Role of future scenarios in understanding deep uncertainty in long-term air quality management
Citation:
Gamas, J., R. Dodder, Dan Loughlin, AND C. Gage. Role of future scenarios in understanding deep uncertainty in long-term air quality management. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, 65(11):1327-1340, (2015).
Impact/Purpose:
This paper introduces the concept of using the Scenario Planning methodology for long-term air quality management. Scenario Planning is particularly useful in this context given deep uncertainties in the drivers of future emissions, such as population growth and migration, economic growth and transformation, climate change, land use change, technology development, human attitudes and behavior, and policies. We describe the development of four alternative scenarios and provide an illustrative application in which they are modeled in MARKAL and diffences in emissions highlighted.
Description:
The environment and its interactions with human systems, whether economic, social or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of deep uncertainty presents a challenge to organizations faced with making decisions about the future, including those involved in air quality management. Scenario Planning is a structured process that involves the development of narratives describing alternative future states of the world, designed to differ with respect to the most critical and uncertain drivers. The resulting scenarios are then used to understand the consequences of those futures and to prepare for them with robust management strategies. We demonstrate a novel air quality management application of Scenario Planning. Through a series of workshops, important air quality drivers were identified. The most critical and uncertain drivers were found to be “technological development” and “change in societal paradigms.” These drivers were used as a basis to develop four distinct scenario storylines. The energy and emission implications of each storyline were then modeled using the MARKAL energy system model. NOX and SO2 emissions were found to decrease for all scenarios, largely a response to existing air quality regulations. Future-year emissions differed considerably from one scenario to another, however, with key differentiating factors being transition to cleaner fuels and energy demand reductions.
