A New High-Resolution N2O Emission Inventory for China in 2008

Tuesday, 16 December 2014
Ziyin Shang1, Feng Zhou1,2, Philippe Ciais1,2, Shu Tao1, Shilong Piao1, Peter A Raymond3, Canfei He1, Bengang Li1, Rong Wang2, Xuhui Wang1,2, Shushi Peng2, Zhenzhong Zeng1, Han Chen1, Na Ying1, Xikang Hou1 and Peng Xu1, (1)Peking University, Beijing, China, (2)CEA Saclay DSM / LSCE, Gif sur Yvette, France, (3)Yale University, New Haven, CT, United States
The amount and geographic distribution of N2O emissions over China remain largely uncertain. Most of existing emission inventories use uniform emission factors (EFs) and the associated parameters and apply spatial proxies to downscale national or provincial data, resulting in the introduction of spatial bias. In this study, county-level and 0.1° × 0.1° gridded anthropogenic N2O emission inventories for China (PKU-N2O) in 2008 are developed based on high-resolution activity data and regional EFs and parameters. These new estimates are compared with estimates from EDGAR v4.2, GAINS-China, National Development and Reform Commission of China (NDRC), and with two sensitivity tests: one that uses high-resolution activity data but the default IPCC methodology (S1) and the other that uses regional EFs and parameters but starts from coarser-resolution activity data. The total N2O emissions are 2150 GgN2O/yr (interquartile range from 1174 to 2787 GgN2O/yr). Agriculture contributes 64% of the total, followed by energy (17%), indirect emissions (12%), wastes (5%), industry (2.8%), and wildfires (0.2%). Our national emission total is 17% greater than that of the EDGAR v4.2 global product sampled over China and is also greater than the GAINS-China, NDRC, and S1 estimates by 10%, 50%, and 17%, respectively. We also found that using uniform EFs and parameters or starting from national/provincial data causes systematic spatial biases compared to PKU-N2O. In addition, the considerable differences between the relative contributions of the six sectors across the six Agro-Climate Zones primarily reflect the different distributions of industrial activities and land use. Eastern China (8.7% area of China) is the largest contributor of N2O emissions and accounts for nearly 25% of the total. Spatial analysis also shows nonlinear relationships between N2O emission intensities and urbanization. Per-capita and per-GDP N2O emissions increase gradually with an increase in the urban population fraction from 0.3 to 0.9 among 2884 counties, and N2O emission density increases with urban expansion. Moreover, additional experiments and the use of a reliable data-driven approach or process-based models can improve the spatial resolution and reduce the uncertainties in PKU-N2O, especially from agricultural soils and manure management.