Carbon Consequences and Agricultural Implications of Growing Biofuel Crops on Marginal Agricultural Lands in China

Abstract

Using marginal agricultural lands to grow energy crops for biofuel feedstocks is a promising option to meet the biofuel needs in populous China without causing further food shortages or environmental problems. Here we quantify the effects of growing switchgrass and Miscanthus on Chinese marginal agricultural lands on biomass production and carbon emissions with a global-scale biogeochemical model. We find that the national net primary production (NPP) of these two biofuel crops are 622 and 1546 g C m(-2) yr(-1), respectively, whereas the NPP of food crops is about 600 g C m(-2) yr(-1) in China. The net carbon sink over the 47 Mha of marginal agricultural lands across China is 2.1 Tg C yr(-1) for switchgrass and 5.0 Tg C yr(-1) for Miscanthus. Soil organic carbon is estimated to be 10 kg C m(-2) in both biofuel ecosystems, which is equal to the soil carbon levels of grasslands in China. In order to reach the goal of 12.5 billion liters of bioethanol in 2020 using crop biomass as biofuel feedstocks, 7.9-8.0 Mha corn grain, 4.3-6.1 Mha switchgrass, or 1.4-2.0 Mha Miscanthus will be needed. Miscanthus has tremendous potential to meet future biofuel needs, and to benefit CO(2) mitigation in China.

Sustainability Indicators of Biomass Production in Agroforestry Systems

“…HFC's and PFC's do not need to be accounted for within the farm gate as they are generally derived from industrial sources and cooling systems. CO 2 and N 2 O have been suggested as the main components to be monitored [19] given that the flux of both compounds is strongly correlated to management practices [20][21][22]. N 2 O may be produced directly through the processes of denitrification and nitrification or indirectly by conversion of deposited NO x and NH 3 as well as through combustion.…”

Biofuels, cropland expansion, and the extensive margin

“…The model has been extensively used to evaluate C dynamics [13][14][15][23][24][25][26]. Its structure, algorithm, parameterization, calibration, and performance have been documented [13,26,27].…”

“…This paper fills a gap in this area and provides a data set which estimates land productivity at 0.5°× 0.5°(longitude × latitude) grid-cell level. To generate this data set, a process-based biogeochemistry model, the terrestrial ecosystem model (TEM) [13][14][15] along with spatially referenced information on climate, elevation, soils, and vegetation land use data are used. This data set can be used in connection with economic partial equilibrium and computable general equilibrium models which are used to assess land use changes induced by economic factors.…”

CARBON SEQUESTRATION AND PRODUCTION OF Eucalyptus camaldulensis PLANTATIONS ON MARGINAL SANDY AGRICULTURAL LANDS

“…Many previous studies have analyzed the beneficial effects of afforestation of marginal agricultural lands in terms of socio-economic uplift and increment in soil fertility (Djanibekov et al, 2013;Djanibekov and Khamzina, 2014;Nawaz et al, 2013). However, there are few studies that have assessed the carbon sequestration status and potential of marginal lands (Parks and Hardie, 1995;Markewitz et al, 2002;Niu and Duiker, 2006;Qin et al, 2011). Keeping in view the forest status in Pakistan (only 2.2% forest cover) and sustainability in wood supply, there is urgent need of tree planting on agricultural lands (Khan et al, 2007;Nawaz et al, 2014).…”