Elke Stehfest

Bio: Elke Stehfest is an academic researcher from University of Kassel. The author has contributed to research in topics: DayCent & Greenhouse gas. The author has an hindex of 6, co-authored 7 publications receiving 1278 citations.

N2O and NO emission from agricultural fields and soils under natural vegetation: summarizing available measurement data and modeling of global annual emissions

Abstract: The number of published N2O and NO emissions measurements is increasing steadily, providing additional information about driving factors of these emissions and allowing an improvement of statistical N-emission models. We summarized information from 1008 N2O and 189 NO emission measurements for agricultural fields, and 207 N2O and 210 NO measurements for soils under natural vegetation. The factors that significantly influence agricultural N2O emissions were N application rate, crop type, fertilizer type, soil organic C content, soil pH and texture, and those for NO emissions include N application rate, soil N content and climate. Compared to an earlier analysis the 20% increase in the number of N2O measurements for agriculture did not yield more insight or reduced uncertainty, because the representation of environmental and management conditions in agro-ecosystems did not improve, while for NO emissions the additional measurements in agricultural systems did yield a considerable improvement. N2O emissions from soils under natural vegetation are significantly influenced by vegetation type, soil organic C content, soil pH, bulk density and drainage, while vegetation type and soil C content are major factors for NO emissions. Statistical models of these factors were used to calculate global annual emissions from fertilized cropland (3.3 Tg N2O-N and 1.4 Tg NO-N) and grassland (0.8 Tg N2O-N and 0.4 Tg NO-N). Global emissions were not calculated for soils under natural vegetation due to lack of data for many vegetation types.

The Protein Puzzle: The Consumption and Production of Meat, Dairy and Fish in the

Abstract: In het rapport 'The protein puzzle. The consumption and production of meat, dairy and fish in the European Union' brengen onderzoekers van het Planbureau voor de Leefomgeving (PBL) in kaart wat de gevolgen van de productie en consumptie van dierlijke eiwitten zijn voor milieu, natuur en gezondheid. Vervolgens schetst het PBL welke opties er in Europees verband zijn om de negatieve effecten te verminderen. Met deze studie verschaft het PBL relevante feiten en cijfers ten behoeve van het debat over eiwitconsumptie, inclusief een indicatie van de onzekerheden daarbij.

Global scale DAYCENT model analysis of greenhouse gas emissions and mitigation strategies for cropped soils

Abstract: Conversion of native vegetation to cropland and intensification of agriculture typically result in increased greenhouse gas (GHG) emissions (mainly N2O and CH4) and more NO3 leached below the root zone and into waterways Agricultural soils are often a source but can also be a sink of CO2 Regional and larger scale estimates of GHG emissions are usually obtained using IPCC emission factor methodology, which is associated with high uncertainty To more realistically represent GHG emissions we used the DAYCENT biogeochemical model for non-rice major crop types (corn, wheat, soybean) IPCC methodology estimates N losses from croplands based solely on N inputs In contrast, DAYCENT accounts for soil class, daily weather, historical vegetation cover, and land management practices such as crop type, fertilizer additions, and cultivation events Global datasets of weather, soils, native vegetation, and cropping fractions were mapped to a 19° × 19° resolution Non-spatial data (eg, rates and dates of fertilizer applications) were assumed to be identical within crop types across regions We compared model generated baseline GHG emissions and N losses for irrigated and rainfed cropping with land management alternatives intended to mitigate GHG emissions Reduced fertilizer resulted in lower N losses, but crop yields were reduced by a similar proportion Use of nitrification inhibitors and split fertilizer applications both led to increased (~ 6%) crop yields but the inhibitor led to a larger reduction in N losses (~ 10%) No-till cultivation, which led to C storage, combined with nitrification inhibitors, resulted in reduced GHG emissions of ~ 50% and increased crop yields of ~ 7%

Simulation of N2O emissions from a urine‐affected pasture in New Zealand with the ecosystem model DayCent

Abstract: [1] We used the trace gas model DayCent to simulate emissions of nitrous oxide (N 2 O) from a urine-affected pasture in New Zealand. The data set for this site contained year-round daily emissions of nitrification-N 2 O (N 2 O nit ) and denitrification-N 2 O (N 2 O den ), meteorological data, soil moisture, and at least weekly data on soil ammonium (NH 4 +) and nitrate (NO - 3) content. Evapotranspiration, soil temperature, and most of the soil moisture data were reasonably well represented. Observed and simulated soil NH4 concentrations agreed well, but DayCent underestimated the NO - 3 concentrations, due possibly to an insufficient nitrification rate. Modeled N 2 O emissions (18.4 kg N 2 O-N ha -1 yr -1 ) showed a similar pattern but exceeded observed emissions (4.4 kg N 2 O-N ha -1 yr -1 ) by more than 3 times. Modeled and observed N 2 O emissions were dominated by peaks following N-application and heavy rainfall events and were favored under high soil temperatures. The contribution of N 2 O den was simulated well except for a 4-week period when water-filled pore space was overestimated and caused high N 2 O emissions which accounted for one third of the simulated annual N 2 O emissions. N 2 O nit fluxes were overestimated with DayCent because they are calculated as a fixed proportion of NH 4 + converted to NO - 3, while the data suggest that significant rates of nitrification can occur without inducing significant N 2 O emissions. The comprehensive data set made it possible to explain discrepancies between modeled and observed values. In-depth model validations with detailed data sets are essential for a better understanding of the internal model behavior and for deriving possible model improvements.

A framework for the cross-sectoral integration of multi-model impact projections

Abstract: Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.

Reducing food’s environmental impacts through producers and consumers

Abstract: Food’s environmental impacts are created by millions of diverse producers. To identify solutions that are effective under this heterogeneity, we consolidated data covering five environmental indicators; 38,700 farms; and 1600 processors, packaging types, and retailers. Impact can vary 50-fold among producers of the same product, creating substantial mitigation opportunities. However, mitigation is complicated by trade-offs, multiple ways for producers to achieve low impacts, and interactions throughout the supply chain. Producers have limits on how far they can reduce impacts. Most strikingly, impacts of the lowest-impact animal products typically exceed those of vegetable substitutes, providing new evidence for the importance of dietary change. Cumulatively, our findings support an approach where producers monitor their own impacts, flexibly meet environmental targets by choosing from multiple practices, and communicate their impacts to consumers.

Sustainable biochar to mitigate global climate change

Abstract: Production of biochar (the carbon (C)-rich solid formed by pyrolysis of biomass) and its storage in soils have been suggested as a means of abating climate change by sequestering carbon, while simultaneously providing energy and increasing crop yields. Substantial uncertainties exist, however, regarding the impact, capacity and sustainability of biochar at the global level. In this paper we estimate the maximum sustainable technical potential of biochar to mitigate climate change. Annual net emissions of carbon dioxide (CO 2 ), methane and nitrous oxide could be reduced by a maximum of 1.8 Pg CO 2 -C equivalent (CO 2 -C e ) per year (12 % of current anthropogenic CO 2 -C e emissions; 1 Pg = 1 Gt), and total net emissions over the course of a century by 130 Pg CO 2 -C e , without endangering food security, habitat or soil conservation. Biochar has a larger climate-change mitigation potential than combustion of the same sustainably procured biomass for bioenergy, except when fertile soils are amended while coal is the fuel being offset.

N 2 O release from agro-biofuel production negates global warming reduction by replacing fossil fuels

Abstract: The relationship, on a global basis, between the amount of N fixed by chemical, biological or atmospheric processes entering the terrestrial biosphere, and the total emission of nitrous oxide (N2O), has been re-examined, us- ing known global atmospheric removal rates and concentra- tion growth of N2O as a proxy for overall emissions. For both the pre-industrial period and in recent times, after taking into account the large-scale changes in synthetic N fertiliser pro- duction, we find an overall conversion factor of 3-5% from newly fixed N to N 2O-N. We assume the same factor to be valid for biofuel production systems. It is covered only in part by the default conversion factor for "direct" emissions from agricultural crop lands (1%) estimated by IPCC (2006), and the default factors for the "indirect" emissions (follow- ing volatilization/deposition and leaching/runoff of N: 0.35- 0.45%) cited therein. However, as we show in the paper, when additional emissions included in the IPCC methodol- ogy, e.g. those from livestock production, are included, the total may not be inconsistent with that given by our "top- down" method. When the extra N2O emission from biofuel production is calculated in "CO2-equivalent" global warm- ing terms, and compared with the quasi-cooling effect of "saving" emissions of fossil fuel derived CO2, the outcome is that the production of commonly used biofuels, such as biodiesel from rapeseed and bioethanol from corn (maize), depending on N fertilizer uptake efficiency by the plants, can contribute as much or more to global warming by N2O emis- sions than cooling by fossil fuel savings. Crops with less N demand, such as grasses and woody coppice species, have more favourable climate impacts. This analysis only consid- ers the conversion of biomass to biofuel. It does not take into account the use of fossil fuel on the farms and for fertil- izer and pesticide production, but it also neglects the produc- tion of useful co-products. Both factors partially compensate each other. This needs to be analyzed in a full life cycle as- sessment.