An Improved Emission Inventory of Crop Residue Burning in Fields in China Based on Statistics and MODIS Fire Products

Abstract:

Agricultural field burning plays an important role in atmospheric pollution and climate change. Current air quality simulation exhibits significant error in crop residue burning season. A high quality emission inventory is the foremost requirement for air quality model simulation. The development of such sporadic emission sources emission inventory is always challenging. Currently, satellite-based burned area methodologies specifically calibrated for crop residue burning are limited, whereas the combination of statistical date and satellite date will improve the accuracy of the result. This work aims to develop a higher accuracy emission inventory for agricultural burning in China and analyze its temporal and spatial distributions. Province-specific statistical data, distributed by the Chinese national government were utilized to estimate the total amount of crop residue burning for the year 2012. Specifically, on the basis of China’s realities we applied the latest China’s grain-to-straw ratio and used agriculture mechanization ratio for the first time to calculate the burning amount of crop residue. Based on the newest local experimental emission factors by province and crop type, the total amounts of TSP, PM₁₀, S0₂, NO_X, NH₃, CH₄, EC, OC, NMVOCs, CO and CO₂, emitted from crop residue burning in the field, were estimated. Emissions were allocated to a 40km×40km grid and 10-day interval by MODIS Fire product(MOD/MYD14A1). To reduce the impact of missing fire counts we modified the satellite date by statistical analysis. Our inventory applied the most detailed and latest activity date and improved the problem of satellite products’ limitation for crop residue burning in fields. Our approach provides a more consistent methodology for quantifying the emission of crop residue burning than the previously available method and our emission inventory could meet the need of air quality simulations.