Large-scale 2nd generation bioenergy deployment is a key element of 1.5 °C and 2 °C transformation pathways. However, large-scale bioenergy production might have negative sustainability implications ...and thus may conflict with the Sustainable Development Goal (SDG) agenda. Here, we carry out a multi-criteria sustainability assessment of large-scale bioenergy crop production throughout the 21st century (300 EJ in 2100) using a global land-use model. Our analysis indicates that large-scale bioenergy production without complementary measures results in negative effects on the following sustainability indicators: deforestation, CO2 emissions from land-use change, nitrogen losses, unsustainable water withdrawals and food prices. One of our main findings is that single-sector environmental protection measures next to large-scale bioenergy production are prone to involve trade-offs among these sustainability indicators-at least in the absence of more efficient land or water resource use. For instance, if bioenergy production is accompanied by forest protection, deforestation and associated emissions (SDGs 13 and 15) decline substantially whereas food prices (SDG 2) increase. However, our study also shows that this trade-off strongly depends on the development of future food demand. In contrast to environmental protection measures, we find that agricultural intensification lowers some side-effects of bioenergy production substantially (SDGs 13 and 15) without generating new trade-offs-at least among the sustainability indicators considered here. Moreover, our results indicate that a combination of forest and water protection schemes, improved fertilization efficiency, and agricultural intensification would reduce the side-effects of bioenergy production most comprehensively. However, although our study includes more sustainability indicators than previous studies on bioenergy side-effects, our study represents only a small subset of all indicators relevant for the SDG agenda. Based on this, we argue that the development of policies for regulating externalities of large-scale bioenergy production should rely on broad sustainability assessments to discover potential trade-offs with the SDG agenda before implementation.
► The study analyses the impact of increased trade on economic and environmental indicators. ► Global costs of food production decrease and the food scarcity index increases with a lower rate. ► ...Deforestation, mainly in Latin America, leads to significant amounts of additional carbon emissions. ► Non-CO2 emissions will increase most in China due to comparative advantages in livestock production. ► With the generated economic benefits it is possible to compensate for increased emissions and deforestation.
The volume of agricultural trade increased by more than ten times throughout the past six decades and is likely to continue with high rates in the future. Thereby, it largely affects environment and climate. We analyse future trade scenarios covering the period of 2005–2045 by evaluating economic and environmental effects using the global land-use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”). This is the first trade study using spatially explicit mapping of land use patterns and greenhouse gas emissions. We focus on three scenarios: the reference scenario fixes current trade patterns, the policy scenario follows a historically derived liberalisation pathway, and the liberalisation scenario assumes a path, which ends with full trade liberalisation in 2045.
Further trade liberalisation leads to lower global costs of food. Regions with comparative advantages like Latin America for cereals and oil crops and China for livestock products will export more. In contrast, regions like the Middle East, North Africa, and South Asia face the highest increases of imports. Deforestation, mainly in Latin America, leads to significant amounts of additional carbon emissions due to trade liberalisation. Non-CO2 emissions will mostly shift to China due to comparative advantages in livestock production and rising livestock demand in the region. Overall, further trade liberalisation leads to higher economic benefits at the expense of environment and climate, if no other regulations are put in place.
Ambitious climate targets, such as the 2 °C target, are likely to require the removal of carbon dioxide from the atmosphere. Afforestation is one such mitigation option but could, through the ...competition for land, also lead to food prices hikes. In addition, afforestation often decreases land-surface albedo and the amount of short-wave radiation reflected back to space, which results in a warming effect. In particular in the boreal zone, such biophysical warming effects following from afforestation are estimated to offset the cooling effect from carbon sequestration. We assessed the food price response of afforestation, and considered the albedo effect with scenarios in which afforestation was restricted to certain latitudinal zones. In our study, afforestation was incentivized by a globally uniform reward for carbon uptake in the terrestrial biosphere. This resulted in large-scale afforestation (2580 Mha globally) and substantial carbon sequestration (860 GtCO2) up to the end of the century. However, it was also associated with an increase in food prices of about 80% by 2050 and a more than fourfold increase by 2100. When afforestation was restricted to the tropics the food price response was substantially reduced, while still almost 60% cumulative carbon sequestration was achieved. In the medium term, the increase in prices was then lower than the increase in income underlying our scenario projections. Moreover, our results indicate that more liberalised trade in agricultural commodities could buffer the food price increases following from afforestation in tropical regions.
Systematic model inter-comparison helps to narrow discrepancies in the analysis of the future impact of climate change on agricultural production. This paper presents a set of alternative scenarios ...by five global climate and agro-economic models. Covering integrated assessment (IMAGE), partial equilibrium (CAPRI, GLOBIOM, MAgPIE) and computable general equilibrium (MAGNET) models ensures a good coverage of biophysical and economic agricultural features. These models are harmonized with respect to basic model drivers, to assess the range of potential impacts of climate change on the agricultural sector by 2050. Moreover, they quantify the economic consequences of stringent global emission mitigation efforts, such as non-CO2 emission taxes and land-based mitigation options, to stabilize global warming at 2 °C by the end of the century under different Shared Socioeconomic Pathways. A key contribution of the paper is a vis-à-vis comparison of climate change impacts relative to the impact of mitigation measures. In addition, our scenario design allows assessing the impact of the residual climate change on the mitigation challenge. From a global perspective, the impact of climate change on agricultural production by mid-century is negative but small. A larger negative effect on agricultural production, most pronounced for ruminant meat production, is observed when emission mitigation measures compliant with a 2 °C target are put in place. Our results indicate that a mitigation strategy that embeds residual climate change effects (RCP2.6) has a negative impact on global agricultural production relative to a no-mitigation strategy with stronger climate impacts (RCP6.0). However, this is partially due to the limited impact of the climate change scenarios by 2050. The magnitude of price changes is different amongst models due to methodological differences. Further research to achieve a better harmonization is needed, especially regarding endogenous food and feed demand, including substitution across individual commodities, and endogenous technological change.
The possibility of using bioenergy as a climate change mitigation measure has sparked a discussion of whether and how bioenergy production contributes to sustainable development. We undertook a ...systematic review of the scientific literature to illuminate this relationship and found a limited scientific basis for policymaking. Our results indicate that knowledge on the sustainable development impacts of bioenergy production is concentrated in a few well‐studied countries, focuses on environmental and economic impacts, and mostly relates to dedicated agricultural biomass plantations. The scope and methodological approaches in studies differ widely and only a small share of the studies sufficiently reports on context and/or baseline conditions, which makes it difficult to get a general understanding of the attribution of impacts. Nevertheless, we identified regional patterns of positive or negative impacts for all categories – environmental, economic, institutional, social and technological. In general, economic and technological impacts were more frequently reported as positive, while social and environmental impacts were more frequently reported as negative (with the exception of impacts on direct substitution of GHG emission from fossil fuel). More focused and transparent research is needed to validate these patterns and develop a strong science underpinning for establishing policies and governance agreements that prevent/mitigate negative and promote positive impacts from bioenergy production.
Transformation pathways for the land sector in line with the Paris Agreement depend on the assumption of globally implemented greenhouse gas (GHG) emission pricing, and in some cases also on ...inclusive socio-economic development and sustainable land-use practices. In such pathways, the majority of GHG emission reductions in the land system is expected to come from low- and middle-income countries, which currently account for a large share of emissions from agriculture, forestry and other land use (AFOLU). However, in low- and middle-income countries the economic, financial and institutional barriers for such transformative changes are high. Here, we show that if sustainable development in the land sector remained highly unequal and limited to high-income countries only, global AFOLU emissions would remain substantial throughout the 21st century. Our model-based projections highlight that overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. While also a scenario purely based on either global GHG emission pricing or on inclusive socio-economic development would achieve the stringent emissions reductions required, only the latter ensures major co-benefits for other Sustainable Development Goals, especially in low- and middle-income regions.
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.
► 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
Livestock farming is the world's largest land use sector and utilizes around 60% of the global biomass harvest. Over the coming decades, climate change will affect the natural resource base of ...livestock production, especially the productivity of rangeland and feed crops. Based on a comprehensive impact modeling chain, we assess implications of different climate projections for agricultural production costs and land use change and explore the effectiveness of livestock system transitions as an adaptation strategy. Simulated climate impacts on crop yields and rangeland productivity generate adaptation costs amounting to 3% of total agricultural production costs in 2045 (i.e. 145 billion US$). Shifts in livestock production towards mixed crop-livestock systems represent a resource- and cost-efficient adaptation option, reducing agricultural adaptation costs to 0.3% of total production costs and simultaneously abating deforestation by about 76 million ha globally. The relatively positive climate impacts on grass yields compared with crop yields favor grazing systems inter alia in South Asia and North America. Incomplete transitions in production systems already have a strong adaptive and cost reducing effect: a 50% shift to mixed systems lowers agricultural adaptation costs to 0.8%. General responses of production costs to system transitions are robust across different global climate and crop models as well as regarding assumptions on CO2 fertilization, but simulated values show a large variation. In the face of these uncertainties, public policy support for transforming livestock production systems provides an important lever to improve agricultural resource management and lower adaptation costs, possibly even contributing to emission reduction.
Abstract
The major social and economic impacts of international migration have led to a strong interest in better understanding the drivers of cross-border movement. Quantitative models have sought ...to explain global migration patterns in terms of economic, social, climatic, and other variables, and future projections of these variables are increasingly being used to forecast international migration flows. An important implicit assumption in the most widely used class of these approaches, so-called gravity models, is that their parameterisation based on panel data enables them to describe the effects of predictor variables on migration flows across both space and time, i.e., that they explain flow variation both across country pairs at a given time and across time for a given country pair. Here we show that this assumption does not hold. Whilst gravity models describe spatial patterns of international migration very well, they fail to capture even basic temporal dynamics, indeed, often worse than even the time-invariant average of the historical flows. We show that standard validation techniques have been unable to detect this important limitation of gravity models due to the different orders of magnitude of migration flows across spatial corridors, on the one hand, and over time, on the other hand. Our analysis suggests that gravity-model-based inferences about the effects that certain variables have had, or will have, on international migration over time may in reality represent statistical artefacts rather than true mechanisms. We argue that future predictions based on gravity models lack statistical support and that, in its current form, this class of models is not suited for informing policy makers about migration trajectories in the coming years and decades.
Abstract
In India, the production of rice and wheat account for more than 80% of its total agricultural water use. As farming is highly dependent on water availability, rapidly receding water levels ...require urgent measures to manage withdrawals. We assess policy instruments that can reduce pressures on water resources, while at the same time limiting adverse impacts on water-intensive cereal production systems, land-use changes and economic welfare. To this end, we use a dynamic and integrated partial equilibrium model of agricultural production and its impact on the environment to reflect two options: an increase in energy costs for irrigation water (price-related effects), and alternatively, physical quotas on water withdrawals (quantity-related effects). We conclude that it is possible to increase energy prices for agriculture with minimal impacts on agricultural production, agricultural prices, and trade in cereal crops, and moderately reduce water withdrawals by 2050. We find that the intermediate effects of pricing policies are negative for all indicators as compared to quota policies. However, by 2050, both policies yield similar outcomes for all indicators. Our results offer insights into ways in which these policies drive different mechanisms and trade-offs on important agro-economic indicators, and they offer the choice for water conservation policy decision-making based on other critical factors such as implementation costs.
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