• TA-23-C030 – Evaluating Occupants’ Willingness-to-Pay to Avoid Consequences of Extreme Climate Change Weather Events: Lessons Learned From the Ottawa 2022 Derecho

TA-23-C030 – Evaluating Occupants’ Willingness-to-Pay to Avoid Consequences of Extreme Climate Change Weather Events: Lessons Learned From the Ottawa 2022 Derecho

ASHRAE , 2023

Publisher: ASHRAE

File Format: PDF

$8.00$16.00


Extreme weather events are predicted to increase both in frequency and intensity requiring new and novel adaptation solutions while continuing to reduce annual greenhouse gas emissions. Power outages can occur due to these extreme weather events and cause subsequent consequences such as loss of productivity, perishable goods, and health-related impacts. Financial consequences can be quantified using different strategies such as Value of Loss Load (VoLL) and occupants’ Willingness-to-Pay (WTP), concepts previously used in energy supply security. VoLL has been previously considered in terms of building performance simulation, but WTP could not be directly assessed through simulation as it requires experimental investigation on occupants' risk tolerance in the face of extreme weather events. The goal of this research is to evaluate occupants’ WTP and find effective indicators and their relative importance by considering the Ottawa May 2022 derecho weather event which caused extended power outages of up to two weeks. To better understand occupants' WTP, a survey was developed and polled 403 participants to evaluate their experience and opinions relating to Ottawa’s derecho event. The survey found that participants’ WTP varies in the range of $571 to $16,666 considering different outage times and experienced costs. Experiencing costs such as emergency supply costs (i.e., food, batteries, flashlights, and power generator) and leaving costs is the most impactful parameter affecting the rate of occupants’ WTP. Moreover, experiencing outage events is significantly impactful when they cause more than a four-day power outage which could be considered as a factor in developing future time-variant cost models for extreme climate change events.

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