Carbon footprints of grain-, forage-, and energy-based cropping systems in the North China plain

Purpose Low carbon footprint agriculture has received increasing attention in the effect of reducing greenhouse gas emissions and mitigating climate change. However, little is known about how crop diversification may affect the system productivity and the carbon footprint. Methods In this study, we analyzed the carbon footprints of four cropping systems: winter wheat ( Triticum aestivum L.)–summer maize ( Zea mays L.) (WM, grain crop pattern, 1-year cycle); ryegrass ( Lolium perenne L.)–sweet sorghum ( Sorghum bicolor (L.) Moench) (RS, forage crop pattern, 1-year cycle); ryegrass–sweet sorghum → winter wheat–summer maize (RSWM, grain plus forage crop pattern, 2-year cycle); and switchgrass ( Panicum virgatum L.) perennial cropping (SG, energy crop pattern) that have been evaluated in a long-term (2009–2015) field experiment in the North China Plain (NCP). Carbon footprints were expressed using three metrics: CF a (per unit area), CF b (per kg of biomass), and CF e (per unit of economic output). Results and discussion The results showed that switchgrass as a perennial herbaceous crop with one cut per year had the lowest annual carbon footprint at three metrics. The WM cropping system had the highest annual CF a , CF b , and CF e values which were 1.73, 2.23, and 1.78 times higher, respectively, than those of the RSWM cropping system. The RS cropping system had the lower annual CF a , CF b , and CF e values, which accounted for 20.9, 3.4, and 2.9%, respectively, of the WM cropping system. The four cropping systems had annual carbon footprints at per unit area, per kilogram of biomass and per unit of economic output ranked from lowest to highest of SG < RS < RSWM < WM. Conclusions We conclude that appropriately designed, diversified cropping systems that include grain, forage, and bioenergy crops can effectively reduce the carbon footprint while maintaining or even increasing the systems productivity in the North China Plain.