Abstract
This thesis exploits satellite remote sensing and in situ smoke measurement to estimate emissions from agricultural residue burning in Eastern China, a densely populated region with often poor air quality and which is one of China’s main agricultural burning regions. A new active fire (AF) detection and fire radiative power (FRP) retrieval algorithm is developed for use with the Suomi-NPP satellite’s VIIRS sensor, whose high spatial resolution band “I’ Bands provide an ability to detect the smaller (low FRP) fires missing from current satellite AF datasets. Daily fire radiative energy (FRE) – and thus fuel consumption - estimates are obtained by a link to diurnal cycle information from the Himawari geostationary spacecraft, and used to estimate emissions (CO2, CO, PM2.5 and BC) via multiplication by emissions factors derived from in situ measurements of smoke made by exploiting a new multi-sensor sampling design.Results show that VIIRS detects AFs with an FRP-minimum below 0.5 MW (cf. 6–8 MW for MODIS), and identifies typically 5 to 10 times more AF pixels across Eastern China. The resulting high spatiotemporal resolution agricultural fire emissions inventory is compared to two state-of-the-art global fire databases (GFAS and GFED), and shows fuel consumption emissions estimates 1 to 4 times higher for the burning seasons, highlighting the significance of the formally undetected low FRP active fires. Mean annual emissions of CO2, CO, PM2.5 and BC range from 16932 to 31107, 562 to 1035, 70 to 130, 6 to 11 Gg respectively (mean of 2012 – 2015), and the interannual variations seen appear potentially linked to changing farming activity and local fire management practices.
This research has improved understanding and quantification of agricultural residue burning in Eastern China, and the new “small fire” detection capability could in future be extended to wider (even global) scales, particularly in agricultural burning regions, in order to reduce the low biases that have been now clearly exposed in current fire emissions estimates of those areas.
| Date of Award | 2017 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Jeff Garmany (Supervisor) & Martin Wooster (Supervisor) |