive performance. In contrast to the inverted-U relationship, implemention of the extended-U in indoor climate control implies substantial reductions in building energy demand, since it permits the heating and cooling setpoint deadband to expand across the full width of the thermal comfort zone, or even slightly further during emergencies such as peak demand events on the electricity grid. Use of personal comfort systems can further extend the thermostat setpoint range beyond the comfort zone.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.

Biomass plays an important role in the world primary energy supplies, currently providing ∼14% of the world's primary energy needs and being the fourth largest contributor following coal, oil and natural gas. Over the past decade, domestic biomass heating has received more governmental and public supports than ever before in many developed countries, such as the UK. Although biomass combustion releases some combustion pollutants, biomass is renewable and produces little net CO 2 emissions to the atmosphere. Owing to the low sulphur and low nitrogen contents of many biomass materials, substituting biomass for fossil fuels, particularly coal, can reduce SO x and NO x emissions. This study investigated flue gas emissions, particularly carbon monoxide and nitrogen oxides, of a domestic biomass boiler under various operating conditions. The biomass boiler used in this study satisfies the current EU regulation (EN 303-05) on emissions of domestic biomass boilers. Emissions of the boiler had been measured not only under normal combustion conditions, but also under 'idle' combustion conditions when the boiler was not in but was ready for full operation. The experimental results are analysed and presented in this paper. Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Effective waste management is of paramount importance as it contributes significantly to environmental preservation, mitigates health hazards, and aids in the preservation of precious resources. Conversely, mishandling waste not only presents severe environmental risks but can also disrupt the balance of ecosystems and pose threats to biodiversity. The emission of carbon dioxide, methane, and greenhouse gases (GHGs) can constitute a significant factor in the progression of global warming and climate change, consequently giving rise to atmospheric pollution. This pollution, in turn, has the potential to exacerbate respiratory ailments, elevate the likelihood of cardiovascular disorders, and negatively impact overall public health. Hence, efficient management of trash is extremely crucial in any society. It requires integrating technology and innovative solutions, which can help eradicate this global issue. The internet of things (IoT) is a revolutionary communication paradigm with significant contributions to remote monitoring and control. IoT-based trash management aids remote garbage level monitoring but entails drawbacks like high installation and maintenance costs, increased electronic waste production (53 million metric tons in 2013), and substantial energy consumption for always-vigilant IoT devices. Our research endeavors to formulate a comprehensive model for an efficient and cost-effective waste collection system. It emphasizes the need for global commitment by policymakers, stakeholders, and civil society, working together to achieve a common goal. In order to mitigate the depletion of manpower, fuel resources, and time, our proposed method leverages quick response (QR) codes to enable the remote monitoring of waste bin capacity across diverse city locations. We propose to minimize the deployment of IoT devices, utilizing them only when absolutely necessary and thereby allocating their use exclusively to central garbage collection facilities. Our solution places the onus of monitoring garbage levels at the community level firmly on the shoulders of civilians, demonstrating that a critical aspect of any technology is its ability to interact and collaborate with humans. Within our framework, citizens will employ our proposed mobile application to scan QR codes affixed to waste bins, select the relevant garbage level, and transmit this data to the waste collection teams’ database. Subsequently, these teams will plan for optimized garbage collection procedures, considering parameters such as garbage volume and the most efficient collection routes aimed at minimizing both time and fuel consumption.

The COVID-19 pandemic represents a type of force majeure that significantly and unexpectedly affected all human lifestyles. This study includes an integrative review of articles published across Scopus and Web of Science journals and compiled using the systematic review methodology based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement and VOSreview (visualization of similarities) software by defining keywords that include “construction industry” and “force majeure” and “environmental risks” as a starting point. Moreover, the research years and the countries covered by this research were determined in a second stage. Finally, the abstracts of selected studies were reviewed in order to extract factors similar to the pandemic conditions of COVID-19 along with the brief results of the research. Out of 6384 publications identified and 56 publications reporting, 20 studies fulfilled the inclusion criteria with full text. Based on our findings, there has been a continuous growth of publications on construction risk and environmental research since 2010. Malaysia had the greatest contribution to the research topic of the countries covered by the study, followed by Egypt. The Engineering, Construction and Architectural Management journal published the greatest number of publications related to the research topic. In this review, the most important previous studies are classified according to their handling of force majeure and environmental risks and the most important factors mentioned in these studies are identified. In addition, recommendations are made for dealing with the COVID-19 pandemic and for mitigating its effects on the construction industry in the Arab world and Malaysia. The results of this review will benefit researchers and construction companies alike in furthering research on reducing the risks of COVID-19 to construction projects and avoiding the significant economic loss that results from stopping these projects.

Abstract A biomass oil/diesel blend was prepared using an emulsion method and combusted in a diesel engine. An injector was then removed and the morphology, composition, and structure of the carbonaceous deposits on the pintle-type nozzle were characterized using a combination of HRTEM, SEM/EDAX, Raman and XRD. Results showed that the carbon deposition of the emulsified fuel with high crystallinity was greater than that of diesel. The agglomerated particulate diameters of the deposited carbon from diesel and emulsified fuel were approximately 10–30 μm and 50 μm, respectively. The carbon deposition mechanism from the emulsified fuel was attributed to the high oxygen content of the groups leading to increased polymerization and subsequent condensation on the nozzle surfaces that was then carbonised.

Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.