Abstract
Cities are responsible for a large share of global energy consumption and CO2 emissions. Significant reduction of urban energy consumption and CO2 emissions is essential for meeting the ambitious climate stabilization targets. This hinges on having adequate understanding of the patterns and trends of emissions. It is essential to create datasets of cities emissions and utilize mapping techniques to inform planners and decision makers about the dynamics of urban carbon emissions. Due to the openness of cities and issues related to availability and accessibility of urban energy consumption data, this is a challenging task. It is critical to develop consistent methods for mapping emissions. Such methods and frameworks should enable cities to map their emissions with minimum data requirements. They should also be applicable to different cities across the world. As a preliminary effort, this study introduces a framework for synthesizing building and transport energy consumption data with the Local Climate Zones (LCZs) classification system. Drawing on preliminary results from applying the framework to Bangkok, Shanghai, and Tokyo, we explain how this approach can provide opportunities for standardizing urban carbon accounting. The paper concludes with suggestions for improving granularity and accuracy of emissions accounting. The concept of Local Energy Zones (LEZs) is introduced and is suggested to be used as a potentially suitable concept for analysing CO2 emissions dynamics of cities.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.