Assessing the potential for greenhouse gas mitigation in intensively managed annual cropping systems at the regional scale

We predicted changes in yields and direct net soil greenhouse gas (GHG) fluxes from converting conventional to alternative management practices across one of the world's most productive agricultural regions, the Central Valley of California, using the DAYCENT model. Alternative practices included conservation tillage, winter cover cropping, manure application, a 25% reduction in N fertilizer input and combinations of these. Alternative practices were evaluated for all unique combinations of crop rotation, climate, and soil types for the period 1997-2006. The crops included were alfalfa, corn, cotton, melon, safflower, sunflower, tomato, and wheat. Our predictions indicate that, adopting alternative management practices would decrease yields up to 5%. Changes in modeled SOC and net soil GHG fluxes corresponded to values reported in the literature. Average potential reductions of net soil GHG fluxes with alternative practices ranged from −0.7 to −3.3 Mg CO₂-eq ha⁻¹ yr⁻¹ in the Sacramento Valley and −0.5 to −2.5 Mg CO₂-eq ha⁻¹ yr⁻¹ for the San Joaquin Valley. While adopting a single alternative practice led to modest net soil GHG flux reductions (on average −1 Mg CO₂-eq ha⁻¹ yr⁻¹), combining two or more of these practices led to greater decreases in net soil GHG fluxes of up to −3 Mg CO₂-eq ha⁻¹ yr⁻¹. At the regional scale, the combination of winter cover cropping with manure application was particularly efficient in reducing GHG emissions. However, GHG mitigation potentials were mostly non-permanent because 60-80% of the decreases in net soil GHG fluxes were attributed to increases in SOC, except for the reduced fertilizer input practice, where reductions were mainly attributed to decreased N₂O emissions. In conclusion, there are long-term GHG mitigation potentials within agriculture, but spatial and temporal aggregation will be necessary to reduce uncertainties around GHG emission reductions and the delivery risk of the associated C credits.     

Tillage and field scale controls on greenhouse gas emissions

There is a lack of understanding of how associations among soil properties and management-induced changes control the variability of greenhouse gas (GHG) emissions from soil. We performed a laboratory investigation to quantify relationships between GHG emissions and soil indicators in an irrigated agricultural field under standard tillage (ST) and a field recently converted (2 yr) to no-tillage (NT). Soil cores (15-cm depth) were incubated at 25 degrees C at field moisture content and 75% water holding capacity. Principal component analysis (PCA) identified that most of the variation of the measured soil properties was related to differences in soil C and N and soil water conditions under ST, but soil texture and bulk density under NT. This trend became more apparent after irrigation. However, principal component regression (PCR) suggested that soil physical properties or total C and N were less important in controlling GHG emissions across tillage systems. The CO2 flux was more strongly determined by microbial biomass under ST and inorganic N content under NT than soil physical properties. Similarly, N2O and CH4 fluxes were predominantly controlled by NO3- content and labile C and N availability in both ST and NT soils at field moisture content, and NH4+ content after irrigation. Our study indicates that the field-scale variability of GHG emissions is controlled primarily by biochemical parameters rather than physical parameters. Differences in the availability and type of C and N sources for microbial activity as affected by tillage and irrigation develop different levels and combinations of field-scale controls on GHG emissions.     

Managing the nitrogen cycle to reduce greenhouse gas emissions from crop production and biofuel expansion

Public policies are promoting biofuels as an alternative to fossil fuel consumption in order to mitigate greenhouse gas (GHG) emissions. However, the mitigation benefit can be at least partially compromised by emissions occurring during feedstock production. One of the key sources of GHG emissions from biofuel feedstock production, as well as conventional crops, is soil nitrous oxide (N₂O), which is largely driven by nitrogen (N) management. Our objective was to determine how much GHG emissions could be reduced by encouraging alternative N management practices through application of nitrification inhibitors and a cap on N fertilization. We used the US Renewable Fuel Standards (RFS2) as the basis for a case study to evaluate technical and economic drivers influencing the N management mitigation strategies. We estimated soil N₂O emissions using the DayCent ecosystem model and applied the US Forest and Agricultural Sector Optimization Model with Greenhouse Gases (FASOMGHG) to project GHG emissions for the agricultural sector, as influenced by biofuel scenarios and N management options. Relative to the current RSF2 policy with no N management interventions, results show decreases in N₂O emissions ranging from 3 to 4 % for the agricultural sector (5.5–6.5 million metric tonnes CO₂?eq.?year^?1; 1 million metric tonnes is equivalent to a Teragram) in response to a cap that reduces N fertilizer application and even larger reductions with application of nitrification inhibitors, ranging from 9 to 10 % (15.5–16.6 million tonnes CO₂?eq.?year^?1). The results demonstrate that climate and energy policies promoting biofuel production could consider options to manage the N cycle with alternative fertilization practices for the agricultural sector and likely enhance the mitigation of GHG emissions associated with biofuels.     

Crediting uncertain ecosystem services in a market

The margin of safety (MOS) approach is an increasingly prevalent tool for ensuring the integrity of market-based programs for providing ecosystem services. Over-crediting is reduced by setting aside mean estimates of uncertain services in favor of a more conservative estimate. Like many environmental policy problems, ecosystem service markets involve the aggregation of uncertainty over multiple scales, e.g. from landowners to market intermediaries to the overall market. We examine how the MOS instrument affects, and is affected by, an ecosystem services market. We show that the common bottom-up approach of imposing risk preferences at a local, disaggregated level—held over from earlier development in the context of toxics and command and control-style health risk regulation—leads to several unintended consequences. Furthermore, discounting landowner services can actually increase their profits, conditional on the elasticity of credit demand. We illustrate theoretical insights with an empirical application to greenhouse gas offset crediting in agriculture.     

A constrained least-squares approach to combine bottom-up and top-down CO2 flux estimates

Terrestrial CO₂ flux estimates are obtained from two fundamentally different methods generally termed bottom-up and top-down approaches. Inventory methods are one type of bottom-up approach which uses various sources of information such as crop production surveys and forest monitoring data to estimate the annual CO₂ flux at locations covering a study region. Top-down approaches are various types of atmospheric inversion methods which use CO₂ concentration measurements from monitoring towers and atmospheric transport models to estimate CO₂ flux over a study region. Both methods can also quantify the uncertainty associated with their estimates. Historically, these two approaches have produced estimates that differ considerably. The goal of this work is to construct a statistical model which sensibly combines estimates from the two approaches to produce a new estimate of CO₂ flux for our study region. The two approaches have complementary strengths and weaknesses, and our results show that certain aspects of the uncertainty associated with each of the approaches are greatly reduced by combining the methods. Our model is purposefully simple and designed to take the two approaches’ estimates and measures of uncertainty at ‘face value’. Specifically, we use a constrained least-squares approach to appropriately weigh the estimates by the inverse of their variance, and the constraint imposes agreement between the two sources. Our application involves nearly 18,000 flux estimates for the upper midwest United States. The constrained dependencies result in a non-sparse covariance matrix, but computation requires only minutes due to the structure of the model.     

Framework for improved confidence in modeled nitrous oxide estimates for biofuel regulatory standards

Biofuels vary greatly in their carbon intensity, depending on the specifics of how they are produced. Policy frameworks are needed to ensure that biofuels actually achieve intended reductions in greenhouse gas emissions. Current approaches do not account for important variables during cultivation that influence emissions. Estimating emissions based on biogeochemical models would allow accounting of farm-specific conditions, which in turn provides an incentive for producers to adopt low emissions practices. However, there are substantial uncertainties in the application of biogeochemical models. This paper proposes a policy framework that manages this uncertainty while retaining the ability of the models to account for (and hence incentivize) low emissions practices. The proposed framework is demonstrated on nitrous oxide (N₂O) emissions from the cultivation of winter barley. The framework aggregates uncertainties over time, which (1) avoids penalizing producers for uncertainty in weather, (2) allows for a high degree of confidence in the emissions reductions achieved, and (3) attenuates the uncertainty penalties borne by producers within a timescale of several years. Results indicate that with effective management, N₂O emissions from feedstock cultivation may be <?5% of the carbon intensity of gasoline, whereas the existing policy approach estimates emissions >?20% of the carbon intensity of gasoline. If these emissions reductions are monetized, the framework can provide up to $0.002 per liter credits (0.8 cents per gallon) to fuel producers, which could incentivize emissions mitigation practices by biofuel feedstock suppliers, such as avoiding fall N application on silty clay loam soils. The conservatism in the current approach fails to incentivize the adoption of biofuels, while the lack of specificity fails to incentivize site-level mitigation practices. Improved uncertainty accounting and consideration of farm-level practices will incentivize mitigation efforts at landscape to global scales.     

Inerted vessels: Avoiding hazards caused by gas buoyancy

Performing hot work on a process vessel that previously contained a flammable hydrocarbon liquid poses a significant explosion and fire hazard. To reduce the combustion hazard potential, the facility operator may choose to purge and blanket the vessel with an inert gas such as nitrogen or carbon dioxide. Numerous accidents have occurred during hot work due to inadequate inerting operations. Oftentimes the source of the problem was inadequate gas composition control caused by gas buoyancy.A useful paradigm for analyzing the inerting process is the well-stirred control volume with a spatially uniform chemical composition (i.e., perfect mixing). Certain features of the vessel construction, in concert with the physical properties of the inert gas, can interfere with the complete mixing of the inert gas with the vessel atmosphere. This paper discusses how to evaluate the potential for buoyant flows to disrupt and interfere with the design goal of perfect mixing. Three case studies of accident investigations are used to illustrate the potentially detrimental effects of buoyancy on inerting operations. Finally, recommendations are presented on how to use buoyancy to improve the effectiveness of inerting operations.