Embodied versus operational environmental indicators are often studied in isolation. This paper presents a cradle-to-grave Life Cycle Analysis of energy conservation measures for a planned large, operational carbon emission savings compared to Target Emissions Rate. The LCA solutions focused on structure, envelope, and operational systems. Embodied energy saving strategies encompassed the application of lean design principles and integration of low carbon materials. Operational energy saving techniques included the adoption of a fabric-first approach, adaptive thermal conditions and sustainable building systems. Cumulatively, these optimization strategies achieved a maximum of 16% and 13% savings on life cycle carbon and energy, respectively, compared to the original design.Embodied strategies saved 32% and 9% on embodied carbon and energy, respectively, while operational strategies reduced the original consumption by 14% on both indicators. Over a 60-year building lifetime, operational energy was 10 times higher than embodied energy, while operational carbon was 8 times higher than embodied carbon. The study findings have highlighted the significance of LCA for early stage building design decisions.

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Abstract. This paper presents findings of a case-study demonstrating the effectiveness of using WiFi networks to detect occupancy as opposed to CO 2 sensors, commonly used for demand-controlled heating, ventilation and air conditioning (HVAC) systems. The study took place in one building at the University of Manitoba Fort Garry campus in Canada. In a classroom, the number of WiFi connections was collected on an hourly basis over one-week, simultaneously with CO 2 concentration levels at 10-min intervals. The number of occupants in this classroom was also counted on an hourly basis over the same study period. Data analysis showed that WiFi counts predicted actual occupancy levels more accurately than CO 2 concentration levels, thus validating the use of this technology to track occupancy. This study was the first to use both CO 2 concentration and WiFi counts simultaneously as indicators for occupancy. Results demonstrated the possibility of using WiFi counts in large buildings for controlling HVAC systems at a higher accuracy and lower cost than other sensor technologies. Implications and influences: Given the large contribution of HVAC systems to overall buildings' energy consumption, this study presents a new method for efficiently operating HVAC systems. Results highlighted the accuracy of using WiFi connections as predictors for occupancy patterns to be used for controlling HVAC systems instead of CO 2 sensors. These findings provide a foundation for further research on using WiFi networks to manage and operate HVAC systems in new buildings. Efficient operation of these systems based on real-time occupancy as opposed to static schedules provides facility managers with an opportunity for significant energy savings at a relatively low cost.Keywords: buildings energy management / occupancy and energy consumption / smart buildings systems / green buildings / sensor-based HVAC systems

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