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Kang, Shujiang

Publications and source records attributed to Kang, Shujiang.

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Bioenergy Supply and Environmental Impacts on Cropland: Insights from Multi‐market Forecasts in a Great Lakes Subregional Bioeconomic Model

Abstract Using subregional models of crop production choices in central Wisconsin and southwest Michigan, we predict biomass production, land use, and environmental impacts with details that are unavailable from national scale models. When biomass prices are raised exogenously, we find that the subregional models overestimate the supply, the land use, and the beneficial environmental aspects of perennial biomass crops. Multi‐market price feedbacks tied to realistic policy parameters predict high threshold absolute prices for biomass to enter production, resulting in intensified production of biomass from annual grain crops with damaging environmental impacts. Multi‐market feedbacks also predict regional specialization in energy biomass production in areas with lower yields of food crops. Policies promoting biofuels will not necessarily generate environmental benefits in the absence of environmental regulations.

Egbendewe‐Mondzozo, Aklesso↗
DOE OSTI2014

Development of mpi_EPIC model for global agroecosystem modeling

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmental effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Global Simulation of Bioenergy Crop Productivity: Analytical framework and Case Study for Switchgrass

Contemporary global assessments of the deployment potential and sustainability aspects of biofuel crops lack quantitative details. This paper describes an analytical framework capable of meeting the challenges associated with global scale agro-ecosystem modeling. We designed a modeling platform for bioenergy crops, consisting of five major components: (i) standardized global natural resources and management data sets, (ii) global simulation unit and management scenarios, (iii) model calibration and validation, (iv) high-performance computing (HPC) modeling, and (v) simulation output processing and analysis. A case study with the HPC- Environmental Policy Integrated Climate model (HPC-EPIC) to simulate a perennial bioenergy crop, switchgrass (Panicum virgatum L.) and global biomass feedstock analysis on grassland demonstrates the application of this platform. The results illustrate biomass feedstock variability of switchgrass and provide insights on how the modeling platform can be expanded to better assess sustainable production criteria and other biomass crops. Feedstock potentials on global grasslands and within different countries are also shown. Future efforts involve developing databases of productivity, implementing global simulations for other bioenergy crops (e.g. miscanthus, energycane and agave), and assessing environmental impacts under various management regimes. We anticipated this platform will provide an exemplary tool and assessment data for international communities to conduct global analysis of biofuel biomass feedstocks and sustainability.

Nair, S. Surendran↗
DOE OSTI2013

Hierarchical Marginal Land Assessment for Land Use Planning

Marginal land provides an alternative potential for food and bioenergy production in the face of limited land resources; however, effective assessment of marginal lands is not well addressed. Concerns over environmental risks, ecosystem services and sustainability for marginal land have been widely raised. The objective of this study was to develop a hierarchical marginal land assessment framework for land use planning and management. We first identified major land functions linking production, environment, ecosystem services and economics, and then classified land resources into four categories of marginal land using suitability and limitations associated with major management goals, including physically marginal land, biologically marginal land, environmental-ecological marginal land, and economically marginal land. We tested this assessment framework in south-western Michigan, USA. Our results indicated that this marginal land assessment framework can be potentially feasible on land use planning for food and bioenergy production, and balancing multiple goals of land use management. We also compared our results with marginal land assessment from the Conservation Reserve Program (CRP) and land capability classes (LCC) that are used in the US. The hierarchical assessment framework has advantages of quantitatively reflecting land functions and multiple concerns. This provides a foundation upon which focused studies can be identified in order to improve the assessment framework by quantifying high-resolution land functions associated with environment and ecosystem services as well as their criteria are needed to improve the assessment framework.

Kang, Shujiang↗
DOE OSTI2013

Marginal Lands: Concept, Assessment and Management

Marginal lands have received wide attention for their potential to improve food security and support bioenergy production. However, environmental, ecosystem service, and sustainability concerns have been widely raised over the use of marginal land. Knowledge of the extent, location, and quality of marginal lands as well as their assessment and management are limited and diverse. This paper provides a review of the historical development of marginal concept, its application and assessment. Limitations and priority research needs of marginal land assessment and management were discussed.

Kang, Shujiang↗
DOE OSTI2013

Global Simulation of Bioenergy Crop Productivity: Analytical Framework and Case Study for Switchgrass

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high-performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC-Environmental Policy Integrated Climate (HPC-EPIC) model simulated a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field-trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.

Kang, Shujiang↗
DOE OSTI2012

Bioenergy crop models: Descriptions, data requirements and future challenges

Field studies that address the production of lignocellulosic biomass as a potential source of renewable energy are making available critical information for the development, validation, and use of bioenergy crop models. A literature survey revealed that 14 models have been developed and validated for herbaceous and woody bioenergy crops, and for Crassulacean acid metabolism (CAM) crops adapted to arid lands. These models simulate field-scale production of biomass for switchgrass (ALMANAC, EPIC, and Agro-BGC), miscanthus (MISCANFOR, MISCANMOD, and WIMOVAC), sugarcane (APSIM, AUSCANE, and CANEGRO), and poplar and willow (SECRETS and 3PG). Two models are adaptations of dynamic global vegetation models and simulate biomass yields of miscanthus and sugarcane as plant function types at regional scales (Agro-IBIS and LPJmL). A model of biomass production in CAM plants has been developed (EPI), but lacks the sophistication of the other models. Except for CAM plants, all the models include representations of leaf area dynamics, radiation interception and utilization, biomass production, and partitioning of biomass to roots and shoots. A few of the models are capable of simulating soil water, nutrient, and carbon cycle processes, making them especially useful for assessing environmental consequences (e.g., erosion and nutrient losses) associated with the field-scale deployment of bioenergy crops. Similar to other process-based models, simulations are challenged by computing and data management issues and an integrated framework for model testing and inter-comparison is needed. Considerable work remains concerning the development of models for unconventional bioenergy crops like CAM plants, generation and distribution of high-quality field data for model development and validation, and development of an integrated framework for efficient execution of large-scale simulations for use in planning regional to global sustainable bioenergy production systems.

Surendran Nair, Sujith↗
DOE OSTI2012

Software System Design for Large Scale, Spatially-explicit Agroecosystem Modeling

Recently, site-based agroecosystem model has been applied at regional and state level to enable comprehensive analyses of environmental sustainability of food and biofuel production. Those large-scale, spatially-explicit simulations present computational challenges in software systems design. Herein, we describe our software system design for large-scale, spatially-explicit agroecosystem modeling and data analysis. First, we describe the software design principles in three major phases: data preparation, high performance simulation, and data management and analysis. Then, we use a case study at a regional intensive modeling area (RIMA) to demonstrate our system implementation and capability.

Wang, Dali↗
DOE OSTI2011

HPC-EPIC for High Resolution Simulations of Environmental and Sustainability Assessment

Multiple concerns over the impact of wide scale changes in land management have motivated comprehensive analyses of environmental sustainability of food and biofuel production. These call for high-resolution, spatial-temporal information of lands using tools that enable comprehensive analyses of natural resources for decision-making. Most agroecosystem simulation models are point models with a user interface that allows users to provide inputs and examine results for agricultural field scale analyses, and they aren’t able to meet the needs of the regional and national simulation with high spatial resolutions. We describe an efficient computational approach over deployment of the Environmental Policy Integrated Climate (EPIC) model at high-resolution scales using a high performance computing (HPC) technique in this study. We concentrate on an integrated procedure for executing millions of simulations required, but also address building databases for model initialization and forcing the simulations, and post-processing model outputs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗