Agricultural activities are a substantial contributor to global greenhouse gas (GHG) emissions, accounting for about 58% of the world's anthropogenic non‐carbon dioxide GHG emissions and 14% of all anthropogenic GHG emissions, and agriculture is often viewed as a potential source of relatively low‐cost emissions reductions. We estimate the costs of GHG mitigation for 36 world agricultural regions for the 2000–2020 period, taking into account net GHG reductions, yield effects, livestock productivity effects, commodity prices, labor requirements, and capital costs where appropriate. For croplands and rice cultivation, we use biophysical, process‐based models (DAYCENT and DNDC) to capture the net GHG and yield effects of baseline and mitigation scenarios for different world regions. For the livestock sector, we use information from the literature on key mitigation options and apply the mitigation options to emission baselines compiled by EPA.
Abstract. No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to large uncertainties, as the processes producing the emissions are complex and strongly non-linear. Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA, to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management and/or the representation of soil water dynamics. Model results were compared to observational data and outputs from field-scale DayCent simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer data base for comparison than non-continuous measurements at the experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions as well as the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to over-estimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water as well as the N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management as well as improvements in soil moisture highlight the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.
Climate smart agriculture has been emphasized for mitigating anthropogenic greenhouse gas (GHG) emissions, yet the mitigation potential of individual management practices remain largely unexplored in semi-arid cropping systems. This study evaluated the effects of different winter cover crop mixtures on CO2 and N2O emissions, net GHG balance (GHGnet), greenhouse gas intensity (GHGI), yield-scaled GHG emissions, and soil properties in irrigated forage corn (Zea mays L.) and sorghum (Sorghum bicolor L. Moench) rotations. Four cover crop treatments: (1) grasses, brassicas, and legumes mixture (GBL), (2) grasses and brassicas mixture (GB), (3) grasses and legumes mixture (GL), and (4) a no-cover crop (NCC) control, each replicated four times under corn and sorghum phase of the rotations, were tested in the semi-arid Southern Great Plains of USA. Results showed 5–10 times higher soil respiration with cover crop mixtures than NCC during the cover crop phase and no difference during the cash crop phase. The average N2O-N emission in NCC was 44% lower than GL and 77% lower than GBL in corn and sorghum rotations. Cash crop yield was 13–30% greater in cover crop treatments than NCC, but treatment effects were not observed for GHGnet, yield-scaled emissions, and GHGI. Integrating cover crops could be a climate smart strategy for forage production in irrigated semi-arid agroecosystems.
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