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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Feedstock Carbon Intensity Calculator (FD-CIC): Users’ Manual and Technical Documentation

The carbon intensities (CIs) of biofuels are determined with the life cycle analysis (LCA) technique, which accounts for the energy/material uses and emissions during the complete supply chain of biofuel including feedstock production and fuel conversion stages. Regulatory agencies such as California Air Resources Board (CARB) adopts LCA to calculate biofuel CIs. The Low Carbon Fuel Standard (LCFS) program developed by CARB allows individual biofuel conversion facilities to submit their own biofuel CIs with their facility input data and incentivizes the reduction in the CI specific to that particular facility compared to a reference fuel’s CI (Liu et al 2020). Such an incentive program has driven innovations in biorefineries to reduce their greenhouse gas (GHG) emissions by linking their revenue directly to its CI score through LCFS credit trading. Besides the biofuel conversion stage, different farming practices for feedstock growth can result in significant CI variations for feedstocks, thus for biofuels. To provide evidence-based research findings, the U.S. Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) has supported the Systems Assessment Center of the Energy Systems and Infrastructure Analysis Division at Argonne National Laboratory to examine CI variations of different farming practices to grow agricultural crops for biofuel production. Meanwhile, the ARPA-E has launched the Systems for Monitoring and Analytics for Renewable Transportation Fuels from Agricultural Resources and Management (SMARTFARM) program to develop technologies and data platforms that enable an accurate measurement of key farming parameters that can help robust accounting of the GHG benefits of sustainable, low-carbon agronomic practices at farm level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Precision Agriculture using Networks of Degradable Analytical Sensors (PANDAS) (Final Technical Report)

Precision agriculture, where sensing of soil, environment and crop conditions are used to precisely synchronize inputs (such as water and fertilizer) to crop needs enhances input use efficiency. This can improve yields and farm profitability while mitigating environmental losses, improving soil carbon content and substantially decreasing energy use for food, feed and fuel crops. Unfortunately, farmers are not yet able to harness the full potential of these management technologies as there is a lack of available management information, and there is therefore a need for sensors that are able to economically measure spatio-temporal variability in soil and crop properties of extremely heterogeneous farm fields precisely at high resolution and at low cost. Real-time, in-situ monitoring of agricultural soil conditions is today carried out using devices that limit the total number of nodes that can be used economically to typically one per acre or less. Higher spatio-temporal resolution sensing would enable more precise agricultural input optimization, with significant benefits to the farmer and the environment. In order to address this issue, this project focused on developing additively manufactured, biodegradable, soil sensors with predicted costs of < $\$$1 per unit to monitor crop inputs (such as water and fertilizer) that predictably, harmlessly degrade away into the soil when no longer needed. These sensor nodes should be easy to place, accurately and continuously monitor soil and crop conditions for an entire season, be read remotely using existing farm equipment, require no ongoing maintenance, not impede farm operations and produce no persistent waste. This approach could enable a >100× increase in information density over current solutions for precision farming of row and other crops, and lead to significant reductions in input energy use and provide increased yield for biofuel crops. Over the course of this project the team at the University of Colorado Boulder, University of California Berkeley, and Colorado State University/Kansas State University investigated a wide range of printable biodegradable electronic materials and sensor designs for determining soil moisture and soil nitrate concentration. These efforts expanded the available materials set for printed soil degradable electronic materials, particularly for conductors, enabling high conductivity and stability. Printed soil moisture and nitrate sensors with suitable sensitivity and selectivity were developed and characterized. Low power and passive wireless electronic systems were integrated with the soil sensors, and testing was carried out with completed sensors to understand their functionality under agricultural conditions. Additionally, other sensor types enabled by the biodegradable materials set created during this project, such as soil microbial activity sensors, were also developed and demonstrated. Project outputs include 10 peer reviewed publications, 4 patent applications, 21 technical presentations, 3 PhD thesis, 10 media reports, 8 additional grants worth over $\$$6M, and the formation of 3 start-up companies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Comparative nutrient drawdown capacities of farmed kelps and implications of metabolic strategy and nutrient source

Abstract Seaweed aquaculture, particularly kelp farming, is a popular topic as a potential solution for mitigating anthropogenic pollutants and enhancing coastal drawdown of carbon and nitrogen. Using a common garden approach, this study evaluated nutrient drawdown capacities of Alaria marginata (ribbon kelp) and Saccharina latissima (sugar kelp) across four commercial kelp farms in Southeast and Southcentral Alaska. Our findings show that A. marginata exhibited ~30% more carbon and 21% more nitrogen content compared to S. latissima . These results demonstrate the potential for A. marginata to serve as a more efficient species for nutrient drawdown into farmed kelp tissues (per unit biomass) for consideration of potential mitigative actions. The efficacy of this drawdown is likely to be driven by the careful pairing of kelp species with farming environment. Temporally, there was a noted increase in carbon content and a decline in nitrogen content from March to May for both species, consistent with known seasonal nutrient dynamics in coastal waters. Notably, differences in the carbon stable isotope signatures (δ 13 C) between the kelps may hint at variations in metabolic pathways and nutrient sourcing, particularly concerning the preferential assimilation of CO 2 versus , and highlight the need for further work on this topic for applied macroalgal research.

Stephens, Tiffany↗
DOE OSTI2022

Characterization of the SRNL-Washed Tank 51 Sludge Batch 10 Qualification Sample

Savannah River National Laboratory (SRNL) personnel have been requested to qualify the next sludge batch (Sludge Batch 10 – SB10) for processing at the Defense Waste Processing Facility (DWPF). To accomplish this task, Savannah River Remediation (SRR) sent SRNL two 3-L samples of Tank 51H slurry to be characterized, washed, and then used in a lab-scale demonstration of the DWPF flowsheet. Sample HTF-51-19-114 was received on January 28, 2020, and HTF-51-20-15 was received on February 4, 2020. SRNL washed the Tank 51H sample per the Tank Farm washing strategy. During washing, material from H Canyon Tanks 16.3 and 16.4 was also added to the Tank 51 samples to simulate canyon discharges subsequent to sampling. A part of the qualification process is extensive radionuclide and chemical characterization of the SRNL-washed Tank 51H slurry. This report documents the chemical characterization of the washed slurry; radiological characterization will be documented in a separate report. The major supernatant components, elements on a weight percent calcined basis, and the weight percent solids of the SRNL-washed sample were comparable to the Tank Farm projections, with the exception of free hydroxide and carbonate. Therefore, this SRNL-washed sample is suitable for further SB10 qualification activities and SRR planning for SB10.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Impacts of photovoltaic solar energy on soil carbon: A global systematic review and framework

Globally, solar energy is anticipated to be the primary source of electricity as early as 2050, and the greatest additions in capacity are currently in the form of large, ground-mounted photovoltaic solar energy facilities (GPVs). Growing interest lies in understanding and anticipating opportunities to increase soil carbon sequestration across the footprint and perimeter of both conventional and multi-use GPVs (e.g., ecovoltaics, agrivoltaics, and rangevolatics), especially as operators increasingly deputize as land managers. To date, studies on the relationship between soils and PV solar energy are limited to unique, localized sites. This study employed a systematic review to (i) identify a global corpus of 18 studies on interactions between GPVs and soils, (ii) collect and characterize 113 soil and soil-related experimental variables interacting with GPVs from this corpus, and (iii) synthesize trends among these experimental variables. Next, this study combined data from the systematic review with an iterative, knowledge co-production approach to produce a conceptual model for the study of soil and GPV interactions that applies to multiple installation types, scales, and contexts where GPVs are deployed, and identified research opportunities, threats, and priorities. This study's baseline understanding, conceptual model, and co-produced knowledge confer unique insight into the feasibility of combining soil carbon sequestration with the climate change mitigation potential of PV solar energy.

agrivoltaics↗
DOE OSTI2024

Advances in Miscanthus × Giganteus Planting Techniques May Increase Carbon Uptake in the Establishment Year

Agricultural lands hold significant potential for CO 2 sequestration, particularly when utilizing biomass crops and agricultural residues. Among these, Miscanthus × giganteus (mxg) stands out due to its high productivity and carbon sequestration capabilities. Recognizing the importance of such biomass crops, the Intergovernmental Panel on Climate Change (IPCC) has identified Bioenergy with Carbon Capture and Storage (BECCS) as a crucial strategy for achieving net-zero CO 2 emissions by 2050. This study examines the carbon uptake potential of mxg during its establishment year at the Sustainable Advanced Bioeconomy Research (SABR) farm in Iowa, USA, where mxg was planted at a density exceeding previous studies. Using eddy covariance (EC) measurements, we quantified the net ecosystem carbon exchange (NEE), and derived gross primary productivity (GPP), and ecosystem respiration (R eco ). Our findings reveal that SABR's mxg exhibited a significant carbon uptake of –621 g C m –2 , a threefold increase compared to a similar EC site in the “corn-belt” (University of Illinois Energy Research Farm; UIEF), which was established with lower planting density and pre-commercial planting equipment. Favorable growing conditions and advanced planting technologies at SABR likely contributed to this high carbon uptake. Comparisons with other global EC studies indicated a strong correlation between higher planting densities and greater carbon uptake. These results suggest that increasing mxg planting density can enhance carbon uptake, but further studies are necessary to evaluate the impacts under varying environmental conditions and management practices. Additionally, economic analyses are essential to determine the viability of higher planting densities. Our study underscores the potential of optimized mxg management practices to contribute significantly to CO 2 uptake and supports the development of BECCS as a viable climate change mitigation strategy.

09 BIOMASS FUELS↗
DOE OSTI2022

2021 Component Innovation Project Awardee: Bergey Windpower

In recent years, the cost of small wind turbines for homes, farms, and small businesses has decreased dramatically thanks to advances in American technology made possible by research and development support from the U.S. Department of Energy. But further reductions are needed to realize the gigawatt-scale potential of distributed wind energy to help electrify rural America, reduce carbon emissions, and create jobs. Currently, for residential- and farm-scale wind turbines with direct-drive, permanent-magnet alternators, the alternator is the highest-cost component of the wind turbine (excluding the tower). The Bergey Windpower Excel 15 wind turbine incorporates advanced technology in its rotor and controls and will soon incorporate advanced power electronics - but its alternator is based on technology that is more than a decade old. To help reduce capital expenditures of the Excel 15 wind turbine, Bergey Windpower is developing an advanced, lower- cost, permanent-magnet alternator.

CIP↗
DOE OSTI2026

Producing cultivated meat cuts that match traditional meat in quality and affordability (CRADA Final Report)

Novel Farms, Inc., as a participant of the Cyclotron Road Lab-Embedded Entrepreneurship Program, investigated the performance of various animal cell lines and animal cell media formulations using its proprietary scaffolds as a growth substratum towards the development of economically-feasible cultivated meat production. As an alternative to conventionally farmed animal meat, cultivated meat production has the potential to yield a marginal carbon footprint while providing sustainable and cruelty-free animal protein. The prohibitively high cost of the growth factors necessary in animal cell culture media constitutes the primary barrier that hinders the economically viable production of cultivated meat products. Furthermore, scaffolding is required to create structured meat products, but current options are unsuitable for cost-effective large-scale production of cultivated meat. Novel Farms has developed a proprietary technology to produce scaffolding that has the potential to reduce production costs while providing an ideal 3D surface for cell growth. Developing cost-efficient methods for cultivated meat production will be vital in satisfying the growing demand for animal protein while avoiding the deforestation, carbon emissions, biodiversity loss and other negative outcomes of industrial animal farming.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Feedstock Carbon Intensity Calculator (FD-CIC) Users’ Manual and Technical Documentation

A transparent and easy-to-use tool for feedstock-specific, farm-level CI calculation of feedstocks is helpful. With the ARPA-E support, we have developed a tool–the Feedstock Carbon Intensity Calculator (FD-CIC). The first version of FD-CIC was released with the GREET® model in 2020 (Wang et al., 2020) so that corn feedstock producers could use this publicly available tool (https://greet.es.anl.gov/tool_fd_cic) to quantify corn grain CIs with farm-level input data and management practices. In the 2021 version, we expand the tool’s capabilities by including additional feedstocks such as soybeans, sorghum, and rice. Similar to corn, it calculates the farm-level CI for these feedstocks by allowing user-defined farm-level farming inputs and incorporating the GHG emission intensities of these inputs from GREET (in particular, GREET1, the fuel cycle model of GREET).

09 BIOMASS FUELS↗
DOE OSTI2023

Disruptive Supplies of Affordable Biomass Feedstock Grown in the Open Ocean

Marine BioEnergy was founded to commercialize a patented invention to enable open ocean kelp farms to produce feedstock by depth-cycling the farms. The concept is to surface the kelp during the day to absorb sunlight and CO 2 , and submerge the kelp at night to the nutrient-rich waters below the thermocline (~60-300 m deep). In an experiment, the kelp thrived in the depth-cycling environment. ARPA-E provided additional funds for Marine BioEnergy to develop a design of a full-scale farm system. Marine BioEnergy is preparing to deploy these farms, towed by unmanned drone submarines, to depth-cycle the kelp and produce disruptive supplies of affordable biomass feedstock that can be used to make carbon-neutral, drop-in fuels to enable the transition to net-zero carbon.

09 BIOMASS FUELS↗
NASA NTRS2003

Farming in space: environmental and biophysical concerns

The colonization of space will depend on our ability to routinely provide for the metabolic needs (oxygen, water, and food) of a crew with minimal re-supply from Earth. On Earth, these functions are facilitated by the cultivation of plant crops, thus it is important to develop plant-based food production systems to sustain the presence of mankind in space. Farming practices on earth have evolved for thousands of years to meet both the demands of an ever-increasing population and the availability of scarce resources, and now these practices must adapt to accommodate the effects of global warming. Similar challenges are expected when earth-based agricultural practices are adapted for space-based agriculture. A key variable in space is gravity; planets (e.g. Mars, 1/3 g) and moons (e.g. Earth's moon, 1/6 g) differ from spacecraft orbiting the Earth (e.g. Space stations) or orbital transfer vehicles that are subject to microgravity. The movement of heat, water vapor, CO2 and O2 between plant surfaces and their environment is also affected by gravity. In microgravity, these processes may also be affected by reduced mass transport and thicker boundary layers around plant organs caused by the absence of buoyancy dependent convective transport. Future space farmers will have to adapt their practices to accommodate microgravity, high and low extremes in ambient temperatures, reduced atmospheric pressures, atmospheres containing high volatile organic carbon contents, and elevated to super-elevated CO2 concentrations. Farming in space must also be carried out within power-, volume-, and mass-limited life support systems and must share resources with manned crews. Improved lighting and sensor technologies will have to be developed and tested for use in space. These developments should also help make crop production in terrestrial controlled environments (plant growth chambers and greenhouses) more efficient and, therefore, make these alternative agricultural systems more economically feasible food production systems. c2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

Review↗
DOE OSTI2020

Shifting agricultural practices to produce sustainable, low carbon intensity feedstocks for biofuel production

The carbon intensity (CI) of biofuel's well-to-pump life cycle is calculated by life cycle analysis (LCA) to account for the energy/material inputs of the feedstock production and fuel conversion stages and the associated greenhouse gas (GHG) emissions during these stages. The LCA is used by the California Air Resources Board's Low Carbon Fuel Standard (LCFS) program to calculate CI and monetary credits are issued based on the difference between a given fuel's CI and a reference fuel's CI. Through the Tier 2 certification program under which individual fuel production facilities can submit their own CIs with their facility input data, the LCFS has driven innovative technologies to biofuel conversion facilities, resulting in substantial reductions in GHG emissions as compared to the baseline gasoline or diesel. A similar approach can be taken to allow feedstock petition in the LCFS so that lower-CI feedstock can be rewarded. Here we examined the potential for various agronomic practices to improve the GHG profiles of corn ethanol by performing feedstock-level CI analysis for the Midwestern United States. Our system boundary covers GHG emissions from the cradle-to-farm-gate activities (i.e. farm input manufacturing and feedstock production), along with the potential impacts of soil organic carbon change during feedstock production. We conducted scenario-based CI analysis of ethanol, coupled with regionalized inventory data, for various farming practices to manage corn fields, and identified key parameters affecting cradle-to-farm-gate GHG emissions. The results demonstrate large spatial variations in CI of ethanol due to farm input use and land management practices. In particular, adopting conservation tillage, reducing nitrogen fertilizer use, and implementing cover crops has the potential to reduce GHG emissions per unit corn produced when compared to a baseline scenario of corn–soybean rotation. This work shows a large potential emission offset opportunity by allowing feedstock producers a path to Tier 2 petitions that reward low-CI feedstocks and further reduce biofuels' CI. The prevalence of significant acreage that has not been optimized for CI suggests that policy changes that incentivize optimization of this parameter could provide significant additionality over current trends in farm efficiency and adoption of conservation practice.

09 BIOMASS FUELS↗
NASA NTRS2015

A Framework for the Cross-Sectoral Integration of Multi-Model Impact Projections: Land Use Decisions Under Climate Impacts Uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

farmlands↗
DOE OSTI2020

Assessment of Water Quality in Indo-Gangetic Plain of South-Eastern Asia under Organic vs. Conventional Rice Farming

Water contamination is often reported in agriculturally intensive areas such as the Indo-Gangetic Plain (IGP) in south-eastern Asia. We evaluated the impact of the organic and conventional farming of basmati rice on water quality during the rainy season (July to October) of 2011 and 2016 at Kaithal, Haryana, India. The study area comprised seven organic and seven conventional fields where organic farming has been practiced for more than two decades. Water quality parameters used for drinking (nitrate, NO 3 ; total dissolved solids (TDS); electrical conductivity (EC) pH) and irrigation (sodium adsorption ratio (SAR) and residual sodium carbonate (RSC)) purposes were below permissible limits for all samples collected from organic fields and those from conventional fields over the long-term (~15 and ~20 years). Importantly, the magnitude of water NO 3 contamination in conventional fields was approximately double that of organic fields, which is quite alarming and needs attention in future for farming practices in the IGP in south-eastern Asia.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗
DOE OSTI2023

Technical Assessment of Potential Climate Impact and Economic Viability of Biochar Technologies for Small-Scale Agriculture in the Pacific Northwest

The goal of this study is to evaluate the state of biochar technology and determine the feasibility of integrating small-scale biochar production in ways that benefit smaller, diversified producers. Because of the emergence of carbon markets, this innovative climate and agricultural solution may be financed externally, making biochar more accessible to the growers that could benefit. In this report, we review the current state of biochar technology (Section 2), methods for assessing the potential climate impacts derived from its implementation (Section 3), and the current state of carbon-offset mechanisms for biochar technology (Section 4). In Section 5, we apply this knowledge to several specific biochar technology scenarios involving combinations of different feedstocks, production methods, and economic incentives to arrive at estimates of climate-mitigation impacts and costs per carbon credit generated. We conclude with a summary in Section 6.

09 BIOMASS FUELS↗
DOE OSTI2024

Economic, Greenhouse Gas, and Resource Assessment for Fuel and Protein Production from Microalgae: 2022 Algae Harmonization Update

This report presents an updated “harmonization study” documenting the collaborative analysis of saline microalgae cultivation and conversion to fuels and products. Four national laboratory modeling teams reconvened to investigate the resource, economic, and environmental sustainability implications of integrated systems encompassing large-scale algae farms and conversion biorefineries. Relative to prior harmonization analyses conducted by these partners, the present effort focuses on more near-term technology potential based on the use of nutrient-replete, high-protein algal biomass compositions (more readily achievable today without sacrificing cultivation productivity) coupled with individual algae farms varying in size but generally smaller at 3,900 acres on average (more realistic in practice than a fixed 5,000-acre farm scale previously considered). Additionally, the present assessment adds further granularity around carbon dioxide (CO 2 ) sourcing and transport via carbon capture of nearby point sources, as well as handling of high-saline cultivation media and resultant blowdown/disposal processing. Finally, this assessment focuses on conversion opportunities to produce both fuel (prioritizing sustainable aviation fuel [SAF], in this case via hydrothermal liquefaction) and protein products for the food and feed markets, recognizing growing needs for such products.

09 BIOMASS FUELS↗
NASA NTRS2014

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

carbon dioxide↗