Increased biofuel production has been associated with direct and indirect land-use change, changes in land management practices, and increased application of fertilizers and pesticides. This has resulted in negative environmental consequences in terms of increased carbon emissions, water quality, pollution, and sediment loads, which may offset the pursued environmental benefits of biofuels. This study analyzes two distinct policies aimed at mitigating the negative environmental impacts of increased agricultural production due to biofuel expansion. The first scenario is a fertilizer tax, which results in an increase in the US nitrogen fertilizer price, and the second is a policy-driven reversion of US cropland into forestland (afforestation). Results show that taxing fertilizer reduces US production of nitrogen-intensive crops, but this is partially offset by higher fertilizer use in other countries responding to higher crop prices. In the afforestation scenario, crop production shifts from high-yielding land in the United States to low-yielding land in the rest of the world. Important policy implications are that domestic policy changes implemented by a large producer like the United States can have fairly significant impacts on the aggregate world commodity markets. Also, the law of unintended consequences results in an inadvertent increase in global greenhouse gas emissions.
World agriculture has been significantly impacted by a number of events that have occurred in the past five to ten years. Arguably the most prominent is the dramatic global expansion of biofuels, especially in the United States and Brazil, driven by mandates, federal and state incentives, and trade barriers [
While biofuel production has been touted as a solution to the adverse environmental impacts of fossil fuels, studies have challenged this notion especially as it relates to indirect land-use change [
Agricultural management practices in general and land use in particular play a key role in determining the effectiveness of major policy proposals aimed at mitigating climate change, including the implementation of different offset policies that encourage afforestation. A report by the USDA [
Additionally, the increased application of fertilizers and pesticides as well as changes in land management practices (e.g., corn-corn rotation versus corn-soybean rotation) associated with higher biofuel production has been shown to have environmental consequences in terms of water quality, pollution, and sediment loads [
Given the increased use of both agricultural land and fertilizer brought about by biofuel expansion and the corresponding environmental effects, the overall purpose of this study is to provide policy-relevant information to further the development of rational policies aimed at mitigating negative environmental impacts of the expanded production in the agricultural sector. Specifically, the objective is to analyze the impact of two alternative policy scenarios. The first is a US fertilizer tax scenario, where a tax on nitrogen fertilizer increases its price by 10%. The second is a policy-driven afforestation scenario, in which we evaluate the effects of large areas of cropland being used for forests to sequester carbon, in response, for example, to incentive payments for carbon.
An improved version of the deterministic FAPRI-CARD agricultural modeling system is used for this analysis.
The FAPRI-CARD agricultural modeling system is a set of multimarket, partial-equilibrium, and nonspatial econometric models.
FAPRI-CARD model inputs and output.
Exogenous inputs | Population, GDP, GDP deflator, exchange rate, population, policy variables |
Historical data |
Production, consumption, exports, imports, ending stocks, Domestic prices, world prices |
Commodities | |
Grains | Corn, wheat, sorghum, barley |
Oilseeds | soybeans, rapeseed, sunflower |
Livestock products | beef, poultry, pork |
Dairy | milk, cheese, butter |
Sugar | |
Ethanol/biodiesel | |
Major countries/regions | |
North America | United States, Canada, Mexico |
South America | Brazil, Argentina, and so forth* |
Asia | China, Japan, India, Indonesia, Malaysia, and so forth* |
Africa | South Africa, Egypt, and so forth* |
European Union | |
Australia, |
|
Middle East | |
Output by commodity |
World prices, domestic prices, production, consumption, net trade, stocks, area harvested, yield |
The commodity models capture the biological, technical, and economic relationships among key variables within a particular commodity and across commodities (see Figure
FAPRI-CARD model interactions. The model interactions represent trade, prices, and physical flows.
The models specify behavioral equations for production, use, stocks, and trade between countries/regions. The crop supply side is the product of area harvested and yields, wherein the former is determined by a system of land allocation based on the relative expected profitability of competing enterprises (e.g., corn and soybeans) and the latter is driven by an exogenous trend yield as well as intensification and extensification effects. The intensification effect reflects more intensive use of inputs such as fertilizer when revenue grows faster than cost. The extensification effect reflects declining yield as more marginal land is brought into production.
In general, the demand side of the model is categorized into food, feed, and industrial demand, whereby one aspect of industrial demand is the demand from the biofuel sector for feedstocks. Food demand is primarily driven by macroeconomic assumptions such as income and population while feed demand is driven by the livestock, poultry, and dairy sectors. Industrial (biofuel) demand is determined by the energy price assumption as well as by existing government policies such as the US EISA 2007 and the Renewable Energy Directive of the European Union. The meat supply side is a combination of investment decisions on the breeding herd and output decisions on slaughter. The animal inventory is the main driver of the feed grain and oilseed meals demand.
For each commodity, a number of countries and regional aggregates are included so as to have worldwide coverage. In general, for each commodity sector, the economic relationship that quantity supplied equals quantity demanded is achieved through a market-clearing price for the commodity. In many countries, domestic prices are modeled as a function of the world price using a price transmission equation, which includes exchange rates and relevant trade policies. As is evident from Figure
The agricultural modeling system also includes a fertilizer component where changes in yields due to intensification are linked to changes in the fertilizer cost. The fertilizer cost is composed of the application rate of nitrogen (N), phosphorous (P), and potassium (K) multiplied by their respective prices. The linkage between yields and fertilizer cost is a function of the yield elasticities with respect to fertilizer application rates and the share of fertilizer cost in the total variable cost. This component also enables us to project fertilizer application rates and fertilizer demand by commodity, by country, and by nutrient. A more detailed explanation of the FAPRI-CARD fertilizer component is available in a paper by Rosas [
A model that is able to account for the GHG emissions from agriculture can be linked to the FAPRI-CARD system. The model, called Greenhouse Gases from Agriculture Simulation Model (
The GHG model tracks six categories of land, namely, forest, shrub land, grass land, set-aside, cropland, and pasture. Pastureland is derived from changes in animal inventory and some historical stocking rate. The algorithm of land dynamics in the model for increases in agricultural land is such that idle land comes into production first. Moreover, a “last in, first out” rule is applied in the conversion of agricultural land. Only when idle land is exhausted will native vegetation be converted into agricultural land. The GHG model also uses fertilizer application rates and aggregate fertilizer demand information from the FAPRI-CARD model. A more detailed description of this model is given in Dumortier et al. [
The baseline provides a starting point for evaluating and comparing scenarios. This baseline provides 15-year projections (2011–2025) of world agricultural production, consumption, stocks, trade, and prices by country and commodity. The projections are grounded in a series of assumptions about the general economy, agricultural policies, the weather, and technological change. Specifically, these projections are based on the assumption of average weather patterns, existing farm policy, and policy commitments under current trade agreements and custom unions. They also generally assume that current agricultural policies will remain in force in the United States and in other trading nations during the projection period.
Bioenergy mandates in a number of countries are key drivers in the baseline. In the United States, the Renewable Fuel Standard (RFS) and other provisions of EISA 2007 are implemented, with the exception of the cellulosic ethanol RFS (because of waivers). The existing US biofuel mandates are binding in the baseline. Another key assumption is that ethanol and biodiesel support policies in the United States disappear in 2012. These include ethanol and biodiesel tax credits and biofuel import tariffs.
Additionally, long-run equilibrium is imposed in the ethanol sector in the United States as well as in the international livestock and dairy sectors. In the long run, in equilibrium, there is no incentive to build new ethanol plants and there is no incentive to shut down existing plants. This means that the profit margins of the ethanol plants are zero in the long run. In the livestock and dairy sectors, supply and prices adjust so that net returns go back to “normal” levels in the long run; that is, the returns are at levels sufficient to keep producers in business. This long-run equilibrium is imposed in the year 2023.
The baseline projections are run against a backdrop of a macroeconomic environment that includes an economic turnaround, which began in 2010, continuing population growth and urbanization and ever-expanding biofuel mandates such as EISA 2007 in the United States and the Renewable Energy Directive of the European Union.
Overall, throughout the projection period, agricultural markets are impacted by increasing demand and higher prices driven by income growth, population growth, and expanding demand for biofuel feedstocks. Table
Baseline prices for major commodities.
2011 | Long run* | |
---|---|---|
(US dollars per metric ton) | ||
Wheat FOB Gulf | 270 | 274 |
Corn FOB Gulf | 183 | 200 |
Soybean CIF Rotterdam | 442 | 475 |
Beef Nebraska Direct | 2,274 | 2,530 |
Barrow and Gilt, National | 1,226 | 1,463 |
Broiler U.S. 12-City | 1,924 | 2,256 |
(US dollars per gallon) | ||
Anhydrous ethanol, Brazil | 1.63 | 2.60 |
Ethanol FOB Omaha | 1.97 | 2.04 |
Biodiesel Central Europe FOB | 4.77 | 5.81 |
US biodiesel plant | 4.22 | 4.84 |
In the baseline, the world corn prices are driven by both strong demand from various uses of corn, which leads to an increase in price, and growth in trend yields and the capping of the RFS by 2015. This results in a downward pressure on prices. Thus, corn prices remain fairly flat over the projection period, increasing to $200 per metric ton by 2023. Corn trade grows by 4% annually over the decade. Corn used as ethanol feedstock also increases with rising mandates in several countries. For example, Canada’s ethanol feedstock represents 20% of its total domestic use, the European Union, 12%, and the United States, 39%. Other grains follow the same pattern as corn, whereby both prices and net trade rise over the projection period.
Because of rising incomes, strong demand, mostly for vegetable oils for food and biodiesel use, sustains the prices of oilseeds and their products at high levels. Crush is increasingly driven by the demand of vegetable oil, which pressures soybean meal prices downward by the end of the period.
World fertilizer use increases 5% by 2023 relative to the 2010 crop season, reflecting the expansion of the world’s cropland. Higher use is also driven by the more intensive use of fertilizers at the world level in commodities such as corn, barley, rapeseed, peanuts, and cotton, driven by their strong prices. World fertilizer use in corn is projected to be higher in NPK relative to 2010 because of the increase in both corn harvested areas and fertilizer application rates. This is especially true for the United States, the world’s second largest fertilizer consuming country (after China). The use of P and K increases by a larger percentage relative to N because of their higher elasticity with respect to corn price changes. World fertilizer use in soybeans has similar levels of N and increases of 5% and 2% in P and K, respectively, relative to 2010. This is caused by the increase in global soybean harvested area that offsets the decrease in nutrient application rates per hectare. China, India, the United States, and the EU countries account for more than two-thirds (65%) of the world’s fertilizer consumption in agriculture.
Increased fertilizer use has significant implications on GHG emissions as is evident from Figure
Baseline change in US nitrous oxide emissions between 2011 and 2025.
The expansion in crop area as well as the rise in meat demand and the resulting expansion in livestock increases emissions from livestock products (especially enteric fermentation) and puts pressure on global forests and grasslands. We estimate that global emissions from agricultural production rise by 14% over the projection period.
Once the baseline is established, specific scenarios are run and the results are compared to the baseline. The first scenario is a fertilizer scenario in which a nitrogen tax increases the price of nitrogen in the United States by 10% over the baseline beginning in 2011 and extending to the final projection year of 2025.
In the second scenario, a US afforestation scenario is analyzed in which we use the crop area displacement from afforestation used in a report by the United States Department of Agriculture [
The two scenarios are presented relative to the baseline projections by comparing the long-run equilibrium results for the baseline (year 2023) to those of the scenarios. The impacts on US and world crops and livestock (i.e., agricultural markets), biofuels, and fertilizer are expressed in terms of percent change between the 2023 baseline and scenario numbers. The only exception is the impact on GHG emissions, which are presented in terms of the average percent change over the projection period. Emissions, particularly for land-use change, are nonlinear and vary significantly from year to year. Thus, average changes over the projection period tend to be more informative than choosing one particular year.
We analyze a fertilizer tax scenario in which the tax increases the price of nitrogen in the United States by 10% over the baseline from 2011 to 2025. US farmers usually apply more nitrogen than they need in a typical year. They do this because they realize that nitrogen can leach in wet years and that it therefore makes economic sense to apply excess nitrogen to insure against wet spring weather [
To put the magnitude of this shock in perspective, total fertilizer cost accounts for almost 40% of corn total variable cost in the US Corn Belt region, and the cost of nitrogen fertilizer represents about 50% of total fertilizer cost. In soybeans, total fertilizer cost accounts for 28% of total variable cost, and the cost of nitrogen fertilizer represents 9% of total fertilizer cost [
Table
Change in commodity prices between baseline and fertilizer tax scenario.
2011* | Long run** | |
---|---|---|
Wheat FOB Gulf | 0.11% | 0.09% |
Corn FOB Gulf | 0.25% | 0.14% |
Soybean CIF Rotterdam | −0.07% | −0.05% |
Beef Nebraska Direct | 0.01% | 0.01% |
Barrow and Gilt, National | 0.01% | 0.08% |
Broiler U.S. 12-City | 0.01% | 0.03% |
Anhydrous ethanol, Brazil | 0.004% | 0.01% |
Ethanol FOB Omaha | 0.05% | 0.08% |
Biodiesel Central Europe FOB | 0.00% | −0.01% |
Biodiesel plant | −0.01% | −0.02% |
Table
Changes in production and net trade between baseline and fertilizer tax scenario (2023).
Production | Net trade | |
---|---|---|
United States | ||
Wheat | −0.19% | −0.45% |
Corn | −0.18% | −0.52% |
Soybeans | 0.07% | 0.11% |
Beef | 0.001% | 0.09% |
Pork | −0.07% | −0.29% |
Broiler | 0.001% | 0.02% |
Ethanol | 0.0003% | 0.001% |
Biodiesel | 0.02% | −4.15% |
Rest of the world | ||
Wheat | 0.01% | 0.07% |
Corn | 0.07% | 0.50% |
Soybeans | −0.02% | −1.53% |
Beef | −0.004% | −0.01% |
Pork | 0.02% | 0.05% |
Broiler | −0.003% | −0.01% |
Ethanol | −0.002% | 0.001% |
Biodiesel | 0.002% | −0.01% |
The impacts on biofuel and livestock production and trade are also presented in Table
With a binding ethanol RFS, the higher corn feedstock price induces a substitution of imported sugarcane ethanol for domestic corn ethanol and higher ethanol prices. In contrast, the cheaper soybean oil biodiesel feedstock leads to higher domestic production of biodiesel, despite lower prices for the product.
Figure
Change in fertilizer use between baseline and fertilizer tax scenario (2023).
In the case of corn production, higher nitrogen prices drive down harvested areas, as well as fertilizer application rates, decreasing total fertilizer use in corn. This result shows the inelasticity of demand for fertilizers in corn. A 10% increase in the price of nitrogen has only minor long-run effects on nitrogen demand. A similar result of lower planted area and lower fertilizer application rates occurs in other grains such as barley, oats, sorghum, and wheat. In contrast, soybeans show an increase in fertilizer use even with a lower fertilizer application rate because area is shifted from nitrogen-intensive crops. Soybean production is characterized by a low use of nitrogen fertilizers because of the crop’s ability to fix nitrogen in soils from other sources. Thus, an increase in the price of nitrogen is expected to make soybean production relatively more attractive.
Since the nitrogen fertilizer price increase is isolated to the United States, the rest of the world responds to the higher world crop prices by increasing area and rates of fertilizer use, but the impacts are small. The overall consequence of such a policy is that the reduction in demand from US nitrogen-intensive crops such as corn, barley, oats, and wheat is partially offset by the higher use in the rest of the world such that world fertilizer use shows only a minor reduction.
The CARD-FAPRI model includes landed prices for each country expressed in US dollars per metric ton of nitrogen, phosphate, and potash units, that is, expressed in nutrient units. Table
US fertilizer landed prices: baseline and fertilizer tax scenario (US$/metric ton).
2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | Avg. | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Baseline | ||||||||||||||
Urea | 440 | 459 | 473 | 473 | 481 | 486 | 487 | 492 | 500 | 508 | 508 | 508 | 508 | 486 |
Super phosphate | 509 | 529 | 552 | 563 | 580 | 590 | 597 | 607 | 617 | 627 | 627 | 627 | 627 | 589 |
Potassium chloride | 513 | 533 | 556 | 568 | 585 | 594 | 602 | 612 | 622 | 632 | 632 | 632 | 632 | 593 |
| ||||||||||||||
Fertilizer tax scenario | ||||||||||||||
Urea | 484 | 505 | 520 | 520 | 529 | 534 | 535 | 541 | 550 | 559 | 559 | 559 | 559 | 535 |
Super phosphate | 509 | 529 | 552 | 563 | 580 | 590 | 597 | 607 | 617 | 627 | 627 | 627 | 627 | 589 |
Potassium chloride | 513 | 533 | 556 | 568 | 585 | 594 | 602 | 612 | 622 | 632 | 632 | 632 | 632 | 593 |
In terms of livestock and associated emissions, with the lower prices of soybean meal and hay offsetting the increase in the price of corn, there are no significant changes in GHG emissions from enteric fermentation and manure management.
The more interesting aspect of the scenario is the inability of the 10% fertilizer price increase to significantly reduce synthetic fertilizer emissions (nitrogen) in the United States. Over the projection period, emissions in the United States decline by an average of only 0.15% and also on a global scale the reductions are negligible.
Change in land carbon sequestration between baseline and fertilizer tax scenario.
Country | Change in Mt of CO2-e | Change in % |
---|---|---|
Argentina | −0.067 | −0.10% |
Brazil | 0.122 | 0.02% |
China | 0.414 | 0.38% |
European Union | 0.135 | 0.19% |
India | 1.327 | 0.69% |
United States | −1.548 | 1.63% |
Rest of the world | 1.314 | 0.09% |
| ||
Total | 1.697 | 0.07% |
However, the increase in global crop area is small and leads to only slightly higher emissions when compared with the baseline. Carbon savings from land reversion in the United States may not be significant because reverted cropland goes into idle cropland category. However, land conversion in the rest of the world may be from native vegetation rich with sequestered carbon. The two main drivers of those emissions are India and China, both having low available idle land and a greater likelihood of conversion of native vegetation to supply increases in cropland.
In order to analyze the impact of the afforestation scenario, we used the crop area displacement from afforestation used by the EPA in its 2005 report, which projects the afforestation of roughly 100 million acres of land in the United States under the scenario of $30 per metric ton of carbon and 50 million acres of displaced area from cropland (Table
Initial area reduction by region in the United States (in million acres).
Regions | 2011 | 2015 | 2020 | 2025 |
---|---|---|---|---|
Corn Belt | 3.57 | 10.71 | 19.64 | 25.00 |
Delta States | 2.29 | 6.86 | 12.57 | 16.00 |
Far West | 0.14 | 0.43 | 0.79 | 1.00 |
Lake States | 0.21 | 0.64 | 1.18 | 1.50 |
Southeast | 0.21 | 0.64 | 1.18 | 1.50 |
Southern Plains | 0.71 | 2.14 | 3.93 | 5.00 |
| ||||
Total | 7.14 | 21.43 | 39.29 | 50.00 |
Table
Change in commodity prices between baseline and afforestation scenario.
2011* | Long run** | |
---|---|---|
Wheat FOB Gulf | 1.42% | 10.51% |
Corn FOB Gulf | 3.60% | 17.12% |
Soybean CIF Rotterdam | 3.45% | 18.48% |
Beef Nebraska Direct | 0.10% | 6.78% |
Barrow and Gilt, National | 0.25% | 9.99% |
Broiler U.S. 12-City | 0.28% | 9.91% |
Anhydrous ethanol, Brazil | 0.06% | 0.24% |
Ethanol FOB Omaha | 0.62% | 7.84% |
Biodiesel Central Europe FOB | 0.16% | 3.65% |
Biodiesel plant | 0.33% | 6.48% |
Based on the EPA area displacement estimate, most of the cropland area converted into forest land is from soybean area. As a result, with a short supply, the soybean price increases by 18.5%. In the livestock sector, the strong feed grain and oilseed meal prices resulting from afforestation lead to a general short supply of meat, causing prices to rise for beef, pork, and poultry.
Table
Change in production and net trade between baseline and afforestation scenario (2023).
Production | Net trade | |
---|---|---|
United States | ||
Wheat | −11.20% | −25.14% |
Corn | −10.31% | −31.38% |
Soybeans | −22.85% | −35.97% |
Beef | −6.95% | 118.31% |
Pork | −4.69% | −19.49% |
Broiler | −6.01% | −14.69% |
Ethanol | −0.02% | 0.08% |
Biodiesel | −4.66% | 1082.43%* |
Rest of the world | ||
Wheat | 0.49% | 3.53% |
Corn | 3.91% | 43.90% |
Soybeans | 6.52% | 15.73% |
Beef | 0.66% | 2.52% |
Pork | 2.61% | 3.02% |
Broiler | 1.75% | 3.00% |
Ethanol | −0.06% | 0.21% |
Biodiesel | −0.60% | 0.24% |
Similarly, afforestation of soybean area in the United States increases soybean area in the rest of the world, with production in Argentina and Brazil increasing. In the livestock sector, the strong feed grain and oilseed meal prices resulting from afforestation contract the US livestock and poultry sectors. Total world production impacts for all meats reflect the differential feed cost structure, whereby beef production responds much less than poultry production to the increase in feed prices.
With the area displacement, US exports of corn and wheat decline. The rest of the world responds to the short supply and higher grain prices, with China reducing corn imports and Brazil and South Africa increasing their corn exports. In the case of wheat, China and Russia increase their net wheat exports. As most of the cropland area converted into forest land is from soybean area, soybean production in the United States declines with decline in both area and yields. Moreover, yield declines suggest a decreasing share of high-yield regions in total US production. With a short supply, US soybean exports are reduced. In the livestock sector, net imports of beef increase while exports of pork and poultry decline. Because of their different feeding rations and associated cost structures, the beef sector gains in relative terms compared with pork and poultry when prices of feeds increase, as consumers substitute away from the relatively more expensive pork and poultry.
The afforestation scenario represents a major shift in US agricultural production, and we see that the unintended consequence of this policy is an increase in carbon emissions from land-use change on a global scale. In Table
Change in emissions between baseline and afforestation scenario.
Enteric fermentation | Manure management | Synthetic fertilizer | ASM (except fertilizer) | LUC emission | |
---|---|---|---|---|---|
(Million metric tons of CO2-equivalent) | |||||
Argentina | −0.01 | −0.01 | 0.03 | 0.15 | 6.50 |
Brazil | −0.02 | 0.03 | 0.09 | 1.30 | 140.51 |
China | −0.30 | −0.01 | 0.68 | 1.51 | 31.54 |
European Union | −0.04 | −0.01 | 0.11 | 0.07 | 8.45 |
India | −0.03 | 0.00 | −0.05 | −0.02 | 3.46 |
United States | −1.23 | −0.54 | −2.77 | −3.48 | −158.95 |
Rest of the world | 0.35 | 0.14 | 0.57 | 1.05 | 114.24 |
World | −1.29 | −0.40 | −1.35 | 0.58 | 145.75 |
| |||||
(Percent change) | |||||
Argentina | −0.02% | −0.18% | 0.81% | 0.18% | 9.95% |
Brazil | −0.01% | 0.12% | 0.86% | 0.51% | 24.05% |
China | −0.17% | −0.01% | 0.70% | 0.41% | 29.29% |
European Union | −0.03% | −0.02% | 0.27% | 0.09% | 12.21% |
India | −0.02% | −0.01% | −0.10% | −0.04% | 1.79% |
United States | −1.04% | −1.37% | −6.43% | −1.62% | 167.27% |
Rest of the world | 0.07% | 0.11% | 0.60% | 0.14% | 7.71% |
World | −0.09% | −0.11% | −0.39% | 0.03% | 6.06% |
Emissions from enteric fermentation decrease for all major countries as most livestock and dairy sectors contract under a high feed regime with afforestation, the sharpest decrease occurring in the United States (1.04%). Emissions from nitrogen application are reduced by 0.39% on a global scale. The main driver of this result is the US cropland reduction, although fertilizer consumption in most other countries increases. For example, total fertilizer emissions increase by 0.86% in Brazil, by 0.7% in China, and by 0.27% in the European Union. The most interesting aspect of the scenario is the increase in carbon emissions related to land-use change in the rest of the world. High-quality US cropland is replaced with lower quality cropland (quality in terms of yield), and, hence, more area is needed to compensate for the reduction in production. We see cropland increase in almost all countries, including in Brazil (0.21%) and in China (0.64%). Because many of these countries have exhausted their idle cropland, any increase in cropland is likely to be supplied by converting land covered by native vegetation, leading to a 6.65% increase in global emissions from land-use change compared with the baseline.
This analysis evaluates the impact of two policy scenarios on US and world agricultural markets, as well as on world fertilizer use and world agricultural greenhouse gas emissions. Both scenarios are adverse supply shocks, the first being a 10% increase in the price of nitrogen fertilizer in the United States, and the second a reversion of US cropland into forestland.
At the end of the baseline projection period, the United States accounts for 18% of the world’s idle cropland, Brazil 43%, Russia 10%, and Mexico 9%. Many of the remaining countries have almost exhausted their idle cropland, including Argentina with only 0.09 million hectares, Australia with 0.46, Canada with 1.30, China with 0.97, India with 0.02, and South Africa with 0.04. This situation is important because, in effect, any shock penalizing the United States in the sense of reducing US cropland and thereby reducing US exports may result in unintended consequences elsewhere, with countries that are short of cropland responding to this new market incentive and expanding domestic production by converting native vegetation, thus releasing rich carbon stock.
In the livestock sector, the most interesting lesson from the scenarios is that they have a differential impact by meat type because of differences in cost structures across sectors. That is, feed cost accounts for only 28% of the total cost in a cow-calf operation while it accounts for 74% of a pork farrow-to-finish operation. Any shock in the United States that raises crop prices will automatically result in relatively higher price changes in pork and poultry compared with beef, which sustains domestic beef consumption through substitution and weakens any reduction of the beef sector from the higher crop prices. Also, pasture-based production systems in other countries may not be too adversely affected by higher grain prices, allowing expansion in world beef production and an increase in world GHG emissions.
The impact of a policy that raises nitrogen fertilizer prices on GHG emissions is muted when the entire agricultural sector in the world market is allowed to adjust. For example, although fertilizer-intensive crops (such as corn) are penalized with higher nitrogen fertilizer prices resulting in lower fertilizer use, more fertilizer is used in the same crops in the rest of the world. Moreover, market rigidities caused by policies dull the impact of higher nitrogen fertilizer prices. This is particularly true in biofuels, which have a binding RFS in both ethanol and biodiesel production in the baseline. Higher corn feedstock prices reduce domestic production of ethanol. But because the RFS is binding, any reduction in domestic corn ethanol is simply replaced by an increase in the imports of sugarcane ethanol from Brazil, thereby raising the world ethanol price, sugarcane area, and sugarcane fertilizer use.
In the afforestation scenario, crop production shifts from high-yielding land in the United States to low-yielding land in the rest of the world. Additionally, there is an increased likelihood that land with native vegetation will be converted into cropland. The net impact is an unintended increase in world greenhouse gas emissions.
In general, the results show that the entire international commodity market system is robust with respect to policy changes in one country or in one sector. The policy implication is that domestic policy changes implemented by a large agricultural producer like the United States can have fairly significant impacts on the aggregate world commodity markets. A second point that emerges from the results is that the law of unintended consequences is at work in world agriculture. For example, a policy geared toward sequestering carbon through afforestation in the United States can end up resulting in a net increase in world greenhouse gas emissions.
The results suggest that to avoid the kind of leakage resulting from the unilateral implementation of policies in a major agricultural producer (like the United States) internationally coordinated policies and actions might be needed. An analysis of alternative concerted policy actions (e.g., simultaneous implementation of the nitrogen tax in all countries of the world), particularly in terms of their ability to more effectively reduce emissions, might be an interesting avenue for future research.
Data on the world crude oil price is from the World Bank [
More details on ACES and EISA can be found at
FAPRI is the Food and Agricultural Policy Research Institute at Iowa State University.
We call the modeling system FAPRI-CARD to distinguish it from the FAPRI system, which involves a model of the US agricultural sector developed and maintained by the University of Missouri at Columbia and international models developed and maintained at Iowa State University. In the FAPRI-CARD system, both the domestic and international models are maintained at Iowa State University.
Links to these sources are available: for USDA PSD Online:
For a more detailed description of each of the models, see
This turns out to be the case for ethanol. However, the blender’s tax credit for biodiesel was extended again in early 2013.
Although the projections extend to 2025, we impose the long-run equilibrium in 2023 to allow the models an additional couple of years to adjust.
This baseline is the FAPRI-ISU World Agricultural Outlook, available at
More detailed tables on the baseline and scenario results by country are available from the authors.
The USDA’s Economic Research Service provides data on fertilizer use by crop and by state for the United States.
Unlike the other impacts, which are expressed in terms of percent change between the baseline and the scenario for the year 2023, the impacts on GHG emissions are for the annual percent changes between the baseline and the scenario averaged over the projection period 2011–2023.
In the model, we implement the reduction of 50 million acres. After the model is run and equilibrium is reached, the net result is a 40-million-acre reduction as area responds to increases in prices and returns.
There is no conflict of interests with any modeling system included in this paper.
This work has also benefited from research funded by the United States Department of Agriculture’s National Institute of Food and Agriculture/Agriculture and Food Research Initiative, Award number IOW05307.