Increased greenhouse gas emissions intensity of major croplands in China: Implications for food security and climate change mitigation

Abstract

Balancing crop production and greenhouse gas (GHG) emissions from agriculture soil requires a better understanding and quantification of crop GHG emissions intensity, a measure of GHG emissions per unit crop production. Here we conduct a stateof-the-art estimate of the spatial-temporal variability of GHG emissions intensities for wheat, maize, and rice in China from 1949 to 2012 using an improved agricultural ecosystem model (Dynamic Land Ecosystem Model-Agriculture Version 2.0) and meta-analysis covering 172 field-GHG emissions experiments. The results show that the GHG emissions intensities of these croplands from 1949 to 2012, on average, were 0.10-1.31 kg CO 2-eq/kg, with a significant increase rate of 1.84-3.58 × 10-3 kg CO 2-eq kg −1 year −1. Nitrogen fertilizer was the dominant factor contributing to the increase in GHG emissions intensity in northern China and increased its impact in southern China in the 2000s. Increasing GHG emissions intensity implies that excessive fertilizer failed to markedly stimulate crop yield increase in China but still exacerbated soil GHG emissions. This study found that overfertilization of more than 60% was mainly located in the winter wheat-summer maize rotation systems in the North China Plain, the winter wheat-rice rotation systems in the middle and lower reaches of the Yangtze River and southwest China, and most of the double rice systems in the South. Our simulations suggest that roughly a one-third reduction in the current N fertilizer application level over these "overfertilization" regions would not significantly influence crop yield but decrease soil GHG emissions by 29.60%-32.50% and GHG emissions intensity by 0.13-0.25 kg CO 2-eq/ kg. This reduction is about 29% and 5% of total agricultural soil GHG emissions in China and the world, respectively. This study suggests that improving nitrogen use efficiency would be an effective strategy to mitigate GHG emissions and sustain China's food security.

A historical reconstruction of cropland in China from 1900 to 2016

“…5a), a more intensive reclamation resulted in a substantial net increase of cropland in that area. It is important to note that the other hot spot of recent cropland expansion is located in the Northeast China Plain, which is also documented in other studies (Xia et al, 2016;Zhang et al, 2018). The intensive cropland reclamation might have triggered a significant amount of carbon emissions, as the region is well known for its high carbon storage; our updated cropland maps are expected to be helpful for such an assessment.…”

“…Although a large degree of uncertainty remains in HYDE land use maps, they have been widely used by the global change modeling community (e.g., Van Oost et al, 2007;Tian et al, 2013;Wang et al, 2020). However, the HYDE cropland maps might cause significant bias if they are used in regional and local biogeochemical simulations.…”

“…Another approach is to use fractional coverage to describe cropland distribution in each grid cell, which is common for mid-and low-resolution gridded maps, such as the History Database of the Global Environment (HYDE v3.2) (Klein Goldewijk et al, 2017). HYDE has been widely applied in global and regional model simulations due to its unique advantage with respect to depicting cropland distribution with long-term (10 000 BCE to 2017 CE) and global coverages (e.g., Wang et al, 2020). Nonetheless, the relatively coarse resolution (5 arcmin) has restricted its applicability.…”

A historical reconstruction of cropland in China from 1900 to 2016

“…Although a large degree of uncertainty remains in HYDE land use maps, they have been widely used by the global change modeling community (e.g., Van Oost et al, 2007;Tian et al, 2013;Wang et al, 2020). However, the HYDE cropland maps might cause significant bias if they are used in regional and local biogeochemical simulations.…”

“…However, the HYDE cropland maps might cause significant bias if they are used in regional and local biogeochemical simulations. Based on the HYDE maps, 480 Wang et al (2020) and Zhang et al (2020) estimated N2O emissions globally and in China's croplands from 1961 and 1949, respectively. However, we expected that the N2O emission results might have been biased as fertilizer was applied in a smaller cropland area (e.g., 103.99 Mha in HYDE vs. 132.68 Mha in our data during 1960-1980.…”