A Review of Integrated Urban Planning Tools for Greenhouse Gas Mitigation : Linking Land Use, Infrastructure Transition, Technology, and Behavioral Change
Achieving the Sustainable Development Goals (SDGs) over the next 30 years will critically depend upon urban land use and infrastructure development actions taken across multiple sectors (buildings, energy, transportation, water-sanitation, and wast...
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| Language: | English |
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World Bank, Washington, DC
2020
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| Online Access: | http://documents.worldbank.org/curated/en/799601589271548870/A-Review-of-Integrated-Urban-Planning-Tools-for-Greenhouse-Gas-Mitigation-Linking-Land-Use-Infrastructure-Transition-Technology-and-Behavioral-Change-Technical-Paper http://hdl.handle.net/10986/33784 |
| Summary: | Achieving the Sustainable Development
Goals (SDGs) over the next 30 years will critically depend
upon urban land use and infrastructure development actions
taken across multiple sectors (buildings, energy,
transportation, water-sanitation, and waste) in global
cities. Integrated urban planning addresses a multiplicity
of urban sustainability objectives (e.g., economy,
environment, inclusivity, and resilience) (GPSC, World Bank
2018), including cross-sectoral and cross-scale linkages
(Ramaswami et al. 2016) and connection of physical planning
with social, cultural, behavior, and policy dimensions. The
objective of this report is to review the state of knowledge
(science) and the state of practice (models actually used by
cities for policy) for modeling the GHG mitigation benefits
achievable through integrated urban planning across the four
levers, with attention to the foundational Lever 1, CUD.
Although the field of urban sustainability is relatively
young, and the availability of robust data is uneven across
world cities, our review found that significant scientific
advances have occurred in modeling the four levers
representing integrated urban planning in the context of GHG
mitigation. Within each of the four levers, more than 30+
strategies were identified in the literature. For all the
strategies, the GHG mitigation potential can be modeled
using the same structure of algorithms, which is computed by
multiplying two key parameters: the first parameter is the
strategy effect per unit of an intervention, i.e., the
reduction in demand or resource use per unit of
intervention. The second parameter is the penetration rate
or adoption rate of each intervention in the strategy
scenario. Examples include the percentage of households
experiencing CUD improvements or purchasing energy-efficient
cars compared to the baseline. This rate has a high impact
on the citywide potential for GHG mitigation from
implementing a strategy and is shaped by human behavior and policy. |
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