Environmental sustainability assessment using dynamic Autoregressive-Distributed Lag simulations—Nexus between greenhouse gas emissions, biomass energy, food and economic growth

Samuel Asumadu Sarkodie, Vladimir Strezov, Haftom Weldekidan, Ernest Frimpong Asamoah, Phebe Asantewaa Owusu, Israel Nutifafa Yawo Doyi

    Research output: Contribution to journalArticlepeer-review

    217 Citations (Scopus)

    Abstract

    Increasing population demand has triggered the enhancement of food production, energy consumption and economic development, however, its impact on climate change has become a global concern. This study applied a novel environmental sustainability assessment tool using dynamic Autoregressive-Distributed Lag (ARDL) simulations for model estimation of the relationships between greenhouse gas (GHG) emissions, energy, biomass, food and economic growth for Australia using data spanning from 1970 to 2017. The study found an inversed-U shaped relationship between energy consumption and income level, showing a decarbonized and services economy, hence, improved energy efficiency. While energy consumption increases emissions by 0.4 to 2.8%, biomass consumption supports Australia's transition to a decarbonized economy by reducing GHG emissions by 0.13% and shifts the demand for fossil fuel. Food and energy consumption underpin socio-economic development and vice versa. However, food waste from production and consumption increases ecological footprint, implying a lost opportunity to improve food security and reduce environmental pressure from agricultural production. There is no single path to achieving environmental sustainability, nonetheless, the integrated approach applied in this study reveals conceptual tools which are applicable for decision making.
    Original languageEnglish
    Pages (from-to)318-332
    Number of pages15
    JournalScience of the Total Environment
    Volume668
    DOIs
    Publication statusPublished - 10 Jun 2019

    Keywords

    • Australia
    • Autoregressive-Distributed Lag
    • Climate change
    • Cointegration
    • Dynamic modelling
    • Dynardl

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