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Bennetzen, E. H., Smith, P., & Porter, J. R. (2016). Agricultural production and greenhouse gas emissions from world regions—The major trends over 40 years. Glob. Environ. Change, 37, 43–55.
Abstract: Since 1970, global agricultural production has more than doubled with agriculture and land-use change now responsible for similar to 1/4 of greenhouse gas emissions from human activities. Yet, while greenhouse gas (GHG) emissions per unit of agricultural product have been reduced at a global level, trends in world regions have been quantified less thoroughly. The KPI (Kaya-Porter Identity) is a novel framework for analysing trends in agricultural production and land-use change and related GHG emissions. We apply this to assess trends and differences in nine world regions over the period 1970-2007. We use a deconstructed analysis of emissions from the mix of multiple sources, and show how each is changing in terms of absolute emissions on a per area and per produced unit basis, and how the change of emissions from each source contributes to the change in total emissions over time. The doubling of global agricultural production has mainly been delivered by developing and transitional countries, and this has been mirrored by increased GHG emissions. The decoupling of emissions from production shows vast regional differences. Our estimates show that emissions per unit crop (as kg CO2-equivalents per Giga Joule crop product), in Oceania, have been reduced by 94% from 1093 to 69; in Central & South America by 57% from 849 to 362; in sub-Saharan Africa by 27% from 421 to 309, and in Europe by 56% from 86 to 38. Emissions per unit livestock (as kg CO2-eq. GJ(-1) livestock product) have reduced; in sub-Saharan Africa by 24% from 6001 to 4580; in Central & South America by 61% from 3742 to 1448; in Central & Eastern Asia by 82% from 3,205 to 591, and; in North America by 28% from 878 to 632. In general, intensive and industrialised systems show the lowest emissions per unit of agricultural production. (C) 2016 Elsevier Ltd. All rights reserved.
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Dietrich, J. P., Schmitz, C., Lotze-Campen, H., Popp, A., & Müller, C. (2014). Forecasting technological change in agriculture—An endogenous implementation in a global land use model. Technological Forecasting and Social Change, 81, 236–249.
Abstract: ► Endogenous technological change in an economic land use model ► Estimation of yield elasticity with respect to investments in technological change ► Projections of future agricultural productivity rates ► Validation with observed data and historic trends ► Trade-off between required technological change and forest protection objectives Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 0.29 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995–2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change.
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