We review concepts that have been used to address uncertainty in integrated modeling. Although conceptual approaches to tackle uncertainty seem diverse, a synthesis reveals more similarities than ...differences in the concepts published, especially if one adopts a model application-oriented focus. Given our findings, we slightly adapt the uncertainty framework table (UFT) developed by Walker et al. (2003) and apply it for an existing integrated modeling framework for the bio-economy. The use of color coded UFTs with a graphical visualization of uncertainty propagation pathways has facilitated a better overview and communication of uncertainties and uncertainty propagation pathways among the authors. Systematic consideration of uncertainties in integrated modeling may allow for more trust in model results and, if simulations are conducted, for a better robustness check of policy interventions.
•We review uncertainty concepts for integrated modeling.•Focus is put on eliciting uncertainties and uncertainty propagation pathways.•An adapted uncertainty concept is applied for an integrated modeling framework.•The adapted uncertainty concept helps to identify relevant uncertainties.•Further application of the uncertainty concept to test its usefulness is warranted.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The development of innovative metal catalysis for selective bond formation is an important task in organic chemistry. The group 13 metal indium is appealing for catalysis because indium-based ...reagents are minimally toxic, selective, and tolerant toward various functional groups. Among elements in this group, the most stable oxidation state is typically +3, but in molecules with larger group 13 atoms, the chemistry of the +1 oxidation state is also important. The use of indium(III) compounds in organic synthesis has been well-established as Lewis acid catalysts including asymmetric versions thereof. In contrast, only sporadic examples of the use of indium(I) as a stoichiometric reagent have been reported: to the best of our knowledge, our investigations represent the first synthetic method that uses a catalytic amount of indium(I). Depending on the nature of the ligand or the counteranion to which it is coordinated, indium(I) can act as both a Lewis acid and a Lewis base because it has both vacant p orbitals and a lone pair of electrons. This potential ambiphilicity may offer unique reactivity and unusual selectivity in synthesis and may have significant implications for catalysis, particularly for dual catalytic processes. We envisioned that indium(I) could be employed as a metallic Lewis base catalyst to activate Lewis acidic boron-based pronucleophiles for selective bond formation with suitable electrophiles. Alternatively, indium(I) could serve as an ambiphilic catalyst that activates both reagents at a single center. In this Account, we describe the development of low-oxidation state indium catalysts for carbon–carbon bond formation between boron-based pronucleophiles and various electrophiles. We discovered that indium(I) iodide was an excellent catalyst for α-selective allylations of C(sp2) electrophiles such as ketones and hydrazones. Using a combination of this low-oxidation state indium compound and a chiral semicorrin ligand, we developed catalytic highly enantioselective allylation, crotylation, and α-chloroallylation reactions of hydrazones. These transformations proceeded with rare constitutional selectivities and remarkable diastereoselectivities. Furthermore, indium(I) triflate served as the most effective catalyst for allylations and propargylations of C(sp3) electrophiles such as O,O-acetals, N,O-aminals, and ethers, and we applied this methodology to carbohydrate chemistry. In addition, a catalyst system composed of indium(I) chloride and a chiral silver BINOL-phosphate facilitated the highly enantioselective allylation and allenylation of N,O-aminals. Overall, these discoveries demonstrate the versatility, efficiency, and sensitivity of low-oxidation state indium catalysts in organic synthesis.
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IJS, KILJ, NUK, PNG, UL, UM
Multi-objective programming is frequently used in agro-environmental management studies to find compromises between competing policy objectives. We develop an integrated modelling framework to ...compute stochastic Pareto frontiers using realizations of three climate scenarios (SIMILAR, DRY, WET) for the semi-arid Seewinkel region in Austria. The stochastic Pareto frontiers relate net benefits of agricultural production (NB) to three environmental goal indicators including groundwater extraction (GWEX), nitrate leaching (NO3), and topsoil organic carbon stocks (SOC). The simulation results depict trade-offs and environmental co-benefits depending on the climate scenario and induced land use changes. A 1% (or 20%) decline of NB reduces GWEX by 11–83% (or 61–100%) and NO3 by 18–19% (or 49–53%), and increases SOC by 1% (or 5%), depending on the climate scenario. The results also reveal some environmental co-benefits for all Pareto frontier combinations. Climate change intensifies or alleviates trade-offs between NB and environmental goal indicators: in a dry climate scenario, trade-offs between NB and GWEX as well as SOC increase, while in a wet climate scenario, trade-offs between NB and NO3 increase. Overall, we find that efficient climate change adaptation of land use and management practices significantly improves the environmental outcomes for fairly small reductions in agricultural net benefits.
•Pareto frontiers are estimated for one economic and three environmental objectives.•Stochasticity of objectives is captured through 90 realizations of three climate scenarios.•Trade-offs are smallest between regional net benefits and groundwater extraction.•Trade-offs are largest between regional net benefits and topsoil organic carbon stocks.•Co-benefits are highest for topsoil organic carbon stocks and nitrate leaching.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The quantification of the effects of space radiation for manned spaceflight can be approximated by nanodosimetric measurements. For the development of nanodosimetric detectors, a Monte Carlo model ...for ion mobility and diffusion for characteristic electric fields is presented.
This model can be used to describe the interactions of ions in their parent gas based solely on commonly known input parameters, such as the ionization potential, kinetic diameter, molar mass, and polarizability of the gas. A model for approximating the resonant charge exchange cross section has been proposed, requiring only the ionization energy and mass of the parent gas as input parameters. The method proposed in this work was tested against experimental drift velocity data for a wide range of gases (helium, neon, nitrogen, argon, krypton, carbon monoxide, carbon dioxide, oxygen, propane). The transverse diffusion coefficients were compared to experimental values for helium, nitrogen, neon, argon, and propane gas.
With the Monte Carlo code and resonant charge exchange cross section approximation model presented in this work, it is now possible to calculate an estimate of the drift velocities, transverse diffusion, and thus the ion mobility of ions in their parent gas. This is essential for further nanodosimetric detector development, as those parameters are often not well known for the gas mixtures used in nanodosimetry.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
15.
Final countdown for biodiversity hotspots Habel, Jan C.; Rasche, Livia; Schneider, Uwe A. ...
Conservation letters,
November/December 2019, 2019-11-00, 20191101, 2019-11-01, Volume:
12, Issue:
6
Journal Article
Peer reviewed
Open access
Most of Earth's biodiversity is found in 36 biodiversity hotspots, yet less than 10% natural intact vegetation remains. We calculated models projecting the future state of most of these hotspots for ...the year 2050, based on future climatic and agroeconomic pressure. Our models project an increasing demand for agricultural land resulting in the conversion of >50% of remaining natural intact vegetation in about one third of all hotspots, and in 2–6 hotspots resulting from climatic pressure. This confirms that, in the short term, habitat loss is of greater concern than climate change for hotspots and their biodiversity. Hotspots are most severely threatened in tropical Africa and parts of Asia, where demographic pressure and the demand for agricultural land is highest. The speed and magnitude of pristine habitat loss is, according to our models, much greater than previously shown when combining both scenarios on future climatic and agroeconomic pressure.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Evaluation of the ongoing efforts for farm level adaptation to climate change is crucial to understand their effectiveness and to suggest further actions at the policy level. The current study ...explores the adaptation of wheat farmers to climate change, its determinants and its impact on food productivity and crop income in rural Pakistan. This study is based on a primary dataset of 442 wheat farmers conducted through face-to-face structured interviews from 65 villages across three agro-ecological zones of Punjab Province, Pakistan. The study employs logistic regression analysis to find adaptation determinants and uses the propensity score matching technique to estimate the causal impact of adaptation on food productivity and crop income. The results of the study suggest that wheat farmers were well aware of climate change, but for various reasons did not adapt accordingly. The major adaptation strategies implemented by wheat farmers include changing planting dates, crop varieties and fertilizer types. Moreover, education, farming experience, access to agricultural extension, weather forecasting and marketing information were the factors that significantly affected farmers' adaptation decisions. Adapting wheat crops to climate change significantly and positively affects wheat productivity and net crop income and hence indirectly improves the farmers' wellbeing and local food security. More benefits were achieved by farmers who used a combination of different adaptation strategies. The study suggests to focus on farmers' education, easy access to farm advisory services and information on new adaptation methods for sustainable food production and local food security.
•The study is based on the cross-sectional dataset of 442 wheat farmers collected in rural Pakistan.•Wheat farmers were well aware of climate change, but for various reasons were unable to adapt accordingly.•Changing planting dates, crop varieties and fertilizer types were the key measures implemented by farmers.•Adaptation was mainly influenced by education, farming experience, access to extension, weather forecasting and marketing information.•Adapting wheat crop to climate change significantly and positively affect the wheat productivity and crop income.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Food systems contribute considerably to greenhouse gas (GHG) emissions and influence land use. In Germany, many strategies have been proposed by policy-makers to reduce negative impacts and make the ...food system more sustainable. It is unclear how close the suggested policies, when bundled, will bring the food and land use system towards the targeted goals; and what stakeholders from non-policy-making organizations consider realistic changes in the German food system. We thus surveyed different stakeholder groups on their opinions about realistic changes in the food and land use system in Germany up to 2050, developed four stakeholder pathways, and used an accounting tool to determine the effect of each pathway on indicators such as land use, GHG emissions, and biodiversity conservation potential. The assessment showed that GHG emissions from agricultural activities and land use are reduced from 66 to − 2–22 TgCO
2
e by 2050, while the area where natural processes predominate increases from 19 to 27–32%, and the resilience of the food system is not negatively influenced. The change is caused mainly by a diet-change-induced reduction of livestock production and agricultural area transformation into areas with higher carbon sequestration rates. If followed, the common stakeholder pathway (based on all stakeholder responses) would thus lead towards a sustainable food and land use system, but only if the underlying assumption of a drastic diet change towards more plant-based products comes true. Stakeholders from the academic and public sectors were more likely to assume that such a change was realistic than stakeholders from the private sector.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Agricultural planning processes at farm to national level are essential for assessing and reacting to land conditions, opportunities, and threats for coffee production. However, lack or uncertainty ...of information is common during these processes. Bayesian networks can be used to manage these uncertainties. We, therefore, developed the first Bayesian network model for an Agroecological Land Evaluation for Coffea arabica L. (ALECA). A newly developed set of suitability functions was used to populate the nodes in the network. ALECA was then adjusted and validated to Central America. The results show that even without the use of coffee maps as input, ALECA accurately scores the suitability of actual coffee areas for coffee production as higher than that non-coffee areas, and can accurately predict the known order of quality of coffee reference zones in Central America. The results also show that ALECA can be used as a decision-support tool even under data uncertainty.
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•A probabilistic framework to evaluate the land suitability for crop production.•Land evaluation model for Coffee arabica L. base on climate, soil and landform factors.•Capable of dealing with lack or uncertain information.•Possible to assess natural or anthropogenic changes in the land suitability for coffee.•A tool for coffee stakeholders during planning processes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Greenhouse gas emission (GHGE) taxes on food products have recently been proposed as means to help reduce agricultural emissions. Numerous authors have calculated potential GHGE reductions in case ...such a tax was implemented in certain countries or regions. They did however assume a reduced production of GHGE-intense foods equal to the decline in demand induced by the tax. This omits however possible increases of net-exports that might offset such a demand reduction. Herein, the market dynamic behind this so-called “emission leakage” is explained and its effect quantified for a greenhouse gas tax in the European Union. We use the European Forest and Agricultural Sector Optimization Model for the quantitative analysis and simulate a greenhouse gas tax on all food products, based on their individual emission levels. The partial equilibrium model covers all world regions and hence the tax's effects on international trade of agricultural commodities can be examined. It was found that 43% of the greenhouse gas reduction indicted by a domestic consumption reduction is lost through emission leakage. This already includes the mitigating effects of a production shift from inefficient to efficient producers that is another consequence of increased exports from the European Union. A greenhouse gas emission tax on food products is hence much less efficient than previously proposed, if it is not introduced globally or trade is not restricted.
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•The effect of a GHG tax on food products in the EU is quantified.•We explain and visualize the general market dynamics of carbon leakage.•Unlike authors before us, we quantify carbon leakage effects.•Previous studies vastly overestimate the effects of a the tax, for omitting leakage.•43% of the mitigation is lost to leakage, despite a shift to efficient producers.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•An agent-based model of optimized bioenergy industry infrastructure is developed.•The new model is applied to emerging economies for the first time.•Bioenergy plants should be ...located close to bioenergy feedstock source regions.•Biomass densification measures are not economically profitable for the case region.•The benefits of smallholder farmers need to be taken into consideration.
In the context of combating climate change and maintaining energy security, ambitious bioenergy development projects in emerging economies face considerable challenges, for example an overburdened bioenergy industry infrastructure due to the growing demand for bioenergy products. There are abundant studies on optimizing the bioenergy industry infrastructure. However, they fail to comprehensively simulate the interactions among the predominant actors of the infrastructure, especially the bioenergy plant operators in emerging economies. To fill this research gap, we develop a new dynamic agent-based model of optimized bioenergy industry infrastructure from the perspective of bioenergy plant operators. We then apply the model to Jiangsu Province of China to simulate the coordination of two types of bioenergy plants and project the optimal distribution of these plants and their corresponding transportation networks for the year of 2030. The model results suggest locating bioenergy plants closer to bioenergy feedstock source regions rather than to bioenergy products consumption sites, an answer to the classical facility location problem. A welfare analysis based on the extended model indicates that the biomass densification process aiming at mitigating the growing transport volumes incurred by the delivery of bulky bioenergy feedstock is not economically profitable in our case region. The experiences from this region further show that for emerging economies, a successful bioenergy industry infrastructure needs to take the benefits of smallholder farmers into consideration.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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