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Abstract. The impact of multiphase reactions involving nitrogen dioxide (NO2) and aromatic compounds was simulated in this study. A mechanism (CAPRAM 2.4, MODAC Mechanism) was applied for the aqueous phase reactions, whereas RACM was applied for the gas phase chemistry. Liquid droplets were considered as monodispersed with a mean radius of 0.1 µm and a liquid content (LC) of 50 µg m-3. The multiphase mechanism has been further extended to the chemistry of aromatics, i.e. reactions involving benzene, toluene, xylene, phenol and cresol have been added. In addition, reaction of NO2 with dissociated hydroxyl substituted aromatic compounds has also been implemented. These reactions proceed through charge exchange leading to nitrite ions and therefore to nitrous acid formation. The strength of this source was explored under urban polluted conditions. It was shown that it may increase gas phase HONO levels under some conditions and that the extent of this effect is strongly pH dependent. Especially under moderate acidic conditions (i.e. pH above 4) this source may represent more than 75% of the total HONO/NO2 - production rate, but this contribution drops down close to zero in acidic droplets (as those often encountered in urban environments).

Abstract Canada has numerous climatic and geographical regions and the Canadian housing stock (CHS) is diversified in terms of vintage, geometry, construction materials, envelope, occupancy, energy sources and heating, ventilation and air conditioning system and equipment. Therefore, strategies to achieve net zero energy (NZE) status with the current stock of houses need to be devised considering the unique characteristics of the housing stock, the economic conditions and energy mix available in each region. Identifying and assessing pathways for converting existing houses to NZE buildings at the housing stock level is a complex and multifaceted problem and requires extensive analysis on the impact of energy efficiency and renewable/alternative energy technology retrofits on the energy use and GHG emissions of households. A techno-economic analysis of retrofitting renewable/alternative energy technologies in the CHS to reduce energy consumption and GHG emissions was conducted to develop strategies to achieve or approach NZE status for Canadian houses. The results indicate that substantial energy savings and GHG emission reductions are techno-economically feasible for the CHS through careful selection of retrofit options. While achieving large scale conversion of existing houses to NZEB is not feasible, approaching NZE status is a realistic goal for a large percentage of Canadian houses.

Abstract Bitumen is too viscous to be produced by conventional recovery methods and significant amounts are too deep to be recovered by mining, necessitating enhanced in-situ oil recovery techniques. The majority of operating and planned in-situ bitumen projects employ thermal techniques to lower the bitumen's viscosity, allowing it to be produced. The viscosity characteristics of the bitumen consequently have a significant effect on production rates and recovery. Bitumen viscosity and chemical composition variation with depth within a single reservoir column has been reported for many heavy oil and oil sand reservoirs in the Western Canadian Sedimentary Basin and elsewhere in the world. This study investigates, through reservoir simulation, the effects of viscosity variation with depth on the SAGD process and the resulting produced oil characteristics. Oil characteristics, including chemical component and viscosity profiles were built into a variety of reservoir simulation models. The simulation results indicate that the produced oil viscosity and component concentration vary as the steam chamber develops. The trend of the produced oil characteristics is related to the original in-situ profiles of and the reservoir flow barriers. In conjunction with oil rate, surface heave, or other available data, the produced oil characteristics may be used to suggest steam chamber development and the presence of barriers or baffles. The presented approach has potential to become a useful technique for SAGD steam chamber growth monitoring and production optimization.

Bioplastics are alternatives of conventional petroleum-based plastics. Bioplastics are polymers processed from renewable sources and are biodegradable. This study aims at conducting an environmental impact assessment of the bioprocessing of agricultural wastes into bioplastics compared to petro-plastics using an LCA approach. Bioplastics were produced from potato peels in laboratory. In a biochemical reaction under heating, starch was extracted from peels and glycerin, vinegar and water were added with a range of different ratios, which resulted in producing different samples of bio-based plastics. Nevertheless, the environmental impact of the bioplastics production process was evaluated and compared to petro-plastics. A life cycle analysis of bioplastics produced in laboratory and petro-plastics was conducted. The results are presented in the form of global warming potential, and other environmental impacts including acidification potential, eutrophication potential, freshwater ecotoxicity potential, human toxicity potential, and ozone layer depletion of producing bioplastics are compared to petro-plastics. The results show that the greenhouse gases (GHG) emissions, through the different experiments to produce bioplastics, range between 0.354 and 0.623 kg CO2 eq. per kg bioplastic compared to 2.37 kg CO2 eq. per kg polypropylene as a petro-plastic. The results also showed that there are no significant potential effects for the bioplastics produced from potato peels on different environmental impacts in comparison with poly-β-hydroxybutyric acid and polypropylene. Thus, the bioplastics produced from agricultural wastes can be manufactured in industrial scale to reduce the dependence on petroleum-based plastics. This in turn will mitigate GHG emissions and reduce the negative environmental impacts on climate change.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

The construction industry is considered as one of the least productive, highest energy consuming, and least digitized industries. The Lean Management (LM) philosophy became a significant way for eliminating non-value-added activities and wastes during a building’s lifecycle. However, studies have shown that philosophies are not efficient by themselves to solve the issues of the construction industry. They need to be supported with the appropriate technologies and tools. Therefore, the integrated use of Building Information Modelling (BIM) with LM or Value Engineering (VE) were proposed in the literature. Nonetheless, it was also seen that BIM can provide more insights and improvements when BIM is integrated with data analysis tools to analyze BIM data. In the literature, the synergies between these concepts are generally addressed pairwise, and there is no comprehensive framework which identifies their relationships. Therefore, this study aims to develop a maturity framework that facilitates the adoption of LM, VE, BIM, and Big Data Analytic (BDA) concepts to address long-standing productivity and digitalization issues in the Architecture, Engineering, and Construction (AEC) industry. Design Science Research (DSR) methodology and its three-cycle view (relevance, rigor, and design cycle) were applied to build the proposed maturity framework. Two interviews were performed to identify and observe research problem in relevance cycle. In the rigor cycle, a comprehensive literature review was performed to create a base for the development of the maturity framework. In addition to the developed base of the framework, lean processes were added to this cycle. In the design cycle, the developed framework was evaluated and validated by five experts through face-to-face interviews. The importance of employer’s requirements to adopt the proposed methodologies, the negative impact of change orders, the importance of pre-construction phases to facilitate value creation and waste elimination, and the usage of common data environment with BIM were identified as the prominent application and adaptation issues.

Optimisation-based Energy Management Strategies for hybrid and electric vehicles have to face some issues for real-time applications. In this study,an online adaptive optimisation-based strategy is used for an electric vehicle with a Hybrid Energy Storage System including supercapacitors and batteries. The SCs voltage limitations are taken into account by using a feedback control. Indeed the voltage limitation is a key point for safe operations in the vehicle. A comparison with a more classical optimisation-based method is performed by simulations on a normalised driving cycle. The results point out a more effective behaviour of the adaptive strategy.