Improvement of a Global High-Resolution Ammonia Emission Inventory for Combustion and Industrial Sources with New Data from the Residential and Transportation Sectors.

Abstract

There is increasing evidence indicating the critical role of ammonia (NH3) in the formation of secondary aerosols. Therefore, high quality NH3 emission inventory is important for modeling particulate matter in the atmosphere. Unfortunately, without directly measured emission factors (EFs) in developing countries, using data from developed countries could result in an underestimation of these emissions. A series of newly reported EFs for China provide an opportunity to update the NH3 emission inventory. In addition, a recently released fuel consumption data product has allowed for a multisource, high-resolution inventory to be assembled. In this study, an improved global NH3 emission inventory for combustion and industrial sources with high sectorial (70 sources), spatial (0.1° × 0.1°), and temporal (monthly) resolutions was compiled for the years 1960 to 2013. The estimated emissions from transportation (1.59 Tg) sectors in 2010 was 2.2 times higher than those of previous reports. The spatial variation of the emissions was associated with population, gross domestic production, and temperature. Unlike other major air pollutants, NH3 emissions continue to increase, even in developed countries, which is likely caused by an increased use of biomass fuel in the residential sector. The emissions density of NH3 in urban areas is an order of magnitude higher than in rural areas.

DOI: 10.1021/acs.est.6b03694

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Cite this paper

@article{Meng2017ImprovementOA, title={Improvement of a Global High-Resolution Ammonia Emission Inventory for Combustion and Industrial Sources with New Data from the Residential and Transportation Sectors.}, author={Wenjun Meng and Qirui Zhong and Xiao Yun and Xi Zhu and T . - Y . Huang and Huizhong Shen and Yilin Chen and Han Chen and Feng Zhou and Junfeng Liu and Xinming Wang and Eddy Y Zeng and Shu Tao}, journal={Environmental science & technology}, year={2017}, volume={51 5}, pages={2821-2829} }