Displaying all 3 publications

Abstract:
Sort:
  1. Alsaedi MA, Abnisa F, Alaba PA, Farouk HU
    PMID: 35103053 DOI: 10.1007/s10098-021-02244-3
    The Saudi economy is driven by the energy sector which mainly derived from petroleum-based resources. Besides export, the Kingdom's consumption of this resource showed a significant increase which linearly promoting CO2 emission increment. Therefore, it is essential to model the Kingdom's energy consumption to estimate the profile of her future energy consumption. This work explores modelling and multi-step-ahead predictions for energy use, gross domestic product (GDP), and CO2 emissions in Saudi Arabia using previous data (1980-2018). The dynamic interrelationship of the variable's nexus was tested using the Granger causality and cointegration method in the short-run and long-run. In the long-run, the models reveal an inverted U-shape relation between CO2 emissions and GDP, validating Environmental Kuznets curve. When energy consumption is increased by 1%, there will be an increase in CO2 emissions by 0.592% at constant GDP, and when GDP is increased by 1%, there will be an increase in CO2 emissions by 0.282% at constant energy used. CO2 emissions appear to be both energy consumption and income elastic in Saudi Arabia in the long-run equilibrium. Granger causality based on vector error correction method reveals unidirectional causality from income to CO2 emissions, and bidirectional causality from CO2 emissions to energy consumption and vice versa in the short-run. In the long-run, bidirectional causality from income to CO2 emissions and vice versa and unidirectional causality from the used energy to CO2 emissions were observed. Also, there is a bidirectional causality from GDP to energy used and vice versa in the short-run, meaning that GDP and energy consumption are interdependent. Saudi Arabia needs to increase energy infrastructure investments and increase energy efficiency by implementing energy management policies, reducing environmental pollution, and preventing the negative effect on economic growth.

    Graphical abstract:

  2. Hoy ZX, Leong JF, Woon KS
    PMID: 37359167 DOI: 10.1007/s10098-023-02508-0
    The COVID-19 pandemic caused profound impacts on the global economy, resulting in a sharp drop in carbon emissions as energy demand fell. The emissions reduction due to past extreme events often follows with a rebound after the economy recovers, but the pandemic's impacts on the long-term carbon emissions trend remain unknown. This study forecasts the carbon emissions of Group of Seven (G7) as developed countries and Emerging Seven (E7) as developing countries using socioeconomic indicators and artificial intelligence-powered predictive analytics to assess the pandemic's impacts on the long-term carbon trajectory curve and their progress toward achieving the Paris Agreement goals. Most E7's carbon emissions have strong positive correlations (> 0.8) with the socioeconomic indicators, whereas most G7's correlate negatively (> 0.6) due to their decoupled economic growth from carbon emissions. The forecasts show higher growth rates in the E7's carbon emissions after the rebound in the pandemic scenario compared to the pandemic-free scenario, while the impact on the G7's carbon emissions is negligible. The overall impact of the pandemic outbreak on long-term carbon emissions is small. Still, its short-term positive impact on the environment should not be misunderstood, and stringent emissions reduction policies must be implemented urgently to ensure the achievement of Paris Agreement goals.

    GRAPHICAL ABSTRACT: Research methodology for assessing the pandemic's impacts on the G7 and E7 countries' long-term carbon trajectory curve.

    SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10098-023-02508-0.

  3. Mohammed MZR, Ng ZW, Putranto A, Kong ZY, Sunarso J, Aziz M, et al.
    PMID: 36643617 DOI: 10.1007/s10098-022-02454-3
    This study aims to propose a new process design, simulation, and techno-economic analysis of an integrated process plant that produces glucose and furfural from palm oil empty fruit bunches (EFB). In this work, an Aspen Plus-based simulation has been established to develop a process flow diagram of co-production of glucose and furfural along with the mass and energy balances. The plant's economics are analyzed by calculating the fixed capital income (FCI), operating costs, and working capital. In contrast, profitability is determined using cumulative cash flow (CCF), net present value (NPV), and internal rate of return (IRR). The findings show that the production capacity of 10 kilotons per year (ktpy) of glucose and 4.96 ktpy of furfural with a purity of 98.21 and 99.54%-weight, respectively, was achieved in this study. The FCI is calculated as United States Dollar (USD) 20.80 million, while the working and operating expenses are calculated as USD 3.74 million and USD 16.93 million, respectively. This project achieves USD 7.65 million NPV with a positive IRR of 14.25% and a return on investment (ROI) of 22.06%. The present work successfully develops a profitable integrated process plant that is established with future upscaling parameters and key cost drivers. The findings provided in this work offer a platform and motivation for future research on integrated plants in the food, environment, and energy nexus with the co-location principle.
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links