Abstract. Open burning of agricultural crop residues is widespread across eastern
China, and during certain post-harvest periods this activity is believed to
significantly influence air quality. However, the exact contribution of crop
residue burning to major air quality exceedances and air quality episodes
has proven difficult to quantify. Whilst highly successful in many regions,
in areas dominated by agricultural burning, MODIS-based (MODIS: Moderate Resolution Imaging
Spectroradiometer) fire emissions
inventories such as the Global
Fire Assimilation System (GFAS) and Global Fire Emissions Database (GFED) are suspected of significantly
underestimating the magnitude of biomass burning emissions due to the
typically very small, but highly numerous, fires involved that are quite
easily missed by coarser-spatial-resolution remote sensing observations. To
address this issue, we use twice-daily fire radiative power (FRP)
observations from the “small-fire-optimised” VIIRS-IM FRP product and
combine them with fire diurnal cycle information taken from the geostationary
Himawari-8 satellite. Using this we generate a unique high-spatio-temporal-resolution agricultural burning inventory for eastern China for the years
2012–2015, designed to fully take into account small fires well below the
MODIS burned area or active fire detection limit, focusing on dry matter
burned (DMB) and emissions of CO2, CO, PM2.5, and black carbon. We
calculate DMB totals 100 % to 400 % higher than reported by the GFAS and
GFED4.1s, and we quantify interesting spatial and temporal patterns previously
un-noted. Wheat residue burning, primarily occurring in May–June, is
responsible for more than half of the annual crop residue burning emissions
of all species, whilst a secondary peak in autumn (September–October) is associated
with rice and corn residue burning. We further identify a new winter
(November–December) burning season, hypothesised to be caused by delays in burning
driven by the stronger implementation of residue burning bans during the
autumn post-harvest season. Whilst our emissions estimates are far higher
than those of other satellite-based emissions inventories for the region,
they are lower than estimates made using traditional “crop-yield-based
approaches” (CYBAs) by a factor of between 2 and 5. We believe that this is
at least in part caused by outdated and overly high burning ratios being
used in the CYBA, leading to the overestimation of DMB. Therefore,
we conclude that satellite remote sensing approaches which adequately
detect the presence of agricultural fires are a far better approach to
agricultural fire emission estimation.
Supplementary material to "New eastern China agricultural burning fire emission inventory and trends analysis from combined geostationary (Himawari-8) and polar-orbiting (VIIRS-IM) fire radiative power products"
