County-level of particle and gases emission inventory for animal dung burning in the Qinghai–Tibetan Plateau, China

Abstract

Emissions from animal dung burning in the Qinghai–Tibetan Plateau (QTP) influenced heavily on the regional and global climate and environment, from which the emission inventory of multiple pollutants is not yet available. This study developed a county-level emission inventory of particles and gases pollution based on field measured emission factors and detailed activity data for the QTP in 2019. The results revealed that the total emissions of particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), organic carbon (OC), elemental carbon (EC), eight ions, fifty-one polycyclic aromatic hydrocarbons (PAHs) in gaseous and particulate phases, 108 volatile organic compounds (VOCs), CO, and CO2 were 41.1, 23.1, 2.36, 3.15, 1.13, 6.55, 135, and 4963 Gg, respectively. Gonghe, Qilian, Nyima, and Gangcha Counties in northeast of Qinghai and northwestern Tibet were the major contributors of all pollutants contributed (accounting for 11.9%–14.6% of the total emission) due to their higher livestock numbers. Sheep dung burning contributed a little more (average of 67.1%) than yak dung burning (32.9%) due to the high EFs and consumptions. For temporal distribution, the heating season contributed majority of the total emissions (70%–82%). Although with much less population, the QTP showed even higher emission densities than those in plain areas due to less oxygen and poor combustion technology. Compared with existing emission inventories, the uncertainties of all pollutant emission inventories were considerably reduced (42.7–163%), with EC as an exception because of its high coefficients of variation of EFs than the other pollutants. The developed emission inventory can help formulate targeted air pollution control measures for the QTP region by providing detailed information on the spatiotemporal distribution of multitype air pollutants. Meanwhile, the relative high resolution and accuracy inventory could serve a better basis for atmospheric modeling such as pollution transportation and source apportionment in both regional and global scales.