• Authors:
    • Sinistore,J. C.
    • Reinemann,D. J.
    • Izaurralde,R. C.
    • Cronin,K. R.
    • Meier,P. J.
    • Runge,T. M.
    • Zhang,X.
  • Source: BioEnergy Research
  • Volume: 8
  • Issue: 3
  • Year: 2015
  • Summary: Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combined with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products. © 2015, The Author(s).
  • Authors:
    • Wang Zhan-biao
    • Wen Xin-ya
    • Zhang Hai-lin
    • Lu Xiao-hong
    • Chen Fu
  • Source: Journal of Integrative Agriculture
  • Volume: 14
  • Issue: 8
  • Year: 2015
  • Summary: Excessive use of N fertilizer in intensive agriculture can increase crop yield and at the same time cause high carbon (C) emissions. This study was conducted to determine optimized N fertilizer application for high grain yield and lower C emissions in summer corn (Zea mays L.). Afield experiment, including 0 (NO), 75(N75), 150 (N150), 225 (N225), and 300 (N300) kg N ha(-1) treatments, was carried out during 2010-2012 in the North China Plain (NCP). The results showed that grain yield, input energy, greenhouse gas (GHG) emissions, and carbon footprint (CF) were all increased with the increase of N rate, except net energy yield (NEY). The treatment of N225 had the highest grain yield (10364.7 kg ha(-1)) and NEY (6.8%), but the CF (0.25) was lower than that of N300, which indicates that a rate of 225 kg N ha(-1) can be optimal for summer corn in NCR Comparing GHG emision compontents, N fertilizer (0-51.1%) was the highest and followed by electricity for irrigation (19.73-49.35%). We conclude that optimazing N fertilizer application rate and reducing electricity for irrigation are the two key measures to increase crop yield, improve energy efficiency and decrease GHG emissions in corn production.
  • Authors:
    • Watson,James
    • Challinor,Andrew J.
    • Fricker,Thomas E.
    • Ferro,Christopher A. T.
  • Source: Climatic Change
  • Volume: 132
  • Issue: 1
  • Year: 2015
  • Summary: Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.
  • Authors:
    • Winchester,N.
    • Reilly,J. M.
  • Source: Energy Economics
  • Volume: 51
  • Year: 2015
  • Summary: What are the feasibility, costs, and environmental implications of large-scale bioenegry? We investigate this question by developing a detailed representation of bioenergy in a global economy-wide model. We develop a scenario with a global carbon dioxide price, applied to all anthropogenic emissions except those from land use change, that rises from $25 per metric ton in 2015 to $99 in 2050. This creates market conditions favorable to biomass energy, resulting in global non-traditional bioenergy production of ~. 150 exajoules (EJ) in 2050. By comparison, in 2010, global energy production was primarily from coal (138 EJ), oil (171 EJ), and gas (106 EJ). With this policy, 2050 emissions are 42% less in our Base Policy case than our Reference case, although extending the scope of the carbon price to include emissions from land use change would reduce 2050 emissions by 52% relative to the same baseline. Our results from various policy scenarios show that lignocellulosic (LC) ethanol may become the major form of bioenergy, if its production costs fall by amounts predicted in a recent survey and ethanol blending constraints disappear by 2030; however, if its costs remain higher than expected or the ethanol blend wall continues to bind, bioelectricity and bioheat may prevail. Higher LC ethanol costs may also result in the expanded production of first-generation biofuels (ethanol from sugarcane and corn) so that they remain in the fuel mix through 2050. Deforestation occurs if emissions from land use change are not priced, although the availability of biomass residues and improvements in crop yields and conversion efficiencies mitigate pressure on land markets. As regions are linked via international agricultural markets, irrespective of the location of bioenergy production, natural forest decreases are largest in regions with the lowest barriers to deforestation. In 2050, the combination of carbon price and bioenergy production increases food prices by 3.2%-5.2%, with bioenergy accounting for 1.3%-3.5%. © 2015.
  • Authors:
    • Mu, J.
    • Guo, J.
    • Zhao, J.
  • Source: Science Article
  • Volume: 207
  • Year: 2015
  • Summary: Understanding regional relationships between climate change and crop yield will help with making the strategic decisions for food security in China under climate change. In this study, the contributions of climate change to spring maize yield over the past three decades in Northeast China were decoupled based on the daily climate variables gathered from 68 meteorological stations and detailed observed data of spring maize from 55 agricultural meteorological experimental stations for the period 1978-2010 in Northeast China, analyzed with a linear statistical model. Then, the key climatic factors limiting the climate-induced yield of spring maize were identified. The agro-climatic similarity theory was applied. Finally, the relationships between the climatic variables and the climate-induced yield of spring maize were further explored by provinces. The results show that: from 1978 to 2010, the observed yields of spring maize in Northeast China increased markedly, with inter-annual fluctuations. Compared with the methods of moving average and harmonic average, Logistic regression optimally decoupled the climate-induced yield of spring maize. The key meteorological factors limiting the climate-induced yield were temperature, precipitation and sunshine, varying in the different regions. In Heilongjiang Province, the climate-induced yields of spring maize were mainly affected by maximum temperatures in August and precipitation in June. In Jilin Province, climate-induced yield was closely related to precipitation during daily the average temperature stably passing 10°C (≥10°C). In Liaoning Province, when the maximum temperature was high and the sunshine was abundant in June, the climate-induced yield of spring maize significantly increased. Finally, the regression models between climatic variables and climate-induced yield of spring maize in 11 representative zones in Northeast China also established geographical differences.
  • Authors:
    • Bosco,S.
    • Volpi,I.
    • o Di Nasso,N. N.
    • Triana,F.
    • Roncucci,N.
    • Tozzini,C.
    • Villani,R.
    • Laville,P.
    • Neri,S.
    • Mattei,F.
    • Virgili,G.
    • Nuvoli,S.
    • Fabbrini,L.
    • Bonari,E.
  • Source: Italian Journal of Agronomy
  • Volume: 10
  • Issue: 3
  • Year: 2015
  • Summary: Agricultural activities are co-responsible for the emission of the most important greenhouse gases: carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Development of methodologies to improve monitoring techniques for N2O are still needful. The LIFE+IPNOA project aims to improve the emissions monitoring of nitrous oxide from agricultural soils and to identify the agricultural practices that can limit N2O production. In order to achieve this objective, both a mobile and a stationary instrument were developed and validated. Several experimental field trials were set up in two different sites investigating the most representative crops of Tuscany (Central Italy), namely durum wheat, maize, sunflower, tomato and faba bean. The field trials were realized in order to test the effect on N2O emissions of key factors: tillage intensity, nitrogen fertiliser rate and irrigation. The field trial on durum wheat was set up in 2013 to test the effect of tillage intensity (minimum and conventional tillage) and nitrogen fertilisation rate (0, 110, 170 kg N ha-1) on soil N2O flux. Monitoring was carried out using the IPNOA mobile prototype. Preliminary results on N2O emissions for the durum wheat growing season showed that mean daily N2O fluxes ranged from –0.13 to 6.43 mg m-2 day-1 and cumulative N2O-N emissions over the period ranged from 827 to 2340 g N2O-N ha-1. Tillage did not affect N2O flux while increasing nitrogen fertilisation rate resulted to significantly increase N2O emissions. The IPNOA mobile prototype performed well during this first year of monitoring, allowing to catch both very low fluxes and peaks on N2O emissions after nitrogen supply, showing a good suitability to the field conditions. © S. Bosco et al., 2015 Licensee PAGEPress, Italy.
  • Authors:
    • Jarchow, M.
    • Horton, R.
    • Pederson, C. H.
    • Helmers, M. J.
    • Zhou, X. B.
    • Daigh, A. L. M.
    • Liebman, M.
  • Source: Journal of Environmental Quality
  • Volume: 44
  • Issue: 5
  • Year: 2015
  • Summary: We compare subsurface-drainage NO 3-N and total reactive phosphorus (TRP) concentrations and yields of select bioenergy cropping systems and their rotational phases. Cropping systems evaluated were grain-harvested corn-soybean rotations, grain- and stover-harvested continuous corn systems with and without a cover crop, and annually harvested reconstructed prairies with and without the addition of N fertilizer in an Iowa field. Drainage was monitored when soils were unfrozen during 2010 through 2013. The corn-soybean rotations without residue removal and continuous corn with residue removal produced similar mean annual flow-weighted NO 3-N concentrations, ranging from 6 to 18.5 mg N L -1 during the 4-yr study. In contrast, continuous corn with residue removal and with a cover crop had significantly lower NO 3-N concentrations of 5.6 mg N L -1 when mean annual flow-weighted values were averaged across the 4 yr. Prairies systems with or without N fertilization produced significantly lower concentrations below <1 mg NO 3-N L -1 than all the row crop systems throughout the study. Mean annual flow-weighted TRP concentrations and annual yields were generally low, with values <0.04 mg TRP L -1 and <0.14 kg TRP ha -1, and were not significantly affected by any cropping systems or their rotational phases. Bioenergy-based prairies with or without N fertilization and continuous corn with stover removal and a cover crop have the potential to supply bioenergy feedstocks while minimizing NO 3-N losses to drainage waters. However, subsurface drainage TRP concentrations and yields in bioenergy systems will need further evaluation in areas prone to higher levels of P losses.
  • Authors:
    • Gao,Wei
    • Yang,Jun
    • Ren,Shun-rong
    • Liu Hailong
  • Source: Nutrient Cycling in Agroecosystems
  • Volume: 103
  • Issue: 1
  • Year: 2015
  • Summary: Evaluating the effects of management practices on the soil organic carbon (SOC), total nitrogen (TN) and grain yields would be valuable to explain field-level variability in crop production. A 33-year field experiment on the fluvo-aquic soil of North China with six treatments in a wheat (Triticum aestivium L.)-maize (Zea mays L.) rotation was evaluated. The six treatments were: non-fertilization (CK), nitrogen (N), nitrogen-phosphorus fertilization (NP), nitrogen-phosphorus-potassium fertilization (NPK), manure and nitrogen fertilization (NM), and straw returned with nitrogen fertilizers (NS). The results showed that the content of SOC and TN significantly increased in NM treatment. Application of inorganic fertilizers had small influence on SOC, but SOC and TN increased significantly in NM treatment over the long-term experiment. Compared to control, grain yield of wheat and maize increased two times under all treatments. The highest grain yield was detected in NM and NPK treatments. However, wheat yield was not significantly different (P > 0.05) between control and N treatment. Grain yields were more than doubled under fertilization for both wheat and maize, with the highest yield under the NM and NPK treatments and the lowest under CK treatment for maize and N treatment for wheat. The NP fertilization had little effect on maize yield in long-term, suggesting that potassium was not the primary limiting nutrients in the study site. Statistical analysis indicated that maize yield was significantly correlated with SOC and TN, and wheat yield was significantly correlated with SOC only. However, the relationships were stronger with TN (r = 0.26-0.42) than SOC (r = 0.12-0.37), indicating the importance of maintaining TN in agricultural soils. There was a strong positive linear correlation between carbon sequestered and carbon input (r = 0.828, P < 0.01) in the study site, indicating that the conversion rate of carbon input to SOC was 8.5 %. SOC did not reach the saturation in fluvo-aquic soil and have the potential to sequester more carbon.
  • Authors:
    • Hua,Keke
    • Zhu,Bo
    • Wang,Xiaoguo
  • Source: Nutrient Cycling in Agroecosystems
  • Volume: 103
  • Issue: 1
  • Year: 2015
  • Summary: Soil carbon dioxide (CO2) and methane (CH4) emissions, as well as runoff and leaching are major pathways of soil organic carbon (SOC) loss, which affect SOC sequestration in croplands. However, fluxes and relationships of the four pathways are still poorly understood. Static chamber-GC techniques were used to measure soil heterotrophic respiration rate and CH4 emission flux on hillslope upland of Regosol soil in Southwest China under traditional mineral fertilizer treatment from 2010 to 2012. Synchronously, SOC loss flux via overland flow, leaching and sediment was measured using free-drained lysimeters (8 m x 4 m). Average annual cumulative soil CO2 emission and CH4 uptake fluxes were 462.8 +/- A 52.2 and -1.1 +/- A 0.16 g cm(-2). Average annual cumulative dissolved organic carbon (DOC) loss fluxes via overland flow and leaching were 0.16 +/- A 0.03 and 0.92 +/- A 0.08 g cm(-2), respectively and organic C loss via sediment was 2.2 +/- A 0.3 g cm(-2). Relationship between DOC loss fluxes and soil heterotrophic respiration rates under natural rainfall events could be described by a significant exponential decay function (R = -0.63, P < 0.01). Moreover, a significantly negative correlation was also found between DOC loss flux and soil DOC content in topsoil at 15 cm depth (R = -0.75, P < 0.05). In conclusion, DOC loss decreases soil DOC content and is an underrated negative regulating factor of soil CO2 emission, especially in the regions where high DOC losses occur.
  • Authors:
    • Kambauwa,Gertrude
    • Mlamba,James
    • Delgado,Jorge A.
    • Kabambe,Vernon
  • Source: Journal of Soil and Water Conservation
  • Volume: 70
  • Issue: 5
  • Year: 2015