CO2 emission from passenger travel in Guangzhou, China: A small area simulation. (September 2018) - Ma, Jing; Zhou, Suhong; Mitchell, Gordon; Zhang, Jiting
Abstract: Urban passenger travel is a major source of greenhouse gas emission. For China, understanding how passenger transport CO2 emission varies within cities is constrained by data availability, which limits development of mitigation policies and interventions targeted at specific areas or populations. We address this problem by applying an improved bottom-up methodology to provide temporal and spatially resolved estimates of daily passenger transport CO2 emission for urban Guangzhou. Drawing on sample census data we develop a spatial microsimulation of the population, which applied with an activity diary survey allows spatial simulation of the synthetic population's daily travel and transport CO2 emission at the sub-district scale for workday and weekend, respectively. Point-of-interest (POI) data is used to quantify the connection between urban form, passenger travel and transport CO2 emission. Results show that people residing in the compact city centre make shorter trips, have more non-motorised travel and emit less CO2 on both workday and weekend. In contrast, residents of newly developed urban areas and remote districts, characterised by low population and employment density, and poor accessibility to facilities and services, travel further generating more CO2 emission on a typical workday, but exhibit significant variation between workday and weekend. The microsimulation approach presents greater insight into the micro-scale spatio-temporal variability of passenger transport CO2 emission in a Chinese mega-city than has previously been possible. Highlights: Develop a spatial microsimulation of urban passenger travel and CO2 emission for Guangzhou. Provide spatially resolved estimates of CO2 emission at the sub-district scale on workday and weekend. Apply POI data to quantify the connection between urban form, passenger travel and carbon emission. Present great insight into the micro-scale spatio-temporal variability of passenger transport CO2 emission.