SIMULATION OF CLIMATE CHANGE IMPACT ON WHEAT PRODUCTION IN THE TIARET REGION OF ALGERIA USING THE DSSAT MODEL

It is now commonly accepted that climate changes is expected to have important effects on diverse economic sectors. Agricultural sector is particularly exposed to changes with climate variability and change due to its influence on production. Predicting the potential effects of climate change on crop yields requires a model witch simulate the crop respond to weather variation. Crop models have been used extensively to predict yield response to various SRES (Special Report Emission Scenarios) scenarios of climate change. The main objective of this study is the use of DSSAT model to simulate and to estimate wheat yield prediction under two climate change scenarios (A2 and B1) in the Tiaret region for adaptation measures and mitigation. The simulation results obtained from this study revealed that the use of the model DSSAT provides an efficient method for evaluating impact of changing climate on wheat production. Adaptation measures to mitigate the potential impact of climate change included possible changes in sowing dates and genotype selection

Life cycle analysis for the cultivation and combustion of miscanthus for biofuel compared with natural gas

As negative environmental and economic impacts of fossil fuels have escalated, so has the importance of renewable bioenergy crops whose feedstocks are noncompetitive with food supplies. Compared with fossil fuels, use of lignocellulosic feedstocks offers potential for greenhouse gas reduction and highly positive net energy returns because of low input demand and high yields per unit of land area, thus making them advantageous for the emerging biofuel industry. The aim of this study was to simulate environmental impacts of producing a biofuel grass for combustion use based on the inventory of inputs and their effects on eutrophication of surface waters; acidification of land and water; photochemical ozone-creation potential (i.e. smog); global atmospheric warming; and nonrenewable resource depletion (mainly fossil fuels). Hybrid miscanthus (Miscanthus x giganteus, or giant miscanthus), a perennial C4 grass originating from East Asia, was compared with natural gas by using a life-cycle analysis model for biomass production in France. The analysis showed a trade-off between natural gas and miscanthus. The latter had a lower global-warming potential and consumed less primary nonrenewable energy but produced more emissions that promote acidification and eutrophication than did natural gas

Using a crop model to account for the effects of local factors on the LCA of sugar beet ethanol in Picardy region, France

CT1 ; CT3 ; EnjS1 ; EnjS4 ; Base de données AgroclimInternational audienceThe results of published Life Cycle Assessments (LCAs) of biofuels are characterized by a large variability, arising from the diversity of both biofuel chains and the methodologies used to estimate inventory data. Here, we suggest that the best option to maximize the accuracy of biofuel LCA is to produce local results taking into account the local soil, climatic and agricultural management factors. Methods We focused on a case study involving the production of first-generation ethanol from sugar beet in the Picardy region in Northern France. To account for local factors, we first defined three climatic patterns according to rainfall from a 20-year series of weather data. We subsequently defined two crop rotations with sugar beet as a break crop, corresponding to current practice and an optimized management scenario, respectively. The six combinations of climate types and rotations were run with the process-based model CERES-EGC to estimate crop yields and environmental emissions. We completed the data inventory and compiled the impact assessments using Simapro v.7.1 and Ecoinvent database v2.0. Results Overall, sugar beet ethanol had lower impacts than gasoline for the abiotic depletion, global warming, ozone layer depletion and photochemical oxidation categories. In particular, it emitted between 28 % and 42 % less greenhouse gases than gasoline. Conversely, sugar beet ethanol had higher impacts than gasoline for acidification and eutrophication due to losses of reactive nitrogen in the arable field. Thus, LCA results were highly sensitive to changes in local conditions and management factors. As a result, an average impact figures for a given biofuel chain at regional or national scales may only be indicative within a large uncertainty band. Conclusions Although the crop model made it possible to take local factors into account in the life-cycle inventory, best management practices that achieved high yields while reducing environmental impacts could not be identified. Further modelling developments are necessary to better account for the effects of management practices, in particular regarding the benefits of fertiliser incorporation into the topsoil in terms of nitrogen losses abatement. Supplementary data and modelling developments also are needed to better estimate the emissions of pesticides and heavy metals in the field

Biofuels, greenhouse gases and climate change. A review

International audienceBiofuels are fuels produced from biomass, mostly in liquid form, within a time frame sufficiently short to consider that their feedstock (biomass) can be renewed, contrarily to fossil fuels. This paper reviews the current and future biofuel technologies, and their development impacts (including on the climate) within given policy and economic frameworks. Current technologies make it possible to provide first generation biodiesel, ethanol or biogas to the transport sector to be blended with fossil fuels. Still under-development 2nd generation biofuels from lignocellulose should be available on the market by 2020. Research is active on the improvement of their conversion efficiency. A ten-fold increase compared with current cost-effective capacities would make them highly competitive. Within bioenergy policies, emphasis has been put on biofuels for transportation as this sector is fast-growing and represents a major source of anthropogenic greenhouse gas emissions. Compared with fossil fuels, biofuel combustion can emit less greenhouse gases throughout their life cycle, considering that part of the emitted CO2 returns to the atmosphere where it was fixed from by photosynthesis in the first place. Life cycle assessment (LCA) is commonly used to assess the potential environmental impacts of biofuel chains, notably the impact on global warming. This tool, whose holistic nature is fundamental to avoid pollution trade-offs, is a standardised methodology that should make comparisons between biofuel and fossil fuel chains objective and thorough. However, it is a complex and time-consuming process, which requires lots of data, and whose methodology is still lacking harmonisation. Hence the life-cycle performances of biofuel chains vary widely in the literature. Furthermore, LCA is a site- and timeindependent tool that cannot take into account the spatial and temporal dimensions of emissions, and can hardly serve as a decision-making tool either at local or regional levels. Focusing on greenhouse gases, emission factors used in LCAs give a rough estimate of the potential average emissions on a national level. However, they do not take into account the types of crop, soil or management practices, for instance. Modelling the impact of local factors on the determinism of greenhouse gas emissions can provide better estimates for LCA on the local level, which would be the relevant scale and degree of reliability for decision-making purposes. Nevertheless, a deeper understanding of the processes involved, most notably N2O emissions, is still needed to definitely improve the accuracy of LCA. Perennial crops are a promising option for biofuels, due to their rapid and efficient use of nitrogen, and their limited farming operations. However, the main overall limiting factor to biofuel development will ultimately be land availability. Given the available land areas, population growth rate and consumption behaviours, it would be possible to reach by 2030 a global 10% biofuel share in the transport sector, contributing to lower global greenhouse gas emissions by up to 1 GtCO2 eq.year−1 (IEA, 2006), provided that harmonised policies ensure that sustainability criteria for the production systems are respected worldwide. Furthermore, policies should also be more integrative across sectors, so that changes in energy efficiency, the automotive sector and global consumption patterns converge towards drastic reduction of the pressure on resources. Indeed, neither biofuels nor other energy source or carriers are likely to mitigate the impacts of anthropogenic pressure on resources in a range that would compensate for this pressure growth. Hence, the first step is to reduce this pressure by starting from the variable that drives it up, i.e. anthropic consumptions

Environmental assessment of biofuel pathways in Ile de France based on ecosystem modelling, including land-use change effects

International audienceThe greenhouse gas (GHG) balance of biofuels largely hinges on the magnitude of nitrous oxide (N2O) emissions from arable soils during feedstock production, which are highly variable. Here, used an agro-ecosystem model to generate these emissions at a high resolution over the Ile-de-France region in Northern France, for a range of feedstocks. The emissions were input to a life-cycle assessment of candidate biofuel pathways: bioethanol from wheat and sugar-beet, biodiesel from oilseed rape, and ethanol from miscanthus. Compared to the widely-used methodology based on fixed emission factors, ecosystem modelling lead to 55% to 70% lower estimates for N2O emissions, emphasizing the importance of regional factors. The life-cycle GHG emissions of 1st generation biofuels were 50% to 70% lower than fossile-based equivalents, and 85% lower for cellulosic ethanol. Indirect land-use change effects negated these savings for bio-diesel and wheat ethanol, but were offset by direct effects for cellulosic ethanol

29 % N2O emission reduction from a modelled low-greenhouse gas cropping system during 2009-2011

Atmospheric concentration of nitrous oxide (N2O), a greenhouse gas (GHG), is rising largely due to agriculture. At the plot scale, N2O emissions from crops are known to be controlled by local agricultural practices such as fertilisation, tillage and residue management. However, knowledge of greenhouse gas emissions at the scale of the cropping system is scarce, notably because N2O monitoring is time consuming. Strategies to reduce impact of farming on climate should therefore be sought at the cropping system level. Agro-ecosystem models are simple alternative means to estimate N2O emissions. Here, we combined ecosystem modelling and field measurements to assess the effect of agronomic management on N2O emissions. The model was tested with series of daily to monthly N2O emission data. It was then used to evaluate the N2O abatement potential of a low-emission system designed to halve greenhouse gas emissions in comparison with a system with high productivity and environmental performance. We found a 29 % N2O abatement potential for the low-emission system compared with the high-productivity system. Among N2O abatement options, reduction in mineral fertiliser inputs was the most effective

Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture

International audienceAgricultural soils are a major source of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG). Because N2O emissions strongly depend on soil type, climate, and crop management, their inventory requires the combination of biophysical and economic modeling, to simulate farmers' behavior. Here, we coupled a biophysical soil-crop model, CERES-EGS, with an economic farm type supply model, AROPAj, at the regional scale in northern France. Response curves of N2O emissions to fertilizer nitrogen (Nf) inputs were generated with CERES-EGC, and linearized to obtain emission factors. The latter ranged from 0.001 to 0.0225 kg N2O-N kg-1 Nf, depending on soil and crop type, compared to the fixed 0.0125 value of the IPCC guidelines. The modeled emission factors were fed into the economic model AROPAj which relates farm-level GHG emissions to production factors. This resulted in a N2O efflux 20% lower than with the default IPCC method. The costs of abating GHG emissions from agriculture were calculated using a first-best tax on GHG emissions, and a second-best tax on their presumed factors (livestock size and fertilizer inputs). The first-best taxation was relatively efficient, achieving an 8\% reduction with a tax of 11 euro/t-CO2-equivalent, compared to 68 euro/t-CO2eq for the same target with the second-best scheme

Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture

Agricultural soils are a major source of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG). Because N2O emissions strongly depend on soil type, climate, and crop management, their inventory requires the combination of biophysical and economic modeling, to simulate farmers' behavior. Here, we coupled a biophysical soil-crop model, CERES-EGS, with an economic farm type supply model, AROPAj, at the regional scale in northern France. Response curves of N2O emissions to fertilizer nitrogen (Nf) inputs were generated with CERES-EGC, and linearized to obtain emission factors. The latter ranged from 0.001 to 0.0225 kg N2O-N kg-1 Nf, depending on soil and crop type, compared to the fixed 0.0125 value of the IPCC guidelines. The modeled emission factors were fed into the economic model AROPAj which relates farm-level GHG emissions to production factors. This resulted in a N2O efflux 20% lower than with the default IPCC method. The costs of abating GHG emissions from agriculture were calculated using a first-best tax on GHG emissions, and a second-best tax on their presumed factors (livestock size and fertilizer inputs). The first-best taxation was relatively efficient, achieving an 8\% reduction with a tax of 11 euro/t-CO2-equivalent, compared to 68 euro/t-CO2eq for the same target with the second-best scheme.nitrous oxide; agro-ecosystem model; economic modeling; greenhouse gas; mitigation measures

L’efficacité de l’utilisation du foam roller sur l’extensibilité musculaire des ischio-jambiers: une étude pilote randomisée contrôlée

Dans le milieu du sport comme en physiothérapie, les étirements sont omniprésents. Le groupe musculaire des ischio-jambiers est celui qui mérite une attention particulière. L’utilisation du foam roller qui permet d’agir sur la musculature, est de plus en plus fréquente. L’objectif de ce travail est d’évaluer la faisabilité d’une étude pilote randomisée contrôlée pour évaluer les effets du foam roller sur l’extensibilité des ischio-jambiers. Étude pilote randomisée contrôlée sur huit semaines avec trois groupes : étirements à l’aide du foam roller, étirements statiques et groupe contrôle

Modeling of nitric oxide emissions from temperate agricultural ecosystems.

48 p.Arable soils are a significant source of nitric oxide (NO), most of which is derived from nitrogen fertilizers. Precise estimates of NO emissions from these soils are thus essential to devise strategies to mitigate the impact of agriculture on tropospheric ozone regulation. This paper presents the implementation of a soil NO emissions submodel within the environmentally-orientated soil crop model, CERES-EGC. The submodel simulates the NO production via nitrification pathway, as modulated by soil environmental drivers. The resulting model was tested with data from 4 field experiments on wheat- and maize-cropped soils representative of two agricultural regions of France, and for three years encompassing various climatic conditions. Overall, the model gave correct predictions of NO emissions, but shortcomings arose from an inadequate vertical distribution of fertilizer N in the soil surface. Inclusion of a 2-cm thick topsoil layer in an 'micro-layer' version of CERES-EGC gave more realistic simulations of NO emissions and of the under-lying microbiological process. From a statistical point, both versions of the model achieved a similar fit to the experimental data, with respectively a MD and a RMSE ranging from 1.8 to 6.2 g N-NO ha−1 d−1, and from 22.8 to 25.2 g N-NO ha−1 d −1 across the 4 experiments. The cumulative NO losses represented 1 to 2% of NH+4 fertilizer applied for the maize crops, and about 1% for the wheat crops. The 'micro-layer' version may be used for spatialized inventories of biogenic NO emissions to point mitigation strategies and to improve air quality prediction in chemistry transport models