| Literature DB >> 28704669 |
Zhiyuan Yao1, Dabin Zhang2, Pengwei Yao1, Na Zhao3, Na Liu1, Bingnian Zhai2, Suiqi Zhang4, Yangyang Li4, Donglin Huang2, Weidong Cao5, Yajun Gao6.
Abstract
Reducing the carbon footprint (CF) of crop production is an efficient way to mitigate climate change. Growing legume green manure (LGM) instead of summer fallow may achieve this goal by lowering synthetic nitrogen (N) fertilizer needs and replenishing the depleted soil carbon (C) pool. The Rothamsted Carbon (RothC) model was incorporated into the Life-Cycle Assessment (LCA) to evaluate the present and projected CFs of green manure-based wheat production systems in dryland agriculture on the Loess Plateau of China. The field study included four main treatments (Huai bean, soybean and mung bean grown as green manure in summer and fallow as control) and four synthetic N rates (0, 108, 135 and 162kgNha-1) applied at wheat sowing. Soybean as LGM increased averaged wheat yield over 4 synthetic N rates by 8% compared with fallow (P<0.05), and synthetic N requirement was reduced by 33% without compromising the wheat yield for all the main treatments. Although LGM treatments had higher greenhouse gas (GHG) emissions from agricultural inputs, the greater amount of C inputs elevated the corresponding SOC stocks (SOCS) by 14-24% after 8years, thus significantly reducing the CF by 25-51% compared with fallow. The modelled SOCS equilibrium indicates that the CF for cropping systems with LGM will be 53-62% lower than fallow and 23-37% lower compared with their current level. In conclusion, introducing legume green manure instead of summer fallow is a highly efficient measure for persistent CF reduction, and coupling the RothC model and LCA is an alternative method to predict the long-term impact of different cropping systems on GHG emissions.Entities:
Keywords: Carbon sequestration; GHG profile; Greenhouse gas emissions; Leguminous green manure; Process-oriented model; Wheat yield
Year: 2017 PMID: 28704669 DOI: 10.1016/j.scitotenv.2017.07.028
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963