economic simulation model: Topics by Science.gov

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Implementing and Evaluating an Innovative Approach to Simulation Training Acquisitions

DTIC Science & Technology

2006-01-01

busi- ness model, compares it with other approaches for buying simulations and simulation training, reviews economic theories relevant to the model, and...Points in Common with Other Approaches but Also Some Distinctive Characteristics ........................... 53 Contents vii CHAPTER FOUR The Economic ...Appropriate? .................... 65 4.3. Summary of Key Findings from Economic Theory .............. 72 xiii Summary In the wake of the failure of the Joint
Macromod: Computer Simulation For Introductory Economics

ERIC Educational Resources Information Center

Ross, Thomas

1977-01-01

The Macroeconomic model (Macromod) is a computer assisted instruction simulation model designed for introductory economics courses. An evaluation of its utilization at a community college indicates that it yielded a 10 percent to 13 percent greater economic comprehension than lecture classes and that it met with high student approval. (DC)
The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;

2012-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

Water scarcity and economic damage in Europe: regionally relevant simulations from 2000 to 2050

NASA Astrophysics Data System (ADS)

Bernhard, Jeroen; de Roo, Ad; Bisselink, Bernard; Gelati, Emiliano; Karssenberg, Derek; de Jong, Steven

2017-04-01

Water availability is unequally distributed across Europe. Where certain regions experience a surplus of water, other areas have limited water availability which causes economic damage to the water using sectors such as households, industries or agriculture. Future changes in climatic and socio-economic conditions are expected to further increase the competition for available water that is already present in Europe. This means there is an increasing need for models that are able to simulate this multi-sectorial system of water availability and demand and incorporate the socio-economic component required for robust decisions and policy support. We present our modelling study which is focused at providing regionally relevant pan-European water scarcity and economic damage simulations. First we developed regionally relevant pan-European water demand simulations for the household and industry sector from 2000 up to 2050. For the household sector we developed a model to simulate water use based on water price, income and several other relevant variables at NUTS-3 level (over 1200 regions in Europe). Alternatively, we modelled industrial water use based on regionally downscaled water productivity values at the national level for ten sub-sections of the NACE (Nomenclature of Economic Activities) classification for economic activities. Subsequently we used scenario projections of our explanatory variables to make scenario simulations of water demand from 2000 up to 2050 at pan-European scale with unprecedented spatial and sub-sectorial detail. In order to analyze the European water use system we integrated these water demand scenarios into the hydrological rainfall-runoff model called LISFLOOD (Distributed Water Balance and Flood Simulation Model), which incorporates a vegetation module for the simulation of crop yield and irrigation water demand of the agriculture sector. We simulated river discharge and groundwater availability for abstractions of water using sectors across Europe from 2000 up to 2050 at 5km grid level for multiple climate and socio-economic scenarios. This allowed us to identify regions with water scarcity problems from the recent past up to 2050 and quantify the economic damage that can be attributed to the limited water availability. Results showed several regions where substantially more water is extracted from the system than what would be sustainable into the future. Furthermore, we analyzed how changing water prices or relocation of economic activities could reduce future water scarcity problems and decrease the related economical damage. We found that for some regions, relatively small measurers already could have a positive impact on water scarcity problems.
Development of Aspen: A microanalytic simulation model of the US economy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pryor, R.J.; Basu, N.; Quint, T.

1996-02-01

This report describes the development of an agent-based microanalytic simulation model of the US economy. The microsimulation model capitalizes on recent technological advances in evolutionary learning and parallel computing. Results are reported for a test problem that was run using the model. The test results demonstrate the model`s ability to predict business-like cycles in an economy where prices and inventories are allowed to vary. Since most economic forecasting models have difficulty predicting any kind of cyclic behavior. These results show the potential of microanalytic simulation models to improve economic policy analysis and to provide new insights into underlying economic principles.more » Work already has begun on a more detailed model.« less
Generalized DSS shell for developing simulation and optimization hydro-economic models of complex water resources systems

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio; Harou, Julien J.; Andreu, Joaquin

2013-04-01

Hydrologic-economic models allow integrated analysis of water supply, demand and infrastructure management at the river basin scale. These models simultaneously analyze engineering, hydrology and economic aspects of water resources management. Two new tools have been designed to develop models within this approach: a simulation tool (SIM_GAMS), for models in which water is allocated each month based on supply priorities to competing uses and system operating rules, and an optimization tool (OPT_GAMS), in which water resources are allocated optimally following economic criteria. The characterization of the water resource network system requires a connectivity matrix representing the topology of the elements, generated using HydroPlatform. HydroPlatform, an open-source software platform for network (node-link) models, allows to store, display and export all information needed to characterize the system. Two generic non-linear models have been programmed in GAMS to use the inputs from HydroPlatform in simulation and optimization models. The simulation model allocates water resources on a monthly basis, according to different targets (demands, storage, environmental flows, hydropower production, etc.), priorities and other system operating rules (such as reservoir operating rules). The optimization model's objective function is designed so that the system meets operational targets (ranked according to priorities) each month while following system operating rules. This function is analogous to the one used in the simulation module of the DSS AQUATOOL. Each element of the system has its own contribution to the objective function through unit cost coefficients that preserve the relative priority rank and the system operating rules. The model incorporates groundwater and stream-aquifer interaction (allowing conjunctive use simulation) with a wide range of modeling options, from lumped and analytical approaches to parameter-distributed models (eigenvalue approach). Such functionality is not typically included in other water DSS. Based on the resulting water resources allocation, the model calculates operating and water scarcity costs caused by supply deficits based on economic demand functions for each demand node. The optimization model allocates the available resource over time based on economic criteria (net benefits from demand curves and cost functions), minimizing the total water scarcity and operating cost of water use. This approach provides solutions that optimize the economic efficiency (as total net benefit) in water resources management over the optimization period. Both models must be used together in water resource planning and management. The optimization model provides an initial insight on economically efficient solutions, from which different operating rules can be further developed and tested using the simulation model. The hydro-economic simulation model allows assessing economic impacts of alternative policies or operating criteria, avoiding the perfect foresight issues associated with the optimization. The tools have been applied to the Jucar river basin (Spain) in order to assess the economic results corresponding to the current modus operandi of the system and compare them with the solution from the optimization that maximizes economic efficiency. Acknowledgments: The study has been partially supported by the European Community 7th Framework Project (GENESIS project, n. 226536) and the Plan Nacional I+D+I 2008-2011 of the Spanish Ministry of Science and Innovation (CGL2009-13238-C02-01 and CGL2009-13238-C02-02).
Calibrating and testing a gap model for simulating forest management in the Oregon Coast Range

Treesearch

Robert J. Pabst; Matthew N. Goslin; Steven L. Garman; Thomas A. Spies

2008-01-01

The complex mix of economic and ecological objectives facing today's forest managers necessitates the development of growth models with a capacity for simulating a wide range of forest conditions while producing outputs useful for economic analyses. We calibrated the gap model ZELIG to simulate stand level forest development in the Oregon Coast Range as part of a...
Integrated Modeling, Mapping, and Simulation (IMMS) framework for planning exercises.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friedman-Hill, Ernest J.; Plantenga, Todd D.

2010-06-01

The Integrated Modeling, Mapping, and Simulation (IMMS) program is designing and prototyping a simulation and collaboration environment for linking together existing and future modeling and simulation tools to enable analysts, emergency planners, and incident managers to more effectively, economically, and rapidly prepare, analyze, train, and respond to real or potential incidents. When complete, the IMMS program will demonstrate an integrated modeling and simulation capability that supports emergency managers and responders with (1) conducting 'what-if' analyses and exercises to address preparedness, analysis, training, operations, and lessons learned, and (2) effectively, economically, and rapidly verifying response tactics, plans and procedures.
Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.
Ultrasound-Guided Vascular Access Simulator for Medical Training: Proposal of a Simple, Economic and Effective Model.

PubMed

Fürst, Rafael Vilhena de Carvalho; Polimanti, Afonso César; Galego, Sidnei José; Bicudo, Maria Claudia; Montagna, Erik; Corrêa, João Antônio

2017-03-01

To present a simple and affordable model able to properly simulate an ultrasound-guided venous access. The simulation was made using a latex balloon tube filled with water and dye solution implanted in a thawed chicken breast with bones. The presented model allows the simulation of all implant stages of a central catheter. The obtained echogenicity is similar to that observed in human tissue, and the ultrasound identification of the tissues, balloon, needle, wire guide and catheter is feasible and reproducible. The proposed model is simple, economical, easy to manufacture and capable of realistically and effectively simulating an ultrasound-guided venous access.
Analysis of the interrelationship of energy, economy, and environment: A model of a sustainable energy future for Korea

NASA Astrophysics Data System (ADS)

Boo, Kyung-Jin

The primary purpose of this dissertation is to provide the groundwork for a sustainable energy future in Korea. For this purpose, a conceptual framework of sustainable energy development was developed to provide a deeper understanding of interrelationships between energy, the economy, and the environment (E 3). Based on this theoretical work, an empirical simulation model was developed to investigate the ways in which E3 interact. This dissertation attempts to develop a unified concept of sustainable energy development by surveying multiple efforts to integrate various definitions of sustainability. Sustainable energy development should be built on the basis of three principles: ecological carrying capacity, economic efficiency, and socio-political equity. Ecological carrying capacity delineates the earth's resource constraints as well as its ability to assimilate wastes. Socio-political equity implies an equitable distribution of the benefits and costs of energy consumption and an equitable distribution of environmental burdens. Economic efficiency dictates efficient allocation of scarce resources. The simulation model is composed of three modules: an energy module, an environmental module and an economic module. Because the model is grounded on economic structural behaviorism, the dynamic nature of the current economy is effectively depicted and simulated through manipulating exogenous policy variables. This macro-economic model is used to simulate six major policy intervention scenarios. Major findings from these policy simulations were: (1) carbon taxes are the most effective means of reducing air-pollutant emissions; (2) sustainable energy development can be achieved through reinvestment of carbon taxes into energy efficiency and renewable energy programs; and (3) carbon taxes would increase a nation's welfare if reinvested in relevant areas. The policy simulation model, because it is based on neoclassical economics, has limitations such that it cannot fully account for socio-political realities (inter- and intra-generational equity) which are core feature of sustainability. Thus, alternative approaches based on qualitative analysis, such as the multi-criteria approach, will be required to complement the current policy simulation model.
[Decision modeling for economic evaluation of health technologies].

PubMed

de Soárez, Patrícia Coelho; Soares, Marta Oliveira; Novaes, Hillegonda Maria Dutilh

2014-10-01

Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.
Autoshaped choice in artificial neural networks: implications for behavioral economics and neuroeconomics.

PubMed

Burgos, José E; García-Leal, Óscar

2015-05-01

An existing neural network model of conditioning was used to simulate autoshaped choice. In this phenomenon, pigeons first receive an autoshaping procedure with two keylight stimuli X and Y separately paired with food in a forward-delay manner, intermittently for X and continuously for Y. Then pigeons receive unreinforced choice test trials of X and Y concurrently present. Most pigeons choose Y. This preference for a more valuable response alternative is a form of economic behavior that makes the phenomenon relevant to behavioral economics. The phenomenon also suggests a role for Pavlovian contingencies in economic behavior. The model used, in contrast to others, predicts autoshaping and automaintenance, so it is uniquely positioned to predict autoshaped choice. The model also contemplates neural substrates of economic behavior in neuroeconomics, such as dopaminergic and hippocampal systems. A feedforward neural network architecture was designed to simulate a neuroanatomical differentiation between two environment-behavior relations X-R1 and Y-R2, [corrected] where R1 and R2 denote two different emitted responses (not unconditionally elicited by the reward). Networks with this architecture received a training protocol that simulated an autoshaped-choice procedure. Most networks simulated the phenomenon. Implications for behavioral economics and neuroeconomics, limitations, and the issue of model appraisal are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.
Development of cost-effective surfactant flooding technology, Quarterly report, October 1995--December 1995

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pope, G.A.; Sepehrnoori, K.

1995-12-31

The objective of this research is to develop cost-effective surfactant flooding technology by using simulation studies to evaluate and optimize alternative design strategies taking into account reservoir characteristics process chemistry, and process design options such as horizontal wells. Task 1 is the development of an improved numerical method for our simulator that will enable us to solve a wider class of these difficult simulation problems accurately and affordably. Task 2 is the application of this simulator to the optimization of surfactant flooding to reduce its risk and cost. In this quarter, we have continued working on Task 2 to optimizemore » surfactant flooding design and have included economic analysis to the optimization process. An economic model was developed using a spreadsheet and the discounted cash flow (DCF) method of economic analysis. The model was designed specifically for a domestic onshore surfactant flood and has been used to economically evaluate previous work that used a technical approach to optimization. The DCF model outputs common economic decision making criteria, such as net present value (NPV), internal rate of return (IRR), and payback period.« less
On the need and use of models to explore the role of economic confidence:a survey.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sprigg, James A.; Paez, Paul J.; Hand, Michael S.

2005-04-01

Empirical studies suggest that consumption is more sensitive to current income than suggested under the permanent income hypothesis, which raises questions regarding expectations for future income, risk aversion, and the role of economic confidence measures. This report surveys a body of fundamental economic literature as well as burgeoning computational modeling methods to support efforts to better anticipate cascading economic responses to terrorist threats and attacks. This is a three part survey to support the incorporation of models of economic confidence into agent-based microeconomic simulations. We first review broad underlying economic principles related to this topic. We then review the economicmore » principle of confidence and related empirical studies. Finally, we provide a brief survey of efforts and publications related to agent-based economic simulation.« less
Agricultural livelihoods in coastal Bangladesh under climate and environmental change--a model framework.

PubMed

Lázár, Attila N; Clarke, Derek; Adams, Helen; Akanda, Abdur Razzaque; Szabo, Sylvia; Nicholls, Robert J; Matthews, Zoe; Begum, Dilruba; Saleh, Abul Fazal M; Abedin, Md Anwarul; Payo, Andres; Streatfield, Peter Kim; Hutton, Craig; Mondal, M Shahjahan; Moslehuddin, Abu Zofar Md

2015-06-01

Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled regional demography model to simulate net agriculture profit. This is used together with a household income-expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilisation due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. For example, under current model assumptions, temperature is more important than salinity for crop production. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of pricing due to greater susceptibility to climate vagaries. The livelihood and poverty results highlight the importance of the holistic consideration of the human-nature system and the careful selection of poverty indicators. Although the simulation model at this stage contains the minimum elements required to simulate the complexity of farmer livelihood interactions in coastal Bangladesh, the crop and socio-economic findings compare well with expected behaviours. The presented integrated model is the first step to develop a holistic, transferable analytic method and tool for coastal Bangladesh.
Economic Analysis. Computer Simulation Models.

ERIC Educational Resources Information Center

Sterling Inst., Washington, DC. Educational Technology Center.

A multimedia course in economic analysis was developed and used in conjunction with the United States Naval Academy. (See ED 043 790 and ED 043 791 for final reports of the project evaluation and development model.) This volume of the text discusses the simulation of behavioral relationships among variable elements in an economy and presents…
Using STELLA Simulation Models to Teach Natural Resource Economics

ERIC Educational Resources Information Center

Dissanayake, Sahan T. M.

2016-01-01

In this article, the author discusses how graphical simulation models created using STELLA software can be used to present natural resource systems in an intuitive way in undergraduate natural resource economics classes based on his experiences at a leading research university, a state university, and a leading liberal arts college in the United…
Computable general equilibrium model fiscal year 2013 capability development report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Brian Keith; Rivera, Michael Kelly; Boero, Riccardo

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences inmore » the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.« less
Gaming via Computer Simulation Techniques for Junior College Economics Education. Final Report.

ERIC Educational Resources Information Center

Thompson, Fred A.

A study designed to answer the need for more attractive and effective economics education involved the teaching of one junior college economics class by the conventional (lecture) method and an experimental class by computer simulation techniques. Econometric models approximating the "real world" were computer programed to enable the experimental…

Introducing GEOPHIRES v2.0: Updated Geothermal Techno-Economic Simulation Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beckers, Koenraad J; McCabe, Kevin

This paper presents an updated version of the geothermal techno-economic simulation tool GEOPHIRES (GEOthermal energy for Production of Heat and electricity ('IR') Economically Simulated). GEOPHIRES combines engineering models of the reservoir, wellbores, and surface plant facilities of a geothermal plant with an economic model to estimate the capital and operation and maintenance costs, lifetime energy production, and overall levelized cost of energy. The available end-use options are electricity, direct-use heat, and cogeneration. The main updates in the new version include conversion of the source code from FORTRAN to Python, the option to import temperature data (e.g., measured or from stand-alonemore » reservoir simulator), updated cost correlations, and more flexibility in selecting the time step and number of injection and production wells. In this paper, we provide an overview of all the updates and two case studies to illustrate the tool's new capabilities.« less
Addressing Hydro-economic Modeling Limitations - A Limited Foresight Sacramento Valley Model and an Open-source Modeling Platform

NASA Astrophysics Data System (ADS)

Harou, J. J.; Hansen, K. M.

2008-12-01

Increased scarcity of world water resources is inevitable given the limited supply and increased human pressures. The idea that "some scarcity is optimal" must be accepted for rational resource use and infrastructure management decisions to be made. Hydro-economic systems models are unique at representing the overlap of economic drivers, socio-political forces and distributed water resource systems. They demonstrate the tangible benefits of cooperation and integrated flexible system management. Further improvement of models, quality control practices and software will be needed for these academic policy tools to become accepted into mainstream water resource practice. Promising features include: calibration methods, limited foresight optimization formulations, linked simulation-optimization approaches (e.g. embedding pre-existing calibrated simulation models), spatial groundwater models, stream-aquifer interactions and stream routing, etc.. Conventional user-friendly decision support systems helped spread simulation models on a massive scale. Hydro-economic models must also find a means to facilitate construction, distribution and use. Some of these issues and model features are illustrated with a hydro-economic optimization model of the Sacramento Valley. Carry-over storage value functions are used to limit hydrologic foresight of the multi- period optimization model. Pumping costs are included in the formulation by tracking regional piezometric head of groundwater sub-basins. To help build and maintain this type of network model, an open-source water management modeling software platform is described and initial project work is discussed. The objective is to generically facilitate the connection of models, such as those developed in a modeling environment (GAMS, MatLab, Octave, "), to a geographic user interface (drag and drop node-link network) and a database (topology, parameters and time series). These features aim to incrementally move hydro- economic models in the direction of more practical implementation.
Computable General Equilibrium Model Fiscal Year 2013 Capability Development Report - April 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Brian Keith; Rivera, Michael K.; Boero, Riccardo

2014-04-01

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences inmore » the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.« less
Discrete event simulation: the preferred technique for health economic evaluations?

PubMed

Caro, Jaime J; Möller, Jörgen; Getsios, Denis

2010-12-01

To argue that discrete event simulation should be preferred to cohort Markov models for economic evaluations in health care. The basis for the modeling techniques is reviewed. For many health-care decisions, existing data are insufficient to fully inform them, necessitating the use of modeling to estimate the consequences that are relevant to decision-makers. These models must reflect what is known about the problem at a level of detail sufficient to inform the questions. Oversimplification will result in estimates that are not only inaccurate, but potentially misleading. Markov cohort models, though currently popular, have so many limitations and inherent assumptions that they are inadequate to inform most health-care decisions. An event-based individual simulation offers an alternative much better suited to the problem. A properly designed discrete event simulation provides more accurate, relevant estimates without being computationally prohibitive. It does require more data and may be a challenge to convey transparently, but these are necessary trade-offs to provide meaningful and valid results. In our opinion, discrete event simulation should be the preferred technique for health economic evaluations today. © 2010, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).
Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

NASA Astrophysics Data System (ADS)

Engström, Kerstin; Olin, Stefan; Rounsevell, Mark D. A.; Brogaard, Sara; van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave; Arneth, Almut

2016-11-01

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.
A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2005-07-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less
A Framework to Design and Optimize Chemical Flooding Processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2006-08-31

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less
A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2004-11-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less
Predicting trends of invasive plants richness using local socio-economic data: An application in North Portugal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santos, Mario, E-mail: mgsantoss@gmail.com; Freitas, Raul, E-mail: raulfreitas@portugalmail.com; Crespi, Antonio L., E-mail: aluis.crespi@gmail.com

2011-10-15

This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasingmore » populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology. - Highlights: {yields} Socio-economic data indicate human induced disturbances. {yields} Socio-economic development increase disturbance in ecosystems. {yields} Disturbance promotes opportunities for invasive plants.{yields} Increased opportunities promote richness of invasive plants.{yields} Increase in richness of invasive plants change natural ecosystems.« less
Integrating global socio-economic influences into a regional land use change model for China

NASA Astrophysics Data System (ADS)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.
Using whole disease modeling to inform resource allocation decisions: economic evaluation of a clinical guideline for colorectal cancer using a single model.

PubMed

Tappenden, Paul; Chilcott, Jim; Brennan, Alan; Squires, Hazel; Glynne-Jones, Rob; Tappenden, Janine

2013-06-01

To assess the feasibility and value of simulating whole disease and treatment pathways within a single model to provide a common economic basis for informing resource allocation decisions. A patient-level simulation model was developed with the intention of being capable of evaluating multiple topics within National Institute for Health and Clinical Excellence's colorectal cancer clinical guideline. The model simulates disease and treatment pathways from preclinical disease through to detection, diagnosis, adjuvant/neoadjuvant treatments, follow-up, curative/palliative treatments for metastases, supportive care, and eventual death. The model parameters were informed by meta-analyses, randomized trials, observational studies, health utility studies, audit data, costing sources, and expert opinion. Unobservable natural history parameters were calibrated against external data using Bayesian Markov chain Monte Carlo methods. Economic analysis was undertaken using conventional cost-utility decision rules within each guideline topic and constrained maximization rules across multiple topics. Under usual processes for guideline development, piecewise economic modeling would have been used to evaluate between one and three topics. The Whole Disease Model was capable of evaluating 11 of 15 guideline topics, ranging from alternative diagnostic technologies through to treatments for metastatic disease. The constrained maximization analysis identified a configuration of colorectal services that is expected to maximize quality-adjusted life-year gains without exceeding current expenditure levels. This study indicates that Whole Disease Model development is feasible and can allow for the economic analysis of most interventions across a disease service within a consistent conceptual and mathematical infrastructure. This disease-level modeling approach may be of particular value in providing an economic basis to support other clinical guidelines. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Passenger rail security, planning, and resilience: application of network, plume, and economic simulation models as decision support tools.

PubMed

Greenberg, Michael; Lioy, Paul; Ozbas, Birnur; Mantell, Nancy; Isukapalli, Sastry; Lahr, Michael; Altiok, Tayfur; Bober, Joseph; Lacy, Clifton; Lowrie, Karen; Mayer, Henry; Rovito, Jennifer

2013-11-01

We built three simulation models that can assist rail transit planners and operators to evaluate high and low probability rail-centered hazard events that could lead to serious consequences for rail-centered networks and their surrounding regions. Our key objective is to provide these models to users who, through planning with these models, can prevent events or more effectively react to them. The first of the three models is an industrial systems simulation tool that closely replicates rail passenger traffic flows between New York Penn Station and Trenton, New Jersey. Second, we built and used a line source plume model to trace chemical plumes released by a slow-moving freight train that could impact rail passengers, as well as people in surrounding areas. Third, we crafted an economic simulation model that estimates the regional economic consequences of a variety of rail-related hazard events through the year 2020. Each model can work independently of the others. However, used together they help provide a coherent story about what could happen and set the stage for planning that should make rail-centered transport systems more resistant and resilient to hazard events. We highlight the limitations and opportunities presented by using these models individually or in sequence. © 2013 Society for Risk Analysis.
Passenger Rail Security, Planning, and Resilience: Application of Network, Plume, and Economic Simulation Models as Decision Support Tools

PubMed Central

Greenberg, Michael; Lioy, Paul; Ozbas, Birnur; Mantell, Nancy; Isukapalli, Sastry; Lahr, Michael; Altiok, Tayfur; Bober, Joseph; Lacy, Clifton; Lowrie, Karen; Mayer, Henry; Rovito, Jennifer

2014-01-01

We built three simulation models that can assist rail transit planners and operators to evaluate high and low probability rail-centered hazard events that could lead to serious consequences for rail-centered networks and their surrounding regions. Our key objective is to provide these models to users who, through planning with these models, can prevent events or more effectively react to them. The first of the three models is an industrial systems simulation tool that closely replicates rail passenger traffic flows between New York Penn Station and Trenton, New Jersey. Second, we built and used a line source plume model to trace chemical plumes released by a slow-moving freight train that could impact rail passengers, as well as people in surrounding areas. Third, we crafted an economic simulation model that estimates the regional economic consequences of a variety of rail-related hazard events through the year 2020. Each model can work independently of the others. However, used together they help provide a coherent story about what could happen and set the stage for planning that should make rail-centered transport systems more resistant and resilient to hazard events. We highlight the limitations and opportunities presented by using these models individually or in sequence. PMID:23718133
Coupling model of aerobic waste degradation considering temperature, initial moisture content and air injection volume.

PubMed

Ma, Jun; Liu, Lei; Ge, Sai; Xue, Qiang; Li, Jiangshan; Wan, Yong; Hui, Xinminnan

2018-03-01

A quantitative description of aerobic waste degradation is important in evaluating landfill waste stability and economic management. This research aimed to develop a coupling model to predict the degree of aerobic waste degradation. On the basis of the first-order kinetic equation and the law of conservation of mass, we first developed the coupling model of aerobic waste degradation that considered temperature, initial moisture content and air injection volume to simulate and predict the chemical oxygen demand in the leachate. Three different laboratory experiments on aerobic waste degradation were simulated to test the model applicability. Parameter sensitivity analyses were conducted to evaluate the reliability of parameters. The coupling model can simulate aerobic waste degradation, and the obtained simulation agreed with the corresponding results of the experiment. Comparison of the experiment and simulation demonstrated that the coupling model is a new approach to predict aerobic waste degradation and can be considered as the basis for selecting the economic air injection volume and appropriate management in the future.
Exploring the optimal economic timing for crop tree release treatments in hardwoods: results from simulation

Treesearch

Chris B. LeDoux; Gary W. Miller

2008-01-01

In this study we used data from 16 Appalachian hardwood stands, a growth and yield computer simulation model, and stump-to-mill logging cost-estimating software to evaluate the optimal economic timing of crop tree release (CTR) treatments. The simulated CTR treatments consisted of one-time logging operations at stand age 11, 23, 31, or 36 years, with the residual...
Effects of global climate change on the US forest sector: response functions derived from a dynamic resource and market simulator.

Treesearch

Bruce A. McCarl; Darius M. Adams; Ralph J. Alig; Diana Burton; Chi-Chung. Chen

2000-01-01

A multiperiod, regional, mathematical programming economic model is used to evaluate the potential economic impacts of global climatic change on the US forest sector. A wide range of scenarios for the biological response of forests to climate change are developed, ranging from small to large changes in forest growth rates. These scenarios are simulated in the economic...
Economic communication model set

NASA Astrophysics Data System (ADS)

Zvereva, Olga M.; Berg, Dmitry B.

2017-06-01

This paper details findings from the research work targeted at economic communications investigation with agent-based models usage. The agent-based model set was engineered to simulate economic communications. Money in the form of internal and external currencies was introduced into the models to support exchanges in communications. Every model, being based on the general concept, has its own peculiarities in algorithm and input data set since it was engineered to solve the specific problem. Several and different origin data sets were used in experiments: theoretic sets were estimated on the basis of static Leontief's equilibrium equation and the real set was constructed on the basis of statistical data. While simulation experiments, communication process was observed in dynamics, and system macroparameters were estimated. This research approved that combination of an agent-based and mathematical model can cause a synergetic effect.
Two Simple Macroeconomic Simulations and the Great Depression. Instructor's Notes [and] A Student Guide [and] Basic Program.

ERIC Educational Resources Information Center

Schenk, Robert E.

Intended for use with college students in introductory macroeconomics or American economic history courses, these two computer simulations of two basic macroeconomic models--a simple Keynesian-type model and a quantity-theory-of-money model--present largely incompatible explanations of the Great Depression. Written in Basic, the simulations are…
Triple Value Simulation Model Fact Sheet

EPA Pesticide Factsheets

The Triple Value Simulation (3VS) is a high-level model that accounts for the complex relationships among economic, social and environmental systems in order to explore scenarios and solutions to improve the health of the Bay.
Analysis of economic benefit of wind power based on system dynamics

NASA Astrophysics Data System (ADS)

Zhao, Weibo; Han, Yaru; Niu, Dongxiao

2018-04-01

The scale of renewable power generation, such as wind power, has increased gradually in recent years. Considering that the economic benefits of wind farms are affected by many dynamic factors. The dynamic simulation model of wind power economic benefit system is established based on the system dynamics method. By comparing the economic benefits of wind farms under different setting scenarios through this model, the impact of different factors on the economic benefits of wind farms can be reflected.

Computational investigation of fluid flow and heat transfer of an economizer by porous medium approach

NASA Astrophysics Data System (ADS)

Babu, C. Rajesh; Kumar, P.; Rajamohan, G.

2017-07-01

Computation of fluid flow and heat transfer in an economizer is simulated by a porous medium approach, with plain tubes having a horizontal in-line arrangement and cross flow arrangement in a coal-fired thermal power plant. The economizer is a thermal mechanical device that captures waste heat from the thermal exhaust flue gasses through heat transfer surfaces to preheat boiler feed water. In order to evaluate the fluid flow and heat transfer on tubes, a numerical analysis on heat transfer performance is carried out on an 110 t/h MCR (Maximum continuous rating) boiler unit. In this study, thermal performance is investigated using the computational fluid dynamics (CFD) simulation using ANSYS FLUENT. The fouling factor ε and the overall heat transfer coefficient ψ are employed to evaluate the fluid flow and heat transfer. The model demands significant computational details for geometric modeling, grid generation, and numerical calculations to evaluate the thermal performance of an economizer. The simulation results show that the overall heat transfer coefficient 37.76 W/(m2K) and economizer coil side pressure drop of 0.2 (kg/cm2) are found to be conformity within the tolerable limits when compared with existing industrial economizer data.
Coupling of a distributed stakeholder-built system dynamics socio-economic model with SAHYSMOD for sustainable soil salinity management. Part 2: Model coupling and application

NASA Astrophysics Data System (ADS)

Inam, Azhar; Adamowski, Jan; Prasher, Shiv; Halbe, Johannes; Malard, Julien; Albano, Raffaele

2017-08-01

Many simulation models focus on simulating a single physical process and do not constitute balanced representations of the physical, social and economic components of a system. The present study addresses this challenge by integrating a physical (P) model (SAHYSMOD) with a group (stakeholder) built system dynamics model (GBSDM) through a component modeling approach based on widely applied tools such as MS Excel, Python and Visual Basic for Applications (VBA). The coupled model (P-GBSDM) was applied to test soil salinity management scenarios (proposed by stakeholders) for the Haveli region of the Rechna Doab Basin in Pakistan. Scenarios such as water banking, vertical drainage, canal lining, and irrigation water reallocation were simulated with the integrated model. Spatiotemporal maps and economic and environmental trade-off criteria were used to examine the effectiveness of the selected management scenarios. After 20 years of simulation, canal lining reduced soil salinity by 22% but caused an initial reduction of 18% in farm income, which requires an initial investment from the government. The government-sponsored Salinity Control and Reclamation Project (SCARP) is a short-term policy that resulted in a 37% increase in water availability with a 12% increase in farmer income. However, it showed detrimental effects on soil salinity in the long term, with a 21% increase in soil salinity due to secondary salinization. The new P-GBSDM was shown to be an effective platform for engaging stakeholders and simulating their proposed management policies while taking into account socioeconomic considerations. This was not possible using the physically based SAHYSMOD model alone.
Introducing GEOPHIRES v2.0: Updated Geothermal Techno-Economic Simulation Tool: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beckers, Koenraad J; McCabe, Kevin

This paper presents an updated version of the geothermal techno-economic simulation tool GEOPHIRES (GEOthermal Energy for Production of Heat and electricity (IR) Economically Simulated). GEOPHIRES combines reservoir, wellbore, surface plant and economic models to estimate the capital, and operation and maintenance costs, lifetime energy production, and overall levelized cost of energy of a geothermal plant. The available end-use options are electricity, direct-use heat and cogeneration. The main updates in the new version include conversion of the source code from FORTRAN to Python, the option to couple to an external reservoir simulator, updated cost correlations, and more flexibility in selecting themore » time step and number of injection and production wells. An overview of all the updates and two case-studies to illustrate the tool's new capabilities are provided in this paper.« less
MULTIREGION: a simulation-forecasting model of BEA economic area population and employment. [Bureau of Economic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olsen, R.J.; Westley, G.W.; Herzog, H.W. Jr.

This report documents the development of MULTIREGION, a computer model of regional and interregional socio-economic development. The MULTIREGION model interprets the economy of each BEA economic area as a labor market, measures all activity in terms of people as members of the population (labor supply) or as employees (labor demand), and simultaneously simulates or forecasts the demands and supplies of labor in all BEA economic areas at five-year intervals. In general the outputs of MULTIREGION are intended to resemble those of the Water Resource Council's OBERS projections and to be put to similar planning and analysis purposes. This report hasmore » been written at two levels to serve the needs of multiple audiences. The body of the report serves as a fairly nontechnical overview of the entire MULTIREGION project; a series of technical appendixes provide detailed descriptions of the background empirical studies of births, deaths, migration, labor force participation, natural resource employment, manufacturing employment location, and local service employment used to construct the model.« less
Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

PubMed

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
A systematic review of health economic models and utility estimation methods in schizophrenia.

PubMed

Németh, Bertalan; Fasseeh, Ahmad; Molnár, Anett; Bitter, István; Horváth, Margit; Kóczián, Kristóf; Götze, Árpád; Nagy, Balázs

2018-06-01

There is a growing need for economic evaluations describing the disease course, as well as the costs and clinical outcomes related to the treatment of schizophrenia. Areas covered: A systematic review on studies describing health economic models in schizophrenia and a targeted literature review on utility mapping algorithms in schizophrenia were carried out. Models found in the review were collated and assessed in detail according to their type and various other attributes. Fifty-nine studies were included in the review. Modeling techniques varied from simple decision trees to complex simulation models. The models used various clinical endpoints as value drivers, 47% of the models used quality-adjusted life years, and eight percent used disability-adjusted life years to measure benefits, while others applied various clinical outcomes. Most models considered patients switching between therapies, and therapeutic adherence, compliance or persistence. The targeted literature review identified four main approaches to map PANSS scores to utility values. Expert commentary: Health economic models developed for schizophrenia showed great variability, with simulation models becoming more frequently used in the last decade. Using PANSS scores as the basis of utility estimations is justifiable.
Modeling and simulation: A key to future defense technology

NASA Technical Reports Server (NTRS)

Muccio, Anthony B.

1993-01-01

The purpose of this paper is to express the rationale for continued technological and scientific development of the modeling and simulation process for the defense industry. The defense industry, along with a variety of other industries, is currently being forced into making sacrifices in response to the current economic hardships. These sacrifices, which may not compromise the safety of our nation, nor jeopardize our current standing as the world peace officer, must be concentrated in areas which will withstand the needs of the changing world. Therefore, the need for cost effective alternatives of defense issues must be examined. This paper provides support that the modeling and simulation process is an economically feasible process which will ensure our nation's safety as well as provide and keep up with the future technological developments and demands required by the defense industry. The outline of this paper is as follows: introduction, which defines and describes the modeling and simulation process; discussion, which details the purpose and benefits of modeling and simulation and provides specific examples of how the process has been successful; and conclusion, which summarizes the specifics of modeling and simulation of defense issues and lends the support for its continued use in the defense arena.
BIOREACTOR ECONOMICS, SIZE AND TIME OF OPERATION (BEST) COMPUTER SIMULATOR FOR DESIGNING SULFATE-REDUCING BACTERIA FIELD BIOREACTORS

EPA Science Inventory

BEST (bioreactor economics, size and time of operation) is an Excel™ spreadsheet-based model that is used in conjunction with the public domain geochemical modeling software, PHREEQCI. The BEST model is used in the design process of sulfate-reducing bacteria (SRB) field bioreacto...
Abhijit Dutta | NREL

Science.gov Websites

Techno-economic analysis Process model development for existing and conceptual processes Detailed heat integration Economic analysis of integrated processes Integration of process simulation learnings into control ;Conceptual Process Design and Techno-Economic Assessment of Ex Situ Catalytic Fast Pyrolysis of Biomass: A
Why an SO/sub 2/ emission tax is an unpopular policy instrument: Simulation results from a general equilibrium model of the Norwegian economy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanson, D.A.; Alfsen, K.H.

1986-01-01

Norway, together with some twenty other countries, signed the Helsinki treaty in July 1985 for the purpose of reducing SO/sub 2/ emissions. Hence, it is interesting to analyze the emission reductions that could be achieved using a tax on SO/sub 2/ emissions, as well as the indirect impacts on the economy. Simulations of the economic impact of the tax (which effectively increases the cost of using energy) were made using the Multi-Sectoral Growth (MSG) model. Results of the simulations indicated a larger than expected reduction in economic output.
FACE-IT. A Science Gateway for Food Security Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montella, Raffaele; Kelly, David; Xiong, Wei

Progress in sustainability science is hindered by challenges in creating and managing complex data acquisition, processing, simulation, post-processing, and intercomparison pipelines. To address these challenges, we developed the Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE-IT) for crop and climate impact assessments. This integrated data processing and simulation framework enables data ingest from geospatial archives; data regridding, aggregation, and other processing prior to simulation; large-scale climate impact simulations with agricultural and other models, leveraging high-performance and cloud computing; and post-processing to produce aggregated yields and ensemble variables needed for statistics, for model intercomparison, and to connectmore » biophysical models to global and regional economic models. FACE-IT leverages the capabilities of the Globus Galaxies platform to enable the capture of workflows and outputs in well-defined, reusable, and comparable forms. We describe FACE-IT and applications within the Agricultural Model Intercomparison and Improvement Project and the Center for Robust Decision-making on Climate and Energy Policy.« less
Documentation and user guides for SPBLOB: a computer simulation model of the join population dynamics for loblolly pine and the southern pine beetle

Treesearch

John Bishir; James Roberds; Brian Strom; Xiaohai Wan

2009-01-01

SPLOB is a computer simulation model for the interaction between loblolly pine (Pinus taeda L.), the economically most important forest crop in the United States, and the southern pine beetle (SPB: Dendroctonus frontalis Zimm.), the major insect pest for this species. The model simulates loblolly pine stands from time of planting...
Strategy and gaps for modeling, simulation, and control of hybrid systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabiti, Cristian; Garcia, Humberto E.; Hovsapian, Rob

2015-04-01

The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers,more » and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.« less
Econ Simulation Cited as Success

ERIC Educational Resources Information Center

Workman, Robert; Maher, John

1973-01-01

A brief description of a computerized economics simulation model which provides students with an opportunity to apply microeconomic principles along with elementary accounting and statistical techniques.'' (Author/AK)
Testing simulation and structural models with applications to energy demand

NASA Astrophysics Data System (ADS)

Wolff, Hendrik

2007-12-01

This dissertation deals with energy demand and consists of two parts. Part one proposes a unified econometric framework for modeling energy demand and examples illustrate the benefits of the technique by estimating the elasticity of substitution between energy and capital. Part two assesses the energy conservation policy of Daylight Saving Time and empirically tests the performance of electricity simulation. In particular, the chapter "Imposing Monotonicity and Curvature on Flexible Functional Forms" proposes an estimator for inference using structural models derived from economic theory. This is motivated by the fact that in many areas of economic analysis theory restricts the shape as well as other characteristics of functions used to represent economic constructs. Specific contributions are (a) to increase the computational speed and tractability of imposing regularity conditions, (b) to provide regularity preserving point estimates, (c) to avoid biases existent in previous applications, and (d) to illustrate the benefits of our approach via numerical simulation results. The chapter "Can We Close the Gap between the Empirical Model and Economic Theory" discusses the more fundamental question of whether the imposition of a particular theory to a dataset is justified. I propose a hypothesis test to examine whether the estimated empirical model is consistent with the assumed economic theory. Although the proposed methodology could be applied to a wide set of economic models, this is particularly relevant for estimating policy parameters that affect energy markets. This is demonstrated by estimating the Slutsky matrix and the elasticity of substitution between energy and capital, which are crucial parameters used in computable general equilibrium models analyzing energy demand and the impacts of environmental regulations. Using the Berndt and Wood dataset, I find that capital and energy are complements and that the data are significantly consistent with duality theory. Both results would not necessarily be achieved using standard econometric methods. The final chapter "Daylight Time and Energy" uses a quasi-experiment to evaluate a popular energy conservation policy: we challenge the conventional wisdom that extending Daylight Saving Time (DST) reduces energy demand. Using detailed panel data on half-hourly electricity consumption, prices, and weather conditions from four Australian states we employ a novel 'triple-difference' technique to test the electricity-saving hypothesis. We show that the extension failed to reduce electricity demand and instead increased electricity prices. We also apply the most sophisticated electricity simulation model available in the literature to the Australian data. We find that prior simulation models significantly overstate electricity savings. Our results suggest that extending DST will fail as an instrument to save energy resources.
A strain-, cow-, and herd-specific bio-economic simulation model of intramammary infections in dairy cattle herds.

PubMed

Gussmann, Maya; Kirkeby, Carsten; Græsbøll, Kaare; Farre, Michael; Halasa, Tariq

2018-07-14

Intramammary infections (IMI) in dairy cattle lead to economic losses for farmers, both through reduced milk production and disease control measures. We present the first strain-, cow- and herd-specific bio-economic simulation model of intramammary infections in a dairy cattle herd. The model can be used to investigate the cost-effectiveness of different prevention and control strategies against IMI. The objective of this study was to describe a transmission framework, which simulates spread of IMI causing pathogens through different transmission modes. These include the traditional contagious and environmental spread and a new opportunistic transmission mode. In addition, the within-herd transmission dynamics of IMI causing pathogens were studied. Sensitivity analysis was conducted to investigate the influence of input parameters on model predictions. The results show that the model is able to represent various within-herd levels of IMI prevalence, depending on the simulated pathogens and their parameter settings. The parameters can be adjusted to include different combinations of IMI causing pathogens at different prevalence levels, representing herd-specific situations. The model is most sensitive to varying the transmission rate parameters and the strain-specific recovery rates from IMI. It can be used for investigating both short term operational and long term strategic decisions for the prevention and control of IMI in dairy cattle herds. Copyright © 2018 Elsevier Ltd. All rights reserved.
VISUAL-SEVEIF, a tool for integrating fire behavior simulation and economic evaluation of the impact of Wildfires

Treesearch

Francisco Rodríguez y Silva; Juan Ramón Molina Martínez; Miguel Ángel Herrera Machuca; Jesús Mª Rodríguez Leal

2013-01-01

Progress made in recent years in fire science, particularly as applied to forest fire protection, coupled with the increased power offered by mathematical processors integrated into computers, has led to important developments in the field of dynamic and static simulation of forest fires. Furthermore, and similarly, econometric models applied to economic...
Effects of matrix shrinkage and swelling on the economics of enhanced-coalbed-methane production and CO{sub 2} sequestration in coal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorucu, F.B.; Jikich, S.A.; Bromhal, G.S.

2007-08-15

In this work, the Palmer-Mansoori model for coal shrinkage and permeability increases during primary methane production was rewritten to also account for coal swelling caused by CO{sub 2} sorption. The generalized model was added to a compositional, dual porosity coalbed-methane reservoir simulator for primary (CBM) and ECBM production. A standard five-spot of vertical wells and representative coal properties for Appalachian coals was used. Simulations and sensitivity analyses were performed with the modified simulator for nine different parameters, including coal seam and operational parameters and economic criteria. The coal properties and operating parameters that were varied included Young's modulus, Poisson's ratio,more » cleat porosity, and injection pressure. The economic variables included CH{sub 4}, price, Col Cost, CO{sub 2} credit, water disposal cost, and interest rate. Net-present value (NPV) analyses of the simulation results included profits resulting from CH{sub 4}, production and potential incentives for sequestered CO{sub 2}, This work shows that for some coal seams, the combination of compressibility, cleat porosity, and shrinkage/swelling of the coal may have a significant impact on project economics.« less
Using support vector machine to predict eco-environment burden: a case study of Wuhan, Hubei Province, China.

PubMed

Li, Xiang-Mei; Zhou, Jing-Xuan; Yuan, Song-Hu; Zhou, Xin-Ping; Fu, Qiang

2008-02-01

The human socio-economic development depends on the planet's natural capital. Humans have had a considerable impact on the earth, such as resources depression and environment deterioration. The objective of this study was to assess the impact of socio-economic development on the ecological environment of Wuhan, Hubei Province, China, during the general planning period 2006-2020. Support vector machine (SVM) model was constructed to simulate the process of eco-economic system of Wuhan. Socio-economic factors of urban total ecological footprint (TEF) were selected by partial least squares (PLS) and leave-one-out cross validation (LOOCV). Historical data of socio-economic factors as inputs, and corresponding historical data of TEF as target outputs, were presented to identify and validate the SVM model. When predicted input data after 2005 were presented to trained model as generalization sets, TEFs of 2005, 2006,..., till 2020 were simulated as output in succession. Up to 2020, the district would have suffered an accumulative TEF of 28.374 million gha, which was over 1.5 times that of 2004 and nearly 3 times that of 1988. The per capita EF would be up to 3.019 gha in 2020. The simulation indicated that although the increase rate of GDP would be restricted in a lower level during the general planning period, urban ecological environment burden could not respond to the socio-economic circumstances promptly. SVM provides tools for dynamic assessment of regional eco-environment. However, there still exist limitations and disadvantages in the model. We believe that the next logical step in deriving better dynamic models of ecosystem is to integrate SVM and other algorithms or technologies.
Simulating water markets with transaction costs

PubMed Central

Erfani, Tohid; Binions, Olga; Harou, Julien J

2014-01-01

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. Key Points Transaction tracking hydro-economic optimization models simulate water markets Proposed model formulation incorporates transaction costs and trading behavior Water markets benefit users with the most restricted water access PMID:25598558

Simulating water markets with transaction costs.

PubMed

Erfani, Tohid; Binions, Olga; Harou, Julien J

2014-06-01

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. Transaction tracking hydro-economic optimization models simulate water marketsProposed model formulation incorporates transaction costs and trading behaviorWater markets benefit users with the most restricted water access.
Modeling complex treatment strategies: construction and validation of a discrete event simulation model for glaucoma.

PubMed

van Gestel, Aukje; Severens, Johan L; Webers, Carroll A B; Beckers, Henny J M; Jansonius, Nomdo M; Schouten, Jan S A G

2010-01-01

Discrete event simulation (DES) modeling has several advantages over simpler modeling techniques in health economics, such as increased flexibility and the ability to model complex systems. Nevertheless, these benefits may come at the cost of reduced transparency, which may compromise the model's face validity and credibility. We aimed to produce a transparent report on the construction and validation of a DES model using a recently developed model of ocular hypertension and glaucoma. Current evidence of associations between prognostic factors and disease progression in ocular hypertension and glaucoma was translated into DES model elements. The model was extended to simulate treatment decisions and effects. Utility and costs were linked to disease status and treatment, and clinical and health economic outcomes were defined. The model was validated at several levels. The soundness of design and the plausibility of input estimates were evaluated in interdisciplinary meetings (face validity). Individual patients were traced throughout the simulation under a multitude of model settings to debug the model, and the model was run with a variety of extreme scenarios to compare the outcomes with prior expectations (internal validity). Finally, several intermediate (clinical) outcomes of the model were compared with those observed in experimental or observational studies (external validity) and the feasibility of evaluating hypothetical treatment strategies was tested. The model performed well in all validity tests. Analyses of hypothetical treatment strategies took about 30 minutes per cohort and lead to plausible health-economic outcomes. There is added value of DES models in complex treatment strategies such as glaucoma. Achieving transparency in model structure and outcomes may require some effort in reporting and validating the model, but it is feasible.
Population, internal migration, and economic growth: an empirical analysis.

PubMed

Moreland, R S

1982-01-01

The role of population growth in the development process has received increasing attention during the last 15 years, as manifested in the literature in 3 broad categories. In the 1st category, the effects of rapid population growth on the growth of income have been studied with the use of simulation models, which sometimes include endogenous population growth. The 2nd category of the literature is concerned with theoretical and empirical studies of the economic determinants of various demographic rates--most usually fertility. Internal migration and dualism is the 3rd population development category to recieve attention. An attempt is made to synthesize developments in these 3 categories by estimating from a consistent set of data a 2 sector economic demographic model in which the major demographic rates are endogenous. Due to the fact that the interactions between economic and demographic variables are nonlinear and complex, the indirect effects of changes in a particular variable may depend upon the balance of numerical coefficients. For this reason it was felt that the model should be empirically grounded. A brief overview of the model is provided, and the model is compared to some similar existing models. Estimation of the model's 9 behavior equations is discussed, followed by a "base run" simulation of a developing country "stereotype" and a report of a number of policy experiments. The relatively new field of economic determinants of demographic variables was drawn upon in estimating equations to endogenize demographic phenomena that are frequently left exogenous in simulation models. The fertility and labor force participation rate functions are fairly standard, but a step beyong existing literature was taken in the life expectancy and intersectorial migration equations. On the economic side, sectoral savings functions were estimated, and it was found that the marginal propensity to save is lower in agriculture than in nonagriculture. Testing to see the effect of a population's age structure on savings rather than assuming a particular direction as Coale-Hoover and Simon do in their models, it was found that a higher proportion of children compete with savings in agriculture but complement savings in industrial areas. This was consistent with the economic value of children in agricultural and nonagricultural regions of less developed countries. The estimated production functions showed that marginal products of labor were considerably higher in agriculture than in nonagriculture. As with other simulation models, the effect of reducing fertility was to accelerate income growth. Reductions in rural fertility were more equitable and raised the overall level of per capita income more than similar efforts directed to urban areas only.
Statistical power of intervention analyses: simulation and empirical application to treated lumber prices

Treesearch

Jeffrey P. Prestemon

2009-01-01

Timber product markets are subject to large shocks deriving from natural disturbances and policy shifts. Statistical modeling of shocks is often done to assess their economic importance. In this article, I simulate the statistical power of univariate and bivariate methods of shock detection using time series intervention models. Simulations show that bivariate methods...
Economic impacts of climate change on water resources in the coterminous United States

EPA Science Inventory

A national-scale simulation-optimization model was created to generate estimates of economic impacts associated with changes in water supply and demand as influenced by climate change. Water balances were modeled for the 99 assessment sub-regions, and are presented for 18 water r...
Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563
Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.
Simulating economic effects of disruptions in the telecommunications infrastructure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Roger Gary; Barton, Dianne Catherine; Reinert, Rhonda K.

2004-01-01

CommAspen is a new agent-based model for simulating the interdependent effects of market decisions and disruptions in the telecommunications infrastructure on other critical infrastructures in the U.S. economy such as banking and finance, and electric power. CommAspen extends and modifies the capabilities of Aspen-EE, an agent-based model previously developed by Sandia National Laboratories to analyze the interdependencies between the electric power system and other critical infrastructures. CommAspen has been tested on a series of scenarios in which the communications network has been disrupted, due to congestion and outages. Analysis of the scenario results indicates that communications networks simulated by themore » model behave as their counterparts do in the real world. Results also show that the model could be used to analyze the economic impact of communications congestion and outages.« less
Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.
Simulating forage crop production in a northern climate with the Integrated Farm System Model

USDA-ARS?s Scientific Manuscript database

Whole-farm simulation models are useful tools for evaluating the effect of management practices and climate variability on the agro-environmental and economic performance of farms. A few process-based farm-scale models have been developed, but none have been evaluated in a northern region with a sho...
A Mathematical Model of Economic Population Dynamics in a Country That Has Optimal Zakat Management

NASA Astrophysics Data System (ADS)

Subhan, M.

2018-04-01

Zakat is the main tools against two issues in Islamic economy: economic justice and helping the poor. However, no government of Islamic countries can solve the economic disparity today. A mathematical model could give some understanding about this phenomenon. The goal of this research is to obtain a mathematical model that can describe the dynamic of economic group population. The research is theoretical based on relevance references. From the analytical and numerical simulation, we conclude that well-manage zakat and full comitment of the wealthy can achieve wealth equilibrium that represents minimum poverty.
Simulation of economic agents interaction in a trade chain

NASA Astrophysics Data System (ADS)

Gimanova, I. A.; Dulesov, A. S.; Litvin, N. V.

2017-01-01

The mathematical model of economic agents interaction is offered in the work. It allowsconsidering the change of price and sales volumesin dynamics according to the process of purchase and sale in the single-product market of the trade and intermediary network. The description of data-flow processes is based on the use of the continuous dynamic market model. The application of ordinary differential equations during the simulation allows one to define areas of coefficients - characteristics of agents - and to investigate their interaction in a chain on stability.
Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions

USDA-ARS?s Scientific Manuscript database

A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting fram...
Economic Theory and Management Games II.

ERIC Educational Resources Information Center

Zernik, Wolfgang

1988-01-01

Description of management games continues a previous article's discussion of how mathematical modeling and microeconomic concepts can be used by players. Highlights include an initial condition simulating a profit-maximizing monopoly; simulating the transition from monopoly to oligopoly; and how mathematical properties of the model affect final…
Spatial Analysis of Biomass Supply: Economic and Environmental Impacts

USDA-ARS?s Scientific Manuscript database

The EPIC simulation model is used with SSURGO soils, field location information, and a transportation cost model to analyze potential biomass supply for a West Central MN bioenergy plant. The simulation shows the relationship between biomass price, locations of where biomass production is profitable...
Assessing the potential of economic instruments for managing drought risk at river basin scale

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Lopez-Nicolas, A.; Macian-Sorribes, H.

2015-12-01

Economic instruments work as incentives to adapt individual decisions to collectively agreed goals. Different types of economic instruments have been applied to manage water resources, such as water-related taxes and charges (water pricing, environmental taxes, etc.), subsidies, markets or voluntary agreements. Hydroeconomic models (HEM) provide useful insight on optimal strategies for coping with droughts by simultaneously analysing engineering, hydrology and economics of water resources management. We use HEMs for evaluating the potential of economic instruments on managing drought risk at river basin scale, considering three criteria for assessing drought risk: reliability, resilience and vulnerability. HEMs allow to calculate water scarcity costs as the economic losses due to water deliveries below the target demands, which can be used as a vulnerability descriptor of drought risk. Two generic hydroeconomic DSS tools, SIMGAMS and OPTIGAMS ( both programmed in GAMS) have been developed to evaluate water scarcity cost at river basin scale based on simulation and optimization approaches. The simulation tool SIMGAMS allocates water according to the system priorities and operating rules, and evaluate the scarcity costs using economic demand functions. The optimization tool allocates water resources for maximizing net benefits (minimizing total water scarcity plus operating cost of water use). SIMGAS allows to simulate incentive water pricing policies based on water availability in the system (scarcity pricing), while OPTIGAMS is used to simulate the effect of ideal water markets by economic optimization. These tools have been applied to the Jucar river system (Spain), highly regulated and with high share of water use for crop irrigation (greater than 80%), where water scarcity, irregular hydrology and groundwater overdraft cause droughts to have significant economic, social and environmental consequences. An econometric model was first used to explain the variation of the production value of irrigated agriculture during droughts, assessing revenue responses to varying crop prices and water availability. Hydroeconomic approaches were then used to show the potential of economic instruments in setting incentives for a more efficient management of water resources systems.
Evaluating the economic damages of transport disruptions using a transnational and interregional input-output model for Japan, China, and South Korea

NASA Astrophysics Data System (ADS)

Irimoto, Hiroshi; Shibusawa, Hiroyuki; Miyata, Yuzuru

2017-10-01

Damage to transportation networks as a result of natural disasters can lead to economic losses due to lost trade along those links in addition to the costs of damage to the infrastructure itself. This study evaluates the economic damages of transport disruptions such as highways, tunnels, bridges, and ports using a transnational and interregional Input-Output Model that divides the world into 23 regions: 9 regions in Japan, 7 regions in China, and 4 regions in Korea, Taiwan, ASEAN5, and the USA to allow us to focus on Japan's regional and international links. In our simulation, economic ripple effects of both international and interregional transport disruptions are measured by changes in the trade coefficients in the input-output model. The simulation showed that, in the case of regional links in Japan, a transport disruption in the Kanmon Straits causes the most damage to our targeted world, resulting in economic damage of approximately 36.3 billion. In the case of international links among Japan, China, and Korea, damage to the link between Kanto in Japan and Huabei in China causes economic losses of approximately 31.1 billion. Our result highlights the importance of disaster prevention in the Kanmon Straits, Kanto, and Huabei to help ensure economic resilience.
Modelling the role of forests on water provision services: a hydro-economic valuation approach

NASA Astrophysics Data System (ADS)

Beguería, S.; Campos, P.

2015-12-01

Hydro-economic models that allow integrating the ecological, hydrological, infrastructure, economic and social aspects into a coherent, scientifically- informed framework constitute preferred tools for supporting decision making in the context of integrated water resources management. We present a case study of water regulation and provision services of forests in the Andalusia region of Spain. Our model computes the physical water flows and conducts an economic environmental income and asset valuation of forest surface and underground water yield. Based on available hydrologic and economic data, we develop a comprehensive water account for all the forest lands at the regional scale. This forest water environmental valuation is integrated within a much larger project aiming at providing a robust and easily replicable accounting tool to evaluate yearly the total income and capital of forests, encompassing all measurable sources of private and public incomes (timber and cork production, auto-consumption, recreational activities, biodiversity conservation, carbon sequestration, water production, etc.). We also force our simulation with future socio-economic scenarios to quantify the physical and economic efects of expected trends or simulated public and private policies on future water resources. Only a comprehensive integrated tool may serve as a basis for the development of integrated policies, such as those internationally agreed and recommended for the management of water resources.
Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, J.; Prskawetz, A.; Grass, D.; Blöschl, G.

2015-06-01

Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.
Modeling the clinical and economic implications of obesity using microsimulation.

PubMed

Su, W; Huang, J; Chen, F; Iacobucci, W; Mocarski, M; Dall, T M; Perreault, L

2015-01-01

The obesity epidemic has raised considerable public health concerns, but there are few validated longitudinal simulation models examining the human and economic cost of obesity. This paper describes a microsimulation model as a comprehensive tool to understand the relationship between body weight, health, and economic outcomes. Patient health and economic outcomes were simulated annually over 10 years using a Markov-based microsimulation model. The obese population examined is nationally representative of obese adults in the US from the 2005-2012 National Health and Nutrition Examination Surveys, while a matched normal weight population was constructed to have similar demographics as the obese population during the same period. Prediction equations for onset of obesity-related comorbidities, medical expenditures, economic outcomes, mortality, and quality-of-life came from published trials and studies supplemented with original research. Model validation followed International Society for Pharmacoeconomics and Outcomes Research practice guidelines. Among surviving adults, relative to a matched normal weight population, obese adults averaged $3900 higher medical expenditures in the initial year, growing to $4600 higher expenditures in year 10. Obese adults had higher initial prevalence and higher simulated onset of comorbidities as they aged. Over 10 years, excess medical expenditures attributed to obesity averaged $4280 annually-ranging from $2820 for obese category I to $5100 for obese category II, and $8710 for obese category III. Each excess kilogram of weight contributed to $140 higher annual costs, on average, ranging from $136 (obese I) to $152 (obese III). Poor health associated with obesity increased work absenteeism and mortality, and lowered employment probability, personal income, and quality-of-life. This validated model helps illustrate why obese adults have higher medical and indirect costs relative to normal weight adults, and shows that medical costs for obese adults rise more rapidly with aging relative to normal weight adults.

Using Discrete Event Simulation to Model the Economic Value of Shorter Procedure Times on EP Lab Efficiency in the VALUE PVI Study.

PubMed

Kowalski, Marcin; DeVille, J Brian; Svinarich, J Thomas; Dan, Dan; Wickliffe, Andrew; Kantipudi, Charan; Foell, Jason D; Filardo, Giovanni; Holbrook, Reece; Baker, James; Baydoun, Hassan; Jenkins, Mark; Chang-Sing, Peter

2016-05-01

The VALUE PVI study demonstrated that atrial fibrillation (AF) ablation procedures and electrophysiology laboratory (EP lab) occupancy times were reduced for the cryoballoon compared with focal radiofrequency (RF) ablation. However, the economic impact associated with the cryoballoon procedure for hospitals has not been determined. Assess the economic value associated with shorter AF ablation procedure times based on VALUE PVI data. A model was formulated from data from the VALUE PVI study. This model used a discrete event simulation to translate procedural efficiencies into metrics utilized by hospital administrators. A 1000-day period was simulated to determine the accrued impact of procedure time on an institution's EP lab when considering staff and hospital resources. The simulation demonstrated that procedures performed with the cryoballoon catheter resulted in several efficiencies, including: (1) a reduction of 36.2% in days with overtime (422 days RF vs 60 days cryoballoon); (2) 92.7% less cumulative overtime hours (370 hours RF vs 27 hours cryoballoon); and (3) an increase of 46.7% in days with time for an additional EP lab usage (186 days RF vs 653 days cryoballoon). Importantly, the added EP lab utilization could not support the time required for an additional AF ablation procedure. The discrete event simulation of the VALUE PVI data demonstrates the potential positive economic value of AF ablation procedures using the cryoballoon. These benefits include more days where overtime is avoided, fewer cumulative overtime hours, and more days with time left for additional usage of EP lab resources.
A dynamic simulation model for analyzing the importance of forest resources in Alaska.

Treesearch

Wilbur R. Maki; Douglas Olson; Con H. Schallau

1985-01-01

A dynamic simulation model has been adapted for use in Alaska. It provides a flexible tool for examining the economic consequences of alternative forest resource management policies. The model could be adapted for use elsewhere if an interindustry transaction table is available or can be developed. To demonstrate the model's usefulness, the contribution of the...
Calibrating and Updating the Global Forest Products Model (GFPM version 2014 with BPMPD)

Treesearch

Joseph Buongiorno; Shushuai Zhu

2014-01-01

The Global Forest Products Model (GFPM) is an economic model of global production, consumption, and trade of forest products. An earlier version of the model is described in Buongiorno et al. (2003). The GFPM 2014 has data and parameters to simulate changes of the forest sector from 2010 to 2030. Buongiorno and Zhu (2014) describe how to use the model for simulation....
Assessing the agricultural costs of climate change: Combining results from crop and economic models

NASA Astrophysics Data System (ADS)

Howitt, R. E.

2016-12-01

Any perturbation to a resource system used by humans elicits both technical and behavioral changes. For agricultural production, economic criteria and their associated models are usually good predictors of human behavior in agricultural production. Estimation of the agricultural costs of climate change requires careful downscaling of global climate models to the level of agricultural regions. Plant growth models for the dominant crops are required to accurately show the full range of trade-offs and adaptation mechanisms needed to minimize the cost of climate change. Faced with the shifts in the fundamental resource base of agriculture, human behavior can either exacerbate or offset the impact of climate change on agriculture. In addition, agriculture can be an important source of increased carbon sequestration. However the effectiveness and timing of this sequestration depends on agricultural practices and farmer behavior. Plant growth models and economic models have been shown to interact in two broad fashions. First there is the direct embedding of a parametric representation plant growth simulations in the economic model production function. A second and more general approach is to have plant growth and crop process models interact with economic models as they are simulated. The development of more general wrapper programs that transfer information between models rapidly and efficiently will encourage this approach. However, this method does introduce complications in terms of matching up disparate scales both in time and space between models. Another characteristic behavioral response of agricultural production is the distinction between the intensive margin which considers the quantity of resource, for example fertilizer, used for a given crop, and the extensive margin of adjustment that measures how farmers will adjust their crop proportions in response to climate change. Ideally economic models will measure the response to both these margins of adjustment simultaneously. The paper will briefly discuss some examples of the direct embedding of results from plant growth models in economic models.
Integrating uncertainties to the combined environmental and economic assessment of algal biorefineries: A Monte Carlo approach.

PubMed

Pérez-López, Paula; Montazeri, Mahdokht; Feijoo, Gumersindo; Moreira, María Teresa; Eckelman, Matthew J

2018-06-01

The economic and environmental performance of microalgal processes has been widely analyzed in recent years. However, few studies propose an integrated process-based approach to evaluate economic and environmental indicators simultaneously. Biodiesel is usually the single product and the effect of environmental benefits of co-products obtained in the process is rarely discussed. In addition, there is wide variation of the results due to inherent variability of some parameters as well as different assumptions in the models and limited knowledge about the processes. In this study, two standardized models were combined to provide an integrated simulation tool allowing the simultaneous estimation of economic and environmental indicators from a unique set of input parameters. First, a harmonized scenario was assessed to validate the joint environmental and techno-economic model. The findings were consistent with previous assessments. In a second stage, a Monte Carlo simulation was applied to evaluate the influence of variable and uncertain parameters in the model output, as well as the correlations between the different outputs. The simulation showed a high probability of achieving favorable environmental performance for the evaluated categories and a minimum selling price ranging from $11gal -1 to $106gal -1 . Greenhouse gas emissions and minimum selling price were found to have the strongest positive linear relationship, whereas eutrophication showed weak correlations with the other indicators (namely greenhouse gas emissions, cumulative energy demand and minimum selling price). Process parameters (especially biomass productivity and lipid content) were the main source of variation, whereas uncertainties linked to the characterization methods and economic parameters had limited effect on the results. Copyright © 2018 Elsevier B.V. All rights reserved.
Assessing groundwater policy with coupled economic-groundwater hydrologic modeling

NASA Astrophysics Data System (ADS)

Mulligan, Kevin B.; Brown, Casey; Yang, Yi-Chen E.; Ahlfeld, David P.

2014-03-01

This study explores groundwater management policies and the effect of modeling assumptions on the projected performance of those policies. The study compares an optimal economic allocation for groundwater use subject to streamflow constraints, achieved by a central planner with perfect foresight, with a uniform tax on groundwater use and a uniform quota on groundwater use. The policies are compared with two modeling approaches, the Optimal Control Model (OCM) and the Multi-Agent System Simulation (MASS). The economic decision models are coupled with a physically based representation of the aquifer using a calibrated MODFLOW groundwater model. The results indicate that uniformly applied policies perform poorly when simulated with more realistic, heterogeneous, myopic, and self-interested agents. In particular, the effects of the physical heterogeneity of the basin and the agents undercut the perceived benefits of policy instruments assessed with simple, single-cell groundwater modeling. This study demonstrates the results of coupling realistic hydrogeology and human behavior models to assess groundwater management policies. The Republican River Basin, which overlies a portion of the Ogallala aquifer in the High Plains of the United States, is used as a case study for this analysis.
Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice.

PubMed

O'Mahony, James F; Newall, Anthony T; van Rosmalen, Joost

2015-12-01

Time is an important aspect of health economic evaluation, as the timing and duration of clinical events, healthcare interventions and their consequences all affect estimated costs and effects. These issues should be reflected in the design of health economic models. This article considers three important aspects of time in modelling: (1) which cohorts to simulate and how far into the future to extend the analysis; (2) the simulation of time, including the difference between discrete-time and continuous-time models, cycle lengths, and converting rates and probabilities; and (3) discounting future costs and effects to their present values. We provide a methodological overview of these issues and make recommendations to help inform both the conduct of cost-effectiveness analyses and the interpretation of their results. For choosing which cohorts to simulate and how many, we suggest analysts carefully assess potential reasons for variation in cost effectiveness between cohorts and the feasibility of subgroup-specific recommendations. For the simulation of time, we recommend using short cycles or continuous-time models to avoid biases and the need for half-cycle corrections, and provide advice on the correct conversion of transition probabilities in state transition models. Finally, for discounting, analysts should not only follow current guidance and report how discounting was conducted, especially in the case of differential discounting, but also seek to develop an understanding of its rationale. Our overall recommendations are that analysts explicitly state and justify their modelling choices regarding time and consider how alternative choices may impact on results.
Economic and financial viability of small-scale dairy systems in central Mexico: economic scenario 2010-2018.

PubMed

Posadas-Domínguez, R R; Callejas-Juárez, N; Arriaga-Jordán, C M; Martínez-Castañeda, F E

2016-12-01

A simulation Monte Carlo model was used to assess the economic and financial viability of 130 small-scale dairy farms in central Mexico, through a Representative Small-Scale Dairy Farm. Net yields were calculated for a 9-year planning horizon by means of simulated values for the distribution of input and product prices taking 2010 as base year and considering four scenarios which were compared against the scenario of actual production. The other scenarios were (1) total hiring in of needed labour; (2) external purchase of 100 % of inputs and (3) withdrawal of subsidies to production. A stochastic modelling approach was followed to determine the scenario with the highest economic and financial viability. Results show a viable economic and financial situation for the real production scenario, as well as the scenarios for total hiring of labour and of withdrawal of subsidies, but the scenario when 100 % of feed inputs for the herd are bought-in was not viable.
Folgen des Globalen Wandels für das Grundwasser in Süddeutschland - Teil 2: Sozioökonomische Aspekte

NASA Astrophysics Data System (ADS)

Barthel, Roland; Krimly, Tatjana; Elbers, Michael; Soboll, Anja; Wackerbauer, Johann; Hennicker, Rolf; Janisch, Stephan; Reichenau, Tim G.; Dabbert, Stephan; Schmude, Jürgen; Ernst, Andreas; Mauser, Wolfram

2011-12-01

In order to account for complex interactions between humans climate and the water cycle, the research consortium GLOWA-Danube (www.glowa-danube.de) has developed the simulation system DANUBIA which consists of 17 coupled models. DANUBIA was applied to investigate various impacts of global-change between 2011 and 2060 in the Upper Danube Catchment. This article describes part 2 of an article series with investigations of socio-economic aspects, while part 1 (Barthel et al. in Grundwasser 16(4), doi:10.1007/s007-011-01794, 2011) deals with natural-spatial aspects. The principles of socio-economic actor-modeling and interactions between socio-economic and natural science model components are described here. We present selected simulations that show impacts on groundwater from changes in agriculture, tourism, economy, domestic water users and water supply. Despite decreases in water consumption, the scenario simulations show significant decreases in groundwater quantity. On the other hand, groundwater quality will likely be influenced more severely by land use changes compared to direct climatic causes. However, overall changes will not be dramatic.
Obesity trend in the United States and economic intervention options to change it: A simulation study linking ecological epidemiology and system dynamics modeling.

PubMed

Chen, H-J; Xue, H; Liu, S; Huang, T T K; Wang, Y C; Wang, Y

2018-05-29

To study the country-level dynamics and influences between population weight status and socio-economic distribution (employment status and family income) in the US and to project the potential impacts of socio-economic-based intervention options on obesity prevalence. Ecological study and simulation. Using the longitudinal data from the 2001-2011 Medical Expenditure Panel Survey (N = 88,453 adults), we built and calibrated a system dynamics model (SDM) capturing the feedback loops between body weight status and socio-economic status distribution and simulated the effects of employment- and income-based intervention options. The SDM-based simulation projected rising overweight/obesity prevalence in the US in the future. Improving people's income from lower to middle-income group would help control the rising prevalence, while only creating jobs for the unemployed did not show such effect. Improving people from low- to middle-income levels may be effective, instead of solely improving reemployment rate, in curbing the rising obesity trend in the US adult population. This study indicates the value of the SDM as a virtual laboratory to evaluate complex distributive phenomena of the interplay between population health and economy. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
FEES: design of a Fire Economics Evaluation System

Treesearch

Thomas J. Mills; Frederick W. Bratten

1982-01-01

The Fire Economics Evaluation System (FEES)--a simulation model--is being designed for long-term planning application by all public agencies with wildland fire management responsibilities. A fully operational version of FEES will be capable of estimating the economic efficiency, fire-induced changes in resource outputs, and risk characteristics of a range of fire...
Efficient Monte Carlo Estimation of the Expected Value of Sample Information Using Moment Matching.

PubMed

Heath, Anna; Manolopoulou, Ioanna; Baio, Gianluca

2018-02-01

The Expected Value of Sample Information (EVSI) is used to calculate the economic value of a new research strategy. Although this value would be important to both researchers and funders, there are very few practical applications of the EVSI. This is due to computational difficulties associated with calculating the EVSI in practical health economic models using nested simulations. We present an approximation method for the EVSI that is framed in a Bayesian setting and is based on estimating the distribution of the posterior mean of the incremental net benefit across all possible future samples, known as the distribution of the preposterior mean. Specifically, this distribution is estimated using moment matching coupled with simulations that are available for probabilistic sensitivity analysis, which is typically mandatory in health economic evaluations. This novel approximation method is applied to a health economic model that has previously been used to assess the performance of other EVSI estimators and accurately estimates the EVSI. The computational time for this method is competitive with other methods. We have developed a new calculation method for the EVSI which is computationally efficient and accurate. This novel method relies on some additional simulation so can be expensive in models with a large computational cost.
PLYMAP : a computer simulation model of the rotary peeled softwood plywood manufacturing process

Treesearch

Henry Spelter

1990-01-01

This report documents a simulation model of the plywood manufacturing process. Its purpose is to enable a user to make quick estimates of the economic impact of a particular process change within a mill. The program was designed to simulate the processing of plywood within a relatively simplified mill design. Within that limitation, however, it allows a wide range of...
Numerical Simulation Of Silicon-Ribbon Growth

NASA Technical Reports Server (NTRS)

Woda, Ben K.; Kuo, Chin-Po; Utku, Senol; Ray, Sujit Kumar

1987-01-01

Mathematical model includes nonlinear effects. In development simulates growth of silicon ribbon from melt. Takes account of entire temperature and stress history of ribbon. Numerical simulations performed with new model helps in search for temperature distribution, pulling speed, and other conditions favoring growth of wide, flat, relatively defect-free silicon ribbons for solar photovoltaic cells at economically attractive, high production rates. Also applicable to materials other than silicon.
Stochastic representation of fire behavior in a wildland fire protection planning model for California.

Treesearch

J. Keith Gilless; Jeremy S. Fried

1998-01-01

A fire behavior module was developed for the California Fire Economics Simulator version 2 (CFES2), a stochastic simulation model of initial attack on wildland fire used by the California Department of Forestry and Fire Protection. Fire rate of spread (ROS) and fire dispatch level (FDL) for simulated fires "occurring" on the same day are determined by making...
A water market simulator considering pair-wise trades between agents

NASA Astrophysics Data System (ADS)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.
[Modeling in value-based medicine].

PubMed

Neubauer, A S; Hirneiss, C; Kampik, A

2010-03-01

Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.
Achieving Sustainability in a Semi-Arid Basin in Northwest Mexico through an Integrated Hydrologic-Economic-Institutional Model

NASA Astrophysics Data System (ADS)

Munoz-Hernandez, A.; Mayer, A. S.

2008-12-01

The hydrologic systems in Northwest Mexico are at risk of over exploitation due to poor management of the water resources and adverse climatic conditions. The purpose of this work is to create and Integrated Hydrologic-Economic-Institutional Model to support future development in the Yaqui River basin, well known by its agricultural productivity, by directing the water management practices toward sustainability. The Yaqui River basin is a semi-arid basin with an area of 72,000 square kilometers and an average precipitation of 527 mm per year. The primary user of water is agriculture followed by domestic use and industry. The water to meet user demands comes from three reservoirs constructed, in series, along the river. The main objective of the integrated simulation-optimization model is to maximize the economic benefit within the basin, subject to physical and environmental constraints. Decision variables include the water allocation to major users and reservoirs as well as aquifer releases. Economic and hydrologic (including the interaction of the surface water and groundwater) simulation models were both included in the integrated model. The surface water model refers to a rainfall-runoff model created, calibrated, and incorporated into a MATLAB code that estimates the monthly storage in the main reservoirs by solving a water balance. The rainfall-runoff model was coupled with a groundwater model of the Yaqui Valley which was previously developed (Addams, 2004). This model includes flow in the main canals and infiltration to the aquifer. The economic benefit of water for some activities such as agricultural use, domestic use, hydropower generation, and environmental value was determined. Sensitivity analysis was explored for those parameters that are not certain such as price elasticities or population growth. Different water allocation schemes were created based on climate change, climate variability, and socio-economic scenarios. Addams L. 2004. Water resource policy evaluation using a combined hydrologic-economic-agronomic modeling framework: Yaqui Valley, Sonora, Mexico. Ph.D.dissertation, Stanford University.
Trade-offs between maintenance of ecosystem services and socio-economic development in rural mountainous communities in southern Spain: a dynamic simulation approach.

PubMed

Vidal-Legaz, Beatriz; Martínez-Fernández, Julia; Picón, Andrés Sánchez; Pugnaire, Francisco I

2013-12-15

Mountainous rural communities have traditionally managed their land extensively, resulting in land uses that provide important ecosystem services for both rural and urban areas. Over recent decades, these communities have undergone drastic changes in economic structure, population size and land use. Our understanding of the exact mechanisms that drive these changes is limited, and there is also a lack of integrative approaches to enable decision makers to steer rural development towards a more sustainable path. In this study, we build a dynamic simulation model to calculate the trade-offs between the provisions of two ecosystem services - landscape aesthetic value and water supply for human use - and the economic development associated with different land use changes. The study area for the simulation comprises two rural communities located in southern Spain. Our results show trade-offs between economic development and the provision of the selected ecosystem services in the selected study area. Land use intensification results in economic development but is not enough to prevent population loss and has a negative impact on both the water supply and on aesthetic services. We conclude that more proactive management policies are needed to mitigate a loss in ecosystem services. Simulation models like ours may facilitate the choice of these policies, as they could test the result of land use planning policies contributing therefore, to a more integrative and sustainable management of rural communities. Copyright © 2013 Elsevier Ltd. All rights reserved.
Modelling the economic impact of three lameness causing diseases using herd and cow level evidence.

PubMed

Ettema, Jehan; Østergaard, Søren; Kristensen, Anders Ringgaard

2010-06-01

Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways. First of all, three underlying diseases causing lameness were modelled: digital dermatitis, interdigital hyperplasia and claw horn diseases. Secondly, the existing simulation model was set-up in way that it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows, marginal posterior probability distributions for disease prevalence in the specific herd are created in a Bayesian network. Random draws from these distributions are used by the simulation model to describe disease risk. Hereby field data on prevalence is used systematically and uncertainty around herd specific risk is represented. Besides the fact that estimated profitability of halving disease risk depended on the hyper-distributions used, the estimates differed for herds with different levels of diseases risk and reproductive efficiency. (c) 2010 Elsevier B.V. All rights reserved.

Simulation of diurnal thermal energy storage systems: Preliminary results

NASA Astrophysics Data System (ADS)

Katipamula, S.; Somasundaram, S.; Williams, H. R.

1994-12-01

This report describes the results of a simulation of thermal energy storage (TES) integrated with a simple-cycle gas turbine cogeneration system. Integrating TES with cogeneration can serve the electrical and thermal loads independently while firing all fuel in the gas turbine. The detailed engineering and economic feasibility of diurnal TES systems integrated with cogeneration systems has been described in two previous PNL reports. The objective of this study was to lay the ground work for optimization of the TES system designs using a simulation tool called TRNSYS (TRaNsient SYstem Simulation). TRNSYS is a transient simulation program with a sequential-modular structure developed at the Solar Energy Laboratory, University of Wisconsin-Madison. The two TES systems selected for the base-case simulations were: (1) a one-tank storage model to represent the oil/rock TES system; and (2) a two-tank storage model to represent the molten nitrate salt TES system. Results of the study clearly indicate that an engineering optimization of the TES system using TRNSYS is possible. The one-tank stratified oil/rock storage model described here is a good starting point for parametric studies of a TES system. Further developments to the TRNSYS library of available models (economizer, evaporator, gas turbine, etc.) are recommended so that the phase-change processes is accurately treated.
Effect of External Economic-Field Cycle and Market Temperature on Stock-Price Hysteresis: Monte Carlo Simulation on the Ising Spin Model

NASA Astrophysics Data System (ADS)

Punya Jaroenjittichai, Atchara; Laosiritaworn, Yongyut

2017-09-01

In this work, the stock-price versus economic-field hysteresis was investigated. The Ising spin Hamiltonian was utilized as the level of ‘disagreement’ in describing investors’ behaviour. The Ising spin directions were referred to an investor’s intention to perform his action on trading his stock. The periodic economic variation was also considered via the external economic-field in the Ising model. The stochastic Monte Carlo simulation was performed on Ising spins, where the steady-state excess demand and supply as well as the stock-price were extracted via the magnetization. From the results, the economic-field parameters and market temperature were found to have significant effect on the dynamic magnetization and stock-price behaviour. Specifically, the hysteresis changes from asymmetric to symmetric loops with increasing market temperature and economic-field strength. However, the hysteresis changes from symmetric to asymmetric loops with increasing the economic-field frequency, when either temperature or economic-field strength is large enough, and returns to symmetric shape at very high frequencies. This suggests competitive effects among field and temperature factors on the hysteresis characteristic, implying multi-dimensional complicated non-trivial relationship among inputs-outputs. As is seen, the results reported (over extensive range) can be used as basis/guideline for further analysis/quantifying how economic-field and market-temperature affect the stock-price distribution on the course of economic cycle.
An economic analysis of life expectancy by gender with application to the United States.

PubMed

Leung, Michael C M; Zhang, Jie; Zhang, Junsen

2004-07-01

This paper presents an economic model to explain the behavior of life expectancy of both sexes. It explicitly examines the relationship between the gender gap in life expectancy and the gender gap in pay. It shows that as the latter narrows over the course of economic development, the former may initially expand but will eventually shrink. Simulation results from our model accord with the behavior of life expectancy for both sexes since the 1940s in the United States.
Economic impacts of climate change on agriculture: the AgMIP approach

NASA Astrophysics Data System (ADS)

Delincé, Jacques; Ciaian, Pavel; Witzke, Heinz-Peter

2015-01-01

The current paper investigates the long-term global impacts on crop productivity under different climate scenarios using the AgMIP approach (Agricultural Model Intercomparison and Improvement Project). The paper provides horizontal model intercomparison from 11 economic models as well as a more detailed analysis of the simulated effects from the Common Agricultural Policy Regionalized Impact (CAPRI) model to systematically compare its performance with other AgMIP models and specifically for the Chinese agriculture. CAPRI is a comparative static partial equilibrium model extensively used for medium and long-term economic and environmental policy impact applications. The results indicate that, at the global level, the climate change will cause an agricultural productivity decrease (between -2% and -15% by 2050), a food price increase (between 1.3% and 56%) and an expansion of cultivated area (between 1% and 4%) by 2050. The results for China indicate that the climate change effects tend to be smaller than the global impacts. The CAPRI-simulated effects are, in general, close to the median across all AgMIP models. Model intercomparison analyses reveal consistency in terms of direction of change to climate change but relatively strong heterogeneity in the magnitude of the effects between models.
Development of the Mathematics of Learning Curve Models for Evaluating Small Modular Reactor Economics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harrison, Thomas J.

2014-03-01

This report documents the efforts to perform dynamic model validation on the Eastern Interconnection (EI) by modeling governor deadband. An on-peak EI dynamic model is modified to represent governor deadband characteristics. Simulation results are compared with synchrophasor measurements collected by the Frequency Monitoring Network (FNET/GridEye). The comparison shows that by modeling governor deadband the simulated frequency response can closely align with the actual system response.
Development of an integrated economic and ecological framework for ecosystem-based fisheries management in New England

NASA Astrophysics Data System (ADS)

Jin, D.; Hoagland, P.; Dalton, T. M.; Thunberg, E. M.

2012-09-01

We present an integrated economic-ecological framework designed to help assess the implementation of ecosystem-based fisheries management (EBFM) in New England. We develop the framework by linking a computable general equilibrium (CGE) model of a coastal economy to an end-to-end (E2E) model of a marine food web for Georges Bank. We focus on the New England region using coastal county economic data for a restricted set of industry sectors and marine ecological data for three top level trophic feeding guilds: planktivores, benthivores, and piscivores. We undertake numerical simulations to model the welfare effects of changes in alternative combinations of yields from feeding guilds and alternative manifestations of biological productivity. We estimate the economic and distributional effects of these alternative simulations across a range of consumer income levels. This framework could be used to extend existing methodologies for assessing the impacts on human communities of groundfish stock rebuilding strategies, such as those expected through the implementation of the sector management program in the US northeast fishery. We discuss other possible applications of and modifications and limitations to the framework.
Policy changes to implement intramural sports in North Carolina middle schools: simulated effects on sports participation rates and physical activity intensity, 2008-2009.

PubMed

Edwards, Michael B; Kanters, Michael A; Bocarro, Jason N

2014-01-16

Extracurricular school sports programs can provide adolescents, including those who are economically disadvantaged, with opportunities to engage in physical activity. Although current models favor more exclusionary interscholastic sports, a better understanding is needed of the potential effects of providing alternative school sports options, such as more inclusive intramural sports. The purpose of this study was to simulate the potential effect of implementing intramural sports programs in North Carolina middle schools on both the rates of sports participation and on energy expenditure related to physical activity levels. Simulations were conducted by using a school-level data set developed by integrating data from multiple sources. Baseline rates of sports participation were extrapolated from individual-level data that were based on school-level characteristics. A regression model was estimated by using the simulated baseline school-level sample. Participation rates and related energy expenditure for schools were calculated on the basis of 2 policy change scenarios. Currently, 37.2% of school sports participants are economically disadvantaged. Simulations suggested that policy changes to implement intramural sports along with interscholastic sports could result in more than 43,000 new sports participants statewide, of which 64.5% would be economically disadvantaged students. This estimate represents a 36.75% increase in economically disadvantaged participants. Adding intramural sports to existing interscholastic sports programs at all middle schools in North Carolina could have an annual effect of an additional 819,892.65 kilogram calories expended statewide. Implementing intramural sports may provide economically disadvantaged students more access to sports, thus reducing disparities in access to school sports while increasing overall physical activity levels among all children.
System-level modeling for economic evaluation of geological CO2storage in gas reservoirs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yingqi; Oldenburg, Curtis M.; Finsterle, Stefan

2006-03-02

One way to reduce the effects of anthropogenic greenhousegases on climate is to inject carbon dioxide (CO2) from industrialsources into deep geological formations such as brine aquifers ordepleted oil or gas reservoirs. Research is being conducted to improveunderstanding of factors affecting particular aspects of geological CO2storage (such as storage performance, storage capacity, and health,safety and environmental (HSE) issues) as well as to lower the cost ofCO2 capture and related processes. However, there has been less emphasisto date on system-level analyses of geological CO2 storage that considergeological, economic, and environmental issues by linking detailedprocess models to representations of engineering components andassociatedmore » economic models. The objective of this study is to develop asystem-level model for geological CO2 storage, including CO2 capture andseparation, compression, pipeline transportation to the storage site, andCO2 injection. Within our system model we are incorporating detailedreservoir simulations of CO2 injection into a gas reservoir and relatedenhanced production of methane. Potential leakage and associatedenvironmental impacts are also considered. The platform for thesystem-level model is GoldSim [GoldSim User's Guide. GoldSim TechnologyGroup; 2006, http://www.goldsim.com]. The application of the system modelfocuses on evaluating the feasibility of carbon sequestration withenhanced gas recovery (CSEGR) in the Rio Vista region of California. Thereservoir simulations are performed using a special module of the TOUGH2simulator, EOS7C, for multicomponent gas mixtures of methane and CO2.Using a system-level modeling approach, the economic benefits of enhancedgas recovery can be directly weighed against the costs and benefits ofCO2 injection.« less
[Simulation and data mining model for identifying and prediction budget changes in the care of patients with hypertension].

PubMed

Joyanes-Aguilar, Luis; Castaño, Néstor J; Osorio, José H

2015-10-01

Objective To present a simulation model that establishes the economic impact to the health care system produced by the diagnostic evolution of patients suffering from arterial hypertension. Methodology The information used corresponds to that available in Individual Health Records (RIPs, in Spanish). A statistical characterization was carried out and a model for matrix storage in MATLAB was proposed. Data mining was used to create predictors. Finally, a simulation environment was built to determine the economic cost of diagnostic evolution. Results 5.7 % of the population progresses from the diagnosis, and the cost overrun associated with it is 43.2 %. Conclusions Results shows the applicability and possibility of focussing research on establishing diagnosis relationships using all the information reported in the RIPS in order to create econometric indicators that can determine which diagnostic evolutions are most relevant to budget allocation.
Resource Economics

NASA Astrophysics Data System (ADS)

Conrad, Jon M.

1999-10-01

Resource Economics is a text for students with a background in calculus, intermediate microeconomics, and a familiarity with the spreadsheet software Excel. The book covers basic concepts, shows how to set up spreadsheets to solve dynamic allocation problems, and presents economic models for fisheries, forestry, nonrenewable resources, stock pollutants, option value, and sustainable development. Within the text, numerical examples are posed and solved using Excel's Solver. Through these examples and additional exercises at the end of each chapter, students can make dynamic models operational, develop their economic intuition, and learn how to set up spreadsheets for the simulation of optimization of resource and environmental systems.
Modeling and optimization of a hybrid solar combined cycle (HYCS)

NASA Astrophysics Data System (ADS)

Eter, Ahmad Adel

2011-12-01

The main objective of this thesis is to investigate the feasibility of integrating concentrated solar power (CSP) technology with the conventional combined cycle technology for electric generation in Saudi Arabia. The generated electricity can be used locally to meet the annual increasing demand. Specifically, it can be utilized to meet the demand during the hours 10 am-3 pm and prevent blackout hours, of some industrial sectors. The proposed CSP design gives flexibility in the operation system. Since, it works as a conventional combined cycle during night time and it switches to work as a hybrid solar combined cycle during day time. The first objective of the thesis is to develop a thermo-economical mathematical model that can simulate the performance of a hybrid solar-fossil fuel combined cycle. The second objective is to develop a computer simulation code that can solve the thermo-economical mathematical model using available software such as E.E.S. The developed simulation code is used to analyze the thermo-economic performance of different configurations of integrating the CSP with the conventional fossil fuel combined cycle to achieve the optimal integration configuration. This optimal integration configuration has been investigated further to achieve the optimal design of the solar field that gives the optimal solar share. Thermo-economical performance metrics which are available in the literature have been used in the present work to assess the thermo-economic performance of the investigated configurations. The economical and environmental impact of integration CSP with the conventional fossil fuel combined cycle are estimated and discussed. Finally, the optimal integration configuration is found to be solarization steam side in conventional combined cycle with solar multiple 0.38 which needs 29 hectare and LEC of HYCS is 63.17 $/MWh under Dhahran weather conditions.
Cellular Automata Simulation for Wealth Distribution

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching

2009-08-01

Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.
Mitigating randomness of consumer preferences under certain conditional choices

NASA Astrophysics Data System (ADS)

Bothos, John M. A.; Thanos, Konstantinos-Georgios; Papadopoulou, Eirini; Daveas, Stelios; Thomopoulos, Stelios C. A.

2017-05-01

Agent-based crowd behaviour consists a significant field of research that has drawn a lot of attention in recent years. Agent-based crowd simulation techniques have been used excessively to forecast the behaviour of larger or smaller crowds in terms of certain given conditions influenced by specific cognition models and behavioural rules and norms, imposed from the beginning. Our research employs conditional event algebra, statistical methodology and agent-based crowd simulation techniques in developing a behavioural econometric model about the selection of certain economic behaviour by a consumer that faces a spectre of potential choices when moving and acting in a multiplex mall. More specifically we try to analyse the influence of demographic, economic, social and cultural factors on the economic behaviour of a certain individual and then we try to link its behaviour with the general behaviour of the crowds of consumers in multiplex malls using agent-based crowd simulation techniques. We then run our model using Generalized Least Squares and Maximum Likelihood methods to come up with the most probable forecast estimations, regarding the agent's behaviour. Our model is indicative about the formation of consumers' spectre of choices in multiplex malls under the condition of predefined preferences and can be used as a guide for further research in this area.
Simulating farmer behaviour under water markets

NASA Astrophysics Data System (ADS)

Padula, SIlvia; Erfani, Tohid; Henriques, Catarina; Maziotis, Alexandros; Garbe, Jennifer; Swinscoe, Thomas; Harou, Julien; Weatherhead, Keith; Beevers, Lindsay; Fleskens, Luuk

2015-04-01

Increasing water scarcity may lead water managers to consider alternative approaches to water allocation including water markets. One concern with markets is how will specific sectors interact with a potential water market, when will they gain or loose water and will they benefit economically - why, when and how? The behaviours of different individual abstractors or institutional actors under water markets is of interest to regulators who seek to design effective market policies which satisfy multiple stakeholder groups. In this study we consider two dozen agricultural water users in eastern England (Nar basin). Using partially synthetic but regionally representative cropping and irrigation data we simulate the buying and selling behaviour of farmers on a weekly basis over multiple years. The impact of on-farm water storage is assessed for farmers who own a reservoir. A river-basin-scale hydro-economic multi-agent model is used that represents individual abstractors and can simulate a spot market under various licensing regimes. Weekly varying economic demand curves for water are calibrated based on historical climate and water use data. The model represents the trade-off between current use value and expected gains from trade to reach weekly decisions. Early results are discussed and model limitations and possible extensions are presented.
New Orleans After Hurricane Katrina: An Unnatural Disaster?

NASA Astrophysics Data System (ADS)

McNamara, D.; Werner, B.; Kelso, A.

2005-12-01

Motivated by destruction in New Orleans following hurricane Katrina, we use a numerical model to explore how natural processes, economic development, hazard mitigation measures and policy decisions intertwine to produce long periods of quiescence punctuated by disasters of increasing magnitude. Physical, economic and policy dynamics are modeled on a grid representing the subsiding Mississippi Delta region surrounding New Orleans. Water flow and resulting sediment erosion and deposition are simulated in response to prescribed river floods and storms. Economic development operates on a limited number of commodities and services such as agricultural products, oil and chemical industries and port services, with investment and employment responding to both local conditions and global constraints. Development permitting, artificial levee construction and pumping are implemented by policy agents who weigh predicted economic benefits (tax revenue), mitigation costs and potential hazards. Economic risk is reduced by a combination of private insurance, federal flood insurance and disaster relief. With this model, we simulate the initiation and growth of New Orleans coupled with an increasing level of protection from a series of flooding events. Hazard mitigation filters out small magnitude events, but terrain and hydrological modifications amplify the impact of large events. In our model, "natural disasters" are the inevitable outcome of the mismatch between policy based on short-time-scale economic calculations and stochastic forcing by infrequent, high-magnitude flooding events. A comparison of the hazard mitigation response to river- and hurricane-induced flooding will be discussed. Supported by NSF Geology and Paleontology and the Andrew W Mellon Foundation.
Epidemic and economic impacts of delayed detection of foot-and-mouth disease: a case study of a simulated outbreak in California.

PubMed

Carpenter, Tim E; O'Brien, Joshua M; Hagerman, Amy D; McCarl, Bruce A

2011-01-01

The epidemic and economic impacts of Foot-and-mouth disease virus (FMDV) spread and control were examined by using epidemic simulation and economic (epinomic) optimization models. The simulated index herd was a ≥2,000 cow dairy located in California. Simulated disease spread was limited to California; however, economic impact was assessed throughout the United States and included international trade effects. Five index case detection delays were examined, which ranged from 7 to 22 days. The simulated median number of infected premises (IP) ranged from approximately 15 to 745, increasing as the detection delay increased from 7 to 22 days. Similarly, the median number of herds under quarantine increased from approximately 680 to 6,200, whereas animals slaughtered went from approximately 8,700 to 260,400 for detection delays of 7-22 days, respectively. The median economic impact of an FMD outbreak in California was estimated to result in national agriculture welfare losses of $2.3-$69.0 billion as detection delay increased from 7 to 22 days, respectively. If assuming a detection delay of 21 days, it was estimated that, for every additional hr of delay, the impact would be an additional approximately 2,000 animals slaughtered and an additional economic loss of $565 million. These findings underline the critical importance that the United States has an effective early detection system in place before an introduction of FMDV if it hopes to avoid dramatic losses to both livestock and the economy.
Economics of residue harvest: Regional partnership evaluation

USDA-ARS?s Scientific Manuscript database

Economic analyses on the viability of corn (Zea mays, L.) stover harvest for bioenergy production have largely been based on simulation modeling. While some studies have utilized field research data, most field-based analyses have included a limited number of sites and a narrow geographic distributi...
Simulation of an integrated system for the production of methane and single cell protein from biomass

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, M.V.

1989-01-01

A numerical model was developed to simulate the operation of an integrated system for the production of methane and single-cell algal protein from a variety of biomass energy crops or waste streams. Economic analysis was performed at the end of each simulation. The model was capable of assisting in the determination of design parameters by providing relative economic information for various strategies. Three configurations of anaerobic reactors were simulated. These included fed-bed reactors, conventional stirred tank reactors, and continuously expanding reactors. A generic anaerobic digestion process model, using lumped substrate parameters, was developed for use by type-specific reactor models. Themore » generic anaerobic digestion model provided a tool for the testing of conversion efficiencies and kinetic parameters for a wide range of substrate types and reactor designs. Dynamic growth models were used to model the growth of algae and Eichornia crassipes was modeled as a function of daily incident radiation and temperature. The growth of Eichornia crassipes was modeled for the production of biomass as a substrate for digestion. Computer simulations with the system model indicated that tropical or subtropical locations offered the most promise for a viable system. The availability of large quantities of digestible waste and low land prices were found to be desirable in order to take advantage of the economies of scale. Other simulations indicated that poultry and swine manure produced larger biogas yields than cattle manure. The model was created in a modular fashion to allow for testing of a wide variety of unit operations. Coding was performed in the Pascal language for use on personal computers.« less
A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

D'Andrea, M.; Fiorucci, P.; Holmes, T. P.

2010-10-01

Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary - each cell either contains a tree or it is empty - and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM), addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.
Version 3.0 of EMINERS - Economic Mineral Resource Simulator

USGS Publications Warehouse

Duval, Joseph S.

2012-01-01

Quantitative mineral resource assessment, as developed by the U.S. Geological Survey (USGS), consists of three parts: (1) development of grade and tonnage mineral deposit models; (2) delineation of tracts permissive for each deposit type; and (3) probabilistic estimation of the numbers of undiscovered deposits for each deposit type. The estimate of the number of undiscovered deposits at different levels of probability is the input to the EMINERS (Economic Mineral Resource Simulator) program. EMINERS uses a Monte Carlo statistical process to combine probabilistic estimates of undiscovered mineral deposits with models of mineral deposit grade and tonnage to estimate mineral resources. Version 3.0 of the EMINERS program is available as this USGS Open-File Report 2004-1344. Changes from version 2.0 include updating 87 grade and tonnage models, designing new templates to produce graphs showing cumulative distribution and summary tables, and disabling economic filters. The economic filters were disabled because embedded data for costs of labor and materials, mining techniques, and beneficiation methods are out of date. However, the cost algorithms used in the disabled economic filters are still in the program and available for reference for mining methods and milling techniques. The release notes included with this report give more details on changes in EMINERS over the years. EMINERS is written in C++ and depends upon the Microsoft Visual C++ 6.0 programming environment. The code depends heavily on the use of Microsoft Foundation Classes (MFC) for implementation of the Windows interface. The program works only on Microsoft Windows XP or newer personal computers. It does not work on Macintosh computers. For help in using the program in this report, see the "Quick-Start Guide for Version 3.0 of EMINERS-Economic Mineral Resource Simulator" (W.J. Bawiec and G.T. Spanski, 2012, USGS Open-File Report 2009-1057, linked at right). It demonstrates how to execute EMINERS software using default settings and existing deposit models.

Forecast-based Interventions Can Reduce the Health and Economic Burden of Wildfires

EPA Science Inventory

We simulated public health forecast-based interventions during a wildfire smoke episode in rural North Carolina to show the potential for use of modeled smoke forecasts toward reducing the health burden and showed a significant economic benefit of reducing exposures. Daily and co...
Empirical analyses on the development trend of non-ferrous metal industry under China’s new normal

NASA Astrophysics Data System (ADS)

Li, C. X.; Liu, C. X.; Zhang, Q. L.

2017-08-01

The CGE model of Yunnan’s macro economy was constructed based on the input-output data of Yunnan in 2012, and the development trend of the non-ferrous metals industry (NMI) under the China’s new normal was simulated. In view of this, according to different expected economic growth, and optimized economic structure, the impact on development of Yunnan NMI was simulated. The results show that the NMI growth rate is expected to decline when the economic growth show a downward trend, but the change of the proportion is relatively small. Moreover, the structure in proportion was adjusted to realize the economic structure optimization, while the proportion of NMI in GDP will decline. In contrast, the biggest influence on the NMI is the change of economic structure. From the statistics of last two years, we can see that NMI is growing, and at the same time, its proportion is declining, which is consistent with the results of simulation. But the adjustment of economic structure will take a long time. It is need to improve the proportion of deep-processing industry, extend the industrial chain, enhance the value chain, so as to be made good use of resource advantage.
A proposed model for economic evaluations of major depressive disorder.

PubMed

Haji Ali Afzali, Hossein; Karnon, Jonathan; Gray, Jodi

2012-08-01

In countries like UK and Australia, the comparability of model-based analyses is an essential aspect of reimbursement decisions for new pharmaceuticals, medical services and technologies. Within disease areas, the use of models with alternative structures, type of modelling techniques and/or data sources for common parameters reduces the comparability of evaluations of alternative technologies for the same condition. The aim of this paper is to propose a decision analytic model to evaluate long-term costs and benefits of alternative management options in patients with depression. The structure of the proposed model is based on the natural history of depression and includes clinical events that are important from both clinical and economic perspectives. Considering its greater flexibility with respect to handling time, discrete event simulation (DES) is an appropriate simulation platform for modelling studies of depression. We argue that the proposed model can be used as a reference model in model-based studies of depression improving the quality and comparability of studies.
New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388
New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.
Marginal economic value of streamflow: A case study for the Colorado River Basin

Treesearch

Thomas C. Brown; Benjamin L. Harding; Elizabeth A. Payton

1990-01-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and...
A health economic model to determine the long-term costs and clinical outcomes of raising low HDL-cholesterol in the prevention of coronary heart disease.

PubMed

Roze, S; Liens, D; Palmer, A; Berger, W; Tucker, D; Renaudin, C

2006-12-01

The aim of this study was to describe a health economic model developed to project lifetime clinical and cost outcomes of lipid-modifying interventions in patients not reaching target lipid levels and to assess the validity of the model. The internet-based, computer simulation model is made up of two decision analytic sub-models, the first utilizing Monte Carlo simulation, and the second applying Markov modeling techniques. Monte Carlo simulation generates a baseline cohort for long-term simulation by assigning an individual lipid profile to each patient, and applying the treatment effects of interventions under investigation. The Markov model then estimates the long-term clinical (coronary heart disease events, life expectancy, and quality-adjusted life expectancy) and cost outcomes up to a lifetime horizon, based on risk equations from the Framingham study. Internal and external validation analyses were performed. The results of the model validation analyses, plotted against corresponding real-life values from Framingham, 4S, AFCAPS/TexCAPS, and a meta-analysis by Gordon et al., showed that the majority of values were close to the y = x line, which indicates a perfect fit. The R2 value was 0.9575 and the gradient of the regression line was 0.9329, both very close to the perfect fit (= 1). Validation analyses of the computer simulation model suggest the model is able to recreate the outcomes from published clinical studies and would be a valuable tool for the evaluation of new and existing therapy options for patients with persistent dyslipidemia.
Modeling human behavior in economics and social science.

PubMed

Dolfin, M; Leonida, L; Outada, N

2017-12-01

The complex interactions between human behaviors and social economic sciences is critically analyzed in this paper in view of possible applications of mathematical modeling as an attainable interdisciplinary approach to understand and simulate the aforementioned dynamics. The quest is developed along three steps: Firstly an overall analysis of social and economic sciences indicates the main requirements that a contribution of mathematical modeling should bring to these sciences; subsequently the focus moves to an overview of mathematical tools and to the selection of those which appear, according to the authors bias, appropriate to the modeling; finally, a survey of applications is presented looking ahead to research perspectives. Copyright © 2017 Elsevier B.V. All rights reserved.
FLBEIA : A simulation model to conduct Bio-Economic evaluation of fisheries management strategies

NASA Astrophysics Data System (ADS)

Garcia, Dorleta; Sánchez, Sonia; Prellezo, Raúl; Urtizberea, Agurtzane; Andrés, Marga

Fishery systems are complex systems that need to be managed in order to ensure a sustainable and efficient exploitation of marine resources. Traditionally, fisheries management has relied on biological models. However, in recent years the focus on mathematical models which incorporate economic and social aspects has increased. Here, we present FLBEIA, a flexible software to conduct bio-economic evaluation of fisheries management strategies. The model is multi-stock, multi-fleet, stochastic and seasonal. The fishery system is described as a sum of processes, which are internally assembled in a predetermined way. There are several functions available to describe the dynamic of each process and new functions can be added to satisfy specific requirements.
A simulated annealing approach for redesigning a warehouse network problem

NASA Astrophysics Data System (ADS)

Khairuddin, Rozieana; Marlizawati Zainuddin, Zaitul; Jiun, Gan Jia

2017-09-01

Now a day, several companies consider downsizing their distribution networks in ways that involve consolidation or phase-out of some of their current warehousing facilities due to the increasing competition, mounting cost pressure and taking advantage on the economies of scale. Consequently, the changes on economic situation after a certain period of time require an adjustment on the network model in order to get the optimal cost under the current economic conditions. This paper aimed to develop a mixed-integer linear programming model for a two-echelon warehouse network redesign problem with capacitated plant and uncapacitated warehouses. The main contribution of this study is considering capacity constraint for existing warehouses. A Simulated Annealing algorithm is proposed to tackle with the proposed model. The numerical solution showed the model and method of solution proposed was practical.
Designing water demand management schemes using a socio-technical modelling approach.

PubMed

Baki, Sotiria; Rozos, Evangelos; Makropoulos, Christos

2018-05-01

Although it is now widely acknowledged that urban water systems (UWSs) are complex socio-technical systems and that a shift towards a socio-technical approach is critical in achieving sustainable urban water management, still, more often than not, UWSs are designed using a segmented modelling approach. As such, either the analysis focuses on the description of the purely technical sub-system, without explicitly taking into account the system's dynamic socio-economic processes, or a more interdisciplinary approach is followed, but delivered through relatively coarse models, which often fail to provide a thorough representation of the urban water cycle and hence cannot deliver accurate estimations of the hydrosystem's responses. In this work we propose an integrated modelling approach for the study of the complete socio-technical UWS that also takes into account socio-economic and climatic variability. We have developed an integrated model, which is used to investigate the diffusion of household water conservation technologies and its effects on the UWS, under different socio-economic and climatic scenarios. The integrated model is formed by coupling a System Dynamics model that simulates the water technology adoption process, and the Urban Water Optioneering Tool (UWOT) for the detailed simulation of the urban water cycle. The model and approach are tested and demonstrated in an urban redevelopment area in Athens, Greece under different socio-economic scenarios and policy interventions. It is suggested that the proposed approach can establish quantifiable links between socio-economic change and UWS responses and therefore assist decision makers in designing more effective and resilient long-term strategies for water conservation. Copyright © 2017 Elsevier B.V. All rights reserved.
Modeling and simulation of emergent behavior in transportation infrastructure restoration

USGS Publications Warehouse

Ojha, Akhilesh; Corns, Steven; Shoberg, Thomas G.; Qin, Ruwen; Long, Suzanna K.

2018-01-01

The objective of this chapter is to create a methodology to model the emergent behavior during a disruption in the transportation system and that calculates economic losses due to such a disruption, and to understand how an extreme event affects the road transportation network. The chapter discusses a system dynamics approach which is used to model the transportation road infrastructure system to evaluate the different factors that render road segments inoperable and calculate economic consequences of such inoperability. System dynamics models have been integrated with business process simulation model to evaluate, design, and optimize the business process. The chapter also explains how different factors affect the road capacity. After identifying the various factors affecting the available road capacity, a causal loop diagram (CLD) is created to visually represent the causes leading to a change in the available road capacity and the effects on travel costs when the available road capacity changes.
A Graphics Design Framework to Visualize Multi-Dimensional Economic Datasets

ERIC Educational Resources Information Center

Chandramouli, Magesh; Narayanan, Badri; Bertoline, Gary R.

2013-01-01

This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a "visual analytical database" for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of…
Economic consequences of aviation system disruptions: A reduced-form computable general equilibrium analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Zhenhua; Rose, Adam Z.; Prager, Fynnwin

The state of the art approach to economic consequence analysis (ECA) is computable general equilibrium (CGE) modeling. However, such models contain thousands of equations and cannot readily be incorporated into computerized systems used by policy analysts to yield estimates of economic impacts of various types of transportation system failures due to natural hazards, human related attacks or technological accidents. This paper presents a reduced-form approach to simplify the analytical content of CGE models to make them more transparent and enhance their utilization potential. The reduced-form CGE analysis is conducted by first running simulations one hundred times, varying key parameters, suchmore » as magnitude of the initial shock, duration, location, remediation, and resilience, according to a Latin Hypercube sampling procedure. Statistical analysis is then applied to the “synthetic data” results in the form of both ordinary least squares and quantile regression. The analysis yields linear equations that are incorporated into a computerized system and utilized along with Monte Carlo simulation methods for propagating uncertainties in economic consequences. Although our demonstration and discussion focuses on aviation system disruptions caused by terrorist attacks, the approach can be applied to a broad range of threat scenarios.« less
Pilot Study: Impact of Computer Simulation on Students' Economic Policy Performance. Pilot Study.

ERIC Educational Resources Information Center

Domazlicky, Bruce; France, Judith

Fiscal and monetary policies taught in macroeconomic principles courses are concepts that might require both lecture and simulation methods. The simulation models, which apply the principles gleened from comparative statistics to a dynamic world, may give students an appreciation for the problems facing policy makers. This paper is a report of a…
Mars Colony in situ resource utilization: An integrated architecture and economics model

NASA Astrophysics Data System (ADS)

Shishko, Robert; Fradet, René; Do, Sydney; Saydam, Serkan; Tapia-Cortez, Carlos; Dempster, Andrew G.; Coulton, Jeff

2017-09-01

This paper reports on our effort to develop an ensemble of specialized models to explore the commercial potential of mining water/ice on Mars in support of a Mars Colony. This ensemble starts with a formal systems architecting framework to describe a Mars Colony and capture its artifacts' parameters and technical attributes. The resulting database is then linked to a variety of ;downstream; analytic models. In particular, we integrated an extraction process (i.e., ;mining;) model, a simulation of the colony's environmental control and life support infrastructure known as HabNet, and a risk-based economics model. The mining model focuses on the technologies associated with in situ resource extraction, processing, storage and handling, and delivery. This model computes the production rate as a function of the systems' technical parameters and the local Mars environment. HabNet simulates the fundamental sustainability relationships associated with establishing and maintaining the colony's population. The economics model brings together market information, investment and operating costs, along with measures of market uncertainty and Monte Carlo techniques, with the objective of determining the profitability of commercial water/ice in situ mining operations. All told, over 50 market and technical parameters can be varied in order to address ;what-if; questions, including colony location.
The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies

USDA-ARS?s Scientific Manuscript database

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation research activity for historical period model intercomparison and future climate change conditions with participation of multiple crop and agricultural economic model groups around the...
The economic feasibility of seawater desalination over the global scale: assessment of the production cost development and national water price until 2050

NASA Astrophysics Data System (ADS)

Gao, L.; Yoshikawa, S.; Iseri, Y.; Kanae, S.

2016-12-01

As many countries are suffering water scarcity due to the climate change and human activities, seawater desalination using reverse osmosis (SWRO) has shown to be a progressively promising countermeasure to satisfy the growing water demand. Therefore, the economic feasibility assessment of SWRO will be beneficial for the potential investors and policy-makers of government. In present study, it have proposed a systematic method to evaluate the economic feasibility of implementing SWRO in 140 counties and further estimated the potential future diffusion of SWRO over global scale by 2050. To the purpose, two models has been separately developed to simulate the production cost of SWRO and conventional water price, which are identified as the critical economic factors for feasibility evaluation of SWRO. These two models were firstly applied to historical validation in which proven to be able to well simulate both these two economic factors, and then were applied globally for future simulation over the period of 2015-2050 under three socioeconomic scenarios, i.e. SSP (Shared Socioeconomic Pathways) 1-3. Basin on the estimated production cost and water price, the economic feasibility of adopting SWRO coupling with its future potentialities were carefully evaluated. As a result, it indicated that SWRO was expected to be cost-effectively adopted in more countries by 2050, especially in these developing countries. The significant potential diffusion of SWRO in countries was mainly attributed to both the diminishing production cost and the increasing conventional water price as a result of income growth globally in three SSPs scenarios.
Cost-benefit analysis model of badger (Meles meles) culling to reduce cattle herd tuberculosis breakdowns in Britain, with particular reference to badger perturbation.

PubMed

Wilkinson, D; Bennett, R; McFarlane, I; Rushton, S; Shirley, M; Smith, G C

2009-10-01

Bovine tuberculosis (TB) is an important economic disease. Badgers (Meles meles) are the wildlife source implicated in many cattle outbreaks of TB in Britain, and extensive badger control is a controversial option to reduce the disease. A badger and cattle population model was developed, simulating TB epidemiology; badger ecology, including postcull social perturbation; and TB-related farm management. An economic cost-benefit module was integrated into the model to assess whether badger control offers economic benefits. Model results strongly indicate that although, if perturbation were restricted, extensive badger culling could reduce rates in cattle, overall an economic loss would be more likely than a benefit. Perturbation of the badger population was a key factor determining success or failure of control. The model highlighted some important knowledge gaps regarding both the spatial and temporal characteristics of perturbation that warrant further research.
Physical-Socio-Economic Modeling of Climate Change

NASA Astrophysics Data System (ADS)

Chamberlain, R. G.; Vatan, F.

2008-12-01

Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media/information operations model. Each of these models focuses on part of the overall picture while; each contributes information about its area of expertise to a common pool and draws from that pool and the feedbacks from the other models as needed. Existing high-quality physical models are based on analysis of the dynamic interactions of atmospheric, land, and ocean processes. The demographic model tracks the civilian demographics needed by the other models. The populations of neighborhood group age-gender cohorts are affected by births, deaths, aging, and migration. This model provides labor supply and product demand curves to the economic model. The political model focuses on political actors and describes how they use their clout to seek their goals. Clout is derived from civilian support, the formal and informal alliances that actors make with each other, military strength, wealth, and control of information. It considers how they are constrained by their cultural heritage. It deals with shifting alliances. The economic model determines local and international prices and production quantities for a small number of products, including imports and exports and black markets; wages, jobs, and unemployment for a small number of labor categories; capital, growth, and inflation; resource usage and pollution. The media/information operations model addresses the effects of the control and content of inter- group and intra-group communications-and the side effects of these on other groups. This model will consist of rules (probably a large number of them) detailing the effects of media/information operations of various kinds on civilian parameters used in the other models, such as political goals, concern saliencies, and shapes of supply and demand curves.

Toward economic flood loss characterization via hazard simulation

NASA Astrophysics Data System (ADS)

Czajkowski, Jeffrey; Cunha, Luciana K.; Michel-Kerjan, Erwann; Smith, James A.

2016-08-01

Among all natural disasters, floods have historically been the primary cause of human and economic losses around the world. Improving flood risk management requires a multi-scale characterization of the hazard and associated losses—the flood loss footprint. But this is typically not available in a precise and timely manner, yet. To overcome this challenge, we propose a novel and multidisciplinary approach which relies on a computationally efficient hydrological model that simulates streamflow for scales ranging from small creeks to large rivers. We adopt a normalized index, the flood peak ratio (FPR), to characterize flood magnitude across multiple spatial scales. The simulated FPR is then shown to be a key statistical driver for associated economic flood losses represented by the number of insurance claims. Importantly, because it is based on a simulation procedure that utilizes generally readily available physically-based data, our flood simulation approach has the potential to be broadly utilized, even for ungauged and poorly gauged basins, thus providing the necessary information for public and private sector actors to effectively reduce flood losses and save lives.
Hamiltonian and potentials in derivative pricing models: exact results and lattice simulations

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Corianò, Claudio; Srikant, Marakani

2004-03-01

The pricing of options, warrants and other derivative securities is one of the great success of financial economics. These financial products can be modeled and simulated using quantum mechanical instruments based on a Hamiltonian formulation. We show here some applications of these methods for various potentials, which we have simulated via lattice Langevin and Monte Carlo algorithms, to the pricing of options. We focus on barrier or path dependent options, showing in some detail the computational strategies involved.
Energy retrofit of an office building by substitution of the generation system: performance evaluation via dynamic simulation versus current technical standards

NASA Astrophysics Data System (ADS)

Testi, D.; Schito, E.; Menchetti, E.; Grassi, W.

2014-11-01

Constructions built in Italy before 1945 (about 30% of the total built stock) feature low energy efficiency. Retrofit actions in this field can lead to valuable energetic and economic savings. In this work, we ran a dynamic simulation of a historical building of the University of Pisa during the heating season. We firstly evaluated the energy requirements of the building and the performance of the existing natural gas boiler, validated with past billings of natural gas. We also verified the energetic savings obtainable by the substitution of the boiler with an air-to-water electrically-driven modulating heat pump, simulated through a cycle-based model, evaluating the main economic metrics. The cycle-based model of the heat pump, validated with manufacturers' data available only at specified temperature and load conditions, can provide more accurate results than the simplified models adopted by current technical standards, thus increasing the effectiveness of energy audits.
Simulation and optimization model for irrigation planning and management

NASA Astrophysics Data System (ADS)

Kuo, Sheng-Feng; Liu, Chen-Wuing

2003-10-01

A simulation and optimization model was developed and applied to an irrigated area in Delta, Utah to optimize the economic benefit, simulate the water demand, and search the related crop area percentages with specified water supply and planted area constraints. The user interface model begins with the weather generation submodel, which produces daily weather data, which is based on long-term monthly average and standard deviation data from Delta, Utah. To simulate the daily crop water demand and relative crop yield for seven crops in two command areas, the information provided by this submodel was applied to the on-farm irrigation scheduling submodel. Furthermore, to optimize the project benefit by searching for the best allocation of planted crop areas given the constraints of projected water supply, the results were employed in the genetic algorithm submodel. Optimal planning for the 394·6-ha area of the Delta irrigation project is projected to produce the maximum economic benefit. That is, projected profit equals US$113 826 and projected water demand equals 3·03 × 106 m3. Also, area percentages of crops within UCA#2 command area are 70·1%, 19% and 10·9% for alfalfa, barley and corn, respectively, and within UCA#4 command area are 41·5%, 38·9%, 14·4% and 5·2% for alfalfa, barley, corn and wheat, respectively. As this model can plan irrigation application depths and allocate crop areas for optimal economic benefit, it can thus be applied to many irrigation projects. Copyright
Visualization of the Eastern Renewable Generation Integration Study: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gruchalla, Kenny; Novacheck, Joshua; Bloom, Aaron

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the U.S. Eastern Interconnection and Quebec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated withmore » evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions. state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.« less
A robust and flexible Geospatial Modeling Interface (GMI) for environmental model deployment and evaluation

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of the GMI (Geospatial Modeling Interface) simulation framework for environmental model deployment and assessment. GMI currently provides access to multiple environmental models including AgroEcoSystem-Watershed (AgES-W), Nitrate Leaching and Economic Analysis 2 (NLEA...
Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, Cynthia; Ruane, Alex C.; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S.; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M.; Sands, Ronald D.; Schleussner, Carl-Friedrich; Valdivia, Roberto O.; Valin, Hugo; Wiebe, Keith

2018-05-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments.

PubMed

Rosenzweig, Cynthia; Ruane, Alex C; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M; Sands, Ronald D; Schleussner, Carl-Friedrich; Valdivia, Roberto O; Valin, Hugo; Wiebe, Keith

2018-05-13

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO 2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Authors.
The Clinical Health Economics System Simulation (CHESS): a teaching tool for systems- and practice-based learning.

PubMed

Voss, John D; Nadkarni, Mohan M; Schectman, Joel M

2005-02-01

Academic medical centers face barriers to training physicians in systems- and practice-based learning competencies needed to function in the changing health care environment. To address these problems, at the University of Virginia School of Medicine the authors developed the Clinical Health Economics System Simulation (CHESS), a computerized team-based quasi-competitive simulator to teach the principles and practical application of health economics. CHESS simulates treatment costs to patients and society as well as physician reimbursement. It is scenario based with residents grouped into three teams, each team playing CHESS using differing (fee-for-service or capitated) reimbursement models. Teams view scenarios and select from two or three treatment options that are medically justifiable yet have different potential cost implications. CHESS displays physician reimbursement and patient and societal costs for each scenario as well as costs and income summarized across all scenarios extrapolated to a physician's entire patient panel. The learners are asked to explain these findings and may change treatment options and other variables such as panel size and case mix to conduct sensitivity analyses in real time. Evaluations completed in 2003 by 68 (94%) CHESS resident and faculty participants at 19 U.S. residency programs preferred CHESS to a traditional lecture-and-discussion format to learn about medical decision making, physician reimbursement, patient costs, and societal costs. Ninety-eight percent reported increased knowledge of health economics after viewing the simulation. CHESS demonstrates the potential of computer simulation to teach health economics and other key elements of practice- and systems-based competencies.
Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural Systems

NASA Astrophysics Data System (ADS)

MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.

2013-12-01

Representative Agricultural Pathways (RAPs) are projections of plausible future biophysical and socio-economic conditions used to carry out climate impact assessments for agriculture. The development of RAPs iss motivated by the fact that the various global and regional models used for agricultural climate change impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation or public availability. These practices have hampered attempts at model inter-comparison, improvement, and synthesis of model results across studies. This paper aims to (1) present RAPs developed for the principal wheat-producing region of the Pacific Northwest, and to (2) combine these RAPs with downscaled climate data, crop model simulations and economic model simulations to assess climate change impacts on winter wheat production and farm income. This research was carried out as part of a project funded by the USDA known as the Regional Approaches to Climate Change in the Pacific Northwest (REACCH). The REACCH study region encompasses the major winter wheat production area in Pacific Northwest and preliminary research shows that farmers producing winter wheat could benefit from future climate change. However, the future world is uncertain in many dimensions, including commodity and input prices, production technology, and policies, as well as increased probability of disturbances (pests and diseases) associated with a changing climate. Many of these factors cannot be modeled, so they are represented in the regional RAPS. The regional RAPS are linked to global agricultural and shared social-economic pathways, and used along with climate change projections to simulate future outcomes for the wheat-based farms in the REACCH region.
Design and application of a technologically explicit hybrid energy-economy policy model with micro and macro economic dynamics

NASA Astrophysics Data System (ADS)

Bataille, Christopher G. F.

2005-11-01

Are further energy efficiency gains, or more recently greenhouse gas reductions, expensive or cheap? Analysts provide conflicting advice to policy makers based on divergent modelling perspectives, a 'top-down/bottom-up debate' in which economists use equation based models that equilibrate markets by maximizing consumer welfare, and technologists use technology simulation models that minimize the financial cost of providing energy services. This thesis summarizes a long term research project to find a middle ground between these two positions that is more useful to policy makers. Starting with the individual components of a behaviourally realistic and technologically explicit simulation model (ISTUM---Inter Sectoral Technology Use Model), or "hybrid", the individual sectors of the economy are linked using a framework of micro and macro economic feedbacks. These feedbacks are taken from the economic theory that informs the computable general equilibrium (CGE) family of models. Speaking in the languages of both economists and engineers, the resulting "physical" equilibrium model of Canada (CIMS---Canadian Integrated Modeling System), equilibrates energy and end-product markets, including imports and exports, for seven regions and 15 economic sectors, including primary industry, manufacturing, transportation, commerce, residences, governmental infrastructure and the energy supply sectors. Several different policy experiments demonstrate the value-added of the model and how its results compare to top-down and bottom-up practice. In general, the results show that technical adjustments make up about half the response to simulated energy policy, and macroeconomic demand adjustments the other half. Induced technical adjustments predominate with minor policies, while the importance of macroeconomic demand adjustment increases with the strength of the policy. Results are also shown for an experiment to derive estimates of future elasticity of substitution (ESUB) and autonomous energy efficiency indices (AEEI) from the model, parameters that could be used in long-run computable general equilibrium (CGE) analysis. The thesis concludes with a summary of the strengths and weakness of the new model as a policy tool, a work plan for its further improvement, and a discussion of the general potential for technologically explicit general equilibrium modelling.
Helicopter training simulators: Key market factors

NASA Technical Reports Server (NTRS)

Mcintosh, John

1992-01-01

Simulators will gain an increasingly important role in training helicopter pilots only if the simulators are of sufficient fidelity to provide positive transfer of skills to the aircraft. This must be done within an economic model of return on investment. Although rotor pilot demand is still only a small percentage of overall pilot requirements, it will grow in significance. This presentation described the salient factors influencing the use of helicopter training simulators.
GAIA - a generalizable, extensible structure for integrating games, models and social networking to support decision makers

NASA Astrophysics Data System (ADS)

Paxton, L. J.; Schaefer, R. K.; Nix, M.; Fountain, G. H.; Weiss, M.; Swartz, W. H.; Parker, C. L.; MacDonald, L.; Ihde, A. G.; Simpkins, S.; GAIA Team

2011-12-01

In this paper we describe the application of a proven methodology for modeling the complex social and economic interactions embodied in real-world decision making to water scarcity and water resources. We have developed a generalizable, extensible facility we call "GAIA" - Global Assimilation of Information for Action - and applied it to different problem sets. We describe the use of the "Green Country Model" and other gaming/simulation tools to address the impacts of climate and climate disruption issues at the intersection of science, economics, policy, and society. There is a long history in the Defense community of using what are known as strategic simulations or "wargames" to model the complex interactions between the environment, people, resources, infrastructure and the economy in a competitive environment. We describe in this paper, work that we have done on understanding how this heritage can be repurposed to help us explore how the complex interplay between climate disruption and our socio/political and economic structures will affect our future. Our focus here is on a fundamental and growing issue - water and water availability. We consider water and the role of "virtual water" in the system. Various "actors" are included in the simulations. While these simulations cannot definitively predict what will happen, they do illuminate non-linear feedbacks between, for example, treaty agreement, the environment, the economy, and the government. These simulations can be focused on the global, regional, or local environment. We note that these simulations are not "zero sum" games - there need not be a winner and a loser. They are, however, competitive influence games: they represent the tools that a nation, state, faction or group has at its disposal to influence policy (diplomacy), finances, industry (economy), infrastructure, information, etc to achieve their particular goals. As in the real world the problem is competitive - not everyone shares the same definition of a successful or favorable outcome.
Modeling emissions of volatile organic compounds from silage storages and feed lanes

USDA-ARS?s Scientific Manuscript database

An initial volatile organic compound (VOC) emission model for silage sources, developed using experimental data from previous studies, was incorporated into the Integrated Farm System Model (IFSM), a whole-farm simulation model used to assess the performance, environmental impacts, and economics of ...
Holistic irrigation water management approach based on stochastic soil water dynamics

NASA Astrophysics Data System (ADS)

Alizadeh, H.; Mousavi, S. J.

2012-04-01

Appreciating the essential gap between fundamental unsaturated zone transport processes and soil and water management due to low effectiveness of some of monitoring and modeling approaches, this study presents a mathematical programming model for irrigation management optimization based on stochastic soil water dynamics. The model is a nonlinear non-convex program with an economic objective function to address water productivity and profitability aspects in irrigation management through optimizing irrigation policy. Utilizing an optimization-simulation method, the model includes an eco-hydrological integrated simulation model consisting of an explicit stochastic module of soil moisture dynamics in the crop-root zone with shallow water table effects, a conceptual root-zone salt balance module, and the FAO crop yield module. Interdependent hydrology of soil unsaturated and saturated zones is treated in a semi-analytical approach in two steps. At first step analytical expressions are derived for the expected values of crop yield, total water requirement and soil water balance components assuming fixed level for shallow water table, while numerical Newton-Raphson procedure is employed at the second step to modify value of shallow water table level. Particle Swarm Optimization (PSO) algorithm, combined with the eco-hydrological simulation model, has been used to solve the non-convex program. Benefiting from semi-analytical framework of the simulation model, the optimization-simulation method with significantly better computational performance compared to a numerical Mote-Carlo simulation-based technique has led to an effective irrigation management tool that can contribute to bridging the gap between vadose zone theory and water management practice. In addition to precisely assessing the most influential processes at a growing season time scale, one can use the developed model in large scale systems such as irrigation districts and agricultural catchments. Accordingly, the model has been applied in Dasht-e-Abbas and Ein-khosh Fakkeh Irrigation Districts (DAID and EFID) of the Karkheh Basin in southwest of Iran. The area suffers from the water scarcity problem and therefore the trade-off between the level of deficit and economical profit should be assessed. Based on the results, while the maximum net benefit has been obtained for the stress-avoidance (SA) irrigation policy, the highest water profitability, defined by economical net benefit gained from unit irrigation water volume application, has been resulted when only about 60% of water used in the SA policy is applied.
Incorporating Psychological Predictors of Treatment Response into Health Economic Simulation Models: A Case Study in Type 1 Diabetes.

PubMed

Kruger, Jen; Pollard, Daniel; Basarir, Hasan; Thokala, Praveen; Cooke, Debbie; Clark, Marie; Bond, Rod; Heller, Simon; Brennan, Alan

2015-10-01

. Health economic modeling has paid limited attention to the effects that patients' psychological characteristics have on the effectiveness of treatments. This case study tests 1) the feasibility of incorporating psychological prediction models of treatment response within an economic model of type 1 diabetes, 2) the potential value of providing treatment to a subgroup of patients, and 3) the cost-effectiveness of providing treatment to a subgroup of responders defined using 5 different algorithms. . Multiple linear regressions were used to investigate relationships between patients' psychological characteristics and treatment effectiveness. Two psychological prediction models were integrated with a patient-level simulation model of type 1 diabetes. Expected value of individualized care analysis was undertaken. Five different algorithms were used to provide treatment to a subgroup of predicted responders. A cost-effectiveness analysis compared using the algorithms to providing treatment to all patients. . The psychological prediction models had low predictive power for treatment effectiveness. Expected value of individualized care results suggested that targeting education at responders could be of value. The cost-effectiveness analysis suggested, for all 5 algorithms, that providing structured education to a subgroup of predicted responders would not be cost-effective. . The psychological prediction models tested did not have sufficient predictive power to make targeting treatment cost-effective. The psychological prediction models are simple linear models of psychological behavior. Collection of data on additional covariates could potentially increase statistical power. . By collecting data on psychological variables before an intervention, we can construct predictive models of treatment response to interventions. These predictive models can be incorporated into health economic models to investigate more complex service delivery and reimbursement strategies. © The Author(s) 2015.
Corruption and economic growth with non constant labor force growth

NASA Astrophysics Data System (ADS)

Brianzoni, Serena; Campisi, Giovanni; Russo, Alberto

2018-05-01

Based on Brianzoni et al. [1] in the present work we propose an economic model regarding the relationship between corruption in public procurement and economic growth. We extend the benchmark model by introducing endogenous labor force growth, described by the logistic equation. The results of previous studies, as Del Monte and Papagni [2] and Mauro [3], show that countries are stuck in one of the two equilibria (high corruption and low economic growth or low corruption and high economic growth). Brianzoni et al. [1] prove the existence of a further steady state characterized by intermediate levels of capital per capita and corruption. Our aim is to investigate the effects of the endogenous growth around such equilibrium. Moreover, due to the high number of parameters of the model, specific attention is given to the numerical simulations which highlight new policy measures that can be adopted by the government to fight corruption.
Forest management and economics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buongiorno, J.; Gilless, J.K.

1987-01-01

This volume provides a survey of quantitative methods, guiding the reader through formulation and analysis of models that address forest management problems. The authors use simple mathematics, graphics, and short computer programs to explain each method. Emphasizing applications, they discuss linear, integer, dynamic, and goal programming; simulation; network modeling; and econometrics, as these relate to problems of determining economic harvest schedules in even-aged and uneven-aged forests, the evaluation of forest policies, multiple-objective decision making, and more.
Annotated Bibliography: Value of Environmental Protection and Restoration

DTIC Science & Technology

1993-02-01

approach. Ecological Economics, 3, 1-24. Key Words: wetlands, ecotechnology A simulation model is developed to predict the efficiency and economics of an...application of ecotechnology using a created wetland to receive and treat coal mine drainage. The model examines the role of loading rates of iron on...shows that the use of ecotechnology such as wetland trt- "’nt systems can provide low-cost solutions to some expensive pollution problems. Wetland
Microfiltration of thin stillage: Process simulation and economic analyses

USDA-ARS?s Scientific Manuscript database

In plant scale operations, multistage membrane systems have been adopted for cost minimization. We considered design optimization and operation of a continuous microfiltration (MF) system for the corn dry grind process. The objectives were to develop a model to simulate a multistage MF system, optim...

Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

PubMed

Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

2018-03-01

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.
Historical disturbance regimes as a reference for forest policy. in a multiowner province: a simulation experiment

Treesearch

Jonathan R. Thompson; K. Norman Johnson; Marie Lennette; Thomas A. Spies; Pete Bettinger

2006-01-01

Using a landscape simulation model, we examined ecological and economic implications of forest policies designed to emulate the historical fire regime across the 2 x 106 ha Oregon Coast Range. Simulated policies included two variants of the current policy and three policies reflecting aspects of the historical fire regime. Policy development was...
Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model: A Web-based program designed to evaluate the cost-effectiveness of disease management programs in heart failure.

PubMed

Reed, Shelby D; Neilson, Matthew P; Gardner, Matthew; Li, Yanhong; Briggs, Andrew H; Polsky, Daniel E; Graham, Felicia L; Bowers, Margaret T; Paul, Sara C; Granger, Bradi B; Schulman, Kevin A; Whellan, David J; Riegel, Barbara; Levy, Wayne C

2015-11-01

Heart failure disease management programs can influence medical resource use and quality-adjusted survival. Because projecting long-term costs and survival is challenging, a consistent and valid approach to extrapolating short-term outcomes would be valuable. We developed the Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model, a Web-based simulation tool designed to integrate data on demographic, clinical, and laboratory characteristics; use of evidence-based medications; and costs to generate predicted outcomes. Survival projections are based on a modified Seattle Heart Failure Model. Projections of resource use and quality of life are modeled using relationships with time-varying Seattle Heart Failure Model scores. The model can be used to evaluate parallel-group and single-cohort study designs and hypothetical programs. Simulations consist of 10,000 pairs of virtual cohorts used to generate estimates of resource use, costs, survival, and incremental cost-effectiveness ratios from user inputs. The model demonstrated acceptable internal and external validity in replicating resource use, costs, and survival estimates from 3 clinical trials. Simulations to evaluate the cost-effectiveness of heart failure disease management programs across 3 scenarios demonstrate how the model can be used to design a program in which short-term improvements in functioning and use of evidence-based treatments are sufficient to demonstrate good long-term value to the health care system. The Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model provides researchers and providers with a tool for conducting long-term cost-effectiveness analyses of disease management programs in heart failure. Copyright © 2015 Elsevier Inc. All rights reserved.
Forest-fire models

Treesearch

Haiganoush Preisler; Alan Ager

2013-01-01

For applied mathematicians forest fire models refer mainly to a non-linear dynamic system often used to simulate spread of fire. For forest managers forest fire models may pertain to any of the three phases of fire management: prefire planning (fire risk models), fire suppression (fire behavior models), and postfire evaluation (fire effects and economic models). In...
A simulation model for wind energy storage systems. Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Warren, A. W.; Edsinger, R. W.; Chan, Y. K.

1977-01-01

A comprehensive computer program for the modeling of wind energy and storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) was developed. The level of detail of Simulation Model for Wind Energy Storage (SIMWEST) is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind source storage application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/O, the integration of systems dynamics, and the iteration for conveyance of variables. SIMWEST program, as described, runs on the UNIVAC 1100 series computers.
Methods and tools to simulate the effect of economic instruments in complex water resources systems. Application to the Jucar river basin.

NASA Astrophysics Data System (ADS)

Lopez-Nicolas, Antonio; Pulido-Velazquez, Manuel

2014-05-01

The main challenge of the BLUEPRINT to safeguard Europe's water resources (EC, 2012) is to guarantee that enough good quality water is available for people's needs, the economy and the environment. In this sense, economic policy instruments such as water pricing policies and water markets can be applied to enhance efficient use of water. This paper presents a method based on hydro-economic tools to assess the effect of economic instruments on water resource systems. Hydro-economic models allow integrated analysis of water supply, demand and infrastructure operation at the river basin scale, by simultaneously combining engineering, hydrologic and economic aspects of water resources management. The method made use of the simulation and optimization hydroeconomic tools SIMGAMS and OPTIGAMS. The simulation tool SIMGAMS allocates water resources among the users according to priorities and operating rules, and evaluate economic scarcity costs of the system by using economic demand functions. The model's objective function is designed so that the system aims to meet the operational targets (ranked according to priorities) at each month while following the system operating rules. The optimization tool OPTIGAMS allocates water resources based on an economic efficiency criterion: maximize net benefits, or alternatively, minimizing the total water scarcity and operating cost of water use. SIMGAS allows to simulate incentive water pricing policies based on marginal resource opportunity costs (MROC; Pulido-Velazquez et al., 2013). Storage-dependent step pricing functions are derived from the time series of MROC values at a certain reservoir in the system. These water pricing policies are defined based on water availability in the system (scarcity pricing), so that when water storage is high, the MROC is low, while low storage (drought periods) will be associated to high MROC and therefore, high prices. We also illustrate the use of OPTIGAMS to simulate the effect of ideal water markets by economic optimization, without considering the potential effect of transaction costs. These methods and tools have been applied to the Jucar River basin (Spain). The results show the potential of economic instruments in setting incentives for a more efficient management of water resources systems. Acknowledgments: The study has been partially supported by the European Community 7th Framework Project (GENESIS project, n. 226536), SAWARES (Plan Nacional I+D+i 2008-2011, CGL2009-13238-C02-01 and C02-02), SCARCE (Consolider-Ingenio 2010 CSD2009-00065) of the Spanish Ministry of Economy and Competitiveness; and EC 7th Framework Project ENHANCE (n. 308438) Reference: Pulido-Velazquez, M., Alvarez-Mendiola, E., and Andreu, J., 2013. Design of Efficient Water Pricing Policies Integrating Basinwide Resource Opportunity Costs. J. Water Resour. Plann. Manage., 139(5): 583-592.
Monte Carlo simulation of single accident airport risk profile

NASA Technical Reports Server (NTRS)

1979-01-01

A computer simulation model was developed for estimating the potential economic impacts of a carbon fiber release upon facilities within an 80 kilometer radius of a major airport. The model simulated the possible range of release conditions and the resulting dispersion of the carbon fibers. Each iteration of the model generated a specific release scenario, which would cause a specific amount of dollar loss to the surrounding community. By repeated iterations, a risk profile was generated, showing the probability distribution of losses from one accident. Using accident probability estimates, the risks profile for annual losses was derived. The mechanics are described of the simulation model, the required input data, and the risk profiles generated for the 26 large hub airports.
Mid-term financial impact of animal welfare improvements in Dutch broiler production.

PubMed

Gocsik, E; Lansink, A G J M Oude; Saatkamp, H W

2013-12-01

This study used a stochastic bioeconomic simulation model to simulate the business and financial risk of different broiler production systems over a 5-yr period. Simulation analysis was conducted using the @Risk add-in in MS Excel. To compare the impact of different production systems on economic feasibility, 2 cases were considered. The first case focused on the economic feasibility of a completely new system, whereas the second examined economic feasibilities when a farm switches from a conventional to an animal welfare-improving production system. A sensitivity analysis was conducted to assess the key drivers of economic feasibility and to reveal systematic differences across production systems. The study shows that economic feasibility of systems with improved animal welfare predominantly depends on the price that farmers receive. Moreover, the study demonstrates the importance of the level and variation of the price premium for improved welfare, particularly in the first 5 yr after conversion. The economic feasibility of the production system increases with the level of welfare improvements for a sufficiently high price level for broiler meat and low volatility in producer prices. If this is not the case, however, risk attitudes of farmers become important as well as the use of potential risk management instruments.
A non-linear model of economic production processes

NASA Astrophysics Data System (ADS)

Ponzi, A.; Yasutomi, A.; Kaneko, K.

2003-06-01

We present a new two phase model of economic production processes which is a non-linear dynamical version of von Neumann's neoclassical model of production, including a market price-setting phase as well as a production phase. The rate of an economic production process is observed, for the first time, to depend on the minimum of its input supplies. This creates highly non-linear supply and demand dynamics. By numerical simulation, production networks are shown to become unstable when the ratio of different products to total processes increases. This provides some insight into observed stability of competitive capitalist economies in comparison to monopolistic economies. Capitalist economies are also shown to have low unemployment.
Agroforestry versus farm mosaic systems - Comparing land-use efficiency, economic returns and risks under climate change effects.

PubMed

Paul, Carola; Weber, Michael; Knoke, Thomas

2017-06-01

Increasing land-use conflicts call for the development of land-use systems that reconcile agricultural production with the provisioning of multiple ecosystem services, including climate change mitigation. Agroforestry has been suggested as a global solution to increase land-use efficiency, while reducing environmental impacts and economic risks for farmers. Past research has often focused on comparing tree-crop combinations with agricultural monocultures, but agroforestry has seldom been systematically compared to other forms of land-use diversification, including a farm mosaic. This form of diversification mixes separate parcels of different land uses within the farm. The objective of this study was to develop a modelling approach to compare the performance of the agroforestry and farm mosaic diversification strategies, accounting for tree-crop interaction effects and economic and climate uncertainty. For this purpose, Modern Portfolio Theory and risk simulation were coupled with the process-based biophysical simulation model WaNuLCAS 4.0. For an example application, we used data from a field trial in Panama. The results show that the simulated agroforestry systems (Taungya, alley cropping and border planting) could outperform a farm mosaic approach in terms of cumulative production and return. Considering market and climate uncertainty, agroforestry showed an up to 21% higher economic return at the same risk level (i.e. standard deviation of economic returns). Farm compositions with large shares of land allocated to maize cultivation were also more severely affected by an increasing drought frequency in terms of both risks and returns. Our study demonstrates that agroforestry can be an economically efficient diversification strategy, but only if the design allows for economies of scope, beneficial interactions between trees and crops and higher income diversification compared to a farm mosaic. The modelling approach can make an important contribution to support land-use decisions at the farm level and reduce land-use conflicts at the landscape level. Copyright © 2017 Elsevier B.V. All rights reserved.
LIME SPRAY DRYER FLUE GAS DESULFURIZATION COMPUTER MODEL USERS MANUAL

EPA Science Inventory

The report describes a lime spray dryer/baghouse (FORTRAN) computer model that simulates SO2 removal and permits study of related impacts on design and economics as functions of design parameters and operating conditions for coal-fired electric generating units. The model allows ...
77 FR 13607 - Agency Forms Undergoing Paperwork Reduction Act Review

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-07

... Transformation Grants: Use of System Dynamic Modeling and Economic Analysis in Select Communities--New--National... community interventions. Using a system dynamics approach, CDC also plans to conduct simulation modeling... the development of analytic tools for system dynamics modeling under more limited conditions. The...
Civil Tiltrotor Feasibility Study for the New York and Washington Terminal Areas

NASA Technical Reports Server (NTRS)

Stouffer, Virginia; Johnson, Jesse; Gribko, Joana; Yackovetsky, Robert (Technical Monitor)

2001-01-01

NASA tasked LMI to assess the potential contributions of a yet-undeveloped Civil Tiltrotor aircraft (CTR) in improving capacity in the National Airspace System in all weather conditions. The CTRs studied have assumed operating parameters beyond current CTR capabilities. LMI analyzed CTRs three ways: in fast-time terminal area modeling simulations of New York and Washington to determine delay and throughput impacts; in the Integrated Noise Model, to determine local environmental impact; and with an economic model, to determine the price viability of a CTR. The fast-time models encompassed a 250 nmi range and included traffic interactions from local airports. Both the fast-time simulation and the noise model assessed impacts from traffic levels projected for 1999, 2007, and 2017. Results: CTRs can reduce terminal area delays due to concrete congestion in all time frames. The maximum effect, the ratio of CTRs to jets and turboprop aircraft at a subject airport should be optimized. The economic model considered US traffic only and forecasted CTR sales beginning in 2010.
CO2, energy and economy interactions: A multisectoral, dynamic, computable general equilibrium model for Korea

NASA Astrophysics Data System (ADS)

Kang, Yoonyoung

While vast resources have been invested in the development of computational models for cost-benefit analysis for the "whole world" or for the largest economies (e.g. United States, Japan, Germany), the remainder have been thrown together into one model for the "rest of the world." This study presents a multi-sectoral, dynamic, computable general equilibrium (CGE) model for Korea. This research evaluates the impacts of controlling COsb2 emissions using a multisectoral CGE model. This CGE economy-energy-environment model analyzes and quantifies the interactions between COsb2, energy and economy. This study examines interactions and influences of key environmental policy components: applied economic instruments, emission targets, and environmental tax revenue recycling methods. The most cost-effective economic instrument is the carbon tax. The economic effects discussed include impacts on main macroeconomic variables (in particular, economic growth), sectoral production, and the energy market. This study considers several aspects of various COsb2 control policies, such as the basic variables in the economy: capital stock and net foreign debt. The results indicate emissions might be stabilized in Korea at the expense of economic growth and with dramatic sectoral allocation effects. Carbon dioxide emissions stabilization could be achieved to the tune of a 600 trillion won loss over a 20 year period (1990-2010). The average annual real GDP would decrease by 2.10% over the simulation period compared to the 5.87% increase in the Business-as-Usual. This model satisfies an immediate need for a policy simulation model for Korea and provides the basic framework for similar economies. It is critical to keep the central economic question at the forefront of any discussion regarding environmental protection. How much will reform cost, and what does the economy stand to gain and lose? Without this model, the policy makers might resort to hesitation or even blind speculation. With the model, the policy makers gain the power of prediction. This model serves as a tool for constructing the most effective strategy for Korea.
Computational study of nonlinear plasma waves. [plasma simulation model applied to electrostatic waves in collisionless plasma

NASA Technical Reports Server (NTRS)

Matsuda, Y.

1974-01-01

A low-noise plasma simulation model is developed and applied to a series of linear and nonlinear problems associated with electrostatic wave propagation in a one-dimensional, collisionless, Maxwellian plasma, in the absence of magnetic field. It is demonstrated that use of the hybrid simulation model allows economical studies to be carried out in both the linear and nonlinear regimes with better quantitative results, for comparable computing time, than can be obtained by conventional particle simulation models, or direct solution of the Vlasov equation. The characteristics of the hybrid simulation model itself are first investigated, and it is shown to be capable of verifying the theoretical linear dispersion relation at wave energy levels as low as .000001 of the plasma thermal energy. Having established the validity of the hybrid simulation model, it is then used to study the nonlinear dynamics of monochromatic wave, sideband instability due to trapped particles, and satellite growth.
Use of a grid simulation model for longer-term analysis of wind energy integration

NASA Astrophysics Data System (ADS)

Bossanyi, E.

A simulation model of an electricity generating system is used to study the integration of wind energy onto the system. Most of the system cost savings achieved are due to the savings of fossil fuels, but in the long term additional savings result from re-optimization of the plant mix. Break-even costs are calculated for wind turbines to become economically viable as fossil fuel savers. This allows the optimum economic penetration level for wind turbines of any given cost to be derived. Break-even costs up to reasonably large penetrations appear to be within reach with modern technology. Results are also given with scenarios of increasing fossil fuel prices and increased nuclear capacity.
The structure of disaster resilience: a framework for simulations and policy recommendations

NASA Astrophysics Data System (ADS)

Edwards, J. H. Y.

2015-04-01

In this era of rapid climate change there is an urgent need for interdisciplinary collaboration and understanding in the study of what determines resistance to disasters and recovery speed. This paper is an economist's contribution to that effort. It traces the entrance of the word "resilience" from ecology into the social science literature on disasters, provides a formal economic definition of resilience that can be used in mathematical modeling, incorporates this definition into a multilevel model that suggests appropriate policy roles and targets at each level, and draws on the recent empirical literature on the economics of disaster, searching for policy handles that can stimulate higher resilience. On the whole it provides a framework for simulations and for formulating disaster resilience policies.
The structure of disaster resilience: a framework for simulations and policy recommendations

NASA Astrophysics Data System (ADS)

Edwards, J. H. Y.

2014-09-01

In this era of rapid climate change there is an urgent need for interdisciplinary collaboration and understanding in the study of what determines resistance to disasters and recovery speed. This paper is an economist's contribution to that effort. It traces the entrance of the word "resilience" from ecology into the social science literature on disasters, provides a formal economic definition of resilience that can be used in mathematical modeling, incorporates this definition into a multilevel model that suggests appropriate policy roles and targets at each level, and draws on the recent empirical literature on the economics of disaster searching for policy handles that can stimulate higher resilience. On the whole it provides a framework for simulations and for formulating disaster resilience policies.
e-Dairy: a dynamic and stochastic whole-farm model that predicts biophysical and economic performance of grazing dairy systems.

PubMed

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N

2013-05-01

A whole-farm, stochastic and dynamic simulation model was developed to predict biophysical and economic performance of grazing dairy systems. Several whole-farm models simulate grazing dairy systems, but most of them work at a herd level. This model, named e-Dairy, differs from the few models that work at an animal level, because it allows stochastic behaviour of the genetic merit of individual cows for several traits, namely, yields of milk, fat and protein, live weight (LW) and body condition score (BCS) within a whole-farm model. This model accounts for genetic differences between cows, is sensitive to genotype × environment interactions at an animal level and allows pasture growth, milk and supplements price to behave stochastically. The model includes an energy-based animal module that predicts intake at grazing, mammary gland functioning and body lipid change. This whole-farm model simulates a 365-day period for individual cows within a herd, with cow parameters randomly generated on the basis of the mean parameter values, defined as input and variance and co-variances from experimental data sets. The main inputs of e-Dairy are farm area, use of land, type of pasture, type of crops, monthly pasture growth rate, supplements offered, nutritional quality of feeds, herd description including herd size, age structure, calving pattern, BCS and LW at calving, probabilities of pregnancy, average genetic merit and economic values for items of income and costs. The model allows to set management policies to define: dry-off cows (ceasing of lactation), target pre- and post-grazing herbage mass and feed supplementation. The main outputs are herbage dry matter intake, annual pasture utilisation, milk yield, changes in BCS and LW, economic farm profit and return on assets. The model showed satisfactory accuracy of prediction when validated against two data sets from farmlet system experiments. Relative prediction errors were <10% for all variables, and concordance correlation coefficients over 0.80 for annual pasture utilisation, yields of milk and milk solids (MS; fat plus protein), and of 0.69 and 0.48 for LW and BCS, respectively. A simulation of two contrasting dairy systems is presented to show the practical use of the model. The model can be used to explore the effects of feeding level and genetic merit and their interactions for grazing dairy systems, evaluating the trade-offs between profit and the associated risk.
Large scale hydro-economic modelling for policy support

NASA Astrophysics Data System (ADS)

de Roo, Ad; Burek, Peter; Bouraoui, Faycal; Reynaud, Arnaud; Udias, Angel; Pistocchi, Alberto; Lanzanova, Denis; Trichakis, Ioannis; Beck, Hylke; Bernhard, Jeroen

2014-05-01

To support European Union water policy making and policy monitoring, a hydro-economic modelling environment has been developed to assess optimum combinations of water retention measures, water savings measures, and nutrient reduction measures for continental Europe. This modelling environment consists of linking the agricultural CAPRI model, the LUMP land use model, the LISFLOOD water quantity model, the EPIC water quality model, the LISQUAL combined water quantity, quality and hydro-economic model, and a multi-criteria optimisation routine. With this modelling environment, river basin scale simulations are carried out to assess the effects of water-retention measures, water-saving measures, and nutrient-reduction measures on several hydro-chemical indicators, such as the Water Exploitation Index (WEI), Nitrate and Phosphate concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the manufacturing-industry sector, the energy-production sector and the domestic sector, as well as the economic loss due to flood damage. Recently, this model environment is being extended with a groundwater model to evaluate the effects of measures on the average groundwater table and available resources. Also, water allocation rules are addressed, while having environmental flow included as a minimum requirement for the environment. Economic functions are currently being updated as well. Recent development and examples will be shown and discussed, as well as open challenges.

Macroeconomic and household-level impacts of HIV/AIDS in Botswana.

PubMed

Jefferis, Keith; Kinghorn, Anthony; Siphambe, Happy; Thurlow, James

2008-07-01

To measure the impact of HIV/AIDS on economic growth and poverty in Botswana and estimate how providing treatment can mitigate its effects. Demographic and financial projections were combined with economic simulation models, including a macroeconomic growth model and a macro-microeconomic computable general equilibrium and microsimulation model. HIV/AIDS significantly reduces economic growth and increases household poverty. The impact is now severe enough to be affecting the economy as a whole, and threatens to pull some of the uninfected population into poverty. Providing antiretroviral therapy can partly offset this negative effect. Treatment increases health's share of government expenditure only marginally, because it increases economic growth and because withholding treatment raises the cost of other health services. Botswana's treatment programme is appropriate from a macroeconomic perspective. Conducting macroeconomic impact assessments is important in countries where prevalence rates are particularly high.
The RTOG Outcomes Model: economic end points and measures.

PubMed

Konski, Andre; Watkins-Bruner, Deborah

2004-03-01

Recognising the value added by economic evaluations of clinical trials and the interaction of clinical, humanistic and economic end points, the Radiation Therapy Oncology Group (RTOG) has developed an Outcomes Model that guides the comprehensive assessment of this triad of end points. This paper will focus on the economic component of the model. The Economic Impact Committee was founded in 1994 to study the economic impact of clinical trials of cancer care. A steep learning curve ensued with considerable time initially spent understanding the methodology of economic analysis. Since then, economic analyses have been performed on RTOG clinical trials involving treatments for patients with non-small cell lung cancer, locally-advanced head and neck cancer and prostate cancer. As the care of cancer patients evolves with time, so has the economic analyses performed by the Economic Impact Committee. This paper documents the evolution of the cost-effectiveness analyses of RTOG from performing average cost-utility analysis to more technically sophisticated Monte Carlo simulation of Markov models, to incorporating prospective economic analyses as an initial end point. Briefly, results indicated that, accounting for quality-adjusted survival, concurrent chemotherapy and radiation for the treatment of non-small cell lung cancer, more aggressive radiation fractionation schedules for head and neck cancer and the addition of hormone therapy to radiation for prostate cancer are within the range of economically acceptable recommendations. The RTOG economic analyses have provided information that can further inform clinicians and policy makers of the value added of new or improved treatments.
Hybrid and electric advanced vehicle systems (heavy) simulation

NASA Technical Reports Server (NTRS)

Hammond, R. A.; Mcgehee, R. K.

1981-01-01

A computer program to simulate hybrid and electric advanced vehicle systems (HEAVY) is described. It is intended for use early in the design process: concept evaluation, alternative comparison, preliminary design, control and management strategy development, component sizing, and sensitivity studies. It allows the designer to quickly, conveniently, and economically predict the performance of a proposed drive train. The user defines the system to be simulated using a library of predefined component models that may be connected to represent a wide variety of propulsion systems. The development of three models are discussed as examples.
The Impacts of Information-Sharing Mechanisms on Spatial Market Formation Based on Agent-Based Modeling

PubMed Central

Li, Qianqian; Yang, Tao; Zhao, Erbo; Xia, Xing’ang; Han, Zhangang

2013-01-01

There has been an increasing interest in the geographic aspects of economic development, exemplified by P. Krugman’s logical analysis. We show in this paper that the geographic aspects of economic development can be modeled using multi-agent systems that incorporate multiple underlying factors. The extent of information sharing is assumed to be a driving force that leads to economic geographic heterogeneity across locations without geographic advantages or disadvantages. We propose an agent-based market model that considers a spectrum of different information-sharing mechanisms: no information sharing, information sharing among friends and pheromone-like information sharing. Finally, we build a unified model that accommodates all three of these information-sharing mechanisms based on the number of friends who can share information. We find that the no information-sharing model does not yield large economic zones, and more information sharing can give rise to a power-law distribution of market size that corresponds to the stylized fact of city size and firm size distributions. The simulations show that this model is robust. This paper provides an alternative approach to studying economic geographic development, and this model could be used as a test bed to validate the detailed assumptions that regulate real economic agglomeration. PMID:23484007
Utilization of eucalyptus for bioelectricity production in brazil via fast pyrolysis: a techno-economic analysis

USDA-ARS?s Scientific Manuscript database

In this study, a process model of a 2000 metric ton per day (MTPD) eucalyptus Tail Gas Reactive Pyrolysis (TGRP) and electricity generation plant was developed and simulated in SimSci Pro/II software for the purpose of evaluating its techno-economic viability in Brazil. Two scenarios were compared b...
Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

NASA Astrophysics Data System (ADS)

Sheer, D. P.

2008-12-01

For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints, and short term objectives) as well. In the models operating rules represent different models of human behavior, and the objective of the modeling is to find rules for human behavior that perform well in terms of long term human objectives. The conceptual model used to represent human behavior incorporates economic multi-objective optimization for surrogate objectives, and rules that set those objectives based on current conditions and accounting for uncertainty, at least implicitly. The author asserts that real world operating rules follow this form and have evolved because they have been perceived as successful in the past. Thus, the modeling efforts focus on human behavior in much the same way that economic models focus on human behavior. This paper illustrates the above concepts with real world examples.
Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

PubMed

Arnold, Matthias

2017-12-02

The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.
A systematic review of health economic models of opioid agonist therapies in maintenance treatment of non-prescription opioid dependence.

PubMed

Chetty, Mersha; Kenworthy, James J; Langham, Sue; Walker, Andrew; Dunlop, William C N

2017-02-24

Opioid dependence is a chronic condition with substantial health, economic and social costs. The study objective was to conduct a systematic review of published health-economic models of opioid agonist therapy for non-prescription opioid dependence, to review the different modelling approaches identified, and to inform future modelling studies. Literature searches were conducted in March 2015 in eight electronic databases, supplemented by hand-searching reference lists and searches on six National Health Technology Assessment Agency websites. Studies were included if they: investigated populations that were dependent on non-prescription opioids and were receiving opioid agonist or maintenance therapy; compared any pharmacological maintenance intervention with any other maintenance regimen (including placebo or no treatment); and were health-economic models of any type. A total of 18 unique models were included. These used a range of modelling approaches, including Markov models (n = 4), decision tree with Monte Carlo simulations (n = 3), decision analysis (n = 3), dynamic transmission models (n = 3), decision tree (n = 1), cohort simulation (n = 1), Bayesian (n = 1), and Monte Carlo simulations (n = 2). Time horizons ranged from 6 months to lifetime. The most common evaluation was cost-utility analysis reporting cost per quality-adjusted life-year (n = 11), followed by cost-effectiveness analysis (n = 4), budget-impact analysis/cost comparison (n = 2) and cost-benefit analysis (n = 1). Most studies took the healthcare provider's perspective. Only a few models included some wider societal costs, such as productivity loss or costs of drug-related crime, disorder and antisocial behaviour. Costs to individuals and impacts on family and social networks were not included in any model. A relatively small number of studies of varying quality were found. Strengths and weaknesses relating to model structure, inputs and approach were identified across all the studies. There was no indication of a single standard emerging as a preferred approach. Most studies omitted societal costs, an important issue since the implications of drug abuse extend widely beyond healthcare services. Nevertheless, elements from previous models could together form a framework for future economic evaluations in opioid agonist therapy including all relevant costs and outcomes. This could more adequately support decision-making and policy development for treatment of non-prescription opioid dependence.
Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

USGS Publications Warehouse

Costanza, Jennifer; Abt, Robert C.; McKerrow, Alexa; Collazo, Jaime

2015-01-01

We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.
Hurricane Sandy Economic Impacts Assessment: A Computable General Equilibrium Approach and Validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boero, Riccardo; Edwards, Brian Keith

Economists use computable general equilibrium (CGE) models to assess how economies react and self-organize after changes in policies, technology, and other exogenous shocks. CGE models are equation-based, empirically calibrated, and inspired by Neoclassical economic theory. The focus of this work was to validate the National Infrastructure Simulation and Analysis Center (NISAC) CGE model and apply it to the problem of assessing the economic impacts of severe events. We used the 2012 Hurricane Sandy event as our validation case. In particular, this work first introduces the model and then describes the validation approach and the empirical data available for studying themore » event of focus. Shocks to the model are then formalized and applied. Finally, model results and limitations are presented and discussed, pointing out both the model degree of accuracy and the assessed total damage caused by Hurricane Sandy.« less
Estimates of the long-term U.S. economic impacts of global climate change-induced drought.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehlen, Mark Andrew; Loose, Verne W.; Warren, Drake E.

2010-01-01

While climate-change models have done a reasonable job of forecasting changes in global climate conditions over the past decades, recent data indicate that actual climate change may be much more severe. To better understand some of the potential economic impacts of these severe climate changes, Sandia economists estimated the impacts to the U.S. economy of climate change-induced impacts to U.S. precipitation over the 2010 to 2050 time period. The economists developed an impact methodology that converts changes in precipitation and water availability to changes in economic activity, and conducted simulations of economic impacts using a large-scale macroeconomic model of themore » U.S. economy.« less
Multi-agent modelling framework for water, energy and other resource networks

NASA Astrophysics Data System (ADS)

Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

2015-12-01

Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be used to evaluate a multitude of topologies for identifying the optimal location of infrastructure investments. Pynsim is available on GitHub or via standard python installer packages such as pip. It comes with several examples and online documentation, making it attractive for those less experienced in software engineering.
Incorporating agricultural management into an earth system model for the Pacific Northwest region: Interactions between climate, hydrology, agriculture, and economics

NASA Astrophysics Data System (ADS)

Chinnayakanahalli, K.; Adam, J. C.; Stockle, C.; Nelson, R.; Brady, M.; Rajagopalan, K.; Barber, M. E.; Dinesh, S.; Malek, K.; Yorgey, G.; Kruger, C.; Marsh, T.; Yoder, J.

2011-12-01

For better management and decision making in the face of climate change, earth system models must explicitly account for natural resource and agricultural management activities. Including crop system, water management, and economic models into an earth system modeling framework can help in answering questions related to the impacts of climate change on irrigation water and crop productivity, how agricultural producers can adapt to anticipated climate change, and how agricultural practices can mitigate climate change. Herein we describe the coupling of the Variability Infiltration Capacity (VIC) land surface model, which solves the water and energy balances of the hydrologic cycle at regional scales, with a crop-growth model, CropSyst. This new model, VIC-CropSyst, is the land surface model that will be used in a new regional-scale model development project focused on the Pacific Northwest, termed BioEarth. Here we describe the VIC-CropSyst coupling process and its application over the Columbia River basin (CRB) using agricultural-specific land cover information. The Washington State Department of Agriculture (WSDA) and U. S. Department of Agriculture (USDA) cropland data layers were used to identify agricultural land use patterns, in which both irrigated and dry land crops were simulated. The VIC-CropSyst model was applied over the CRB for the historical period of 1976 - 2006 to establish a baseline for surface water availability, irrigation demand, and crop production. The model was then applied under future (2030s) climate change scenarios derived from statistically-downscaled Global Circulation Models output under two emission scenarios (A1B and B1). Differences between simulated future and historical irrigation demand, irrigation water availability, and crop production were used in an economics model to identify the most economically-viable future cropping pattern. The economics model was run under varying scenarios of regional growth, trade, water pricing, and water capacity providing a spectrum of possible future cropping patterns. The resulting cropping patterns were then used in VIC-CropSyst to quantify the impacts of climate change, economic, and water management scenarios on crop production, and water resources availability. This modeling framework provides opportunities to study the interactions between human activities and complex natural processes and is a valuable tool for inclusion in an earth system model with the goal of informing land use and water management.
Economic modeling of fault tolerant flight control systems in commercial applications

NASA Technical Reports Server (NTRS)

Finelli, G. B.

1982-01-01

This paper describes the current development of a comprehensive model which will supply the assessment and analysis capability to investigate the economic viability of Fault Tolerant Flight Control Systems (FTFCS) for commercial aircraft of the 1990's and beyond. An introduction to the unique attributes of fault tolerance and how they will influence aircraft operations and consequent airline costs and benefits is presented. Specific modeling issues and elements necessary for accurate assessment of all costs affected by ownership and operation of FTFCS are delineated. Trade-off factors are presented, aimed at exposing economically optimal realizations of system implementations, resource allocation, and operating policies. A trade-off example is furnished to graphically display some of the analysis capabilities of the comprehensive simulation model now being developed.
Effects of the 2008 flood on economic performance and food security in Yemen: a simulation analysis.

PubMed

Breisinger, Clemens; Ecker, Olivier; Thiele, Rainer; Wiebelt, Manfred

2016-04-01

Extreme weather events such as floods and droughts can have devastating consequences for individual well being and economic development, in particular in poor societies with limited availability of coping mechanisms. Combining a dynamic computable general equilibrium model of the Yemeni economy with a household-level calorie consumption simulation model, this paper assesses the economy-wide, agricultural and food security effects of the 2008 tropical storm and flash flood that hit the Hadramout and Al-Mahrah governorates. The estimation results suggest that agricultural value added, farm household incomes and rural food security deteriorated long term in the flood-affected areas. Due to economic spillover effects, significant income losses and increases in food insecurity also occurred in areas that were unaffected by flooding. This finding suggests that while most relief efforts are typically concentrated in directly affected areas, future efforts should also consider surrounding areas and indirectly affected people. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.
Community Level Impact Assessment--Extension Applications.

ERIC Educational Resources Information Center

Woods, Mike D.; Doeksen, Gerald A.

Using the Oklahoma State University (OSU) computerized community simulation model, extension professionals can provide local decision makers with information derived from an impact model that is dynamic, community specific, and easy to adapt to different communities. The four main sections of the OSU model are an economic account, a capital…
A Microcomputer Program that Simulates the Baumol-Tobin Transactions Demand for Money.

ERIC Educational Resources Information Center

Beckman, Steven

1987-01-01

This article describes an economic model dealing with the demand for money and a microcomputer program which enables students to experiment with cash management techniques. By simulating personal experiences, the program teaches how changes in income, interest rates, and charges for exchanging bonds and cash affect money demand. (Author/JDH)
Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

NASA Astrophysics Data System (ADS)

Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

2008-12-01

Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.
A model of economic growth with physical and human capital: The role of time delays.

PubMed

Gori, Luca; Guerrini, Luca; Sodini, Mauro

2016-09-01

This article aims at analysing a two-sector economic growth model with discrete delays. The focus is on the dynamic properties of the emerging system. In particular, this study concentrates on the stability properties of the stationary solution, characterised by analytical results and geometrical techniques (stability crossing curves), and the conditions under which oscillatory dynamics emerge (through Hopf bifurcations). In addition, this article proposes some numerical simulations to illustrate the behaviour of the system when the stationary equilibrium is unstable.
Modelling gambling time and economic assignments to weekly trip behaviour to gambling venues

NASA Astrophysics Data System (ADS)

Baker, R. G. V.; Marshall, D. C.

2005-12-01

The study of gambling and its socio-economic structures should be an area of growing interest to a society-relevant geography. In Australia, electronic gaming machines (EGMs) have dominated recent gambling industry growth. As EGMs have diffused through the urban hierarchy, there is a growing recognition that EGM distribution often correlates with levels of socio-economic status. Marshall and Baker (2002) showed that a similar EGM socio-economic assignment model evolved in the capital cities of Sydney and Melbourne, Australia, even though these cities have substantially different historical and legislative EGM environments. This paper looks at a related space-time model in the context of trip-making to gaming venues, relative to an Index of Economic Resources from the Australian Bureau of Statistics. A simulation of the model predicts different types of gambling behaviour. It also shows that venue hours can affect time-economic trip behaviour. The model is then applied to EGM gambling data gathered in an urban hierarchy on the north coast of New South Wales, Australia. The results define a gaussian-type low involvement ‘recreational random’ gambling for patrons, whereas for more involved gamblers (in terms of time spent gambling), there are discrete behavioural periods over the week for a wider economic cohort. This leads to the possibility of a spectrum of time-economic EGM gambling assignments for participating households in metropolitan and non-metropolitan areas.

An expanded system simulation model for solar energy storage (technical report), volume 1

NASA Technical Reports Server (NTRS)

Warren, A. W.

1979-01-01

The simulation model for wind energy storage (SIMWEST) program now includes wind and/or photovoltaic systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) and is available for the UNIVAC 1100 series and the CDC 6000 series computers. The level of detail is consistent with a role of evaluating the economic feasibility as well as the general performance of wind and/or photovoltaic energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind and/or photovoltaic source/storage/application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/0, the integration of system dynamics, and the iteration for conveyance of variables.
A simulation model for wind energy storage systems. Volume 2: Operation manual

NASA Technical Reports Server (NTRS)

Warren, A. W.; Edsinger, R. W.; Burroughs, J. D.

1977-01-01

A comprehensive computer program (SIMWEST) developed for the modeling of wind energy/storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel, and pneumatic) is described. Features of the program include: a precompiler which generates computer models (in FORTRAN) of complex wind source/storage/application systems, from user specifications using the respective library components; a program which provides the techno-economic system analysis with the respective I/O the integration of system dynamics, and the iteration for conveyance of variables; and capability to evaluate economic feasibility as well as general performance of wind energy systems. The SIMWEST operation manual is presented and the usage of the SIMWEST program and the design of the library components are described. A number of example simulations intended to familiarize the user with the program's operation is given along with a listing of each SIMWEST library subroutine.
Assessment of risk due to the use of carbon fiber composites in commercial and general aviation

NASA Technical Reports Server (NTRS)

Fiksel, J.; Rosenfield, D.; Kalelkar, A.

1980-01-01

The development of a national risk profile for the total annual aircraft losses due to carbon fiber composite (CFC) usage through 1993 is discussed. The profile was developed using separate simulation methods for commercial and general aviation aircraft. A Monte Carlo method which was used to assess the risk in commercial aircraft is described. The method projects the potential usage of CFC through 1993, investigates the incidence of commercial aircraft fires, models the potential release and dispersion of carbon fibers from a fire, and estimates potential economic losses due to CFC damaging electronic equipment. The simulation model for the general aviation aircraft is described. The model emphasizes variations in facility locations and release conditions, estimates distribution of CFC released in general aviation aircraft accidents, and tabulates the failure probabilities and aggregate economic losses in the accidents.
Conceptual modeling for Prospective Health Technology Assessment.

PubMed

Gantner-Bär, Marion; Djanatliev, Anatoli; Prokosch, Hans-Ulrich; Sedlmayr, Martin

2012-01-01

Prospective Health Technology Assessment (ProHTA) is a new and innovative approach to analyze and assess new technologies, methods and procedures in health care. Simulation processes are used to model innovations before the cost-intensive design and development phase. Thus effects on patient care, the health care system as well as health economics aspects can be estimated. To generate simulation models a valid information base is necessary and therefore conceptual modeling is most suitable. Project-specifically improved methods and characteristics of simulation modeling are combined in the ProHTA Conceptual Modeling Process and initially implemented for acute ischemic stroke treatment in Germany. Additionally the project aims at simulation of other diseases and health care systems as well. ProHTA is an interdisciplinary research project within the Cluster of Excellence for Medical Technology - Medical Valley European Metropolitan Region Nuremberg (EMN), which is funded by the German Federal Ministry of Education and Research (BMBF), project grant No. 01EX1013B.
Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review.

PubMed

Kolovos, Spyros; Bosmans, Judith E; Riper, Heleen; Chevreul, Karine; Coupé, Veerle M H; van Tulder, Maurits W

2017-09-01

An increasing number of model-based studies that evaluate the cost effectiveness of treatments for depression are being published. These studies have different characteristics and use different simulation methods. We aimed to systematically review model-based studies evaluating the cost effectiveness of treatments for depression and examine which modelling technique is most appropriate for simulating the natural course of depression. The literature search was conducted in the databases PubMed, EMBASE and PsycInfo between 1 January 2002 and 1 October 2016. Studies were eligible if they used a health economic model with quality-adjusted life-years or disability-adjusted life-years as an outcome measure. Data related to various methodological characteristics were extracted from the included studies. The available modelling techniques were evaluated based on 11 predefined criteria. This methodological review included 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven. There were substantial methodological differences between the studies. Since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be more appropriate than the others for a pragmatic representation of the course of depression. However, direct comparisons between the available modelling techniques are necessary to yield firm conclusions.
Simulating Spatial Growth Patterns in Developing Countries: A Case of Shama in the Western Region of Ghana.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Nyarko, B. K.

2014-12-01

The integration of geographic information systems (GIS) and agent-based modelling (ABM) can be an efficient tool to improve spatial planning practices. This paper utilizes GIS and ABM approaches to simulate spatial growth patterns of settlement structures in Shama. A preliminary household survey on residential location decision-making choice served as the behavioural rule for household agents in the model. Physical environment properties of the model were extracted from a 2005 image implemented in NetLogo. The resulting growth pattern model was compared with empirical growth patterns to ascertain the model's accuracy. The paper establishes that the development of unplanned structures and its evolving structural pattern are a function of land price, proximity to economic centres, household economic status and location decision-making patterns. The application of the proposed model underlines its potential for integration into urban planning policies and practices, and for understanding residential decision-making processes in emerging cities in developing countries. Key Words: GIS; Agent-based modelling; Growth patterns; NetLogo; Location decision making; Computational Intelligence.
The Clinical and Economic Benefits of Co-Testing Versus Primary HPV Testing for Cervical Cancer Screening: A Modeling Analysis.

PubMed

Felix, Juan C; Lacey, Michael J; Miller, Jeffrey D; Lenhart, Gregory M; Spitzer, Mark; Kulkarni, Rucha

2016-06-01

Consensus United States cervical cancer screening guidelines recommend use of combination Pap plus human papillomavirus (HPV) testing for women aged 30 to 65 years. An HPV test was approved by the Food and Drug Administration in 2014 for primary cervical cancer screening in women age 25 years and older. Here, we present the results of clinical-economic comparisons of Pap plus HPV mRNA testing including genotyping for HPV 16/18 (co-testing) versus DNA-based primary HPV testing with HPV 16/18 genotyping and reflex cytology (HPV primary) for cervical cancer screening. A health state transition (Markov) model with 1-year cycling was developed using epidemiologic, clinical, and economic data from healthcare databases and published literature. A hypothetical cohort of one million women receiving triennial cervical cancer screening was simulated from ages 30 to 70 years. Screening strategies compared HPV primary to co-testing. Outcomes included total and incremental differences in costs, invasive cervical cancer (ICC) cases, ICC deaths, number of colposcopies, and quality-adjusted life years for cost-effectiveness calculations. Comprehensive sensitivity analyses were performed. In a simulation cohort of one million 30-year-old women modeled up to age 70 years, the model predicted that screening with HPV primary testing instead of co-testing could lead to as many as 2,141 more ICC cases and 2,041 more ICC deaths. In the simulation, co-testing demonstrated a greater number of lifetime quality-adjusted life years (22,334) and yielded $39.0 million in savings compared with HPV primary, thereby conferring greater effectiveness at lower cost. Model results demonstrate that co-testing has the potential to provide improved clinical and economic outcomes when compared with HPV primary. While actual cost and outcome data are evaluated, these findings are relevant to U.S. healthcare payers and women's health policy advocates seeking cost-effective cervical cancer screening technologies.
Effect of human behavior on economizer efficacy and thermal comfort in southern California

NASA Astrophysics Data System (ADS)

Lanning, TIghe Glennon

California has set a zero net-energy conservation goal for the residential sector that is to be achieved by 2020 (California Energy Commission 2011). To reduce energy consumption in the building sector, modern buildings should fundamentally incorporate sustainable performance standards, involving renewable systems, climate-specific strategies, and consideration of a variety of users. Building occupants must operate in concert with the buildings they inhabit in order to maximize the potential of the building, its systems, and their own comfort. In climates with significant diurnal temperature swings, environmental controls designed to capitalize on this should be considered to reduce cooling-related loads. One specific strategy is the air-side economizer, which uses daily outdoor temperature swings to reduce indoor temperature swings. Traditionally a similar effect could be achieved by using thermal mass to buffer indoor temperature swings through thermal lag. Economizers reduce the amount of thermal mass typically required by naturally ventilated buildings. Fans are used to force cool nighttime air deep into the building, allowing lower mass buildings to take advantage of nighttime cooling. Economizers connect to a thermostat, and when the outdoor temperature dips below a programmed set-point the economizer draws cool air from outside, flushing out the warmed interior air. This type of system can be simulated with reasonable accuracy by energy modeling programs; however, because the system is occupant-driven (as opposed to a truly passive mass-driven system) any unpredictable occupant behavior can reduce its effectiveness and create misleading simulation results. This unpredictably has helped prevent the spread of economizers in the residential market. This study investigated to what extent human behavior affected the performance of economizer-based HVAC systems, based on physical observations, environmental data collections, and energy simulations of a residential building in Los Angeles, California. Tangible measures for alleviating problems, such as user-friendly interface design and the incorporation of human behavior into energy models are recommended based on these observations.
Global economic impacts of severe Space Weather.

NASA Astrophysics Data System (ADS)

Schulte In Den Baeumen, Hagen; Cairns, Iver

Coronal mass ejections (CMEs) strong enough to create electromagnetic effects at latitudes below the auroral oval are frequent events, and could have substantial impacts on electric power transmission and telecommunication grids. Modern society’s heavy reliance on these domestic and international networks increases our susceptibility to such a severe Space Weather event. Using a new high-resolution model of the global economy we simulate the economic impact of large CMEs for 3 different planetary orientations. We account for the economic impacts within the countries directly affected as well as the post-disaster economic shock in partner economies through international trade. For the CMEs modeled the total global economic impacts would range from US 380 billion to US 1 trillion. Of this total economic shock 50 % would be felt in countries outside the zone of direct impact, leading to a loss in global GDP of 0.1 - 1 %. A severe Space Weather event could lead to global economic damages of the same order as other weather disasters, climate change, and extreme financial crisis.
On purpose simulation model for molten salt CSP parabolic trough

NASA Astrophysics Data System (ADS)

Caranese, Carlo; Matino, Francesca; Maccari, Augusto

2017-06-01

The utilization of computer codes and simulation software is one of the fundamental aspects for the development of any kind of technology and, in particular, in CSP sector for researchers, energy institutions, EPC and others stakeholders. In that extent, several models for the simulation of CSP plant have been developed with different main objectives (dynamic simulation, productivity analysis, techno economic optimization, etc.), each of which has shown its own validity and suitability. Some of those models have been designed to study several plant configurations taking into account different CSP plant technologies (Parabolic trough, Linear Fresnel, Solar Tower or Dish) and different settings for the heat transfer fluid, the thermal storage systems and for the overall plant operating logic. Due to a lack of direct experience of Molten Salt Parabolic Trough (MSPT) commercial plant operation, most of the simulation tools do not foresee a suitable management of the thermal energy storage logic and of the solar field freeze protection system, but follow standard schemes. ASSALT, Ase Software for SALT csp plants, has been developed to improve MSPT plant's simulations, by exploiting the most correct operational strategies in order to provide more accurate technical and economical results. In particular, ASSALT applies MSPT specific control logics for the electric energy production and delivery strategy as well as the operation modes of the Solar Field in off-normal sunshine condition. With this approach, the estimated plant efficiency is increased and the electricity consumptions required for the plant operation and management is drastically reduced. Here we present a first comparative study on a real case 55 MWe Molten Salt Parabolic Trough CSP plant placed in the Tibetan highlands, using ASSALT and SAM (System Advisor Model), which is a commercially available simulation tool.
A Discrete Event Simulation Model to Assess the Economic Value of a Hypothetical Pharmacogenomics Test for Statin-Induced Myopathy in Patients Initiating a Statin in Secondary Cardiovascular Prevention.

PubMed

Mitchell, Dominic; Guertin, Jason R; Dubois, Anick; Dubé, Marie-Pierre; Tardif, Jean-Claude; Iliza, Ange Christelle; Fanton-Aita, Fiorella; Matteau, Alexis; LeLorier, Jacques

2018-04-01

Statin (HMG-CoA reductase inhibitor) therapy is the mainstay dyslipidemia treatment and reduces the risk of a cardiovascular (CV) event (CVE) by up to 35%. However, adherence to statin therapy is poor. One reason patients discontinue statin therapy is musculoskeletal pain and the associated risk of rhabdomyolysis. Research is ongoing to develop a pharmacogenomics (PGx) test for statin-induced myopathy as an alternative to the current diagnosis method, which relies on creatine kinase levels. The potential economic value of a PGx test for statin-induced myopathy is unknown. We developed a lifetime discrete event simulation (DES) model for patients 65 years of age initiating a statin after a first CVE consisting of either an acute myocardial infarction (AMI) or a stroke. The model evaluates the potential economic value of a hypothetical PGx test for diagnosing statin-induced myopathy. We have assessed the model over the spectrum of test sensitivity and specificity parameters. Our model showed that a strategy with a perfect PGx test had an incremental cost-utility ratio of 4273 Canadian dollars ($Can) per quality-adjusted life year (QALY). The probabilistic sensitivity analysis shows that when the payer willingness-to-pay per QALY reaches $Can12,000, the PGx strategy is favored in 90% of the model simulations. We found that a strategy favoring patients staying on statin therapy is cost effective even if patients maintained on statin are at risk of rhabdomyolysis. Our results are explained by the fact that statins are highly effective in reducing the CV risk in patients at high CV risk, and this benefit largely outweighs the risk of rhabdomyolysis.
Smoking cessation treatment and outcomes patterns simulation: a new framework for evaluating the potential health and economic impact of smoking cessation interventions.

PubMed

Getsios, Denis; Marton, Jenő P; Revankar, Nikhil; Ward, Alexandra J; Willke, Richard J; Rublee, Dale; Ishak, K Jack; Xenakis, James G

2013-09-01

Most existing models of smoking cessation treatments have considered a single quit attempt when modelling long-term outcomes. To develop a model to simulate smokers over their lifetimes accounting for multiple quit attempts and relapses which will allow for prediction of the long-term health and economic impact of smoking cessation strategies. A discrete event simulation (DES) that models individuals' life course of smoking behaviours, attempts to quit, and the cumulative impact on health and economic outcomes was developed. Each individual is assigned one of the available strategies used to support each quit attempt; the outcome of each attempt, time to relapses if abstinence is achieved, and time between quit attempts is tracked. Based on each individual's smoking or abstinence patterns, the risk of developing diseases associated with smoking (chronic obstructive pulmonary disease, lung cancer, myocardial infarction and stroke) is determined and the corresponding costs, changes to mortality, and quality of life assigned. Direct costs are assessed from the perspective of a comprehensive US healthcare payer ($US, 2012 values). Quit attempt strategies that can be evaluated in the current simulation include unassisted quit attempts, brief counselling, behavioural modification therapy, nicotine replacement therapy, bupropion, and varenicline, with the selection of strategies and time between quit attempts based on equations derived from survey data. Equations predicting the success of quit attempts as well as the short-term probability of relapse were derived from five varenicline clinical trials. Concordance between the five trials and predictions from the simulation on abstinence at 12 months was high, indicating that the equations predicting success and relapse in the first year following a quit attempt were reliable. Predictions allowing for only a single quit attempt versus unrestricted attempts demonstrate important differences, with the single quit attempt simulation predicting 19 % more smoking-related diseases and 10 % higher costs associated with smoking-related diseases. Differences are most prominent in predictions of the time that individuals abstain from smoking: 13.2 years on average over a lifetime allowing for multiple quit attempts, versus only 1.2 years with single quit attempts. Differences in abstinence time estimates become substantial only 5 years into the simulation. In the multiple quit attempt simulations, younger individuals survived longer, yet had lower lifetime smoking-related disease and total costs, while the opposite was true for those with high levels of nicotine dependence. By allowing for multiple quit attempts over the course of individuals' lives, the simulation can provide more reliable estimates on the health and economic impact of interventions designed to increase abstinence from smoking. Furthermore, the individual nature of the simulation allows for evaluation of outcomes in populations with different baseline profiles. DES provides a framework for comprehensive and appropriate predictions when applied to smoking cessation over smoker lifetimes.
Ecological and economic impacts of forest policies: interactions across forestry and agriculture.

Treesearch

R.J. Alig; D.M. Adams; B.A. McCarl

1998-01-01

A linked model of the US forest and agriculture sectors was used to examine the economic and ecological impacts of two forest policies: a minimum harvest age limitation and a reduced public harvest policy. Simulated private responses to both policies indicate that landowners could undertake a range of adjustments to minimize their welfare impacts, but imposition of...
When to use discrete event simulation (DES) for the economic evaluation of health technologies? A review and critique of the costs and benefits of DES.

PubMed

Karnon, Jonathan; Haji Ali Afzali, Hossein

2014-06-01

Modelling in economic evaluation is an unavoidable fact of life. Cohort-based state transition models are most common, though discrete event simulation (DES) is increasingly being used to implement more complex model structures. The benefits of DES relate to the greater flexibility around the implementation and population of complex models, which may provide more accurate or valid estimates of the incremental costs and benefits of alternative health technologies. The costs of DES relate to the time and expertise required to implement and review complex models, when perhaps a simpler model would suffice. The costs are not borne solely by the analyst, but also by reviewers. In particular, modelled economic evaluations are often submitted to support reimbursement decisions for new technologies, for which detailed model reviews are generally undertaken on behalf of the funding body. This paper reports the results from a review of published DES-based economic evaluations. Factors underlying the use of DES were defined, and the characteristics of applied models were considered, to inform options for assessing the potential benefits of DES in relation to each factor. Four broad factors underlying the use of DES were identified: baseline heterogeneity, continuous disease markers, time varying event rates, and the influence of prior events on subsequent event rates. If relevant, individual-level data are available, representation of the four factors is likely to improve model validity, and it is possible to assess the importance of their representation in individual cases. A thorough model performance evaluation is required to overcome the costs of DES from the users' perspective, but few of the reviewed DES models reported such a process. More generally, further direct, empirical comparisons of complex models with simpler models would better inform the benefits of DES to implement more complex models, and the circumstances in which such benefits are most likely.
Modelling the economic losses of historic and present-day high-impact winter storms in Switzerland

NASA Astrophysics Data System (ADS)

Welker, Christoph; Stucki, Peter; Bresch, David; Dierer, Silke; Martius, Olivia; Brönnimann, Stefan

2014-05-01

Severe winter storms such as "Vivian" in February 1990 and "Lothar" in December 1999 are among the most destructive meteorological hazards in Switzerland. Disaster severity resulting from such windstorms is attributable, on the one hand, to hazardous weather conditions such as high wind gust speeds; and on the other hand to socio-economic factors such as population density, distribution of values at risk, and damage susceptibility. For present-day winter storms, the data basis is generally good to describe the meteorological development and wind forces as well as the associated socio-economic impacts. In contrast, the information on historic windstorms is overall sparse and the available historic weather and loss reports mostly do not provide quantitative information. This study illustrates a promising technique to simulate the economic impacts of both historic and present winter storms in Switzerland since end of the 19th century. Our approach makes use of the novel Twentieth Century Reanalysis (20CR) spanning 1871-present. The 2-degree spatial resolution of the global 20CR dataset is relatively coarse. Thus, the complex orography of Switzerland is not realistically represented, which has considerable ramifications for the representation of wind systems that are strongly influenced by the local orography, such as Föhn winds. Therefore, a dynamical downscaling of the 20CR to 3 km resolution using the Weather Research and Forecasting (WRF) model was performed, for in total 40 high-impact winter storms in Switzerland since 1871. Based on the downscaled wind gust speeds and the climada loss model, the estimated economic losses were calculated at municipality level for current economic and social conditions. With this approach, we find an answer to the question what would be the economic losses of e.g. a hazardous Föhn storm - which occurred in northern Switzerland in February 1925 - today, i.e. under current socio-economic conditions. Encouragingly, the pattern of simulated losses for this specific storm is very similar to historic loss reports. A comparison of wind gust speeds with simulated storm losses for all highly damaging winter storms in Switzerland since the late 19th century considered in this study shows that storm losses have been related primarily to population density (and distribution of values at risk, respectively) rather than hazardous wind speed.
Pharmaceutical industry and trade liberalization using computable general equilibrium model.

PubMed

Barouni, M; Ghaderi, H; Banouei, Aa

2012-01-01

Computable general equilibrium models are known as a powerful instrument in economic analyses and widely have been used in order to evaluate trade liberalization effects. The purpose of this study was to provide the impacts of trade openness on pharmaceutical industry using CGE model. Using a computable general equilibrium model in this study, the effects of decrease in tariffs as a symbol of trade liberalization on key variables of Iranian pharmaceutical products were studied. Simulation was performed via two scenarios in this study. The first scenario was the effect of decrease in tariffs of pharmaceutical products as 10, 30, 50, and 100 on key drug variables, and the second was the effect of decrease in other sectors except pharmaceutical products on vital and economic variables of pharmaceutical products. The required data were obtained and the model parameters were calibrated according to the social accounting matrix of Iran in 2006. The results associated with simulation demonstrated that the first scenario has increased import, export, drug supply to markets and household consumption, while import, export, supply of product to market, and household consumption of pharmaceutical products would averagely decrease in the second scenario. Ultimately, society welfare would improve in all scenarios. We presents and synthesizes the CGE model which could be used to analyze trade liberalization policy issue in developing countries (like Iran), and thus provides information that policymakers can use to improve the pharmacy economics.
Development and Application of a Stakeholder Assisted Dynamic Model to Facilitate Socio Hydrological Groundwater Management on Watershed Scale

NASA Astrophysics Data System (ADS)

Baig, A. I.; Adamowski, J. F.; Malard, J. J.; Peng, G.

2017-12-01

Groundwater resource, especially in canal downstream areas are under direct threat due to over extraction by farming community. The resource is easily exploitable and no regulatory policies are enforced effectively in the region. Therefore, there is an urgent need to manage the resource judiciously through policy implementation and stakeholder engagement. In developing countries such as Pakistan, effective management solutions need consideration of some addition factors such as small land holdings, the poor economic status of farmers, and limited modeling and mathematical skills. This presentation will discuss development and application of a comprehensive but simple stakeholder assisted dynamic model to address such challenges. Two major components of the dynamic model were: (i) a system dynamics model that describes socio-economic factors such as market values; and ii) a physically based model that simulates the salt balance in the root zone with conjunctive use of canal and tube well irrigation water. Stakeholder proposed policy scenarios such as canal lining, government-sponsored tubewell installation schemes were tested and optimized through economic and environmental tradeoff criteria. After 20 years of simulation, government subsidies on tubewells appear as a short term policy that resulted 37% increase in water availability with 12% increase in farmer income. However, it showed detrimental effects on groundwater sustainability in long terms, with 10% drop in groundwater levels.
The migraine ACE model: evaluating the impact on time lost and medical resource Use.

PubMed

Caro, J J; Caro, G; Getsios, D; Raggio, G; Burrows, M; Black, L

2000-04-01

To describe the Migraine Adaptive Cost-Effectiveness Model in the context of an analysis of a simulated population of Canadian patients with migraine. The high prevalence of migraine and its substantial impact on patients' ability to function normally present a significant economic burden to society. In light of the recent availability of improved pharmaceutical treatments, a model was developed to assess their economic impact. The Migraine Adaptive Cost-Effectiveness Model incorporates the costs of time lost from both work and nonwork activities, as well as medical resource and medication use. Using Monte Carlo techniques, the model simulates the experience of a population of patients with migraine over the course of 1 year. As an example, analyses of a Canadian population were carried out using data from a multinational trial, surveys, national statistics, and the available literature. Using customary therapy, mean productivity losses (amounting to 84 hours of paid work time, 48 hours of unpaid work time, and 113 hours of leisure time lost) were estimated to cost $1949 (in 1997 Canadian dollars) per patient, with medical expenditures adding an average of $280 to the cost of illness. With customary treatment patterns, the costs of migraine associated with reduced functional capacity are substantial. The migraine model represents a flexible tool for the economic evaluation of different migraine treatments in various populations.
Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bragg-Sitton, Shannon Michelle; Rabiti, Cristian; Kinoshita, Robert Arthur

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for themore » solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.« less
Empirical methods for modeling landscape change, ecosystem services, and biodiversity

Treesearch

David Lewis; Ralph Alig

2009-01-01

The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...

Linking Temporal-Optimization and Spatial-Simulation Models for Forest Planning

Treesearch

Larry A. Leefers; Eric J. Gustafson; Phillip Freeman

2003-01-01

Increasingly, resource management agencies and researchers have turned their analysis and modeling efforts towards spatial and temporal information. This is driven by the need to address wildlife concerns, landscape issues, and social/economic questions. Historically, the USDA Forest Service has used optimization models (i.e., FORPLAN and Spectrum) for timber harvest...
The Tuition Advance Fund: An Analysis Prepared for Boston University.

ERIC Educational Resources Information Center

Botsford, Keith

Three models for anlayzing the Tuition Advance Fund (TAF) are examined. The three models are: projections by the Institute for Demographic and Economic Studies (IDES), projections by Data Resources, Inc. (DRI), and the Tuition Advance Fund Simulation (TAFSIM) models from Boston University. Analysis of the TAF is based on enrollment, price, and…
Core discrete event simulation model for the evaluation of health care technologies in major depressive disorder.

PubMed

Vataire, Anne-Lise; Aballéa, Samuel; Antonanzas, Fernando; Roijen, Leona Hakkaart-van; Lam, Raymond W; McCrone, Paul; Persson, Ulf; Toumi, Mondher

2014-03-01

A review of existing economic models in major depressive disorder (MDD) highlighted the need for models with longer time horizons that also account for heterogeneity in treatment pathways between patients. A core discrete event simulation model was developed to estimate health and cost outcomes associated with alternative treatment strategies. This model simulated short- and long-term clinical events (partial response, remission, relapse, recovery, and recurrence), adverse events, and treatment changes (titration, switch, addition, and discontinuation) over up to 5 years. Several treatment pathways were defined on the basis of fictitious antidepressants with three levels of efficacy, tolerability, and price (low, medium, and high) from first line to third line. The model was populated with input data from the literature for the UK setting. Model outputs include time in different health states, quality-adjusted life-years (QALYs), and costs from National Health Service and societal perspectives. The codes are open source. Predicted costs and QALYs from this model are within the range of results from previous economic evaluations. The largest cost components from the payer perspective were physician visits and hospitalizations. Key parameters driving the predicted costs and QALYs were utility values, effectiveness, and frequency of physician visits. Differences in QALYs and costs between two strategies with different effectiveness increased approximately twofold when the time horizon increased from 1 to 5 years. The discrete event simulation model can provide a more comprehensive evaluation of different therapeutic options in MDD, compared with existing Markov models, and can be used to compare a wide range of health care technologies in various groups of patients with MDD. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Stochastic effects in a discretized kinetic model of economic exchange

NASA Astrophysics Data System (ADS)

Bertotti, M. L.; Chattopadhyay, A. K.; Modanese, G.

2017-04-01

Linear stochastic models and discretized kinetic theory are two complementary analytical techniques used for the investigation of complex systems of economic interactions. The former employ Langevin equations, with an emphasis on stock trade; the latter is based on systems of ordinary differential equations and is better suited for the description of binary interactions, taxation and welfare redistribution. We propose a new framework which establishes a connection between the two approaches by introducing random fluctuations into the kinetic model based on Langevin and Fokker-Planck formalisms. Numerical simulations of the resulting model indicate positive correlations between the Gini index and the total wealth, that suggest a growing inequality with increasing income. Further analysis shows, in the presence of a conserved total wealth, a simultaneous decrease in inequality as social mobility increases, in conformity with economic data.
Realization of planning design of mechanical manufacturing system by Petri net simulation model

NASA Astrophysics Data System (ADS)

Wu, Yanfang; Wan, Xin; Shi, Weixiang

1991-09-01

Planning design is to work out a more overall long-term plan. In order to guarantee a mechanical manufacturing system (MMS) designed to obtain maximum economical benefit, it is necessary to carry out a reasonable planning design for the system. First, some principles on planning design for MMS are introduced. Problems of production scheduling and their decision rules for computer simulation are presented. Realizable method of each production scheduling decision rule in Petri net model is discussed. Second, the solution of conflict rules for conflict problems during running Petri net is given. Third, based on the Petri net model of MMS which includes part flow and tool flow, according to the principle of minimum event time advance, a computer dynamic simulation of the Petri net model, that is, a computer dynamic simulation of MMS, is realized. Finally, the simulation program is applied to a simulation exmple, so the scheme of a planning design for MMS can be evaluated effectively.
Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing.

PubMed

Wu, Desheng; Ning, Shuang

2018-07-01

Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis. Copyright © 2018 Elsevier Inc. All rights reserved.
Technical-economic modelling of integrated water management: wastewater reuse in a French island.

PubMed

Xu, P; Valette, F; Brissaud, F; Fazio, A; Lazarova, V

2001-01-01

An integrated technical-economic model is used to address water management issues in the French island of Noirmoutier. The model simulates potable water production and supply, potable and non potable water demand and consumption, wastewater collection, treatment and disposal, water storage, transportation and reuse. A variety of water management scenarios is assessed through technical, economic and environmental evaluation. The scenarios include wastewater reclamation and reuse for agricultural and landscape irrigation as well as domestic non potable application, desalination of seawater and brackish groundwater for potable water supply. The study shows that, in Noirmoutier, wastewater reclamation and reuse for crop irrigation is the most cost-effective solution to the lack of water resources and the protection of sensitive environment. Some water management projects which are regarded as having less economic benefit in the short-term may become competitive in the future, as a result of tightened environmental policy, changed public attitudes and advanced water treatment technologies. The model provides an appropriate tool for water resources planning and management.
A Simulated Instructional Model for Educating Mentally Retarded Students for Employment in the Hotel-Motel Industry.

ERIC Educational Resources Information Center

McCowan, Richard J.; Mongerson, M. Duane

Developed by the Campus Laboratory School of the State College at Buffalo, this program description proposes a simulated work environment which could be used to train educable and trainable retardates for hotel/motel aides more effectively and economically than on-the-job training or classroom lecture instruction. The proposed method of…
I PASS: an interactive policy analysis simulation system.

Treesearch

Doug Olson; Con Schallau; Wilbur Maki

1984-01-01

This paper describes an interactive policy analysis simulation system(IPASS) that can be used to analyze the long-term economic and demographic effects of alternative forest resource management policies. The IPASS model is a dynamic analytical tool that forecasts growth and development of an economy. It allows the user to introduce changes in selected parameters based...
Huntington II Simulation Program - MALAR. Student Workbook, Teacher's Guide, and Resource Handbook.

ERIC Educational Resources Information Center

Friedland, James; Frishman, Austin

Described is the computer model "MALAR" which deals with malaria and its eradication. A computer program allows the tenth- to twelfth-grade student to attempt to control a malaria epidemic. This simulation provides a context within which to study the biological, economic, social, political, and ecological aspects of a classic world health problem.…
Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auffhammer, M.; Hsiang, S. M.; Schlenker, W.

2013-06-28

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overviewmore » of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.« less
Land-use change in oil palm dominated tropical landscapes-An agent-based model to explore ecological and socio-economic trade-offs.

PubMed

Dislich, Claudia; Hettig, Elisabeth; Salecker, Jan; Heinonen, Johannes; Lay, Jann; Meyer, Katrin M; Wiegand, Kerstin; Tarigan, Suria

2018-01-01

Land-use changes have dramatically transformed tropical landscapes. We describe an ecological-economic land-use change model as an integrated, exploratory tool used to analyze how tropical land-use change affects ecological and socio-economic functions. The model analysis seeks to determine what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity, and economic benefit based on the synergies and trade-offs that we have to account for. More specifically, (1) how do specific ecosystem functions, such as carbon storage, and economic functions, such as household consumption, relate to each other? (2) How do external factors, such as the output prices of crops, affect these relationships? (3) How do these relationships change when production inefficiency differs between smallholder farmers and learning is incorporated? We initialize the ecological-economic model with artificially generated land-use maps parameterized to our study region. The economic sub-model simulates smallholder land-use management decisions based on a profit maximization assumption. Each household determines factor inputs for all household fields and decides on land-use change based on available wealth. The ecological sub-model includes a simple account of carbon sequestration in above-ground and below-ground vegetation. We demonstrate model capabilities with results on household consumption and carbon sequestration from different output price and farming efficiency scenarios. The overall results reveal complex interactions between the economic and ecological spheres. For instance, model scenarios with heterogeneous crop-specific household productivity reveal a comparatively high inertia of land-use change. Our model analysis even shows such an increased temporal stability in landscape composition and carbon stocks of the agricultural area under dynamic price trends. These findings underline the utility of ecological-economic models, such as ours, to act as exploratory tools which can advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes.
Land-use change in oil palm dominated tropical landscapes—An agent-based model to explore ecological and socio-economic trade-offs

PubMed Central

Dislich, Claudia; Hettig, Elisabeth; Heinonen, Johannes; Lay, Jann; Meyer, Katrin M.; Wiegand, Kerstin; Tarigan, Suria

2018-01-01

Land-use changes have dramatically transformed tropical landscapes. We describe an ecological-economic land-use change model as an integrated, exploratory tool used to analyze how tropical land-use change affects ecological and socio-economic functions. The model analysis seeks to determine what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity, and economic benefit based on the synergies and trade-offs that we have to account for. More specifically, (1) how do specific ecosystem functions, such as carbon storage, and economic functions, such as household consumption, relate to each other? (2) How do external factors, such as the output prices of crops, affect these relationships? (3) How do these relationships change when production inefficiency differs between smallholder farmers and learning is incorporated? We initialize the ecological-economic model with artificially generated land-use maps parameterized to our study region. The economic sub-model simulates smallholder land-use management decisions based on a profit maximization assumption. Each household determines factor inputs for all household fields and decides on land-use change based on available wealth. The ecological sub-model includes a simple account of carbon sequestration in above-ground and below-ground vegetation. We demonstrate model capabilities with results on household consumption and carbon sequestration from different output price and farming efficiency scenarios. The overall results reveal complex interactions between the economic and ecological spheres. For instance, model scenarios with heterogeneous crop-specific household productivity reveal a comparatively high inertia of land-use change. Our model analysis even shows such an increased temporal stability in landscape composition and carbon stocks of the agricultural area under dynamic price trends. These findings underline the utility of ecological-economic models, such as ours, to act as exploratory tools which can advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes. PMID:29351290
Techno-economic and Monte Carlo probabilistic analysis of microalgae biofuel production system.

PubMed

Batan, Liaw Y; Graff, Gregory D; Bradley, Thomas H

2016-11-01

This study focuses on the characterization of the technical and economic feasibility of an enclosed photobioreactor microalgae system with annual production of 37.85 million liters (10 million gallons) of biofuel. The analysis characterizes and breaks down the capital investment and operating costs and the production cost of unit of algal diesel. The economic modelling shows total cost of production of algal raw oil and diesel of $3.46 and $3.69 per liter, respectively. Additionally, the effects of co-products' credit and their impact in the economic performance of algal-to-biofuel system are discussed. The Monte Carlo methodology is used to address price and cost projections and to simulate scenarios with probabilities of financial performance and profits of the analyzed model. Different markets for allocation of co-products have shown significant shifts for economic viability of algal biofuel system. Copyright © 2016 Elsevier Ltd. All rights reserved.
Parameterisation of Biome BGC to assess forest ecosystems in Africa

NASA Astrophysics Data System (ADS)

Gautam, Sishir; Pietsch, Stephan A.

2010-05-01

African forest ecosystems are an important environmental and economic resource. Several studies show that tropical forests are critical to society as economic, environmental and societal resources. Tropical forests are carbon dense and thus play a key role in climate change mitigation. Unfortunately, the response of tropical forests to environmental change is largely unknown owing to insufficient spatially extensive observations. Developing regions like Africa where records of forest management for long periods are unavailable the process-based ecosystem simulation model - BIOME BGC could be a suitable tool to explain forest ecosystem dynamics. This ecosystem simulation model uses descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns within vegetation functional types, or biomes. Undocumented parameters for larger-resolution simulations are currently the major limitations to regional modelling in African forest ecosystems. This study was conducted to document input parameters for BIOME-BGC for major natural tropical forests in the Congo basin. Based on available literature and field measurements updated values for turnover and mortality, allometry, carbon to nitrogen ratios, allocation of plant material to labile, cellulose, and lignin pools, tree morphology and other relevant factors were assigned. Daily climate input data for the model applications were generated using the statistical weather generator MarkSim. The forest was inventoried at various sites and soil samples of corresponding stands across Gabon were collected. Carbon and nitrogen in the collected soil samples were determined from soil analysis. The observed tree volume, soil carbon and soil nitrogen were then compared with the simulated model outputs to evaluate the model performance. Furthermore, the simulation using Congo Basin specific parameters and generalised BIOME BGC parameters for tropical evergreen broadleaved tree species were also executed and the simulated results compared. Once the model was optimised for forests in the Congo basin it was validated against observed tree volume, soil carbon and soil nitrogen from a set of independent plots.
Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz Ram model

NASA Astrophysics Data System (ADS)

Morin, Mario A.; Ficarazzo, Francesco

2006-04-01

Rock fragmentation is considered the most important aspect of production blasting because of its direct effects on the costs of drilling and blasting and on the economics of the subsequent operations of loading, hauling and crushing. Over the past three decades, significant progress has been made in the development of new technologies for blasting applications. These technologies include increasingly sophisticated computer models for blast design and blast performance prediction. Rock fragmentation depends on many variables such as rock mass properties, site geology, in situ fracturing and blasting parameters and as such has no complete theoretical solution for its prediction. However, empirical models for the estimation of size distribution of rock fragments have been developed. In this study, a blast fragmentation Monte Carlo-based simulator, based on the Kuz-Ram fragmentation model, has been developed to predict the entire fragmentation size distribution, taking into account intact and joints rock properties, the type and properties of explosives and the drilling pattern. Results produced by this simulator were quite favorable when compared with real fragmentation data obtained from a blast quarry. It is anticipated that the use of Monte Carlo simulation will increase our understanding of the effects of rock mass and explosive properties on the rock fragmentation by blasting, as well as increase our confidence in these empirical models. This understanding will translate into improvements in blasting operations, its corresponding costs and the overall economics of open pit mines and rock quarries.
Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

NASA Astrophysics Data System (ADS)

Juchem Neto, J. P.; Claeyssen, J. C. R.; Pôrto Júnior, S. S.

2018-03-01

In this paper we introduce capital transport cost in a unidimensional spatial Solow-Swan model of economic growth with capital-induced labor migration, considered in an unbounded domain. Proceeding with a stability analysis, we show that there is a critical value for the capital transport cost where the dynamic behavior of the economy changes, provided that the intensity of capital-induced labor migration is strong enough. On the one hand, if the capital transport cost is higher than this critical value, the spatially homogeneous equilibrium of coexistence of the model is stable, and the economy converges to this spatially homogeneous state in the long run; on the other hand, if transport cost is lower than this critical value, the equilibrium is unstable, and the economy may develop different spatio-temporal dynamics, including the formation of stable economic agglomerations and spatio-temporal economic cycles, depending on the other parameters in the model. Finally, numerical simulations support the results of the stability analysis, and illustrate the spatio-temporal dynamics generated by the model, suggesting that the economy as a whole benefits from the formation of economic agglomerations and cycles, with a higher capital transport cost reducing this gain.
Numerical simulation of the circulation of the atmosphere of Titan

NASA Technical Reports Server (NTRS)

Hourdin, F.; Levan, P.; Talagrand, O.; Courtin, Regis; Gautier, Daniel; Mckay, Christopher P.

1992-01-01

A three dimensional General Circulation Model (GCM) of Titan's atmosphere is described. Initial results obtained with an economical two dimensional (2D) axisymmetric version of the model presented a strong superrotation in the upper stratosphere. Because of this result, a more general numerical study of superrotation was started with a somewhat different version of the GCM. It appears that for a slowly rotating planet which strongly absorbs solar radiation, circulation is dominated by global equator to pole Hadley circulation and strong superrotation. The theoretical study of this superrotation is discussed. It is also shown that 2D simulations systemically lead to instabilities which make 2D models poorly adapted to numerical simulation of Titan's (or Venus) atmosphere.
Stimulating household flood risk mitigation investments through insurance and subsidies: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Botzen, Wouter; de Moel, Hans; Aerts, Jeroen

2015-04-01

In the period 1998-2009, floods triggered roughly 52 billion euro in insured economic losses making floods the most costly natural hazard in Europe. Climate change and socio/economic trends are expected to further aggrevate floods losses in many regions. Research shows that flood risk can be significantly reduced if households install protective measures, and that the implementation of such measures can be stimulated through flood insurance schemes and subsidies. However, the effectiveness of such incentives to stimulate implementation of loss-reducing measures greatly depends on the decision process of individuals and is hardly studied. In our study, we developed an Agent-Based Model that integrates flood damage models, insurance mechanisms, subsidies, and household behaviour models to assess the effectiveness of different economic tools on stimulating households to invest in loss-reducing measures. Since the effectiveness depends on the decision making process of individuals, the study compares different household decision models ranging from standard economic models, to economic models for decision making under risk, to more complex decision models integrating economic models and risk perceptions, opinion dynamics, and the influence of flood experience. The results show the effectiveness of incentives to stimulate investment in loss-reducing measures for different household behavior types, while assuming climate change scenarios. It shows how complex decision models can better reproduce observed real-world behaviour compared to traditional economic models. Furthermore, since flood events are included in the simulations, the results provide an analysis of the dynamics in insured and uninsured losses for households, the costs of reducing risk by implementing loss-reducing measures, the capacity of the insurance market, and the cost of government subsidies under different scenarios. The model has been applied to the City of Rotterdam in The Netherlands.
Development of a Systematic Stakeholder Identification System for 3VS Modeling in the Snohomish Basin, Washington, USA

EPA Science Inventory

In the Environmental Protection Agency’s Triple Value Simulation (3VS) models, social, economic and environmental indicators are utilized to understand the interrelated impacts of programs and regulations on ecosystems and human communities. Critical to identifying the app...

Cost and Performance Model for Photovoltaic Systems

NASA Technical Reports Server (NTRS)

Borden, C. S.; Smith, J. H.; Davisson, M. C.; Reiter, L. J.

1986-01-01

Lifetime cost and performance (LCP) model assists in assessment of design options for photovoltaic systems. LCP is simulation of performance, cost, and revenue streams associated with photovoltaic power systems connected to electric-utility grid. LCP provides user with substantial flexibility in specifying technical and economic environment of application.
Spatially and Temporally Detailed Modeling of Water Quality in Narragansett Bay

EPA Science Inventory

Nutrient loading to Narragansett Bay has led to eutrophication, resulting in hypoxia and anoxia, finfish and shellfish kills, loss of seagrass, and reductions in the recreational and economic value of the Bay. We are developing a model that simulates the effects of external nutri...
Economical Sponge Phantom for Teaching, Understanding, and Researching A- and B-Line Reverberation Artifacts in Lung Ultrasound.

PubMed

Blüthgen, Christian; Sanabria, Sergio; Frauenfelder, Thomas; Klingmüller, Volker; Rominger, Marga

2017-10-01

This project evaluated a low-cost sponge phantom setup for its capability to teach and study A- and B-line reverberation artifacts known from lung ultrasound and to numerically simulate sound wave interaction with the phantom using a finite-difference time-domain (FDTD) model. Both A- and B-line artifacts were reproducible on B-mode ultrasound imaging as well as in the FDTD-based simulation. The phantom was found to be an easy-to-set up and economical tool for understanding, teaching, and researching A- and B-line artifacts occurring in lung ultrasound. The FDTD method-based simulation was able to reproduce the artifacts and provides intuitive insight into the underlying physics. © 2017 by the American Institute of Ultrasound in Medicine.
Error and Uncertainty Analysis for Ecological Modeling and Simulation

DTIC Science & Technology

2001-12-01

management (LRAM) accounting for environmental, training, and economic factors. In the ELVS methodology, soil erosion status is used as a quantitative...Monte-Carlo approach. The optimization is realized through economic functions or on decision constraints, such as, unit sample cost, number of samples... nitrate flux to the Gulf of Mexico. Nature (Brief Communication) 414: 166-167. (Uncertainty analysis done with SERDP software) Gertner, G., G
Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model.

PubMed

Mostert, P F; Bokkers, E A M; van Middelaar, C E; Hogeveen, H; de Boer, I J M

2018-01-01

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of diseases can further improve economic estimations.
Power-based Shift Schedule for Pure Electric Vehicle with a Two-speed Automatic Transmission

NASA Astrophysics Data System (ADS)

Wang, Jiaqi; Liu, Yanfang; Liu, Qiang; Xu, Xiangyang

2016-11-01

This paper introduces a comprehensive shift schedule for a two-speed automatic transmission of pure electric vehicle. Considering about driving ability and efficiency performance of electric vehicles, the power-based shift schedule is proposed with three principles. This comprehensive shift schedule regards the vehicle current speed and motor load power as input parameters to satisfy the vehicle driving power demand with lowest energy consumption. A simulation model has been established to verify the dynamic and economic performance of comprehensive shift schedule. Compared with traditional dynamic and economic shift schedules, simulation results indicate that the power-based shift schedule is superior to traditional shift schedules.
A Comparative Study of Spatial Aggregation Methodologies under the BioEarth Framework

NASA Astrophysics Data System (ADS)

Chandrasekharan, B.; Rajagopalan, K.; Malek, K.; Stockle, C. O.; Adam, J. C.; Brady, M.

2014-12-01

The increasing probability of water resource scarcity due to climate change has highlighted the need for adopting an economic focus in modelling water resource uses. Hydro-economic models, developed by integrating economic optimization with biophysical crop models, are driven by the economic value of water, revealing it's most efficient uses and helping policymakers evaluate different water management strategies. One of the challenges in integrating biophysical models with economic models is the difference in the spatial scales in which they operate. Biophysical models that provide crop production functions typically run at smaller scale than economic models, and substantial spatial aggregation is required. However, any aggregation introduces a bias, i.e., a discrepancy between the functional value at the higher spatial scale and the value at the spatial scale of the aggregated units. The objective of this work is to study the sensitivity of net economic benefits in the Yakima River basin (YRB) to different spatial aggregation methods for crop production functions. The spatial aggregation methodologies that we compare involve agro-ecological zones (AEZs) and aggregation levels that reflect water management regimes (e.g. irrigation districts). Aggregation bias can distort the underlying data and result in extreme solutions. In order to avoid this we use an economic optimization model that incorporates the synthetic and historical crop mixes approach (Onal & Chen, 2012). This restricts the solutions between the weighted averages of historical and simulated feasible planting decisions, with the weights associated with crop mixes being treated as endogenous variables. This study is focused on 5 major irrigation districts of the YRB in the Pacific Northwest US. The biophysical modeling framework we use, BioEarth, includes the coupled hydrology and crop growth model, VIC-Cropsyst and an economic optimization model. Preliminary findings indicate that the standard approach of developing AEZs does not perform well when overlaid with irrigation districts. Moreover, net economic benefits were significantly different between the two aggregation methodologies. Therefore, while developing hydro-economic models, significant consideration should be placed on the aggregation methodology.
Intelligent simulation of aquatic environment economic policy coupled ABM and SD models.

PubMed

Wang, Huihui; Zhang, Jiarui; Zeng, Weihua

2018-03-15

Rapid urbanization and population growth have resulted in serious water shortage and pollution of the aquatic environment, which are important reasons for the complex increase in environmental deterioration in the region. This study examines the environmental consequences and economic impacts of water resource shortages under variant economic policies; however, this requires complex models that jointly consider variant agents and sectors within a systems perspective. Thus, we propose a complex system model that couples multi-agent based models (ABM) and system dynamics (SD) models to simulate the impact of alternative economic policies on water use and pricing. Moreover, this model took the constraint of the local water resources carrying capacity into consideration. Results show that to achieve the 13th Five Year Plan targets in Dianchi, water prices for local residents and industries should rise to 3.23 and 4.99 CNY/m 3 , respectively. The corresponding sewage treatment fees for residents and industries should rise to 1.50 and 2.25 CNY/m 3 , respectively, assuming comprehensive adjustment of industrial structure and policy. At the same time, the local government should exercise fine-scale economic policy combined with emission fees assessed for those exceeding a standard, and collect fines imposed as punishment for enterprises that exceed emission standards. When fines reach 500,000 CNY, the total number of enterprises that exceed emission standards in the basin can be controlled within 1%. Moreover, it is suggested that the volume of water diversion in Dianchi should be appropriately reduced to 3.06×10 8 m 3 . The reduced expense of water diversion should provide funds to use for the construction of recycled water facilities. Then the local rise in the rate of use of recycled water should reach 33%, and 1.4 CNY/m 3 for the price of recycled water could be provided to ensure the sustainable utilization of local water resources. Copyright © 2017 Elsevier B.V. All rights reserved.
Transportation Planning for Your Community

DOT National Transportation Integrated Search

2000-12-01

The Highway Economic Requirements System (HERS) is a computer model designed to simulate improvement selection decisions based on the relative benefit-cost merits of alternative improvement options. HERS is intended to estimate national level investm...
Aspen: A microsimulation model of the economy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Basu, N.; Pryor, R.J.; Quint, T.

1996-10-01

This report presents, Aspen. Sandia National Laboratories is developing this new agent-based microeconomic simulation model of the U.S. economy. The model is notable because it allows a large number of individual economic agents to be modeled at a high level of detail and with a great degree of freedom. Some features of Aspen are (a) a sophisticated message-passing system that allows individual pairs of agents to communicate, (b) the use of genetic algorithms to simulate the learning of certain agents, and (c) a detailed financial sector that includes a banking system and a bond market. Results from runs of themore » model are also presented.« less
Simulating water markets with transaction costs

NASA Astrophysics Data System (ADS)

Erfani, Tohid; Binions, Olga; Harou, Julien J.

2014-06-01

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. This article was corrected on 13 JUN 2014. See the end of the full text for details.
Policy model for space economy infrastructure

NASA Astrophysics Data System (ADS)

Komerath, Narayanan; Nally, James; Zilin Tang, Elizabeth

2007-12-01

Extraterrestrial infrastructure is key to the development of a space economy. Means for accelerating transition from today's isolated projects to a broad-based economy are considered. A large system integration approach is proposed. The beginnings of an economic simulation model are presented, along with examples of how interactions and coordination bring down costs. A global organization focused on space infrastructure and economic expansion is proposed to plan, coordinate, fund and implement infrastructure construction. This entity also opens a way to raise low-cost capital and solve the legal and public policy issues of access to extraterrestrial resources.
Calibrating and updating the Global Forest Products Model (GFPM version 2016 with BPMPD)

Treesearch

Joseph Buongiorno; Shushuai Zhu

2016-01-01

The Global Forest Products Model (GFPM) is an economic model of global production, consumption, and trade of forest products. An earlier version of the model is described in Buongiorno et al. (2003). The GFPM 2016 has data and parameters to simulate changes of the forest sector from 2013 to 2030. Buongiorno and Zhu (2015) describe how to use the model for...
Power Market Design | Grid Modernization | NREL

Science.gov Websites

Power Market Design Power Market Design NREL researchers are developing a modeling platform to test (a commercial electricity production simulation model) and FESTIV (the NREL-developed Flexible Energy consisting of researchers in power systems and economics Projects Grid Market Design Project The objective of
Koenraad Beckers | NREL

Science.gov Websites

postdoctoral researcher working on geothermal energy and CSP projects. His interests include heat and mass geothermal energy systems modeling, reservoir simulation, and economic analysis, as well as on the design and transfer, energy conversion and storage systems, reservoir modeling, and direct-use applications of thermal
Project IN/VEST: A Guaranteed Investment

ERIC Educational Resources Information Center

Geier, Charlene

1977-01-01

Describes a simulated auto insurance company at Greenfield High School (Greenfield, Wisconsin), a comprehensive model designed for business students but involving other high school classes such as distributive education, home economics, and auto mechanics. The model is noted to not only train students for an opportunity field but provide them with…
Spatially and Temporally Detailed Modeling of Water Quality in Narragansett Bay (AGU)

EPA Science Inventory

Nutrient loading to Narragansett Bay has led to eutrophication, resulting in hypoxia and anoxia, finfish and shellfish kills, loss of seagrass, and reductions in the recreational and economic value of the Bay. We are developing a model that simulates the effects of external nutri...
Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.
AgMIP Coordinated Global and Regional Assessments for 1.5°C and 2.0°C

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2017-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study performs a proof-of-concept of the CGRA to demonstrate advantages and challenges of the framework. This effort responds to the request by UNFCCC for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), HAPPI and CMIP5 ensemble scenarios, global gridded crop models, global agricultural economic models, site-based crop models, and within-country regional economic models. CGRA results show that at the global scale, mixed areas of positive and negative simulated yield changes, with declines in some breadbasket regions led to overall declines in productivity at both 1.5°C and 2.0°C. These projected global yield changes resulted in increases in prices of major commodities in a global economic model. Simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on region and crop, but with more negative effects on productivity at 2.0°C than at 1.5°C for the most part. In conjunction with price changes from the global economics models, these productivity declines resulted generally in small positive effects on regional farm livelihoods, showing that farming systems should continue to be viable under high mitigation scenarios. CGRA protocols focus on how mitigation actions and effects differ across scales, with main mechanisms studied in the integrated assessment models being policies and technologies that reduce direct non-CO2 emissions from agriculture, reduce CO2 emissions from land use change and forest sink enhancement, and utilize biomass for energy production. At regional scales, increasing soil organic carbon (SOC) is of active interest.
An economical model for simulating droplet spectrum evolution in turbulent cloud chambers and wind tunnels

NASA Astrophysics Data System (ADS)

Krueger, Steven; Cantrell, W.; Niedermeier, D.; Shaw, R.; Stratmann, F.

2017-11-01

Although airborne instruments provide detailed information about the microphysical structure of clouds, the measurements provide only a few snapshots of each cloud. Deducing the droplet spectrum evolution from such measurements is next to impossible. We are using two alternative approaches: laboratory studies and numerical simulations. The former relies on a new turbulent cloud chamber (the Pi Chamber) at Michigan Technical University, as well as the first humid turbulent wind tunnel (LACIS-T) at the Leibniz Institute for Tropospheric Research. Both produce conditions for droplet growth (i.e., supersaturation) by mixing saturated vapor at different temperatures. The Pi Chamber produces turbulence by inducing Rayleigh-Bénard convection, while the wind tunnel generates turbulence with a grid. We are using the Explicit Mixing Parcel Model (EMPM) to numerically simulate droplet spectrum evolution in these flows. The EMPM explicitly links turbulent mixing and droplet spectrum evolution by representing a turbulent flow in a 1D domain with the linear eddy model. The EMPM can economically span scales from those of the smallest turbulent eddies to those of the largest. The EMPM grows or evaporates thousands of individual cloud droplets according to their local environments.

Quantum Social Science

NASA Astrophysics Data System (ADS)

Haven, Emmanuel; Khrennikov, Andrei

2013-01-01

Preface; Part I. Physics Concepts in Social Science? A Discussion: 1. Classical, statistical and quantum mechanics: all in one; 2. Econophysics: statistical physics and social science; 3. Quantum social science: a non-mathematical motivation; Part II. Mathematics and Physics Preliminaries: 4. Vector calculus and other mathematical preliminaries; 5. Basic elements of quantum mechanics; 6. Basic elements of Bohmian mechanics; Part III. Quantum Probabilistic Effects in Psychology: Basic Questions and Answers: 7. A brief overview; 8. Interference effects in psychology - an introduction; 9. A quantum-like model of decision making; Part IV. Other Quantum Probabilistic Effects in Economics, Finance and Brain Sciences: 10. Financial/economic theory in crisis; 11. Bohmian mechanics in finance and economics; 12. The Bohm-Vigier Model and path simulation; 13. Other applications to economic/financial theory; 14. The neurophysiological sources of quantum-like processing in the brain; Conclusion; Glossary; Index.
Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer.

PubMed

Degeling, Koen; Schivo, Stefano; Mehra, Niven; Koffijberg, Hendrik; Langerak, Rom; de Bono, Johann S; IJzerman, Maarten J

2017-12-01

With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required. To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions. An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed. Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure. Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Analysing child mortality in Nigeria with geoadditive discrete-time survival models.

PubMed

Adebayo, Samson B; Fahrmeir, Ludwig

2005-03-15

Child mortality reflects a country's level of socio-economic development and quality of life. In developing countries, mortality rates are not only influenced by socio-economic, demographic and health variables but they also vary considerably across regions and districts. In this paper, we analysed child mortality in Nigeria with flexible geoadditive discrete-time survival models. This class of models allows us to measure small-area district-specific spatial effects simultaneously with possibly non-linear or time-varying effects of other factors. Inference is fully Bayesian and uses computationally efficient Markov chain Monte Carlo (MCMC) simulation techniques. The application is based on the 1999 Nigeria Demographic and Health Survey. Our method assesses effects at a high level of temporal and spatial resolution not available with traditional parametric models, and the results provide some evidence on how to reduce child mortality by improving socio-economic and public health conditions. Copyright (c) 2004 John Wiley & Sons, Ltd.
An Approach to Understanding Complex Socio-Economic Impacts and Responses to Climate Disruption in the Chesapeake Bay Region

NASA Astrophysics Data System (ADS)

Schaefer, R. K.; Nix, M.; Ihde, A. G.; Paxton, L. J.; Weiss, M.; Simpkins, S.; Fountain, G. H.; APl GAIA Team

2011-12-01

In this paper we describe the application of a proven methodology for modeling the complex social and economic interactions of a system under stress to the regional issues that are tied to global climate disruption. Under the auspices of the GAIA project (http://gaia.jhuapl.edu), we have investigated simulating the complex interplay between climate, politics, society, industry, and the environment in the Chesapeake Bay Watershed and associated geographic areas of Maryland, Virginia, and Pennsylvania. This Chesapeake Bay simulation draws on interrelated geophysical and climate models to support decision-making analysis about the Bay. In addition to physical models, however, human activity is also incorporated via input and output calculations. For example, policy implications are modeled in relation to business activities surrounding fishing, farming, industry and manufacturing, land development, and tourism. This approach fosters collaboration among subject matter experts to advance a more complete understanding of the regional impacts of climate change. Simulated interactive competition, in which teams of experts are assigned conflicting objectives in a controlled environment, allow for subject exploration which avoids trivial solutions that neglect the possible responses of affected parties. Results include improved planning, the anticipation of areas of conflict or high risk, and the increased likelihood of developing mutually acceptable solutions.
Cost-utility analysis of antiviral use under pandemic influenza using a novel approach - linking pharmacology, epidemiology and heath economics.

PubMed

Wu, D B C; Chaiyakunapruk, N; Pratoomsoot, C; Lee, K K C; Chong, H Y; Nelson, R E; Smith, P F; Kirkpatrick, C M; Kamal, M A; Nieforth, K; Dall, G; Toovey, S; Kong, D C M; Kamauu, A; Rayner, C R

2018-03-01

Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) - dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients' quality of life. Integrating PK/PD-EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.
DFSIM with economics: A financial analysis option for the DFSIM Douglas-fir simulator.

Treesearch

Roger O. Fight; Judith M. Chittester; Gary W. Clendenen

1984-01-01

A modified version of the DFSIM Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) growth and yield simulator, DFSIM WITH ECONOMICS, now has an economics option that allows the user to estimate present net worth at the same time a silvicultural regime is simulated. If desired, the economics option will apply a...
DOE Office of Scientific and Technical Information (OSTI.GOV)

Gragg, Evan James; Middleton, Richard Stephen

This report describes the benefits of the BECCUS screening tools. The goals of this project are to utilize NATCARB database for site screening; enhance NATCARB database; run CO 2-EOR simulations and economic models using updated reservoir data sets (SCO 2T-EOR).
Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.
Development of an Assessment Model for Sustainable Supply Chain Management in Batik Industry

NASA Astrophysics Data System (ADS)

Mubiena, G. F.; Ma’ruf, A.

2018-03-01

This research proposes a dynamic assessment model for sustainable supply chain management in batik industry. The proposed model identifies the dynamic relationship between economic aspect, environment aspect and social aspect. The economic aspect refers to the supply chain operation reference model. The environment aspect uses carbon emissions and liquid waste as the attribute assessment, while the social aspect focus on employee’s welfare. Lean manufacturing concept was implemented as an alternative approach to sustainability. The simulation result shows that the average of sustainability score for 5 years increased from 65,3% to 70%. Future experiments will be conducted on design improvements to reach the company target on sustainability score.
Modeling hard clinical end-point data in economic analyses.

PubMed

Kansal, Anuraag R; Zheng, Ying; Palencia, Roberto; Ruffolo, Antonio; Hass, Bastian; Sorensen, Sonja V

2013-11-01

The availability of hard clinical end-point data, such as that on cardiovascular (CV) events among patients with type 2 diabetes mellitus, is increasing, and as a result there is growing interest in using hard end-point data of this type in economic analyses. This study investigated published approaches for modeling hard end-points from clinical trials and evaluated their applicability in health economic models with different disease features. A review of cost-effectiveness models of interventions in clinically significant therapeutic areas (CV diseases, cancer, and chronic lower respiratory diseases) was conducted in PubMed and Embase using a defined search strategy. Only studies integrating hard end-point data from randomized clinical trials were considered. For each study included, clinical input characteristics and modeling approach were summarized and evaluated. A total of 33 articles (23 CV, eight cancer, two respiratory) were accepted for detailed analysis. Decision trees, Markov models, discrete event simulations, and hybrids were used. Event rates were incorporated either as constant rates, time-dependent risks, or risk equations based on patient characteristics. Risks dependent on time and/or patient characteristics were used where major event rates were >1%/year in models with fewer health states (<7). Models of infrequent events or with numerous health states generally preferred constant event rates. The detailed modeling information and terminology varied, sometimes requiring interpretation. Key considerations for cost-effectiveness models incorporating hard end-point data include the frequency and characteristics of the relevant clinical events and how the trial data is reported. When event risk is low, simplification of both the model structure and event rate modeling is recommended. When event risk is common, such as in high risk populations, more detailed modeling approaches, including individual simulations or explicitly time-dependent event rates, are more appropriate to accurately reflect the trial data.
The economics of fuel management: Wildfire, invasive plants, and the dynamics of sagebrush rangelands in the western United States

Treesearch

Michael H. Taylor; Kimberly Rollins; Mimako Kobayashi; Robin J. Tausch

2013-01-01

In this article we develop a simulation model to evaluate the economic efficiency of fuel treatments and apply it to two sagebrush ecosystems in the Great Basin of the western United States: the Wyoming Sagebrush Steppe and Mountain Big Sagebrush ecosystems. These ecosystems face the two most prominent concerns in sagebrush ecosystems relative to wildfire: annual grass...
ERDYM: Economic Recovery Dynamics Model. Volume 1. Modifications and Simulations.

DTIC Science & Technology

1984-05-01

Pacific Northwest Laboratories AEAOKNTUSR P.O. Bx 999FEMA Work Unit 4342-D * Richland, Washington 99352 I. CONTROLLING OFFICE NAME AND ADDRESS 12...dleu.,m, hft Controlling Office) 15. SECURITY CLASS. (of thls report) Unclassified I 1a. DECLASSIFICATION/DOWNGRADING SCHEDULE 16. DISTRIBUTION...rationinq and wage and price controls . 2.6.1 Economic Role of Government Revenues * The representation of government financinq in ERDYM is straiqhtfoward. 9
The Impact of Alzheimer's Disease on the Chinese Economy.

PubMed

Keogh-Brown, Marcus R; Jensen, Henning Tarp; Arrighi, H Michael; Smith, Richard D

2016-02-01

Recent increases in life expectancy may greatly expand future Alzheimer's Disease (AD) burdens. China's demographic profile, aging workforce and predicted increasing burden of AD-related care make its economy vulnerable to AD impacts. Previous economic estimates of AD predominantly focus on health system burdens and omit wider whole-economy effects, potentially underestimating the full economic benefit of effective treatment. AD-related prevalence, morbidity and mortality for 2011-2050 were simulated and were, together with associated caregiver time and costs, imposed on a dynamic Computable General Equilibrium model of the Chinese economy. Both economic and non-economic outcomes were analyzed. Simulated Chinese AD prevalence quadrupled during 2011-50 from 6-28 million. The cumulative discounted value of eliminating AD equates to China's 2012 GDP (US$8 trillion), and the annual predicted real value approaches US AD cost-of-illness (COI) estimates, exceeding US$1 trillion by 2050 (2011-prices). Lost labor contributes 62% of macroeconomic impacts. Only 10% derives from informal care, challenging previous COI-estimates of 56%. Health and macroeconomic models predict an unfolding 2011-2050 Chinese AD epidemic with serious macroeconomic consequences. Significant investment in research and development (medical and non-medical) is warranted and international researchers and national authorities should therefore target development of effective AD treatment and prevention strategies.
The Impact of Alzheimer's Disease on the Chinese Economy

PubMed Central

Keogh-Brown, Marcus R.; Jensen, Henning Tarp; Arrighi, H. Michael; Smith, Richard D.

2015-01-01

Background Recent increases in life expectancy may greatly expand future Alzheimer's Disease (AD) burdens. China's demographic profile, aging workforce and predicted increasing burden of AD-related care make its economy vulnerable to AD impacts. Previous economic estimates of AD predominantly focus on health system burdens and omit wider whole-economy effects, potentially underestimating the full economic benefit of effective treatment. Methods AD-related prevalence, morbidity and mortality for 2011–2050 were simulated and were, together with associated caregiver time and costs, imposed on a dynamic Computable General Equilibrium model of the Chinese economy. Both economic and non-economic outcomes were analyzed. Findings Simulated Chinese AD prevalence quadrupled during 2011–50 from 6–28 million. The cumulative discounted value of eliminating AD equates to China's 2012 GDP (US$8 trillion), and the annual predicted real value approaches US AD cost-of-illness (COI) estimates, exceeding US$1 trillion by 2050 (2011-prices). Lost labor contributes 62% of macroeconomic impacts. Only 10% derives from informal care, challenging previous COI-estimates of 56%. Interpretation Health and macroeconomic models predict an unfolding 2011–2050 Chinese AD epidemic with serious macroeconomic consequences. Significant investment in research and development (medical and non-medical) is warranted and international researchers and national authorities should therefore target development of effective AD treatment and prevention strategies. PMID:26981556
Coupled Climate-Economy-Biosphere (CoCEB) model - Part 1: Abatement share and investment in low-carbon technologies

NASA Astrophysics Data System (ADS)

Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

2015-04-01

The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth.
Carbon farming economics: What have we learned?

PubMed

Tang, Kai; Kragt, Marit E; Hailu, Atakelty; Ma, Chunbo

2016-05-01

This study reviewed 62 economic analyses published between 1995 and 2014 on the economic impacts of policies that incentivise agricultural greenhouse (GHG) mitigation. Typically, biophysical models are used to evaluate the changes in GHG mitigation that result from landholders changing their farm and land management practices. The estimated results of biophysical models are then integrated with economic models to simulate the costs of different policy scenarios to production systems. The cost estimates vary between $3 and $130/t CO2 equivalent in 2012 US dollars, depending on the mitigation strategies, spatial locations, and policy scenarios considered. Most studies assessed the consequences of a single, rather than multiple, mitigation strategies, and few considered the co-benefits of carbon farming. These omissions could challenge the reality and robustness of the studies' results. One of the biggest challenges facing agricultural economists is to assess the full extent of the trade-offs involved in carbon farming. We need to improve our biophysical knowledge about carbon farming co-benefits, predict the economic impacts of employing multiple strategies and policy incentives, and develop the associated integrated models, to estimate the full costs and benefits of agricultural GHG mitigation to farmers and the rest of society. Copyright © 2016 Elsevier Ltd. All rights reserved.
Climate, Energy, Water, Land and the Spill-Over Effect (Invited)

NASA Astrophysics Data System (ADS)

Tidwell, V. C.; Backus, G.; Bier, A.; Brune, N.; Brown, T. J.

2013-12-01

Developing nations incur a greater risk to climate stress than the developed world due to poorly managed natural resources, unreliable infrastructure and brittle governing/economic institutions. When fragile states are stressed these vulnerabilities are often manifest in a 'domino effect' of reduced natural resource production-leading to economic hardship-followed by desperate emigration, social unrest, and humanitarian crises. The impact is not limited to a single nation or region but 'spills over' to adjoining areas with even broader impact on global markets and security. Toward this problem we are developing a model of climate aggravated spill-over that couples social, economic, infrastructure and resource dynamics and constraints. The model integrates system dynamics and agent based simulation to identify regions vulnerable to the spill-over effect and to explore potential mitigating and/or adaptive measures. At the heart of the analysis is human migration which is modeled by combining aspects of the Protection Motivation Theory and Theory of Planned Behavior within the mechanistic framework of Fick's first law of diffusion. Agents in the current model are distinguished at the country level by country of residence, country of origin, gender, education/skill, age, and rural/urban roots. The model of the environment in which the agents operate endogenously simulates economy, labor, population, disease, violence, energy, water, and food sectors. Various climate scenarios distinguished by differences in temperature, precipitation and extreme events, are simulated over a 50 year time horizon. Results allow exploration of the nexus between climate change, resource provisioning, especially energy, water and land, and the resultant adaptive response of the impacted population. Current modeling efforts are focused on the developing nations of West Africa. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. Schematic of spill-over effects model.
Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.
An energy-economy-environment model for simulating the impacts of socioeconomic development on energy and environment.

PubMed

Wang, Wenyi; Zeng, Weihua; Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement.
Simulation Activities and Student Learning Characteristics in a College Economics Survey Course.

ERIC Educational Resources Information Center

Fraas, John W.; Rafeld, Frederick J.

The paper describes a study involving simulation activities in a college level survey course in economics. In addition, it compares student learning in an economics course based on simulation with student learning in a lecture discussion course. The hypothesis was that certain types of students would benefit from the simulation-gaming approach…

The potential value of Clostridium difficile vaccine: an economic computer simulation model.

PubMed

Lee, Bruce Y; Popovich, Michael J; Tian, Ye; Bailey, Rachel R; Ufberg, Paul J; Wiringa, Ann E; Muder, Robert R

2010-07-19

Efforts are currently underway to develop a vaccine against Clostridium difficile infection (CDI). We developed two decision analytic Monte Carlo computer simulation models: (1) an Initial Prevention Model depicting the decision whether to administer C. difficile vaccine to patients at-risk for CDI and (2) a Recurrence Prevention Model depicting the decision whether to administer C. difficile vaccine to prevent CDI recurrence. Our results suggest that a C. difficile vaccine could be cost-effective over a wide range of C. difficile risk, vaccine costs, and vaccine efficacies especially, when being used post-CDI treatment to prevent recurrent disease. (c) 2010 Elsevier Ltd. All rights reserved.
The Potential Value of Clostridium difficile Vaccine: An Economic Computer Simulation Model

PubMed Central

Lee, Bruce Y.; Popovich, Michael J.; Tian, Ye; Bailey, Rachel R.; Ufberg, Paul J.; Wiringa, Ann E.; Muder, Robert R.

2010-01-01

Efforts are currently underway to develop a vaccine against Clostridium difficile infection (CDI). We developed two decision analytic Monte Carlo computer simulation models: (1) an Initial Prevention Model depicting the decision whether to administer C. difficile vaccine to patients at-risk for CDI and (2) a Recurrence Prevention Model depicting the decision whether to administer C. difficile vaccine to prevent CDI recurrence. Our results suggest that a C. difficile vaccine could be cost-effective over a wide range of C. difficile risk, vaccine costs, and vaccine efficacies especially when being used post-CDI treatment to prevent recurrent disease. PMID:20541582
Modeling perceptions of climatic risk in crop production.

PubMed

Reinmuth, Evelyn; Parker, Phillip; Aurbacher, Joachim; Högy, Petra; Dabbert, Stephan

2017-01-01

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of "still-good yield" (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in the analysis.
Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models.

PubMed

Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik

2017-12-15

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Modeling perceptions of climatic risk in crop production

PubMed Central

Parker, Phillip; Aurbacher, Joachim; Högy, Petra; Dabbert, Stephan

2017-01-01

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of “still-good yield” (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in the analysis. PMID:28763471
Kinetic exchange models: From molecular physics to social science

NASA Astrophysics Data System (ADS)

Patriarca, Marco; Chakraborti, Anirban

2013-08-01

We discuss several multi-agent models that have their origin in the kinetic exchange theory of statistical mechanics and have been recently applied to a variety of problems in the social sciences. This class of models can be easily adapted for simulations in areas other than physics, such as the modeling of income and wealth distributions in economics and opinion dynamics in sociology.
High Performance Computing for Modeling Wind Farms and Their Impact

NASA Astrophysics Data System (ADS)

Mavriplis, D.; Naughton, J. W.; Stoellinger, M. K.

2016-12-01

As energy generated by wind penetrates further into our electrical system, modeling of power production, power distribution, and the economic impact of wind-generated electricity is growing in importance. The models used for this work can range in fidelity from simple codes that run on a single computer to those that require high performance computing capabilities. Over the past several years, high fidelity models have been developed and deployed on the NCAR-Wyoming Supercomputing Center's Yellowstone machine. One of the primary modeling efforts focuses on developing the capability to compute the behavior of a wind farm in complex terrain under realistic atmospheric conditions. Fully modeling this system requires the simulation of continental flows to modeling the flow over a wind turbine blade, including down to the blade boundary level, fully 10 orders of magnitude in scale. To accomplish this, the simulations are broken up by scale, with information from the larger scales being passed to the lower scale models. In the code being developed, four scale levels are included: the continental weather scale, the local atmospheric flow in complex terrain, the wind plant scale, and the turbine scale. The current state of the models in the latter three scales will be discussed. These simulations are based on a high-order accurate dynamic overset and adaptive mesh approach, which runs at large scale on the NWSC Yellowstone machine. A second effort on modeling the economic impact of new wind development as well as improvement in wind plant performance and enhancements to the transmission infrastructure will also be discussed.
An analysis of intergroup rivalry using Ising model and reinforcement learning

NASA Astrophysics Data System (ADS)

Zhao, Feng-Fei; Qin, Zheng; Shao, Zhuo

2014-01-01

Modeling of intergroup rivalry can help us better understand economic competitions, political elections and other similar activities. The result of intergroup rivalry depends on the co-evolution of individual behavior within one group and the impact from the rival group. In this paper, we model the rivalry behavior using Ising model. Different from other simulation studies using Ising model, the evolution rules of each individual in our model are not static, but have the ability to learn from historical experience using reinforcement learning technique, which makes the simulation more close to real human behavior. We studied the phase transition in intergroup rivalry and focused on the impact of the degree of social freedom, the personality of group members and the social experience of individuals. The results of computer simulation show that a society with a low degree of social freedom and highly educated, experienced individuals is more likely to be one-sided in intergroup rivalry.
Game theory based models to analyze water conflicts in the Middle Route of the South-to-North Water Transfer Project in China.

PubMed

Wei, Shouke; Yang, Hong; Abbaspour, Karim; Mousavi, Jamshid; Gnauck, Albrecht

2010-04-01

This study applied game theory based models to analyze and solve water conflicts concerning water allocation and nitrogen reduction in the Middle Route of the South-to-North Water Transfer Project in China. The game simulation comprised two levels, including one main game with five players and four sub-games with each containing three sub-players. We used statistical and econometric regression methods to formulate payoff functions of the players, economic valuation methods (EVMs) to transform non-monetary value into economic one, cost-benefit Analysis (CBA) to compare the game outcomes, and scenario analysis to investigate the future uncertainties. The validity of game simulation was evaluated by comparing predictions with observations. The main results proved that cooperation would make the players collectively better off, though some player would face losses. However, players were not willing to cooperate, which would result in a prisoners' dilemma. Scenarios simulation results displayed that players in water scare area could not solve its severe water deficit problem without cooperation with other players even under an optimistic scenario, while the uncertainty of cooperation would come from the main polluters. The results suggest a need to design a mechanism to reduce the risk of losses of those players by a side payment, which provides them with economic incentives to cooperate. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Performance modeling and techno-economic analysis of a modular concentrated solar power tower with latent heat storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rea, Jonathan E.; Oshman, Christopher J.; Olsen, Michele L.

In this paper, we present performance simulations and techno-economic analysis of a modular dispatchable solar power tower. Using a heliostat field and power block three orders of magnitude smaller than conventional solar power towers, our unique configuration locates thermal storage and a power block directly on a tower receiver. To make the system dispatchable, a valved thermosyphon controls heat flow from a latent heat thermal storage tank to a Stirling engine. The modular design results in minimal balance of system costs and enables high deployment rates with a rapid realization of economies of scale. In this new analysis, we combinemore » performance simulations with techno-economic analysis to evaluate levelized cost of electricity, and find that the system has potential for cost-competitiveness with natural gas peaking plants and alternative dispatchable renewables.« less
Preventing Pirates from Boarding Commercial Vessels - A Systems Approach

DTIC Science & Technology

2014-09-01

was developed in MATLAB to run simulations designed to estimate the relative effectiveness of each assessed countermeasure. A cost analysis was...project indicated that the P-Trap countermeasure, designed to entangle the pirate’s propellers with thin lines, is both effective and economically viable...vessels. A model of the operational environment was developed in MATLAB to run simulations designed to estimate the relative effectiveness of each
Investment in Communications and Transportation: Socio-economic Impacts on Rural Development.

ERIC Educational Resources Information Center

Hilewick, Carol Lee; And Others

Two rural counties served as model areas in a comparison of the size and sequence of socioeconomic changes that investment in communications, as opposed to investment in transportation networks, might stimulate. A series of communications, rail, and highway changes were simulated through the use of an econometric model. An Industrial Communication…
Participatory Systems Modeling to Explore Sustainable Solutions: Triple Value Simulation Modeling Cases Tackle Nutrient and Watershed Management from a Socio-Ecological Systems (SES) perspective

EPA Science Inventory

Decision makers often need assistance in understanding dynamic interactions and linkages among economic, environmental and social systems in coastal watersheds. They also need scientific input to better evaluate potential costs and benefits of alternative policy interventions. Th...
ASPEN+ and economic modeling of equine waste utilization for localized hot water heating via fast pyrolysis

USDA-ARS?s Scientific Manuscript database

ASPEN Plus based simulation models have been developed to design a pyrolysis process for the on-site production and utilization of pyrolysis oil from equine waste at the Equine Rehabilitation Center at Morrisville State College (MSC). The results indicate that utilization of all available Equine Reh...
Flat-plate solar array project. Volume 8: Project analysis and integration

NASA Technical Reports Server (NTRS)

Mcguire, P.; Henry, P.

1986-01-01

Project Analysis and Integration (PA&I) performed planning and integration activities to support management of the various Flat-Plate Solar Array (FSA) Project R&D activities. Technical and economic goals were established by PA&I for each R&D task within the project to coordinate the thrust toward the National Photovoltaic Program goals. A sophisticated computer modeling capability was developed to assess technical progress toward meeting the economic goals. These models included a manufacturing facility simulation, a photovoltaic power station simulation and a decision aid model incorporating uncertainty. This family of analysis tools was used to track the progress of the technology and to explore the effects of alternative technical paths. Numerous studies conducted by PA&I signaled the achievement of milestones or were the foundation of major FSA project and national program decisions. The most important PA&I activities during the project history are summarized. The PA&I planning function is discussed and how it relates to project direction and important analytical models developed by PA&I for its analytical and assessment activities are reviewed.
Essays on the economics and econometrics of human capital

NASA Astrophysics Data System (ADS)

Mosso, Stefano

This thesis is composed by three distinct chapters. They are related by their common theme: the economic analysis of the process of human capital formation. The first chapter distills and extends the recent research on the economics of human development and social mobility. It critically analyzes the literature on the role of early life conditions in shaping multiple life skills with emphasis on the importance of critical and sensitive investments periods in influencing skill development. It develops economic models that rationalize the empirical evidence on treatment effects of social programs and on family influence. It investigates the empirical support of recent claims, made by part of the literature, on the relevance of credit constraints in limiting skill development. It shows how credit constraints are not a major force explaining differences in the amount of parental and self-investments in skills and how untargeted income transfer policies to poor families do not significantly boost child outcomes. The second chapter compares the performance of maximum likelihood and simulated methods of moments in estimating dynamic discrete choice models. It presents a structural model of education and shows how it can be used to estimate heterogeneous returns from schooling choices which account for their continuation values. Continuation values have a large impact on returns, but are ignored in the measures commonly used to assess the value of schooling choices. The estimates from the model are used to compute a synthetic dataset. This is used to assess the ability of maximum likelihood and simulated methods of moments to recover the model parameters. It finally proposes a Monte Carlo exercise to gain confidence on the performance of a simulated method of moments algorithm. The last chapter proposes a method to assess long run impacts on earnings of early interventions even in absence of long-term data collection on earnings histories for program participants. It combines the methodological approaches of the literature on program evaluation, data combination and forecasting to develop estimators of the average treatment effects. This exercise allows a more complete cost-benefit evaluation of social programs accounting for benefits over the whole life cycle.
Diagnosing observed characteristics of the wet season across Africa to identify deficiencies in climate model simulations

NASA Astrophysics Data System (ADS)

Dunning, C.; Black, E.; Allan, R. P.

2017-12-01

The seasonality of rainfall over Africa plays a key role in determining socio-economic impacts for agricultural stakeholders, influences energy supply from hydropower, affects the length of the malaria transmission season and impacts surface water supplies. Hence, failure or delays of these rains can lead to significant socio-economic impacts. Diagnosing and interpreting interannual variability and long-term trends in seasonality, and analysing the physical driving mechanisms, requires a robust definition of African precipitation seasonality, applicable to both observational datasets and model simulations. Here we present a methodology for objectively determining the onset and cessation of multiple wet seasons across the whole of Africa. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite-based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. Application of this method to observational datasets reveals that over East Africa cessation of the short rains is 5 days earlier in La Nina years, and the failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons over this region. The method is used to examine the representation of the seasonality of African precipitation in CMIP5 model simulations. Overall, atmosphere-only and fully coupled CMIP5 historical simulations represent essential aspects of the seasonal cycle; patterns of seasonal progression of the rainy season are captured, for the most part mean model onset/ cessation dates agree with mean observational dates to within 18 days. However, unlike the atmosphere-only simulations, the coupled simulations do not capture the biannual regime over the southern West African coastline, linked to errors in Gulf of Guinea Sea Surface Temperature. Application to both observational and climate model datasets, and good agreement with agricultural onset methods, indicates the potential applicability of this method to a variety of meteorological and climate impact studies.
Village power options

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lilienthal, P.

1997-12-01

This paper describes three different computer codes which have been written to model village power applications. The reasons which have driven the development of these codes include: the existance of limited field data; diverse applications can be modeled; models allow cost and performance comparisons; simulations generate insights into cost structures. The models which are discussed are: Hybrid2, a public code which provides detailed engineering simulations to analyze the performance of a particular configuration; HOMER - the hybrid optimization model for electric renewables - which provides economic screening for sensitivity analyses; and VIPOR the village power model - which is amore » network optimization model for comparing mini-grids to individual systems. Examples of the output of these codes are presented for specific applications.« less
Resource Economics

NASA Astrophysics Data System (ADS)

Conrad, Jon M.

2000-01-01

Resource Economics is a text for students with a background in calculus, intermediate microeconomics, and a familiarity with the spreadsheet software Excel. The book covers basic concepts, shows how to set up spreadsheets to solve dynamic allocation problems, and presents economic models for fisheries, forestry, nonrenewable resources, stock pollutants, option value, and sustainable development. Within the text, numerical examples are posed and solved using Excel's Solver. These problems help make concepts operational, develop economic intuition, and serve as a bridge to the study of real-world problems of resource management. Through these examples and additional exercises at the end of Chapters 1 to 8, students can make dynamic models operational, develop their economic intuition, and learn how to set up spreadsheets for the simulation of optimization of resource and environmental systems. Book is unique in its use of spreadsheet software (Excel) to solve dynamic allocation problems Conrad is co-author of a previous book for the Press on the subject for graduate students Approach is extremely student-friendly; gives students the tools to apply research results to actual environmental issues
The economic impact of NASA R and D spending: Executive summary

NASA Technical Reports Server (NTRS)

Evans, M. K.

1976-01-01

An evaluation of the economic impact of NASA research and development programs is made. The methodology and the results revolve around the interrelationships existing between the demand and supply effects of increased research and development spending, in particular, NASA research and development spending. The INFORUM Inter-Industry Forecasing Model is used to measure the short-run economic impact of alternative levels of NASA expenditures for 1975. An aggregate production function approach is used to develop the data series necessary to measure the impact of NASA research and development spending, and other determinants of technological progress, on the rate of growth in productivity of the U. S. economy. The measured relationship between NASA research and development spending and technological progress is simulated in the Chase Macroeconometric Model to measure the immediate, intermediate, and long-run economic impact of increased NASA research and development spending over a sustained period.

Modeling uncertainties in workforce disruptions from influenza pandemics using dynamic input-output analysis.

PubMed

El Haimar, Amine; Santos, Joost R

2014-03-01

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input-output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as-planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health-care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics. © 2013 Society for Risk Analysis.
Modeling of materials supply, demand and prices

NASA Technical Reports Server (NTRS)

1982-01-01

The societal, economic, and policy tradeoffs associated with materials processing and utilization, are discussed. The materials system provides the materials engineer with the system analysis required for formulate sound materials processing, utilization, and resource development policies and strategies. Materials system simulation and modeling research program including assessments of materials substitution dynamics, public policy implications, and materials process economics was expanded. This effort includes several collaborative programs with materials engineers, economists, and policy analysts. The technical and socioeconomic issues of materials recycling, input-output analysis, and technological change and productivity are examined. The major thrust areas in materials systems research are outlined.
Cost-effectiveness simulation analysis of schizophrenia at the Instituto Mexicano del Seguro Social: Assessment of typical and atypical antipsychotics.

PubMed

Mould-Quevedo, Joaquín; Contreras-Hernández, Iris; Verduzco, Wáscar; Mejía-Aranguré, Juan Manuel; Garduño-Espinosa, Juan

2009-07-01

Estimation of the economic costs of schizophrenia is a fundamental tool for a better understanding of the magnitude of this health problem. The aim of this study was to estimate the costs and effectiveness of five antipsychotic treatments (ziprasidone, olanzapine, risperidone, haloperidol and clozapine), which are included in the national formulary at the Instituto Mexicano del Seguro Social, through a simulation model. Type of economic evaluation: complete economic evaluation of cost-effectiveness. direct medical costs. 1 year. Effectiveness measure: number of months free of psychotic symptoms. to estimate cost-effectiveness, a Markov model was constructed and a Monte Carlo simulation was carried out. Effectiveness: the results of the Markov model showed that the antipsychotic with the highest number months free of psychotic symptoms was ziprasidone (mean 9.2 months). The median annual costs for patients using ziprasidone included in the hypothetical cohort was 194,766.6 Mexican pesos (MXP) (95% CI, 26,515.6-363,017.6 MXP), with an exchange rate of 1 € = 17.36 MXP. The highest costs in the probabilistic analysis were estimated for clozapine treatment (260,236.9 MXP). Through a probabilistic analysis, ziprasidone showed the lowest costs and the highest number of months free of psychotic symptoms and was also the most costeffective antipsychotic observed in acceptability curves and net monetary benefits. Copyright © 2009 Sociedad Española de Psiquiatría and Sociedad Española de Psiquiatría Biológica. Published by Elsevier Espana. All rights reserved.
Quick-start guide for version 3.0 of EMINERS - Economic Mineral Resource Simulator

USGS Publications Warehouse

Bawiec, Walter J.; Spanski, Gregory T.

2012-01-01

Quantitative mineral resource assessment, as developed by the U.S. Geological Survey (USGS), consists of three parts: (1) development of grade and tonnage mineral deposit models; (2) delineation of tracts permissive for each deposit type; and (3) probabilistic estimation of the numbers of undiscovered deposits for each deposit type (Singer and Menzie, 2010). The estimate of the number of undiscovered deposits at different levels of probability is the input to the EMINERS (Economic Mineral Resource Simulator) program. EMINERS uses a Monte Carlo statistical process to combine probabilistic estimates of undiscovered mineral deposits with models of mineral deposit grade and tonnage to estimate mineral resources. It is based upon a simulation program developed by Root and others (1992), who discussed many of the methods and algorithms of the program. Various versions of the original program (called "MARK3" and developed by David H. Root, William A. Scott, and Lawrence J. Drew of the USGS) have been published (Root, Scott, and Selner, 1996; Duval, 2000, 2012). The current version (3.0) of the EMINERS program is available as USGS Open-File Report 2004-1344 (Duval, 2012). Changes from version 2.0 include updating 87 grade and tonnage models, designing new templates to produce graphs showing cumulative distribution and summary tables, and disabling economic filters. The economic filters were disabled because embedded data for costs of labor and materials, mining techniques, and beneficiation methods are out of date. However, the cost algorithms used in the disabled economic filters are still in the program and available for reference for mining methods and milling techniques included in Camm (1991). EMINERS is written in C++ and depends upon the Microsoft Visual C++ 6.0 programming environment. The code depends heavily on the use of Microsoft Foundation Classes (MFC) for implementation of the Windows interface. The program works only on Microsoft Windows XP or newer personal computers. It does not work on Macintosh computers. This report demonstrates how to execute EMINERS software using default settings and existing deposit models. Many options are available when setting up the simulation. Information and explanations addressing these optional parameters can be found in the EMINERS Help files. Help files are available during execution of EMINERS by selecting EMINERS Help from the pull-down menu under Help on the EMINERS menu bar. There are four sections in this report. Part I describes the installation, setup, and application of the EMINERS program, and Part II illustrates how to interpret the text file that is produced. Part III describes the creation of tables and graphs by use of the provided Excel templates. Part IV summarizes grade and tonnage models used in version 3.0 of EMINERS.
Supplemental nutrition assistance program and body weight outcomes: the role of economic contextual factors.

PubMed

Han, Euna; Powell, Lisa M; Isgor, Zeynep

2012-06-01

We explored the extent to which economic contextual factors moderated the association of Supplemental Nutrition Assistance Program (SNAP) participation with body mass index (BMI) among low-income adults whose family income (adjusted for family size) is less than 130% of the federal poverty guideline. We drew on individual-level data from the Panel Study of Income Dynamics in the United States, including three waves of data in 1999, 2001, and 2003. Economic contextual data were drawn from the American Chamber of Commerce Researchers Association for food prices and Dun & Bradstreet for food outlet measures. In addition to cross-sectional estimation, a longitudinal individual fixed effects model was used to control for permanent unobserved individual heterogeneity. Our study found a statistically significant joint moderating effect of the economic contextual factors in longitudinal individual fixed effects model for both women (BMI only) and men (both BMI and obesity). For both women and men, SNAP participants' BMI was statistically significantly lower if they faced increased numbers of available supermarkets/grocery stores in the longitudinal model. A simulated 20% reduction in the price of fruits and vegetables resulted in a larger decrease in BMI among SNAP participants than non-participants for women and men, whereas a simulated 20% increase in the availability of supermarkets and grocery stores resulted in a statistically significant difference in the change in BMI by SNAP participation for women but not for men. Policies related to economic contextual factors, such as subsidies for fruits and vegetables or those that would improve access to supermarkets and grocery stores may enhance the relationship between SNAP participation and body mass outcomes among food assistance program participants. Copyright © 2012 Elsevier Ltd. All rights reserved.
System-level modeling for geological storage of CO2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yingqi; Oldenburg, Curtis M.; Finsterle, Stefan

2006-04-24

One way to reduce the effects of anthropogenic greenhousegases on climate is to inject carbon dioxide (CO2) from industrialsources into deep geological formations such as brine formations ordepleted oil or gas reservoirs. Research has and is being conducted toimprove understanding of factors affecting particular aspects ofgeological CO2 storage, such as performance, capacity, and health, safetyand environmental (HSE) issues, as well as to lower the cost of CO2capture and related processes. However, there has been less emphasis todate on system-level analyses of geological CO2 storage that considergeological, economic, and environmental issues by linking detailedrepresentations of engineering components and associated economic models.Themore » objective of this study is to develop a system-level model forgeological CO2 storage, including CO2 capture and separation,compression, pipeline transportation to the storage site, and CO2injection. Within our system model we are incorporating detailedreservoir simulations of CO2 injection and potential leakage withassociated HSE effects. The platform of the system-level modelingisGoldSim [GoldSim, 2006]. The application of the system model is focusedon evaluating the feasibility of carbon sequestration with enhanced gasrecovery (CSEGR) in the Rio Vista region of California. The reservoirsimulations are performed using a special module of the TOUGH2 simulator,EOS7C, for multicomponent gas mixtures of methane and CO2 or methane andnitrogen. Using this approach, the economic benefits of enhanced gasrecovery can be directly weighed against the costs, risks, and benefitsof CO2 injection.« less
HOMER Economic Models - US Navy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, Jason William; Myers, Kurt Steven

This LETTER REPORT has been prepared by Idaho National Laboratory for US Navy NAVFAC EXWC to support in testing pre-commercial SIREN (Simulated Integration of Renewable Energy Networks) computer software models. In the logistics mode SIREN software simulates the combination of renewable power sources (solar arrays, wind turbines, and energy storage systems) in supplying an electrical demand. NAVFAC EXWC will create SIREN software logistics models of existing or planned renewable energy projects at five Navy locations (San Nicolas Island, AUTEC, New London, & China Lake), and INL will deliver additional HOMER computer models for comparative analysis. In the transient mode SIRENmore » simulates the short time-scale variation of electrical parameters when a power outage or other destabilizing event occurs. In the HOMER model, a variety of inputs are entered such as location coordinates, Generators, PV arrays, Wind Turbines, Batteries, Converters, Grid costs/usage, Solar resources, Wind resources, Temperatures, Fuels, and Electric Loads. HOMER's optimization and sensitivity analysis algorithms then evaluate the economic and technical feasibility of these technology options and account for variations in technology costs, electric load, and energy resource availability. The Navy can then use HOMER’s optimization and sensitivity results to compare to those of the SIREN model. The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) possesses unique expertise and experience in the software, hardware, and systems design for the integration of renewable energy into the electrical grid. NAVFAC EXWC will draw upon this expertise to complete mission requirements.« less
A multiple perspective modeling and simulation approach for renewable energy policy evaluation

NASA Astrophysics Data System (ADS)

Alyamani, Talal M.

Environmental issues and reliance on fossil fuel sources, including coal, oil, and natural gas, are the two most common energy issues that are currently faced by the United States (U.S.). Incorporation of renewable energy sources, a non-economical option in electricity generation compared to conventional sources that burn fossil fuels, single handedly promises a viable solution for both of these issues. Several energy policies have concordantly been suggested to reduce the financial burden of adopting renewable energy technologies and make such technologies competitive with conventional sources throughout the U.S. This study presents a modeling and analysis approach for comprehensive evaluation of renewable energy policies with respect to their benefits to various related stakeholders--customers, utilities, governmental and environmental agencies--where the debilitating impacts, advantages, and disadvantages of such policies can be assessed and quantified at the state level. In this work, a novel simulation framework is presented to help policymakers promptly assess and evaluate policies from different perspectives of its stakeholders. The proposed framework is composed of four modules: 1) a database that collates the economic, operational, and environmental data; 2) elucidation of policy, which devises the policy for the simulation model; 3) a preliminary analysis, which makes predictions for consumption, supply, and prices; and 4) a simulation model. After the validity of the proposed framework is demonstrated, a series of planned Florida and Texas renewable energy policies are implemented into the presented framework as case studies. Two solar and one energy efficiency programs are selected as part of the Florida case study. A utility rebate and federal tax credit programs are selected as part of the Texas case study. The results obtained from the simulation and conclusions drawn on the assessment of current energy policies are presented with respect to the conflicting objectives of different stakeholders.
Dynamic energy budget model: a monitoring tool for growth and reproduction performance of Mytilus galloprovincialis in Bizerte Lagoon (Southwestern Mediterranean Sea).

PubMed

Béjaoui-Omri, Amel; Béjaoui, Béchir; Harzallah, Ali; Aloui-Béjaoui, Nejla; El Bour, Monia; Aleya, Lotfi

2014-11-01

Mussel farming is the main economic activity in Bizerte Lagoon, with a production that fluctuates depending on environmental factors. In the present study, we apply a bioenergetic growth model to the mussel Mytilus galloprovincialis, based on dynamic energy budget (DEB) theory which describes energy flux variation through the different compartments of the mussel body. Thus, the present model simulates both mussel growth and sexual cycle steps according to food availability and water temperature and also the effect of climate change on mussel behavior and reproduction. The results point to good concordance between simulations and growth parameters (metric length and weight) for mussels in the lagoon. A heat wave scenario was also simulated using the DEB model, which highlighted mussel mortality periods during a period of high temperature.
Hydro-Economic Modeling with Minimum Data Requirements: An Application to the São Francisco River Basin, Brazil

NASA Astrophysics Data System (ADS)

Torres, M.; Maneta, M.; Vosti, S.; Wallender, W.; Howitt, R.

2008-12-01

Policymakers have been charged with the efficient, equitable, and sustainable use of water resources of the São Francisco River Basin (SFRB), Brazil, and also with the promotion of economic growth and the reduction of poverty within the basin. To date, policymakers lack scientific evidence on the potential consequences for growth, poverty alleviation or environmental sustainability of alternative uses of water resources. To address these key knowledge gaps, we have linked a hydrologic and an economic model of agriculture to investigate how economic decisions affect available water, and vice versa. More specifically, the models are used to predict the effects of the application of Brazilian federal surface water use policies on farmer's net revenues and on the hydrologic system. The Economic Model of Agriculture. A spatially explicit, farm-level model capable of accommodating a broad array of farm sizes and farm/farmer characteristics is developed and used to predict the effects of alternative water policies and neighbors' water use patterns on crop mix choice. A production function comprised of seven categories of non-water-related inputs used in agriculture (land, fertilizers, pesticides, seeds, hired labor, family labor and machinery) and four water-related inputs used in agriculture (applied water, irrigation labor, irrigation capital and energy) is estimated. The parameters emerging from this estimated production function are then introduced into a non-linear, net revenue maximization positive mathematical programming algorithm that is used for simulations. The Hydrological Model. MIKE Basin, a semi-distributed hydrology model, is used to calculate water budgets for the SFRB. MIKE Basin calculates discharge at selected nodes by accumulating runoff down the river network; it simulates reservoirs using stage-area-storage and downstream release rule curves. The data used to run the model are discharge to calculate local runoff, precipitation, reference ET, crop coefficients to calculate adjusted transpiration, and reservoir operating rules. Linking the Hydro and Economic Models. Based on the crop mix and area under plow of a reference year the economic model of agriculture was calibrated. Following a Monte Carlo procedure, the statistical distribution of water flows was estimated at each of the 16 selected nodes in the SFRB. The 5th and 95th percentiles of that distribution were used as benchmarks of water availability for drought and wet years, respectively. After subtracting 2000 m3 s-1 reserved for downstream uses estimates of water availability are used as constraints in the net revenue maximization algorithm included in the model of agriculture economics. If water is binding, it will influence crop mix, area under plow and product mix choices. Results. The application of the Brazilian federal water use policies will have immediate and substantial effects on agricultural area and product mix. Agricultural incomes will fall, especially in downstream areas located near major river channels.
Model of Market Share Affected by Social Media Reputation

NASA Astrophysics Data System (ADS)

Ishii, Akira; Kawahata, Yasuko; Goto, Ujo

Proposal of market theory to put the effect of social media into account is presented in this paper. The standard market share model in economics is employed as a market theory and the effect of social media is considered quantitatively using the mathematical model for hit phenomena. Using this model, we can estimate the effect of social media in market share as a simple market model simulation using our proposed method.
An Energy-Economy-Environment Model for Simulating the Impacts of Socioeconomic Development on Energy and Environment

PubMed Central

Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement. PMID:24683332
Cyanide removal from industrial wastewater by cross-flow nanofiltration: transport modeling and economic evaluation.

PubMed

Pal, Parimal; Bhakta, Pamela; Kumar, Ramesh

2014-08-01

A modeling and simulation study, along with an economic analysis, was carried out for the separation of cyanide from industrial wastewater using a flat sheet cross-flow nanofiltration membrane module. With the addition of a pre-microfiltration step, nanofiltration was carried out using real coke wastewater under different operating conditions. Under the optimum operating pressure of 13 bars and a pH of 10.0, a rate of more than 95% separation of cyanide was achieved. That model predictions agreed very well with the experimental findings, as is evident in the Willmott d-index value (> 0.95) and relative error (< 0.1). Studies were carried out with industrial wastewater instead of a synthetic solution, and an economic analysis was also done, considering the capacity of a running coking plant. The findings are likely to be very useful in the scale-up and design of industrial plants for the treatment of cyanide-bearing wastewater.
Sahra integrated modeling approach to address water resources management in semi-arid river basins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Springer, E. P.; Gupta, Hoshin V.; Brookshire, David S.

Water resources decisions in the 21Sf Century that will affect allocation of water for economic and environmental will rely on simulations from integrated models of river basins. These models will not only couple natural systems such as surface and ground waters, but will include economic components that can assist in model assessments of river basins and bring the social dimension to the decision process. The National Science Foundation Science and Technology Center for Sustainability of semi-Arid Hydrology and Riparian Areas (SAHRA) has been developing integrated models to assess impacts of climate variability and land use change on water resources inmore » semi-arid river basins. The objectives of this paper are to describe the SAHRA integrated modeling approach and to describe the linkage between social and natural sciences in these models. Water resources issues that arise from climate variability or land use change may require different resolution models to answer different questions. For example, a question related to streamflow may not need a high-resolution model whereas a question concerning the source and nature of a pollutant will. SAHRA has taken a multiresolution approach to integrated model development because one cannot anticipate the questions in advance, and the computational and data resources may not always be available or needed for the issue to be addressed. The coarsest resolution model is based on dynamic simulation of subwatersheds or river reaches. This model resolution has the advantage of simplicity and social factors are readily incorporated. Users can readily take this model (and they have) and examine the effects of various management strategies such as increased cost of water. The medium resolution model is grid based and uses variable grid cells of 1-12 km. The surface hydrology is more physically based using basic equations for energy and water balance terms, and modules are being incorporated that will simulate engineering components such as reservoirs or irrigation diversions and economic features such as variable demand. The fine resolution model is viewed as a tool to examine basin response using best available process models. The fine resolution model operates on a grid cell size of 100 m or less, which is consistent with the scale that our process knowledge has developed. The fine resolution model couples atmosphere, surface water and groundwater modules using high performance computing. The medium and fine resolution models are not expected at this time to be operated by users as opposed to the coarse resolution model. One of the objectives of the SAHRA integrated modeling task is to present results in a manner that can be used by those making decisions. The application of these models within SAHRA is driven by a scenario analysis and a place location. The place is the Rio Grande from its headwaters in Colorado to the New Mexico-Texas border. This provides a focus for model development and an attempt to see how the results from the various models relate. The scenario selected by SAHRA is the impact of a 1950's style drought using 1990's population and land use on Rio Grande water resources including surface and groundwater. The same climate variables will be used to drive all three models so that comparison will be based on how the three resolutions partition and route water through the river basin. Aspects of this scenario will be discussed and initial model simulation will be presented. The issue of linking economic modules into the modeling effort will be discussed and the importance of feedback from the social and economic modules to the natural science modules will be reviewed.« less
Simulating Quantile Models with Applications to Economics and Management

NASA Astrophysics Data System (ADS)

Machado, José A. F.

2010-05-01

The massive increase in the speed of computers over the past forty years changed the way that social scientists, applied economists and statisticians approach their trades and also the very nature of the problems that they could feasibly tackle. The new methods that use intensively computer power go by the names of "computer-intensive" or "simulation". My lecture will start with bird's eye view of the uses of simulation in Economics and Statistics. Then I will turn out to my own research on uses of computer- intensive methods. From a methodological point of view the question I address is how to infer marginal distributions having estimated a conditional quantile process, (Counterfactual Decomposition of Changes in Wage Distributions using Quantile Regression," Journal of Applied Econometrics 20, 2005). Illustrations will be provided of the use of the method to perform counterfactual analysis in several different areas of knowledge.
Using Earth Observations to Assess the Socioeconomic Impact of Human Decision Making during the Suppression of a Wildland Fire

NASA Astrophysics Data System (ADS)

Miller, V. V.; Kochanski, A.; Mandel, J.; Herr, V.; Schranz, S.

2016-12-01

This presentation will discuss the fire simulation system based on WRF-SFIRE and assimilation of satellite Active Fires detection to estimate the socio-economic impact of Earth observations and fire behavior modeling for the 2011 Las Conchas fire in New Mexico. Multiple scenarios will be developed with the WRF-SFIRE simulation based on value of information (VOI) provided by retired incident commanders, whose decision inputs will steer scenario development and simulation. The scenarios will differ according to the Earth observations available through NASA and then deemed useful to incident commanders. Each scenario will be evaluated in terms of its socio-economic impact as specified by NASA (2012) for its wildland fire program. This presentation is a proposed supplement to NASA grant NNX13AH59G Wildland Fire Behavior and Risk Forecasting, Sher Schranz, PI.
Simulating Water Markets to Help Design Water Rights Regimes

NASA Astrophysics Data System (ADS)

Harou, J. J.; Erfani, T.; Huskova, I.; Binions, O.

2012-12-01

In many catchments in England no further licenses are available from the Environmental regulator that provides them. The possibility of trading water between license holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. Although trading licenses has been possible since several years, it very rarely happens (roughly 50 trades in 8 years). Several barriers to trade exist including lack of sufficient and prolonged scarcity, license-holder unwillingness to risk future renewal, likelihood license will be downgraded during a trade, duration of time required for approving a trade, etc. Regulators seek to make policy changes so that their inability to grant new licenses will not harm the local and national economy. What policy changes will most cost-effectively increase trading and allow it to effectively reduce the economic cost of scarcity events? A screening tool that could help evaluate problems and advantages of different regulatory solutions, and that could serve to test, assuming transaction costs can be quantified, their effect on trading under specific conditions would be useful. We propose such a water market simulator that predicts economically efficient pair-wise trade (between willing buyers and sellers) and represents the interaction of trades with natural hydrological flows, engineered infrastructure and a particular regulatory regime. The model emulates license-holders' willingness to engage in short-term trade transactions. In their initial form different 'agents' (license holders) are represented using an economic benefit function of water use which is supplemented by rules to represent behavioral or other characteristics of realistic system behavior. A case study based on the river Ouse basin (UK) is made to test the model. The model simulates the catchment weekly over several years considering reservoirs and pair-wise specific transaction costs. Several regulatory policies are tested by evaluating their possible impact on transaction costs and then verifying impact on the number and type of predicted transactions.
Temporal Variations of Water Productivity in Irrigated Corn: An Analysis of Factors Influencing Yield and Water Use across Central Nebraska

PubMed Central

Carr, Tony; Yang, Haishun; Ray, Chittaranjan

2016-01-01

Water Productivity (WP) of a crop defines the relationship between the economic or physical yield of the crop and its water use. With this concept it is possible to identify disproportionate water use or water-limited yield gaps and thereby support improvements in agricultural water management. However, too often important qualitative and quantitative environmental factors are not part of a WP analysis and therefore neglect the aspect of maintaining a sustainable agricultural system. In this study, we examine both the physical and economic WP in perspective with temporally changing environmental conditions. The physical WP analysis was performed by comparing simulated maximum attainable corn yields per unit of water using the crop model Hybrid-Maize with observed data from 2005 through 2013 from 108 farm plots in the Central Platte and the Tri Basin Natural Resource Districts of Nebraska. In order to expand the WP analysis on external factors influencing yields, a second model, Maize-N, was used to estimate optimal nitrogen (N)–fertilizer rate for specific fields in the study area. Finally, a vadose zone flow and transport model, HYDRUS-1D for simulating vertical nutrient transport in the soil, was used to estimate locations of nitrogen pulses in the soil profile. The comparison of simulated and observed data revealed that WP was not on an optimal level, mainly due to large amounts of irrigation used in the study area. The further analysis illustrated year-to-year variations of WP during the nine consecutive years, as well as the need to improve fertilizer management to favor WP and environmental quality. In addition, we addressed the negative influence of groundwater depletion on the economic WP through increasing pumping costs. In summary, this study demonstrated that involving temporal variations of WP as well as associated environmental and economic issues can represent a bigger picture of WP that can help to create incentives to sustainably improve agricultural production. PMID:27575368
Power generation using sugar cane bagasse: A heat recovery analysis

NASA Astrophysics Data System (ADS)

Seguro, Jean Vittorio

The sugar industry is facing the need to improve its performance by increasing efficiency and developing profitable by-products. An important possibility is the production of electrical power for sale. Co-generation has been practiced in the sugar industry for a long time in a very inefficient way with the main purpose of getting rid of the bagasse. The goal of this research was to develop a software tool that could be used to improve the way that bagasse is used to generate power. Special focus was given to the heat recovery components of the co-generation plant (economizer, air pre-heater and bagasse dryer) to determine if one, or a combination, of them led to a more efficient co-generation cycle. An extensive review of the state of the art of power generation in the sugar industry was conducted and is summarized in this dissertation. Based on this models were developed. After testing the models and comparing the results with the data collected from the literature, a software application that integrated all these models was developed to simulate the complete co-generation plant. Seven different cycles, three different pressures, and sixty-eight distributions of the flue gas through the heat recovery components can be simulated. The software includes an economic analysis tool that can help the designer determine the economic feasibility of different options. Results from running the simulation are presented that demonstrate its effectiveness in evaluating and comparing the different heat recovery components and power generation cycles. These results indicate that the economizer is the most beneficial option for heat recovery and that the use of waste heat in a bagasse dryer is the least desirable option. Quantitative comparisons of several possible cycle options with the widely-used traditional back-pressure turbine cycle are given. These indicate that a double extraction condensing cycle is best for co-generation purposes. Power generation gains between 40 and 100% are predicted for some cycles with the addition of optimum heat recovery systems.
Communicating Value in Simulation: Cost-Benefit Analysis and Return on Investment.

PubMed

Asche, Carl V; Kim, Minchul; Brown, Alisha; Golden, Antoinette; Laack, Torrey A; Rosario, Javier; Strother, Christopher; Totten, Vicken Y; Okuda, Yasuharu

2018-02-01

Value-based health care requires a balancing of medical outcomes with economic value. Administrators need to understand both the clinical and the economic effects of potentially expensive simulation programs to rationalize the costs. Given the often-disparate priorities of clinical educators relative to health care administrators, justifying the value of simulation requires the use of economic analyses few physicians have been trained to conduct. Clinical educators need to be able to present thorough economic analyses demonstrating returns on investment and cost-effectiveness to effectively communicate with administrators. At the 2017 Academic Emergency Medicine Consensus Conference "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes," our breakout session critically evaluated the cost-benefit and return on investment of simulation. In this paper we provide an overview of some of the economic tools that a clinician may use to present the value of simulation training to financial officers and other administrators in the economic terms they understand. We also define three themes as a call to action for research related to cost-benefit analysis in simulation as well as four specific research questions that will help guide educators and hospital leadership to make decisions on the value of simulation for their system or program. © 2017 by the Society for Academic Emergency Medicine.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Behboodi, Sahand; Crawford, Curran

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council (WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methodsmore » presented.« less
Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

DOE PAGES

Chassin, David P.; Behboodi, Sahand; Crawford, Curran; ...

2015-12-23

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council (WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methodsmore » presented.« less
Operations Research techniques in the management of large-scale reforestation programs

Treesearch

Joseph Buongiorno; D.E. Teeguarden

1978-01-01

A reforestation planning system for the Douglas-fir region of the Western United States is described. Part of the system is a simulation model to predict plantation growth and to determine economic thinning regimes and rotation ages as a function of site characteristics, initial density, reforestation costs, and management constraints. A second model estimates the...
Estimating the economic opportunity cost of water use with river basin simulators in a computationally efficient way

NASA Astrophysics Data System (ADS)

Rougé, Charles; Harou, Julien J.; Pulido-Velazquez, Manuel; Matrosov, Evgenii S.

2017-04-01

The marginal opportunity cost of water refers to benefits forgone by not allocating an additional unit of water to its most economically productive use at a specific location in a river basin at a specific moment in time. Estimating the opportunity cost of water is an important contribution to water management as it can be used for better water allocation or better system operation, and can suggest where future water infrastructure could be most beneficial. Opportunity costs can be estimated using 'shadow values' provided by hydro-economic optimization models. Yet, such models' use of optimization means the models had difficulty accurately representing the impact of operating rules and regulatory and institutional mechanisms on actual water allocation. In this work we use more widely available river basin simulation models to estimate opportunity costs. This has been done before by adding in the model a small quantity of water at the place and time where the opportunity cost should be computed, then running a simulation and comparing the difference in system benefits. The added system benefits per unit of water added to the system then provide an approximation of the opportunity cost. This approximation can then be used to design efficient pricing policies that provide incentives for users to reduce their water consumption. Yet, this method requires one simulation run per node and per time step, which is demanding computationally for large-scale systems and short time steps (e.g., a day or a week). Besides, opportunity cost estimates are supposed to reflect the most productive use of an additional unit of water, yet the simulation rules do not necessarily use water that way. In this work, we propose an alternative approach, which computes the opportunity cost through a double backward induction, first recursively from outlet to headwaters within the river network at each time step, then recursively backwards in time. Both backward inductions only require linear operations, and the resulting algorithm tracks the maximal benefit that can be obtained by having an additional unit of water at any node in the network and at any date in time. Results 1) can be obtained from the results of a rule-based simulation using a single post-processing run, and 2) are exactly the (gross) benefit forgone by not allocating an additional unit of water to its most productive use. The proposed method is applied to London's water resource system to track the value of storage in the city's water supply reservoirs on the Thames River throughout a weekly 85-year simulation. Results, obtained in 0.4 seconds on a single processor, reflect the environmental cost of water shortage. This fast computation allows visualizing the seasonal variations of the opportunity cost depending on reservoir levels, demonstrating the potential of this approach for exploring water values and its variations using simulation models with multiple runs (e.g. of stochastically generated plausible future river inflows).
Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos

2013-09-05

The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less
Interdisciplinary pharmacometrics linking oseltamivir pharmacology, influenza epidemiology and health economics to inform antiviral use in pandemics.

PubMed

Kamal, Mohamed A; Smith, Patrick F; Chaiyakunapruk, Nathorn; Wu, David B C; Pratoomsoot, Chayanin; Lee, Kenneth K C; Chong, Huey Yi; Nelson, Richard E; Nieforth, Keith; Dall, Georgina; Toovey, Stephen; Kong, David C M; Kamauu, Aaron; Kirkpatrick, Carl M; Rayner, Craig R

2017-07-01

A modular interdisciplinary platform was developed to investigate the economic impact of oseltamivir treatment by dosage regimen under simulated influenza pandemic scenarios. The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration-time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (R 0 ), a measure of transmissibility, was linked by reduction of viral shedding duration. The number of infected patients per population of 100 000 susceptible individuals was simulated for a series of pandemic scenarios, varying oseltamivir dose, R 0 (1.9 vs. 2.7), and drug uptake (25%, 50%, and 80%). The number of infected patients for each scenario was entered into the health economics module, a decision analytic model populated with branch probabilities, disease utility, costs of hospitalized patients developing complications, and case-fatality rates. Change in quality-adjusted life years was determined relative to base case. Oseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios. This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework. © 2017 The British Pharmacological Society.
Tipping Points towards Regional Forest or Urban Transition in Stressed Rural Areas: An Agent-based Modelling Application of Socio-Economic Shifts in Rural Vermont US

NASA Astrophysics Data System (ADS)

Tsai, Y.; Turnbull, S.; Zia, A.

2015-12-01

In rural areas where farming competes with urban development and environmental amenities, urban and forest transitions occur simultaneously at different locales with different rates due to the underlying socio-economic shifts. Here we develop an interactive land use transition agent-based model (ILUTABM) in which farmers' land use decisions are made contingent on expansion and location choices of urban businesses and urban residences, as well as farmers' perceived ecosystem services produced by their land holdings. The ILUTABM simulates heterogeneity in land use decisions at parcel levels by differentiating decision making processes for agricultural and urban landowners. Landowners are simulated to make land-use transition decisions as bounded rational agents that maximize their partial expected utility functions under different underlying socio-economic conditions given the category of a landowner and the spatial characteristics of the landowner's landholdings. The ILUTABM is parameterized by spatial data sets such as National Land Cover Database (NLCD), zoning, parcels, property prices, US census, farmers surveys, building/facility characteristics, soil, slope and elevation. We then apply the ILUTABM to the rural Vermont landscape, located in the Northeast Arm District of Lake Champlain and the downstream sub-watersheds of Missisquoi River, to generate phase transitions of rural land towards urban land near peri-urban areas and towards forest land near financially stressed farmlands during 2001-2051. Possible tipping point trajectories of rural land towards regional forest or urban transition are simulated under three socio-economic scenarios: business as usual (ILUTABM calibrated to 2011 NLCD), increased incentives for conservation easements, and increased incentives for attracting urban residences and businesses.
Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Adamowski, J. F.; Wang, L. Y.; Rojas, M.; Carrera, J.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.
Issues in container transportation in the Northeast : background, framework, illustrative results and future directions

DOT National Transportation Integrated Search

2004-12-01

An integrated framework for addressing container transportation issues in the Northeast US is developed and illustrated. The framework involves the extension of a spatial-economic coastal container port and related multimodal demand simulation model ...
EFFECTIVENESS OF SOIL AND WATER CONSERVATION PRACTICES FOR POLLUTION CONTROL

EPA Science Inventory

The potential water quality effects and economic implications of soil and water conservation practices (SWCPs) are identified. Method for estimating the effects of SWCPs on pollutant losses from croplands are presented. Mathematical simulation and linear programming models were u...
Computer Series, 13: Bits and Pieces, 11.

ERIC Educational Resources Information Center

Moore, John W., Ed.

1982-01-01

Describes computer programs (with ordering information) on various topics including, among others, modeling of thermodynamics and economics of solar energy, radioactive decay simulation, stoichiometry drill/tutorial (in Spanish), computer-generated safety quiz, medical chemistry computer game, medical biochemistry question bank, generation of…
Economic consequences of population size, structure and growth.

PubMed

Lee, R

1983-01-01

There seems to be 4 major approaches to conceptualizing and modeling demographic influences on economic and social welfare. These approaches are combined in various ways to construct richer and more comprehensive models. The basic approaches are: demographic influences on household or family behavior; population growth and reproducible capital; population size and fixed factors; and population and advantages of scale. These 4 models emphasize the supply side effects of population. A few of the ways in which these theories have been combined are sketched. Neoclassical growth models often have been combined with age distributed populations of individuals (or households), assumed to pursue optimal life cycle consumption and saving. In some well known development models, neoclassical growth models for the modern sector are linked by labor markets and migration to fixed factor (land) models of the traditional (agricultural) sector. A whole series of macro simulation models for developed and developing countries was based on single sector neoclassical growth models with age distributed populations. Yet, typically the household level foundations of assumed age distribution effects were not worked out. Simon's (1977) simulation models are in a class by themselves, for they are the only models that attempt to incorporate all the kinds of effects discussed. The economic demography of the individual and family cycle, as it is affected by regimes of fertility, mortality, and nuptiality, taken as given, are considered. The examination touches on many of the purported consequences of aggregate population growth and age composition, since so many of these are based implicitly or explicitly on assertions about micro level behavior. Demographic influences on saving and consumption, on general labor supply and female labor supply, and on problems of youth and old age dependency frequently fall in this category. Finally, attention is focused specifically on macro economic issues in the consequences of population in both developed and developing countries. In general cross national studies have failed to provide rough and stylized depiction of the consequences of rapid population growth, unless the absence of significant results is itself the result.
Economic and environmental benefits of higher-octane gasoline.

PubMed

Speth, Raymond L; Chow, Eric W; Malina, Robert; Barrett, Steven R H; Heywood, John B; Green, William H

2014-06-17

We quantify the economic and environmental benefits of designing U.S. light-duty vehicles (LDVs) to attain higher fuel economy by utilizing higher octane (98 RON) gasoline. We use engine simulations, a review of experimental data, and drive cycle simulations to estimate the reduction in fuel consumption associated with using higher-RON gasoline in individual vehicles. Lifecycle CO2 emissions and economic impacts for the U.S. LDV fleet are estimated based on a linear-programming refinery model, a historically calibrated fleet model, and a well-to-wheels emissions analysis. We find that greater use of high-RON gasoline in appropriately tuned vehicles could reduce annual gasoline consumption in the U.S. by 3.0-4.4%. Accounting for the increase in refinery emissions from production of additional high-RON gasoline, net CO2 emissions are reduced by 19-35 Mt/y in 2040 (2.5-4.7% of total direct LDV CO2 emissions). For the strategies studied, the annual direct economic benefit is estimated to be $0.4-6.4 billion in 2040, and the annual net societal benefit including the social cost of carbon is estimated to be $1.7-8.8 billion in 2040. Adoption of a RON standard in the U.S. in place of the current antiknock index (AKI) may enable refineries to produce larger quantities of high-RON gasoline.
Modeling Negotiation by a Paticipatory Approach

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Ishida, Toru; Bousquet, François

In a participatory approach by social scientists, role playing games (RPG) are effectively used to understand real thinking and behavior of stakeholders, but RPG is not sufficient to handle a dynamic process like negotiation. In this study, a participatory simulation where user-controlled avatars and autonomous agents coexist is introduced to the participatory approach for modeling negotiation. To establish a modeling methodology of negotiation, we have tackled the following two issues. First, for enabling domain experts to concentrate interaction design for participatory simulation, we have adopted the architecture in which an interaction layer controls agents and have defined three types of interaction descriptions (interaction protocol, interaction scenario and avatar control scenario) to be described. Second, for enabling domain experts and stakeholders to capitalize on participatory simulation, we have established a four-step process for acquiring negotiation model: 1) surveys and interviews to stakeholders, 2) RPG, 3) interaction design, and 4) participatory simulation. Finally, we discussed our methodology through a case study of agricultural economics in the northeast Thailand.
Integrated Modeling to Assess the Impacts of Changes in Climate and Socio Economics on Agriculture in the Columbia River Basin

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Malek, K.; Nelson, R.; Stockle, C.; Brady, M.; Dinesh, S.; Barber, M. E.; Yorgey, G.; Kruger, C.

2012-12-01

The objective of this work is to assess the impacts of climate change and socio economics on agriculture in the Columbia River basin (CRB) in the Pacific Northwest region of the U.S. and a portion of Southwestern Canada. The water resources of the CRB are managed to satisfy multiple objectives including agricultural withdrawal, which is the largest consumptive user of CRB water with 14,000 square kilometers of irrigated area. Agriculture is an important component of the region's economy, with an annual value over 5 billion in Washington State alone. Therefore, the region is relevant for applying a modeling framework that can aid agriculture decision making in the context of a changing climate. To do this, we created an integrated biophysical and socio-economic regional modeling framework that includes human and natural systems. The modeling framework captures the interactions between climate, hydrology, crop growth dynamics, water management and socio economics. The biophysical framework includes a coupled macro-scale physically-based hydrology model (the Variable Infiltration Capacity, VIC model), and crop growth model (CropSyst), as well as a reservoir operations simulation model. Water rights data and instream flow target requirements are also incorporated in the model to simulate the process of curtailment during water shortage. The economics model informs the biophysical model of the short term agricultural producer response to water shortage as well as the long term agricultural producer response to domestic growth and international trade in terms of an altered cropping pattern. The modeling framework was applied over the CRB for the historical period 1976-2006 and compared to a future 30-year period centered on the 2030s. Impacts of climate change on irrigation water availability, crop irrigation demand, frequency of curtailment, and crop yields are quantified and presented. Sensitivity associated with estimates of water availability, irrigation demand, crop yields, unmet demand and available instream flows due to climate inputs, hydrology and crop model parameterization, water management assumptions, model integration assumptions, as well as multiple socio economic alternatives are also presented. Compared to historical conditions, for the 2030s time period, our results show an average additional irrigation water demand requirement of 370 million cubic meters in the CRB, an increased frequency of curtailment and a revenue impact between 70 and $150 million resulting from adverse crop yield impacts due to curtailment in the state of Washington. The impacts vary spatially and some of the CRB tributary watersheds are impacted more than others, e.g., unmet demand in the Yakima River basin is expected to increase by 50%. Increased irrigation demand, coupled with decreased seasonal supply poses difficult water resources management questions in the region.
Evaluation of regional climate simulations for air quality modelling purposes

NASA Astrophysics Data System (ADS)

Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

2013-05-01

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.
An Integrated Decision Support System with Hydrological Processes and Socio-economic Assessments

NASA Astrophysics Data System (ADS)

Yu, Yang; Disse, Markus; Yu, Ruide

2017-04-01

The debate over the effectiveness of Integrated Water Resources Management (IWRM) in practice has lasted for years. As the complexity and scope of IWRM increases, the difficulties of hydrological modeling is shifting from the model itself into the links with other cognate sciences, to understand the interactions among water, earth, ecosystem and humans. This work presents the design and development of a decision support system (DSS) that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use changes. Discharge and glacier geometry changes were simulated with hydrological model WASA. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were integrated as inputs into the DSS in three types of links: regression equations, stationary data inputs, or dynamic data inputs into DSS as the models running parallel in the simulation periods. Within DSS, three types of logics were established: equations, conditional statements and fuzzy logics. The programming was realized in C++. The implementation of DSS takes place in the Tarim River Basin. With the mainstream of 1,321km and located in an arid area in northwest China, the Tarim River is China's longest inland river. The Tarim basin on the northern edge of the Taklamakan desert is an extremely arid region. In this region, agricultural water consumption and allocation management are crucial to address the conflicts among irrigation water users from upstream to downstream. Since 2011, the German Ministry of Science and Education BMBF established the Sino-German SuMaRiO project, for the sustainable management of river oases along the Tarim River. Project SuMaRiO focus on realizable management strategies, considering social, economic and ecological criteria. This will have positive effects for nearly 10 million inhabitants of different ethnic groups. DSS is the main outcome of SuMaRiO. The overall goal of the DSS is to integrate all crucial research results of SuMaRiO, also including stakeholder perspectives, into a model based decision support system, which allows a Sustainability Impact Assessment (SIA) within regional planning. This SIA will take into account the perspectives of all relevant actors in the problem field of land and water management in the Tarim River Basin, to understand ecosystem services (ESS) and integrating them into land and water management. Under scenario assumptions, possible actions and their impacts are estimated in a semi-quantitative way with the help of sustainable indicators, which includes climate indicators, socio-economic Indicators, management Indicators, and ESS Indicators. A user-friendly graphical user interface (GUI) was developed to assist the decision-makers and common users, with Chinese and English versions available at the moment.
The Use of Computer Simulation Gaming in Teaching Broadcast Economics.

ERIC Educational Resources Information Center

Mancuso, Louis C.

The purpose of this study was to develop a broadcast economic computer simulation and to ascertain how a lecture-computer simulation game compared as a teaching method with a more traditional lecture and case study instructional methods. In each of three sections of a broadcast economics course, a different teaching methodology was employed: (1)…
Hydroeconomic DSS for optimal hydrology-oriented forest management in semiarid areas

NASA Astrophysics Data System (ADS)

Garcia-Prats, A.; del Campo, A.; Pulido-Velazquez, M.

2016-12-01

In semiarid regions like the Mediterranean, managing the upper-catchment forests for water provision goals (hydrology-oriented silviculture) offers a strategy to increase the resilience of catchments to droughts and lower precipitation and higher evapotranspiration due to climate change. Understanding the effects of forest management on vegetation water use and groundwater recharge is particularly important in those regions. Despite the essential role that forests play in the water cycle on the provision of water resources, this contribution is often neither quantified nor explicitly valued. The aim of this work is to develop a novel decision support system (DSS) based on hydro-economic modelling, for assessing and designing the optimal integrated forest and water management for forested catchments. Hydro-economic modelling may support the design of economically efficient strategies integrating the hydrologic, engineering, environmental and economic aspects of water resources systems within a coherent framework. The optimization model explicitly integrates changes in water yield (increase n groundwater recharge) induced by the management of forest density, and the value of the additional water provided to the system. This latter component could serve as an indicator for the design of a "payment for environmental services" scheme in which groundwater beneficiaries could contribute towards funding and promoting efficient forest management operations. Besides, revenues from timber logging are also articulated in the modelling. The case study was an Aleppo pine forest in south-western Valencia province (Spain), using a typical 100-year rotation horizon. The model determines the optimal schedule of thinning interventions in the stands in order to maximize the total net benefits in the system (timber and water). Canopy cover and biomass evolution over time were simulated using growth and yield allometric equations specific for the species in Mediterranean conditions. Silvicultural operation costs were modelled using local cost databases. Groundwater recharge was simulated using HYDRUS, calibrated and validated with data from the experimental plots. This research reveal the potential of integrated water and forest policies and encourage their application by governments and policy makers.
Game Theoretic Modeling of Water Resources Allocation Under Hydro-Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Brown, C.; Lall, U.; Siegfried, T.

2005-12-01

Typical hydrologic and economic modeling approaches rely on assumptions of climate stationarity and economic conditions of ideal markets and rational decision-makers. In this study, we incorporate hydroclimatic variability with a game theoretic approach to simulate and evaluate common water allocation paradigms. Game Theory may be particularly appropriate for modeling water allocation decisions. First, a game theoretic approach allows economic analysis in situations where price theory doesn't apply, which is typically the case in water resources where markets are thin, players are few, and rules of exchange are highly constrained by legal or cultural traditions. Previous studies confirm that game theory is applicable to water resources decision problems, yet applications and modeling based on these principles is only rarely observed in the literature. Second, there are numerous existing theoretical and empirical studies of specific games and human behavior that may be applied in the development of predictive water allocation models. With this framework, one can evaluate alternative orderings and rules regarding the fraction of available water that one is allowed to appropriate. Specific attributes of the players involved in water resources management complicate the determination of solutions to game theory models. While an analytical approach will be useful for providing general insights, the variety of preference structures of individual players in a realistic water scenario will likely require a simulation approach. We propose a simulation approach incorporating the rationality, self-interest and equilibrium concepts of game theory with an agent-based modeling framework that allows the distinct properties of each player to be expressed and allows the performance of the system to manifest the integrative effect of these factors. Underlying this framework, we apply a realistic representation of spatio-temporal hydrologic variability and incorporate the impact of decision-making a priori to hydrologic realizations and those made a posteriori on alternative allocation mechanisms. Outcomes are evaluated in terms of water productivity, net social benefit and equity. The performance of hydro-climate prediction modeling in each allocation mechanism will be assessed. Finally, year-to-year system performance and feedback pathways are explored. In this way, the system can be adaptively managed toward equitable and efficient water use.

Optimizing Sustainable Geothermal Heat Extraction

NASA Astrophysics Data System (ADS)

Patel, Iti; Bielicki, Jeffrey; Buscheck, Thomas

2016-04-01

Geothermal heat, though renewable, can be depleted over time if the rate of heat extraction exceeds the natural rate of renewal. As such, the sustainability of a geothermal resource is typically viewed as preserving the energy of the reservoir by weighing heat extraction against renewability. But heat that is extracted from a geothermal reservoir is used to provide a service to society and an economic gain to the provider of that service. For heat extraction used for market commodities, sustainability entails balancing the rate at which the reservoir temperature renews with the rate at which heat is extracted and converted into economic profit. We present a model for managing geothermal resources that combines simulations of geothermal reservoir performance with natural resource economics in order to develop optimal heat mining strategies. Similar optimal control approaches have been developed for managing other renewable resources, like fisheries and forests. We used the Non-isothermal Unsaturated-saturated Flow and Transport (NUFT) model to simulate the performance of a sedimentary geothermal reservoir under a variety of geologic and operational situations. The results of NUFT are integrated into the optimization model to determine the extraction path over time that maximizes the net present profit given the performance of the geothermal resource. Results suggest that the discount rate that is used to calculate the net present value of economic gain is a major determinant of the optimal extraction path, particularly for shallower and cooler reservoirs, where the regeneration of energy due to the natural geothermal heat flux is a smaller percentage of the amount of energy that is extracted from the reservoir.
Seventh symposium on systems analysis in forest resources; 1997 May 28-31; Traverse City, MI.

Treesearch

J. Michael Vasievich; Jeremy S. Fried; Larry A. Leefers

2000-01-01

This international symposium included presentations by representatives from government, academic, and private institutions. Topics covered management objectives; information systems: modeling, optimization, simulation and decision support techniques; spatial methods; timber supply; and economic and operational analyses.
Analysis of longitudinal data from the Puget Sound transportation panel : task E : modal split analysis

DOT National Transportation Integrated Search

1996-11-01

The Highway Economic Requirements System (HERS) is a computer model designed to simulate improvement selection decisions based on the relative benefit-cost merits of alternative improvement options. HERS is intended to estimate national level investm...
A systematic review of models used in cost-effectiveness analyses of preventing osteoporotic fractures.

PubMed

Si, L; Winzenberg, T M; Palmer, A J

2014-01-01

This review was aimed at the evolution of health economic models used in evaluations of clinical approaches aimed at preventing osteoporotic fractures. Models have improved, with medical continuance becoming increasingly recognized as a contributor to health and economic outcomes, as well as advancements in epidemiological data. Model-based health economic evaluation studies are increasingly used to investigate the cost-effectiveness of osteoporotic fracture preventions and treatments. The objective of this study was to carry out a systematic review of the evolution of health economic models used in the evaluation of osteoporotic fracture preventions. Electronic searches within MEDLINE and EMBASE were carried out using a predefined search strategy. Inclusion and exclusion criteria were used to select relevant studies. References listed of included studies were searched to identify any potential study that was not captured in our electronic search. Data on country, interventions, type of fracture prevention, evaluation perspective, type of model, time horizon, fracture sites, expressed costs, types of costs included, and effectiveness measurement were extracted. Seventy-four models were described in 104 publications, of which 69% were European. Earlier models focused mainly on hip, vertebral, and wrist fracture, but later models included multiple fracture sites (humerus, pelvis, tibia, and other fractures). Modeling techniques have evolved from simple decision trees, through deterministic Markov processes to individual patient simulation models accounting for uncertainty in multiple parameters. Treatment continuance has been increasingly taken into account in the models in the last decade. Models have evolved in their complexity and emphasis, with medical continuance becoming increasingly recognized as a contributor to health and economic outcomes. This evolution may be driven in part by the desire to capture all the important differentiating characteristics of medications under scrutiny, as well as the advancement in epidemiological data relevant to osteoporosis fractures.
Complex Dynamics in Nonequilibrium Economics and Chemistry

NASA Astrophysics Data System (ADS)

Wen, Kehong

Complex dynamics provides a new approach in dealing with economic complexity. We study interactively the empirical and theoretical aspects of business cycles. The way of exploring complexity is similar to that in the study of an oscillatory chemical system (BZ system)--a model for modeling complex behavior. We contribute in simulating qualitatively the complex periodic patterns observed from the controlled BZ experiments to narrow the gap between modeling and experiment. The gap between theory and reality is much wider in economics, which involves studies of human expectations and decisions, the essential difference from natural sciences. Our empirical and theoretical studies make substantial progress in closing this gap. With the help from the new development in nonequilibrium physics, i.e., the complex spectral theory, we advance our technique in detecting characteristic time scales from empirical economic data. We obtain correlation resonances, which give oscillating modes with decays for correlation decomposition, from different time series including S&P 500, M2, crude oil spot prices, and GNP. The time scales found are strikingly compatible with business experiences and other studies in business cycles. They reveal the non-Markovian nature of coherent markets. The resonances enhance the evidence of economic chaos obtained by using other tests. The evolving multi-humped distributions produced by the moving-time -window technique reveal the nonequilibrium nature of economic behavior. They reproduce the American economic history of booms and busts. The studies seem to provide a way out of the debate on chaos versus noise and unify the cyclical and stochastic approaches in explaining business fluctuations. Based on these findings and new expectation formulation, we construct a business cycle model which gives qualitatively compatible patterns to those found empirically. The soft-bouncing oscillator model provides a better alternative than the harmonic oscillator or the random walk model as the building block in business cycle theory. The mathematical structure of the model (delay differential equation) is studied analytically and numerically. The research pave the way toward sensible economic forecasting.
Climate Change Impacts for the Conterminous USA: An Integrated Assessment Part 7. Economic Analysis of Field Crops and Land Use with Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sands, Ronald D.; Edmonds, James A.

PNNL's Agriculture and Land Use (AgLU) model is used to demonstrate the impact of potential changes in climate on agricultural production and land use in the United States. AgLU simulates production of four crop types in several world regions, in 15-year time steps from 1990 to 2095. Changes in yield of major field crops in the United States, for 12 climate scenarios, are obtained from simulations of the EPIC crop growth model. Results from the HUMUS model are used to constrain crop irrigation, and the BIOME3 model is used to simulate productivity of unmanaged ecosystems. Assumptions about changes in agriculturalmore » productivity outside the United States are treated on a scenario basis, either responding in the same way as in the United States, or not responding to climate.« less
ECUT (Energy Conversion and Utilization Technologies Program). Biocatalysis Project

NASA Technical Reports Server (NTRS)

1986-01-01

Presented are the FY 1985 accomplishments, activities, and planned research efforts of the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Program. The Project's technical activities were organized as follows: In the Molecular Modeling and Applied Genetics work element, research focused on (1) modeling and simulation studies to establish the physiological basis of high temperature tolerance in a selected enzyme and the catalytic mechanisms of three species of another enzyme, and (2) determining the degree of plasmid amplification and stability of several DNA bacterial strains. In the Bioprocess Engineering work element, research focused on (1) studies of plasmid propagation and the generation of models, (2) developing methods for preparing immobilized biocatalyst beads, and (3) developing an enzyme encapsulation method. In the Process Design and Analysis work element, research focused on (1) further refinement of a test case simulation of the economics and energy efficiency of alternative biocatalyzed production processes, (2) developing a candidate bioprocess to determine the potential for reduced energy consumption and facility/operating costs, and (3) a techno-economic assessment of potential advancements in microbial ammonia production.
Enhancement of urban heat load through social inequalities on an example of a fictional city King's Landing.

PubMed

Žuvela-Aloise, M

2017-03-01

The numerical model MUKLIMO_3 is used to simulate the urban climate of an imaginary city as an illustrative example to demonstrate that the residential areas with deprived socio-economic conditions can exhibit an enhanced heat load at night, and thus more disadvantageous environmental conditions, compared with the areas of higher socio-economic status. The urban climate modelling simulations differentiate between orographic, natural landscape, building and social effects, where social differences are introduced by selection of location, building type and amount of vegetation. The model results show that the increase of heat load can be found in the areas inhabited by the poor population as a combined effect of natural and anthropogenic factors. The unfavourable location in the city and the building type, consisting of high density, low housing with high fraction of pavement and small amount of vegetation contribute to the formation of excessive heat load. This abstract example shows that the enhancement of urban heat load can be linked to the concept of a socially stratified city and is independent of the historical development of any specific city.
Enhancement of urban heat load through social inequalities on an example of a fictional city King's Landing

NASA Astrophysics Data System (ADS)

Žuvela-Aloise, M.

2017-03-01

The numerical model MUKLIMO_3 is used to simulate the urban climate of an imaginary city as an illustrative example to demonstrate that the residential areas with deprived socio-economic conditions can exhibit an enhanced heat load at night, and thus more disadvantageous environmental conditions, compared with the areas of higher socio-economic status. The urban climate modelling simulations differentiate between orographic, natural landscape, building and social effects, where social differences are introduced by selection of location, building type and amount of vegetation. The model results show that the increase of heat load can be found in the areas inhabited by the poor population as a combined effect of natural and anthropogenic factors. The unfavourable location in the city and the building type, consisting of high density, low housing with high fraction of pavement and small amount of vegetation contribute to the formation of excessive heat load. This abstract example shows that the enhancement of urban heat load can be linked to the concept of a socially stratified city and is independent of the historical development of any specific city.
Assessment of extreme flood events in a changing climate for a long-term planning of socio-economic infrastructure in the Russian Arctic

NASA Astrophysics Data System (ADS)

Shevnina, Elena; Kourzeneva, Ekaterina; Kovalenko, Viktor; Vihma, Timo

2017-05-01

Climate warming has been more acute in the Arctic than at lower latitudes and this tendency is expected to continue. This generates major challenges for economic activity in the region. Among other issues is the long-term planning and development of socio-economic infrastructure (dams, bridges, roads, etc.), which require climate-based forecasts of the frequency and magnitude of detrimental flood events. To estimate the cost of the infrastructure and operational risk, a probabilistic form of long-term forecasting is preferable. In this study, a probabilistic model to simulate the parameters of the probability density function (PDF) for multi-year runoff based on a projected climatology is applied to evaluate changes in extreme floods for the territory of the Russian Arctic. The model is validated by cross-comparison of the modelled and empirical PDFs using observations from 23 sites located in northern Russia. The mean values and coefficients of variation (CVs) of the spring flood depth of runoff are evaluated under four climate scenarios, using simulations of six climate models for the period 2010-2039. Regions with substantial expected changes in the means and CVs of spring flood depth of runoff are outlined. For the sites located within such regions, it is suggested to account for the future climate change in calculating the maximal discharges of rare occurrence. An example of engineering calculations for maximal discharges with 1 % exceedance probability is provided for the Nadym River at Nadym.
A systematic and critical review of model-based economic evaluations of pharmacotherapeutics in patients with bipolar disorder.

PubMed

Mohiuddin, Syed

2014-08-01

Bipolar disorder (BD) is a chronic and relapsing mental illness with a considerable health-related and economic burden. The primary goal of pharmacotherapeutics for BD is to improve patients' well-being. The use of decision-analytic models is key in assessing the added value of the pharmacotherapeutics aimed at treating the illness, but concerns have been expressed about the appropriateness of different modelling techniques and about the transparency in the reporting of economic evaluations. This paper aimed to identify and critically appraise published model-based economic evaluations of pharmacotherapeutics in BD patients. A systematic review combining common terms for BD and economic evaluation was conducted in MEDLINE, EMBASE, PSYCINFO and ECONLIT. Studies identified were summarised and critically appraised in terms of the use of modelling technique, model structure and data sources. Considering the prognosis and management of BD, the possible benefits and limitations of each modelling technique are discussed. Fourteen studies were identified using model-based economic evaluations of pharmacotherapeutics in BD patients. Of these 14 studies, nine used Markov, three used discrete-event simulation (DES) and two used decision-tree models. Most of the studies (n = 11) did not include the rationale for the choice of modelling technique undertaken. Half of the studies did not include the risk of mortality. Surprisingly, no study considered the risk of having a mixed bipolar episode. This review identified various modelling issues that could potentially reduce the comparability of one pharmacotherapeutic intervention with another. Better use and reporting of the modelling techniques in the future studies are essential. DES modelling appears to be a flexible and comprehensive technique for evaluating the comparability of BD treatment options because of its greater flexibility of depicting the disease progression over time. However, depending on the research question, modelling techniques other than DES might also be appropriate in some cases.
An economic decision-making support system for selection of reproductive management programs on dairy farms.

PubMed

Giordano, J O; Fricke, P M; Wiltbank, M C; Cabrera, V E

2011-12-01

Because the reproductive performance of lactating dairy cows influences the profitability of dairy operations, predicting the future reproductive and economic performance of dairy herds through decision support systems would be valuable to dairy producers and consultants. In this study, we present a highly adaptable tool created based on a mathematical model combining Markov chain simulation with partial budgeting to obtain the net present value (NPV; $/cow per year) of different reproductive management programs. The growing complexity of reproductive programs used by dairy farms demands that new decision support systems precisely reflect the events that occur on the farm. Therefore, the model requires productive, reproductive, and economic input data used for simulation of farm conditions to account for all factors related to reproductive management that increase costs and generate revenue. The economic performance of 3 different reproductive programs can be simultaneously compared with the current model. A program utilizing 100% visual estrous detection (ED) for artificial insemination (AI) is used as a baseline for comparison with 2 other programs that may include 100% timed AI (TAI) as well as any combination of TAI and ED. A case study is presented in which the model was used to compare 3 different reproductive management strategies (100% ED baseline compared with two 100% TAI options) using data from a commercial farm in Wisconsin. Sensitivity analysis was then used to assess the effect of varying specific reproductive parameters on the NPV. Under the simulated conditions of the case study, the model indicated that the two 100% TAI programs were superior to the 100% ED program and, of the 100% TAI programs, the one with the higher conception rate (CR) for resynchronized AI services was economically superior despite having higher costs and a longer interbreeding interval. A 4% increase in CR for resynchronized AI was sufficient for the inferior 100% TAI to outperform the superior program. Adding ED to the 100% TAI programs was only beneficial for the program with the lower CR. The improvement in service rate required for the 100% ED program to have the same NPV as the superior 100% TAI program was 12%. The decision support system developed in this study is a valuable tool that may be used to assist dairy producers and industry consultants in selecting the best farm-specific reproductive management strategy. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Integrated Earth System Model (iESM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thornton, Peter Edmond; Mao, Jiafu; Shi, Xiaoying

2016-12-02

The iESM is a simulation code that represents the physical and biological aspects of Earth's climate system, and also includes the macro-economic and demographic properties of human societies. The human aspect of the simulation code is focused in particular on the effects of human activities on land use and land cover change, but also includes aspects such as energy economies. The time frame for predictions with iESM is approximately 1970 through 2100.
Communicating Value in Simulation: Cost Benefit Analysis and Return on Investment.

PubMed

Asche, Carl V; Kim, Minchul; Brown, Alisha; Golden, Antoinette; Laack, Torrey A; Rosario, Javier; Strother, Christopher; Totten, Vicken Y; Okuda, Yasuharu

2017-10-26

Value-based health care requires a balancing of medical outcomes with economic value. Administrators need to understand both the clinical and economic effects of potentially expensive simulation programs to rationalize the costs. Given the often-disparate priorities of clinical educators relative to health care administrators, justifying the value of simulation requires the use of economic analyses few physicians have been trained to conduct. Clinical educators need to be able to present thorough economic analyses demonstrating returns on investment and cost effectiveness to effectively communicate with administrators. At the 2017 Academic Emergency Medicine Consensus Conference "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes", our breakout session critically evaluated the cost benefit and return on investment of simulation. In this paper we provide an overview of some of the economic tools that a clinician may use to present the value of simulation training to financial officers and other administrators in the economic terms they understand. We also define three themes as a call to action for research related to cost benefit analysis in simulation as well as four specific research questions that will help guide educators and hospital leadership to make decisions on the value of simulation for their system or program. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Large Scale Simulation Platform for NODES Validation Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sotorrio, P.; Qin, Y.; Min, L.

2017-04-27

This report summarizes the Large Scale (LS) simulation platform created for the Eaton NODES project. The simulation environment consists of both wholesale market simulator and distribution simulator and includes the CAISO wholesale market model and a PG&E footprint of 25-75 feeders to validate the scalability under a scenario of 33% RPS in California with additional 17% of DERS coming from distribution and customers. The simulator can generate hourly unit commitment, 5-minute economic dispatch, and 4-second AGC regulation signals. The simulator is also capable of simulating greater than 10k individual controllable devices. Simulated DERs include water heaters, EVs, residential and lightmore » commercial HVAC/buildings, and residential-level battery storage. Feeder-level voltage regulators and capacitor banks are also simulated for feeder-level real and reactive power management and Vol/Var control.« less
Spatial and Temporal Self-Calibration of a Hydroeconomic Model

NASA Astrophysics Data System (ADS)

Howitt, R. E.; Hansen, K. M.

2008-12-01

Hydroeconomic modeling of water systems where risk and reliability of water supply are of critical importance must address explicitly how to model water supply uncertainty. When large fluctuations in annual precipitation and significant variation in flows by location are present, a model which solves with perfect foresight of future water conditions may be inappropriate for some policy and research questions. We construct a simulation-optimization model with limited foresight of future water conditions using positive mathematical programming and self-calibration techniques. This limited foresight netflow (LFN) model signals the value of storing water for future use and reflects a more accurate economic value of water at key locations, given that future water conditions are unknown. Failure to explicitly model this uncertainty could lead to undervaluation of storage infrastructure and contractual mechanisms for managing water supply risk. A model based on sequentially updated information is more realistic, since water managers make annual storage decisions without knowledge of yet to be realized future water conditions. The LFN model runs historical hydrological conditions through the current configuration of the California water system to determine the economically efficient allocation of water under current economic conditions and infrastructure. The model utilizes current urban and agricultural demands, storage and conveyance infrastructure, and the state's hydrological history to indicate the scarcity value of water at key locations within the state. Further, the temporal calibration penalty functions vary by year type, reflecting agricultural water users' ability to alter cropping patterns in response to water conditions. The model employs techniques from positive mathematical programming (Howitt, 1995; Howitt, 1998; Cai and Wang, 2006) to generate penalty functions that are applied to deviations from observed data. The functions are applied to monthly flows across key nodes on the network and to annual carryover storage at ground and surface water storage facilities. To our knowledge, this is the first hydroeconomic model to perform spatial and temporal calibration simultaneously. The base for the LFN model is CALVIN, a hydroeconomic optimization model of the California water system developed at the University of California, Davis (Draper, et al. 2003). The LFN model, programmed in GAMS, is nonlinear, which permits incorporation of dynamic groundwater pumping costs that reflect head elevation. Hydropower production, also nonlinear in storage levels, could be added in the future. In this paper, we describe model implementation and performance over a sequence of water years drawn from the historical hydrologic record in California. Preliminary findings indicate that calibration occurs within acceptable limits and simulations replicate base case results well. Cai, X., and Wang, D. 2006. "Calibrating Holistic Water Resources-Economic Models." Journal of Water Resources Planning and Management November-December. Draper, A.J., M.W. Jenkins, K.W. Kirby, J.R. Lund, and R.E. Howitt. 2003. "Economic-Engineering Optimization for California Water Management." Journal of Water Resources Planning and Management 129(3):155-164. Howitt, R.E. 1995. "Positive Mathematical Programming." American Journal of Agricultural Economics 77:329-342. Howitt, R.E. 1998. "Self-Calibrating Network Flow Models." Working Paper, Department of Agricultural and Resource Economics, University of California, Davis. October 1998. class="ab'>
Economic Dispatch for Microgrid Containing Electric Vehicles via Probabilistic Modeling: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Yin; Gao, Wenzhong; Momoh, James

In this paper, an economic dispatch model with probabilistic modeling is developed for a microgrid. The electric power supply in a microgrid consists of conventional power plants and renewable energy power plants, such as wind and solar power plants. Because of the fluctuation in the output of solar and wind power plants, an empirical probabilistic model is developed to predict their hourly output. According to different characteristics of wind and solar power plants, the parameters for probabilistic distribution are further adjusted individually for both. On the other hand, with the growing trend in plug-in electric vehicles (PHEVs), an integrated microgridmore » system must also consider the impact of PHEVs. The charging loads from PHEVs as well as the discharging output via the vehicle-to-grid (V2G) method can greatly affect the economic dispatch for all of the micro energy sources in a microgrid. This paper presents an optimization method for economic dispatch in a microgrid considering conventional power plants, renewable power plants, and PHEVs. The simulation results reveal that PHEVs with V2G capability can be an indispensable supplement in a modern microgrid.« less
Analytical Problems and Suggestions in the Analysis of Behavioral Economic Demand Curves.

PubMed

Yu, Jihnhee; Liu, Liu; Collins, R Lorraine; Vincent, Paula C; Epstein, Leonard H

2014-01-01

Behavioral economic demand curves (Hursh, Raslear, Shurtleff, Bauman, & Simmons, 1988) are innovative approaches to characterize the relationships between consumption of a substance and its price. In this article, we investigate common analytical issues in the use of behavioral economic demand curves, which can cause inconsistent interpretations of demand curves, and then we provide methodological suggestions to address those analytical issues. We first demonstrate that log transformation with different added values for handling zeros changes model parameter estimates dramatically. Second, demand curves are often analyzed using an overparameterized model that results in an inefficient use of the available data and a lack of assessment of the variability among individuals. To address these issues, we apply a nonlinear mixed effects model based on multivariate error structures that has not been used previously to analyze behavioral economic demand curves in the literature. We also propose analytical formulas for the relevant standard errors of derived values such as P max, O max, and elasticity. The proposed model stabilizes the derived values regardless of using different added increments and provides substantially smaller standard errors. We illustrate the data analysis procedure using data from a relative reinforcement efficacy study of simulated marijuana purchasing.
Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU

PubMed Central

Xia, Yong; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations. PMID:26581957
Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU.

PubMed

Xia, Yong; Wang, Kuanquan; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations.

Effect of fertility on the economics of pasture-based dairy systems.

PubMed

Shalloo, L; Cromie, A; McHugh, N

2014-05-01

There are significant costs associated with reproductive inefficiency in pasture-based dairy herds. This study has quantified the economic effect of a number of key variables associated with reproductive inefficiency in a dairy herd and related them to 6-week calving rate for both cows and heifers. These variables include: increased culling costs, the effects of sub optimum calving dates, increased labour costs and increased artificial insemination (AI) and intervention costs. The Moorepark Dairy Systems Model which is a stochastic budgetary simulation model was used to simulate the overall economic effect at farm level. The effect of change in each of the components was simulated in the model and the costs associated with each component was quantified. An analysis of national data across a 4-year period using the Irish Cattle Breeding Federation database was used to quantify the relationship between the 6-week calving rate of a herd with survivability (%), calving interval (days) and the level of AI usage. The costs associated with increased culling (%), calving date slippage (day), increased AI and intervention costs (0.1 additional inseminations), as well as, increased labour costs (10%) were quantified as €13.68, €3.86, €4.56 and €29.6/cow per year. There was a statistically significant association between the 6-week calving rate and survivability, calving interval and AI usage at farm level. A 1% change in 6-week calving rate was associated with €9.26/cow per annum for cows and €3.51/heifer per annum for heifers. This study does not include the indirect costs such as reduced potential for expansion, increased costs associated with failing to maintain a closed herd as well as the unrealised potential within the herd.
Simulation and experimental research of 1MWe solar tower power plant in China

NASA Astrophysics Data System (ADS)

Yu, Qiang; Wang, Zhifeng; Xu, Ershu

2016-05-01

The establishment of a reliable simulation system for a solar tower power plant can greatly increase the economic and safety performance of the whole system. In this paper, a dynamic model of the 1MWe Solar Tower Power Plant at Badaling in Beijing is developed based on the "STAR-90" simulation platform, including the heliostat field, the central receiver system (water/steam), etc. The dynamic behavior of the global CSP plant can be simulated. In order to verify the validity of simulation system, a complete experimental process was synchronously simulated by repeating the same operating steps based on the simulation platform, including the locations and number of heliostats, the mass flow of the feed water, etc. According to the simulation and experimental results, some important parameters are taken out to make a deep comparison. The results show that there is good alignment between the simulations and the experimental results and that the error range can be acceptable considering the error of the models. In the end, a comprehensive and deep analysis on the error source is carried out according to the comparative results.
Addition of meloxicam to the treatment of bovine clinical mastitis results in a net economic benefit to the dairy farmer.

PubMed

van Soest, Felix J S; Abbeloos, Elke; McDougall, Scott; Hogeveen, Henk

2018-04-01

Recently, it has been shown that the addition of meloxicam to standard antimicrobial therapy for clinical mastitis (CM) improves the conception rate of dairy cows contracting CM in the first 120 d in milk. The objective of our study was to assess whether this improved reproduction through additional treatment with meloxicam would result in a positive net economic benefit for the farmer. We developed a stochastic bio-economic simulation model, in which a dairy cow with CM in the first 120 d in milk was simulated. Two scenarios were simulated in which CM cases were treated with meloxicam in conjunction with antimicrobial therapy or with antimicrobial therapy alone. The scenarios differed for conception rates (31% with meloxicam or 21% without meloxicam) and for the cost of CM treatment. Sensitivity analyses were undertaken for the biological and economic components of the model to assess the effects of a wide range of inputs on inferences about the cost effectiveness of meloxicam treatment. Model results showed an average net economic benefit of €42 per CM case per year in favor of the meloxicam scenario. Cows in the no-meloxicam treatment scenario had higher returns on milk production, lower costs upon calving, and reduced costs of treatment. However, these did not outweigh the savings associated with lower feed intake, reduced number of inseminations, and the reduced culling rate. The net economic benefit favoring meloxicam therapy was a consequence of the better reproductive performance in the meloxicam scenario in which cows had a shorter calving to conception interval (132 vs. 143 d), a shorter intercalving interval (405 vs. 416 d), and fewer inseminations per conception (2.9 vs. 3.7) compared with cows in the no-meloxicam treatment scenario. This resulted in a shorter lactation, hence a lower lactational milk production (8,441 vs. 8,517 kg per lactation) with lower feeding costs in the meloxicam group. A lower culling rate (12 vs. 25%) resulted in lower replacement costs in the meloxicam treatment scenario. All of the scenarios evaluated in the sensitivity analyses favored meloxicam treatment over no meloxicam. This study demonstrated that improvements in conception rate achieved by the use of meloxicam, as additional therapy for mild to moderate CM in the first 120 d in milk, have positive economic benefits. This inference remained true over a wide range of technical and economic inputs, demonstrating that use of meloxicam is likely to be cost effective across many production systems. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
An economic model of friendship and enmity for measuring social balance in networks

NASA Astrophysics Data System (ADS)

Lee, Kyu-Min; Shin, Euncheol; You, Seungil

2017-12-01

We propose a dynamic economic model of networks where agents can be friends or enemies with one another. This is a decentralized relationship model in that agents decide whether to change their relationships so as to minimize their imbalanced triads. In this model, there is a single parameter, which we call social temperature, that captures the degree to which agents care about social balance in their relationships. We show that the global structure of relationship configuration converges to a unique stationary distribution. Using this stationary distribution, we characterize the maximum likelihood estimator of the social temperature parameter. Since the estimator is computationally challenging to calculate from real social network datasets, we provide a simple simulation algorithm and verify its performance with real social network datasets.
Can hydro-economic river basin models simulate water shadow prices under asymmetric access?

PubMed

Kuhn, A; Britz, W

2012-01-01

Hydro-economic river basin models (HERBM) based on mathematical programming are conventionally formulated as explicit 'aggregate optimization' problems with a single, aggregate objective function. Often unintended, this format implicitly assumes that decisions on water allocation are made via central planning or functioning markets such as to maximize social welfare. In the absence of perfect water markets, however, individually optimal decisions by water users will differ from the social optimum. Classical aggregate HERBMs cannot simulate that situation and thus might be unable to describe existing institutions governing access to water and might produce biased results for alternative ones. We propose a new solution format for HERBMs, based on the format of the mixed complementarity problem (MCP), where modified shadow price relations express spatial externalities resulting from asymmetric access to water use. This new problem format, as opposed to commonly used linear (LP) or non-linear programming (NLP) approaches, enables the simultaneous simulation of numerous 'independent optimization' decisions by multiple water users while maintaining physical interdependences based on water use and flow in the river basin. We show that the alternative problem format allows the formulation HERBMs that yield more realistic results when comparing different water management institutions.
Using the Monopoly[R] Board Game as an In-Class Economic Simulation in the Introductory Financial Accounting Course

ERIC Educational Resources Information Center

Shanklin, Stephen B.; Ehlen, Craig R.

2007-01-01

This paper discusses using the Monopoly[R] board game as an economic simulation exercise to reinforce an understanding of how the accounting cycle impacts financial statements used to evaluate management performance. This approach uses the rules and strategies of a familiar board game to create a simulation of business and economic realities,…
[Development of APSIM (agricultural production systems simulator) and its application].

PubMed

Shen, Yuying; Nan, Zhibiao; Bellotti, Bill; Robertson, Michael; Chen, Wen; Shao, Xinqing

2002-08-01

Soil-crop simulator model is an effective tool for providing decision on agricultural management. APSIM (Agricultural Production Systems Simulator) was developed to simulate the biophysical process in farming system, and particularly in the economic and ecological features of the systems under climatic risk. The current literatures revealed that APSIM could be applied in wide zone, including temperate continental, temperate maritime, sub-tropic and arid climate, and Mediterranean climates, with the soil type of clay, duplex soil, vertisol, silt sandy, silt loam and silt clay loam. More than 20 crops have been simulated well. APSIM is powerful on describing crop structure, crop sequence, yield prediction, and quality control as well as erosion estimation under different planting pattern.
The ScanTrainer obstetrics and gynaecology ultrasound virtual reality training simulator: A cost model to determine the cost viability of replacing clinical training with simulation training.

PubMed

Carolan-Rees, G; Ray, A F

2015-05-01

The aim of this study was to produce an economic cost model comparing the use of the Medaphor ScanTrainer virtual reality training simulator for obstetrics and gynaecology ultrasound to achieve basic competence, with the traditional training method. A literature search and survey of expert opinion were used to identify resources used in training. An executable model was produced in Excel. The model showed a cost saving for a clinic using the ScanTrainer of £7114 per annum. The uncertainties of the model were explored and it was found to be robust. Threshold values for the key drivers of the model were identified. Using the ScanTrainer is cost saving for clinics with at least two trainees per year to train, if it would take at least six lists to train them using the traditional training method and if a traditional training list has at least two fewer patients than a standard list.
Avoiding chaos in Wonderland

NASA Astrophysics Data System (ADS)

Kohring, G. A.

2006-08-01

Wonderland, a compact, integrated economic, demographic and environmental model, is investigated using methods developed for studying critical phenomena. Simulation results show the parameter space separates into two phases, one of which contains the property of long term, sustainable development. By employing information contain in the phase diagram, an optimal strategy involving pollution taxes is developed as a means of moving a system initially in a unsustainable region of the phase diagram into a region of sustainability while ensuring minimal regret with respect to long-term economic growth.
Institutional Transformation Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-10-19

Reducing the energy consumption of large institutions with dozens to hundreds of existing buildings while maintaining and improving existing infrastructure is a critical economic and environmental challenge. SNL's Institutional Transformation (IX) work integrates facilities and infrastructure sustainability technology capabilities and collaborative decision support modeling approaches to help facilities managers at Sandia National Laboratories (SNL) simulate different future energy reduction strategies and meet long term energy conservation goals.
Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

NASA Astrophysics Data System (ADS)

Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali

2013-04-01

This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.
SimLife a new model of simulation using a pulsated revascularized and reventilated cadaver for surgical education.

PubMed

Delpech, P O; Danion, J; Oriot, D; Richer, J P; Breque, C; Faure, J P

2017-02-01

Alike becoming a pilot requires competences, acquisition of technical skills is essential to become a surgeon. Halsted's theory on surgical education "See one, do one, and teach one" is not currently compatible with the reality of socio-economic constraints of the operating room, the patient's safety demand and the reduction of residents' work hours. In all countries, this brings mandatory to simulation education for surgery resident's training. Many models are available: video trainers or pelvi-trainers, computed simulator, animal models or human cadaver… Human cadaveric dissection has long been used to teach surgical anatomy. Surgery on human cadaveric model brings greatest accuracy to the haptic characteristics of surgical procedures. Learning in an appropriate and realistic simulation context increases the level of acquisition of the residents' skills and reduces stress and anxiety when performing real procedures. We present a technique of perfusion and ventilation of a fresh human cadaver that restores pulsatile circulation and respiratory movements of the model. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
The contribution of future agricultural trends in the US Midwest to global climate change mitigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomson, Allison M.; Kyle, G. Page; Zhang, Xuesong

2014-01-19

Land use change is a complex response to changing environmental and socioeconomic systems. Historical drivers of land use change include changes in the natural resource availability of a region, changes in economic conditions for production of certain products and changing policies. Most recently, introduction of policy incentives for biofuel production have influenced land use change in the US Midwest, leading to concerns that bioenergy production systems may compete with food production and land conservation. Here we explore how land use may be impacted by future climate mitigation measures by nesting a high resolution agricultural model (EPIC – Environmental Policy Indicatormore » Climate) for the US Midwest within a global integrated assessment model (GCAM – Global Change Assessment Model). This approach is designed to provide greater spatial resolution and detailed agricultural practice information by focusing on the climate mitigation potential of agriculture and land use in a specific region, while retaining the global economic context necessary to understand the far ranging effects of climate mitigation targets. We find that until the simulated carbon prices are very high, the US Midwest has a comparative advantage in producing traditional food and feed crops over bioenergy crops. Overall, the model responds to multiple pressures by adopting a mix of future responses. We also find that the GCAM model is capable of simulations at multiple spatial scales and agricultural technology resolution, which provides the capability to examine regional response to global policy and economic conditions in the context of climate mitigation.« less
Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.
Conversion of bioprocess ethanol to industrial chemical products - Applications of process models for energy-economic assessments

NASA Technical Reports Server (NTRS)

Rohatgi, Naresh K.; Ingham, John D.

1992-01-01

An assessment approach for accurate evaluation of bioprocesses for large-scale production of industrial chemicals is presented. Detailed energy-economic assessments of a potential esterification process were performed, where ethanol vapor in the presence of water from a bioreactor is catalytically converted to ethyl acetate. Results show that such processes are likely to become more competitive as the cost of substrates decreases relative to petrolium costs. A commercial ASPEN process simulation provided a reasonably consistent comparison with energy economics calculated using JPL developed software. Detailed evaluations of the sensitivity of production cost to material costs and annual production rates are discussed.
Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, Johanna; Fürnkranz-Prskawetz, Alexia; Grass, Dieter; Viglione, Alberto; Blöschl, Günter

2016-04-01

Recently socio-hydrology models have been proposed to analyze the interplay of community risk-coping culture, flooding damage and economic growth. These models descriptively explain the feedbacks between socio-economic development and natural disasters such as floods. Complementary to these descriptive models, we develop a dynamic optimization model, where the inter-temporal decision of an economic agent interacts with the hydrological system. This interdisciplinary approach matches with the goals of Panta Rhei i.e. to understand feedbacks between hydrology and society. It enables new perspectives but also shows limitations of each discipline. Young scientists need mentors from various scientific backgrounds to learn their different research approaches and how to best combine them such that interdisciplinary scientific work is also accepted by different science communities. In our socio-hydrology model we apply a macro-economic decision framework to a long-term flood-scenario. We assume a standard macro-economic growth model where agents derive utility from consumption and output depends on physical capital that can be accumulated through investment. To this framework we add the occurrence of flooding events which will destroy part of the capital. We identify two specific periodic long term solutions and denote them rich and poor economies. Whereas rich economies can afford to invest in flood defense and therefore avoid flood damage and develop high living standards, poor economies prefer consumption instead of investing in flood defense capital and end up facing flood damages every time the water level rises. Nevertheless, they manage to sustain at least a low level of physical capital. We identify optimal investment strategies and compare simulations with more frequent and more intense high water level events.
Simulation model for wind energy storage systems. Volume II. Operation manual. [SIMWEST code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren, A.W.; Edsinger, R.W.; Burroughs, J.D.

1977-08-01

The effort developed a comprehensive computer program for the modeling of wind energy/storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic). An acronym for the program is SIMWEST (Simulation Model for Wind Energy Storage). The level of detail of SIMWEST is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. Volume II, the SIMWEST operation manual, describes the usage of the SIMWEST program, the designmore » of the library components, and a number of simple example simulations intended to familiarize the user with the program's operation. Volume II also contains a listing of each SIMWEST library subroutine.« less
Fertility, Human Capital, and Economic Growth over the Demographic Transition

PubMed Central

Mason, Andrew

2009-01-01

Do low fertility and population aging lead to economic decline if couples have fewer children, but invest more in each child? By addressing this question, this article extends previous work in which the authors show that population aging leads to an increased demand for wealth that can, under some conditions, lead to increased capital per worker and higher per capita consumption. This article is based on an overlapping generations (OLG) model which highlights the quantity–quality tradeoff and the links between human capital investment and economic growth. It incorporates new national level estimates of human capital investment produced by the National Transfer Accounts project. Simulation analysis is employed to show that, even in the absence of the capital dilution effect, low fertility leads to higher per capita consumption through human capital accumulation, given plausible model parameters. PMID:20495605
Economic resilience through "One-Water" management

USGS Publications Warehouse

Hanson, Randall T.; Schmid, Wolfgang

2013-01-01

Disruption of water availability leads to food scarcity and loss of economic opportunity. Development of effective water-resource policies and management strategies could provide resiliance to local economies in the face of water disruptions such as drought, flood, and climate change. To accomplish this, a detailed understanding of human water use and natural water resource availability is needed. A hydrologic model is a computer software system that simulates the movement and use of water in a geographic area. It takes into account all components of the water cycle--“One Water”--and helps estimate water budgets for groundwater, surface water, and landscape features. The U.S. Geological Survey MODFLOW One-Water Integrated Hydrologic Model (MODFLOWOWHM) software and scientific methods can provide water managers and political leaders with hydrologic information they need to help ensure water security and economic resilience.
Analysis and Design of International Emission Trading Markets Applying System Dynamics Techniques

NASA Astrophysics Data System (ADS)

Hu, Bo; Pickl, Stefan

2010-11-01

The design and analysis of international emission trading markets is an important actual challenge. Time-discrete models are needed to understand and optimize these procedures. We give an introduction into this scientific area and present actual modeling approaches. Furthermore, we develop a model which is embedded in a holistic problem solution. Measures for energy efficiency are characterized. The economic time-discrete "cap-and-trade" mechanism is influenced by various underlying anticipatory effects. With a systematic dynamic approach the effects can be examined. First numerical results show that fair international emissions trading can only be conducted with the use of protective export duties. Furthermore a comparatively high price which evokes emission reduction inevitably has an inhibiting effect on economic growth according to our model. As it always has been expected it is not without difficulty to find a balance between economic growth and emission reduction. It can be anticipated using our System Dynamics model simulation that substantial changes must be taken place before international emissions trading markets can contribute to global GHG emissions mitigation.

Economic Analysis of an Integrated Annatto Seeds-Sugarcane Biorefinery Using Supercritical CO2 Extraction as a First Step

PubMed Central

Albarelli, Juliana Q.; Santos, Diego T.; Cocero, María José; Meireles, M. Angela A.

2016-01-01

Recently, supercritical fluid extraction (SFE) has been indicated to be utilized as part of a biorefinery, rather than as a stand-alone technology, since besides extracting added value compounds selectively it has been shown to have a positive effect on the downstream processing of biomass. To this extent, this work evaluates economically the encouraging experimental results regarding the use of SFE during annatto seeds valorization. Additionally, other features were discussed such as the benefits of enhancing the bioactive compounds concentration through physical processes and of integrating the proposed annatto seeds biorefinery to a hypothetical sugarcane biorefinery, which produces its essential inputs, e.g., CO2, ethanol, heat and electricity. For this, first, different configurations were modeled and simulated using the commercial simulator Aspen Plus® to determine the mass and energy balances. Next, each configuration was economically assessed using MATLAB. SFE proved to be decisive to the economic feasibility of the proposed annatto seeds-sugarcane biorefinery concept. SFE pretreatment associated with sequential fine particles separation process enabled higher bixin-rich extract production using low-pressure solvent extraction method employing ethanol, meanwhile tocotrienols-rich extract is obtained as a first product. Nevertheless, the economic evaluation showed that increasing tocotrienols-rich extract production has a more pronounced positive impact on the economic viability of the concept. PMID:28773616
TRIPLE-VALUE SIMULATION MODELING CASES TACKLE NUTRIENT AND WATERSHED MANAGEMENT FROM A SOCIAL-ECOLOGICAL SYSTEMS PERSPECTIVE

EPA Science Inventory

Decision makers often need assistance in understanding dynamic interactions and linkages among economic, environmental and social systems in coastal watersheds. They also need scientific input to better evaluate potential costs and benefits of alternative policy interventions. EP...
Groundwater economics: An object-oriented foundation for integrated studies of irrigated agricultural systems

USDA-ARS?s Scientific Manuscript database

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater we...
Simulation for assessment of bulk cargo berths number

NASA Astrophysics Data System (ADS)

Kuznetsov, A. L.; Kirichenko, A. V.; Slitsan, A. E.

2017-10-01

The world trade volumes of mineral resources have been growing constantly for decades, notwithstanding any economical crises. At the same time, the proximity of the bulk materials as products to the starting point of the integrated value added or logistic supply chain makes their unit price relatively low. This fact automatically causes a strong economic sensitivity of the supply chain to the level of operational expenses in every link. The core of the integrated logistic supply chain is its maritime segment, with the fleet and terminals (i.e. the cargo transportation system) serving as the base platform for it. In its turn, the terminal berths play a role of the interface between the fleet and the land-transportation sub-system. Current development of the maritime transportation technologies, ships and terminal specialization, vessel size growth, rationalization of route patterns, regionalization of trade etc., has made conventional calculation methods inadequate. The solution of the problem is in using object oriented simulation. At the same time, this approch usually assumes only ad hoc models. Thus, it does not provide the generality of its conventional analytical predecessors. The time and labor consumpting procedure of simulation results in a very narrow application domain of the model. This article describes a new simulation instrument, combining the generality of the analytical technoques with the efficiency of the object-oriented simulation. The approach implemented as a software module, which validity and adequacy are proved. The software was tested on several sea terminal design projects and confirmed its efficiency.
Multispectral system analysis through modeling and simulation

NASA Technical Reports Server (NTRS)

Malila, W. A.; Gleason, J. M.; Cicone, R. C.

1977-01-01

The design and development of multispectral remote sensor systems and associated information extraction techniques should be optimized under the physical and economic constraints encountered and yet be effective over a wide range of scene and environmental conditions. Direct measurement of the full range of conditions to be encountered can be difficult, time consuming, and costly. Simulation of multispectral data by modeling scene, atmosphere, sensor, and data classifier characteristics is set forth as a viable alternative, particularly when coupled with limited sets of empirical measurements. A multispectral system modeling capability is described. Use of the model is illustrated for several applications - interpretation of remotely sensed data from agricultural and forest scenes, evaluating atmospheric effects in Landsat data, examining system design and operational configuration, and development of information extraction techniques.
Multispectral system analysis through modeling and simulation

NASA Technical Reports Server (NTRS)

Malila, W. A.; Gleason, J. M.; Cicone, R. C.

1977-01-01

The design and development of multispectral remote sensor systems and associated information extraction techniques should be optimized under the physical and economic constraints encountered and yet be effective over a wide range of scene and environmental conditions. Direct measurement of the full range of conditions to be encountered can be difficult, time consuming, and costly. Simulation of multispectral data by modeling scene, atmosphere, sensor, and data classifier characteristics is set forth as a viable alternative, particularly when coupled with limited sets of empirical measurements. A multispectral system modeling capability is described. Use of the model is illustrated for several applications - interpretation of remotely sensed data from agricultural and forest scenes, evaluating atmospheric effects in LANDSAT data, examining system design and operational configuration, and development of information extraction techniques.
Estimation of Hepatitis C Disease Burden and Budget Impact of Treatment Using Health Economic Modeling.

PubMed

Chhatwal, Jagpreet; Chen, Qiushi; Aggarwal, Rakesh

2018-06-01

Oral direct-acting antiviral agents have revolutionized treatment of hepatitis C virus (HCV) infection. Nonetheless, barriers exist to elimination of HCV as a public health threat including low uptake of treatment, limited budget allocations for HCV treatment, and low awareness rates of HCV status among infected people. Mathematical modeling provides a systematic framework to analyze and compare potential solutions and elimination strategies by simulating the HCV epidemic under different conditions. Such models evaluate impact of interventions in advance of implementation. This article describes key components of developing an HCV burden model and illustrates its use by simulating the HCV epidemic in the United States. Copyright © 2018 Elsevier Inc. All rights reserved.
Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501
Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080

PubMed Central

Fischer, Günther; Shah, Mahendra; N. Tubiello, Francesco; van Velhuizen, Harrij

2005-01-01

A comprehensive assessment of the impacts of climate change on agro-ecosystems over this century is developed, up to 2080 and at a global level, albeit with significant regional detail. To this end an integrated ecological–economic modelling framework is employed, encompassing climate scenarios, agro-ecological zoning information, socio-economic drivers, as well as world food trade dynamics. Specifically, global simulations are performed using the FAO/IIASA agro-ecological zone model, in conjunction with IIASAs global food system model, using climate variables from five different general circulation models, under four different socio-economic scenarios from the intergovernmental panel on climate change. First, impacts of different scenarios of climate change on bio-physical soil and crop growth determinants of yield are evaluated on a 5′×5′ latitude/longitude global grid; second, the extent of potential agricultural land and related potential crop production is computed. The detailed bio-physical results are then fed into an economic analysis, to assess how climate impacts may interact with alternative development pathways, and key trends expected over this century for food demand and production, and trade, as well as key composite indices such as risk of hunger and malnutrition, are computed. This modelling approach connects the relevant bio-physical and socio-economic variables within a unified and coherent framework to produce a global assessment of food production and security under climate change. The results from the study suggest that critical impact asymmetries due to both climate and socio-economic structures may deepen current production and consumption gaps between developed and developing world; it is suggested that adaptation of agricultural techniques will be central to limit potential damages under climate change. PMID:16433094
Simulation System for Making Political and Macroeconomical Decisions and Its Development

NASA Astrophysics Data System (ADS)

Vnukov, A. A.; Blinov, A. E.

2018-01-01

Object of this research are macroeconomic indicators, which are important to descript economic situation in a country. Purpose of this work is to identify these indicators and to analyze how the state can affect these figures with available instruments. Here was constructed a model where the targets can be calculated from raw data - tools in the field of economic policy. Software code that implements all relations among the indicators and allows to analyze with high accuracy, sufficiently successful economic policies and with the help of some tools, you can achieve better results. This model can be used to forecast macroeconomic scenarios. The corresponding values of the objective (outcome) variables are set as a consequence of the configuration data of the previous period, subject to external influences and depend on the instrumental variables. The results may be useful in economical predictions. The results were successfully checked on real scenarios of Russian, European and Chinese economics. Moreover, the results can be applied in the field of education. Program is available to use as “economical game” the educational process of the University, in which you can virtually implement various macroeconomic scenarios, draw conclusions about their success.
Economic modelling of grazing management against gastrointestinal nematodes in dairy cattle.

PubMed

van der Voort, M; Van Meensel, J; Lauwers, L; de Haan, M H A; Evers, A G; Van Huylenbroeck, G; Charlier, J

2017-03-15

Grazing management (GM) interventions, such as reducing the grazing time or mowing pasture before grazing, have been proposed to limit the exposure to gastrointestinal (GI) nematode infections in grazed livestock. However, the farm-level economic effects of these interventions have not yet been assessed. In this paper, the economic effects of three GM interventions in adult dairy cattle were modelled for a set of Flemish farms: later turnout on pasture (GM1), earlier housing near the end of the grazing season (GM2), and reducing the daily grazing time (GM3). Farm accountancy data were linked to Ostertagia ostertagi bulk tank milk ELISA results and GM data for 137 farms. The economic effects of the GM interventions were investigated through a combination of efficiency analysis and a whole-farm simulation model. Modelling of GM1, GM2 and GM3 resulted in a marginal economic effect of € 8.36, € -9.05 and € -53.37 per cow per year, respectively. The results suggest that the dairy farms can improve their economic performance by postponing the turnout date, but that advancing the housing date or reducing daily grazing time mostly leads to a lower net economic farm performance. Overall, the GM interventions resulted in a higher technical efficiency and milk production but these benefits were offset by increased feed costs as a result of higher maintenance and cultivation costs. Because the results differed highly between farms, GM interventions need to be evaluated at the individual level for appropriate decision support. Copyright © 2017 Elsevier B.V. All rights reserved.
Can marine protected areas enhance both economic and biological situations?

PubMed

Ami, Dominique; Cartigny, Pierre; Rapaport, Alain

2005-04-01

This paper investigates impacts of the creation of Marine Protected Areas (MPAs), in both economic and biological perspectives. The economic indicator is defined as the sum of discounted benefits derived from exploitation of the resource in the fishery sector, assumed to be optimally managed. The biological indicator is taken as the stock density of the resource. The basic fishery model (C.W. Clark, Mathematical Bioeconomics: The Optimal Management of Renewable Resources, second ed., John Wiley and Sons, New York, 1990) will serve as a convenient benchmark in comparing results with those that are derived from a model of two patchy populations (cf. R. Hannesson, Marine reserves: what would they accomplish, Mar. Resour. Econ. 13 (1998) 159). In the latter, a crucial characteristic is the migration coefficient with describes biological linkages between protected and unprotected areas. A set of situations where both economic and biological criteria are enhanced, after introducing a MPA, is presented. These results are obtained with the help of numerical simulations.
The economic impact of pig-associated parasitic zoonosis in Northern Lao PDR.

PubMed

Choudhury, Adnan Ali Khan; Conlan, James V; Racloz, Vanessa Nadine; Reid, Simon Andrew; Blacksell, Stuart D; Fenwick, Stanley G; Thompson, Andrew R C; Khamlome, Boualam; Vongxay, Khamphouth; Whittaker, Maxine

2013-03-01

The parasitic zoonoses human cysticercosis (Taenia solium), taeniasis (other Taenia species) and trichinellosis (Trichinella species) are endemic in the Lao People's Democratic Republic (Lao PDR). This study was designed to quantify the economic burden pig-associated zoonotic disease pose in Lao PDR. In particular, the analysis included estimation of the losses in the pork industry as well as losses due to human illness and lost productivity. A Markov-probability based decision-tree model was chosen to form the basis of the calculations to estimate the economic and public health impacts of taeniasis, trichinellosis and cysticercosis. Two different decision trees were run simultaneously on the model's human cohort. A third decision tree simulated the potential impacts on pig production. The human capital method was used to estimate productivity loss. The results found varied significantly depending on the rate of hospitalisation due to neurocysticerosis. This study is the first systematic estimate of the economic impact of pig-associated zoonotic diseases in Lao PDR that demonstrates the significance of the diseases in that country.
Simulation of Solar Energy Use in Livelihood of Buildings

NASA Astrophysics Data System (ADS)

Lvocich, I. Ya; Preobrazhenskiy, A. P.; Choporov, O. N.

2017-11-01

Solar energy can be considered as the most technological and economical type of renewable energy. The purpose of the paper is to increase the efficiency of solar energy utilization on the basis of the mathematical simulation of the solar collector. A mathematical model of the radiant heat transfer vacuum solar collector is clarified. The model was based on the process of radiative heat transfer between glass and copper walls with the defined blackness degrees. A mathematical model of the ether phase transition point is developed. The dependence of the reservoir walls temperature change on the ambient temperature over time is obtained. The results of the paper can be useful for the development of prospective sources using solar energy.
Body models in forensic ballistics: reconstruction of a gunshot injury to the chest by bullet fragmentation after shooting through a finger.

PubMed

Thali, M J; Kneubuehl, B P; Dirnhofer, R; Zollinger, U

2001-11-15

Forensic science uses substitutes to reconstruct injury patterns in order to answer questions regarding the dynamic formation of unusual injuries. Using a case study, an experimental simulation of a finger was designed, for the first time with a combination of hard wood and glycerin soap. With this model as an intermediate target simulation, it was possible not only to demonstrate the "bullet-body (finger) interaction", but also to recreate the wound pattern found in the victim. This case demonstrates that by using ballistic models and body-part substitutes, gunshot cases can be reproduced simply and economically, without coming into conflict with ethical guidelines.
BIOASPEN: System for technology development

NASA Technical Reports Server (NTRS)

1986-01-01

The public version of ASPEN was installed in the VAX 11/750 computer. To examine the idea of BIOASPEN, a test example (the manufacture of acetone, butanol, and ethanol through a biological route) was chosen for simulation. Previous reports on the BIOASPEN project revealed the limitations of ASPEN in modeling this process. To overcome some of the difficulties, modules were written for the acid and enzyme hydrolyzers, the fermentor, and a sterilizer. Information required for these modules was obtained from the literature whenever possible. Additional support modules necessary for interfacing with ASPEN were also written. Some of ASPEN subroutines were themselves altered in order to ensure the correct running of the simulation program. After testing of these additions and charges was completed, the Acetone-Butanol-Ethanol (ABE) process was simulated. A release of ASPEN (which contained the Economic Subsystem) was obtained and installed. This subsection was tested and numerous charges were made in the FORTRAN code. Capital investment and operating cost studies were performed on the ABE process. Some alternatives in certain steps of the ABE simulation were investigated in order to elucidate their effects on the overall economics of the process.
The Importance of Considering the Temporal Distribution of Climate Variables for Ecological-Economic Modeling to Calculate the Consequences of Climate Change for Agriculture

NASA Astrophysics Data System (ADS)

Plegnière, Sabrina; Casper, Markus; Hecker, Benjamin; Müller-Fürstenberger, Georg

2014-05-01

The basis of many models to calculate and assess climate change and its consequences are annual means of temperature and precipitation. This method leads to many uncertainties especially at the regional or local level: the results are not realistic or too coarse. Particularly in agriculture, single events and the distribution of precipitation and temperature during the growing season have enormous influences on plant growth. Therefore, the temporal distribution of climate variables should not be ignored. To reach this goal, a high-resolution ecological-economic model was developed which combines a complex plant growth model (STICS) and an economic model. In this context, input data of the plant growth model are daily climate values for a specific climate station calculated by the statistical climate model (WETTREG). The economic model is deduced from the results of the plant growth model STICS. The chosen plant is corn because corn is often cultivated and used in many different ways. First of all, a sensitivity analysis showed that the plant growth model STICS is suitable to calculate the influences of different cultivation methods and climate on plant growth or yield as well as on soil fertility, e.g. by nitrate leaching, in a realistic way. Additional simulations helped to assess a production function that is the key element of the economic model. Thereby the problems when using mean values of temperature and precipitation in order to compute a production function by linear regression are pointed out. Several examples show why a linear regression to assess a production function based on mean climate values or smoothed natural distribution leads to imperfect results and why it is not possible to deduce a unique climate factor in the production function. One solution for this problem is the additional consideration of stress indices that show the impairment of plants by water or nitrate shortage. Thus, the resulting model takes into account not only the ecological factors (e.g. the plant growth) or the economical factors as a simple monetary calculation, but also their mutual influences. Finally, the ecological-economic model enables us to make a risk assessment or evaluate adaptation strategies.
Rainfall-runoff modelling of the Okavango River catchment to assess impacts of land use change on runoff and downstream ecosystems

NASA Astrophysics Data System (ADS)

Milzow, Christian; Bauer-Gottwein, Peter

2010-05-01

The competition between human water use and ecosystem water use is one of the major challenges for water resources management at the global scale. We analyse the situation for the Okavango River basin of southern Africa. The Okavango River is representative for many large rivers throughout the developing world in that it is ungauged and poorly studied. The Okavango basin - spanning over Angola, Namibia and Botswana - represents a multi-objective problem in an international setting. Economic benefits of agricultural development and conservation of ecosystem services call for opposed actions. A semi-distributed rainfall-runoff model of the Okavango catchment is set up using the Soil and Water Assessment Tool (SWAT). The model is sufficiently physically based to simulate the impact on runoff of extent of agricultural use, crop types and management practices. Precipitation and temperature inputs are taken from datasets covering large parts of the globe. The methodology can thus easily be applied for other ungauged catchments. For temperature we use the ERA-Interim reanalysis product of the European Centre for Medium-Range Weather Forecasts and for precipitation the Famine Early Warning Systems Network data (FEWS-Net). Tropical Rainfall Measurement Mission (TRMM) data resulted in poor model performance compared to the FEWS-Net data. Presently, the upstream catchment in Angola is largely pristine and agriculture is basically restricted to dry land subsistence farming. But economic growth in Angola is likely to result in agricultural development and consequent impacts on catchment runoff. Land use scenarios that are simulated include large scale irrigated agriculture with water extractions from the river and the shallow aquifer. Climate change impacts are also studied and compared to land use change impacts. The downstream part of the basin consists of the large Okavango Wetlands, which are a biodiversity hotspot of global importance and, through tourism, an important source of economic income for Botswana. A second hydrological model simulating flow through the wetlands is used to study the impact of catchment runoff changes on the hydrology and ecology of the wetlands. The final goal of the project is to demonstrate the relation between economic benefits of water abstractions in the upstream and downstream environmental impact. Furthermore the results will provide a basis for defining adequate compensations for upstream stakeholders who forego benefits of agricultural intensification to ensure the conservation of downstream ecosystem services.
Prediction of diffuse organic micropollutant loads in streams under changing climatic, socio-economic and technical boundary conditions with an integrated transport model

NASA Astrophysics Data System (ADS)

Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Ghielmetti, Nico; Stamm, Christian

2014-05-01

Catchments are complex systems where water quantity, quality and the ecological services provided are determined by interacting physical, chemical, biological, economical and social factors. The realization of these interactions led to the prevailing catchment management paradigm: Integrated Water Resources Management (IWRM). IWRM requires considering all these aspects during the design of sustainable resource utilization. Due to the complexity of this task, mathematical modeling plays a key role in IWRM, namely in the evaluation of the impacts of hypothetical scenarios and management measures. Toxicity is a key determinant of the ecological state and as such a focal point in IWRM, but we still have significant knowledge gaps about the diffuse loads of organic micropollutants (OMP) that leak from both urban and agricultural areas. Most European catchments possess mixed land use, containing rural (natural and agricultural) landscapes and settlements in varying proportions. Thus, a catchment model supporting IWRM must be able to cope with both classes. However, the majority of existing catchment models is dedicated to either rural or urban areas, while the minority capable of simulating both contain overly simplified descriptions for either land use category. We applied a conceptual model that describes all major land use classes for assessing the impacts of climate change, socio-economic development and management alternatives on diffuse OMP loads. We simulated the loads of 12 compounds (agricultural and urban pesticides and urban biocides) with daily resolution at 11 locations in the stream network of a small catchment (46 km2) in Switzerland. The model considers all important diffuse transport pathways separately, but each with a simple empirical process rate. Consequently, some site-specific observations were required to calibrate rate parameters. We assessed uncertainty during both calibration and prediction phases. Predictions indicated that future OMP loads were predominantly determined by human activities in each simulated sub-catchment, as reflected by the socio-economic scenarios and management alternatives. Climatic and the corresponding hydrological changes had a much weaker influence. This indicates that - conditionally on the confidence of our predictions - catchment management would possess effective options to prevent the degradation of water quality in the future. However, prediction uncertainty varied between high and huge levels depending on compound. Most of the identified uncertainty was related to the quality of input data. Application rates and timings could be estimated only roughly for most compounds. Concentration peaks were simulated with high uncertainty. The highest pollutant concentrations were often associated with known but unidentified pollution sources such as accidental spills, or brief high-intensity precipitation events whose amount could only be observed with high uncertainty. So while acute exposure would be as important as the chronic one for IWRM, neither climatic nor catchment models excel at predicting rare and brief events. This deficiency highlights why the assessment of predictive uncertainty should be an integral part of OMP modeling.
Projection of Diabetes Population Size and Associated Economic Burden through 2030 in Iran: Evidence from Micro-Simulation Markov Model and Bayesian Meta-Analysis

PubMed Central

Javanbakht, Mehdi; Mashayekhi, Atefeh; Baradaran, Hamid R.; Haghdoost, AliAkbar; Afshin, Ashkan

2015-01-01

Background The aim of this study was to estimate the economic burden of diabetes mellitus (DM) in Iran from 2009 to 2030. Methods A Markov micro-simulation (MM) model was developed to predict the DM population size and associated economic burden. Age- and sex-specific prevalence and incidence of diagnosed and undiagnosed DM were derived from national health surveys. A systematic review was performed to identify the cost of diabetes in Iran and the mean annual direct and indirect costs of patients with DM were estimated using a random-effect Bayesian meta-analysis. Face, internal, cross and predictive validity of the MM model were assessed by consulting an expert group, performing sensitivity analysis (SA) and comparing model results with published literature and national survey reports. Sensitivity analysis was also performed to explore the effect of uncertainty in the model. Results We estimated 3.78 million cases of DM (2.74 million diagnosed and 1.04 million undiagnosed) in Iran in 2009. This number is expected to rise to 9.24 million cases (6.73 million diagnosed and 2.50 million undiagnosed) by 2030. The mean annual direct and indirect costs of patients with DM in 2009 were US$ 556 (posterior standard deviation, 221) and US$ 689 (619), respectively. Total estimated annual cost of DM was $3.64 (2009 US$) billion (including US$1.71 billion direct and US$1.93 billion indirect costs) in 2009 and is predicted to increase to $9.0 (in 2009 US$) billion (including US$4.2 billion direct and US$4.8 billion indirect costs) by 2030. Conclusions The economic burden of DM in Iran is predicted to increase markedly in the coming decades. Identification and implementation of effective strategies to prevent and manage DM should be considered as a public health priority. PMID:26200913

Projection of Diabetes Population Size and Associated Economic Burden through 2030 in Iran: Evidence from Micro-Simulation Markov Model and Bayesian Meta-Analysis.

PubMed

Javanbakht, Mehdi; Mashayekhi, Atefeh; Baradaran, Hamid R; Haghdoost, AliAkbar; Afshin, Ashkan

2015-01-01

The aim of this study was to estimate the economic burden of diabetes mellitus (DM) in Iran from 2009 to 2030. A Markov micro-simulation (MM) model was developed to predict the DM population size and associated economic burden. Age- and sex-specific prevalence and incidence of diagnosed and undiagnosed DM were derived from national health surveys. A systematic review was performed to identify the cost of diabetes in Iran and the mean annual direct and indirect costs of patients with DM were estimated using a random-effect Bayesian meta-analysis. Face, internal, cross and predictive validity of the MM model were assessed by consulting an expert group, performing sensitivity analysis (SA) and comparing model results with published literature and national survey reports. Sensitivity analysis was also performed to explore the effect of uncertainty in the model. We estimated 3.78 million cases of DM (2.74 million diagnosed and 1.04 million undiagnosed) in Iran in 2009. This number is expected to rise to 9.24 million cases (6.73 million diagnosed and 2.50 million undiagnosed) by 2030. The mean annual direct and indirect costs of patients with DM in 2009 were US$ 556 (posterior standard deviation, 221) and US$ 689 (619), respectively. Total estimated annual cost of DM was $3.64 (2009 US$) billion (including US$1.71 billion direct and US$1.93 billion indirect costs) in 2009 and is predicted to increase to $9.0 (in 2009 US$) billion (including US$4.2 billion direct and US$4.8 billion indirect costs) by 2030. The economic burden of DM in Iran is predicted to increase markedly in the coming decades. Identification and implementation of effective strategies to prevent and manage DM should be considered as a public health priority.
Clinical laboratory as an economic model for business performance analysis

PubMed Central

Buljanović, Vikica; Patajac, Hrvoje; Petrovečki, Mladen

2011-01-01

Aim To perform SWOT (strengths, weaknesses, opportunities, and threats) analysis of a clinical laboratory as an economic model that may be used to improve business performance of laboratories by removing weaknesses, minimizing threats, and using external opportunities and internal strengths. Methods Impact of possible threats to and weaknesses of the Clinical Laboratory at Našice General County Hospital business performance and use of strengths and opportunities to improve operating profit were simulated using models created on the basis of SWOT analysis results. The operating profit as a measure of profitability of the clinical laboratory was defined as total revenue minus total expenses and presented using a profit and loss account. Changes in the input parameters in the profit and loss account for 2008 were determined using opportunities and potential threats, and economic sensitivity analysis was made by using changes in the key parameters. The profit and loss account and economic sensitivity analysis were tools for quantifying the impact of changes in the revenues and expenses on the business operations of clinical laboratory. Results Results of simulation models showed that operational profit of €470 723 in 2008 could be reduced to only €21 542 if all possible threats became a reality and current weaknesses remained the same. Also, operational gain could be increased to €535 804 if laboratory strengths and opportunities were utilized. If both the opportunities and threats became a reality, the operational profit would decrease by €384 465. Conclusion The operational profit of the clinical laboratory could be significantly reduced if all threats became a reality and the current weaknesses remained the same. The operational profit could be increased by utilizing strengths and opportunities as much as possible. This type of modeling may be used to monitor business operations of any clinical laboratory and improve its financial situation by implementing changes in the next fiscal period. PMID:21853546
Clinical laboratory as an economic model for business performance analysis.

PubMed

Buljanović, Vikica; Patajac, Hrvoje; Petrovecki, Mladen

2011-08-15

To perform SWOT (strengths, weaknesses, opportunities, and threats) analysis of a clinical laboratory as an economic model that may be used to improve business performance of laboratories by removing weaknesses, minimizing threats, and using external opportunities and internal strengths. Impact of possible threats to and weaknesses of the Clinical Laboratory at Našice General County Hospital business performance and use of strengths and opportunities to improve operating profit were simulated using models created on the basis of SWOT analysis results. The operating profit as a measure of profitability of the clinical laboratory was defined as total revenue minus total expenses and presented using a profit and loss account. Changes in the input parameters in the profit and loss account for 2008 were determined using opportunities and potential threats, and economic sensitivity analysis was made by using changes in the key parameters. The profit and loss account and economic sensitivity analysis were tools for quantifying the impact of changes in the revenues and expenses on the business operations of clinical laboratory. Results of simulation models showed that operational profit of €470 723 in 2008 could be reduced to only €21 542 if all possible threats became a reality and current weaknesses remained the same. Also, operational gain could be increased to €535 804 if laboratory strengths and opportunities were utilized. If both the opportunities and threats became a reality, the operational profit would decrease by €384 465. The operational profit of the clinical laboratory could be significantly reduced if all threats became a reality and the current weaknesses remained the same. The operational profit could be increased by utilizing strengths and opportunities as much as possible. This type of modeling may be used to monitor business operations of any clinical laboratory and improve its financial situation by implementing changes in the next fiscal period.
An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.
Using a dynamic model to assess trends in land degradation by water erosion in Spanish Rangelands

NASA Astrophysics Data System (ADS)

Ibáñez, Javier; Francisco Lavado-Contador, Joaquín; Schnabel, Susanne; Pulido-Fernández, Manuel; Martínez Valderrama, Jaime

2014-05-01

This work presents a model aimed at evaluating land degradation by water erosion in dehesas and montados of the Iberian Peninsula, that constitute valuable rangelands in the area. A multidisciplinary dynamic model was built including weather, biophysical and economic variables that reflect the main causes and processes affecting sheet erosion on hillsides of the study areas. The model has two main and two derived purposes: Purpose 1: Assessing the risk of degradation that a land-use system is running. Derived purpose 1: Early warning about land-use systems that are particularly threatened by degradation. Purpose 2: Assessing the degree to which different factors would hasten degradation if they changed from the typical values they show at present. Derived purpose 2: Evaluating the role of human activities on degradation. Model variables and parameters have been calibrated for a typical open woodland rangeland (dehesa or montado) defined along 22 working units selected from 10 representative farms and distributed throughout the Spanish region of Extremadura. The model is the basis for a straightforward assessment methodology which is summarized by the three following points: i) The risk of losing a given amount of soil before a given number of years was specifically estimated as the percentage of 1000 simulations where such a loss occurs, being the simulations run under randomly-generated scenarios of rainfall amount and intensity and meat and supplemental feed market prices; ii) Statistics about the length of time that a given amount of soil takes to be lost were calculated over 1000 stochastic simulations run until year 1000, thereby ensuring that such amount of soil has been lost in all of the simulations, i.e. the total risk is 100%; iii) Exogenous factors potentially affecting degradation, mainly climatic and economic, were ranked in order of importance by means of a sensitivity analysis. Particularly remarkable in terms of model performance is the major role played in our case study by two positive feedback loops in which the erosion rate is involved. Those loops are responsible for erosion to accelerate over time, thereby outweighing the effect of negative feedbacks also involved in the erosion rate. The estimated lengths of time to loss the upper 5, 10, 15 and 20 cm of the soil (with and initial depth of 23.4 cm) corresponds to 138, 245, 317 and 360 years, respectively. The importance of climatic factors on soil removal considerably exceeds that of the economic ones, which showed low impacts on the final model results.
Decadal shifts of East Asian summer monsoon in a climate model free of explicit GHGs and aerosols

NASA Astrophysics Data System (ADS)

Lin, Renping; Zhu, Jiang; Zheng, Fei

2016-12-01

The East Asian summer monsoon (EASM) experienced decadal transitions over the past few decades, and the associated "wetter-South-drier-North" shifts in rainfall patterns in China significantly affected the social and economic development in China. Two viewpoints stand out to explain these decadal shifts, regarding the shifts either a result of internal variability of climate system or that of external forcings (e.g. greenhouse gases (GHGs) and anthropogenic aerosols). However, most climate models, for example, the Atmospheric Model Intercomparison Project (AMIP)-type simulations and the Coupled Model Intercomparison Project (CMIP)-type simulations, fail to simulate the variation patterns, leaving the mechanisms responsible for these shifts still open to dispute. In this study, we conducted a successful simulation of these decadal transitions in a coupled model where we applied ocean data assimilation in the model free of explicit aerosols and GHGs forcing. The associated decadal shifts of the three-dimensional spatial structure in the 1990s, including the eastward retreat, the northward shift of the western Pacific subtropical high (WPSH), and the south-cool-north-warm pattern of the upper-level tropospheric temperature, were all well captured. Our simulation supports the argument that the variations of the oceanic fields are the dominant factor responsible for the EASM decadal transitions.
Decadal shifts of East Asian summer monsoon in a climate model free of explicit GHGs and aerosols

PubMed Central

Lin, Renping; Zhu, Jiang; Zheng, Fei

2016-01-01

The East Asian summer monsoon (EASM) experienced decadal transitions over the past few decades, and the associated "wetter-South-drier-North" shifts in rainfall patterns in China significantly affected the social and economic development in China. Two viewpoints stand out to explain these decadal shifts, regarding the shifts either a result of internal variability of climate system or that of external forcings (e.g. greenhouse gases (GHGs) and anthropogenic aerosols). However, most climate models, for example, the Atmospheric Model Intercomparison Project (AMIP)-type simulations and the Coupled Model Intercomparison Project (CMIP)-type simulations, fail to simulate the variation patterns, leaving the mechanisms responsible for these shifts still open to dispute. In this study, we conducted a successful simulation of these decadal transitions in a coupled model where we applied ocean data assimilation in the model free of explicit aerosols and GHGs forcing. The associated decadal shifts of the three-dimensional spatial structure in the 1990s, including the eastward retreat, the northward shift of the western Pacific subtropical high (WPSH), and the south-cool-north-warm pattern of the upper-level tropospheric temperature, were all well captured. Our simulation supports the argument that the variations of the oceanic fields are the dominant factor responsible for the EASM decadal transitions. PMID:27934933
Pandemic recovery analysis using the dynamic inoperability input-output model.

PubMed

Santos, Joost R; Orsi, Mark J; Bond, Erik J

2009-12-01

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model((1,2)) and the dynamic inoperability input-output model (DIIM).((3)) These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.
A generic bio-economic farm model for environmental and economic assessment of agricultural systems.

PubMed

Janssen, Sander; Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K

2010-12-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.
A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

PubMed Central

Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K.

2010-01-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. PMID:21113782
Active and Cooperative Learning Using Web-Based Simulations.

ERIC Educational Resources Information Center

Schmidt, Stephen J.

2003-01-01

Cites advantages of using computers and the World Wide Web in classroom simulations. Provides a sample simulation that teaches the basic economic principles of trade, investment, and public goods in the context of U.S. economic history. (JEH)
COMPUTER SIMULATOR (BEST) FOR DESIGNING SULFATE-REDUCING BACTERIA FIELD BIOREACTORS

EPA Science Inventory

BEST (bioreactor economics, size and time of operation) is a spreadsheet-based model that is used in conjunction with public domain software, PhreeqcI. BEST is used in the design process of sulfate-reducing bacteria (SRB) field bioreactors to passively treat acid mine drainage (A...
Analysis, Modeling, and Simulation (AMS) testbed framework for Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) programs.

DOT National Transportation Integrated Search

1997-08-01

A Regional ITS/CVO Coordination Plan outlines a strategy for the deployment of Intelligent Transportation Systems (ITS)/Commercial Vehicle Operations (CVO) technologies by a group of states with common economic and transportation needs. The Coordinat...
Process Simulation of Aluminium Sheet Metal Deep Drawing at Elevated Temperatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winklhofer, Johannes; Trattnig, Gernot; Lind, Christoph

Lightweight design is essential for an economic and environmentally friendly vehicle. Aluminium sheet metal is well known for its ability to improve the strength to weight ratio of lightweight structures. One disadvantage of aluminium is that it is less formable than steel. Therefore complex part geometries can only be realized by expensive multi-step production processes. One method for overcoming this disadvantage is deep drawing at elevated temperatures. In this way the formability of aluminium sheet metal can be improved significantly, and the number of necessary production steps can thereby be reduced. This paper introduces deep drawing of aluminium sheet metalmore » at elevated temperatures, a corresponding simulation method, a characteristic process and its optimization. The temperature and strain rate dependent material properties of a 5xxx series alloy and their modelling are discussed. A three dimensional thermomechanically coupled finite element deep drawing simulation model and its validation are presented. Based on the validated simulation model an optimised process strategy regarding formability, time and cost is introduced.« less
Solar energy system economic evaluation: Fern Tunkhannock, Tunkhannock, Pennsylvania

NASA Astrophysics Data System (ADS)

1980-09-01

The economic performance of an Operational Test Site (OTS) is described. The long term economic performance of the system at its installation site and extrapolation to four additional selected locations to demonstrate the viability of the design over a broad range of environmental and economic conditions is reported. Topics discussed are: system description, study approach, economic analysis and system optimization, and technical and economical results of analysis. Data for the economic analysis are generated through evaluation of the OTS. The simulation is based on the technical results of the seasonal report simulation. In addition localized and standard economic parameters are used for economic analysis.
Solar energy system economic evaluation: Fern Tunkhannock, Tunkhannock, Pennsylvania

NASA Technical Reports Server (NTRS)

1980-01-01

The economic performance of an Operational Test Site (OTS) is described. The long term economic performance of the system at its installation site and extrapolation to four additional selected locations to demonstrate the viability of the design over a broad range of environmental and economic conditions is reported. Topics discussed are: system description, study approach, economic analysis and system optimization, and technical and economical results of analysis. Data for the economic analysis are generated through evaluation of the OTS. The simulation is based on the technical results of the seasonal report simulation. In addition localized and standard economic parameters are used for economic analysis.
The epidemiological and economic effects from systematic depopulation of Norwegian marine salmon farms infected with pancreas disease virus.

PubMed

Pettersen, J M; Brynildsrud, O B; Huseby, R B; Rich, K M; Aunsmo, A; Bang, B Jensen; Aldrin, M

2016-09-15

Pancreas disease (PD) is a viral disease associated with significant economic losses in Scottish, Irish, and Norwegian marine salmon aquaculture. In this paper, we investigate how disease-triggered harvest strategies (systematic depopulation of infected marine salmon farms) towards PD can affect disease dynamics and salmon producer profits in an endemic area in the southwestern part of Norway. Four different types of disease-triggered harvest strategies were evaluated over a four-year period (2011-2014), each scenario with different disease-screening procedures, timing for initiating the harvest interventions on infected cohorts, and levels of farmer compliance to the strategy. Our approach applies a spatio-temporal stochastic model for simulating the spread of PD in the separate scenarios. Results from these simulations were then used in cost-benefit analyses to estimate the net benefits of different harvest strategies over time. We find that the most aggressive strategy, in which infected farms are harvested without delay, was most efficient in terms of reducing infection pressure in the area and providing economic benefits for the studied group of salmon producers. On the other hand, lower farm compliance leads to higher infection pressure and less economic benefits. Model results further highlight trade-offs in strategies between those that primarily benefit individual producers and those that have collective benefits, suggesting a need for institutional mechanisms that address these potential tensions. Copyright © 2016 Elsevier B.V. All rights reserved.
Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.
Thermodynamics and the evolution of a city: a tale of how ...

EPA Pesticide Factsheets

Cities are complex organized systems, similar to biological and ecological systems in the way that they are structured and function. These systems are subject to the laws of thermodynamics and the principles of Energy Systems Theory (EST). Like other systems, cities experience larger scale drivers of change in resources. Unlike other ecosystems, cities react through socio-economic responses.Important contributions towards an integrated understanding of urban dynamics can be gained when their structures, functions and developments are interpreted within EST contexts.We have constructed a systems dynamics model that simulates some structural and functional aspects of Chicago in space and over time and we interpret model outcomes using EST. The purposes of the model are twofold, a knowledge base for integrating historical information, and for scenario modeling. Our history of Chicago starts in 1830 as a narrative, on the economic development and human population growth. Illustrated by a series of conceptual Energy Systems Models, it describes changes in trade, land tenure, and transportation as a result of increased access to nonlocal resources. Our simulation model, covers the post-World War II period to the present, and examines changes in population and its distribution on the landscape, material and energy flows, alterations of fresh water flows and management of wastewater. Scenario modeling is performed using a platform that estimates the potential impli
An Agent-Based Model of Farmer Decision Making in Jordan

NASA Astrophysics Data System (ADS)

Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

2016-04-01

We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

Technical Performance and Economic Evaluation of Evaporative and Membrane-Based Concentration for Biomass-Derived Sugars

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sievers, David A.; Stickel, Jonathan J.; Grundl, Nicholas J.

Several conversion pathways of lignocellulosic biomass to advanced biofuels require or benefit from using concentrated sugar syrups of 600 g/L or greater. And while concentration may seem straightforward, thermal sugar degradation and energy efficiency remain major concerns. This study evaluated the trade-offs in product recovery, energy consumption, and economics between evaporative and membrane-based concentration methods. The degradation kinetics of xylose and glucose were characterized and applied to an evaporator process simulation. Though significant sugar loss was predicted for certain scenarios due to the Maillard reaction, industrially common falling-film plate evaporators offer short residence times (<5 min) and are expected tomore » limit sugar losses. Membrane concentration experiments characterized flux and sugar rejection, but diminished flux occurred at >100 g/L. A second step using evaporation is necessary to achieve target concentrations. Techno-economic process model simulations evaluated the overall economics of concentrating a 35 g/L sugar stream to 600 g/L in a full-scale biorefinery. A two-step approach of preconcentrating using membranes and finishing with an evaporator consumed less energy than evaporation alone but was more expensive because of high capital expenses of the membrane units.« less
Technical Performance and Economic Evaluation of Evaporative and Membrane-Based Concentration for Biomass-Derived Sugars

DOE PAGES

Sievers, David A.; Stickel, Jonathan J.; Grundl, Nicholas J.; ...

2017-09-18

Several conversion pathways of lignocellulosic biomass to advanced biofuels require or benefit from using concentrated sugar syrups of 600 g/L or greater. And while concentration may seem straightforward, thermal sugar degradation and energy efficiency remain major concerns. This study evaluated the trade-offs in product recovery, energy consumption, and economics between evaporative and membrane-based concentration methods. The degradation kinetics of xylose and glucose were characterized and applied to an evaporator process simulation. Though significant sugar loss was predicted for certain scenarios due to the Maillard reaction, industrially common falling-film plate evaporators offer short residence times (<5 min) and are expected tomore » limit sugar losses. Membrane concentration experiments characterized flux and sugar rejection, but diminished flux occurred at >100 g/L. A second step using evaporation is necessary to achieve target concentrations. Techno-economic process model simulations evaluated the overall economics of concentrating a 35 g/L sugar stream to 600 g/L in a full-scale biorefinery. A two-step approach of preconcentrating using membranes and finishing with an evaporator consumed less energy than evaporation alone but was more expensive because of high capital expenses of the membrane units.« less
Implementing economic evaluation in simulation-based medical education: challenges and opportunities.

PubMed

Lin, Yiqun; Cheng, Adam; Hecker, Kent; Grant, Vincent; Currie, Gillian R

2018-02-01

Simulation-based medical education (SBME) is now ubiquitous at all levels of medical training. Given the substantial resources needed for SBME, economic evaluation of simulation-based programmes or curricula is required to demonstrate whether improvement in trainee performance (knowledge, skills and attitudes) and health outcomes justifies the cost of investment. Current literature evaluating SBME fails to provide consistent and interpretable information on the relative costs and benefits of alternatives. Economic evaluation is widely applied in health care, but is relatively scarce in medical education. Therefore, in this paper, using a focus on SBME, we define economic evaluation, describe the key components, and discuss the challenges associated with conducting an economic evaluation of medical education interventions. As a way forward to the rigorous and state of the art application of economic evaluation in medical education, we outline the steps to gather the necessary information to conduct an economic evaluation of simulation-based education programmes and curricula, and describe the main approaches to conducting an economic evaluation. A properly conducted economic evaluation can help stakeholders (i.e., programme directors, policy makers and curriculum designers) to determine the optimal use of resources in selecting the modality or method of assessment in simulation. It also helps inform broader decision making about allocation of scarce resources within an educational programme, as well as between education and clinical care. Economic evaluation in medical education research is still in its infancy, and there is significant potential for state-of-the-art application of these methods in this area. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.
Assessing Regional-Scale Impacts of Short Rotation Coppices on Ecosystem Services by Modeling Land-Use Decisions.

PubMed

Schulze, Jule; Frank, Karin; Priess, Joerg A; Meyer, Markus A

2016-01-01

Meeting the world's growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted.
Assessing Regional-Scale Impacts of Short Rotation Coppices on Ecosystem Services by Modeling Land-Use Decisions

PubMed Central

Schulze, Jule; Frank, Karin; Priess, Joerg A.; Meyer, Markus A.

2016-01-01

Meeting the world’s growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted. PMID:27082742
Using Copulas in the Estimation of the Economic Project Value in the Mining Industry, Including Geological Variability

NASA Astrophysics Data System (ADS)

Krysa, Zbigniew; Pactwa, Katarzyna; Wozniak, Justyna; Dudek, Michal

2017-12-01

Geological variability is one of the main factors that has an influence on the viability of mining investment projects and on the technical risk of geology projects. In the current scenario, analyses of economic viability of new extraction fields have been performed for the KGHM Polska Miedź S.A. underground copper mine at Fore Sudetic Monocline with the assumption of constant averaged content of useful elements. Research presented in this article is aimed at verifying the value of production from copper and silver ore for the same economic background with the use of variable cash flows resulting from the local variability of useful elements. Furthermore, the ore economic model is investigated for a significant difference in model value estimated with the use of linear correlation between useful elements content and the height of mine face, and the approach in which model parameters correlation is based upon the copula best matched information capacity criterion. The use of copula allows the simulation to take into account the multi variable dependencies at the same time, thereby giving a better reflection of the dependency structure, which linear correlation does not take into account. Calculation results of the economic model used for deposit value estimation indicate that the correlation between copper and silver estimated with the use of copula generates higher variation of possible project value, as compared to modelling correlation based upon linear correlation. Average deposit value remains unchanged.
Modelling economic losses of historic and present-day high-impact winter storms in Switzerland

NASA Astrophysics Data System (ADS)

Welker, Christoph; Martius, Olivia; Stucki, Peter; Bresch, David; Dierer, Silke; Brönnimann, Stefan

2015-04-01

Windstorms can cause significant financial damage and they rank among the most hazardous meteorological hazards in Switzerland. Risk associated with windstorms involves the combination of hazardous weather conditions, such as high wind gust speeds, and socio-economic factors, such as the distribution of assets as well as their susceptibilities to damage. A sophisticated risk assessment is important in a wide range of areas and has benefits for e.g. the insurance industry. However, a sophisticated risk assessment needs a large sample of storm events for which high-resolution, quantitative meteorological and/or loss data are available. Latter is typically an aggravating factor. For present-day windstorms in Switzerland, the data basis is generally sufficient to describe the meteorological development and wind forces as well as the associated impacts. In contrast, historic windstorms are usually described by graphical depictions of the event and/or by weather and loss reports. The information on historic weather events is overall sparse and the available historic weather and loss reports mostly do not provide quantitative information. It has primarily been the field of activity of environmental historians to study historic weather extremes and their impacts. Furthermore, the scarce availability of atmospheric datasets reaching back sufficiently in time has so far limited the analysis of historic weather events. The Twentieth Century Reanalysis (20CR) ensemble dataset, a global atmospheric reanalysis currently spanning 1871 to 2012, offers potentially a very valuable resource for the analysis of historic weather events. However, the 2°×2° latitude-longitude grid of the 20CR is too coarse to realistically represent the complex orography of Switzerland, which has considerable ramifications for the representation of smaller-scale features of the surface wind field influenced by the local orography. Using the 20CR as a starting point, this study illustrates a method to simulate the wind field and related economic impact of both historic and present-day high-impact winter storms in Switzerland since end of the 19th century. Our technique involves the dynamical downscaling of the 20CR to 3 km horizontal resolution using the numerical Weather Research and Forecasting model and the subsequent loss simulation using an open-source impact model. This impact model estimates, for modern economic and social conditions, storm-related economic losses at municipality level, and thus allows a numerical simulation of the impact from both historic and present-day severe winter storms in Switzerland on a relatively fine spatial scale. In this study, we apply the modelling chain to a storm sample of almost 90 high-impact winter storms in Switzerland since 1871, and we are thus able to make a statement of the typical wind and loss patterns of hazardous windstorms in Switzerland. To evaluate our modelling chain, we compare simulated storm losses with insurance loss data for the present-day windstorms "Lothar" and "Joachim" in December 1999 and December 2011, respectively. Our study further includes a range of sensitivity experiments and a discussion of the main sources of uncertainty.
Parameterization of Nitrogen Limitation for a Dynamic Ecohydrological Model: a Case Study from the Luquillo Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Bastola, S.; Bras, R. L.

2017-12-01

Feedbacks between vegetation and the soil nutrient cycle are important in ecosystems where nitrogen limits plant growth, and consequently influences the carbon balance in the plant-soil system. However, many biosphere models do not include such feedbacks, because interactions between carbon and the nitrogen cycle can be complex, and remain poorly understood. In this study we coupled a nitrogen cycle model with an eco-hydrological model by using the concept of carbon cost economics. This concept accounts for different "costs" to the plant of acquiring nitrogen via different pathways. This study builds on tRIBS-VEGGIE, a spatially explicit hydrological model coupled with a model of photosynthesis, stomatal resistance, and energy balance, by combining it with a model of nitrogen recycling. Driven by climate and spatially explicit data of soils, vegetation and topography, the model (referred to as tRIBS-VEGGIE-CN) simulates the dynamics of carbon and nitrogen in the soil-plant system; the dynamics of vegetation; and different components of the hydrological cycle. The tRIBS-VEGGIE-CN is applied in a humid tropical watershed at the Luquillo Critical Zone Observatory (LCZO). The region is characterized by high availability and cycling of nitrogen, high soil respiration rates, and large carbon stocks.We drive the model under contemporary CO2 and hydro-climatic forcing and compare results to a simulation under doubling CO2 and a range of future climate scenarios. The results with parameterization of nitrogen limitation based on carbon cost economics show that the carbon cost of the acquisition of nitrogen is 14% of the net primary productivity (NPP) and the N uptake cost for different pathways vary over a large range depending on leaf nitrogen content, turnover rates of carbon in soil and nitrogen cycling processes. Moreover, the N fertilization simulation experiment shows that the application of N fertilizer does not significantly change the simulated NPP. Furthermore, an experiment with doubling of the CO2 concentration level shows a significant increase of the NPP and turnover of plant tissues. The simulation with future climate scenarios shows consistent decrease in NPP but the uncertainties in projected NPP arising from selection of climate model and scenario is large.
Application of the malaria management model to the analysis of costs and benefits of DDT versus non-DDT malaria control.

PubMed

Pedercini, Matteo; Movilla Blanco, Santiago; Kopainsky, Birgit

2011-01-01

DDT is considered to be the most cost-effective insecticide for combating malaria. However, it is also the most environmentally persistent and can pose risks to human health when sprayed indoors. Therefore, the use of DDT for vector control remains controversial. In this paper we develop a computer-based simulation model to assess some of the costs and benefits of the continued use of DDT for Indoor Residual Spraying (IRS) versus its rapid phase out. We apply the prototype model to the aggregated sub Saharan African region. For putting the question about the continued use of DDT for IRS versus its rapid phase out into perspective we calculate the same costs and benefits for alternative combinations of integrated vector management interventions. Our simulation results confirm that the current mix of integrated vector management interventions with DDT as the main insecticide is cheaper than the same mix with alternative insecticides when only direct costs are considered. However, combinations with a stronger focus on insecticide-treated bed nets and environmental management show higher levels of cost-effectiveness than interventions with a focus on IRS. Thus, this focus would also allow phasing out DDT in a cost-effective manner. Although a rapid phase out of DDT for IRS is the most expensive of the tested intervention combinations it can have important economic benefits in addition to health and environmental impacts that are difficult to assess in monetary terms. Those economic benefits captured by the model include the avoided risk of losses in agricultural exports. The prototype simulation model illustrates how a computer-based scenario analysis tool can inform debates on malaria control policies in general and on the continued use of DDT for IRS versus its rapid phase out in specific. Simulation models create systematic mechanisms for analyzing alternative interventions and making informed trade offs.
Application of the Malaria Management Model to the Analysis of Costs and Benefits of DDT versus Non-DDT Malaria Control

PubMed Central

Pedercini, Matteo; Movilla Blanco, Santiago; Kopainsky, Birgit

2011-01-01

Introduction DDT is considered to be the most cost-effective insecticide for combating malaria. However, it is also the most environmentally persistent and can pose risks to human health when sprayed indoors. Therefore, the use of DDT for vector control remains controversial. Methods In this paper we develop a computer-based simulation model to assess some of the costs and benefits of the continued use of DDT for Indoor Residual Spraying (IRS) versus its rapid phase out. We apply the prototype model to the aggregated sub Saharan African region. For putting the question about the continued use of DDT for IRS versus its rapid phase out into perspective we calculate the same costs and benefits for alternative combinations of integrated vector management interventions. Results Our simulation results confirm that the current mix of integrated vector management interventions with DDT as the main insecticide is cheaper than the same mix with alternative insecticides when only direct costs are considered. However, combinations with a stronger focus on insecticide-treated bed nets and environmental management show higher levels of cost-effectiveness than interventions with a focus on IRS. Thus, this focus would also allow phasing out DDT in a cost-effective manner. Although a rapid phase out of DDT for IRS is the most expensive of the tested intervention combinations it can have important economic benefits in addition to health and environmental impacts that are difficult to assess in monetary terms. Those economic benefits captured by the model include the avoided risk of losses in agricultural exports. Conclusions The prototype simulation model illustrates how a computer-based scenario analysis tool can inform debates on malaria control policies in general and on the continued use of DDT for IRS versus its rapid phase out in specific. Simulation models create systematic mechanisms for analyzing alternative interventions and making informed trade offs. PMID:22140467
GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease.

PubMed

Bresso, Emmanuel; Togawa, Roberto; Hammond-Kosack, Kim; Urban, Martin; Maigret, Bernard; Martins, Natalia Florencio

2016-12-15

Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed. As several G-protein coupled receptors (GPCRs) are implicated in signaling pathways critical for the fungi development and survival, such proteins could be valuable efficient targets to reduce Fusarium growth and therefore to prevent food contamination. In this study, GPCRs were predicted in the FG proteome using a manually curated pipeline dedicated to the identification of GPCRs. Based on several successive filters, the most appropriate GPCR candidate target for developing new fungicides was selected. Searching for new compounds blocking this particular target requires the knowledge of its 3D-structure. As no experimental X-Ray structure of the selected protein was available, a 3D model was built by homology modeling. The model quality and stability was checked by 100 ns of molecular dynamics simulations. Two stable conformations representative of the conformational families of the protein were extracted from the 100 ns simulation and were used for an ensemble docking campaign. The model quality and stability was checked by 100 ns of molecular dynamics simulations previously to the virtual screening step. The virtual screening step comprised the exploration of a chemical library with 11,000 compounds that were docked to the GPCR model. Among these compounds, we selected the ten top-ranked nontoxic molecules proposed to be experimentally tested to validate the in silico simulation. This study provides an integrated process merging genomics, structural bioinformatics and drug design for proposing innovative solutions to a world wide threat to grain producers and consumers.
Anticipating the unintended consequences of security dynamics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Backus, George A.; Overfelt, James Robert; Malczynski, Leonard A.

2010-01-01

In a globalized world, dramatic changes within any one nation causes ripple or even tsunamic effects within neighbor nations and nations geographically far removed. Multinational interventions to prevent or mitigate detrimental changes can easily cause secondary unintended consequences more detrimental and enduring than the feared change instigating the intervention. This LDRD research developed the foundations for a flexible geopolitical and socioeconomic simulation capability that focuses on the dynamic national security implications of natural and man-made trauma for a nation-state and the states linked to it through trade or treaty. The model developed contains a database for simulating all 229 recognizedmore » nation-states and sovereignties with the detail of 30 economic sectors including consumers and natural resources. The model explicitly simulates the interactions among the countries and their governments. Decisions among governments and populations is based on expectation formation. In the simulation model, failed expectations are used as a key metric for tension across states, among ethnic groups, and between population factions. This document provides the foundational documentation for the model.« less
SPH-based numerical simulations of flow slides in municipal solid waste landfills.

PubMed

Huang, Yu; Dai, Zili; Zhang, Weijie; Huang, Maosong

2013-03-01

Most municipal solid waste (MSW) is disposed of in landfills. Over the past few decades, catastrophic flow slides have occurred in MSW landfills around the world, causing substantial economic damage and occasionally resulting in human victims. It is therefore important to predict the run-out, velocity and depth of such slides in order to provide adequate mitigation and protection measures. To overcome the limitations of traditional numerical methods for modelling flow slides, a mesh-free particle method entitled smoothed particle hydrodynamics (SPH) is introduced in this paper. The Navier-Stokes equations were adopted as the governing equations and a Bingham model was adopted to analyse the relationship between material stress rates and particle motion velocity. The accuracy of the model is assessed using a series of verifications, and then flow slides that occurred in landfills located in Sarajevo and Bandung were simulated to extend its applications. The simulated results match the field data well and highlight the capability of the proposed SPH modelling method to simulate such complex phenomena as flow slides in MSW landfills.
Decision making on fitness landscapes

NASA Astrophysics Data System (ADS)

Arthur, R.; Sibani, P.

2017-04-01

We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et al. that we call the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures.
a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems

NASA Astrophysics Data System (ADS)

Shao, Xiao; Chai, Li H.

As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.
Statistical, economic and other tools for assessing natural aggregate

USGS Publications Warehouse

Bliss, J.D.; Moyle, P.R.; Bolm, K.S.

2003-01-01

Quantitative aggregate resource assessment provides resource estimates useful for explorationists, land managers and those who make decisions about land allocation, which may have long-term implications concerning cost and the availability of aggregate resources. Aggregate assessment needs to be systematic and consistent, yet flexible enough to allow updating without invalidating other parts of the assessment. Evaluators need to use standard or consistent aggregate classification and statistic distributions or, in other words, models with geological, geotechnical and economic variables or interrelationships between these variables. These models can be used with subjective estimates, if needed, to estimate how much aggregate may be present in a region or country using distributions generated by Monte Carlo computer simulations.
Integration of Multiple Data Sources to Simulate the Dynamics of Land Systems

PubMed Central

Deng, Xiangzheng; Su, Hongbo; Zhan, Jinyan

2008-01-01

In this paper we present and develop a new model, which we have called Dynamics of Land Systems (DLS). The DLS model is capable of integrating multiple data sources to simulate the dynamics of a land system. Three main modules are incorporated in DLS: a spatial regression module, to explore the relationship between land uses and influencing factors, a scenario analysis module of the land uses of a region during the simulation period and a spatial disaggregation module, to allocate land use changes from a regional level to disaggregated grid cells. A case study on Taips County in North China is incorporated in this paper to test the functionality of DLS. The simulation results under the baseline, economic priority and environmental scenarios help to understand the land system dynamics and project near future land-use trajectories of a region, in order to focus management decisions on land uses and land use planning. PMID:27879726
Analysis and Comparison on the Flood Simulation in Typical Hilly & Semi-mountainous Region

NASA Astrophysics Data System (ADS)

Luan, Qinghua; Wang, Dong; Zhang, Xiang; Liu, Jiahong; Fu, Xiaoran; Zhang, Kun; Ma, Jun

2017-12-01

Water-logging and flood are both serious in hilly and semi-mountainous cities of China, but the related research is rare. Lincheng Economic Development Zone (EDZ) in Hebei Province as the typical city was selected and storm water management model (SWMM) was applied for flood simulation in this study. The regional model was constructed through calibrating and verifying the runoff coefficient of different flood processes. Different designed runoff processes in five-year, ten-year and twenty-year return periods in basic scenario and in the low impact development (LID) scenario, respectively, were simulated and compared. The result shows that: LID measures have effect on peak reduction in the study area, but the effectiveness is not significant; the effectiveness of lagging peak time is poor. These simulation results provide decision support for the rational construction of LID in the study area, and provide the references for regional rain flood management.
Urban Stormwater Management Model and Tools for Designing Stormwater Management of Green Infrastructure Practices

NASA Astrophysics Data System (ADS)

Haris, H.; Chow, M. F.; Usman, F.; Sidek, L. M.; Roseli, Z. A.; Norlida, M. D.

2016-03-01

Urbanization is growing rapidly in Malaysia. Rapid urbanization has known to have several negative impacts towards hydrological cycle due to decreasing of pervious area and deterioration of water quality in stormwater runoff. One of the negative impacts of urbanization is the congestion of the stormwater drainage system and this situation leading to flash flood problem and water quality degradation. There are many urban stormwater management softwares available in the market such as Storm Water Drainage System design and analysis program (DRAINS), Urban Drainage and Sewer Model (MOUSE), InfoWorks River Simulation (InfoWork RS), Hydrological Simulation Program-Fortran (HSPF), Distributed Routing Rainfall-Runoff Model (DR3M), Storm Water Management Model (SWMM), XP Storm Water Management Model (XPSWMM), MIKE-SWMM, Quality-Quantity Simulators (QQS), Storage, Treatment, Overflow, Runoff Model (STORM), and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS). In this paper, we are going to discuss briefly about several softwares and their functionality, accessibility, characteristics and components in the quantity analysis of the hydrological design software and compare it with MSMA Design Aid and Database. Green Infrastructure (GI) is one of the main topics that has widely been discussed all over the world. Every development in the urban area is related to GI. GI can be defined as green area build in the develop area such as forest, park, wetland or floodway. The role of GI is to improve life standard such as water filtration or flood control. Among the twenty models that have been compared to MSMA SME, ten models were selected to conduct a comprehensive review for this study. These are known to be widely accepted by water resource researchers. These ten tools are further classified into three major categories as models that address the stormwater management ability of GI in terms of quantity and quality, models that have the capability of conducting the economic analysis of GI and models that can address both stormwater management and economic aspects together.
Performance and driveline analyses of engine capacity in range extender engine hybrid vehicle

NASA Astrophysics Data System (ADS)

Praptijanto, Achmad; Santoso, Widodo Budi; Nur, Arifin; Wahono, Bambang; Putrasari, Yanuandri

2017-01-01

In this study, range extender engine designed should be able to meet the power needs of a power generator of hybrid electrical vehicle that has a minimum of 18 kW. Using this baseline model, the following range extenders will be compared between conventional SI piston engine (Baseline, BsL), engine capacity 1998 cm3, and efficiency-oriented SI piston with engine capacity 999 cm3 and 499 cm3 with 86 mm bore and stroke square gasoline engine in the performance, emission prediction of range extender engine, standard of charge by using engine and vehicle simulation software tools. In AVL Boost simulation software, range extender engine simulated from 1000 to 6000 rpm engine loads. The highest peak engine power brake reached up to 38 kW at 4500 rpm. On the other hand the highest torque achieved in 100 Nm at 3500 rpm. After that using AVL cruise simulation software, the model of range extended electric vehicle in series configuration with main components such as internal combustion engine, generator, electric motor, battery and the arthemis model rural road cycle was used to simulate the vehicle model. The simulation results show that engine with engine capacity 999 cm3 reported the economical performances of the engine and the emission and the control of engine cycle parameters.

Cyberwar XXI: quantifying the unquantifiable: adaptive AI for next-generation conflict simulations

NASA Astrophysics Data System (ADS)

Miranda, Joseph; von Kleinsmid, Peter; Zalewski, Tony

2004-08-01

The era of the "Revolution in Military Affairs," "4th Generation Warfare" and "Asymmetric War" requires novel approaches to modeling warfare at the operational and strategic level of modern conflict. For example, "What if, in response to our planned actions, the adversary reacts in such-and-such a manner? What will our response be? What are the possible unintended consequences?" Next generation conflict simulation tools are required to help create and test novel courses of action (COA's) in support of real-world operations. Conflict simulations allow non-lethal and cost-effective exploration of the "what-if" of COA development. The challenge has been to develop an automated decision-support software tool which allows competing COA"s to be compared in simulated dynamic environments. Principal Investigator Joseph Miranda's research is based on modeling an integrated military, economic, social, infrastructure and information (PMESII) environment. The main effort was to develop an adaptive AI engine which models agents operating within an operational-strategic conflict environment. This was implemented in Cyberwar XXI - a simulation which models COA selection in a PMESII environment. Within this framework, agents simulate decision-making processes and provide predictive capability of the potential behavior of Command Entities. The 2003 Iraq is the first scenario ready for V&V testing.
Impact of Nonmedical Vaccine Exemption Policies on the Health and Economic Burden of Measles.

PubMed

Whittington, Melanie D; Kempe, Allison; Dempsey, Amanda; Herlihy, Rachel; Campbell, Jonathan D

2017-07-01

Despite relatively high national vaccination coverage for measles, geographic vaccination variation exists resulting in clusters of susceptibility. A portion of this geographic variation can be explained by differences in state policies related to nonmedical vaccine exemptions. The objective of this analysis was to determine the magnitude, likelihood, and cost of a measles outbreak under different nonmedical vaccine exemption policies. An agent-based transmission model simulated the likelihood and magnitude of a measles outbreak under different nonmedical vaccine exemption policies, previously categorized as easy, medium, or difficult. The model accounted for measles herd immunity, infectiousness of the pathogen, vaccine efficacy, duration of incubation and communicable periods, acquired natural immunity, and the rate of recovery. Public health contact tracing was also modeled. Model outcomes, including the number of secondary cases, hospitalizations, and deaths, were monetized to determine the economic burden of the simulated outbreaks. A state with easy nonmedical vaccine exemption policies is 140% and 190% more likely to experience a measles outbreak compared with states with medium or difficult policies, respectively. The magnitude of these outbreaks can be reduced by half by strengthening exemption policies. These declines are associated with significant cost reductions to public health, the health care system, and the individual. Strengthening nonmedical vaccine exemption policies is 1 mechanism to increase vaccination coverage to reduce the health and economic effect of a measles outbreak. States exploring options for decreasing their vulnerability to outbreaks of vaccine-preventable diseases should consider more stringent requirements for nonmedical vaccine exemptions. Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.
Modeling and assessing international climate financing

NASA Astrophysics Data System (ADS)

Wu, Jing; Tang, Lichun; Mohamed, Rayman; Zhu, Qianting; Wang, Zheng

2016-06-01

Climate financing is a key issue in current negotiations on climate protection. This study establishes a climate financing model based on a mechanism in which donor countries set up funds for climate financing and recipient countries use the funds exclusively for carbon emission reduction. The burden-sharing principles are based on GDP, historical emissions, and consumptionbased emissions. Using this model, we develop and analyze a series of scenario simulations, including a financing program negotiated at the Cancun Climate Change Conference (2010) and several subsequent programs. Results show that sustained climate financing can help to combat global climate change. However, the Cancun Agreements are projected to result in a reduction of only 0.01°C in global warming by 2100 compared to the scenario without climate financing. Longer-term climate financing programs should be established to achieve more significant benefits. Our model and simulations also show that climate financing has economic benefits for developing countries. Developed countries will suffer a slight GDP loss in the early stages of climate financing, but the longterm economic growth and the eventual benefits of climate mitigation will compensate for this slight loss. Different burden-sharing principles have very similar effects on global temperature change and economic growth of recipient countries, but they do result in differences in GDP changes for Japan and the FSU. The GDP-based principle results in a larger share of financial burden for Japan, while the historical emissions-based principle results in a larger share of financial burden for the FSU. A larger burden share leads to a greater GDP loss.
Decision Support for Environmental Management of Industrial Non-Hazardous Secondary Materials: New Analytical Methods Combined with Simulation and Optimization Modeling

EPA Science Inventory

Non-hazardous solid materials from industrial processes, once regarded as waste and disposed in landfills, offer numerous environmental and economic advantages when put to beneficial uses (BUs). Proper management of these industrial non-hazardous secondary materials (INSM) requir...
An individual-based modeling approach to simulating recreation use in wilderness settings

Treesearch

Randy Gimblett; Terry Daniel; Michael J. Meitner

2000-01-01

Landscapes protect biological diversity and provide unique opportunities for human-nature interactions. Too often, these desirable settings suffer from extremely high visitation. Given the complexity of social, environmental and economic interactions, resource managers need tools that provide insights into the cause and effect relationships between management actions...
Marine and Hydrokinetic Research | Water Power | NREL

Science.gov Websites

. Resource Characterization and Maps NREL develops measurement systems, simulation tools, and web-based models and tools to evaluate the economic potential of power-generating devices for all technology Acceleration NREL analysts study the potential impacts that developing a robust MHK market could have on
The Behavioral and Social Sciences Survey: Economics.

ERIC Educational Resources Information Center

Ruggles, Nancy D., Ed.

This is one of a series in the Survey of the Behavioral and Social Sciences (BASS) conducted between 1967 and 1969. Three chapters of a general nature discuss the concerns of economists, professional organization, and research procedures (simulation, modeling, data needs, survey research, behavioral research, operations research), and the…
INTEGRATING STAKEHOLDER PERSPECTIVES IN A SYSTEMS APPROACH TO EXPLORING SUSTAINABLE SOLUTIONS: TRIPLE VALUE SIMULATION (3VS) MODELS IN COASTAL WATERSHEDS

EPA Science Inventory

Decision makers often need assistance in understanding the dynamic interactions and linkages among economic, environmental and social systems in coastal watersheds. They also need scientific input to better evaluate the potential costs and benefits of intervention options. The US...
Examining Long-Term Trends in Mobile Source Related Pollutants through Analysis of Emissions, Observations and Model Simulations

EPA Science Inventory

Anthropogenic emissions from a variety of sectors including mobile sources have decreased substantially over the past decades despite continued growth in population and economic activity. In this study, we analyze 1990-2010 trends in emission inventories, ambient observations and...
Sources of uncertainty in climate change impacts on groundwater recharge

NASA Astrophysics Data System (ADS)

Holman, I. P.

2007-12-01

This paper assesses the significance of the many sources of uncertainty in future groundwater recharge estimation, based on lessons learnt from an integrated approach to assessing the regional impacts of climate and socio-economic change on groundwater recharge in East Anglia, UK. Many factors affect simulations of future groundwater recharge including changed precipitation and temperature regimes, coastal flooding, urbanization, woodland establishment, and changes in cropping, rotations and management practices. Stochastic modelling of potential recharge showed median annual recharge decreasing under a High emissions future from 75 mm (1961-90) to 56 mm in the 2020s and 45 mm in the 2050s. However, the median values for individual simulations ranged from 46-75 mm (2020s) and 30-71 mm (2050s) highlighting a decreasing but uncertain trend. The impacts of (and uncertainty in) the climate scenarios are generally regionally more important than those of the socio-economic scenarios. However, locally, the impacts of the socio-economic scenarios can be significant, especially where there are large increases in urbanization, agricultural land cover, bioenergy production, or agricultural management practices. For example, management of soil conditions can increase potential groundwater recharge by around 5 %, but poor management can further reduce potential recharge by up to 15 %. The paper will demonstrate that to focus on the direct impacts of climate change is to neglect the potentially important role of policy, societal values and economic processes in shaping the landscape above aquifers. If the likely consequences of future changes of groundwater recharge, resulting from both climate and socio-economic change, are to be assessed, hydrogeologists must increasingly work with researchers from other disciplines, such as socio-economists, agricultural modellers and soil scientists
Simulation of transboundary pollutant transport action in the Pearl River delta.

PubMed

Chau, K W; Jiang, Y W

2003-09-01

The rapid economic development in The Pearl River delta region (PRDR) has exerted serious potential pollution threats to areas in the vicinity, which have complicated the task of environmental protection in Hong Kong and Macau. In this paper, a three-dimensional numerical pollutant transport model coupled with a synchronised numerical hydrodynamic model, is developed and employed to simulate the unsteady transport of a representative water quality variable chemical oxygen demand in The Pearl River Estuary. It is demonstrated that there exists a transboundary pollutant transport action between Guangdong Province and Hong Kong for the pollutants in the wastewater discharged from PRDR.
Mathematical Model of Seasonal Influenza with Treatment in Constant Population

NASA Astrophysics Data System (ADS)

Kharis, M.; Arifudin, R.

2017-04-01

Seasonal Influenza is one of disease that outbreaks periodically at least once every year. This disease caused many people hospitalized. Many hospitalized people as employers would infect production quantities, distribution time, and some economic aspects. It will infect economic growth. Infected people need treatments to reduce infection period and cure the infection. In this paper, we discussed about a mathematical model of seasonal influenza with treatment. Factually, the disease was held in short period, less than one year. Hence, we can assume that the population is constant at the disease outbreak time. In this paper, we analyzed the existence of the equilibrium points of the model and their stability. We also give some simulation to give a geometric image about the results of the analysis process.
The value of forage measurement information in rangeland management. [implementation of satellite data in range management

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1975-01-01

An economic model and simulation are developed to estimate the potential social benefit arising from the use of alternative measurement systems in rangeland management. In order to estimate these benefits, it was necessary to model three separate systems: the range environment, the rangeland manager, and the information system which links the two. The rancher's decision-making behavior is modeled according to sound economic principles. Results indicate substantial potential benefits, particularly when used in assisting management of government-operated ranges; possible annual benefits in this area range from $20 to $46 million, depending upon the system capabilities assumed. Possible annual benefit in privately-managed stocker operations range from $2.8 to $49.5 million, depending upon where actual rancher capabilities lie and what system capabilities are assumed.
Foraging optimally for home ranges

USGS Publications Warehouse

Mitchell, Michael S.; Powell, Roger A.

2012-01-01

Economic models predict behavior of animals based on the presumption that natural selection has shaped behaviors important to an animal's fitness to maximize benefits over costs. Economic analyses have shown that territories of animals are structured by trade-offs between benefits gained from resources and costs of defending them. Intuitively, home ranges should be similarly structured, but trade-offs are difficult to assess because there are no costs of defense, thus economic models of home-range behavior are rare. We present economic models that predict how home ranges can be efficient with respect to spatially distributed resources, discounted for travel costs, under 2 strategies of optimization, resource maximization and area minimization. We show how constraints such as competitors can influence structure of homes ranges through resource depression, ultimately structuring density of animals within a population and their distribution on a landscape. We present simulations based on these models to show how they can be generally predictive of home-range behavior and the mechanisms that structure the spatial distribution of animals. We also show how contiguous home ranges estimated statistically from location data can be misleading for animals that optimize home ranges on landscapes with patchily distributed resources. We conclude with a summary of how we applied our models to nonterritorial black bears (Ursus americanus) living in the mountains of North Carolina, where we found their home ranges were best predicted by an area-minimization strategy constrained by intraspecific competition within a social hierarchy. Economic models can provide strong inference about home-range behavior and the resources that structure home ranges by offering falsifiable, a priori hypotheses that can be tested with field observations.
State-and-transition models: Conceptual versus simulation perspectives, usefulness and breadth of use, and land management applications

USGS Publications Warehouse

Provencher, Louis; Frid, Leonardo; Czembor, Christina; Morisette, Jeffrey T.

2016-01-01

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.
Regional assessment of the hydropower potential of rivers in West Africa

NASA Astrophysics Data System (ADS)

Kling, Harald; Stanzel, Philipp; Fuchs, Martin

2016-04-01

The 15 countries of the Economic Community of West African States (ECOWAS) face a constant shortage of energy supply, which limits sustained economic growth. Currently there are about 50 operational hydropower plants and about 40 more are under construction or refurbishment. The potential for future hydropower development - especially for small-scale plants in rural areas - is assumed to be large, but exact data are missing. This study supports the energy initiatives of the "ECOWAS Centre for Renewable Energy and Energy Efficiency" (ECREEE) by assessing the hydropower potential of all rivers in West Africa. For more than 500,000 river reaches the hydropower potential was computed from channel slope and mean annual discharge. In large areas there is a lack of discharge observations. Therefore, an annual water balance model was used to simulate discharge. The model domain covers 5 Mio km², including e.g. the Niger, Volta, and Senegal River basins. The model was calibrated with observed data of 410 gauges, using precipitation and potential evapotranspiration data as inputs. Historic variations of observed annual discharge between 1950 and 2010 are simulated well by the model. As hydropower plants are investments with a lifetime of several decades we also assessed possible changes in future discharge due to climate change. To this end the water balance model was driven with bias-corrected climate projections of 15 Regional Climate Models for two emission scenarios of the CORDEX-Africa ensemble. The simulation results for the river network were up-scaled to sub-areas and national summaries. This information gives a regional quantification of the hydropower potential, expected climate change impacts, as well as a regional classification for general suitability (or non-suitability) of hydropower plant size - from small-scale to large projects.
SIMULATION AND VISUALIZATION OF FLOW PATTERN IN MICROARRAYS FOR LIQUID PHASE OLIGONUCLEOTIDE AND PEPTIDE SYNTHESIS

PubMed Central

O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

2008-01-01

Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053
Forecast-based interventions can reduce the health and economic burden of wildfires.

PubMed

Rappold, Ana G; Fann, Neal L; Crooks, James; Huang, Jin; Cascio, Wayne E; Devlin, Robert B; Diaz-Sanchez, David

2014-09-16

We simulated public health forecast-based interventions during a wildfire smoke episode in rural North Carolina to show the potential for use of modeled smoke forecasts toward reducing the health burden and showed a significant economic benefit of reducing exposures. Daily and county wide intervention advisories were designed to occur when fine particulate matter (PM2.5) from smoke, forecasted 24 or 48 h in advance, was expected to exceed a predetermined threshold. Three different thresholds were considered in simulations, each with three different levels of adherence to the advisories. Interventions were simulated in the adult population susceptible to health exacerbations related to the chronic conditions of asthma and congestive heart failure. Associations between Emergency Department (ED) visits for these conditions and daily PM2.5 concentrations under each intervention were evaluated. Triggering interventions at lower PM2.5 thresholds (≤ 20 μg/m(3)) with good compliance yielded the greatest risk reduction. At the highest threshold levels (50 μg/m(3)) interventions were ineffective in reducing health risks at any level of compliance. The economic benefit of effective interventions exceeded $1 M in excess ED visits for asthma and heart failure, $2 M in loss of productivity, $100 K in respiratory conditions in children, and $42 million due to excess mortality.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruth, M.; Pratt, A.; Lunacek, M.

The combination of distributed energy resources (DER) and retail tariff structures to provide benefits to both utility consumers and the utilities is not well understood. To improve understanding, an Integrated Energy System Model (IESM) is being developed to simulate the physical and economic aspects of DER technologies, the buildings where they reside, and feeders servicing them. The IESM was used to simulate 20 houses with home energy management systems on a single feeder under a time-of-use (TOU) tariff to estimate economic and physical impacts on both the households and the distribution utilities. Home energy management systems (HEMS) reduce consumers’ electricmore » bills by precooling houses in the hours before peak electricity pricing. Utilization of HEMS reduce peak loads during high price hours but shifts it to hours with off-peak and shoulder prices, resulting in a higher peak load. used to simulate 20 houses with home energy management systems on a single feeder under a time-of-use (TOU) tariff to estimate economic and physical impacts on both the households and the distribution utilities. Home energy management systems (HEMS) reduce consumers’ electric bills by precooling houses in the hours before peak electricity pricing. Utilization of HEMS reduce peak loads during high price hours but shifts it to hours with off-peak and shoulder prices, resulting in a higher peak load.« less
Projected climate change impacts on winter recreation in the ...

EPA Pesticide Factsheets

A physically-based water and energy balance model is used to simulate natural snow accumulation at 247 winter recreation locations across the continental United States. We combine this model with projections of snowmaking conditions to determine downhill skiing, cross-country skiing, and snowmobiling season lengths under baseline and future climates, using data from five climate models and two emissions scenarios. The present-day simulations from the snow model without snowmaking are validated with observations of snow-water-equivalent from snow monitoring sites. Projected season lengths are combined with baseline estimates of winter recreation activity to monetize impacts to the selected winter recreation activity categories for the years 2050 and 2090. Estimate the physical and economic impact of climate change on winter recreation in the contiguous U.S.

Integrating Climate Science, Marine Ecology, and Fisheries Economics to Predict the Effects of Climate Change on New England lobster Fisheries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Pershing, A. J.; Holland, D. S.; Mills, K.; Sun, C. H. J.

2016-02-01

The Gulf of Maine and the northwest Atlantic shelf have experienced one of the fastest warming rates of the global ocean over the past decade, and concerns are growing about the long-term sustainability of the fishing industries in the region. The lucrative American lobster fishery occurs over a steep temperature gradient, providing a unique opportunity to evaluate the consequences of climate change and variability on marine socio-ecological systems. This study aims at developing an integrated climate, population dynamics, and fishery economics model to predict consequences of climate change on the American lobster fishery. In this talk, we first describe a mechanistic model that combines life-history theory and a size-spectrum approach to simulate the dynamics of the population. Results show that as temperature increases, early growth rate and predation on small individuals increases, while size-at-maturity, maximum length and predation on large individuals decreases, resulting in a lower recruitment in the southern New-England and higher recruitment in the northern Gulf of Maine. Second, we present an integrated fishery and economic module that links temperature to landings and price through its influence on catchability and abundance. Preliminary results show that temperature is positively correlated with landings and negatively correlated with price in the Gulf of Maine. Finally, we discuss how model simulations under various fishing effort, market and climate scenarios can be used to identify adaptation opportunities to improve the resilience of the fishery to climate change.
Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation

PubMed Central

Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J.; Moore, Kenneth J.; Thorburn, Peter; Archontoulis, Sotirios V.

2016-01-01

Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR’s were within the historical N rate error range (40–50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability. PMID:27891133
Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation.

PubMed

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J; Moore, Kenneth J; Thorburn, Peter; Archontoulis, Sotirios V

2016-01-01

Improved prediction of optimal N fertilizer rates for corn ( Zea mays L. ) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean ( Glycine max L. ) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha -1 ) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha -1 ). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability.
Demographics, political power and economic growth.

PubMed

Holtz-eakin, D

1993-01-01

"Growth theory may be used to predict the response of saving, capital formation, and output growth to large demographic shifts. Such large shifts would also be expected to alter the demand for government services and the desired levels of taxation in the population. This paper extends the overlapping-generations model of economic growth to predict the evolution of government tax and spending policy through the course of a major demographic shift. Simulations suggest that this approach may yield valuable insights into the evolution of policy in the United States and other industrialized economies." excerpt
Threat in opportunity and opportunity in threat: energy prospects for Australia and New Zealand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nemetz, P.N.; Vertinsky, I.B.; Vertinsky, P.

A review of the determinants of energy policy options available to Australia and New Zealand compares their choices and assesses their long-term vulnerability to changes in the global energy situation. The authors use a cross-impact simulation model using six alternative scenarios of petroleum prices and world economic conditions. The results indicate that Australia is susceptible to short-run fluctuations, but its resource endowment is a stabilizing factor. New Zealand, however, is gambling its economic development on the increasing value of its resources.
Regional-scale yield simulations using crop and climate models: assessing uncertainties, sensitivity to temperature and adaptation options

NASA Astrophysics Data System (ADS)

Challinor, A. J.

2010-12-01

Recent progress in assessing the impacts of climate variability and change on crops using multiple regional-scale simulations of crop and climate (i.e. ensembles) is presented. Simulations for India and China used perturbed responses to elevated carbon dioxide constrained using observations from FACE studies and controlled environments. Simulations with crop parameter sets representing existing and potential future adapted varieties were also carried out. The results for India are compared to sensitivity tests on two other crop models. For China, a parallel approach used socio-economic data to account for autonomous farmer adaptation. Results for the USA analysed cardinal temperatures under a range of local warming scenarios for 2711 varieties of spring wheat. The results are as follows: 1. Quantifying and reducing uncertainty. The relative contribution of uncertainty in crop and climate simulation to the total uncertainty in projected yield changes is examined. The observational constraints from FACE and controlled environment studies are shown to be the likely critical factor in maintaining relatively low crop parameter uncertainty. Without these constraints, crop simulation uncertainty in a doubled CO2 environment would likely be greater than uncertainty in simulating climate. However, consensus across crop models in India varied across different biophysical processes. 2. The response of yield to changes in local mean temperature was examined and compared to that found in the literature. No consistent response to temperature change was found across studies. 3. Implications for adaptation. China. The simulations of spring wheat in China show the relative importance of tolerance to water and heat stress in avoiding future crop failures. The greatest potential for reducing the number of harvests less than one standard deviation below the baseline mean yield value comes from alleviating water stress; the greatest potential for reducing harvests less than two standard deviations below the mean comes from alleviation of heat stress. The socio-economic analysis suggests that adaptation is also possible through measures such as greater investment. India. The simulations of groundnut in India identified regions where heat stress will play an increasing role in limiting crop yields, and other regions where crops with greater thermal time requirement will be needed. The simulations were used, together with an observed dataset and a simple analysis of crop cardinal temperatures and thermal time, to estimate the potential for adaptation using existing cultivars. USA. Analysis of spring wheat in the USA showed that at +2oC of local warming, 87% of the 2711 varieties examined, and all of the five most common varieties, could be used to maintain the crop duration of the current climate (i.e. successful adaptation to mean warming). At +4o this fell to 54% of all varieties, and two of the top five. 4. Future research. The results, and the limitations of the study, suggest directions for research to link climate and crop models, socio-economic analyses and crop variety trial data in order to prioritise adaptation options such as capacity building, plant breeding and biotechnology.
Using economic instruments to develop effective management of invasive species: insights from a bioeconomic model.

PubMed

McDermott, Shana M; Irwin, Rebecca E; Taylor, Brad W

2013-07-01

Economic growth is recognized as an important factor associated with species invasions. Consequently, there is increasing need to develop solutions that combine economics and ecology to inform invasive species management. We developed a model combining economic, ecological, and sociological factors to assess the degree to which economic policies can be used to control invasive plants. Because invasive plants often spread across numerous properties, we explored whether property owners should manage invaders cooperatively as a group by incorporating the negative effects of invader spread in management decisions (collective management) or independently, whereby the negative effects of invasive plant spread are ignored (independent management). Our modeling approach used a dynamic optimization framework, and we applied the model to invader spread using Linaria vulgaris. Model simulations allowed us to determine the optimal management strategy based on net benefits for a range of invader densities. We found that optimal management strategies varied as a function of initial plant densities. At low densities, net benefits were high for both collective and independent management to eradicate the invader, suggesting the importance of early detection and eradication. At moderate densities, collective management led to faster and more frequent invader eradication compared to independent management. When we used a financial penalty to ensure that independent properties were managed collectively, we found that the penalty would be most feasible when levied on a property's perimeter boundary to control spread among properties. At the highest densities, the optimal management strategy was "do nothing" because the economic costs of removal were too high relative to the benefits of removal. Spatial variation in L. vulgaris densities resulted in different optimal management strategies for neighboring properties, making a formal economic policy to encourage invasive species removal critical. To accomplish the management and enforcement of these economic policies, we discuss modification of existing agencies and infrastructure. Finally, a sensitivity analysis revealed that lowering the economic cost of invader removal would strongly increase the probability of invader eradication. Taken together, our results provide quantitative insight into management decisions and economic policy instruments that can encourage invasive species removal across a social landscape.
Transforming Healthcare Delivery: Integrating Dynamic Simulation Modelling and Big Data in Health Economics and Outcomes Research.

PubMed

Marshall, Deborah A; Burgos-Liz, Lina; Pasupathy, Kalyan S; Padula, William V; IJzerman, Maarten J; Wong, Peter K; Higashi, Mitchell K; Engbers, Jordan; Wiebe, Samuel; Crown, William; Osgood, Nathaniel D

2016-02-01

In the era of the Information Age and personalized medicine, healthcare delivery systems need to be efficient and patient-centred. The health system must be responsive to individual patient choices and preferences about their care, while considering the system consequences. While dynamic simulation modelling (DSM) and big data share characteristics, they present distinct and complementary value in healthcare. Big data and DSM are synergistic-big data offer support to enhance the application of dynamic models, but DSM also can greatly enhance the value conferred by big data. Big data can inform patient-centred care with its high velocity, volume, and variety (the three Vs) over traditional data analytics; however, big data are not sufficient to extract meaningful insights to inform approaches to improve healthcare delivery. DSM can serve as a natural bridge between the wealth of evidence offered by big data and informed decision making as a means of faster, deeper, more consistent learning from that evidence. We discuss the synergies between big data and DSM, practical considerations and challenges, and how integrating big data and DSM can be useful to decision makers to address complex, systemic health economics and outcomes questions and to transform healthcare delivery.
Organic dairy production systems in Pennsylvania: a case study evaluation.

PubMed

Rotz, C A; Kamphuis, G H; Karsten, H D; Weaver, R D

2007-08-01

The current market demand and price for organic milk is encouraging dairy producers, particularly those on smaller farms, to consider organic production as a means for improving the economic viability of their operations. Organic production systems vary widely in scale, in practices, and across agroclimatic settings. Within this context, case studies of 4 actual organic dairy farms were used to characterize existing systems in Pennsylvania. Based on data from these farms, a whole-farm simulation model (Integrated Farm System Model) was used to compare 4 production systems representing organic grass, organic crop, conventional crop with grazing, and conventional confinement production. The performance of each of these systems was simulated over each year of 25 yr of central Pennsylvania weather data. Simulation results indicated that farm level accumulation of soil P and K may be a concern on organic farms that use poultry manure as a primary crop nutrient source, and that erosion and runoff loss of P may be of concern on organic farms producing annual crops because more tillage is required for weed control. Whole-farm budgets with prices that reflect recent conditions showed an economic advantage for organic over conventional production. A sensitivity analysis showed that this economic advantage depended on a higher milk price for producers of organic milk and was influenced by the difference in milk production maintained by herds using organic and conventional systems. Factors found to have little effect on the relative profitability of organic over conventional production included the differences between organic and conventional prices for seed, chemicals, forage, and animals and the overall costs or prices assumed for organic certification, machinery, pasture fencing, fuel, and labor. Thus, at the current organic milk price, relative to other prices, the case study organic production systems seem to provide an option for improving the economic viability of dairy operations of the scale considered in Pennsylvania. To motivate transition to organic systems, the economic advantage found requires the persistence of a substantial difference between conventional and organic raw milk prices.
Calibrating and testing a gap model for simulating forest management in the Oregon Coast Range

USGS Publications Warehouse

Pabst, R.J.; Goslin, M.N.; Garman, S.L.; Spies, T.A.

2008-01-01

The complex mix of economic and ecological objectives facing today's forest managers necessitates the development of growth models with a capacity for simulating a wide range of forest conditions while producing outputs useful for economic analyses. We calibrated the gap model ZELIG to simulate stand-level forest development in the Oregon Coast Range as part of a landscape-scale assessment of different forest management strategies. Our goal was to incorporate the predictive ability of an empirical model with the flexibility of a forest succession model. We emphasized the development of commercial-aged stands of Douglas-fir, the dominant tree species in the study area and primary source of timber. In addition, we judged that the ecological approach of ZELIG would be robust to the variety of other forest conditions and practices encountered in the Coast Range, including mixed-species stands, small-scale gap formation, innovative silvicultural methods, and reserve areas where forests grow unmanaged for long periods of time. We parameterized the model to distinguish forest development among two ecoregions, three forest types and two site productivity classes using three data sources: chronosequences of forest inventory data, long-term research data, and simulations from an empirical growth-and-yield model. The calibrated model was tested with independent, long-term measurements from 11 Douglas-fir plots (6 unthinned, 5 thinned), 3 spruce-hemlock plots, and 1 red alder plot. ZELIG closely approximated developmental trajectories of basal area and large trees in the Douglas-fir plots. Differences between simulated and observed conifer basal area for these plots ranged from -2.6 to 2.4 m2/ha; differences in the number of trees/ha ???50 cm dbh ranged from -8.8 to 7.3 tph. Achieving these results required the use of a diameter-growth multiplier, suggesting some underlying constraints on tree growth such as the temperature response function. ZELIG also tended to overestimate regeneration of shade-tolerant trees and underestimate total tree density (i.e., higher rates of tree mortality). However, comparisons with the chronosequences of forest inventory data indicated that the simulated data are within the range of variability observed in the Coast Range. Further exploration and improvement of ZELIG is warranted in three key areas: (1) modeling rapid rates of conifer tree growth without the need for a diameter-growth multiplier; (2) understanding and remedying rates of tree mortality that were higher than those observed in the independent data; and (3) improving the tree regeneration module to account for competition with understory vegetation. ?? 2008 Elsevier B.V.
Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations

PubMed Central

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. PMID:27010692
Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

PubMed

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.
Simulation models and designs for advanced Fischer-Tropsch technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, G.N.; Kramer, S.J.; Tam, S.S.

1995-12-31

Process designs and economics were developed for three grass-roots indirect Fischer-Tropsch coal liquefaction facilities. A baseline and an alternate upgrading design were developed for a mine-mouth plant located in southern Illinois using Illinois No. 6 coal, and one for a mine-mouth plane located in Wyoming using Power River Basin coal. The alternate design used close-coupled ZSM-5 reactors to upgrade the vapor stream leaving the Fischer-Tropsch reactor. ASPEN process simulation models were developed for all three designs. These results have been reported previously. In this study, the ASPEN process simulation model was enhanced to improve the vapor/liquid equilibrium calculations for themore » products leaving the slurry bed Fischer-Tropsch reactors. This significantly improved the predictions for the alternate ZSM-5 upgrading design. Another model was developed for the Wyoming coal case using ZSM-5 upgrading of the Fischer-Tropsch reactor vapors. To date, this is the best indirect coal liquefaction case. Sensitivity studies showed that additional cost reductions are possible.« less
Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.
Development and Implications of a Predictive Cost Methodology for Modular Pumped Storage Hydropower (m-PSH) Projects in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Witt, Adam; Chalise, Dol Raj; Hadjerioua, Boualem

The slow pace of Pumped Storage Hydropower development in the US over the past twenty years has led to widespread interest in the feasibility and viability of alternative PSH designs, development schemes, and technologies. Since 2011, Oak Ridge National Lab has been exploring the economic viability of modular Pumped Storage Hydropower (m-PSH) development through targeted case studies, revenue simulations, and analysis of innovative configurations and designs. This paper outlines the development and supporting analysis of a scalable, comprehensive cost modeling tool designed to simulate the initial capital costs for a variety of potential m-PSH projects and deployment scenarios. The toolmore » is used to explore and determine innovative research strategies that can improve the economic viability of m-PSH in US markets.« less
How severe space weather can disrupt global supply chains

NASA Astrophysics Data System (ADS)

Schulte in den Bäumen, H.; Moran, D.; Lenzen, M.; Cairns, I.; Steenge, A.

2014-10-01

Coronal mass ejections (CMEs) strong enough to create electromagnetic effects at latitudes below the auroral oval are frequent events that could soon have substantial impacts on electrical grids. Modern society's heavy reliance on these domestic and international networks increases our susceptibility to such a severe space-weather event. Using a new high-resolution model of the global economy, we simulate the economic impact of strong CMEs for three different planetary orientations. We account for the economic impacts within the countries directly affected, as well as the post-disaster economic shock in partner economies linked by international trade. For a 1989 Quebec-like event, the global economic impacts would range from USD 2.4 to 3.4 trillion over a year. Of this total economic shock, about 50% would be felt in countries outside the zone of direct impact, leading to a loss in global Gross Domestic Product (GDP) of 3.9 to 5.6%. The global economic damage is of the same order as wars, extreme financial crisis and estimated for future climate change.
How severe Space Weather can disrupt global supply chains

NASA Astrophysics Data System (ADS)

Schulte in den Bäumen, H.; Moran, D.; Lenzen, M.; Cairns, I.; Steenge, A.

2014-06-01

Coronal mass ejections (CMEs) strong enough to create electromagnetic effects at latitudes below the auroral oval are frequent events that could soon have substantial impacts on electrical grids. Modern society's heavy reliance on these domestic and international networks increases our susceptibility to such a severe space weather event. Using a new high-resolution model of the global economy we simulate the economic impact of strong CMEs for 3 different planetary orientations. We account for the economic impacts within the countries directly affected as well as the post-disaster economic shock in partner economies linked by international trade. For a 1989 Quebec-like event the global economic impacts would range from USD 2.4 to 3.4 trillion over a year. Of this total economic shock about 50% would be felt in countries outside the zone of direct impact, leading to a loss in global GDP of 3.9 to 5.6%. The global economic damages are of the same order as wars, extreme financial crisis and estimated for future climate change.
Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Epiney, Aaron Simon; Chen, Jun; Rabiti, Cristian

Continued effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year (FY) 2016. The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status of their progress. Several tasks have been accomplished. First, a synthetic time history generator has been developed in RAVEN, which consists of Fourier series and autoregressive moving average model. The former is used to capture the seasonal trend in historical data, while the latter is to characterizemore » the autocorrelation in residue time series (e.g., measurements with seasonal trends subtracted). As demonstration, both synthetic wind speed and grid demand are generated, showing matching statistics with database. In order to build a design and operations optimizer in RAVEN, a new type of sampler has been developed with highly object-oriented design. In particular, simultaneous perturbation stochastic approximation algorithm is implemented. The optimizer is capable to drive the model to optimize a scalar objective function without constraint in the input space, while the constraints handling is a work in progress and will be implemented to improve the optimization capability. Furthermore, a simplified cash flow model of the performance of an NHES in the electric market has been developed in Python and used as external model in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces. Finally, an example calculation is performed that shows the integration and proper data passing in RAVEN of the synthetic time history generator, the cash flow model and the optimizer. It has been shown that the developed Python models external to RAVEN are able to communicate with RAVEN and each other through the newly developed RAVEN capability called “EnsembleModel”.« less
A New Approach for Simulating Galaxy Cluster Properties

NASA Astrophysics Data System (ADS)

Arieli, Y.; Rephaeli, Y.; Norman, M. L.

2008-08-01

We describe a subgrid model for including galaxies into hydrodynamical cosmological simulations of galaxy cluster evolution. Each galaxy construct—or galcon—is modeled as a physically extended object within which star formation, galactic winds, and ram pressure stripping of gas are modeled analytically. Galcons are initialized at high redshift (z ~ 3) after galaxy dark matter halos have formed but before the cluster has virialized. Each galcon moves self-consistently within the evolving cluster potential and injects mass, metals, and energy into intracluster (IC) gas through a well-resolved spherical interface layer. We have implemented galcons into the Enzo adaptive mesh refinement code and carried out a simulation of cluster formation in a ΛCDM universe. With our approach, we are able to economically follow the impact of a large number of galaxies on IC gas. We compare the results of the galcon simulation with a second, more standard simulation where star formation and feedback are treated using a popular heuristic prescription. One advantage of the galcon approach is explicit control over the star formation history of cluster galaxies. Using a galactic SFR derived from the cosmic star formation density, we find the galcon simulation produces a lower stellar fraction, a larger gas core radius, a more isothermal temperature profile, and a flatter metallicity gradient than the standard simulation, in better agreement with observations.
Computer simulation models of pre-diabetes populations: a systematic review protocol

PubMed Central

Khurshid, Waqar; Pagano, Eva; Feenstra, Talitha

2017-01-01

Introduction Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations. Methods and analysis A systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status. Ethics and dissemination This systematic review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences. Reviewregistration number CRD42016047228. PMID:28982807

The Distributed Geothermal Market Demand Model (dGeo): Documentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCabe, Kevin; Mooney, Meghan E; Sigrin, Benjamin O

The National Renewable Energy Laboratory (NREL) developed the Distributed Geothermal Market Demand Model (dGeo) as a tool to explore the potential role of geothermal distributed energy resources (DERs) in meeting thermal energy demands in the United States. The dGeo model simulates the potential for deployment of geothermal DERs in the residential and commercial sectors of the continental United States for two specific technologies: ground-source heat pumps (GHP) and geothermal direct use (DU) for district heating. To quantify the opportunity space for these technologies, dGeo leverages a highly resolved geospatial database and robust bottom-up, agent-based modeling framework. This design is consistentmore » with others in the family of Distributed Generation Market Demand models (dGen; Sigrin et al. 2016), including the Distributed Solar Market Demand (dSolar) and Distributed Wind Market Demand (dWind) models. dGeo is intended to serve as a long-term scenario-modeling tool. It has the capability to simulate the technical potential, economic potential, market potential, and technology deployment of GHP and DU through the year 2050 under a variety of user-defined input scenarios. Through these capabilities, dGeo can provide substantial analytical value to various stakeholders interested in exploring the effects of various techno-economic, macroeconomic, financial, and policy factors related to the opportunity for GHP and DU in the United States. This report documents the dGeo modeling design, methodology, assumptions, and capabilities.« less
Annual economic impacts of seasonal influenza on US counties: Spatial heterogeneity and patterns

PubMed Central

2012-01-01

Economic impacts of seasonal influenza vary across US counties, but little estimation has been conducted at the county level. This research computed annual economic costs of seasonal influenza for 3143 US counties based on Census 2010, identified inherent spatial patterns, and investigated cost-benefits of vaccination strategies. The computing model modified existing methods for national level estimation, and further emphasized spatial variations between counties, in terms of population size, age structure, influenza activity, and income level. Upon such a model, four vaccination strategies that prioritize different types of counties were simulated and their net returns were examined. The results indicate that the annual economic costs of influenza varied from $13.9 thousand to $957.5 million across US counties, with a median of $2.47 million. Prioritizing vaccines to counties with high influenza attack rates produces the lowest influenza cases and highest net returns. This research fills the current knowledge gap by downscaling the estimation to a county level, and adds spatial variability into studies of influenza economics and interventions. Compared to the national estimates, the presented statistics and maps will offer detailed guidance for local health agencies to fight against influenza. PMID:22594494
School-Based Influenza Vaccination: Health and Economic Impact of Maine's 2009 Influenza Vaccination Program.

PubMed

Basurto-Dávila, Ricardo; Meltzer, Martin I; Mills, Dora A; Beeler Asay, Garrett R; Cho, Bo-Hyun; Graitcer, Samuel B; Dube, Nancy L; Thompson, Mark G; Patel, Suchita A; Peasah, Samuel K; Ferdinands, Jill M; Gargiullo, Paul; Messonnier, Mark; Shay, David K

2017-12-01

To estimate the societal economic and health impacts of Maine's school-based influenza vaccination (SIV) program during the 2009 A(H1N1) influenza pandemic. Primary and secondary data covering the 2008-09 and 2009-10 influenza seasons. We estimated weekly monovalent influenza vaccine uptake in Maine and 15 other states, using difference-in-difference-in-differences analysis to assess the program's impact on immunization among six age groups. We also developed a health and economic Markov microsimulation model and conducted Monte Carlo sensitivity analysis. We used national survey data to estimate the impact of the SIV program on vaccine coverage. We used primary data and published studies to develop the microsimulation model. The program was associated with higher immunization among children and lower immunization among adults aged 18-49 years and 65 and older. The program prevented 4,600 influenza infections and generated $4.9 million in net economic benefits. Cost savings from lower adult vaccination accounted for 54 percent of the economic gain. Economic benefits were positive in 98 percent of Monte Carlo simulations. SIV may be a cost-beneficial approach to increase immunization during pandemics, but programs should be designed to prevent lower immunization among nontargeted groups. © Health Research and Educational Trust.
To Simulate or Not to Simulate? Bridging the Gap from Classroom to Profession. College Teaching Monograph.

ERIC Educational Resources Information Center

Markovich, Denise

A simulation game being used in the economics department at the University of North Dakota to introduce students to the world of banking is described. The rationale for this approach is that the economics curriculum tends to be more conceptual than practical in content, and provides limited internship opportunities. The simulation game approach…
Eastern Renewable Generation Integration Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bloom, Aaron; Townsend, Aaron; Palchak, David

2016-08-01

The Eastern Interconnection (EI) is one of the largest power systems in the world, and its size and complexity have historically made it difficult to study in high levels of detail in a modeling environment. In order to understand how this system might be impacted by high penetrations (30% of total annual generation) of wind and solar photovoltaic (PV) during steady state operations, the National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy (DOE) conducted the Eastern Renewable Generation Integration Study (ERGIS). This study investigates certain aspects of the reliability and economic efficiency problem faced by power systemmore » operators and planners. Specifically, the study models the ability to meet electricity demand at a 5-minute time interval by scheduling resources for known ramping events, while maintaining adequate reserves to meet random variation in supply and demand, and contingency events. To measure the ability to meet these requirements, a unit commitment and economic dispatch (UC&ED) model is employed to simulate power system operations. The economic costs of managing this system are presented using production costs, a traditional UC&ED metric that does not include any consideration of long-term fixed costs. ERGIS simulated one year of power system operations to understand regional and sub-hourly impacts of wind and PV by developing a comprehensive UC&ED model of the EI. In the analysis, it is shown that, under the study assumptions, generation from approximately 400 GW of combined wind and PV capacity can be balanced on the transmission system at a 5-minute level. In order to address the significant computational burdens associated with a model of this detail we apply novel computing techniques to dramatically reduce simulation solve time while simultaneously increasing the resolution and fidelity of the analysis. Our results also indicate that high penetrations of wind and PV (collectively variable generation (VG)), significantly impact the operation of traditional generating resources and cause these resources to be used less frequently and operate across a broader output range because wind and PV have lower operating costs and variable output levels.« less
Teacher's Guide for "Tightrope," a Simulation Game in Economics.

ERIC Educational Resources Information Center

Baskind, Larry; And Others

"Tightrope" is a simulation based on economic stability and growth in a country. Several small groups of students, acting as Economic Advisory Councils, make fiscal and monetary policy decisions for their country based on their knowledge of business cycles, monetary policy, and fiscal policy. In each of the four rounds the Advisory Councils study…
DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, La Tonya Nicole; Malczynski, Leonard A.

DYNAMO is a computer program for building and running 'continuous' simulation models. It was developed by the Industrial Dynamics Group at the Massachusetts Institute of Technology for simulating dynamic feedback models of business, economic, and social systems. The history of the system dynamics method since 1957 includes many classic models built in DYANMO. It was not until the late 1980s that software was built to take advantage of the rise of personal computers and graphical user interfaces that DYNAMO was supplanted. There is much learning and insight to be gained from examining the DYANMO models and their accompanying research papers.more » We believe that it is a worthwhile exercise to convert DYNAMO models to more recent software packages. We have made an attempt to make it easier to turn these models into a more current system dynamics software language, Powersim © Studio produced by Powersim AS 2 of Bergen, Norway. This guide shows how to convert DYNAMO syntax into Studio syntax.« less
Short communication: economics of sex-biased milk production.

PubMed

Ettema, J F; Østergaard, S

2015-02-01

In a recent data study using 2.4 million lactations of 1.5 million cows, it was reported that gestation of a female calf in the first parity increases cumulative milk production by approximately 445kg over the first 2 lactations. The reported effect in this study is large and remarkable because it has not been found before. To our knowledge, the economic implications of this or any other sex bias have not been studied. The objective of the current study was to quantify the reported influence of fetal sex across lactations by using a simulation model of a dairy herd including youngstock. Two scenarios were evaluated and compared with a scenario in which cows and heifers were exclusively bred with conventional (nonsexed) semen. In the first scenario, sexed semen was used moderately-on 30% of all heifers and 30% of the first parity cows. A second scenario was studied in which sexed semen was used intensively-on all heifers and 50% of the first-parity cows. The simulated proportion of cows giving birth to 2 consecutive heifers increased from 23% when using exclusively conventional semen up to 31 and 48% when using sexed semen moderately and intensively, respectively. The proportion of cows having 2 consecutive bulls decreased from 27% (conventional semen only) to 20 and 8% when using sexed semen moderately and intensively, respectively. When incorporating the sex bias in the simulation model, the simulated milk yield in the scenario in which sexed semen was used moderately increased by 48kg of energy-corrected milk (ECM) per cow/yr, compared with only 36kg of ECM when not incorporating the sex bias in the model. For the scenario in which sexed semen was used intensively, milk yield increased by 66 and 99kg of ECM when excluding and including the sex bias, respectively. The economic implications of the assumed sex bias were €4.0 and €9.9 per cow/yr, in the scenarios in which sexed semen was used moderately and intensively, respectively. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Simulating crop yield losses in Switzerland for historical and present Tambora climate scenarios

NASA Astrophysics Data System (ADS)

Flückiger, Simon; Brönnimann, Stefan; Holzkämper, Annelie; Fuhrer, Jürg; Krämer, Daniel; Pfister, Christian; Rohr, Christian

2017-07-01

Severe climatic anomalies in summer 1816, partly due to the eruption of Tambora in April 1815, contributed to delayed growth and poor harvests of important crops in Central Europe. Coinciding with adverse socio-economic conditions, this event triggered the last subsistence crisis in the western World. Here, we model reductions in potential crop yields for 1816 and 1817 and address the question, what impact a similar climatic anomaly would have today. We reconstructed daily weather for Switzerland for 1816/17 on a 2 km grid using historical observations and an analogue resampling method. These data were used to simulate potential crop yields for potato, grain maize, and winter barley using the CropSyst model calibrated for current crop cultivars. We also simulated yields for the same weather anomalies, but referenced to a present-day baseline temperature. Results show that reduced temperature delayed growth and harvest considerably, and in combination with reduced solar irradiance led to a substantial reduction (20%-50%) in the potential yield of potato in 1816. Effects on winter barley were smaller. Significant reductions were also modelled for 1817 and were mainly due to a cold late spring. Relative reductions for the present-day scenario for the two crops were almost indistinguishable from the historical ones. An even stronger response was found for maize, which was not yet common in 1816/17. Waterlogging, which we assessed using a stress-day approach, likely added to the simulated reductions. The documented, strong east-west gradient in malnutrition across Switzerland in 1817/18 could not be explained by biophysical yield limitations (though excess-water limitation might have contributed), but rather by economic, political and social factors. This highlights the importance of these factors for a societies’ ability to cope with extreme climate events. While the adaptive capacity of today’s society in Switzerland is much greater than in the early 19th century, our results emphasize the need for interdisciplinary approaches to climate change adaptation considering not only biophysical, but also social, economic and political aspects.
A model of urban scaling laws based on distance dependent interactions

NASA Astrophysics Data System (ADS)

Ribeiro, Fabiano L.; Meirelles, Joao; Ferreira, Fernando F.; Neto, Camilo Rodrigues

2017-03-01

Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log-log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.
A model of urban scaling laws based on distance dependent interactions.

PubMed

Ribeiro, Fabiano L; Meirelles, Joao; Ferreira, Fernando F; Neto, Camilo Rodrigues

2017-03-01

Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log-log plot, the so-called superlinear scaling . Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.
HIV/AIDS, growth and poverty in KwaZulu-Natal and South Africa: an integrated survey, demographic and economy-wide analysis

PubMed Central

2009-01-01

Background This paper estimates the economic impact of HIV/AIDS on the KwaZulu-Natal province and the rest of South Africa. Methods We extended previous studies by employing: an integrated analytical framework that combined firm surveys of workers' HIV prevalence by sector and occupation; a demographic model that produced both population and workforce projections; and a regionalized economy-wide model linked to a survey-based micro-simulation module. This framework permits a full macro-microeconomic assessment. Results Results indicate that HIV/AIDS greatly reduces annual economic growth, mainly by lowering the long-run rate of technical change. However, impacts on income poverty are small, and inequality is reduced by HIV/AIDS. This is because high unemployment among low-income households minimises the economic costs of increased mortality. By contrast, slower economic growth hurts higher income households despite lower HIV prevalence. Conclusion We conclude that the increase in economic growth that results from addressing HIV/AIDS is sufficient to offset the population pressure placed on income poverty. Moreover, incentives to mitigate HIV/AIDS lie not only with poorer infected households, but also with uninfected higher income households. Our findings reveal the substantial burden that HIV/AIDS places on future economic development in KwaZulu-Natal and South Africa, and confirms the need for policies to curb the economic costs of the pandemic. PMID:19758444
Assessing the impacts of 1.5°C of global warming - The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) approach

NASA Astrophysics Data System (ADS)

Zhao, F.; Frieler, K.; Warszawski, L.; Lange, S.; Schewe, J.; Reyer, C.; Ostberg, S.; Piontek, F.; Betts, R. A.; Burke, E.; Ciais, P.; Deryng, D.; Ebi, K. L.; Emanuel, K.; Elliott, J. W.; Galbraith, E. D.; Gosling, S.; Hickler, T.; Hinkel, J.; Jones, C.; Krysanova, V.; Lotze-Campen, H.; Mouratiadou, I.; Popp, A.; Tian, H.; Tittensor, D.; Vautard, R.; van Vliet, M. T. H.; Eddy, T.; Hattermann, F.; Huber, V.; Mengel, M.; Stevanovic, M.; Kirsten, T.; Mueller Schmied, H.; Denvil, S.; Halladay, K.; Suzuki, T.; Lotze, H. K.

2016-12-01

In Paris, France, December 2015 the Conference of Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the IPCC to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016 the IPCC panel accepted the invitation. Here we describe the model simulations planned within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to address the request by providing tailored cross-sectoral consistent impacts projections. The protocol is designed to allow for 1) a separation of the impacts of the historical warming starting from pre-industrial conditions from other human drivers such as historical land use changes (based on pre-industrial and historical impact model simulations), 2) a quantification of the effects of an additional warming to 1.5°C including a potential overshoot and long term effects up to 2300 in comparison to a no-mitigation scenario (based on the low emissions Representative Concentration Pathway RCP2.6 and a no-mitigation scenario RCP6.0) keeping socio-economic conditions fixed at year 2005 levels, and 3) an assessment of the climate effects based on the same climate scenarios but accounting for parallel changes in socio-economic conditions following the middle of the road Shared Socioeconomic Pathway (SSP2) and differential bio-energy requirements associated with the transformation of the energy system to reach RCP2.6 compared to RCP6.0. To provide the scientific basis for an aggregation of impacts across sectors and an analysis of cross-sectoral interactions potentially damping or amplifying sectoral impacts the protocol is designed to provide consistent impacts projections across a range of impact models from different sectors (global and regional hydrological models, global gridded crop models, global vegetation models, regional forestry models, global and regional marine ecosystem and fisheries models, global and regional coastal infrastructure models, energy models, health models, and agro-economic models).
Assessing the impacts of 1.5°C of global warming - The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) approach

NASA Astrophysics Data System (ADS)

Frieler, Katja; Warszawski, Lila; Zhao, Fang

2017-04-01

In Paris, France, December 2015 the Conference of Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the IPCC to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016 the IPCC panel accepted the invitation. Here we describe the model simulations planned within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to address the request by providing tailored cross-sectoral consistent impacts projections. The protocol is designed to allow for 1) a separation of the impacts of the historical warming starting from pre-industrial conditions from other human drivers such as historical land use changes (based on pre-industrial and historical impact model simulations), 2) a quantification of the effects of an additional warming to 1.5°C including a potential overshoot and long term effects up to 2300 in comparison to a no-mitigation scenario (based on the low emissions Representative Concentration Pathway RCP2.6 and a no-mitigation scenario RCP6.0) keeping socio-economic conditions fixed at year 2005 levels, and 3) an assessment of the climate effects based on the same climate scenarios but accounting for parallel changes in socio-economic conditions following the middle of the road Shared Socioeconomic Pathway (SSP2) and differential bio-energy requirements associated with the transformation of the energy system to reach RCP2.6 compared to RCP6.0. To provide the scientific basis for an aggregation of impacts across sectors and an analysis of cross-sectoral interactions potentially damping or amplifying sectoral impacts the protocol is designed to provide consistent impacts projections across a range of impact models from different sectors (global and regional hydrological models, global gridded crop models, global vegetation models, regional forestry models, global and regional marine ecosystem and fisheries models, global and regional coastal infrastructure models, energy models, health models, and agro-economic models).
Ho Chi Minh City adaptation to increasing risk of coastal and fluvial floods

NASA Astrophysics Data System (ADS)

Scussolini, Paolo; Lasage, Ralph

2016-04-01

Coastal megacities in southeast Asia are a hotspot of vulnerability to floods. In such contexts, the combination of fast socio-economic development and of climate change impacts on precipitation and sea level generates concerns about the flood damage to people and assets. This work focuses on Ho Chi Minh City, Vietnam, for which we estimate the present and future direct risk from river and coastal floods. A model cascade is used that comprises the Saigon river basin and the urban network, plus the land-use-dependent damaging process. Changes in discharge for five return periods are simulated, enabling the probabilistic calculation of the expected annual economic damage to assets, for differnt scenarios of global emissions, local socio-economic growth, and land subsidence, up to year 2100. The implementation of a range of adaptation strategies is simulated, including building dykes, elevating, creating reservoirs, managing water and sediment upstream, flood-proofing, halting groundwater abstraction. Results are presented on 1) the relative weight of each future driver in determining the flood risk of Ho Chi Minh, and 2) the efficiency and feasibility of each adaptation strategy.
Simulating Water Resource Disputes of Transboundary River: A Case Study of the Zhanghe River Basin, China

NASA Astrophysics Data System (ADS)

Yuan, Liang; He, Weijun; Liao, Zaiyi; Mulugeta Degefu, Dagmawi; An, Min; Zhang, Zhaofang

2018-01-01

Water resource disputes within transboundary river basin has been hindering the sustainable use of water resources and efficient management of environment. The problem is characterized by a complex information feedback loop that involves socio-economic and environmental systems. This paper presents a system dynamics based model that can simulate the dynamics of water demand, water supply, water adequacy and water allocation instability within a river basin. It was used for a case study in the Zhanghe River basin of China. The base scenario has been investigated for the time period between 2000 and 2050. The result shows that the Chinese national government should change the water allocation scheme of downstream Zhanghe River established in 1989, more water need to be allocated to the downstream cities and the actual allocation should be adjusted to reflect the need associated with the socio-economic and environmental changes within the region, and system dynamics improves the understanding of concepts and system interactions by offering a comprehensive and integrated view of the physical, social, economic, environmental, and political systems.
Raising taxes to reduce smoking prevalence in the US: a simulation of the anticipated health and economic impacts.

PubMed

Ahmad, Sajjad; Franz, Gregor A

2008-01-01

To estimate health and economic outcomes of raising the excise taxes on cigarettes. We use a dynamic computer simulation model to estimate health and economic impacts of raising taxes on cigarettes (up to 100% price increase) for the entire population of the USA over 20 years. We also perform sensitivity analysis on price elasticity. A 40% tax-induced cigarette price increase would reduce smoking prevalence from 21% in 2004 to 15.2% in 2025 with large gains in cumulative life years (7 million) and quality adjusted life years (13 million) over 20 years. Total tax revenue will increase by $365 billion in that span, and total smoking-related medical costs would drop by $317 billion, resulting in total savings of $682 billion. These benefits increase greatly with larger tax increases, and tax revenues continue to rise even as smoking prevalence falls. Increasing taxes on cigarettes is a unique policy intervention that reduces smoking prevalence, generates additional tax revenue, and results in significant savings in medical care costs.
Raising Taxes to Reduce Smoking Prevalence in the US: A Simulation of the Anticipated Health and Economic Impacts

PubMed Central

Ahmad, Sajjad; Franz, Gregor A.

2008-01-01

Objective To estimate health and economic outcomes of raising the excise taxes on cigarettes. Methods We use a dynamic computer simulation model to estimate health and economic impacts of raising taxes on cigarettes (up to 100% price increase) for the entire population of USA over 20 years. We also perform sensitivity analysis on price elasticity. Results A 40% tax-induced cigarette price increase would reduce smoking prevalence from 21% in 2004 to 15.2% in 2025 with large gains in cumulative life years (7 million) and quality adjusted life years (13 million) over 20 years. Total tax revenue will increase by $365 billion in that span, and total smoking-related medical costs would drop by $317 billion, resulting in total savings of $682 billion. These benefits increase greatly with larger tax increases, and tax revenues continue to rise even as smoking prevalence falls. Conclusions Increasing taxes on cigarettes is a unique policy intervention that reduces smoking prevalence, generates additional tax revenue, and results in significant savings in medical care costs. PMID:17610918
Mapping the spatial distribution of Aedes aegypti and Aedes albopictus.

PubMed

Ding, Fangyu; Fu, Jingying; Jiang, Dong; Hao, Mengmeng; Lin, Gang

2018-02-01

Mosquito-borne infectious diseases, such as Rift Valley fever, Dengue, Chikungunya and Zika, have caused mass human death with the transnational expansion fueled by economic globalization. Simulating the distribution of the disease vectors is of great importance in formulating public health planning and disease control strategies. In the present study, we simulated the global distribution of Aedes aegypti and Aedes albopictus at a 5×5km spatial resolution with high-dimensional multidisciplinary datasets and machine learning methods Three relatively popular and robust machine learning models, including support vector machine (SVM), gradient boosting machine (GBM) and random forest (RF), were used. During the fine-tuning process based on training datasets of A. aegypti and A. albopictus, RF models achieved the highest performance with an area under the curve (AUC) of 0.973 and 0.974, respectively, followed by GBM (AUC of 0.971 and 0.972, respectively) and SVM (AUC of 0.963 and 0.964, respectively) models. The simulation difference between RF and GBM models was not statistically significant (p>0.05) based on the validation datasets, whereas statistically significant differences (p<0.05) were observed for RF and GBM simulations compared with SVM simulations. From the simulated maps derived from RF models, we observed that the distribution of A. albopictus was wider than that of A. aegypti along a latitudinal gradient. The discriminatory power of each factor in simulating the global distribution of the two species was also analyzed. Our results provided fundamental information for further study on disease transmission simulation and risk assessment. Copyright © 2017 Elsevier B.V. All rights reserved.
Power System Simulation for Policymaking and Making Policymakers

NASA Astrophysics Data System (ADS)

Cohen, Michael Ari

Power system simulation is a vital tool for anticipating, planning for and ultimately addressing future conditions on the power grid, especially in light of contemporary shifts in power generation, transmission and use that are being driven by a desire to utilize more environmentally responsible energy sources. This dissertation leverages power system simulation and engineering-economic analysis to provide initial answers to one open question about future power systems: how will high penetrations of distributed (rooftop) solar power affect the physical and economic operation of distribution feeders? We find that the overall impacts of distributed solar power (both positive and negative) on the feeders we modeled are minor compared to the overall cost of energy, but that there is on average a small net benefit provided by distributed generation. We then describe an effort to make similar analyses more accessible to a non-engineering (high school) audience by developing an educational video game called "Griddle" that is based on the same power system simulation techniques used in the first study. We describe the design and evaluation of Griddle and find that it demonstrates potential to provide students with insights about key power system learning objectives.

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