School of Earth Sciences - Theses
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ItemRecent Trajectories in Urban Emissions from Remote Sensing Proxies( 2021)The United Nations Framework Convention on Climate Change (UNFCCC) motivates monitoring fossil fuel emission variations. This thesis studies the trends in urban fossil fuel emissions of Carbon Dioxide (CO2) and their drivers by developing an algorithm for delineating urban boundaries to generate masks for population and CO2 emissions and applies bottom-up techniques to approximate on-road emissions. The algorithm named BUNTUS (Built-up, Nighttime Lights, and Travel time for Urban Size) incorporates three remote sensing datasets; built-up area extracted from Landsat imagery, nighttime lights datasets, and travel time rasters. These three datasets are combined through a ruleset to produce an urban boundary. BUNTUS made 125 city boundaries, out of which 91 cities are studied. There are two opinions about the impact of urbanization on fossil fuel emissions intensification. First, some scientists consider that developing cities produce more fossil fuel emissions due to the migration of the rural population into cities. On contrary, the second opinion says that once a city develops economically, it becomes a low-emissions city. To test the role of urbanization in emissions intensification, this study quantified the urban emissions of 91 cities by taking ODIAC (Open-source Data Inventory for Anthropogenic CO2) as CO2 emission proxies and LandScan’s raster for population count. We find that urban CO2 emissions are increasing everywhere but that the dominant drivers differ according to development. Urban emissions are increasing along with urban populations, but per capita emissions are often growing more slowly than their national counterparts. A cluster analysis of factors shows that developing countries are dominated by cities with the rapid area and per capita CO2 emissions increases. Cities in the developed world, by contrast, show slow area and per capita CO2 emissions growth. The thesis also updates an existing global CO2 emissions inventory (FFDAS), improving its resolution and sectoral detail. FFDAS employs a data assimilation approach and yields globally gridded datasets of CO2 emissions. This study can serve as a foundation to study emissions trends in cities and on-road emissions inventory development.