Modeling Sustainability Scenarios in the Baltimore-Washington (DC) Region: Implications for Methodology and Policy

• Published in: Journal of the American Planning Association 2020-04, Vol.86 (2), p.250-263
• Main Authors: Knaap, Gerrit-Jan, Engelberg, Daniel, Avin, Uri, Erdogan, Sevgi, Ducca, Fred, Welch, Timothy F., Finio, Nicholas, Moeckel, Rolf, Shahumyan, Harutyun
• Format: Article
• Language: English
• Subjects: autonomous vehicles; Baltimore-Washington region; exploratory scenario analysis; loosely coupled models; uncertainty
• ISSN: 0194-4363; 1939-0130
• DOI: 10.1080/01944363.2019.1680311

Problem, research strategy, and findings: Planners today are confronted with unprecedented uncertainty in economic, political, and technological environments, especially at the regional scale. An increasingly common approach to addressing such uncertainty is exploratory scenario analysis. To provide new insights into the methods and utility of such analyses, we conducted a scenario analysis of the Baltimore (MD)-Washington (DC) region by engaging a technical advisory committee and exercising a loosely coupled suite of advanced transportation, land use, and environmental impact models. Our analysis suggests the future is indeed uncertain and may evolve into plausible but quite different alternative scenarios. Key drivers of these scenarios include fuel prices; the rate and form of technological change, especially in the transportation sector; and the restrictiveness of land use controls. Takeaway for practice: By developing exploratory scenario analyses and analyzing them using advanced computational models, planners can gain insights into how best to address uncertain development trends, such as how and to what degree planners can influence the adoption of electric and automated vehicles, how and where to guide development patterns through land use controls, and how best to respond to variation in the cost of energy, which could have dramatic impacts on the future sustainability of cities and regions. Although such scenario analyses cannot in most circumstances provide unambiguous robust or contingent policy prescriptions, they can provide important insights for raising public awareness and provide the foundation for further policy evaluation.