Abstract. Emission inventories are important for both simulating pollutant
concentrations and designing emission mitigation policies. Ho Chi Minh City
(HCMC) is the biggest city in Vietnam but lacks an updated spatial
emission inventory (EI). In this study, we propose a new approach to update
and improve a comprehensive spatial EI for major short-lived climate
pollutants (SLCPs) and greenhouse gases (GHGs) (SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs), PM10,
PM2.5, black carbon (BC), organic carbon (OC), NH3, CH4, N2O and CO2). Our originality is the use of
satellite-derived urban land use morphological maps which allow spatial
disaggregation of emissions. We investigated the possibility of using freely
available coarse-resolution satellite-derived digital surface models (DSMs) to
estimate building height. Building height is combined with urban built-up
area classified from Landsat images and nighttime light data to generate
annual urban morphological maps. With outstanding advantages of these remote
sensing data, our novel method is expected to make a major improvement in
comparison with conventional allocation methodologies such as those based on
population data. A comparable and consistent local emission inventory (EI)
for HCMC has been prepared, including three key sectors, as a successor of
previous EIs. It provides annual emissions of transportation, manufacturing
industries, and construction and residential sectors at 1 km resolution. The
target years are from 2009 to 2016. We consider both Scope 1, all direct
emissions from the activities occurring within the city, and Scope 2, that is
indirect emissions from electricity purchased. The transportation sector was
found to be the most dominant emission sector in HCMC followed by
manufacturing industries and residential area, responsible for over 682 Gg CO, 84.8 Gg NOx, 20.4 Gg PM10 and 22 000 Gg CO2 emitted in 2016. Due to a sharp
rise in vehicle population, CO, NOx, SO2 and CO2 traffic emissions show
increases of 80 %, 160 %, 150 % and 103 % respectively between 2009
and 2016. Among five vehicle types, motorcycles contributed around 95 % to
total CO emission, 14 % to total NOx emission and 50 %–60 % to CO2
emission. Heavy-duty vehicles are the biggest emission source of NOx, SO2 and particulate matter (PM)
while personal cars are the largest contributors to NMVOCs and CO2.
Electricity consumption accounts for the majority of emissions from
manufacturing industries and residential sectors. We also found that Scope 2
emissions from manufacturing industries and residential areas in 2016
increased by 87 % and 45 %, respectively, in comparison with 2009. Spatial
emission disaggregation reveals that emission hotspots are found in central
business districts like Quan 1, Quan 4 and Quan 7, where emissions can be
over 1900 times those estimated for suburban HCMC. Our estimates show
relative agreement with several local inherent EIs, in terms of total amount
of emission and sharing ratio among elements of EI. However, the big gap was
observed when comparing with REASv2.1, a regional EI, which mainly applied
national statistical data. This publication provides not only an approach
for updating and improving the local EI but also a novel method of spatial
allocation of emissions on the city scale using available data sources.
Building an Urban Spatial Structure from Urban Land Use Data: An Example Using Automated Recognition of the City Centre