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

Abstract

The amount and geographic distribution of N2O emissions over China remain largely uncertain. 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 emission factors (EFs) and parameters. These new estimates are compared with previous inventories, 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. Spatial analysis 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.

Spatio-Temporal Patterns and Source Identification of Water Pollution in Lake Taihu (China)

“…DA was used in backward stepwise mode to confirm the groups found by CA and to evaluate the spatio-temporal variations of the discriminant variables. In DA, the monitoring period or site variables were the clustering variables, while the parameters from originally-measured datasets were independent [11,31]. Principal component analysis (PCA) is based on the assumption that there exists a bilinear model, which could explain the variance of observed water quality data by using less orthogonal variables, known as principal components [32].…”

New model for capturing the variations of fertilizer‐induced emission factors of N2O

“…These EF values of 1% and 0.3% are assumed to remain constant. However, considerable evidence from field experiments and meta‐analysis demonstrates that EFs differ largely from the IPCC defaults and change with nitrogen additions, cultivation practice, and environmental conditions [ McSwiney and Robertson , ; Grace et al ., ; Hoben et al ., ; Kim et al ., ; Decock , ; Shcherbak et al ., ; Zhou et al ., ] (see supporting information Figure S1). For example, Shcherbak et al .…”

An inventory of the emission of ammonia from agricultural fertilizer application in China for 2010 and its high-resolution spatial distribution

“…These fertilizers (including synthetic and organic fertilizers) are used on 7% of the world's land area, making Chinese agriculture a hotspot for the global nitrogen (N) cycle . The use of synthetic fertilizers includes straight N and compound N (nitrogen and compound fertilizer respectively) (Zhou et al, 2014), and amounts to approximately 30% of the global total (http://faostat3.fao.org), or 41.5 Tg in 2010 (NBSC, 2011). This is 1.5 times the fertilizer use in 1995 (NBSC, 1996).…”

“…(5) Uncertainties. A reliable emission inventory requires a comprehensive assessment of uncertainties in activity data, EFs and parameters (Beusen et al, 2008) (Zhou et al, 2014). Previous studies typically focus only on uncertainties in EFs.…”