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  1. Lin Z, Ooi JK, Woon KS
    Sci Total Environ, 2022 Apr 10;816:151541.
    PMID: 34774629 DOI: 10.1016/j.scitotenv.2021.151541
    Food waste is a universal problem in many countries. In line with Sustainable Development Goals 7 and 12, it is crucial to identify a cost-effective food waste valorization management framework with the least human health and environmental impacts. However, studies on the synergistic effect of life cycle assessment and mathematical optimization interconnected with human health, environment, and economic are relatively few and far between; hence they cannot provide holistic recommendations to policymakers in developing environmental and economic feasibility of food waste management frameworks. Taking Malaysia as a case study, this study proposes a simple and deterministic model that integrates life cycle assessment and multi-objective mathematical optimization to unpack the health-environment-economic wellbeing nexus in food waste management sector. The model evaluates the life cycle human health, environmental, and economic impacts of five food waste disposal and valorization technologies: open landfill, sanitary landfill, aerated windrow composting, high-temperature drying sterilization, and anaerobic digestion, and identifies the optimal food waste valorization configuration solution in Malaysia. Based on the results modeled by SimaPro 9.0 and General Algebraic Modeling System with augmented ε-constraint, valorization of food waste into electricity via anaerobic digestion is the most favorable option, with 146% and 161% reduction of human health and ecosystems, respectively, as compared with open landfill. If cost is combined as an objective function with human health and ecosystems, high-temperature drying sterilization is the most attractive scenario due to the high livestock feed revenue. Among the 10 Pareto-optimal solutions, 9% sanitary landfill, 3% aerated windrow composting, 30% high-temperature drying sterilization, 30% anaerobic digestion to electricity, and 28% anaerobic digestion to cooking gas, is recommended as future food waste management configuration. The sensitivity results demonstrate that prices of electricity, cooking gas, and livestock feed affect the optimal configuration food waste management system.
  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. Nizam NUM, Hanafiah MM, Woon KS
    Nanomaterials (Basel), 2021 Dec 07;11(12).
    PMID: 34947673 DOI: 10.3390/nano11123324
    This paper provides a comprehensive review of 71 previous studies on the life cycle assessment (LCA) of nanomaterials (NMs) from 2001 to 2020 (19 years). Although various studies have been carried out to assess the efficiency and potential of wastes for nanotechnology, little attention has been paid to conducting a comprehensive analysis related to the environmental performance and hotspot of NMs, based on LCA methodology. Therefore, this paper highlights and discusses LCA methodology's basis (goal and scope definition, system boundary, life cycle inventory, life cycle impact assessment, and interpretation) to insights into current practices, limitations, progress, and challenges of LCA application NMs. We found that there is still a lack of comprehensive LCA study on the environmental impacts of NMs until end-of-life stages, thereby potentially supporting misleading conclusions, in most of the previous studies reviewed. For a comprehensive evaluation of LCA of NMs, we recommend that future studies should: (1) report more detailed and transparent LCI data within NMs LCA studies; (2) consider the environmental impacts and potential risks of NMs within their whole life cycle; (3) adopt a transparent and prudent characterization model; and (4) include toxicity, uncertainty, and sensitivity assessments to analyze the exposure pathways of NMs further. Future recommendations towards improvement and harmonization of methodological for future research directions were discussed and provided. This study's findings redound to future research in the field of LCA NMs specifically, considering that the release of NMs into the environment is yet to be explored due to limited understanding of the mechanisms and pathways involved.
  4. Sofian Azizi DD, Hanafiah MM, Woon KS, Ismail H
    Heliyon, 2023 Jun;9(6):e17244.
    PMID: 37441409 DOI: 10.1016/j.heliyon.2023.e17244
    The disposal practises and preferences of household waste from electrical and electronic equipment disposal (WEEE) are essential components in material flow analysis (MFA). Nevertheless, the synergistic of consumers' behaviours and preferences with the disposal of different WEEE has yet to be investigated in depth. This study examined several consumer features of WEEE management using a quantitative questionnaire survey, including consumers' disposal behaviours and preferences. As a Malaysian federal government administrative centre, and model of a contemporary and sustainable Malaysian city, Putrajaya was chosen as the study area. Using stratified random sampling, the questionnaire was distributed through face-to-face and online surveys among households across 20 precincts within Putrajaya. From June 2021 to January 2022, 500 surveys were distributed over seven months, and IBM SPSS Statistic version 26 was used to analyse the data. The result shows that 80% of respondents have a good knowledge of WEEE management and are fully aware of the dangerous materials they have in their WEEE. 75% said they would recycle their WEEE, but only 44% said they would separate it from other household wastes. It was also shown that 88% of the household were willing to pay a collection fee of at least RM 10 for each collection. This analysis found that Extended Producer Responsibility (EPR) mechanisms can assist in overcoming weaknesses in WEEE management by including beneficial schemes to incentivise consumers to improve current waste policies. In the meantime, governments, media, and local non-governmental organisations may help by increasing awareness of effective and sustainable WEEE management.
  5. Chew ZL, Tan EH, Palaniandy SA, Woon KS, Phuang ZX
    Sci Total Environ, 2023 Jan 15;856(Pt 1):159007.
    PMID: 36167122 DOI: 10.1016/j.scitotenv.2022.159007
    Improper discard of oil palm trunk and empty fruit bunch renders massive greenhouse gases. Turning these palm wastes into solid biofuels could aid in carbon reduction. The embodied environmental impacts of the solid biofuel densification process are neglected in carbon emission quantification studies applying Greenhouse Gas Protocol while the significance of classifying the system's direct and indirect carbon emissions were overlooked in those utilising life cycle assessment. Despite the prospect of both methodologies to complement their limitations for carbon emissions quantification, no study integrates both methodologies to investigate direct and indirect emissions systematically from a life cycle perspective. An integrated framework of life cycle assessment and Greenhouse Gas Protocol is developed to quantify the direct and indirect carbon emissions of oil palm trunk and empty fruit bunch densification from cradle-to-gate for three pellet plants in Indonesia and Malaysia. The emissions are categorised into three emission scopes: Scope 1, Scope 2, and Scope 3 according to the Greenhouse Gas Protocol, integrated with avoided emissions which are quantified via life cycle assessment. The pellet plants generate 534.7-732.3 kg CO2-eq/tonnepellet per hour, in which Scope 1 (i.e., direct emissions) is the major emission scope due to high emissions from wastewater production and drying fuel combustion. Washing equipment (169.2-439.0 kg CO2-eq/tonnepellet per hour) and burners (87.1-214.5 kg CO2-eq/tonnepellet per hour) are the hotspots found in the pellet plants. Producing empty fruit bunch pellets could reduce 62.0-74.1 % of emissions than landfilling the empty fruit bunch. Empty fruit bunch pellet and oil palm trunk pellet are recommended to co-fire with coal to phase down coal usage in achieving COP26 pledge. This study provides data-driven insights for quantifying carbon emissions through the integrated framework and could be a reference in future life cycle carbon footprint studies of the biomass densification process.
  6. Hoy ZX, Woon KS, Chin WC, Van Fan Y, Yoo SJ
    Science, 2023 Nov 17;382(6672):797-800.
    PMID: 37972189 DOI: 10.1126/science.adg3177
    No global analysis has considered the warming that could be averted through improved solid waste management and how much that could contribute to meeting the Paris Agreement's 1.5° and 2°C pathway goals or the terms of the Global Methane Pledge. With our estimated global solid waste generation of 2.56 to 3.33 billion tonnes by 2050, implementing abrupt technical and behavioral changes could result in a net-zero warming solid waste system relative to 2020, leading to 11 to 27 billion tonnes of carbon dioxide warming-equivalent emissions under the temperature limits. These changes, however, require accelerated adoption within 9 to 17 years (by 2033 to 2041) to align with the Global Methane Pledge. Rapidly reducing methane, carbon dioxide, and nitrous oxide emissions is necessary to maximize the short-term climate benefits and stop the ongoing temperature rise.
  7. Wan MJ, Phuang ZX, Hoy ZX, Dahlan NY, Azmi AM, Woon KS
    Sci Total Environ, 2024 Feb 20;912:168779.
    PMID: 38016556 DOI: 10.1016/j.scitotenv.2023.168779
    Although large-scale solar (LSS) is a promising renewable energy technology, it causes adverse impacts on the ecosystem, human health, and resource depletion throughout its upstream (i.e., raw material extraction to solar panel production) and downstream (i.e., plant demolition and waste management) processes. The LSS operational performance also fluctuates due to meteorological conditions, leading to uncertainty in electricity generation and raising concerns about its overall environmental performance. Hitherto, there has been no evidence-backed study that evaluates the ecological sustainability of LSS with the consideration of meteorological uncertainties. In this study, a novel integrated Life Cycle Assessment (LCA) and Artificial Neural Network (ANN) framework is developed to forecast the meteorological impacts on LSS's electricity generation and its life cycle environmental sustainability. For LCA, 18 impact categories and three damage categories are characterised and assessed by ReCiPe 2016 via SimaPro v. 9.1. For ANN, a feedforward neural network is applied via Neural Designer 5.9.3. Taking an LSS plant in Malaysia as a case study, the photovoltaic panel production stage contributes the highest environmental impact in LSS (30 % of human health, 30 % of ecosystem quality, and 34 % of resource scarcity). Aluminium recycling reduces by 10 % for human health, 10 % for ecosystem quality, and 9 % for resource scarcity. The emissions avoided by the forecasted LSS-generated electricity offset the environmental burden for human health, ecosystem quality, and resource scarcity 12-68 times, 13-73 times, and 18-98 times, respectively. The developed ANN-LCA framework can provide LSS stakeholders with data-backed insights to effectively design an environmentally conscious LSS facility, considering meteorological influences.
  8. Luo Z, Li Y, Pei X, Woon KS, Liu M, Lin X, et al.
    Environ Res, 2024 May 04;252(Pt 4):119076.
    PMID: 38710430 DOI: 10.1016/j.envres.2024.119076
    The large yield of anaerobic digestates and the suboptimal efficacy of nutrient slow-release severely limit its practical application. To address these issues, a new biochar based fertilizer (MAP@BRC) was developed using biogas residue biochar (BRC) to recover nitrogen and phosphorus from biogas slurry. The nutrient release patterns of MAP@BRC and mechanisms for enhancing soil fertility were studied, and it demonstrated excellent performance, with 59% total nitrogen and 50% total phosphorus nutrient release rates within 28 days. This was attributed to the coupling of the mechanism involving the dissolution of struvite skeletons and the release of biochar pores. Pot experiments showed that crop yield and water productivity were doubled in the MAP@BRC group compared with unfertilized planting. The application of MAP@BRC also improved soil nutrient levels, reduced soil acidification, increased microbial populations, and decreased soil heavy metal pollution risk. The key factors that contributed to the improvement in soil fertility by MAP@BRC were an increase in available nitrogen and the optimization of pH levels in the soil. Overall, MAP@BRC is a safe, slow-release fertilizer that exhibits biochar-fertilizer interactions and synergistic effects. This slow-release fertilizer was prepared by treating a phosphorus-rich biogas slurry with a nitrogen-rich biogas slurry, and it simultaneously addresses problems associated with livestock waste treatment and provides a promising strategy to promote zero-waste agriculture.
  9. Hoy ZX, Phuang ZX, Farooque AA, Fan YV, Woon KS
    Environ Pollut, 2024 Mar 01;344:123386.
    PMID: 38242306 DOI: 10.1016/j.envpol.2024.123386
    Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine learning models are applied for MSW-related trend prediction to provide insights on future waste generation or carbon emissions trends and assist the formulation of effective low-carbon policies. Yet, the existing machine learning models are diverse and scattered. This inconsistency poses challenges for researchers in the MSW domain who seek to identify and optimize the machine learning techniques and configurations for their applications. This systematic review focuses on MSW-related trend prediction using the most frequently applied machine learning model, artificial neural network (ANN), while addressing potential methodological improvements for reducing prediction uncertainty. Thirty-two papers published from 2013 to 2023 are included in this review, all applying ANN for MSW-related trend prediction. Observing a decrease in the size of data samples used in studies from daily to annual timescales, the summarized statistics suggest that well-performing ANN models can still be developed with approximately 33 annual data samples. This indicates promising opportunities for modeling macroscale greenhouse gas emissions in future works. Existing literature commonly used the grid search (manual) technique for hyperparameter (e.g., learning rate, number of neurons) optimization and should explore more time-efficient automated optimization techniques. Since there are no one-size-fits-all performance indicators, it is crucial to report the model's predictive performance based on more than one performance indicator and examine its uncertainty. The predictive performance of newly-developed integrated models should also be benchmarked to show performance improvement clearly and promote similar applications in future works. The review analyzed the shortcomings, best practices, and prospects of ANNs for MSW-related trend predictions, supporting the realization of practical applications of ANNs to enhance waste management practices and reduce carbon emissions.
  10. Mong GR, Liew CS, Idris R, Woon KS, Chong WWF, Chiong MC, et al.
    J Environ Manage, 2024 Sep;368:122172.
    PMID: 39137640 DOI: 10.1016/j.jenvman.2024.122172
    Driven by the need for solutions to address the global issue of waste accumulation from human activities and industries, this study investigates the thermal behaviors of empty fruit bunch (EFB), tyre waste (TW), and their blends during co-pyrolysis, exploring a potential method to convert waste into useable products. The kinetics mechanism and thermodynamics properties of EFB and TW co-pyrolysis were analysed through thermogravimetric analysis (TGA). The rate of mass loss for the blend of EFB:TW at a 1:3 mass ratio shows an increase of around 20% due to synergism. However, the blend's average activation energy is higher (298.64 kJ/mol) when compared with single feedstock pyrolysis (EFB = 257.29 kJ/mol and TW = 252.92 kJ/mol). The combination of EFB:TW at a 3:1 ratio does not result in synergistic effects on mass loss. However, a lower activation energy is reported, indicating the decomposition process can be initiated at a lower energy requirement. The reaction model that best describes the pyrolysis of EFB, TW and their blends can be categorised into the diffusion and power model categories. An equal mixture of EFB and TW was the preferred combination for co-management because of the synergistic effect, which significantly impacts the co-pyrolysis process. The mass loss rate experiences an inhibitive effect at an earlier stage (320 °C), followed by a promotional impact at the later stage (380 °C). The activation energy needed for a balanced mixture is the least compared to all tested feedstocks, even lower than the pyrolysis of a single feedstock. The study revealed the potential for increasing decomposition rates using lower energy input through the co-pyrolysis of both feedstocks. These findings evidenced that co-pyrolysis is a promising waste management and valorisation pathway to deal with overwhelming waste accumulation. Future works can be conducted at a larger scale to affirm the feasibility of EFB and TW co-management.
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