John C. Little
· Assistant ProfessorVerifiedVirginia Tech · Civil and Environmental Engineering
Active 1950–2026
About
Professor John C. Little's research interests focus on process dynamics in environmental systems and societal challenges involving systems of Anthropocene systems. His work addresses the complex interactions and dynamics within environmental processes and how these relate to broader societal issues in the context of the Anthropocene, the current geological epoch characterized by significant human impact on Earth's geology and ecosystems. Through his research, Professor Little contributes to understanding and modeling the intricate systems that define environmental and societal interactions during this era.
Research topics
- Computer Science
- Engineering
- Artificial Intelligence
- Environmental science
- Management science
- Ecology
- Political Science
- Biology
- Oceanography
- Geography
- Risk analysis (engineering)
- Business
- Geotechnical engineering
- Knowledge management
- Systems engineering
- Biochemical engineering
- Geology
- Data science
- Process management
- Atmospheric sciences
- Physics
Selected publications
Integrated Modeling for Chemistry of Indoor Environments: Progress and Future Perspectives
ACS ES&T Air · 2026-02-24
articleSenior authorCorrespondingThe Modeling Consortium for Chemistry of Indoor Environments (MOCCIE) develops and integrates various indoor models across a wide range of spatial and temporal scales, including molecular dynamics simulations, kinetic process models, gas-phase and aerosol chemistry models, and computational fluid dynamic simulations. We take a holistic approach to apply our models to numerous laboratory experiments and indoor field campaigns to constrain model parameters, gain molecular- and process-level understanding, and extrapolate to different building operating conditions. We summarize our major findings of model applications to cross-cutting themes, including partitioning and reactions on indoor surfaces, human skin ozonolysis to form the human oxidation field, oxidation of volatile organic compounds to generate semivolatile organic compounds and secondary organic aerosols, and spatial distributions of indoor compounds around human occupants and in rooms. Finally, we discuss future perspectives of indoor chemistry modeling, including indoor emissions as a source of outdoor air pollutants and the impacts of climate change on indoor chemistry.
Socio-Environmental Systems Modeling · 2026-04-29
articleOpen accessSocial-ecological systems (SESs) are complex adaptive systems that encompass multiple spatial, temporal, and organisational scales and levels. The dynamics of SESs are driven by interactions among processes occurring both within and across different levels. These multi-level interactions generate patterns of system behaviour that emerge at different spatial, temporal, and organisational levels. This has profound implications for managing SESs. Agent-based models (ABMs) are known for their ability to simulate emergent phenomena and are powerful tools for modelling SESs. However, most multi-level ABMs focus merely on individual/micro-level interactions and aggregated/macro-level interactions and rarely capture the true multi-level dynamics of SESs, which often include effects that cascade across multiple levels. We describe a conceptual framework for multi-level ABMs that couple processes occurring at intermediate levels with those occurring at micro and macro levels, and, more importantly, propose a mathematical construct that embodies the generic features of a truly multi-level ABM. We then discuss our proposed model within the context of past and potential future multi-level agent-based modelling efforts.
A Hetero-functional Graph State Estimator for Watershed Systems: Application to the Chesapeake Bay
arXiv (Cornell University) · 2026-03-02
preprintOpen accessRegional watersheds are complex systems of systems encompassing hydrology, land-use decision-making, estuarine ecological feedbacks, and overlapping governance jurisdictions. Their effective management underlies many modern societal challenges and therefore requires models that capture interdependencies between natural and institutional systems. Regional-specific models such as the Chesapeake Assessment Scenario Tool, used in this paper's case study, provide valuable nutrient estimates but rely on structurally opaque watershed routing that limits integration into broader systems-level analyses. This paper introduces a modeling framework for watershed systems. First, a region-independent reference architecture is developed. Second, the Weighted Least Squares Error Hetero-functional Graph State Estimator, an extension of Hetero-functional Graph Theory (HFGT), is adapted to estimate nutrient flows from uncertain data. The framework is demonstrated through instantiation in the Chesapeake Bay Watershed. By establishing a shared ontology grounded in Systems Modeling Language and HFGT, the approach enables integration of economic and governance systems to support sustainable watershed management.
arXiv (Cornell University) · 2026-02-16
preprintOpen accessCharacterizing the interdependent nature of Anthropocene systems of systems is fundamental to making informed decisions to address challenges across complex ecological, environmental, and coupled human-natural systems. This paper presents the first application of Model-Based Systems Engineering (MBSE) and Hetero-functional Graph Theory (HFGT) to economic systems, establishing a scalable and extensible methodology for integrating economic input-output (EIO) models within a unified system-of-systems modeling framework. Integrating EIO models into the MBSE-HFGT workflow demonstrates how the structural form and function of economic systems can be expressed through SysML's graphical ontology and subsequently translated into the computational structure of HFGT. Using a synthetic Rectangular Choice of Technology (RCOT) example as a pedagogical foundation, the study confirms that the dynamics captured by basic EIO models, as well as other complex economic models grounded in EIO theory, can be equivalently reproduced within the MBSE-HFGT framework. The integration with MBSE and HFGT thus preserves analytical precision while offering enhanced graphical clarity and system-level insight through a shared ontological structure. By integrating modeling languages and mathematical frameworks, the proposed methodology establishes a foundation for knowledge co-production and integrated decision-making to address the multifaceted sustainability challenges associated with Anthropocene systems of systems.
A System-of-Systems Convergence Paradigm for Societal Challenges of the Anthropocene
Open MIND · 2026-03-02
preprintModern societal challenges, such as climate change, urbanization, and water resource management, demand integrated, multi-discipline, multi-problem approaches to frame and address their complexity. Unfortunately, current methodologies often operate within disciplinary silos, leading to fragmented insights and missed opportunities for convergence. A critical barrier to cross-disciplinary integration lies in the disparate ontologies that shape how different fields conceptualize and communicate knowledge. To address these limitations, this paper proposes a system-of-systems (SoS) convergence paradigm grounded in a meta-cognition map, a framework that integrates five complementary domains: real-world observations, systems thinking, visual modeling, mathematics, and computing. The paradigm is based on the Systems Modeling Language (SysML), offering a standardized, domain-neutral approach for representing and analyzing complex systems. The proposed methodology is demonstrated through a case study of the Chesapeake Bay Watershed, a socio-environmental system requiring coordination across land use, hydrology, economic and policy domains. By modeling this system with SysML, the study illustrates practical strategies for navigating interdisciplinary challenges and highlights the potential of agile SoS modeling to support large-scale, multi-dimensional decision-making.
A Conceptual Introduction to Hetero‐Functional Graph Theory for Systems‐of‐Systems
Systems Engineering · 2026-04-22
articleOpen accessSenior authorABSTRACT A defining feature of 21st century engineering challenges is their inherent complexity, demanding the convergence of knowledge across diverse disciplines. Establishing consistent methodological foundations for engineering systems remains a challenge—one that both systems engineering and network science have sought to address. Model‐based systems engineering (MBSE) has recently emerged as a practical, interdisciplinary approach for developing complex systems from concept through implementation. In contrast, network science focuses on the quantitative analysis of networks present within engineering systems. This article introduces hetero‐functional graph theory (HFGT) as a conceptual bridge between these two fields, serving as an entry point for both communities. For systems engineers, HFGT preserves the heterogeneity of conceptual and ontological constructs in MBSE, including system form, function, and concept. For network scientists, it provides multiple graph‐based data structures enabling matrix‐based quantitative analysis. The modeling process begins with ontological foundations, where an engineering system is defined as an abstraction and represented with a model. Model fidelity is assessed using four linguistic properties: soundness, completeness, lucidity, and laconicity. A meta‐architecture is introduced to manage the convergence challenges between domain‐specific reference architectures and case‐specific instantiations. Unlike other meta‐architectures, HFGT is rooted in linguistic structures, modeling resources as subjects, system processes as predicates, and operands—such as matter, energy, organisms, information, and money—as objects. These elements are integrated within a system meta‐architecture expressed in the Systems Modeling Language (SysML). The article concludes by offering guidance for further reading. Significance and Practitioner Points This article introduces hetero‐functional graph theory (HFGT) as a methodological bridge between the graphical modeling of Model‐Based Systems Engineering (MBSE) and mathematical models founded in network science, dynamic systems, and operations research. For researchers, HFGT provides a rigorous methodological foundation that addresses the complex and heterogeneous interdependencies in systems of systems, overcomes the ontological limitations of multilayer networks, and reconciles the methods for structural analysis, dynamic simulation, and optimization. It addresses a critical gap in the systems science literature by enabling the mathematical synthesis of structural and functional viewpoints of complex engineering systems. For practitioners, HFGT offers a scalable and automatable methodology to translate complex architectural diagrams into computable mathematical models. This allows for proactive and self‐consistent design and analysis of the structural and dynamic properties of a system‐of‐systems from the earliest phases of the system life cycle to its final implementation. Ultimately, the paper provides a conceptual introduction to HFGT, demonstrating a foundational language for engineering systems that ensures architectural descriptions are not just visual aids, but mathematically actionable blueprints.
A System-of-Systems Convergence Paradigm for Societal Challenges of the Anthropocene
ArXiv.org · 2026-03-02
articleOpen accessModern societal challenges, such as climate change, urbanization, and water resource management, demand integrated, multi-discipline, multi-problem approaches to frame and address their complexity. Unfortunately, current methodologies often operate within disciplinary silos, leading to fragmented insights and missed opportunities for convergence. A critical barrier to cross-disciplinary integration lies in the disparate ontologies that shape how different fields conceptualize and communicate knowledge. To address these limitations, this paper proposes a system-of-systems (SoS) convergence paradigm grounded in a meta-cognition map, a framework that integrates five complementary domains: real-world observations, systems thinking, visual modeling, mathematics, and computing. The paradigm is based on the Systems Modeling Language (SysML), offering a standardized, domain-neutral approach for representing and analyzing complex systems. The proposed methodology is demonstrated through a case study of the Chesapeake Bay Watershed, a socio-environmental system requiring coordination across land use, hydrology, economic and policy domains. By modeling this system with SysML, the study illustrates practical strategies for navigating interdisciplinary challenges and highlights the potential of agile SoS modeling to support large-scale, multi-dimensional decision-making.
arXiv (Cornell University) · 2026-02-16
articleOpen accessCharacterizing the interdependent nature of Anthropocene systems of systems is fundamental to making informed decisions to address challenges across complex ecological, environmental, and coupled human-natural systems. This paper presents the first application of Model-Based Systems Engineering (MBSE) and Hetero-functional Graph Theory (HFGT) to economic systems, establishing a scalable and extensible methodology for integrating economic input-output (EIO) models within a unified system-of-systems modeling framework. Integrating EIO models into the MBSE-HFGT workflow demonstrates how the structural form and function of economic systems can be expressed through SysML's graphical ontology and subsequently translated into the computational structure of HFGT. Using a synthetic Rectangular Choice of Technology (RCOT) example as a pedagogical foundation, the study confirms that the dynamics captured by basic EIO models, as well as other complex economic models grounded in EIO theory, can be equivalently reproduced within the MBSE-HFGT framework. The integration with MBSE and HFGT thus preserves analytical precision while offering enhanced graphical clarity and system-level insight through a shared ontological structure. By integrating modeling languages and mathematical frameworks, the proposed methodology establishes a foundation for knowledge co-production and integrated decision-making to address the multifaceted sustainability challenges associated with Anthropocene systems of systems.
A Hetero-functional Graph State Estimator for Watershed Systems: Application to the Chesapeake Bay
ArXiv.org · 2026-03-02
articleOpen accessRegional watersheds are complex systems of systems encompassing hydrology, land-use decision-making, estuarine ecological feedbacks, and overlapping governance jurisdictions. Their effective management underlies many modern societal challenges and therefore requires models that capture interdependencies between natural and institutional systems. Regional-specific models such as the Chesapeake Assessment Scenario Tool, used in this paper's case study, provide valuable nutrient estimates but rely on structurally opaque watershed routing that limits integration into broader systems-level analyses. This paper introduces a modeling framework for watershed systems. First, a region-independent reference architecture is developed. Second, the Weighted Least Squares Error Hetero-functional Graph State Estimator, an extension of Hetero-functional Graph Theory (HFGT), is adapted to estimate nutrient flows from uncertain data. The framework is demonstrated through instantiation in the Chesapeake Bay Watershed. By establishing a shared ontology grounded in Systems Modeling Language and HFGT, the approach enables integration of economic and governance systems to support sustainable watershed management.
One Earth + One Health: An Agile, Evolutionary, System-of-Systems Convergence Paradigm
Environmental Science & Technology · 2026-03-26
articleOpen access1st authorCorrespondingEvolutionary mechanisms have enabled humans to transform Earth systems. Because the resulting Anthropocene systems are highly interdependent and dynamically evolving, often with accelerating rates of cultural and technological evolution, One Earth and One Health must be framed and addressed in a holistic fashion. An agile, evolutionary, system-of-systems, convergence paradigm, which is based on a partially quantifiable, scientifically falsifiable theoretical framework, can be used to systematically identify, decompose, characterize, and then converge a nested, evolutionary ensemble of geophysical, biophysical, sociocultural, and sociotechnical systems. The paradigm includes individual organisms (spanning plants, fungi, and animals) engaging in niche construction in a global meta-ecosystem that integrates the deep evolutionary history of all Anthropocene systems. To coherently span the vast range of scales, the paradigm is divided into a somatic realm (externally oriented with respect to individual organisms) that can be applied at global, regional, urban, and local scales, as well as a visceral realm (internally oriented with respect to individual organisms) that includes organs, cells, organelles, genes, and molecules. The paradigm requires a causally coherent evolutionary framework, cross-scale, modular, and hierarchical conceptual models (based on a common language and reconciled ontology), with agile, extensible, and scalable computational frameworks, an associated decision-support system, and an educational pedagogy.
Recent grants
Hypolimnetic Oxygenation: Coupling Bubble-Plume and Reservoir Models
NSF · $215k · 2002–2007
Developing Barrier Layers to Minimize Volatile Emissions from Structural Insulated Panels (SIPs)
NSF · $375k · 2006–2010
NSF · $272k · 2011–2015
Emission of Phthalates from Vinyl Flooring and Interaction with Fine Particles
NSF · $396k · 2005–2010
NSF · $80k · 2013–2017
Frequent coauthors
- 26 shared
Clara M. A. Eichler
University of North Carolina at Chapel Hill
- 24 shared
Steven S. Cox
- 23 shared
Ying Xu
- 22 shared
Elaine A. Cohen Hubal
National Center for Environmental Assessment (EPA)
- 20 shared
Benito J. Mariñas
University of Illinois Urbana-Champaign
- 18 shared
Lee D. Bryant
University of Bath
- 14 shared
William W. Nazaroff
- 14 shared
Yaoxing Wu
Virginia Tech
Labs
Process dynamics in environmental systems and societal challenges involving systems of Anthropocene systems.
Education
- 1990
PhD, Civil and Environmental Engineering
University of California Berkeley
- 1988
MS, Civil and Environmental Engineering
University of California Berkeley
- 1985
BS, Chemical Engineering
University of Cape Town
- 1984
MS, Physical Chemistry
University of Cape Town
Awards & honors
- North American Lake Management Society (NALMS) Technical Mer…
- Association of Environmental Engineering and Science Profess…
- Association of Environmental Engineering and Science Profess…
- International Society of Indoor Air Quality and Climate (ISI…
- National Science Foundation CAREER Award (1996)
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