Life Cycle Inventory of Electricity Cogeneration from Bagasse in the South African Sugar Industry

by Monkgogi Bonolo Otohogile

South Africa’s sugar industry is worth over $1.11 billion and South Africa is consistently ranked as one of the top 15 sugar producing countries in the world. The sugar manufacturing process also produces thousands of tonnes of a biomass called bagasse that is being underutilized. Mashoko et al. (2013) investigated the potential for the cogeneration of steam and electricity using bagasse in South Africa’s sugar industry. The authors’ developed life cycle inventories for bagasse electricity production, which they used to evaluate the environmental impacts of cogeneration. Using data supplied by various affiliated organizations and studies, Mashoko and colleagues determined the greenhouse gases, energy ratio, non-renewable energy input, sulfur dioxide, and nitrogen dioxide of a functional unit of 1 GWh of bagasse-derived electricity produced in the South African sugar industry and compared it to coal-derived electricity and bagasse-derived electricity in Mauritius. The authors found that bagasse-derived electricity performed better than coal-derived electricity in every category outlined above. Mashoko et al. argued that by increasing their boiler pressure, the sugar industry could produce cleaner electricity during the sugar life cycle by following in the footsteps of Mauritius. Bagasse-derived electricity could mitigate South Africa’s massive carbon dioxide emissions while also making the sugar industry self-sufficient and contributing to the grid. Continue reading

Aquaponics and the Active Promotion of Symbiosis in Agriculture

by Carin Ragland

On a large number of farms, land owners rent their land to farmers instead of cultivating the land themselves. Through such agreements, land ownership becomes a source of income, which is provided by the proceeds of the tenants. But in every market there is competition. In the 20th century, the seeds of rapid urban development were sown around urban hubs as the invention of commercial cars and public transit systems pushed suburbs further into the surrounding rural areas (Fainstein, 2014; Rodrigue, 2014). Owners of agricultural land now have a choice: rent their land to farmers or sell it to developers. The decision depends on the highest bidder: tenants may continue to farm the land as long as they can grow and sell enough produce to pay their landlords a sum comparable to potential profits of a land sale to developers. Continue reading

Sustainable Bioenergy: Evolving Stakeholder Interests

by Christina Whalen

The diversity of stakeholders’ interest and values complicates the decision-making process involved in the future of sustainable bioenergy production. Johnson et al. explores the different stakeholder perspectives and then examines how this diversity affects research on the subject. Biofuel production has been brought to the public’s attention because of the need to mitigate greenhouse gas (GHG) emissions, increase energy security, support farm production, and improve economic growth in rural areas. The recent increase in biofuel consumption has resulted in stakeholders questioning environmental, economic, and social benefits of using agriculture to produce ethanol and biodiesel. As a result, policy makers have passed legislation and modified regulations about renewable fuel production in order to promote the use of alternative biomass feedstocks. The general research community is looking for ways to convert this feedstock to a usable fuel source in vehicles. The expansion of biofuel production coincides with Continue reading

Farmers Think Hard Before Planting Biofuel Crops

by Christina Whalen

Using Kansas as an example, White et al. (2012) examine the various factors that influence farmer decision-making during this controversial era of climate change and energy conservation. A conceptual model for understanding farmer’s decisions was developed from interviews conducted with a diversity of farmers and key informants. Interestingly enough, results demonstrate that most farmers hold a positive perception of the natural environment and don’t have a strong concern about climate change issues. The guiding factors of farmer’s decisions about whether or not to cultivate biofuel crops are the relative advantages of the practice and the ability to discuss the practice with a social network. There is a strong need to create a renewable energy market in the U.S. because of its potential to reduce greenhouse gases and increase production benefits; biofuel crops pose one plausible solution. The paper addresses the following question: considering global climate and energy concerns, what are the main influences on farmer’s decisions regarding land use, specifically the decision to cultivate biofuel crops? Continue reading

Kansas: Why Farmers Grow Biofuel Crops

Agriculture has been criticized for its contribution to greenhouse gas emissions (GHG), but there has not been sufficient research investigating how agriculture can be beneficial in a future with climate change. One beneficial solution is biofuel cultivation, which according to the 2009 Renewable Fuels Standard (RFS2) would significantly reduce GHG emissions (White and Selfa, 2013). As one of the most productive agricultural states, Kansas was chosen by White and Selfa as a valuable case study to investigate factors that influence the farmer decision-making process regarding innovations. Prior to the case study, White and Selfa conducted a literature review on previous studies done nationally and internationally. From the data they developed a conceptual model of key elements involved in farmer decisions. With this model in mind White and Selfa conducted their own study in Kansas by interviewing 16 key informants with expertise in agriculture and environmental issues and 17 farmers. The study concluded that farmers were influential in adopting a new idea such as biofuel cultivation by local environmental conditions, communication through existing social relations, the assurance of farmers continual independence, a contribution to a greater societal good, and whether change was more economically advantageous than previous practices. –Caroline Vurlumis


White, S., Selfa, T., 2013. Shifting Lands: Exploring Kansas Farmers Decision-Making in an Era of Climate Change and Biofuels Production. Environmental Management 51.2, 379-391

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Measuring Agricultural Land–Use Intensity — A Global Analysis Using a Model–Assisted Approach

As future demand for agricultural produce rises, we must develop methods to increase production and satisfy our food needs.  The conversion of land into farms is a solution, but comes with the price of habitat destruction, altered CO2 output and input, and land erosion.  A more sensible solution would be to improve production on farmlands we currently have.  Dietrich et al. (2012) investigates and compares the agricultural land–use intensities for 10 world regions and 12 crops.  The authors use the Lund–Potsdam–Jena dynamic global vegetation model with managed Land (LPJmL) to project reference yields that are compared to current observed yields.  The results show parts of Russia, Asia, and Africa having low agricultural land–use intensities, whereas Eastern U.S., Western Europe, and parts of China have high agricultural land–use intensities.  Measuring for agricultural land–use intensity differs from the more commonly used method of calculating gap yields.  In light of the author’s results and analysis, this paper shows the value in using the t-factor for measuring land-use intensity which can be more accurate than other measuring methods.—Anthony Li
Dietrich, J. P., Schmitz, C., Mueller, C., Fader, M., Lotze-Campen, H., Popp, A., Measuring agricultural land-use intensity — A global analysis using a model-assisted approach.  Ecological Modeling May 10th, 2012

In calculating land–use intensities, the authors introduce a new measure called the t–factor.  The t–factor is the ratio between actual, observable yield to a reference, calculated yield under well–defined management and technology conditions.  The t–factor is independent of the physical environment and is proportional to the agricultural land–use intensity.  The reference yield used to calculate the t–factor can be either deduced from models or statistical analysis.  In this study, the authors use the LPJmL model to project the reference yield.  The LPJmL model simulates the growth, production, and phenology of plant and functional crop types, and reports it as maximum leaf area index, scaling factor from simulated leaf-level photosynthesis to field scale, and harvesting index.  Actual yields were compiled from the Food and Agricultural Organization of the United Nations Statistics (FAOSTAT), but were first applied to the same LPJmL model in order to account for discrepancies due to bias or systematic errors.  The authors calculated t–factors for 10 global regions and 12 different crop types for 2000, and omitted any data for crops that produced less than 0.1% of the global crop production.
The authors compared variations in t–factor, homogeneity in t–factor and the t–factor itself between the regions of the world.  Europe had the highest total t–factor, as well as the highest crop–specific t–factors for wheat, millet, field peas, and rapeseed.  The Middle East and North Africa ranked lowest in total t–factors, but was closely followed by Africa despite the fact that Africa had more crops with the lowest t–factor.  Africa and Europe had the least variation in their t–factors, which contributed to their lowest and highest t–factors, respectively.  In contrast, the Pacific Organization for Economic Cooperation and Development and the Middle East and North Africa showed the strongest variations in t–factor between crops.  In terms of homogeneity in t–factors across each country, Ireland, the United Kingdom, France, Germany, and Sweden show homogeneous values at a high t–factor while Madagascar and Mozambique had homogeneous values at a low t–factor. 
The t–factor measure used in this study differs from other measures of land–use intensity by eliminating the environmental component from observed actual yields via a reference yield.  Other typical, input–oriented measures determine land–use intensity by measuring individual drivers of land–use intensity such as fertilizer use, labor use, and machinery.  Since the t–factor is independent of natural conditions, it can be used as a measure of yield differences due to human activity.  If sample region A has twice the t–factor than sample region B, then it will have twice the yield due to human activities.  The same could be said for the reverse; assuming they have the same t–factors, if the physical conditions in region A are half as good as in region B, then the yields in both regions will be equal.  While the t–factor estimates total land–use intensity which cannot be attributed to individual factors, input–oriented measures record the relevance of certain individual inputs to the attributing factors of overall land–use intensity.  The authors make the point that low agricultural land–use intensities do not necessarily mean higher yield increases in the future.  Factors such as political instability or weak governing bodies may inhibit a nation’s opportunity to improve yields.  While these results may not accurately represent yield increases in specific countries, it is still representative of global agricultural conditions as the results are similar with FAO/OECD yield growth projections.  Without taking into account political stability or effectiveness of governing body, regions such as Africa, South and Eastern Europe, Russia, South Asia, and Latin America show long-term chances for yield increases.  This paper introduces a new method, the t–factor, for measuring agricultural land–use intensity that does not take into account environmental conditions.  Because of this, the t–factor is proportional to agriculture land–use intensity and is a good measurement if we want to calculate land–use intensity solely as a result of human activity.

Recent Land Use Change in the Western Corn Belt Threatens Grasslands and Wetlands

The recent boom in the biofuel industry, in part due to incentives that promote the conversion of grassland to corn and soybean cropping, is reshaping the landscape of the US Corn Belt. Wright et al. (2013) sought to study the extent to which this land use conversion is occurring, and what its implications may mean for the environment.  The researchers used the National Agricultural Services (NASS) Cropland Data Layer (CDL) to examine the rate at which grasslands have been converted into corn/soy cultivation over five states of the Western Corn Belt: North and South Dakota, Nebraska, Minnesota, and Iowa.  The authors considered the agronomic and environmental attributes of lands on which grassland conversion was occurring, as well as the effects on nearby waterfowl nesting sites, and included these in the results as well.  The results of this study show that the rate at which land was being converted has not been seen in the US since the advent of the mechanization of US agriculture in the 1920s.  The implications of this rate are bleak as it threatens waterfowl populations, soil quality, and water resources.  The authors recommend we shift to biofuels produced from perennial feedstocks, as these fuels have desirable traits with respect to net energy and greenhouse gas balances and wildlife conservation. —Anthony Li
Wright, C. K., Wimberly, M. C., 2013. Recent land use change in the Western Corn Belt threatens grasslands and wetlands.  Proceedings of the National Academy of Sciences of the United States of America published ahead of print February 19, 2013

The authors acquired land cover data from 2006 to 2011 of the Western Corn Belt from the NASS CDL.  They selected this year range because the extent of the data recording goes back to 2006. The NASS CDL uses land cover data acquired from satellite imagery and maps agricultural land cover at a very high crop-type specificity.  Using the 2006 NASS CDL data and comparing it with the 2011 NASS CDL on a per-pixel basis allowed the researchers to observe a general grass-dominated land cover be converted into a general corn/soy cultivation land.  In order to see if the land use data derived from the NASS CDL was representative of long-term land cover change region-wide, they performed a trend analysis of grassland conversion in North Dakota and Iowa.  The analysis showed that the data were representative.  The researchers also took note of the agronomic and environmental attributes of the lands in which NASS CDL recorded data on.  Lastly, the authors examined the relationship between grassland conversion and lands protected under the Conservation Reserve Program (CRP).  The CRP “pays farmers to establish and maintain grassland cover on retired cropland in exchanged for a fixed rental payment over a fixed period,” but in recent years with the rise of corn and soybean prices as well as a projected consistently high commodity prices, more farmers have not been renewing their CRP contracts.  By examining this relationship, the authors were able to see which recently converted areas were formerly protected by the CRP, showing some insight in the farmer’s reasons for changing crop.
The results showed that across the Western Corn Belt, there was a net decline in grass-dominated land cover totaling near 530,000 ha, more than 1.3 million acres, from 2006 to 2011.  This change in land cover was concentrated in South Dakota and Iowa.  The rates at which grassland is being converted to corn/soy is comparable to the deforestation rates in Brazil, Malaysia, and Indonesia.  The authors make the comparison that the current rates of grassland conversion have not been seen in the Corn Belt since the advent of agriculture’s mechanization in the 1920’s.  Grassland conversion is also occurring dangerously close to the Prairie Pothole Region, a wetland region that acts as a climate-change refugia for North American waterfowl.  The current rate of grassland conversion threatens one of the few breeding grounds of waterfowl.  The authors found that grassland conversion was concentrated on relatively high quality lands in Minnesota and the Dakotas, suggesting that the local landowners are seeking higher rates of return by swapping to corn and soybean cultivation.  This trend has become increasingly consistent due to the emerging market of corn/soy production and its rate of return.  In Iowa, they found grassland conversion was occurring on less suitable land, reflecting the lack of high quality land for soybean/corn cultivation.  Similar to Iowa, Nebraska was also shown to have used unsuitable land for crop production, suggesting that both these states will have to acquire more resource-intensive irrigation practices to sustain the soy/corn crops.  The authors also predicted that fewer landowners will be renewing their CRP contracts as the higher rates of return for soybean/corn cultivation is more economically viable.
While this paper shows the rate at which the biofuel industry has grown, it also shows the daunting implications for such a growth. Grassland conversion into corn/soy production is characterized by high erosion risk and vulnerability to drought.  This grassland conversion also threatens waterfowl populations, as the soy/corn fields encroach upon diminishing waterfowl breeding sites.  The grassland conversion also effects the soil’s carbon sequestration ability.  The authors predict that with the reductions in soil sequestration caused by grassland conversion, “more than three decades of biofuel substitution” will be required to counteract this.  In the face of all this the researchers suggest an alternative, saying that biofuels derived from perennial feedstocks are more efficient with respect to net energy and greenhouse gas balances as well as wildlife conservation.

Closing the Gap: Global Potential for Increasing Biofuel Production Through Agricultural Intensification

In the past couple of decades, the global agricultural industry has seen a massive boom, in part due to a combination of fertilizers, pesticides, herbicides, smart management techniques, mechanization, irrigation, and optimized seed varieties and genetic engineering.  This jump in agriculture not only provides the opportunity to feed our growing population, but to also create ethanol and biodiesel to meet our energy demands.  Johnston et al. (2011) looked at the magnitude and spatial variation of new agricultural production potential from closing of ‘yield gaps’ for 20 major ethanol and biodiesel crops.  By using data sets of annual crop yields to determine the amount of additional biofuel produced from obtaining yield gaps up to the global median yield, the researchers deduced that approximately 112.5 billion liters of ethanol and 8.5 billion liters of biodiesel could be made.  While this shows an optimistic future for energy security, it also has a profound effect on policymakers and how individuals will determine goals of reaching a level of biofuel use.  —Anthony Li
Johnston M., Licker R., Foley J., Holloway T., Mueller N. D., Barford C., Kucharik C. 2011. Closing the gap: global potential for increasing biofuel production through agricultural intensification. Environmental Research Letters 6, 034028

The authors of this paper investigated 20 common biofuel and biodiesel crops, some notable ones include maize, rice, sugarcane and wheat for biofuel, or ethanol, and soybean, rapeseed, and oil palm for biodiesel crops.  The researchers obtained the M3 data set of global farming yields for these 20 crops and organized the data based on region.  With information on the average global yields of crops, the authors were able to calculate the yield gaps, which they defined for this study as the “difference between current agricultural yields and future potential based on climatic and biophysical characteristics of the growing region.”  They calculated the potential yields of biodiesel and ethanol if yield gaps of these crops were closed to multiple degrees, such as the global median or the 90thpercentile gap of what is completely attainable.  In order to observe the effects of unequal distributions of irrigation infrastructure and sustainable water resources on crop yields, the researchers re-ran their analysis with irrigated areas excluded.  In order to get a rough idea of what was needed to increase crop yield, the authors calculated the growing degree days for each crop, which is a measure of heat to predict plant development rates.
The researchers found that increasing yield gaps to the median global yield would result in 112.5 billion additional liters of ethanol and 8.5 billion liters of ethanol, while obtaining the 90th percentile gap would result in 450 billion liters of additional ethanol and 33 billion liters of biodiesel.  While the new tonnage varied considerably between biodiesel and ethanol, the overall percentage increase between the two were roughly equal, ranging from 10%–17%.  The majority of ethanol potential identified was attributable to maize, wheat, and rice crops, while the majority of biodiesel potential was attributable to soybean, rapeseed, and oil palm.  Biodiesel fuel production was generally more evenly distributed amongst its constituent crops, whereas ethanol fuel production was incredibly uneven between the crops.
The implications of this study in energy security are obvious, but they also provide a benefit to policymakers or anyone setting goals for biofuel use.  The research performed here shows policymakers how much additional biofuel we can expect from closing various yield gaps to different degrees, allowing them to make more accurate goals.  For example, The Renewable Fuel Standard Program Final Rule of the 2007 Energy Independence and Security Act made a goal for the US to blend 36 billion gallons of biomass-based fuels by 2022.  As ambitious as this goal was, this study showed that even if all the countries were to increase their biofuel crop yields to only the median level, there would still not be enough fuel to meet this goal.  This study is also useful in that it shows the biofuel and biodiesel distribution based on specific crop.  For ethanol, a very notable crop for fuel production was sugarcane.  While this may not mean that sugarcane produces the most ethanol of any other crop per mass, if we can identify whichever crop produces more fuel than others, we can focus our biofuel industry to take advantage of these specific crops.
In the face of our energy and food crisis, our nations should begin looking towards agriculture for potential solutions.  Johnston et al.’s study shows how much additional biofuel can be produced by closing various yield gap levels per crop.  This information will prove useful to governments seeking to implement goals of reaching certain levels of biofuel use and individuals such as farmers who want to capitalize on the most biofuel yielding crop.

Engineering Crops to Use Alternate Forms of Phosphorous May Slow Phosphorous Depletion and Provide Weed Control

The limited stores of phosphorous (P) here on earth have been a concern for the agricultural industry for many years. Consequently, a great deal of research is being done to find ways to use P more efficiently. One proposed system for managing P use in agricultural crops is to genetically engineer them to use a form of P that weeds and common bacteria cannot consume, or even find poisonous (López-Arredondo and Herrera-Estrella 2012). Not only would such a mechanism ensure that almost all P applied to agricultural crops is used by the desired crop, but also noxious weeds would be stunted and potentially killed by the same chemical. Numerous benefits may be reaped if these modified crops can be implemented, including reduced fertilizer and pesticide use, lower food prices, and a smaller chemical load contaminating aquatic ecosystems.—Chad Redman
            López-Arredondo, D. L., Herrera-Estrella, L., 2012. Engineering Phosphorus Metabolism in Plants to Produce a Dual Fertilization and Weed Control System. Nature Biotechnology 30, 889–895.

            López-Arredondo and Herrera-Estrella set out to genetically modify plants, giving them the capability of using a form of P that most plants are incapable to metabolizing. For now, both crop plants and weeds use a form of P called orthophosphate (PO4–3) as an essential nutrient. However, some bacteria digest phosphite (PO3–3) and produce orthophosphate. Previous studies have identified a gene called ptxD as the reason they can utilize phosphite, and López-Arredondo and Herrera-Estrella proceeded to implant this gene in Arabidopsis plants, a model organism commonly known as mouse-ear cress. After producing these transgenic plants (plants with the ptxD gene engineered into them), the researchers attempted to grow them, along with control wild-type plants, in a medium completely lacking orthophosphate but supplemented with phosphite. They were interested in the height each type of seedling achieved over a few days, and how the root systems developed over a longer time window.
            Next, López-Arredondo and Herrera-Estrella tested the growth ability of these transgenic plants against wild-type plants in greenhouse conditions. That is, in a greenhouse, both transgenic and wild-type plants were grown in sandy soils containing either orthophosphate or phosphite as their sole source of P. After a period of time, the biomass and root length of each plant in each condition were measured.
            Of course, López-Arredondo and Herrera-Estrella were interested in the effectiveness of the ptxD gene in more than just mouse-ear cress. As a further step, they produced transgenic tobacco plants and grew them alongside wild-type plants in unfertilized, orthophosphate fertilized, and phosphite fertilized conditions. Importantly, all of these different soil types were sterilized so as to control for the effects of bacteria. Furthermore, the researchers measured the rate of photosynthesis of wild-type and transgenic tobacco plants under similar fertilization conditions. Photosynthesis rate is relevant because plants use P in their respiration processes.
            As any genetically modified food crop inevitably raises health questions, López-Arredondo and Herrera-Estrella preformed measurements to detect the presence of phosphite in the leaves, flowers and fruits of transgenic plants. This was merely a precaution, as the US Food and Drug Administration has declared phosphite safe for animal consumption.
            The next step in this procedure was to test the ptxDtransgenic plants in more realistic soil taken from active farm ground. This soil varied most from previous experiments because it contained all the microorganisms normally found in soil. Both alkali and acidic soils were used, taken from farms in Mexico, and transgenic and wild-type mouse-ear cress was raised using varied concentrations of both orthophosphate and phosphite fertilizer.
            Finally, López-Arredondo and Herrera-Estrella investigated the viability of phosphite as a weed control mechanism. They tested two common weeds, false brome grass and tall morning-glory, to determine if these plants were capable of utilizing phosphite as a source of P. Upon discovering that they were not, the researchers used these plants in a greenhouse competition test against transgenic plants. The plants were grown in soil that was directly extracted from an active farm, and again various fertilizer applications were tried. Bear in mind that both the weeds and the crop were raised in the same planter in this trial. Fertilizer conditions were unfertilized, orthophosphate fertilized, and phosphite fertilized. The same procedure was conducted with transgenic mouse-ear cress and transgenic tobacco.
            The many results of this study were all in line with the notion that ptxD transgenic crops may be highly beneficial if used on a large scale. The initial test to determine if transgenic plants would grow normally in the absence of orthophosphate proved successful, with the wild-type plants completely failing in the same medium. This result set up the rest of the López-Arredondo and Herrera-Estrella experiments, showing that their transgenic plants had acquired the ability to metabolize phosphite. Ensuing greenhouse tests had similar results, with transgenic and wild-type plants responding similarly to orthophosphate fertilization and no fertilization, but with the transgenic plants developing normally with phosphite as the sole source of P and wild-type plants completely dying out. Identical results were recorded for tobacco plants as well. These data are more strong evidence that genetically engineered crops with the ptxD gene are well suited to replace traditional crops using either orthophosphate or phosphite as a source of P. Moreover, there was no detectable amount of phosphite on the leaves, fruit, or flowers of the tobacco transgenic plants.
            Testing of transgenic plants is non-sterile soils produced results that were in line with previous greenhouse testing. Transgenic plants matched the growth of wild-type plants over many different concentrations of orthophosphate fertilizer while demonstrating this same phenotype growing in phosphite fertilizer. Impressively, equal biomass and root length was achieved with a substantially lower concentration of phosphite fertilizer as compared to orthophosphate fertilizer.
            Lastly, the greenhouse competition tests between crops and weeds ended with crops being outstripped when the planter was fertilized with orthophosphate, but transgenic crops completely smothered out all tested weed forms when treated with phosphite. These results suggest that phosphite could not only conserve the finite supply of P, but also reduce the necessity of additional herbicide chemicals given its disruptive effects on most wild-type plants.

The Effects of Solar Radiation Management Geoengineering on Global Crop Yields

Climate change studies have demonstrated an increase in global mean temperature. This increase in temperature has detrimental affects for both the environment and human health. It has also been predicted that climate change may have adverse effects on crop yields. For this reason, solar radiation management (SRM) has been discussed as a method to mitigate climate change and global warming. While the effects of SRM could combat climate change, it could also threaten food and water supply for billions of people. Pongratz et al. (2012) use climate models to simulate the effects of a geoengineered climate on global crop yields. The authors found that crop yields increase in the model with SRM in a high-CO2 climate. They reason that the reduction of temperature stresses while maintaining the benefits of CO2 fertilization account for this result. However, they conclude that even so, with the many potential adverse consequences of geoengineering, the best way to protect crop yields is to reduce greenhouse gas emission. —Michela Isono
Pongratz, J., Lobell, D., Cao, L., Caldeira, K., 2012. Crop Yields in a Geoengineered Climate. Natural Climate Change, 10.1038.

            Global warming has become a main topic of focus within the scientific community. To counteract this effect, geoengineering techniques have been discussed as a mitigation method. Specifically, SRM has been proposed because of its ability to deflect sunlight away from the planet and reduce the amount of solar insolation absorbed. However, SRM also affects precipitation rates. For this reason, crop yields could be adversely affected. Pongratz et al. studied the impacts of changes in temperature, precipitation and the atmospheric CO2 concentration on crop yields.
            Methods: Pongratz et al. combined climate-model simulations with models of crop-yield responses to climate changes. Three global climate simulations were used: a climate to represent today’s environment with an atmospheric concentration of CO2 of ~400ppm (control); a climate with twice the amount of CO2 (2 x CO2); and a climate with twice the amount of CO2 andsulphate aerosols to stabilize global mean temperatures at control levels (SRM). The models are used to isolate the effects of a high-CO2 environment with and without SRM compared with the present-day climate. The crops used are: wheat, maize, and rice. These crops were chosen because they provide about half of the calories consumed by humans and a large fraction of calories consumed by livestock.
            Results and Discussion: When comparing results from 2 x CO2 and SRM with control for all three crops, 2 x CO2 showed much lower percent yield and production than SRM, where 2 x CO2 also showed a negative percentage yield and production for maize when compared to control (meaning the control model produced more yield and had a greater production). This result was due to the detrimental influences of climate change and the beneficial influences of CO2 fertilization. Warming climate changes at most latitudes have negatively effect maize and wheat yields. In contrast, the increased temperatures may benefit rice at high latitudes by enabling a longer growing season. The yield decreases at low latitudes are a result of heat and drought. CO2 fertilization also greatly compensated for yield losses of maize, and yield increases of wheat and rice.
            In the SRM compared to the control, the yields and production increased for all three crops across all latitudes. This is due to the effects of CO2 fertilization. However, there were few small negative impacts on yields across some latitudes in the SRM, but these impacts were smaller than in the 2 x CO2 case.
In the SRM compared to 2 x CO2 case, a significant loss in yield was only shown for rice growing at high altitudes. The production of maize, wheat and rice was higher under SRM than 2 x CO2overall. Therefore, the simulations demonstrated that SRM would create an increase in global yields compared to the global yields in a 2 x CO2climate.
Even with a stabilized temperature, specific regions may experience different changes in their yield and crop productivity due to climate changes. The authors concluded that their simulations counter concerns about SRM threatening food security in large regions, but small regions may also experience greater changes in yields. This may endanger local food security and shift market shares and producer ranking.
In conclusion, the authors did not final substantial reductions in yields by SRM compared to the control. Warming, rather than precipitation change, caused most of the climate-induced yield reductions. When SRM was applied in the high-CO2 climate, the yields and production of maize, wheat and rice increased at the global mean temperature and across most latitudes. This phenomenon represents stabilization in temperature, reduced CO2 levels, and beneficial effects of CO2 fertilization on plant productivity.
Recommendations: Because the effects of climate change on a global scale is better understood than on a regional scale, the authors stated that more research is needed to better understand the effect of SRM on a smaller geographical scale. The authors do not believe that SRM can maintain the economic status quo because market shares of agricultural output will change with climate changes. Therefore,an analysis of the environmental and socioeconomic consequences of SRM is needed as well. Lastly, the authors stated that further research is needed to understand the anticipated and unanticipated effects of SRM.