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Kyle, P., Müller, C., Calvin, K., & Thomson, A. (2014). Meeting the radiative forcing targets of the representative concentration pathways in a world with agricultural climate impacts. Earth’s Future, 2, 83–98.
Abstract: This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the representative concentration pathways (RCPs). We build on the recently completed Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to the GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6W/m(2) in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.
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Bodirsky, B. L., & Müller, C. (2014). Robust relationship between yields and nitrogen inputs indicates three ways to reduce nitrogen pollution. Environ. Res. Lett., 9(11), 111005.
Abstract: Historic increases in agricultural production came at the expense of substantial environmental burden through nitrogen pollution. Lassaletta et al (2014 Environ. Res. Lett. 9 105011) examine the historic relationship of crop yields and nitrogen fertilizer inputs globally and find a simple and robust relationship of declining nitrogen use efficiency with increasing nitrogen inputs. This general relationship helps to understand the dilemma between increased agricultural production and nitrogen pollution and allows identifying pathways towards more sustainable agricultural production and necessary associated policies.
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Lehtonen, H. S., & Irz, X. (2013). Impacts of reducing red meat consumption on agricultural production in Finland. Agriculture and Food Science, 22(3), 356–370.
Abstract: This paper summarises the simulated effects on Finnish agrcultural production and trade of a 20% decrease in Finnish demand for red meat (beef, pork, lamb). According to our results, reduced red meat consumption would be offset by increased consumption of poultry meat, eggs, dairy products and fish, as well as small increases in consumption of fruits and vegetables, peas, nuts, cereal products and sweets. By including the derived demand changes in an agricultural sector model, we show that livestock production in Finland, incentivised by national production-linked payments for milk and bovine animals, would decrease by much less than 20% due to the complex nature of agricultural production and trade. Overall, assuming unchanged consumer preferences and agricultural policy, a 20% reduction in red meat consumption is not likely to lead to a substantial decrease in livestock production or changed land use, or greenhouse gas emissions, from Finnish agriculture.
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Bennetzen, E. H., Smith, P., Soussana, J. - F., & Porter, J. R. (2012). Identity-based estimation of greenhouse gas emissions from crop production: case study from Denmark. European Journal of Agronomy, 41, 66–72.
Abstract: In order to feed the world we need innovative thinking on how to increase agricultural production whilst also mitigating climate change. Agriculture and land-use change are responsible for approximately one-third of total anthropogenic greenhouse gas (GHG) emissions but hold potential for climate change mitigation but are only tangentially included in UNFCCC mitigation policies. To get a full estimate of GHG emissions from agricultural crop production both energy-based emissions and land-based emissions need to be accounted for. Furthermore, the major mitigation potential is likely to be indirect reduction of emissions i.e. reducing emissions per unit of agricultural product rather than the absolute emissions per se. Hence the system productivity must be included in the same analysis. This paper presents the Kaya-Porter identity, derived from the Maya identity, as a new way to calculate GHG emissions from agricultural crop production by deconstructing emissions into five elements; the GHG intensity of the energy used for production (kg CO2-eq./MJ), energy intensity of the production (MJ/kg dry matter), areal productivity (kg dry matter/ha), areal land-based GHG emissions (CO2-eq./ha) and area (ha). These separate elements in the identity can be targeted in emissions reduction and mitigation policies and are useful to analyse past and current trends in emissions and to explore future scenarios. Using the Kaya-Porter identity we have performed a case study on Danish crop production and find emissions to have been reduced by 12% from 1992 to 2008, whilst yields per unit area have remained constant. Both land-based emissions and energy-based emissions have decreased, mainly due to a 41% reduction in nitrogen fertilizer use. The initial identity based analysis for crop production presented here needs to be extended to include livestock to reflect the entire agricultural production and food demand sectors, thereby permitting analysis of the trade-offs between animal and plant food production, human dietary preferences and population and resulting GHG emissions. (C) 2012 Elsevier B.V. All rights reserved.
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