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Ecological Network Analysis of State-Level Energy Consumption in Maryland, USA

Author

Listed:
  • Graham Hyde

    (Department of Physics, Astronomy & Geosciences, Towson University, Towson, MD 21252, USA)

  • Brian D. Fath

    (Department of Biological Sciences, Towson University, Towson, MD 21252, USA
    Advancing Systems Analysis Program, International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria
    Department of Environmental Studies, Masaryk University, 602 00 Brno, Czech Republic)

Abstract

Renewable and clean energy sources are being integrated into the United States’ modern energy industry to mitigate climate change effects, creating a more complex network of energy production, distribution, and consumption. This study defines the state of Maryland’s energy industry as a network of producers and consumers and analyzes the network’s characteristics by using ecological network analysis (ENA), an analytical tool useful for identifying a system’s indirect effects. The energy industry within Maryland is analyzed over a nine-year time span to understand how its evolution is influencing the network’s characteristics. Maryland’s renewable portfolio standard (RPS) for the year 2030 is then simulated by adjusting renewable and non-renewable energy sources according to energy trends and related state policy. Results from the ENA over the nine-year period of 2010–2019 indicate that the energy industry is highly linear. While typical cycling indices range from 5–15% in ecological energy flow models, cycling indices in this study ranged from 0.007% to 0.0082%. Maryland’s energy industry in the year 2030 is simulated and displays increased cycling because renewable sources typically feed the electricity sector for energy distribution, increasing indirect pathways within the system. The percentage of electricity generated by renewable energy increased from 9.71% in 2019 to 50% in 2030, as mandated in the RPS. Network analyses here emphasize the large gap between Maryland’s current energy infrastructure and what is necessary to meet its renewable targets in 2030. Furthermore, they indicate that a more uniform distribution of energy to consumers may increase efficiency in modern energy industries.

Suggested Citation

  • Graham Hyde & Brian D. Fath, 2022. "Ecological Network Analysis of State-Level Energy Consumption in Maryland, USA," Energies, MDPI, vol. 15(16), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5995-:d:891943
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    References listed on IDEAS

    as
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    5. Korhonen, Jouni & Snakin, Juha-Pekka, 2005. "Analysing the evolution of industrial ecosystems: concepts and application," Ecological Economics, Elsevier, vol. 52(2), pages 169-186, January.
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