• Energy Research

Abstract Synthetic nitrogen (N) fertilization has helped boost agricultural yields, but it is also responsible for direct and indirect greenhouse gas (GHG) emissions. Fertilizer-related emissions are also promoted by irrigation and manure application, which has increased with livestock industrialization. Spanish agriculture provides a paradigmatic example of high industrialization under two different climates (temperate and Mediterranean) and two contrasting water management regimes (rainfed and irrigated). In this study, we estimated the historical evolution of the C footprint of N fertilization (including all the life cycle GHG emissions related to N fertilization) in Spanish agriculture from 1860 to 2018 at the province level (50 provinces) for 122 crops, using climate-specific N2O emission factors (EFs) adjusted to the type of water management and the N source (synthetic fertilizer, animal manure, crop residues and soil N mineralization) and considering changes in the industrial efficiency of N fertilizer production. Overall, N-related GHG emissions increased ∼12-fold, up to 10–14 Tg CO2e yr−1 in the 2010s, with much higher growth in Mediterranean than in temperate areas. Direct N2O EFs of N fertilizers doubled due to the expansion of irrigation, synthetic fertilizers and liquid manure, associated with livestock industrialization. Synthetic N production dominated the emissions balance (55%–60% of GHGe in the 21st century). Large energy efficiency gains of industrial fertilizer production were largely offset by the changes in the fertilizer mix. Downstream N2O emissions associated with NH3 volatilization and NO3 − leaching increased tenfold. The yield-scaled carbon footprint of N use in Spanish agriculture increased fourfold, from 4 and 5 Mg CO2e Mg N−1 to 16–18 Mg CO2e Mg N−1. Therefore, the results reported herein indicate that increased productivity could not offset the growth in manufacture and soil emissions related to N use, suggesting that mitigation efforts should not only aim to increase N use efficiency but also consider water management, fertilizer type and fertilizer manufacture as key drivers of emissions.

The frequency and intensity of extreme weather is increasing concomitant with changes in the global climate change. Although wheat is the most important food crop in Europe, there is currently no comprehensive empirical information available regarding the sensitivity of European wheat to extreme weather. In this study, we assessed the sensitivity of European wheat yields to extreme weather related to phenology (sowing, heading) in cultivar trials across Europe (latitudes 37.21 degrees to 61.34 degrees and longitudes- 6.02 degrees to 26.24 degrees) during the period 1991-2014. All the observed agro-climatic extremes (>= 31 degrees C, >= 35 degrees C, or drought around heading; >= 35 degrees C from heading to maturity; excessive rainfall; heavy rainfall and low global radiation) led to marked yield penalties in a selected set of European cultivars, whereas few cultivars were found to with no yield penalty in such conditions. There were no European wheat cultivars that responded positively (+ 10%) to drought after sowing, or frost during winter (- 15 degrees C and - 20 degrees C). Positive responses to extremes were often shown by cultivars associated with specific regions, such as good performance under high temperatures by southern-origin cultivars. Consequently, a major future breeding challenge will be to evaluate the potential of combining such cultivar properties with other properties required under different growing conditions with, for example, long day conditions at higher latitudes, when the intensity and frequency of extremes rapidly increase.

Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.

AbstractUnderstanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.