MODELING BIOENERGY, LAND USE, AND GHG EMISSIONS WITH FASOMGHG: MODEL OVERVIEW AND ANALYSIS OF STORAGE COST IMPLICATIONS

Biofuels production has increased rapidly in recent years due to higher petroleum prices as well as heightened concerns regarding climate change and energy security. However, because commercially viable biofuels are currently produced primarily from agricultural feedstocks, higher production volumes increase pressure on land resources. Thus, large-scale biofuels production has important implications for the forest and agriculture sectors, land use, trade, and net greenhouse gas (GHG) emissions. Competition for land is expected to continue growing in the future as mandated biofuels volumes increase along with rising demand for food, feed, and fiber, both domestically and internationally. In response to heightened concern regarding impacts such as indirect land-use change and higher food prices, the U.S. policy is focusing on second-generation (cellulosic) feedstocks to contribute the majority of the mandated increase in biofuels volume through 2022. However, there has been little work exploring the logistics of supplying these feedstocks or examining feedstock mix and net GHG effects of combining renewable fuels mandates with climate policy. In this paper, we apply the recently updated Forest and Agricultural Sector Optimization Model with GHGs (FASOMGHG) to explore the implications of alternative assumptions regarding feedstock storage costs and carbon price for renewable energy production mix, land use, and net GHG emissions. The model is used to quantify the magnitude and regional distribution of changes in the optimal mix of bioenergy feedstocks when accounting for storage costs. In addition, we find that combining the biofuels volume mandate with a carbon price policy has additional implications for feedstock mix and provides a substantially larger net reduction in GHG than a renewable fuels mandate alone.

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LAND-USE AND GREENHOUSE GAS IMPLICATIONS OF BIOFUELS: ROLE OF TECHNOLOGY AND POLICY

Climate Change Economics ◽

10.1142/s2010007812500133 ◽

2012 ◽

Vol 03 (03) ◽

pp. 1250013 ◽

Cited By ~ 23

Author(s):

XIAOGUANG CHEN ◽

HAIXIAO HUANG ◽

MADHU KHANNA

Keyword(s):

Land Use ◽

Ghg Emissions ◽

Carbon Price ◽

Price Policy ◽

Biofuel Production ◽

Tax Credit ◽

Cellulosic Biofuels ◽

Cellulosic Biofuel ◽

The U.S ◽

Ghg Savings

This paper examines the changes in land use in the U.S. likely to be induced by biofuel and climate policies and the implications of these policies for greenhouse gas (GHG) emissions over the 2007–2022 period. The policies considered here include a modified Renewable Fuel Standard (RFS) by itself as well as combined with a cellulosic biofuel tax credit or a carbon price policy. We use a dynamic, spatial, multi-market equilibrium model, Biofuel and Environmental Policy Analysis Model (BEPAM), to endogenously determine the effects of these policies on cropland allocation, food and fuel prices, and the mix of first- and second-generation biofuels. We find that the RFS could be met by diverting 6% of cropland for biofuel production and would result in corn prices increasing by 16% in 2002 relative to the business-as-usual baseline. The reduction in GHG emissions in the U.S. due to the RFS is about 2%; these domestic GHG savings can be severely eroded by emissions due to indirect land-use changes and the increase in gasoline consumption in the rest of the world. Supplementing the RFS with a carbon price policy or a cellulosic biofuel tax credit induces a switch away from corn ethanol to cellulosic biofuels and achieves the mandated level of biofuel production with a smaller adverse impact on crop prices. These supplementary policies enhance the GHG savings achieved by the RFS alone, although through different mechanisms; greater production of cellulosic biofuels with the tax credit but larger reduction in fossil fuel consumption with a carbon tax.

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Economic and Environmental Consequences of the ECJ Genome Editing Judgment in Agriculture

Agronomy ◽

10.3390/agronomy11061212 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1212

Author(s):

Alexander Gocht ◽

Nicola Consmüller ◽

Ferike Thom ◽

Harald Grethe

Keyword(s):

Genome Editing ◽

Agricultural Sector ◽

Ghg Emissions ◽

Food Products ◽

Food Prices ◽

Farm Income ◽

The European Union ◽

Environmental Consequences ◽

European Court ◽

The Eu

Genome-edited crops are on the verge of being placed on the market and their agricultural and food products will thus be internationally traded soon. National regulations, however, diverge regarding the classification of genome-edited crops. Major countries such as the US and Brazil do not specifically regulate genome-edited crops, while in the European Union, they fall under GMO legislation, according to the European Court of Justice (ECJ). As it is in some cases impossible to analytically distinguish between products from genome-edited plants and those from non-genome-edited plants, EU importers may fear the risk of violating EU legislation. They may choose not to import any agricultural and food products based on crops for which genome-edited varieties are available. Therefore, crop products of which the EU is currently a net importer would become more expensive in the EU, and production would intensify. Furthermore, an intense substitution of products covered and not covered by genome editing would occur in consumption, production, and trade. We analyzed the effects of such a cease of EU imports for cereals and soy in the EU agricultural sector with the comparative static agricultural sector equilibrium model CAPRI. Our results indicate dramatic effects on agricultural and food prices as well as on farm income. The intensification of EU agriculture may result in negative net environmental effects in the EU as well as in an increase in global greenhouse gas (GHG) emissions. This suggests that trade effects should be considered when developing domestic regulation for genome-edited crops.

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Greenhouse Gas Emissions in Norwegian Agriculture: The Regional and Structural Dimension

Sustainability ◽

10.3390/su12062506 ◽

2020 ◽

Vol 12 (6) ◽

pp. 2506

Author(s):

Klaus Mittenzwei

Keyword(s):

Greenhouse Gas ◽

Crop Production ◽

Agricultural Sector ◽

Regional Distribution ◽

Ghg Emissions ◽

Animal Production ◽

Small Scale ◽

Agricultural Activity ◽

Resource Base ◽

Farm Structure

This paper studies the hypothesis that farm structure and the regional distribution of agricultural activity themselves have a significant impact on greenhouse gas (GHG) emissions from agriculture. Applying a dynamic model for the Norwegian agricultural sector covering the entire farm population, the model results support the hypothesis. Even without mitigation options, GHG emissions decline by 1.4 per cent if agriculture becomes regionally concentrated and increase by 1.5 per cent if a policy that favors a small-scale farm structure is put in place. Adding a carbon tax to a policy that leads to regional concentration, may help to reconcile competing policy objectives. A switch from animal production to crop production, and an extensification of animal production keeps a large resource base across the country while cutting GHG emissions.

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Biofuels and land-use changes: searching for the top model

Interface Focus ◽

10.1098/rsfs.2010.0043 ◽

2011 ◽

Vol 1 (2) ◽

pp. 224-232 ◽

Cited By ~ 41

Author(s):

Andre M. Nassar ◽

Leila Harfuch ◽

Luciane C. Bachion ◽

Marcelo R. Moreira

Keyword(s):

Land Use ◽

Land Use Change ◽

Policy Making ◽

Agricultural Sector ◽

Land Use Changes ◽

Ghg Emissions ◽

Biofuel Production ◽

Policy Makers ◽

Green House Gas ◽

Biofuel Policies

The use of agricultural-based biofuels has expanded. Discussions on how to assess green house gas (GHG) emissions from biofuel policies, specifically on (non-observed) land-use change (LUC) effects involve two main topics: (i) the limitations on the existing methodologies, and (ii) how to isolate the effects of biofuels. This paper discusses the main methodologies currently used by policy-makers to take decisions on how to quantify LUCs owing to biofuel production expansion. It is our opinion that the concerns regarding GHG emissions associated with LUCs should focus on the agricultural sector as a whole rather than concentrating on biofuel production. Actually, there are several limitations of economic models and deterministic methodologies for simulating and explaining LUCs resulting from the expansion of the agricultural sector. However, it is equally true that there are avenues of possibilities to improve models and make them more accurate and precise in order to be used for policy-making. Models available need several improvements to reach perfection. Any top model requires a concentration of interdisciplinary designers in order to replicate empirical evidence and capture correctly the agricultural sector dynamics for different countries and regions. Forgetting those limitations means that models will be used for the wrong purposes.

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Beneficial land-use change in Europe: deployment scenarios for multifunctional riparian buffers and windbreaks

10.21203/rs.3.rs-128604/v1 ◽

2021 ◽

Author(s):

Oskar Englund ◽

Pål Börjesson ◽

Blas Mola-Yudego ◽

Göran Berndes ◽

Ioannis Dimitriou ◽

...

Keyword(s):

Land Use ◽

Biomass Production ◽

Large Scale ◽

Production Systems ◽

Ghg Emissions ◽

Riparian Buffers ◽

Environmental Benefits ◽

Land Use Impacts ◽

Eu Member States ◽

The Eu

Abstract The land sector needs to increase biomass production to meet multiple demands while reducing negative land use impacts and transitioning from being a source to being a sink of carbon. The new Common Agricultural Policy of the EU (CAP) steers towards a more needs-based, targeted approach to addressing multiple environmental and climatic objectives, in coherence with other EU policies. In relation to this, new schemes are developed to offer farmers direct payments to adapt practices beneficial for climate, water, soil, air and biodiversity. Multifunctional biomass production systems have potential to reduce environmental impacts from agriculture while maintaining or increasing biomass production for the bioeconomy across Europe. Here, we present the first attempt to model the deployment of two such systems, riparian buffers and windbreaks, across >81.000 landscapes in Europe (EU27 + UK), aiming to quantify the resulting ecosystem services and environmental benefits, considering three deployment scenarios with different incentives for implementation. We found that these multifunctional biomass production systems can reduce N emissions to water and soil loss by wind erosion, respectively, down to a “low” impact level all over Europe, while simultaneously providing substantial environmental co-benefits, using less than 1% of the area under annual crops in the EU. The GHG emissions savings of utilizing the biomass produced in these systems for replacing fossil alternatives, combined with the increases in soil organic carbon, correspond to 1-1,4% of total GHG emissions in EU28. The introduction of “eco-schemes” in the new CAP may resolve some of the main barriers to implementation of large-scale multifunctional biomass production systems. Increasing the knowledge of these opportunities among all EU member states, before designing and introducing country-specific Eco-scheme options in the new CAP, is critical.

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Food security under high bioenergy demand toward long-term climate goals

Climatic Change ◽

10.1007/s10584-020-02838-8 ◽

2020 ◽

Vol 163 (3) ◽

pp. 1587-1601 ◽

Cited By ~ 1

Author(s):

Tomoko Hasegawa ◽

Ronald D. Sands ◽

Thierry Brunelle ◽

Yiyun Cui ◽

Stefan Frank ◽

...

Keyword(s):

At Risk ◽

Food Security ◽

Food Production ◽

Large Scale ◽

Agricultural Land ◽

Carbon Price ◽

Food Prices ◽

Greenhouse Gas Mitigation ◽

Bioenergy Feedstock ◽

Model Framework

AbstractBioenergy is expected to play an important role in the achievement of stringent climate-change mitigation targets requiring the application of negative emissions technology. Using a multi-model framework, we assess the effects of high bioenergy demand on global food production, food security, and competition for agricultural land. Various scenarios simulate global bioenergy demands of 100, 200, 300, and 400 exajoules (EJ) by 2100, with and without a carbon price. Six global energy-economy-agriculture models contribute to this study, with different methodologies and technologies used for bioenergy supply and greenhouse-gas mitigation options for agriculture. We find that the large-scale use of bioenergy, if not implemented properly, would raise food prices and increase the number of people at risk of hunger in many areas of the world. For example, an increase in global bioenergy demand from 200 to 300 EJ causes a − 11% to + 40% change in food crop prices and decreases food consumption from − 45 to − 2 kcal person−1 day−1, leading to an additional 0 to 25 million people at risk of hunger compared with the case of no bioenergy demand (90th percentile range across models). This risk does not rule out the intensive use of bioenergy but shows the importance of its careful implementation, potentially including regulations that protect cropland for food production or for the use of bioenergy feedstock on land that is not competitive with food production.

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Direct and indirect land-use change caused by large-scale land acquisitions in Cambodia

Environmental Research Letters ◽

10.1088/1748-9326/ab6397 ◽

2020 ◽

Vol 15 (2) ◽

pp. 024010 ◽

Cited By ~ 3

Author(s):

Nicholas R Magliocca ◽

Quy Van Khuc ◽

Ariane de Bremond ◽

Evan A Ellicott

Keyword(s):

Land Use ◽

Land Use Change ◽

Large Scale ◽

Indirect Land Use Change ◽

Land Acquisitions ◽

Large Scale Land

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GHG emissions and other environmental impacts of indirect land use change mitigation

GCB Bioenergy ◽

10.1111/gcbb.12394 ◽

2016 ◽

Vol 9 (4) ◽

pp. 725-742 ◽

Cited By ~ 12

Author(s):

Sarah J. Gerssen-Gondelach ◽

Birka Wicke ◽

Andre P. C. Faaij

Keyword(s):

Land Use ◽

Land Use Change ◽

Environmental Impacts ◽

Ghg Emissions ◽

Indirect Land Use Change ◽

Change Mitigation

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GHG Balance of Agricultural Intensification & Bioenergy Production in the Orinoquia Region, Colombia

Land ◽

10.3390/land10030289 ◽

2021 ◽

Vol 10 (3) ◽

pp. 289

Author(s):

Nidia Elizabeth Ramírez-Contreras ◽

David Munar-Florez ◽

Floor van der Hilst ◽

Juan Carlos Espinosa ◽

Álvaro Ocampo-Duran ◽

...

Keyword(s):

Land Use ◽

Biomass Production ◽

Fossil Fuels ◽

Agricultural Sector ◽

Agricultural Land ◽

Agricultural Productivity ◽

Ghg Emissions ◽

Energy Crop ◽

Agricultural Yields ◽

High Scenario

Energy crop expansion can increase land demand and generate displacement of food crops, which impacts greenhouse gas (GHG) emissions mainly through land-use change (LUC). Increased agricultural productivity could compensate for this. Our study aims to evaluate the regional combined GHG emissions of increasing agricultural yields for food crop and beef production and using the generated surplus land for biomass production to replace fossil fuels in the Orinoquia region of Colombia until 2030. The results show that surplus land for biomass production is obtained only when strong measures are applied to increase agricultural productivity. In the medium and high scenario, a land surplus of 0.6 and 2.4 Mha, respectively, could be generated. Such intensification results in up to 83% emission reduction in Orinoquia’s agricultural sector, largely coming from increasing productivity of cattle production and improving degraded pastures. Biofuel potential from the surplus land is projected at 36 to 368 PJ per year, with a low risk of causing indirect LUC, and results in GHG emission reductions of more than 100% compared to its fossil fuel equivalent. An integrated perspective of the agricultural land use enables sustainable production of both food and bioenergy.

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Modelling of greenhouse gas emissions from European croplands with the biogeochemical model ECOSSE

10.5194/egusphere-egu21-12249 ◽

2021 ◽

Author(s):

Matthias Kuhnert ◽

Michael Martin ◽

Matthew Mcgrath ◽

Pete Smith

Keyword(s):

Greenhouse Gas ◽

Large Scale ◽

Agricultural Sector ◽

Ghg Emissions ◽

Production Model ◽

Small Scale ◽

Biogeochemical Model ◽

Annual Data ◽

System Variable ◽

Nitrogen Emissions

Greenhouse gas (GHG) emissions contribute to climate change. Agricultural production contributes 10 &#8211; 14 % of the global anthropogenic GHG emission, including 37 % from soils (Paustian et al., 2016). Monitoring and analysis of emissions from agriculture is the basis for reducing GHG emissions and applying mitigation options. Measuring and estimating emissions from the agricultural sector are challenging and modelling is a useful tool to capture the heterogeneity of the dynamics. Agricultural management is the main driver for the carbon and nitrogen dynamics in croplands, which makes model approaches difficult, as potentially there is great heterogeneity in the influencing factors, but also a lack of robust data for management data for larger scales. Additionally, measurements of GHG emissions are scarce, on small (spatial and temporal) scales, or do not reflect the entire range of system variable combinations. This hinders the evaluation of large scale simulation results. The objective of the study was to simulate the GHG emissions (CO2 and N2O) for European croplands and use national inventory data for the evaluation of the results. We used the model ECOSSE which is based on the carbon model RothC and the nitrogen model SUNDIAL. For yield production, the primary production model MIAMI is coupled with ECOSSE. The model structure allows small scale differences (resolution for simulation is 0.1&#176;) to be captured, while simulating monthly time steps. This balances the uncertainty of the available input data with the accuracy of the simulated results. The model shows reasonable results for the CO2 emissions, but underestimates heterotrophic respiration, which leads to an overestimation of carbon fluxes to the soil. Nitrogen emissions are underestimated due to underestimation of fertilizer applications in some hot spots. The comparison with national inventories that depend mainly on statistics using simpler approaches shows differences to the simulation approach, which indicates the strong dependency of the emissions on the management data. The model approach provides the spatial distribution of the emissions as well as inter-annual dynamics. The changes on the model showed already the improved performances by the model and the extension to include more target variables. More sub-national and sub-annual data sets for evaluation will allow a further improvement of the model performance.&#160;

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